=========================================================================== COMPARATIVE STUDY OF ELECTORAL SYSTEMS (CSES) - MODULE 5 (2016-2021) CODEBOOK PART 2: VARIABLES DESCRIPTION FULL RELEASE - JULY 25, 2023 CSES Secretariat www.cses.org =========================================================================== HOW TO CITE THE STUDY: The Comparative Study of Electoral Systems (www.cses.org). CSES MODULE 5 FULL RELEASE [dataset and documentation]. July 25, 2023 version. doi:10.7804/cses.module5.2023-07-25. These materials are based on work supported by the American National Science Foundation (www.nsf.gov) under grant numbers SES-1420973 and SES-1760058, the GESIS - Leibniz Institute for the Social Sciences, the University of Michigan, in-kind support of participating election studies, the many organizations that sponsor planning meetings and conferences, and the numerous organizations that fund national election studies by CSES Collaborators. Any opinions, findings and conclusions, or recommendations expressed in these materials are those of the author(s) and do not necessarily reflect the views of the funding organizations. =========================================================================== NOTE TO USERS: We recommend that researchers become familiar with the CSES design, units of analysis, documentation, and dataset weights before beginning their investigations. For instance, while the set of respondents appearing within each election study represents their respective nations, the group of nations that appear within CSES is not a random sample of countries worldwide. Furthermore, while many election studies include 1,000 or so respondents, other election studies may consist of over 10,000 respondents. Some nations will have studies of more than one election in a CSES module, and occasionally there will be two independent studies of a single election. Last, some election studies include oversamples of specific subpopulations or would otherwise benefit from use of the included weight variables. We hope you find our website and documentation useful as you proceed with your work, and welcome any questions or suggestions you have. =========================================================================== TABLE OF CONTENTS =========================================================================== ))) OVERVIEW OF "CODEBOOK PART 2: VARIABLES DESCRIPTION" ))) HOW TO NAVIGATE THE CSES MODULE 5 CODEBOOK ))) CSES CODEBOOK - VARIABLE NOTES AND ELECTION STUDY NOTES ))) DERIVATIVE VARIABLES ))) CSES MODULE 5 CODING OF PARTIES/COALITIONS & LEADERS ))) CSES DATA BRIDGING: NEW FRONTIERS ))) LIST OF TABLES IN CODEBOOK PART 2 ))) CSES MODULE 5 VARIABLE LIST ))) CSES MODULE 5 VARIABLES: IDENTIFICATION, WEIGHT, AND STUDY ADMINISTRATION DATA ))) CSES MODULE 5 VARIABLES: MICRO-LEVEL (SURVEY) DATA DEMOGRAPHIC DATA ))) CSES MODULE 5 VARIABLES: MICRO-LEVEL (SURVEY) DATA THE CSES MODULE 5 QUESTIONNAIRE ))) CSES MODULE 5 VARIABLES: DISTRICT-LEVEL DATA ))) CSES MODULE 5 VARIABLES: MACRO-LEVEL DATA ))) CSES MODULE 5 VARIABLES: DATA BRIDGING WITH CSES PRODUCTS =========================================================================== ))) OVERVIEW OF "CODEBOOK PART 2: VARIABLES DESCRIPTION" =========================================================================== Part 2 of the CSES Codebook provides users with information about the variables in the CSES dataset as well as accompanying information about each polity's election study. =========================================================================== ))) HOW TO NAVIGATE THE CSES MODULE 5 CODEBOOK =========================================================================== In the CSES MODULE 5 dataset, all variables begin with the letter "E" (E being the fourth letter of the English alphabet and thus signifying MODULE 5). The CSES Codebook is especially extensive and users are advised that the best way to navigate it is electronically. It is a .txt format which allows it to be accessed via a variety of programs. In this part of the Codebook (Part 2), the headers for individual variables are surrounded by two lines of dashes. For e.g., --------------------------------------------------------------------------- VARIABLE NAME VARIABLE DESCRIPTION --------------------------------------------------------------------------- The CSES Codebook can be navigated quickly in the electronic files, with the following commands allowing for quick searching: ))) = Section Header. >>> = Sub-section Header 1. <<>> = Sub-section Header 2. +++ = Tables. CSES QUESTION CLASSIFICATION = For survey level variables only, CSES Question Classification details whether the variable is part of the CSES Core component, which are questions asked repeatedly in CSES Modules, whether a variable is part of the CSES Module Theme component, which are questions specific to the Module Theme under exploration and might not be included in CSES repeatedly, or whether a variable is a Derivative Variable, which is explained below. VARIABLE NOTES = Notes for particular variables. ELECTION STUDY NOTES = Notes for a particular election study . DERIVATIVE VARIABLE = Highlights a variable derived from another variable or variables within the CSES. POTENTIAL POLITY LEVEL BRIDGING IDENTIFIER = Highlights a variable that may be used for data bridging at polity level. POTENTIAL REGIONAL LEVEL BRIDGING IDENTIFIER = Highlights a variable that may be used for data bridging at regional level. POTENTIAL TIME BRIDGING IDENTIFIER = Highlights a variable that may be used for data bridging by time. POTENTIAL PARTY/COALITION LEVEL BRIDGING IDENTIFIER = Highlights a variable that may be used for data bridging at party/coalition level. POTENTIAL CSES PRODUCT BRIDGING IDENTIFIER = Highlights a variable that may be used for data bridging with other CSES products. For further details on the CSES MODULE 5 documentation, users are advised to consult Part 1 of the CSES Codebook. =========================================================================== ))) CSES CODEBOOK - VARIABLE NOTES AND ELECTION STUDY NOTES =========================================================================== <<>> VARIABLE NOTES Variable notes provide information on the rationale of a variable as well as source information for that variable. It also details the polities for which no data for that particular variable are available. VARIABLE NOTES are listed below the descriptive information for the said variable and can be navigated in the Codebook by searching for "VARIABLE NOTES" in Part 2 of the CSES Codebook. <<>> ELECTION STUDY NOTES A unique dimension of the CSES are the inclusion of ELECTION STUDY NOTES. They are notes which are attached to each variable included in the dataset and refer to case-specific information regarding a particular variable. Their purpose is to provide users with more detailed information on the case or explain essential deviations specific to cases from CSES conventions. They are also used to provide source data information for users. Where applicable, ELECTION STUDY NOTES are listed below a particular variable and any VARIABLE NOTES in Part 2 and 3 of the CSES Codebook. They can be navigated in the Codebook by searching for "ELECTION STUDY NOTES" in Parts 2-4 of the CSES Codebook. --------------------------------------------------------------------------- ))) DERIVATIVE VARIABLES --------------------------------------------------------------------------- CSES MODULE 5 includes several derivative variables. A derivative variable is a variable that is derived from another variable or variables within the CSES. Their purpose is to facilitate speedier analysis for users with derivative variables capturing some of the most common analytical concepts in the discipline. A list of the DERIVATIVE VARIABLES are below this explanation and can be navigated in the Codebook by searching for DERIVATIVE VARIABLES in Part 2 of the CSES MODULE 5 Codebook. - E2001_A AGE OF RESPONDENT (IN YEARS) - E2001_GG BIRTH GENERATION: GREATEST GENERATION (BORN 1927 OR BEFORE) - E2001_GS BIRTH GENERATION: SILENT GENERATION (BORN FROM 1928 TO 1945) - E2001_GBB BIRTH GENERATION: BABY BOOMERS (BORN FROM 1946 TO 1964) - E2001_GX BIRTH GENERATION: GENERATION X (BORN FROM 1965 TO 1980) - E2001_GY BIRTH GENERATION: GENERATION Y (BORN FROM 1981 TO 1996) - E2001_GZ BIRTH GENERATION: GENERATION Z (BORN FROM 1997 ONWARDS) - E3012_TS TURNOUT SWITCHER BETWEEN CURRENT ELECTION AND PREVIOUS ELECTION - E3012_FTV FIRST-TIME VOTER IN CURRENT MAIN ELECTION - E3013_OUTGOV CURRENT MAIN ELECTION: VOTE CHOICE - OUTGOING GOVERNMENT (INCUMBENT) - E3013_VS_1 VOTE SWITCHER BETWEEN CURRENT ELECTION AND PREVIOUS ELECTION - E3013_LR_CSES CURRENT MAIN ELECTION - VOTE FOR LEFTIST/CENTER/RIGHTIST - CSES - E3013_LR_MARPOR CURRENT MAIN ELECTION - VOTE FOR LEFTIST/RIGHTIST (RILE) - MARPOR/CMP - E3013_IF_CSES CURRENT MAIN ELECTION - VOTE CHOICE BY IDEOLOGICAL FAMILY CLASSIFICATION - CSES - E3100_LR_CSES CURRENT MAIN ELECTION - VOTE CHOICE LINKED WITH CSES COLLABORATOR EXPERT JUDGMENT L-R - E3100_LR_MARPOR CURRENT MAIN ELECTION - VOTE CHOICE LINKED WITH MARPOR/CMP RILE - E3100_POP_CSES CURRENT MAIN ELECTION - VOTE CHOICE LINKED WITH CSES COLLABORATOR EXPERT JUDGMENT ON POPULISM - E3100_IF_CSES CURRENT MAIN ELECTION - VOTE CHOICE LINKED WITH CSES COLLABORATOR EXPERT JUDGMENT IDEOLOGICAL FAMILY =========================================================================== ))) CSES MODULE 5 CODING OF PARTIES/COALITIONS & LEADERS =========================================================================== CSES codes parties/coalitions in its dataset numerically and alphabetically. Below we provide explanations of both of these coding schemes. The details of each party/leader classification are available in Part 3 of the Codebook. <<>> CSES NUMERICAL PARTY/COALITION CODING Each party is assigned a unique numerical code which consists of two components and six digits in total: - the first three digits indicate the numerical country UN code - the latter three digits indicate the numerical party code within the given election study. All parties/coalitions or Presidential candidates, where applicable, participating in the election or the previous election receive a numerical code. These codes are used to identify the following: - who respondents feel best represented by (variable E3010_2). - who a respondent voted for in the current election (variable E3013). - who the respondent voted for in the previous election (variable E3015). - the respondent's party identification (variable E3024). The numeric coding is also used to identify macro level information about the parties/coalitions, namely: - numeric party code identifiers for relational data (E5000) - which party/coalition held the presidency before and after the elections (variable E5009 and E5013). - which party/coalition held the Prime Ministership before and after the elections (variable E5010 and E5014). Numerical codes assigned to parties/coalitions are consistent for the current and previous election. <<>> CSES ALPHABETICAL PARTY/COALITION CODING Parties A through F are the six most popular parties/coalitions, ordered in descending order of their share of the popular vote in the parliamentary election (unless otherwise stated). Thus Party A is the party/coalition that received the most votes in the election, party B the second most votes, etc... Parties/coalitions who achieve at least 1% of the vote nationally are eligible for an alphabetical A-F assignment. In countries with multiple electoral tiers and where one vote is cast, parties are ordered according to their vote share in tier 1 (the lowest tier), unless otherwise stated. In countries where voters have two votes (i.e., a constituency and a list vote) simultaneously, for example Germany, parties are ordered by the national share of the party list vote (tier 2). Parties G, H, and I are supplemental parties. They may, but do not have to, accord with how parties A-F are ordered, that is ordered on the popular share of the vote in a country. More often, they are codified in no particular order. These parties are voluntarily provided by each country's election study and often reflect important or notable parties within a country. They may also include data about individual parties within a coalition, where data about the coalition and the individual parties, or some of these parties that make it up, are provided. These codes are used to identify the following in the micro component of the CSES dataset: - Respondent's likeability of the party/coalition (variable E3017). - Respondent's left-right placement of the party/coalition (variable E3019). - Respondent's placement of the party/coalition on an alternative scale, if applicable (variable E3021). These alphabetical codes are used to identify district and macro level information about these said parties/coalitions, namely: - The said party/coalition's vote share in the respondent's electoral district (variable E4004). - the said party/coalition's share of the seats in the election in the respondent's electoral district (variable E4005) - the said party/coalition's share of the vote in the election (variable E5001, E5003, and E5005). - the said party/coalition's share of the seats in the election (variable E5002 and E5004). - the said party/coalition's share of cabinet portfolios before and after the election (variable E5011 and E5015). - expert judgments by the national Collaborators of the said party/ coalition's ideological family (variable E5017). - expert judgments by the national Collaborators of the said party/ coalition's left-right placement (variable E5018). - expert judgments by the national Collaborators of the said party/ coalition's placement on an alternative scale, if applicable (variable E5019). - expert judgments by the national Collaborators of the said party/ coalition's level of populism (variable E5020). - The said party/coalition's Manifesto Research on Political Representation (MARPOR/CMP) Identifier (variable E5200). - The said party/coalition's Parliaments and Government Database (ParlGov) Identifier (variable E5201). - The said party/coalition's Chapel Hill Expert Survey (CHES) Identifier (variable E5202). - The said party/coalition's Party Facts Identifier (variable E5203). <<>> CSES ALPHABETICAL LEADER CODING Leaders A through F tend to be the leaders of the six most popular parties/ coalitions or the Presidential candidates of these parties. They correspond to parties A-F (i.e., Leader A will be related to Party A in some way, Leader B will be related to Party B, etc.). Leaders G, H, and I are supplemental leaders. They may be related to parties G, H, I, but they do not have to be. These leaders are voluntarily provided by each country's election study and often include data about additional personalities of interest. For example, in a parliamentary system, data about a President might be provided, even if the Presidency is not being contested. On many occasions, slots Leader G, H, and I will include additional data for parties/coalitions that have multiple leaders. These codes are used to identify the following in the micro and macro components of the CSES dataset: - Respondent's likeability of the leader/personality in question (variable E3018). =========================================================================== ))) CSES DATA BRIDGING: NEW FRONTIERS =========================================================================== Data Bridging enables users to bring together information from CSES with other data sources. The concept is part of CSES Data Linkage efforts. CSES has been a pioneer of Data Linkage with the inclusion of various macro-level data originating from other sources (e.g., The World Bank, the IDEA) directly in CSES data products, including in CSES MODULE 5. These macro data classify the political system's characteristics and contextual conditions of a polity at the election time. Data Bridging gives users the power to build on the direct data linkage in CSES products by enabling users to easily link other data with CSES products. CSES MODULE 5 enables users to bridge data with other prominent datasets in political science by including standard identifiers at the polity, year, and party level used by other projects to facilitate merging. CSES MODULE 5 facilitates data bridging with other datasets at the polity level with the following variables: - E1006_UN ID COMPONENT - POLITY UN ISO_3166-1 NUMERIC CODE - E1006_UNALPHA2 ID COMPONENT - POLITY UN ISO_3166-1 ALPHABETIC TWO LETTER CODE - E1006_NAM ID COMPONENT - POLITY NAME - E1006_VDEM ID COMPONENT - V-Dem POLITY IDENTIFIER More details can be found on all these variables in CSES Codebook Part 2 by searching for the variable name (e.g., "E1006_UN") or using the search term "POTENTIAL POLITY LEVEL BRIDGING IDENTIFIER". CSES MODULE 5 facilitates data bridging with other datasets at the regional level through the following variables: - E1006_REG ID COMPONENT - POLITY UN GEOGRAPHIC REGIONS NUMERIC CODES More details can be found on all these variables in CSES Codebook Part 2 by searching for the variable name (e.g., "E1006_REG") or using the search term "POTENTIAL REGIONAL LEVEL BRIDGING IDENTIFIER". CSES MODULE 5 facilitates data bridging with other datasets by date through the following variables: - E1008_YEAR ID COMPONENT - ELECTION YEAR - E1016 DATE 1ST ROUND ELECTION BEGAN - MONTH - E1017 DATE 1ST ROUND ELECTION BEGAN - DAY - E1018 DATE 1ST ROUND ELECTION BEGAN - YEAR - E1018_1 DATE 1ST ROUND ELECTION BEGAN - YYYY-MM-DD - E1018_2 DATE 1ST ROUND ELECTION BEGAN - YYYYMM - E1019 DATE 2ND ROUND ELECTION BEGAN - MONTH - E1020 DATE 2ND ROUND ELECTION BEGAN - DAY - E1021 DATE 2ND ROUND ELECTION BEGAN - YEAR - E1021_1 DATE 2ND ROUND ELECTION BEGAN - YYYY-MM-DD - E1021_2 DATE 2ND ROUND ELECTION BEGAN - YYYYMM More details can be found on all these variables in CSES Codebook Part 2 by searching for the variable name (e.g., "E1008_YEAR") or using the search term "POTENTIAL TIME BRIDGING IDENTIFIER". CSES MODULE 5 facilitates data bridging with other datasets at the party/coalition level with the following variables: - E5200_A-I MANIFESTO RESEARCH ON POLITICAL REPRESENTATION (MARPOR/CMP) IDENTIFIER - PARTY A-I - E5201_A-I PARLIAMENTS AND GOVERNMENT DATABASE (PARLGOV) IDENTIFIER - PARTY A-I - E5202_A-I CHAPEL HILL EXPERT SURVEY (CHES) IDENTIFIER - PARTY A-I - E5203_A-I PARTY FACTS IDENTIFIER - PARTY A-I More details can be found on all these variables in CSES Codebook Part 2 by searching for the variable name (e.g., "E5200_A") or using the search term "POTENTIAL PARTY/COALITION LEVEL BRIDGING IDENTIFIER." Users can also see the specific bridging codes for each party/coalition assigned an alphabetical code in CSES by other projects in Part 3 of the CSES MODULE 5 Codebook. CSES MODULE 5 facilitates data bridging with other CSES products at the party/coalition level with the following variables: - E6000_PR_1 IMD BRIDGING VARIABLE: CURRENT PRESIDENTIAL ELECTION: VOTE CHOICE - 1ST ROUND - E6000_PR_2 IMD BRIDGING VARIABLE: CURRENT PRESIDENTIAL ELECTION: VOTE CHOICE - 2ND ROUND - E6000_LH_PL IMD BRIDGING VARIABLE: CURRENT LOWER HOUSE ELECTION: VOTE CHOICE: PARTY LIST - E6000_LH_DC IMD BRIDGING VARIABLE: CURRENT LOWER HOUSE ELECTION: VOTE CHOICE: DISTRICT CANDIDATE More details can be found on all these variables in CSES Codebook Part 2 by searching for the variable name (e.g., "E6000_PR_1") or using the search term "POTENTIAL CSES PRODUCT BRIDGING IDENTIFIER". =========================================================================== ))) LIST OF TABLES IN CODEBOOK PART 2 =========================================================================== Below, we list the Tables located in Codebook Part 2. Tables can be accessed in the electronic version of the CSES Codebook by searching for "+++". - TYPE OF ORIGINAL WEIGHTS BY INDIVIDUAL ELECTION STUDIES - ELECTION STUDIES BY TYPE OF ELECTION - DATES OF FIELDWORK BY POLITY - INCOME MEASURE TYPE BY ELECTION STUDY - LANGUAGES (E3006_3) AND RELIGIONS (E3006_6_PT) ASKED ABOUT IN THE ELECTION STUDIES - FREQUENCIES ON E3010_2 FOR RESPONDENTS REPORTING NOT TO HAVE A PARTY REPRESENTING THEIR VIEWS BEST - ELECTION STUDIES BY TYPE OF MAIN ELECTION - ELECTION STUDIES BY TYPE OF MAIN ELECTION - PREVIOUS PRESIDENTIAL ELECTION (1ST ROUND) AND THE YEAR IN WHICH IT WAS HELD - PREVIOUS LOWER HOUSE ELECTION AND THE YEAR IN WHICH IT WAS HELD - PREVIOUS UPPER HOUSE ELECTION AND THE YEAR IN WHICH IT WAS HELD - FREQUENCIES OF RESPONDENTS REPORTING THAT THEY HAD NOT HEARD OF A SPECIFIC PARTY BUT PROVIDE AN EVALUATION OF THE PARTY ON ANY OTHER SCALE - FREQUENCIES ON E3019_ AND E3020 FOR RESPONDENTS REPORTING THAT THEY DID NOT KNOW OF THE LEFT-RIGHT SCALE BUT PROVIDE AN EVALUATION OF A PARTY ON THE LEFT-RIGHT SCALE - FREQUENCIES ON E3021_ AND E3022 FOR RESPONDENTS WHO SAID THEY DID NOT KNOW OF THE ALTERNATIVE SCALE IN ONE VARIABLE, BUT EVALUATING OTHER PARTIES ON THE ALTERNATIVE SCALE - FREQUENCIES ON E3024_3 FOR RESPONDENTS THAT DO NOT FEEL CLOSE (E3024_1) OR AT LEAST CLOSER (E3024_2) TO A PARTY - FREQUENCIES ON E3024_4 FOR RESPONDENTS THAT DO NOT MENTION A PARTY IN E3024_3 - SUMMARY OF POLITY AND WHICH ELECTION IN THAT POLITY THAT THE DISTRICT DATA REFERS TO - TOTAL NUMBER OF ELECTORAL DISTRICTS PER POLITY AND TOTAL NUMBER OF ELECTORAL DISTRICTS REPRESENTED IN CSES DATA - GINI COEFFICIENT YEAR OF CALCULATION BY ELECTION STUDY - POPULATION CLASSIFICATIONS SOURCE DATA YEAR BY ELECTION STUDY - LINGUISTIC FRACTIONALIZATION SOURCE DATA YEAR BY ELECTION STUDY - RELIGIOUS FRACTIONALIZATION SOURCE DATA YEAR BY ELECTION STUDY - ETHNIC FRACTIONALIZATION METRIC SOURCE DATA YEAR BY ELECTION STUDY - PARTIES INCLUDED IN E3013_PR_ FOR WHICH IMD NUMERIC PARTY CODES HAVE NOT BEEN ASSIGNED YET - PARTIES INCLUDED IN E3013_LH_PL FOR WHICH IMD NUMERIC PARTY CODES HAVE NOT BEEN ASSIGNED YET - PARTIES INCLUDED IN E3013_LH_DC FOR WHICH IMD NUMERIC PARTY CODES HAVE NOT BEEN ASSIGNED YET =========================================================================== ))) CSES MODULE 5 VARIABLE LIST =========================================================================== ))) CSES MODULE 5 VARIABLES: IDENTIFICATION, WEIGHT, AND STUDY ADMINISTRATION DATA E1001 >>> DATASET E1002_VER >>> DATASET VERSION E1002_DOI >>> DIGITAL OBJECT IDENTIFIER E1003 >>> ID VARIABLE - ELECTION STUDY (NUMERIC POLITY) E1004 >>> ID VARIABLE - ELECTION STUDY (POLITY ALPHABETIC AND YEAR OF ELECTION) E1005 >>> ID VARIABLE - RESPONDENT E1006 >>> ID COMPONENT - POLITY CSES CODE E1006_UN >>> ID COMPONENT - POLITY UN ISO_3166-1 NUMERIC CODE E1006_UNALPHA2 >>> ID COMPONENT - POLITY UN ISO_3166-1 ALPHABETIC TWO LETTER CODE E1006_UNALPHA3 >>> ID COMPONENT - POLITY UN ISO_3166-1 ALPHABETIC THREE LETTER CODE E1006_NAM >>> ID COMPONENT - POLITY NAME E1006_REG >>> ID COMPONENT - POLITY UN GEOGRAPHIC REGIONS NUMERIC CODES E1006_OECD >>> ID COMPONENT - POLITY MEMBER OF OECD E1006_EU >>> ID COMPONENT - POLITY MEMBER OF EUROPEAN UNION E1006_VDEM >>> ID COMPONENT - V-Dem POLITY IDENTIFIER E1007 >>> ID COMPONENT - SAMPLE COMPONENT E1008 >>> ID COMPONENT - ELECTION YEAR E1009 >>> A01 ID COMPONENT - RESPONDENT WITHIN ELECTION STUDY E1009_P1 >>> ID COMPONENT - WHETER RESPONDENT COMPLETED CSES MODULE MULTIPLE TIMES IN PANEL STUDY E1009_P2 >>> ID COMPONENT - PANEL ID FOR R THAT COMPLETED CSES MODULE MULTIPLE TIMES IN PANEL STUDY E1010_1 >>> A05 ORIGINAL WEIGHT: SAMPLE E1010_2 >>> A05 ORIGINAL WEIGHT: DEMOGRAPHIC E1010_3 >>> A05 ORIGINAL WEIGHT: POLITICAL E1011_1 >>> FACTOR: MEAN OF SAMPLE WEIGHT E1011_2 >>> FACTOR: MEAN OF DEMOGRAPHIC WEIGHT E1011_3 >>> FACTOR: MEAN OF POLITICAL WEIGHT E1012_1 >>> POLITY WEIGHT: SAMPLE E1012_2 >>> POLITY WEIGHT: DEMOGRAPHIC E1012_3 >>> POLITY WEIGHT: POLITICAL E1013 >>> FACTOR: SAMPLE SIZE ADJUSTMENT E1014_1 >>> DATASET WEIGHT: SAMPLE E1014_2 >>> DATASET WEIGHT: DEMOGRAPHIC E1014_3 >>> DATASET WEIGHT: POLITICAL E1015 >>> ELECTION TYPE E1016 >>> DATE 1ST ROUND ELECTION BEGAN - MONTH E1017 >>> DATE 1ST ROUND ELECTION BEGAN - DAY E1018 >>> DATE 1ST ROUND ELECTION BEGAN - YEAR E1018_1 >>> DATE 1ST ROUND ELECTION BEGAN - YYYY-MM-DD E1018_2 >>> DATE 1ST ROUND ELECTION BEGAN - YYYYMM E1019 >>> DATE 2ND ROUND ELECTION BEGAN - MONTH E1020 >>> DATE 2ND ROUND ELECTION BEGAN - DAY E1021 >>> DATE 2ND ROUND ELECTION BEGAN - YEAR E1021_1 >>> DATE 2ND ROUND ELECTION BEGAN - YYYY-MM-DD E1021_2 >>> DATE 2ND ROUND ELECTION BEGAN - YYYYMM E1022 >>> STUDY TIMING E1023 >>> STUDY CONTEXT E1024_1 >>> MODE OF INTERVIEW - STUDY - FIRST E1024_2 >>> MODE OF INTERVIEW - STUDY - SECOND E1024_3 >>> MODE OF INTERVIEW - STUDY - THIRD E1025_1 >>> MODE OF INTERVIEW - RESPONDENT - FIRST E1025_2 >>> MODE OF INTERVIEW - RESPONDENT - SECOND E1025_3 >>> MODE OF INTERVIEW - RESPONDENT - THIRD E1026 >>> SELF-SELECTION INTO MODE OF INTERVIEW E1027 >>> DURATION OF INTERVIEW E1028 >>> A02 INTERVIEWER ID WITHIN ELECTION STUDY E1029 >>> A03 INTERVIEWER GENDER E1030 >>> DAYS FIELDWORK STARTED POST ELECTION E1031 >>> DURATION OF FIELDWORK E1032 >>> A04a DATE QUESTIONNAIRE ADMINISTERED - MONTH E1033 >>> A04b DATE QUESTIONNAIRE ADMINISTERED - DAY E1034 >>> A04c DATE QUESTIONNAIRE ADMINISTERED - YEAR E1035_1 >>> DAYS INTERVIEW CONDUCTED POST FIRST ROUND OF ELECTION E1035_2 >>> DAYS INTERVIEW CONDUCTED POST SECOND ROUND OF ELECTION E1036 >>> A06 LANGUAGE OF QUESTIONNAIRE ADMINISTRATION E1037 >>> QUESTIONNAIRE VERSION E1038 >>> STUDY TIMING WITH RESPECT TO COVID-19 PANDEMIC E1039 >>> ID COMPONENT - WHETHER POLITY ADMINISTERED CSES MODULE 5 MULTIPLE TIMES ))) CSES MODULE 5 VARIABLES: MICRO-LEVEL (SURVEY) DATA DEMOGRAPHIC DATA E2001_Y >>> D01b DATE OF BIRTH OF RESPONDENT - YEAR E2001_A >>> AGE OF RESPONDENT (IN YEARS) E2001_GG >>> BIRTH GENERATION: GREATEST GENERATION (BORN 1927 OR BEFORE) E2001_GS >>> BIRTH GENERATION: SILENT GENERATION (BORN FROM 1928 TO 1945) E2001_GBB >>> BIRTH GENERATION: BABY BOOMERS (BORN FROM 1946 TO 1964) E2001_GX >>> BIRTH GENERATION: GENERATION X (BORN FROM 1965 TO 1980) E2001_GY >>> BIRTH GENERATION: GENERATION Y (BORN FROM 1981 TO 1996) E2001_GZ >>> BIRTH GENERATION: GENERATION Z (BORN FROM 1997 ONWARDS) E2002 >>> D02 GENDER E2003 >>> D03 EDUCATION E2004 >>> D04 MARITAL STATUS OR CIVIL UNION STATUS E2005 >>> D05 UNION MEMBERSHIP E2006 >>> D06 CURRENT EMPLOYMENT STATUS E2007 >>> D07 MAIN OCCUPATION E2008 >>> D07a SOCIO ECONOMIC STATUS E2009 >>> D08 EMPLOYMENT TYPE - PUBLIC OR PRIVATE E2010 >>> HOUSEHOLD INCOME - QUINTILES E2011 >>> D09 HOUSEHOLD INCOME - ORIGINAL VARIABLE E2012 >>> D20 NUMBER IN HOUSEHOLD E2013 >>> D10 RELIGIOUS DENOMINATION E2014 >>> D11 RELIGIOUS SERVICES ATTENDANCE E2015 >>> D12 RACE E2016 >>> D13 ETHNICITY E2017 >>> D14 COUNTRY OF BIRTH E2018 >>> D15 WAS EITHER BIOLOGICAL PARENT BORN OUTSIDE OF THE COUNTRY E2019 >>> D16 LANGUAGE USUALLY SPOKEN AT HOME E2020 >>> D17 REGION OF RESIDENCE E2021 >>> D18 PRIMARY ELECTORAL DISTRICT E2022 >>> D19 RURAL OR URBAN RESIDENCE ))) CSES MODULE 5 VARIABLES: MICRO-LEVEL (SURVEY) DATA THE CSES MODULE 5 QUESTIONNAIRE E3001 >>> Q01 POLITICAL INTEREST E3002 >>> Q02 FOLLOWS POLITICS IN THE MEDIA E3003 >>> Q03 INTERNAL EFFICACY E3004_1 >>> Q04a ATTITUDES ABOUT ELITES: COMPROMISE IS SELLING OUT ONE'S PRINCIPLES E3004_1_PT >>> Q04a_PT ATTITUDES ABOUT ELITES: IMPORTANT TO SEEK COMPROMISE - PRE-TEST E3004_2 >>> Q04b ATTITUDES ABOUT ELITES: DO NOT CARE ABOUT THE PEOPLE E3004_3 >>> Q04c ATTITUDES ABOUT ELITES: ARE TRUSTWORTHY E3004_4 >>> Q04d ATTITUDES ABOUT ELITES: ARE THE MAIN PROBLEM E3004_5 >>> Q04e ATTITUDES ABOUT ELITES: STRONG LEADER BENDS THE RULES E3004_6 >>> Q04f ATTITUDES ABOUT ELITES: PEOPLE SHOULD MAKE POLICY DECISIONS E3004_7 >>> Q04g ATTITUDES ABOUT ELITES: RICH AND POWERFUL E3004_8_PT >>> Q04h_PT ATTITUDES ABOUT ELITES: POOR PEOPLE SHOULD HAVE GREATER VOICE - PRE-TEST E3005_1 >>> Q05a OUT-GROUP ATTITUDES: MINORITIES - CUSTOMS AND TRADITIONS E3005_2 >>> Q05b OUT-GROUP ATTITUDES: MINORITIES - WILL OF THE MAJORITY E3005_3 >>> Q05c OUT-GROUP ATTITUDES: IMMIGRANTS GOOD FOR ECONOMY E3005_4 >>> Q05d OUT-GROUP ATTITUDES: CULTURE HARMED BY IMMIGRANTS E3005_5 >>> Q05e OUT-GROUP ATTITUDES: IMMIGRANTS INCREASE CRIME E3006_1 >>> Q06a NATIONAL IDENTITY: TO HAVE BEEN BORN IN COUNTRY E3006_2 >>> Q06b NATIONAL IDENTITY: ANCESTRY E3006_3 >>> Q06c NATIONAL IDENTITY: TO BE ABLE TO SPEAK COUNTRY LANGUAGES E3006_4 >>> Q06d NATIONAL IDENTITY: TO FOLLOW CUSTOMS AND TRADITIONS COUNTRY E3006_5_PT >>> Q06e_PT NATIONAL IDENTITY: TO HAVE LIVED IN COUNTRY FOR MOST OF LIFE - PRE-TEST E3006_6_PT >>> Q06f_PT NATIONAL IDENTITY: TO BE COUNTRY DOMINANT RELIGION - PRE-TEST E3006_7_PT >>> Q06g_PT NATIONAL IDENTITY: TO RESPECT POLITICAL INSTITUTIONS AND LAWS - PRE-TEST E3006_8_PT >>> Q06h_PT NATIONAL IDENTITY: TO FEEL COUNTRY NATIONALITY - PRE-TEST E3007 >>> Q07 HOW WIDESPREAD IS CORRUPTION E3008 >>> Q08 GOVERNMENT ACTION - DIFFERENCES IN INCOME LEVELS E3008_PT >>> Q08_PT GOVERNMENT ACTION - ATTITUDES TOWARDS REDISTRIBUTION - PRE-TEST E3009 >>> Q09 GOVERNMENT PERFORMANCE: GENERAL E3010_1 >>> Q10a IS THERE A PARTY THAT REPRESENTS RESPONDENT'S VIEWS E3010_2 >>> Q10b PARTY THAT REPRESENTS RESPONDENT'S VIEWS BEST E3011 >>> Q11 STATE OF THE ECONOMY E3012 >>> TURNOUT: MAIN ELECTION E3012_PR_1 >>> Q12P1-a CURRENT PRESIDENTIAL ELECTION: DID RESPONDENT CAST A BALLOT - 1ST ROUND E3012_PR_2 >>> Q12P2-a CURRENT PRESIDENTIAL ELECTION: DID RESPONDENT CAST A BALLOT - 2ND ROUND E3012_LH >>> Q12LH-a CURRENT LOWER HOUSE ELECTION: DID RESPONDENT CAST A BALLOT E3012_UH >>> Q12UH-a CURRENT UPPER HOUSE ELECTION: DID RESPONDENT CAST A BALLOT E3012_TS >>> TURNOUT SWITCHER BETWEEN CURRENT ELECTION AND PREVIOUS ELECTION E3012_FTV >>> FIRST TIME VOTER IN CURRENT MAIN ELECTION E3013_PR_1 >>> Q12P1-b CURRENT PRESIDENTIAL ELECTION: VOTE CHOICE - 1ST ROUND E3013_PR_2 >>> Q12P2-b CURRENT PRESIDENTIAL ELECTION: VOTE CHOICE - 2ND ROUND E3013_LH_PL >>> Q12LH-b CURRENT LOWER HOUSE ELECTION: VOTE CHOICE - PARTY LIST E3013_LH_DC >>> Q12LH-c CURRENT LOWER HOUSE ELECTION: VOTE CHOICE - DISTRICT CANDIDATE E3013_LH_PF >>> Q12LH-d CURRENT LOWER HOUSE ELECTION: DID RESPONDENT CAST CANDIDATE PREFERENCE VOTE E3013_UH_PL >>> Q12UH-b CURRENT UPPER HOUSE ELECTION: VOTE CHOICE - PARTY LIST E3013_UH_DC_1 >>> Q12UH-c CURRENT UPPER HOUSE ELECTION: VOTE CHOICE - DISTRICT CANDIDATE 1 E3013_UH_DC_2 >>> Q12UH-c CURRENT UPPER HOUSE ELECTION: VOTE CHOICE - DISTRICT CANDIDATE 2 E3013_UH_PF >>> Q12UH-d CURRENT UPPER HOUSE ELECTION: DID RESPONDENT CAST CANDIDATE PREFERENCE VOTE E3013_OUTGOV >>> CURRENT MAIN ELECTION - VOTE CHOICE - OUTGOING GOVERNMENT (INCUMBENT) E3013_VS_1 >>> VOTE SWITCHER BETWEEN CURRENT ELECTION AND PREVIOUS ELECTION E3013_LR_CSES >>> CURRENT MAIN ELECTION - VOTE FOR LEFTIST/CENTER/RIGHTIST - CSES E3013_LR_MARPOR >>> CURRENT MAIN ELECTION - VOTE FOR LEFT/RIGHT (RILE) - MARPOR/CMP E3013_IF_CSES >>> CURRENT MAIN ELECTION - VOTE CHOICE BY IDEOLOGICAL FAMILY CLASSIFICATION - CSES E3014_PR_1 >>> Q13a PREVIOUS PRESIDENTIAL ELECTION: DID RESPONDENT CAST A BALLOT - 1ST ROUND E3014_PR_2 >>> Q13a PREVIOUS PRESIDENTIAL ELECTION: DID RESPONDENT CAST A BALLOT - 2ND ROUND E3014_LH >>> Q13a PREVIOUS LOWER HOUSE ELECTION: DID RESPONDENT CAST A BALLOT E3014_UH >>> PREVIOUS UPPER HOUSE ELECTION: DID RESPONDENT CAST A BALLOT E3015_PR_1 >>> Q13b PREVIOUS PRESIDENTIAL ELECTION: VOTE CHOICE - 1ST ROUND E3015_PR_2 >>> Q13b PREVIOUS PRESIDENTIAL ELECTION: VOTE CHOICE - 2ND ROUND E3015_LH_PL >>> Q13b PREVIOUS LOWER HOUSE ELECTION: VOTE CHOICE - PARTY LIST E3015_LH_DC >>> Q13c PREVIOUS LOWER HOUSE ELECTION: VOTE CHOICE - DISTRICT CANDIDATE E3015_UH_PL >>> PREVIOUS UPPER HOUSE ELECTION: VOTE CHOICE - PARTY LIST E3015_UH_DC_1 >>> PREVIOUS UPPER HOUSE ELECTION: VOTE CHOICE - DISTRICT CANDIDATE 1 E3015_UH_DC_2 >>> PREVIOUS UPPER HOUSE ELECTION: VOTE CHOICE - DISTRICT CANDIDATE 2 E3016_1 >>> Q14a WHO IS IN POWER CAN MAKE DIFFERENCE E3016_2 >>> Q14b WHO PEOPLE VOTE FOR MAKES A DIFFERENCE E3017_A >>> Q15a LIKE-DISLIKE - PARTY A E3017_B >>> Q15b LIKE-DISLIKE - PARTY B E3017_C >>> Q15c LIKE-DISLIKE - PARTY C E3017_D >>> Q15d LIKE-DISLIKE - PARTY D E3017_E >>> Q15e LIKE-DISLIKE - PARTY E E3017_F >>> Q15f LIKE-DISLIKE - PARTY F E3017_G >>> Q15g LIKE-DISLIKE - ADDITIONAL - PARTY G E3017_H >>> Q15h LIKE-DISLIKE - ADDITIONAL - PARTY H E3017_I >>> Q15i LIKE-DISLIKE - ADDITIONAL - PARTY I E3018_A >>> Q16a LIKE-DISLIKE - LEADER A E3018_B >>> Q16b LIKE-DISLIKE - LEADER B E3018_C >>> Q16c LIKE-DISLIKE - LEADER C E3018_D >>> Q16d LIKE-DISLIKE - LEADER D E3018_E >>> Q16e LIKE-DISLIKE - LEADER E E3018_F >>> Q16f LIKE-DISLIKE - LEADER F E3018_G >>> Q16g LIKE-DISLIKE - ADDITIONAL - LEADER G E3018_H >>> Q16h LIKE-DISLIKE - ADDITIONAL - LEADER H E3018_I >>> Q16i LIKE-DISLIKE - ADDITIONAL - LEADER I E3019_A >>> Q17a IDEOLOGY: LEFT-RIGHT - PARTY A E3019_B >>> Q17b IDEOLOGY: LEFT-RIGHT - PARTY B E3019_C >>> Q17c IDEOLOGY: LEFT-RIGHT - PARTY C E3019_D >>> Q17d IDEOLOGY: LEFT-RIGHT - PARTY D E3019_E >>> Q17e IDEOLOGY: LEFT-RIGHT - PARTY E E3019_F >>> Q17f IDEOLOGY: LEFT-RIGHT - PARTY F E3019_G >>> Q17g IDEOLOGY: LEFT-RIGHT - ADDITIONAL - PARTY G E3019_H >>> Q17h IDEOLOGY: LEFT-RIGHT - ADDITIONAL - PARTY H E3019_I >>> Q17i IDEOLOGY: LEFT-RIGHT - ADDITIONAL - PARTY I E3020 >>> Q18 IDEOLOGY: LEFT-RIGHT - SELF E3021_A >>> Q19a OPTIONAL ALTERNATIVE SCALE - PARTY A E3021_B >>> Q19b OPTIONAL ALTERNATIVE SCALE - PARTY B E3021_C >>> Q19c OPTIONAL ALTERNATIVE SCALE - PARTY C E3021_D >>> Q19d OPTIONAL ALTERNATIVE SCALE - PARTY D E3021_E >>> Q19e OPTIONAL ALTERNATIVE SCALE - PARTY E E3021_F >>> Q19f OPTIONAL ALTERNATIVE SCALE - PARTY F E3021_G >>> Q19g OPTIONAL ALTERNATIVE SCALE - ADDITIONAL - PARTY G E3021_H >>> Q19h OPTIONAL ALTERNATIVE SCALE - ADDITIONAL - PARTY H E3021_I >>> Q19i OPTIONAL ALTERNATIVE SCALE - ADDITIONAL - PARTY I E3022 >>> Q20 OPTIONAL ALTERNATIVE SCALE - SELF E3023 >>> Q21 SATISFACTION WITH DEMOCRACY E3024_1 >>> Q22a PARTY ID: ARE YOU CLOSE TO ANY POLITICAL PARTY E3024_2 >>> Q22b PARTY ID: DO YOU FEEL CLOSER TO ONE PARTY E3024_3 >>> Q22c PARTY ID: WHICH PARTY DO YOU FEEL CLOSEST TO E3024_4 >>> Q22d PARTY ID: DEGREE OF CLOSENESS TO THIS PARTY E3100_LR_CSES >>> CURRENT MAIN ELECTION - VOTE CHOICE LINKED WITH CSES COLLABORATOR EXPERT JUDGMENT L-R E3100_LR_MARPOR >>> CURRENT MAIN ELECTION - VOTE CHOICE LINKED WITH MARPOR/CMP RILE E3100_POP_CSES >>> CURRENT MAIN ELECTION - VOTE CHOICE LINKED WITH CSES COLLABORATOR EXPERT JUDGMENT ON POPULISM E3100_IF_CSES >>> CURRENT MAIN ELECTION - VOTE CHOICE LINKED WITH CSES COLLABORATOR EXPERT JUDGMENT IDEOLOGICAL FAMILY ))) CSES MODULE 5 VARIABLES: DISTRICT-LEVEL DATA E4001 >>> NUMBER OF SEATS IN DISTRICT E4001_N >>> NUMBER OF SEATS IN DISTRICT - NATIONWIDE ELECTORAL DISTRICT E4002 >>> NUMBER OF CANDIDATES IN DISTRICT E4002_N >>> NUMBER OF CANDIDATES IN DISTRICT - NATIONWIDE ELECTORAL DISTRICT E4003 >>> NUMBER OF PARTY LISTS IN DISTRICT E4003_N >>> NUMBER OF PARTY LISTS IN DISTRICT - NATIONWIDE ELECTORAL DISTRICT E4004_A >>> PERCENT VOTE IN DISTRICT - PARTY A E4004_B >>> PERCENT VOTE IN DISTRICT - PARTY B E4004_C >>> PERCENT VOTE IN DISTRICT - PARTY C E4004_D >>> PERCENT VOTE IN DISTRICT - PARTY D E4004_E >>> PERCENT VOTE IN DISTRICT - PARTY E E4004_F >>> PERCENT VOTE IN DISTRICT - PARTY F E4004_G >>> PERCENT VOTE IN DISTRICT - PARTY G E4004_H >>> PERCENT VOTE IN DISTRICT - PARTY H E4004_I >>> PERCENT VOTE IN DISTRICT - PARTY I E4004_A_N >>> PERCENT VOTE IN DISTRICT - PARTY A - NATIONWIDE ELECTORAL DISTRICT E4004_B_N >>> PERCENT VOTE IN DISTRICT - PARTY B - NATIONWIDE ELECTORAL DISTRICT E4004_C_N >>> PERCENT VOTE IN DISTRICT - PARTY C - NATIONWIDE ELECTORAL DISTRICT E4004_D_N >>> PERCENT VOTE IN DISTRICT - PARTY D - NATIONWIDE ELECTORAL DISTRICT E4004_E_N >>> PERCENT VOTE IN DISTRICT - PARTY E - NATIONWIDE ELECTORAL DISTRICT E4004_F_N >>> PERCENT VOTE IN DISTRICT - PARTY F - NATIONWIDE ELECTORAL DISTRICT E4004_G_N >>> PERCENT VOTE IN DISTRICT - PARTY G - NATIONWIDE ELECTORAL DISTRICT E4004_H_N >>> PERCENT VOTE IN DISTRICT - PARTY H - NATIONWIDE ELECTORAL DISTRICT E4004_I_N >>> PERCENT VOTE IN DISTRICT - PARTY I - NATIONWIDE ELECTORAL DISTRICT E4005_A >>> SEATS IN DISTRICT - PARTY A E4005_B >>> SEATS IN DISTRICT - PARTY B E4005_C >>> SEATS IN DISTRICT - PARTY C E4005_D >>> SEATS IN DISTRICT - PARTY D E4005_E >>> SEATS IN DISTRICT - PARTY E E4005_F >>> SEATS IN DISTRICT - PARTY F E4005_G >>> SEATS IN DISTRICT - PARTY G E4005_H >>> SEATS IN DISTRICT - PARTY H E4005_I >>> SEATS IN DISTRICT - PARTY I E4005_A_N >>> SEATS IN DISTRICT - PARTY A - NATIONWIDE ELECTORAL DISTRICT E4005_B_N >>> SEATS IN DISTRICT - PARTY B - NATIONWIDE ELECTORAL DISTRICT E4005_C_N >>> SEATS IN DISTRICT - PARTY C - NATIONWIDE ELECTORAL DISTRICT E4005_D_N >>> SEATS IN DISTRICT - PARTY D - NATIONWIDE ELECTORAL DISTRICT E4005_E_N >>> SEATS IN DISTRICT - PARTY E - NATIONWIDE ELECTORAL DISTRICT E4005_F_N >>> SEATS IN DISTRICT - PARTY F - NATIONWIDE ELECTORAL DISTRICT E4005_G_N >>> SEATS IN DISTRICT - PARTY G - NATIONWIDE ELECTORAL DISTRICT E4005_H_N >>> SEATS IN DISTRICT - PARTY H - NATIONWIDE ELECTORAL DISTRICT E4005_I_N >>> SEATS IN DISTRICT - PARTY I - NATIONWIDE ELECTORAL DISTRICT E4006 >>> TURNOUT IN DISTRICT E4006_N >>> TURNOUT IN DISTRICT - NATIONWIDE ELECTORAL DISTRICT E4007 >>> SIZE OF ELECTORATE OR POPULATION IN DISTRICT E4007_N >>> SIZE OF ELECTORATE OR POPULATION IN DISTRICT - NATIONWIDE ELECTORAL DISTRICT ))) CSES MODULE 5 VARIABLES: RELATIONAL DATA IDENTIFIERS & MACRO-LEVEL DATA I. RELATIONAL DATA - ALPHABETICAL IDENTIFIERS E5000_A >>> PARTY A IDENTIFIER - NUMERICAL E5000_B >>> PARTY B IDENTIFIER - NUMERICAL E5000_C >>> PARTY C IDENTIFIER - NUMERICAL E5000_D >>> PARTY D IDENTIFIER - NUMERICAL E5000_E >>> PARTY E IDENTIFIER - NUMERICAL E5000_F >>> PARTY F IDENTIFIER - NUMERICAL E5000_G >>> PARTY G IDENTIFIER - NUMERICAL E5000_H >>> PARTY H IDENTIFIER - NUMERICAL E5000_I >>> PARTY I IDENTIFIER - NUMERICAL E5000_L_A >>> LEADER A IDENTIFIER - NUMERICAL E5000_L_B >>> LEADER B IDENTIFIER - NUMERICAL E5000_L_C >>> LEADER C IDENTIFIER - NUMERICAL E5000_L_D >>> LEADER D IDENTIFIER - NUMERICAL E5000_L_E >>> LEADER E IDENTIFIER - NUMERICAL E5000_L_F >>> LEADER F IDENTIFIER - NUMERICAL E5000_L_G >>> LEADER G IDENTIFIER - NUMERICAL E5000_L_H >>> LEADER H IDENTIFIER - NUMERICAL E5000_L_I >>> LEADER I IDENTIFIER - NUMERICAL II. ELECTION-SPECIFIC AND ELECTORAL RULES DATA E5001_A >>> PERCENT VOTE - LOWER HOUSE - PARTY A E5001_B >>> PERCENT VOTE - LOWER HOUSE - PARTY B E5001_C >>> PERCENT VOTE - LOWER HOUSE - PARTY C E5001_D >>> PERCENT VOTE - LOWER HOUSE - PARTY D E5001_E >>> PERCENT VOTE - LOWER HOUSE - PARTY E E5001_F >>> PERCENT VOTE - LOWER HOUSE - PARTY F E5001_G >>> PERCENT VOTE - LOWER HOUSE - PARTY G E5001_H >>> PERCENT VOTE - LOWER HOUSE - PARTY H E5001_I >>> PERCENT VOTE - LOWER HOUSE - PARTY I E5002_A >>> PERCENT SEATS - LOWER HOUSE - PARTY A E5002_B >>> PERCENT SEATS - LOWER HOUSE - PARTY B E5002_C >>> PERCENT SEATS - LOWER HOUSE - PARTY C E5002_D >>> PERCENT SEATS - LOWER HOUSE - PARTY D E5002_E >>> PERCENT SEATS - LOWER HOUSE - PARTY E E5002_F >>> PERCENT SEATS - LOWER HOUSE - PARTY F E5002_G >>> PERCENT SEATS - LOWER HOUSE - PARTY G E5002_H >>> PERCENT SEATS - LOWER HOUSE - PARTY H E5002_I >>> PERCENT SEATS - LOWER HOUSE - PARTY I E5003_A >>> PERCENT VOTE - UPPER HOUSE - PARTY A E5003_B >>> PERCENT VOTE - UPPER HOUSE - PARTY B E5003_C >>> PERCENT VOTE - UPPER HOUSE - PARTY C E5003_D >>> PERCENT VOTE - UPPER HOUSE - PARTY D E5003_E >>> PERCENT VOTE - UPPER HOUSE - PARTY E E5003_F >>> PERCENT VOTE - UPPER HOUSE - PARTY F E5003_G >>> PERCENT VOTE - UPPER HOUSE - PARTY G E5003_H >>> PERCENT VOTE - UPPER HOUSE - PARTY H E5003_I >>> PERCENT VOTE - UPPER HOUSE - PARTY I E5004_A >>> PERCENT SEATS - UPPER HOUSE - PARTY A E5004_B >>> PERCENT SEATS - UPPER HOUSE - PARTY B E5004_C >>> PERCENT SEATS - UPPER HOUSE - PARTY C E5004_D >>> PERCENT SEATS - UPPER HOUSE - PARTY D E5004_E >>> PERCENT SEATS - UPPER HOUSE - PARTY E E5004_F >>> PERCENT SEATS - UPPER HOUSE - PARTY F E5004_G >>> PERCENT SEATS - UPPER HOUSE - PARTY G E5004_H >>> PERCENT SEATS - UPPER HOUSE - PARTY H E5004_I >>> PERCENT SEATS - UPPER HOUSE - PARTY I E5005_A >>> PERCENT VOTE - PRESIDENT - PARTY A E5005_B >>> PERCENT VOTE - PRESIDENT - PARTY B E5005_C >>> PERCENT VOTE - PRESIDENT - PARTY C E5005_D >>> PERCENT VOTE - PRESIDENT - PARTY D E5005_E >>> PERCENT VOTE - PRESIDENT - PARTY E E5005_F >>> PERCENT VOTE - PRESIDENT - PARTY F E5005_G >>> PERCENT VOTE - PRESIDENT - PARTY G E5005_H >>> PERCENT VOTE - PRESIDENT - PARTY H E5005_I >>> PERCENT VOTE - PRESIDENT - PARTY I E5006_1 >>> ELECTORAL TURNOUT - TURNOUT AS A PERCENTAGE OF REGISTERED VOTERS (ER) E5006_2 >>> ELECTORAL TURNOUT - TURNOUT AS A PERCENTAGE OF THE VOTING AGE POPULATION (VAP) E5007_1 >>> ELECTORAL MANAGEMENT: ELECTORAL ADMINISTRATION MODEL E5007_2 >>> ELECTORAL MANAGEMENT: COMPULSORY VOTER REGISTRATION E5008_1 >>> M04c VOTING OPERATIONS: EARLY/ADVANCE VOTING E5008_2 >>> M04d VOTING OPERATIONS: VOTE BY MAIL/POSTAL E5008_3 >>> M04e VOTING OPERATIONS: VOTE ONLINE/INTERNET E5009 >>> M02a PARTY OF THE PRESIDENT BEFORE E5010 >>> M02b PARTY OF THE PRIME MINISTER BEFORE E5011_A >>> M02c NUMBER OF PORTFOLIOS BEFORE ELECTION - PARTY A E5011_B >>> M02c NUMBER OF PORTFOLIOS BEFORE ELECTION - PARTY B E5011_C >>> M02c NUMBER OF PORTFOLIOS BEFORE ELECTION - PARTY C E5011_D >>> M02c NUMBER OF PORTFOLIOS BEFORE ELECTION - PARTY D E5011_E >>> M02c NUMBER OF PORTFOLIOS BEFORE ELECTION - PARTY E E5011_F >>> M02c NUMBER OF PORTFOLIOS BEFORE ELECTION - PARTY F E5011_G >>> M02c NUMBER OF PORTFOLIOS BEFORE ELECTION - PARTY G E5011_H >>> M02c NUMBER OF PORTFOLIOS BEFORE ELECTION - PARTY H E5011_I >>> M02c NUMBER OF PORTFOLIOS BEFORE ELECTION - PARTY I E5012 >>> M02d SIZE OF THE CABINET BEFORE ELECTION E5013 >>> M03a PARTY OF THE PRESIDENT AFTER ELECTION E5014 >>> M03b PARTY OF THE PRIME MINISTER AFTER ELECTION E5015_A >>> M03c NUMBER OF PORTFOLIOS AFTER ELECTION - PARTY A E5015_B >>> M03c NUMBER OF PORTFOLIOS AFTER ELECTION - PARTY B E5015_C >>> M03c NUMBER OF PORTFOLIOS AFTER ELECTION - PARTY C E5015_D >>> M03c NUMBER OF PORTFOLIOS AFTER ELECTION - PARTY D E5015_E >>> M03c NUMBER OF PORTFOLIOS AFTER ELECTION - PARTY E E5015_F >>> M03c NUMBER OF PORTFOLIOS AFTER ELECTION - PARTY F E5015_G >>> M03c NUMBER OF PORTFOLIOS AFTER ELECTION - PARTY G E5015_H >>> M03c NUMBER OF PORTFOLIOS AFTER ELECTION - PARTY H E5015_I >>> M03c NUMBER OF PORTFOLIOS AFTER ELECTION - PARTY I E5016 >>> M03d SIZE OF THE CABINET AFTER ELECTION E5017_A >>> M05a.a EXPERT: IDEOLOGICAL FAMILY - PARTY A E5017_B >>> M05a.b EXPERT: IDEOLOGICAL FAMILY - PARTY B E5017_C >>> M05a.c EXPERT: IDEOLOGICAL FAMILY - PARTY C E5017_D >>> M05a.d EXPERT: IDEOLOGICAL FAMILY - PARTY D E5017_E >>> M05a.e EXPERT: IDEOLOGICAL FAMILY - PARTY E E5017_F >>> M05a.f EXPERT: IDEOLOGICAL FAMILY - PARTY F E5017_G >>> M05a.g EXPERT: IDEOLOGICAL FAMILY - PARTY G E5017_H >>> M05a.h EXPERT: IDEOLOGICAL FAMILY - PARTY H E5017_I >>> M05a.i EXPERT: IDEOLOGICAL FAMILY - PARTY I E5018_A >>> M06a1.a EXPERT: IDEOLOGY LEFT-RIGHT - PARTY A E5018_B >>> M06a1.b EXPERT: IDEOLOGY LEFT-RIGHT - PARTY B E5018_C >>> M06a1.c EXPERT: IDEOLOGY LEFT-RIGHT - PARTY C E5018_D >>> M06a1.d EXPERT: IDEOLOGY LEFT-RIGHT - PARTY D E5018_E >>> M06a1.e EXPERT: IDEOLOGY LEFT-RIGHT - PARTY E E5018_F >>> M06a1.f EXPERT: IDEOLOGY LEFT-RIGHT - PARTY F E5018_G >>> M06a1.g EXPERT: IDEOLOGY LEFT-RIGHT - PARTY G E5018_H >>> M06a1.h EXPERT: IDEOLOGY LEFT-RIGHT - PARTY H E5018_I >>> M06a1.i EXPERT: IDEOLOGY LEFT-RIGHT - PARTY I E5019 >>> M06b1 ALTERNATIVE DIMENSION E5019_A >>> M06b1.a ALTERNATIVE DIMENSION - PARTY A E5019_B >>> M06b1.b ALTERNATIVE DIMENSION - PARTY B E5019_C >>> M06b1.c ALTERNATIVE DIMENSION - PARTY C E5019_D >>> M06b1.d ALTERNATIVE DIMENSION - PARTY D E5019_E >>> M06b1.e ALTERNATIVE DIMENSION - PARTY E E5019_F >>> M06b1.f ALTERNATIVE DIMENSION - PARTY F E5019_G >>> M06b1.g ALTERNATIVE DIMENSION - PARTY G E5019_H >>> M06b1.h ALTERNATIVE DIMENSION - PARTY H E5019_I >>> M06b1.i ALTERNATIVE DIMENSION - PARTY I E5020 >>> M06c EXPERT: POPULISM BY PARTY E5020_A >>> M06c.a EXPERT: POPULISM SCALE - PARTY A E5020_B >>> M06c.b EXPERT: POPULISM SCALE - PARTY B E5020_C >>> M06c.c EXPERT: POPULISM SCALE - PARTY C E5020_D >>> M06c.d EXPERT: POPULISM SCALE - PARTY D E5020_E >>> M06c.e EXPERT: POPULISM SCALE - PARTY E E5020_F >>> M06c.f EXPERT: POPULISM SCALE - PARTY F E5020_G >>> M06c.g EXPERT: POPULISM SCALE - PARTY G E5020_H >>> M06c.h EXPERT: POPULISM SCALE - PARTY H E5020_I >>> M06c.i EXPERT: POPULISM SCALE - PARTY I E5021_1 >>> M07.1 MOST SALIENT FACTORS IN ELECTION - 1ST E5021_2 >>> M07.2 MOST SALIENT FACTORS IN ELECTION - 2ND E5021_3 >>> M07.3 MOST SALIENT FACTORS IN ELECTION - 3RD E5021_4 >>> M07.4 MOST SALIENT FACTORS IN ELECTION - 4TH E5021_5 >>> M07.5 MOST SALIENT FACTORS IN ELECTION - 5TH E5022 >>> M08a FAIRNESS OF THE ELECTION E5023 >>> M08b FORMAL COMPLAINTS AGAINST NATIONAL LEVEL RESULTS E5024 >>> M08c ELECTION IRREGULARITIES REPORTED E5025_1 >>> M08d DATE ELECTION SCHEDULED - MONTH E5025_2 >>> M08d DATE ELECTION SCHEDULED - DAY E5025_3 >>> M08d DATE ELECTION SCHEDULED - YEAR E5026_1 >>> M08e DATE ELECTION HELD - MONTH E5026_2 >>> M08e DATE ELECTION HELD - DAY E5026_3 >>> M08e DATE ELECTION HELD - YEAR E5026_W >>> DATE ELECTION HELD - TIMING E5026_S >>> DATE ELECTION HELD - SEASON E5027 >>> M08e ELECTION DATE IRREGULARITIES E5028 >>> M09a ELECTION VIOLENCE E5029 >>> M09b GEOGRAPHIC CONCENTRATION OF VIOLENCE E5030 >>> M09c POST-ELECTION VIOLENCE E5031 >>> M09d POST-ELECTION PROTEST E5032 >>> M10a ELECTORAL ALLIANCES PERMITTED IN ELECTION E5033 >>> M10b ELECTORAL ALLIANCES IN PRACTICE E5034 >>> M10c DID ANY ELECTORAL ALLIANCES FORM? E5035 >>> M11 REQUIREMENTS FOR JOINT PARTY LISTS E5036 >>> M12a THE POSSIBILITY OF APPARENTEMENT E5037 >>> M12b TYPES OF APPARENTEMENT AGREEMENTS E5038 >>> M13a MULTI-PARTY ENDORSEMENTS E5039 >>> M13b MULTI-PARTY ENDORSEMENTS ON BALLOT E5040_1 >>> M15a VOTES CAST - LOWER - 1ST SEGMENT (TIER) E5040_2 >>> M15a VOTES CAST - LOWER - 2ND SEGMENT (TIER) E5040_3 >>> M15a VOTES CAST - UPPER - 1ST SEGMENT (TIER) E5040_4 >>> M15a VOTES CAST - UPPER - 2ND SEGMENT (TIER) E5041_1 >>> M15b VOTING PROCEDURE - LOWER - 1ST SEGMENT (TIER) E5041_2 >>> M15b VOTING PROCEDURE - LOWER - 2ND SEGMENT (TIER) E5041_3 >>> M15b VOTING PROCEDURE - UPPER - 1ST SEGMENT (TIER) E5041_4 >>> M15b VOTING PROCEDURE - UPPER - 2ND SEGMENT (TIER) E5042_1 >>> M15c VOTING ROUNDS - LOWER - 1ST SEGMENT (TIER) E5042_2 >>> M15c VOTING ROUNDS - LOWER - 2ND SEGMENT (TIER) E5042_3 >>> M15c VOTING ROUNDS - UPPER - 1ST SEGMENT (TIER) E5042_4 >>> M15c VOTING ROUNDS - UPPER - 2ND SEGMENT (TIER) E5043_1 >>> M15d PARTY LISTS - LOWER - 1ST SEGMENT (TIER) E5043_2 >>> M15d PARTY LISTS - LOWER - 2ND SEGMENT (TIER) E5043_3 >>> M15d PARTY LISTS - UPPER - 1ST SEGMENT (TIER) E5043_4 >>> M15d PARTY LISTS - UPPER - 2ND SEGMENT (TIER) E5044_1 >>> M16 TRANSFERABLE VOTES - LOWER - 1ST SEGMENT (TIER) E5044_2 >>> M16 TRANSFERABLE VOTES - LOWER - 2ND SEGMENT (TIER) E5044_3 >>> M16 TRANSFERABLE VOTES - UPPER - 1ST SEGMENT (TIER) E5044_4 >>> M16 TRANSFERABLE VOTES - UPPER - 2ND SEGMENT (TIER) E5045_1 >>> M17 CUMULATED VOTES - LOWER - 1ST SEGMENT (TIER) E5045_2 >>> M17 CUMULATED VOTES - LOWER - 2ND SEGMENT (TIER) E5045_3 >>> M17 CUMULATED VOTES - UPPER - 1ST SEGMENT (TIER) E5045_4 >>> M17 CUMULATED VOTES - UPPER - 2ND SEGMENT (TIER) E5046_1 >>> M18 COMPULSORY VOTING - LOWER - 1ST SEGMENT (TIER) E5046_2 >>> M18 COMPULSORY VOTING - LOWER - 2ND SEGMENT (TIER) E5046_3 >>> M18 COMPULSORY VOTING - UPPER - 1ST SEGMENT (TIER) E5046_4 >>> M18 COMPULSORY VOTING - UPPER - 2ND SEGMENT (TIER) E5047_1 >>> M20a IS THERE PARTY THRESHOLD - LOWER - 1ST SEGMENT (TIER) E5047_2 >>> M20a IS THERE PARTY THRESHOLD - LOWER - 2ND SEGMENT (TIER) E5047_3 >>> M20a IS THERE PARTY THRESHOLD - UPPER - 1ST SEGMENT (TIER) E5047_4 >>> M20a IS THERE PARTY THRESHOLD - UPPER - 2ND SEGMENT (TIER) E5048_1 >>> M20b PARTY THRESHOLD - LOWER - 1ST SEGMENT (TIER) E5048_2 >>> M20b PARTY THRESHOLD - LOWER - 2ND SEGMENT (TIER) E5048_3 >>> M20b PARTY THRESHOLD - UPPER - 1ST SEGMENT (TIER) E5048_4 >>> M20b PARTY THRESHOLD - UPPER - 2ND SEGMENT (TIER) E5049_1 >>> M20c UNIT FOR THE THRESHOLD - LOWER - 1ST SEGMENT (TIER) E5049_2 >>> M20c UNIT FOR THE THRESHOLD - LOWER - 2ND SEGMENT (TIER) E5049_3 >>> M20c UNIT FOR THE THRESHOLD - UPPER - 1ST SEGMENT (TIER) E5049_4 >>> M20c UNIT FOR THE THRESHOLD - UPPER - 2ND SEGMENT (TIER) E5050 >>> AGE OF THE CURRENT REGIME E5051 >>> REGIME: TYPE OF EXECUTIVE E5052 >>> NUMBER OF MONTHS SINCE LAST LOWER HOUSE ELECTION E5053 >>> NUMBER OF MONTHS SINCE LAST PRESIDENTIAL ELECTION E5054 >>> PRESIDENTIAL ELECTIONS ELECTORAL FORMULA E5055 >>> ELECTORAL FORMULA IN ALL ELECTORAL SEGMENTS (TIERS) E5056 >>> NUMBER OF ELECTORAL SEGMENTS (TIERS) E5057 >>> LINKED ELECTORAL SEGMENTS (TIERS) E5058 >>> DEPENDENT FORMULAE IN MIXED SYSTEMS E5059 >>> SUBTYPES OF MIXED ELECTORAL SYSTEMS E5060 >>> NUMBER OF ELECTORAL DISTRICTS - LOWEST SEGMENT (TIER) - LOWER HOUSE E5061 >>> AVERAGE DISTRICT MAGNITUDE - LOWEST SEGMENT (TIER) - LOWER HOUSE E5062 >>> ELECTORAL FORMULA - LOWEST SEGMENT (TIER) - LOWER HOUSE E5063 >>> NUMBER OF ELECTORAL DISTRICTS - SECOND SEGMENT (TIER) - LOWER HOUSE E5064 >>> AVERAGE DISTRICT MAGNITUDE - SECOND SEGMENT (TIER) - LOWER HOUSE E5065 >>> ELECTORAL FORMULA - SECOND SEGMENT (TIER) - LOWER HOUSE E5066 >>> NUMBER OF ELECTORAL DISTRICTS - THIRD SEGMENT (TIER) - LOWER HOUSE E5067 >>> AVERAGE DISTRICT MAGNITUDE - THIRD SEGMENT (TIER) - LOWER HOUSE E5068 >>> ELECTORAL FORMULA - THIRD SEGMENT (TIER) - LOWER HOUSE E5069 >>> NUMBER OF SEATS ABOVE THE FIRST SEGMENT (TIER) - LOWER HOUSE E5070 >>> PERCENTAGE OF SEATS ABOVE THE FIRST SEGMENT (TIER) - LOWER HOUSE E5071 >>> FUSED VOTE E5072 >>> SIZE OF THE LOWER HOUSE E5073 >>> CONSTITUTIONAL FEDERAL STRUCTURE E5074 >>> NUMBER OF LEGISLATIVE CHAMBERS E5075 >>> PERCENTAGE OF WOMEN IN PARLIAMENT E5076_1 >>> PARTY FUNDING: DIRECT PUBLIC FUNDING E5076_2 >>> PARTY FUNDING: INDIRECT PUBLIC FUNDING E5077 >>> NUMBER OF PARTIES PARTICIPATING IN ELECTION E5078 >>> EFFECTIVE NUMBER OF ELECTORAL PARTIES E5079 >>> CORRECTED EFFECTIVE NUMBER OF ELECTORAL PARTIES E5080 >>> EFFECTIVE NUMBER OF PARLIAMENTARY PARTIES E5081 >>> CORRECTED EFFECTIVE NUMBER OF PARLIAMENTARY PARTIES E5082_1 >>> DIRECT DEMOCRACY: REFERENDUM MANDATORY E5082_2 >>> DIRECT DEMOCRACY: REFERENDUM OPTIONAL E5082_3 >>> DIRECT DEMOCRACY: REFERENDUMS BY CITIZEN INITIATIVE E5082_4 >>> DIRECT DEMOCRACY: REFERENDUM RESULT BINDING OR CONSULTATIVE III. OTHER MACRO-LEVEL DATA E5083_1 >>> COVID-19 PANDEMIC - CUMULATIVE N INFECTIONS - TIME T-4 DAYS E5083_2 >>> COVID-19 PANDEMIC - CUMULATIVE N INFECTIONS - TIME T-7 DAYS E5083_3 >>> COVID-19 PANDEMIC - CUMULATIVE N INFECTIONS - TIME T-14 DAYS E5083_4 >>> COVID-19 PANDEMIC - CUMULATIVE N INFECTIONS - TIME T-28 DAYS E5083_5 >>> COVID-19 PANDEMIC - CUMULATIVE N INFECTIONS - TIME T-91 DAYS E5084_1 >>> COVID-19 PANDEMIC - CUMULATIVE N DEATHS - TIME T-4 DAYS E5084_2 >>> COVID-19 PANDEMIC - CUMULATIVE N DEATHS - TIME T-7 DAYS E5084_3 >>> COVID-19 PANDEMIC - CUMULATIVE N DEATHS - TIME T-14 DAYS E5084_4 >>> COVID-19 PANDEMIC - CUMULATIVE N DEATHS - TIME T-28 DAYS E5084_5 >>> COVID-19 PANDEMIC - CUMULATIVE N DEATHS - TIME T-91 DAYS E5085_1 >>> COVID-19 PANDEMIC - REPRODUCTION RATE - TIME T-4 DAYS E5085_2 >>> COVID-19 PANDEMIC - REPRODUCTION RATE - TIME T-7 DAYS E5085_3 >>> COVID-19 PANDEMIC - REPRODUCTION RATE - TIME T-14 DAYS E5085_4 >>> COVID-19 PANDEMIC - REPRODUCTION RATE - TIME T-28 DAYS E5085_5 >>> COVID-19 PANDEMIC - REPRODUCTION RATE - TIME T-91 DAYS E5090_1 >>> FREEDOM HOUSE RATING - TIME T E5090_2 >>> FREEDOM HOUSE RATING - TIME T-1 E5090_3 >>> FREEDOM HOUSE RATING - TIME T-2 E5091_1 >>> DEMOCRACY-AUTOCRACY - POLITY IV RATING - TIME T E5091_2 >>> DEMOCRACY-AUTOCRACY - POLITY IV RATING - TIME T-1 E5091_3 >>> DEMOCRACY-AUTOCRACY - POLITY IV RATING - TIME T-2 E5092 >>> GINI COEFFICIENT OF EQUALIZED DISPOSABLE INCOME - (YEAR CLOSEST TO ELECTION YEAR AVAILABLE) E5093_1 >>> GDP GROWTH - ANNUAL % (WORLD BANK) - TIME T E5093_2 >>> GDP GROWTH - ANNUAL % (WORLD BANK) - TIME T-1 E5093_3 >>> GDP GROWTH - ANNUAL % (WORLD BANK) - TIME T-2 E5094_1 >>> GDP PER CAPITA, PPP (WORLD BANK) - TIME T E5094_2 >>> GDP PER CAPITA, PPP (WORLD BANK) - TIME T-1 E5094_3 >>> GDP PER CAPITA, PPP (WORLD BANK) - TIME T-2 E5095_1 >>> INFLATION, GDP DEFLATOR (ANNUAL %) (WORLD BANK) - TIME T E5095_2 >>> INFLATION, GDP DEFLATOR (ANNUAL %) (WORLD BANK) - TIME T-1 E5095_3 >>> INFLATION, GDP DEFLATOR (ANNUAL %) (WORLD BANK) - TIME T-2 E5096_1 >>> CENTRAL GOVERNMENT DEBT, TOTAL (% GDP) TIME T E5096_2 >>> CENTRAL GOVERNMENT DEBT, TOTAL (% GDP) TIME T-1 E5096_3 >>> CENTRAL GOVERNMENT DEBT, TOTAL (% GDP) TIME T-2 E5097_1 >>> HUMAN DEVELOPMENT INDEX (UNPD) - TIME T E5097_2 >>> HUMAN DEVELOPMENT INDEX (UNPD) - TIME T-1 E5097_3 >>> HUMAN DEVELOPMENT INDEX (UNPD) - TIME T-2 E5098_1 >>> POPULATION, TOTAL (WORLD BANK) - TIME T E5098_2 >>> POPULATION, TOTAL (WORLD BANK) - TIME T-1 E5098_3 >>> POPULATION, TOTAL (WORLD BANK) - TIME T-2 E5099_1 >>> UNEMPLOYMENT, TOTAL (WORLD BANK) - TIME T E5099_2 >>> UNEMPLOYMENT, TOTAL (WORLD BANK) - TIME T-1 E5099_3 >>> UNEMPLOYMENT, TOTAL (WORLD BANK) - TIME T-2 E5100_1 >>> UNEMPLOYMENT, TOTAL FOR PEOPLE AGED 15-24 YEARS (WORLD BANK) - TIME T E5100_2 >>> UNEMPLOYMENT, TOTAL FOR PEOPLE AGED 15-24 YEARS (WORLD BANK) - TIME T-1 E5100_3 >>> UNEMPLOYMENT, TOTAL FOR PEOPLE AGED 15-24 YEARS (WORLD BANK) - TIME T-2 E5101 >>> COUNTRY SUBJECT TO IMF CONDITIONALITY AT ELECTION E5102 >>> TI CORRUPTION PERCEPTION INDEX E5103_1 >>> CONTROL OF CORRUPTION INDEX - TIME T E5103_1se >>> CONTROL OF CORRUPTION INDEX - TIME T STANDARD ERROR E5103_2 >>> CONTROL OF CORRUPTION INDEX - TIME T-1 E5103_2se >>> CONTROL OF CORRUPTION INDEX - TIME T-1 STANDARD ERROR E5103_3 >>> CONTROL OF CORRUPTION INDEX - TIME T-2 E5103_3se >>> CONTROL OF CORRUPTION INDEX - TIME T-2 STANDARD ERROR E5104_1 >>> QOG EXPERT JUDGEMENT OF PUBLIC SECTOR: FIRMS PROVIDE KICKBACKS TO PUBLIC SERVANTS E5104_2 >>> QOG EXPERT JUDGEMENT OF PUBLIC SECTOR: PUBLIC SECTOR EMPLOYEES AND HOW THEY TREAT SOCIETY E5104_3 >>> QOG EXPERT JUDGEMENT OF PUBLIC SECTOR: TREAT CASES IMPARTIALLY E5104_4 >>> QOG EXPERT JUDGEMENT OF PUBLIC SECTOR: STRIVE TO FOLLOW RULES E5105_1 >>> NET MIGRATION RATE 2000-2005 E5105_2 >>> NET MIGRATION RATE 2005-2010 E5105_3 >>> NET MIGRATION RATE 2010-2015 E5105_4 >>> NET MIGRATION RATE 2015-2020 E5106_1 >>> POPULATION BY CITIZENSHIP: PERCENTAGE OF POPULATION WHO ARE CITIZENS E5106_2 >>> POPULATION BY CITIZENSHIP: PERCENTAGE OF POPULATION FOREIGN BORN/NOT CITIZEN E5106_3 >>> POPULATION BY CITIZENSHIP: PERCENTAGE OF POPULATION UNKNOWN CITIZENSHIP STATUS E5107 >>> LINGUISTIC FRACTIONALIZATION INDEX: ALESINA ET AL. 2003 E5108 >>> RELIGIOUS FRACTIONALIZATION INDEX: ALESINA ET AL. 2003 E5109 >>> ETHNIC FRACTIONALIZATION INDEX: ALESINA ET AL. 2003 E5110 >>> POLITY FRAGMENTATION INDEX E5111 >>> PERCENTAGE OF INDIVIDUALS USING THE INTERNET E5112 >>> MOBILE PHONE SUBSCRIPTIONS PER 100 INHABITANTS E5113 >>> FIXED TELEPHONE LINES PER 100 INHABITANTS IV. MACRO DATA: ADDITIONAL DATA BRIDGING VARIABLES E5200_A >>> MANIFESTO RESEARCH ON POLITICAL REPRESENTATION (MARPOR/CMP) IDENTIFIER - PARTY A E5200_B >>> MANIFESTO RESEARCH ON POLITICAL REPRESENTATION (MARPOR/CMP) IDENTIFIER - PARTY B E5200_C >>> MANIFESTO RESEARCH ON POLITICAL REPRESENTATION (MARPOR/CMP) IDENTIFIER - PARTY C E5200_D >>> MANIFESTO RESEARCH ON POLITICAL REPRESENTATION (MARPOR/CMP) IDENTIFIER - PARTY D E5200_E >>> MANIFESTO RESEARCH ON POLITICAL REPRESENTATION (MARPOR/CMP) IDENTIFIER - PARTY E E5200_F >>> MANIFESTO RESEARCH ON POLITICAL REPRESENTATION (MARPOR/CMP) IDENTIFIER - PARTY F E5200_G >>> MANIFESTO RESEARCH ON POLITICAL REPRESENTATION (MARPOR/CMP) IDENTIFIER - PARTY G E5200_H >>> MANIFESTO RESEARCH ON POLITICAL REPRESENTATION (MARPOR/CMP) IDENTIFIER - PARTY H E5200_I >>> MANIFESTO RESEARCH ON POLITICAL REPRESENTATION (MARPOR/CMP) IDENTIFIER - PARTY I E5201_A >>> PARLIAMENTS AND GOVERNMENT DATABASE (ParlGov) IDENTIFIER - PARTY A E5201_B >>> PARLIAMENTS AND GOVERNMENT DATABASE (ParlGov) IDENTIFIER - PARTY B E5201_C >>> PARLIAMENTS AND GOVERNMENT DATABASE (ParlGov) IDENTIFIER - PARTY C E5201_D >>> PARLIAMENTS AND GOVERNMENT DATABASE (ParlGov) IDENTIFIER - PARTY D E5201_E >>> PARLIAMENTS AND GOVERNMENT DATABASE (ParlGov) IDENTIFIER - PARTY E E5201_F >>> PARLIAMENTS AND GOVERNMENT DATABASE (ParlGov) IDENTIFIER - PARTY F E5201_G >>> PARLIAMENTS AND GOVERNMENT DATABASE (ParlGov) IDENTIFIER - PARTY G E5201_H >>> PARLIAMENTS AND GOVERNMENT DATABASE (ParlGov) IDENTIFIER - PARTY H E5201_I >>> PARLIAMENTS AND GOVERNMENT DATABASE (ParlGov) IDENTIFIER - PARTY I E5202_A >>> CHAPEL HILL EXPERT SURVEY (CHES) IDENTIFIER - PARTY A E5202_B >>> CHAPEL HILL EXPERT SURVEY (CHES) IDENTIFIER - PARTY B E5202_C >>> CHAPEL HILL EXPERT SURVEY (CHES) IDENTIFIER - PARTY C E5202_D >>> CHAPEL HILL EXPERT SURVEY (CHES) IDENTIFIER - PARTY D E5202_E >>> CHAPEL HILL EXPERT SURVEY (CHES) IDENTIFIER - PARTY E E5202_F >>> CHAPEL HILL EXPERT SURVEY (CHES) IDENTIFIER - PARTY F E5202_G >>> CHAPEL HILL EXPERT SURVEY (CHES) IDENTIFIER - PARTY G E5202_H >>> CHAPEL HILL EXPERT SURVEY (CHES) IDENTIFIER - PARTY H E5202_I >>> CHAPEL HILL EXPERT SURVEY (CHES) IDENTIFIER - PARTY I E5203_A >>> PARTY FACTS IDENTIFIER - PARTY A E5203_B >>> PARTY FACTS IDENTIFIER - PARTY B E5203_C >>> PARTY FACTS IDENTIFIER - PARTY C E5203_D >>> PARTY FACTS IDENTIFIER - PARTY D E5203_E >>> PARTY FACTS IDENTIFIER - PARTY E E5203_F >>> PARTY FACTS IDENTIFIER - PARTY F E5203_G >>> PARTY FACTS IDENTIFIER - PARTY G E5203_H >>> PARTY FACTS IDENTIFIER - PARTY H E5203_I >>> PARTY FACTS IDENTIFIER - PARTY I ))) CSES MODULE 5 VARIABLES: DATA BRIDGING WITH CSES PRODUCTS E6000_PR_1 >>> IMD BRIDGING VARIABLE: CURRENT PRESIDENTIAL ELECTION: VOTE CHOICE - 1ST ROUND E6000_PR_2 >>> IMD BRIDGING VARIABLE: CURRENT PRESIDENTIAL ELECTION: VOTE CHOICE - 2ND ROUND E6000_LH_PL >>> IMD BRIDGING VARIABLE: CURRENT LOWER HOUSE ELECTION: VOTE CHOICE: PARTY LIST E6000_LH_DC >>> IMD BRIDGING VARIABLE: CURRENT LOWER HOUSE ELECTION: VOTE CHOICE: DISTRICT CANDIDATE =========================================================================== ))) CSES MODULE 5 VARIABLES: IDENTIFICATION, WEIGHT, AND STUDY ADMINISTRATION DATA =========================================================================== --------------------------------------------------------------------------- E1001 >>> DATASET --------------------------------------------------------------------------- Dataset. .................................................................. CSES-MODULE-5. CSES MODULE 5 | VARIABLE NOTES: E1001 | | E1001 details the CSES Module administered by each election | study. CSES MODULE 5 was intended to be administered during the | years 2016 and 2021, inclusive. One study was administered in | 2015 using the pilot questionnaire as part of the CSES MODULE 5 | pre-tests (see Variables E1008 & E1037). --------------------------------------------------------------------------- E1002_VER >>> DATASET VERSION --------------------------------------------------------------------------- Dataset version. .................................................................. VER2023-JUL-25. Dataset version released on July 25, 2023. | VARIABLE NOTES: E1002_VER | | E1002_VER reports the version date (i.e., the release date) of | the CSES MODULE 5 dataset. --------------------------------------------------------------------------- E1002_DOI >>> DIGITAL OBJECT IDENTIFIER --------------------------------------------------------------------------- Dataset version: Digital Object Identifier (DOI). .................................................................. doi: 10.7804/cses.module5.2023-07-25. | VARIABLE NOTES: E1002_DOI | | E1002_DOI reports the Digital Object Identifier (DOI) which is | registered for the CSES MODULE 5. CSES DOI registration is with | the DA|RA registration agency for economic and social science | data. Each CSES MODULE 5 dataset version (see Variable E1002_VER) | has a unique, persistent DOI. --------------------------------------------------------------------------- E1003 >>> ID VARIABLE - ELECTION STUDY (NUMERIC POLITY) --------------------------------------------------------------------------- Election Study Identifier: Numeric Polity Code & Election Year. .................................................................. 00802017. ALBANIA (2017) 03602019. AUSTRALIA (2019) 04002017. AUSTRIA (2017) 05612019. BELGIUM-FLANDERS (2019) 05622019. BELGIUM-WALLONIA (2019) 07602018. BRAZIL (2018) 12402019. CANADA (2019) 15202017. CHILE (2017) 18802018. COSTA RICA (2018) 20302017. CZECHIA (2017) 20302021. CZECHIA (2021) 20802019. DENMARK (2019) 22202019. EL SALVADOR (2019) 24602019. FINLAND (2019) 25002017. FRANCE (2017) 27602017. GERMANY (2017) 27602021. GERMANY (2021) 82602017. GREAT BRITAIN (2017) 82602019. GREAT BRITAIN (2019) 30002015. GREECE (2015) 30002019. GREECE (2019) 34402016. HONG KONG (2016) 34802018. HUNGARY (2018) 35202016. ICELAND (2016) 35202017. ICELAND (2017) 35602019. INDIA (2019) 37202016. IRELAND (2016) 37602020. ISRAEL (2020) 38002018. ITALY (2018) 39202017. JAPAN (2017) 42802018. LATVIA (2018) 44002016. LITHUANIA (2016) 44002020. LITHUANIA (2020) 48402018. MEXICO (2018) 49902016. MONTENEGRO (2016) 52802017. NETHERLANDS (2017) 52802021. NETHERLANDS (2021) 55402017. NEW ZEALAND (2017) 55402020. NEW ZEALAND (2020) 57802017. NORWAY (2017) 60402021. PERU (2021) 61602019. POLAND (2019) 62002019. PORTUGAL (2019) 64202016. ROMANIA (2016) 70302020. SLOVAKIA (2020) 41002016. SOUTH KOREA (2016) 75202018. SWEDEN (2018) 75602019. SWITZERLAND (2019) 15802016. TAIWAN (2016) 15802020. TAIWAN (2020) 76402019. THAILAND (2019) 78802019. TUNISIA (2019) 79202018. TURKEY (2018) 84002016. UNITED STATES (2016) 84002020. UNITED STATES (2020) 85802019. URUGUAY (2019) | VARIABLE NOTES: E1003 | | E1003 is an eight-digit numeric variable that identifies an | election study within CSES MODULE 5. The variable is constructed | from two components, namely: Variable E1006_UN (UN ISO_3166-1 | numeric polity code) and Variable E1008 (election year). | | The first three digits are the numeric version of the country | codes created by the United Nations Statistics Division as | specified in variable E1006_UN. | The fourth digit distinguishes between multiple studies | conducted within a single country, for the same election. | The fifth through eighth digits correspond to the election year | as specified in variable E1008. --------------------------------------------------------------------------- E1004 >>> ID VARIABLE - ELECTION STUDY (POLITY ALPHABETIC AND YEAR OF ELECTION) --------------------------------------------------------------------------- Election Study Identifier: Alphabetic Polity Code & Election Year. .................................................................. ALB_2017. ALBANIA (2017) AUS_2019. AUSTRALIA (2019) AUT_2017. AUSTRIA (2017) BELF2019. BELGIUM-FLANDERS (2019) BELW2019. BELGIUM-WALLONIA (2019) BRA_2018. BRAZIL (2018) CAN_2019. CANADA (2019) CHL_2017. CHILE (2017) CRI_2018. COSTA RICA (2018) CZE_2017. CZECHIA (2017) CZE_2021. CZECHIA (2021) DNK_2019. DENMARK (2019) SLV_2019. EL SALVADOR (2019) FIN_2019. FINLAND (2019) FRA_2017. FRANCE (2017) DEU_2017. GERMANY (2017) DEU_2021. GERMANY (2021) GBR_2017. GREAT BRITAIN (2017) GBR_2019. GREAT BRITAIN (2019) GRC_2015. GREECE (2015) GRC_2019. GREECE (2019) HKG_2016. HONG KONG (2016) HUN_2018. HUNGARY (2018) ISL_2016. ICELAND (2016) ISL_2017. ICELAND (2017) IND_2019. INDIA (2019) IRL_2016. IRELAND (2016) ISR_2020. ISRAEL (2020) ITA_2018. ITALY (2018) JPN_2017. JAPAN (2017) LVA_2018. LATVIA (2018) LTU_2016. LITHUANIA (2016) LTU_2020. LITHUANIA (2020) MEX_2018. MEXICO (2018) MNE_2016. MONTENEGRO (2016) NLD_2017. NETHERLANDS (2017) NLD_2021. NETHERLANDS (2021) NZL_2017. NEW ZEALAND (2017) NZL_2020. NEW ZEALAND (2020) NOR_2017. NORWAY (2017) PER_2021. PERU (2021) POL_2019. POLAND (2019) PRT_2019. PORTUGAL (2019) ROU_2016. ROMANIA (2016) SVK_2020. SLOVAKIA (2020) KOR_2016. SOUTH KOREA (2016) SWE_2018. SWEDEN (2018) CHE_2019. SWITZERLAND (2019) TWN_2016. TAIWAN (2016) TWN_2020. TAIWAN (2020) THA_2019. THAILAND (2019) TUN_2019. TUNISIA (2019) TUR_2018. TURKEY (2018) USA_2016. UNITED STATES (2016) USA_2020. UNITED STATES (2020) URY_2019. URUGUAY (2019) | VARIABLE NOTES: E1004 | | E1004 is an eight-character variable that identifies an | election study within CSES MODULE 5. The variable is constructed | from two components, namely: Variable E1006_UNALPHA3 (Polity | alphabetical three letter code) and E1008 (election year). | | The first three characters are the alphabetic country codes | 'alpha-3' created by the International Organization for | Standardization in their ISO 3166 Standard and shared by the | United Nations Statistics Division (see Variable E1006_UNALPHA3). | If appropriate, the fourth character distinguishes between | multiple studies conducted within a single country, for the same | election. If only one study is in place for the election, this | character appears as an underscore (_). | | The fifth through eighth characters correspond to the election | year as specified in Variable E1008. --------------------------------------------------------------------------- E1005 >>> ID VARIABLE - RESPONDENT --------------------------------------------------------------------------- Respondent Identifier. .................................................................. | VARIABLE NOTES: E1005 | | E1005 is an eighteen character variable uniquely identifying a | respondent within CSES MODULE 5. | The variable is constructed from three components: variable | E1006 (CSES polity code), E1008 (election year), and E1009 | (respondent within election study). | | The first three characters are the numeric version of the | country codes created by the United Nations Statistics | Division ("countries or areas, codes and abbreviations", | revised February 13, 2002). | If appropriate, the fourth character distinguishes between | multiple studies conducted within a single country, for the same | election. If only one study is in place for the election, this | character appears as a zero (0). | | The fifth through eighth characters correspond to the election | year as specified in variable E1008. | | The last ten characters are the respondent identifier from E1009, | which is unique within each election study. | ELECTION STUDY NOTES - JAPAN (2017): E1005 | | Respondent identifiers are originally composed of three | variables: Branch (2 digits), Point (3 digits), & RID (2 digits). | The value of Branch starts from "00", Point starts from "000", | and RID begins from "00." Consequently, there is one respondent | with a respondent ID composed of all zeros. --------------------------------------------------------------------------- E1006 >>> ID COMPONENT - POLITY CSES CODE --------------------------------------------------------------------------- Polity Identifier. .................................................................. 0080. ALBANIA 0360. AUSTRALIA 0400. AUSTRIA 0561. BELGIUM-FLANDERS 0562. BELGIUM-WALLONIA 0760. BRAZIL 1240. CANADA 1520. CHILE 1880. COSTA RICA 2030. CZECHIA 2080. DENMARK 2220. EL SALVADOR 2460. FINLAND 2500. FRANCE 2760. GERMANY 8260. GREAT BRITAIN 3000. GREECE 3440. HONG KONG 3480. HUNGARY 3520. ICELAND 3560. INDIA 3720. IRELAND 3760. ISRAEL 3800. ITALY 3920. JAPAN 4280. LATVIA 4400. LITHUANIA 4840. MEXICO 4990. MONTENEGRO 5280. NETHERLANDS 5540. NEW ZEALAND 5780. NORWAY 6040. PERU 6160. POLAND 6200. PORTUGAL 6420. ROMANIA 7030. SLOVAKIA 4100. SOUTH KOREA 7520. SWEDEN 7560. SWITZERLAND 1580. TAIWAN 7640. THAILAND 7880. TUNISIA 7920. TURKEY 8400. UNITED STATES 8580. URUGUAY | VARIABLE NOTES: E1006 | | E1006 is a four-digit variable that identifies a polity that has | a study in CSES MODULE 5. The variable is constructed in part | from Variable E1006_UN (UN ISO_3166-1 numeric polity code) and an | additional classification added by CSES. | | The first three characters are the numeric version of | the polity codes created by the United Nations Statistics | Division ("countries or areas, codes and abbreviations", | revised February 13, 2002). | The fourth character distinguishes between multiple studies | conducted with a single country, for the same election. | | Polities above are listed in alphabetical order. --------------------------------------------------------------------------- E1006_UN >>> ID COMPONENT - POLITY UN ISO_3166-1 NUMERIC CODE --------------------------------------------------------------------------- Polity Identifier UN Country Code. .................................................................. 008. ALBANIA 036. AUSTRALIA 040. AUSTRIA 056. BELGIUM 076. BRAZIL 124. CANADA 152. CHILE 188. COSTA RICA 203. CZECHIA 208. DENMARK 222. EL SALVADOR 246. FINLAND 250. FRANCE 276. GERMANY 826. GREAT BRITAIN 300. GREECE 344. HONG KONG 348. HUNGARY 352. ICELAND 356. INDIA 372. IRELAND 376. ISRAEL 380. ITALY 392. JAPAN 428. LATVIA 440. LITHUANIA 484. MEXICO 499. MONTENEGRO 528. NETHERLANDS 554. NEW ZEALAND 578. NORWAY 604. PERU 616. POLAND 620. PORTUGAL 642. ROMANIA 703. SLOVAKIA 410. SOUTH KOREA 752. SWEDEN 756. SWITZERLAND 158. TAIWAN 764. THAILAND 788. TUNISIA 792. TURKEY 840. UNITED STATES 858. URUGUAY | VARIABLE NOTES: E1006_UN | | POTENTIAL POLITY LEVEL BRIDGING IDENTIFIER | | E1006_UN is a three-digit numeric variable identifying a polity | conducting an election study present in CSES MODULE 5. | | It consists of the numeric version of the country codes created | by the United Nations Statistics Division ("Countries or areas, | codes and abbreviations", revised February 13, 2002). | | Polities above are listed in alphabetical order. --------------------------------------------------------------------------- E1006_UNALPHA2 >>> ID COMPONENT - POLITY UN ISO_3166-1 ALPHABETIC TWO LETTER CODE --------------------------------------------------------------------------- United Nations (UN) ISO Alpha-2 country codes. .................................................................. AL. Albania AT. Austria AU. Australia BE. Belgium BR. Brazil CA. Canada CH. Switzerland CL. Chile CR. Costa Rica CZ. Czechia DE. Germany DK. Denmark FI. Finland FR. France GB. Great Britain GR. Greece HK. Hong Kong HU. Hungary IE. Ireland IL. Israel IN. India IS. Iceland IT. Italy JP. Japan KR. Republic of Korea LT. Lithuania LV. Latvia ME. Montenegro MX. Mexico NL. Netherlands NO. Norway NZ. New Zealand PE. Peru PL. Poland PT. Portugal RO. Romania SE. Sweden SK. Slovakia SV. El Salvador TH. Thailand TN. Tunisia TR. Turkey TW. Taiwan US. United States of America UY. Uruguay | VARIABLE NOTES: E1006_UNALPHA2 | | POTENTIAL POLITY LEVEL BRIDGING IDENTIFIER | | E1006_UNALPHA2 is a two-character variable identifying a polity | conducting an election study present in CSES MODULE 5. | | E1006_UNALPHA2 provides alphabetic country codes 'alpha-2' | created by the International Organization for Standardization | in their ISO 3166 Standard and shared by the United Nations | Statistics Division ("Countries or areas, codes and | abbreviations", revised February 13, 2002). | | Source of data: https://www.iso.org/obp/ui/#search | (Date accessed: September 01, 2020). | | Polities above are listed in alphabetical order. --------------------------------------------------------------------------- E1006_UNALPHA3 >>> ID COMPONENT - POLITY UN ISO_3166-1 ALPHABETIC THREE LETTER CODE --------------------------------------------------------------------------- United Nations (UN) ISO Alpha-3 country codes. .................................................................. ALB. Albania AUS. Australia AUT. Austria BEL. Belgium BRA. Brazil CAN. Canada CHE. Switzerland CHL. Chile CRI. Costa Rica CZE. Czechia DEU. Germany DNK. Denmark FIN. Finland FRA. France GBR. Great Britain GRC. Greece HKG. Hong Kong HUN. Hungary IND. India IRL. Ireland ISL. Iceland ISR. Israel ITA. Italy JPN. Japan KOR. South Korea LTU. Lithuania LVA. Latvia MEX. Mexico MNE. Montenegro NLD. Netherlands NOR. Norway NZL. New Zealand PER. Peru POL. Poland PRT. Portugal ROU. Romania SLV. El Salvador SVK. Slovakia SWE. Sweden THA. Thailand TUN. Tunisia TUR. Turkey TWN. Taiwan URY. Uruguay USA. United States | VARIABLE NOTES: E1006_UNALPHA3 | | POTENTIAL POLITY LEVEL BRIDGING IDENTIFIER | | E1006_UNALPHA3 is a three-character variable identifying a polity | conducting an election study present in CSES MODULE 5. | | E1006_UNALPHA3 provides alphabetic country codes 'alpha-3' | created by the International Organization for Standardization | in their ISO 3166 Standard and shared by the United Nations | Statistics Division ("Countries or areas, codes and | abbreviations", revised February 13, 2002). | | Source of data: https://www.iso.org/obp/ui/#search | (Date accessed: September 01, 2020). | | Polities are listed in alphabetical order. --------------------------------------------------------------------------- E1006_NAM >>> ID COMPONENT - POLITY NAME --------------------------------------------------------------------------- Polity Identifier Country Name. .................................................................. Albania Australia Austria Belgium Brazil Canada Chile Costa Rica Czechia Denmark El Salvador Finland France Germany Great Britain Greece Hong Kong Hungary Iceland India Ireland Israel Italy Japan Latvia Lithuania Mexico Montenegro Netherlands New Zealand Norway Peru Poland Portugal Republic of Korea Romania Slovakia Sweden Switzerland Taiwan Thailand Tunisia Turkey United States of America Uruguay | VARIABLE NOTES: E1006_NAM | | POTENTIAL POLITY LEVEL BRIDGING IDENTIFIER | | E1006_NAM is a string variable identifying a polity conducting | an election study present in CSES MODULE 5. | | E1006_NAM consists of polity names based on those principally | used by the United Nations Statistics Division ("Countries or | areas, codes and abbreviations", revised February 13, 2002). | However, in some instances, polity names deviate from those used | by the United Nations. | | Polities above are listed in alphabetical order. | ELECTION STUDY NOTES - CZECHIA (2017 & 2021): E1006_NAM | | In July 2016, the Czech government officially changed the | polity's name from Czech Republic to Czechia. | ELECTION STUDY NOTES - TURKEY (2018): E1006_NAM | | In 2022, the Turkish government officially changed the polity's | name from Turkey to Tuerkiye. But CSES uses the name of a polity | as of the election date (in Turkey's case 2018). Hence, this | nomenclature is used for CSES MODULE 5. --------------------------------------------------------------------------- E1006_REG >>> ID COMPONENT - POLITY UN GEOGRAPHIC REGIONS NUMERIC CODES --------------------------------------------------------------------------- Geographic region of polity .................................................................. AFRICA 014. EASTERN AFRICA 015. NORTHERN AFRICA 018. SOUTHERN AFRICA AMERICAS 005. SOUTH AMERICA 013. CENTRAL AMERICA 021. NORTHERN AMERICA ASIA 030. EASTERN ASIA 035. SOUTH EASTERN ASIA 143. CENTRAL ASIA 145. WESTERN ASIA EUROPE 039. SOUTHERN EUROPE 151. EASTERN EUROPE 154. NORTHERN EUROPE 155. WESTERN EUROPE 009. OCEANIA | VARIABLE NOTES: E1006_REG | | POTENTIAL REGIONAL LEVEL BRIDGING IDENTIFIER | | E1006_REG is a numeric variable identifying the gepgraphic | region of a polity conducting an election study present in CSES | MODULE 5. | | E1006_REG provides the geographical region codes applied by the | United Nations Statistics Division. The geographic regions are | based on continental regions which are further subdivided. | | Source of data: https://unstats.un.org/unsd/methodology/m49/ | (Date accessed: February 11, 2020). | ELECTION STUDY NOTES - TAIWAN (2016 & 2020): E1006_REG | | Taiwan is not included in UN classification. The polity has | been classified as "030. EASTERN ASIA". --------------------------------------------------------------------------- E1006_OECD >>> ID COMPONENT - POLITY MEMBER OF OECD --------------------------------------------------------------------------- Polity a member of the Organization for Economic Cooperation and Development (OECD) at the time of the election. .................................................................. 0. POLITY NOT A MEMBER OF OECD AT THE TIME OF ELECTION 1. POLITY A MEMBER OF OECD AT THE TIME OF ELECTION | VARIABLE NOTES: E1006_OECD | | The Organization for Economic Cooperation and Development (OECD) | is an intergovernmental economic organization founded in 1961 to | stimulate economic progress and world trade. | | Source of data: www.oecd.org | Date accessed: February 10, 2020 | ELECTION STUDY NOTES - LITHUANIA (2016 & 2020): E1006_OECD | | Lithuania joined the OECD on July 5, 2018. Consequently, for the | Lithuanian 2016 study is coded "0. Polity not a member of OECD | at the time of election" in E1006_OECD, while the Lithuanian | 2020 study is coded "1. Polity a member of OECD at the time of | election". --------------------------------------------------------------------------- E1006_EU >>> ID COMPONENT - POLITY MEMBER OF EUROPEAN UNION --------------------------------------------------------------------------- Polity a member of the European Union (EU) at the time of the election. .................................................................. 0. POLITY NOT EU MEMBER AT THE TIME OF ELECTION 1. POLITY A MEMBER OF EU AT THE TIME OF ELECTION 7. NOT APPLICABLE: NOT IN CONTINENTAL EUROPE | VARIABLE NOTES: E1006_EU | | The European Union (EU) is a political and economic union of | polities located primarily in Europe. The EU came into being | in 1993 as the Maastrict Treaty came into force. The Union | traces its origins to the European Coal and Steel Community | (ECSC) established in 1951 and the European Economic | Community (EEC) established in 1957 under the Treaty of Rome. | | Source of data: | https://europa.eu/european-union/about-eu/countries_en | (Date accessed: February 26, 2020). --------------------------------------------------------------------------- E1006_VDEM >>> ID COMPONENT - V-Dem POLITY IDENTIFIER --------------------------------------------------------------------------- Polity identifier in the Varieties of Democracy (V-Dem) project .................................................................. 012. ALBANIA 003. MEXICO 005. SWEDEN 006. SWITZERLAND 009. JAPAN 017. POLAND 019. BRAZIL 020. UNITED STATES OF AMERICA 021. PORTUGAL 022. EL SALVADOR 030. PERU 039. INDIA 042. REPUBLIC OF KOREA 048. TAIWAN 049. THAILAND 066. CANADA 067. AUSTRALIA 072. CHILE 073. COSTA RICA 076. FRANCE 077. GERMANY 081. IRELAND 082. ITALY 084. LATVIA 091. NETHERLANDS 098. TUNISIA 099. TURKEY 101. GREAT BRITAIN 102. URUGUAY 144. AUSTRIA 148. BELGIUM 157. CZECHIA 158. DENMARK 163. FINLAND 164. GREECE 167. HONG KONG 168. ICELAND 169. ISRAEL 173. LITHUANIA 183. MONTENEGRO 185. NEW ZEALAND 186. NORWAY 190. ROMANIA 201. SLOVAKIA 210. HUNGARY | VARIABLE NOTES: E1006_VDEM | | POTENTIAL POLITY LEVEL BRIDGING IDENTIFIER | | E1006_VDEM identifies a polity conducting an election study | that is present in CSES MODULE 5 and links it with the numerical | code assigned to the polity by the Varieties of Democracy (V-Dem) | project. V-Dem provides a multidimensional and disaggregated | dataset that reflects the complexity of the concept of democracy | distinguishing between five high-level principles of democracy: | electoral, liberal, participatory, deliberative, and egalitarian, | and collects data to measure these principles. | | Source of data: www.v-dem.net/en/ | Data accessed: July 15, 2020 --------------------------------------------------------------------------- E1007 >>> ID COMPONENT - SAMPLE COMPONENT --------------------------------------------------------------------------- Sample Components within an election study .................................................................. 01.-25. [SEE ELECTION STUDY NOTES] 999. MISSING | VARIABLE NOTES: E1007 | | E1007 details the number of sampling components included in a | study, i.e., differentiation in administering a survey in terms | of language, pre- and post-election designs, oversampling of | selected subpopulations, etc. | In some cases, analysts may wish to consider regions of polities | or other sample components units of analysis (e.g., what form of | questionnaire was administered to a respondent or timing of | administration). This variable provides this information. If | applicable, ELECTION STUDY NOTES BELOW detail the individual | sampling components. For studies that do not provide multiple | sample components, the default value is 1. | ELECTION STUDY NOTES - FINLAND (2019): E1007 | | The data collection organization programmed the questionnaire | incorrectly and consequently, 288 respondents were not asked | several items in the Finnish study. This affected two CSES | items: turnout and vote choice variables. | The error was detected after the data collection had concluded. | To amend the problem, the data collection organization attempted | to re-contact the affected respondents by phone and ask the | questions that had not been included during the initial | interview. The affected respondents did not retake the entire | interview. | Thus, E1007 distinguishes between the following three categories | of respondents: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Asked the entire questionnaire in the original | interview | 02. Asked several items during the second data | collection round in a phone interview | 03. The second data collection round should have been | conducted, but R could not be reached | ELECTION STUDY NOTES - GERMANY (2017 & 2021): E1007 | | E1007 provides an exact geographic differentiation between | respondents living in territories of former East Germany | ("German Democratic Republic", GDR) and former West Germany | ("Federal Republic of Germany", FRG), as the current federal | state lines are not an accurate representation of these | territories. East and West Germany were sampled separately with | an oversampling of East Germans. | The sample components are coded as 1='West' and 2='East'. The | final 2017 data contains 1,368 respondents from West and 664 | respondents from East Germany. | In the 2021 study, 2,171 Western German respondents participated, | as did 981 Eastern Germans. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. West Germany | 02. East Germany | ELECTION STUDY NOTES - GREECE (2015): E1007 | | Respondents for the Greek September 2015 study were sampled via | random digit dialing. In addition to this freshly recruited main | sample (N = 602), Collaborators contacted 797 respondents from a | previous election study on the January 2015 election who stated | to be willing to participate in future surveys. From this pool | of panelists, 476 participated in the September 2015 study | included in CSES. E1007 distinguishes the two components. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Respondents sampled for the previous election | study (January 2015 elections) | 02. Respondents sampled newly for the September 2015 | election study | ELECTION STUDY NOTES - HUNGARY (2018): E1007 | | Interviews for the Hungarian study were collected in two rounds | of data collection. After the first round, invalid interviews | were excluded, and the sample was heavily distorted in terms of | gender and age. This was compensated with an additional round of | data collection. Variable E1007 distinguishes between respondents | interviewed in the first and second round. For more information, | see Codebook Part 6. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. First round of data collection | 02. Second round of data collection | ELECTION STUDY NOTES - ITALY (2018): E1007 | | After an initial step involving a random stratified sampling of | electoral districts, the Italian 2018 study recruited respondents | from two different sources: An existing web panel maintained by | Demetra Opinioni.net that was initially sampled randomly | (N = 500) and a freshly sampled dual-frame telephone survey | (random digit dialing, N = 1,501). E1007 distinguishes between | the two components. For more information, see Codebook Part 6. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Respondents sampled from web panel | 02. Respondents sampled through random digit dialing | ELECTION STUDY NOTES - NETHERLANDS (2017): E1007 | | The Dutch 2017 study consists of two independent sampling | components, a simple random sample drawn from population | registers (N = 723) and a sample drawn from the ongoing "LISS" | online panel (Langlopende Internet Studies voor de Sociale | wetenschappen, N = 1,180). The LISS panel was launched in 2007 | and refreshed in four subsequent waves, all based on probability | sampling. For more information, users are referred to the study | design overview provided in Codebook Part 6. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Respondents sampled from population registers | (face-to-face interviews with drop-off | questionnaire) | 02. Respondents sampled from LISS web panel | (online interviews) | ELECTION STUDY NOTES - NETHERLANDS (2021): E1007 | | The Dutch 2021 Parliamentary Election Study (DPES) consists of | two independent sampling components, a simple random sample | drawn from population registers (N = 1,688) and a sample drawn | from the ongoing "LISS" online panel (N = 1,766) (Langlopende | Internet Studies voor de Sociale wetenschappen). | The LISS panel was launched in 2007 and refreshed in five | subsequent waves, all based on probability sampling. | Respondents from both components were interviewed both before | and after the election. As the DPES spread CSES-related | questions throughout pre- and post-election interviews, the | CSES retained only those respondents who participated in both | the pre- and post-election interviews. | Wherever possible, the post-election survey was used for coding | CSES variables. For variables in which this is not the case, | there is a reference in the Election Study Notes. | | E1007 further differentiates 31 respondents from the LISS-Panel | as a separate sampling component. These respondents stated to | be ineligible to vote in an open-ended question not included in | CSES. Collaborators note they do not possess any additional | information suggesting ineligibility. | | For more information on the DPES 2021 sampling design, please | refer to the Study Design Overview provided in Codebook Part 6. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Respondents sampled from population registers | (self-administered online or mail-back | questionnaire) | 02. Respondents sampled from the LISS web panel | (online interviews) | 03. Respondents sampled from the LISS web panel | stating to be ineligible to vote in an open-ended | question | ELECTION STUDY NOTES - SLOVAKIA (2020): E1007 | | The fieldwork for the Slovakian study was conducted from June to | August 2020, as a face-to-face study, in the midst of the | COVID-19 pandemic. Due to lockdown measures in some parts of the | country and a shortage of interviewers because of the pandemic, | about 20% of selected primary sampling units (PSUs) were not | reachable. To compensate for this, Slovakian Collaborators | decided to conduct a second round of PSU-selection again based | on the whole country. This resulted in a second round of | fieldwork to collect the missing approx. 33% of the sample. | E1007 distinguishes between the two rounds of fieldwork. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Interview conducted during the first part of | fieldwork (N = 668) | 02. Interview conducted during the second part of | fieldwork (N = 335) | ELECTION STUDY NOTES - THAILAND (2019): E1007 | | The Thai 2019 study was administered as a multistage systematic | random sample, in which substitution of individuals was | permissible at the final stage of selection. | The substitution process was coordinated by Collaborators and | was applied in case interviewers could not contact the sampled | person, due to relocation, decease, illnesses etc. Substituted | individuals were sampled in the same manner as regular | respondents, and matched the age and gender of the originally | sampled person. | E1007 distinguishes respondents who were selected via | substitution from other persons in the sample. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Respondent selected as a substitution for another | non-reachable person (N = 370) | 02. Respondent selected for initial sample, | no substitution (N = 1,166) | ELECTION STUDY NOTES - UNITED STATES (2016): E1007 | | E1007 differentiates between two sample components in the U.S. | 2016 data, namely voters who cast their vote early prior to the | pre-election interview (N=131) and voters who cast their ballot | after the pre-election interview. Respondents who affirmed to | have voted early were asked to report their vote choice in the | pre-election survey. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Voted after the pre-election interview | 02. Voted early before the pre-election interview | | Furthermore, the ANES 2016 Time Series is composed of two | independently drawn probability samples split along modes - one | sample for face-to-face interviews, one sample for interviews | administered on the web. SEE ELECTION STUDY NOTES - UNITED | STATES (2016): E1025_ for more information. | ELECTION STUDY NOTES - UNITED STATES (2020): E1007 | | E1007 differentiates between ten sample components in the 2020 | study. These ten sample components comprise two-digit identifiers | which represent the following distinctions. The first digit | (a "1" or a "2") differentiates between voters that report | casting their ballot before the pre-election and those who report | doing so after the pre-election interview. Voters who report the | former receive a code of "2" (and thus are represented by codes | 21-25, N=371). Voters who report the latter receive a code of "1" | and thus are represented by codes 11-15. | | The second digit of the identifier classifies the respondent | mode of interview and in certain circumstances, the timing period | in which the respondent was invited to undertake the interview. | Respondents part of the 2020 sample are classified with a second | digit (i.e., codes 11-14 and codes 21-24 respectively). The two | replicates (codes 11 & 12 and 21 and 22) comprise respondents | invited to undertake the interview before the party conventions | (replicate 1 - codes 11 and 21 respectively) and after the party | conventions (replicate 2 - codes 12 and 22 respectively). | Respondents originating from the ANES 2016 study and | re-interviewed in 2020 are classified in codes 15 and 25. | Further details on the 2020 sampling components are provided in | Part 6 of the CSES MODULE 5 Codebook. | For further information on the 2016-2020 Panel component, see | ELECTION STUDY NOTES for variables E1009_P1 and E1009_P2. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | VOTED AFTER THE PRE-ELECTION INTERVIEW: | 11. Fresh 2020 sample: web only, replicate 1 | 12. Fresh 2020 sample: web only, replicate 2 | 13. Fresh 2020 sample: web or phone | 14. Fresh 2020 sample: video, web, or phone | 15. 2016-2020 Panel | | VOTED EARLY BEFORE THE PRE-ELECTION INTERVIEW: | 21. Fresh 2020 sample: web only, replicate 1 | 22. Fresh 2020 sample: web only, replicate 2 | 23. Fresh 2020 sample: web or phone | 24. Fresh 2020 sample: video, web, or phone | 25. 2016-2020 Panel --------------------------------------------------------------------------- E1008 >>> ID COMPONENT - ELECTION YEAR --------------------------------------------------------------------------- Election year. .................................................................. 2015-2021. ELECTION YEAR | VARIABLE NOTES: E1008 | | POTENTIAL TIME BRIDGING IDENTIFIER | | E1008 details the year in which an election was held for a study | included in CSES MODULE 5. | | The official period covered by CSES MODULE 5 is from 2016 | to 2021, coinciding with the development of the pilot and | finalized questionnaire. However, one pilot study was fielded | in 2016 for Greece focused on the September 2015 election. --------------------------------------------------------------------------- E1009 >>> ID COMPONENT - RESPONDENT WITHIN ELECTION STUDY --------------------------------------------------------------------------- A01. Respondent identifier. .................................................................. | VARIABLE NOTES: E1009 | | E1009 is ten characters in length and is a unique identifier | for each survey respondent within an election study. | | While this variable uniquely identifies a respondent within | an election study, it is not unique across CSES MODULE 5. | ELECTION STUDY NOTES - HUNGARY (2018): E1009 | | The ID variable in the original dataset consisted of 11 digits. | The CSES uses 10-digit ID variables for the E1009 variable. To | derive E1009, we cut the 7th digit from the original ID variable | (named "sorszam" in the deposited dataset) using the following | Stata commands: | | tostring sorszam, gen(E1009a) format(%11.0f) | gen E1009_1 = substr(E1009a,1,6) | gen E1009_2 = substr(E1009a,8,11) | gen str E1009 = E1009_1 + E1009_2 | ELECTION STUDY NOTES - ICELAND (2016): E1009 | | The deposited identifier had a length of 12 digits. The last | four digits uniquely identify the respondents. To preserve | the ten-digit character of E1009, the last ten digits of | the original variable are used. The original Iceland election | study identifier can be recreated by using "20" (first two | digits in the original identifier) and adding E1009. | ELECTION STUDY NOTES - ICELAND (2017): E1009 | | The deposited identifier had a length of 12 digits. The last | four digits uniquely identify the respondents. To preserve | the ten-digit character of E1009, the last ten digits of | the original variable are used. The original Iceland election | study identifier can be recreated by using "20" (first two | digits in the original identifier) and adding E1009. | ELECTION STUDY NOTES - ITALY (2018): E1009 | | The ID variable in the original dataset consisted of 13 digits. | The CSES uses a 10-digit ID variable for E1009. To derive E1009, | we used the first ten digits from the original ID (A1) which | uniquely identifies the respondents (we added zeros in cases | where the ID length was shorter than ten digits). | ELECTION STUDY NOTES - JAPAN (2017): E1009 | | For the Japanese study, this variable was originally composed of | three variables: Branch (2 digits), Point (3 digits), and RID | (2 digits). The value of Branch starts from "00", Point starts | from "000", and RID begins from "00." Thus, there is one | respondent in the Japanese study with an ID of all 0s. | ELECTION STUDY NOTES - UNITED STATES (2016): E1009 | | Researchers are advised that the American National Election Study | (ANES) 2016 Time Series includes two respondent identifiers: | A respondent identifier assigned by ANES (variable V160001 in | the original dataset) and a respondent identifier assigned by | the fieldwork agency Westat (variable V160001_orig in the | original dataset). | Variables E1009 and E1005 as included in CSES are coded based on | V160001, the respondent identifier coded by ANES. A respondent | identifier based on V160001_orig, the Westat identifier, is | available in E1009_P2 for those 2,670 respondents who were | re-interviewed in 2020. SEE ELECTION STUDY NOTES - UNITED STATES | (2016): E1009_P2 for more information. --------------------------------------------------------------------------- E1009_P1 >>> ID COMPONENT - WHETHER RESPONDENT COMPLETED CSES MODULE MULTIPLE TIMES IN PANEL STUDY --------------------------------------------------------------------------- Whether or not a respondent completed a CSES Module multiple times. .................................................................. 0. R DID NOT COMPLETE MODULE MULTIPLE TIMES (CSES ADMINISTERED PANEL) 1. R COMPLETED MODULE MULTIPLE TIMES (CSES ADMINISTERED PANEL) 7. NOT APPLICABLE: MODULE ADMINISTERED AS CROSS-SECTION 9. MISSING | VARIABLE NOTES: E1009_P1 | | E1009_P1 details whether a respondent completed the CSES MODULE 5 | Questionnaire multiple times or not. A CSES Module is often | administered multiple times within one polity but conventionally, | it is administered on fresh cross-sectional samples of the | polity's population. However, in rare circumstances, the module | has been administered multiple times to the same respondent at | different time intervals. Consequently, E1009_P1 applies only to | respondents originating from studies that administered CSES | MODULE 5 in a panel design, including it in at least two | consecutive waves. | | Respondents coded 1 in E1009_P1 completed the CSES MODULE 5 | Questionnaire on two occasions (at different time points). In the | dataset, they are represented by two separate observations, | the first classifying their responses at Time 1 (T1) and the | second classifying their responses at Time 2 (T2). | Respondents coded 0 in E1009_P1 did not complete the MODULE 5 | Questionnaire twice, even though they were part of a study which | had a panel component. Alternatively, it may classify | respondents recruited in studies combining respondents from | multiple electoral cycles with freshly sampled individuals to the | universe of already existing respondents. | Respondents coded 7 in E1009_P1 are part of regular cross- | sectional designs, which applies to the vast majority of studies | included in CSES. | | This variable facilitates researchers who wish to study intra- | respondent behavior (i.e., the behavior of a respondent at T1 and | T2). For more details on how to connect respondents interviewed | on two occasions, and which are represented in the MODULE 5 | dataset as two separate observations, please consult | variable E1009_P2 which classifies the respondent ID at T1 for | respondents interviewed the second time (T2). | | Researchers interested in analyzing cross-sectional data only | may do so by dropping all cases coded 1 in E1009_P1 from the | CSES MODULE 5 dataset. | ELECTION STUDY NOTES - UNITED STATES (2016): E1009_P1 | | The American National Election Study (ANES) 2020 Time Series | includes 2,670 individuals that were sampled for the 2016 ANES | time series study and were re-interviewed in 2020. Hence, these | 2,670 respondents are included twice in CSES: Once in the USA | 2016 study and once in the USA 2020 study. | Respondents from 2016 who were re-interviewed successfully in | 2020 are coded 1 in E1009_P1. Respondents only participating in | 2016 are coded 0. | Panel identifiers for respondents interviewed in 2016 and 2020 | are available in E1009_P2. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Respondent sampled in 2016 and re-interviewed in | 2020, included in UNITED STATES 2016 and 2020 | study | 00. Respondent included in UNITED STATES 2016 study | only, no re-interview | ELECTION STUDY NOTES - UNITED STATES (2020): E1009_P1 | | The American National Election Study (ANES) 2020 Time Series has | a pre- post-election panel design in which 4,779 respondents were | interviewed twice: Once before the election and once after the | election. Another 2,670 individuals were sampled for the 2016 | ANES time series study and were re-interviewed in 2020 before | and after the election. | Respondents who were sampled in 2016 and took part in both rounds | of the 2020 studies are coded 1 in E1009_P1. Respondents freshly | sampled in 2020 are coded 0. | Panel identifiers for respondents sampled in 2016 are available | in E1009_P2. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Respondent sampled in 2016 and re-interviewed in | 2020, included in UNITED STATES 2016 and 2020 | study | 00. Respondent freshly sampled for UNITED STATES | 2020 study, no re-interview --------------------------------------------------------------------------- E1009_P2 >>> ID COMPONENT - PANEL ID FOR R THAT COMPLETED CSES MODULE MULTIPLE TIMES IN PANEL STUDY --------------------------------------------------------------------------- Panel respondent ID for respondents who completed CSES MODULE 5 multiple times. .................................................................. 1 - 90000000000. RESPONDENT-LEVEL PANEL ID 99999999997. NOT APPLICABLE: R COMPLETED MODULE ONLY ONCE/ MODULE ADMINISTERED AS CROSS-SECTION 99999999999. MISSING | VARIABLE NOTES: E1009_P2 | | E1009_P2 applies only to respondents who completed the MODULE 5 | Questionnaire at least twice and at two different time points. | A CSES Module is often administered multiple times within one | polity but conventionally, it is administered on fresh cross- | sectional samples of the polity's population. | However, in rare circumstances, the module has been administered | multiple times to the same respondent at different time | intervals. E1009_P1 classifies those respondents who have been | interviewed twice - i.e., respondents originating from studies | that administered CSES MODULE 5 in a panel design, including | it in at least two consecutive waves. | | Respondents that completed the MODULE 5 Questionnaire on two | occasions (at different time points) are represented by two | separate observations, the first classifying their responses | at Time 1 (T1) and the second classifying their responses at | Time 2 (T2). E1009_P2 allows researchers to connect these two | observations. It lists the respondent ID applied to the | respondent at T1 for respondents interviewed at T2. | ELECTION STUDY NOTES - UNITED STATES (2016): E1009_P2 | | All respondents that are represented both in the UNITED STATES | 2016 and 2020 studies are assigned their respondent ID from the | 2016 study in E1009_P2. All respondents interviewed in 2016 only | are coded "99999999997. NOT APPLICABLE" in E1009_P2. | | Furthermore, researchers are advised that the American National | Election Study (ANES) 2016 Time Series includes two respondent | identifiers: A respondent identifier assigned by ANES (variable | V160001 in the original dataset) and a respondent identifier | assigned by the fieldwork agency Westat (variable V160001_orig | in the original dataset). | Variables E1009 and E1005 as included in CSES are coded based on | V160001, the respondent identifier coded by ANES. However, as the | 2020 ANES data provided panel identifiers based on V160001_orig, | the Westat identifier, only, E1009_P2 is coded based on | V160001_orig for respondents re-interviewed in the ANES 2020. | ELECTION STUDY NOTES - UNITED STATES (2020): E1009_P2 | | All respondents that are represented both in the UNITED STATES | 2016 and 2020 studies are assigned their respondent ID from the | 2016 study (based on V160001_orig in the ANES 2016 dataset) in | E1009_P2. Respondents freshly sampled in 2020 are coded | "99999999997. NOT APPLICABLE". --------------------------------------------------------------------------- E1010_1 >>> ORIGINAL WEIGHT: SAMPLE E1010_2 >>> ORIGINAL WEIGHT: DEMOGRAPHIC E1010_3 >>> ORIGINAL WEIGHT: POLITICAL --------------------------------------------------------------------------- Original Weights provided by the national election study .................................................................. | VARIABLE NOTES: E1010 | | E1010_ details the original weights provided by each election | study in CSES MODULE 5. | | Sample weights include those intended to correct for unequal | selection probabilities resulting from "booster" samples, | procedures for selection within the household, non-response, | as well as other features of the sample design. | | Demographic weights adjust sample distributions of socio- | demographic characteristics to more closely resemble the | characteristics of the population. | | Political weights reconcile discrepancies in the reported | electoral behavior of the survey respondents from the | official vote counts. | | In cases where a Collaborator provides a single weight that | is a combination of one or more of the three weight categories | (sample, demographic, and political), the weight is duplicated | in the two or more appropriate variables. Thus, analysts using | two or more of the weights simultaneously will need to account | for this duplication. | | Use of weights is at the discretion of the analyst based upon | the considerations of her/his individual research question. | We recommend that analysts familiarize themselves with the | weights, their components, and their methods of creation | before applying them. | | Additionally, analysts will want to keep in mind that these | weights are prepared to be election study weights, not country | weights. To convert the weights to country weights requires an | adjustment for those countries for which one or more polities | or election studies appear in the dataset. | | Where a weight of a particular type is unavailable, these | variables are coded 1. | | Collaborators provided the original weights with a varying | number of decimal places. In this CSES dataset, however, all | of the original weights have been rounded to four decimal | places at maximum (i.e. 1.1234) using STATA. | | Further details on the overall sampling design, including the | weights deposited with CSES, are provided in the "Overview of | Study Design and Weights" available for each election study in | Part 6 of the CSES MODULE 5 Codebook. | Additionally, users may consult the Design Reports for even more | comprehensive information. Design Reports for each polity | included in CSES are available on the CSES MODULE 5 Study Page at | https://cses.org/data-download/cses-module-5-2016-2021/. | | In some instances, original weights as deposited with CSES | included missing values or observations coded as zero. ELECTION | STUDY NOTES for E1010_ detail how the affected cases were handled | in the CSES MODULE 5 dataset. | | +++ TABLE: TYPE OF ORIGINAL WEIGHTS BY INDIVIDUAL ELECTION | STUDIES | | Sample Demographic Political | POLITY (ELEC YEAR) Weight Weight Weight | ----------------------------------------------------------- | AUSTRALIA (2019) X X - | AUSTRIA (2017) - X X | BELGIUM-FLANDERS (2019) - X X | BELGIUM-WALLONIA (2019) - X X | CANADA (2019) X X - | CHILE (2017) - X - | COSTA RICA (2018) - X - | CZECHIA (2021) - X - | DENMARK (2019) - X X | EL SALVADOR (2019) - X X | FINLAND (2019) - X X | FRANCE (2017) - X X | GERMANY (2017) X X - | GERMANY (2021) X X - | GREAT BRITAIN (2017) X X - | GREAT BRITAIN (2019) - X - | GREECE (2015) - X - | GREECE (2019) X X - | HONG KONG (2016) - X - | HUNGARY (2018) - X - | INDIA (2019) X X X | IRELAND (2016) - X - | ISRAEL (2020) - X - | ITALY (2018) X X X | JAPAN (2017) X X - | LATVIA (2018) - X - | LITHUANIA (2016) - X - | LITHUANIA (2020) - X X | MEXICO (2018) X X - | MONTENEGRO (2016) - X - | NETHERLANDS (2017) - X X | NETHERLANDS (2021) - X X | NEW ZEALAND (2017) - X - | NEW ZEALAND (2020) - X - | NORWAY (2017) - X - | PERU (2021) - X - | POLAND (2019) - X - | PORTUGAL (2019) - X X | ROMANIA (2016) X X X | SLOVAKIA (2020) X X - | SWEDEN (2018) - X - | SWITZERLAND (2019) X - X | TAIWAN (2016) - X - | TAIWAN (2020) - X - | TURKEY (2018) - X - | UNITED STATES (2016) X X - | UNITED STATES (2020) X X - | URUGUAY (2019) X X X | ----------------------------------------------------------- | KEY: X = available; - = not available. | | Weights are unavailable for ALBANIA (2017), BRAZIL (2018), | CZECHIA (2017), ICELAND (2016 & 2017), SOUTH KOREA (2016), | THAILAND (2019) and TUNISIA (2019). | ELECTION STUDY NOTES - BELGIUM-FLANDERS (2019): E1010_2 & E1010_3 | | The combined political and demographic weight (E1010_3) was not | constructed for 146 respondents due to the missing information | on the variables used for constructing weights. These cases were | recoded to 0 for the political weight variable and thus, are | dropped from analyses if E1010_3 is applied. | ELECTION STUDY NOTES - BELGIUM-WALLONIA (2019): E1010_2 & E1010_3 | | The combined political and demographic weight (E1010_3) was not | constructed for 149 respondents due to the missing information | on the variables used for constructing weights. These cases were | recoded to 0 for the political weight variable and thus, are | dropped from analyses if E1010_3 is applied. | ELECTION STUDY NOTES - BRAZIL (2018): E1010_ | | The Brazilian sample is proportional to the universe of voters, | both geographically and demographically, so there is no need to | weight it. Thus, all weights are set to 1 for Brazil (2018). | ELECTION STUDY NOTES - COSTA RICA (2018): E1010_2 | | We alert users that the demographic weight (E1010_2) was | constructed on all 1,456 respondents. However, the study contains | 28 respondents who did not provide information on their year of | birth (E2001_Y). The voting eligibility of those 28 respondents | can thus not be ascertained. | ELECTION STUDY NOTES - GERMANY (2021): E1010_2 | | For 62 respondents in E1010_2, no weight value was provided | because one or multiple of the demographic variables used for | calculating the weights were missing. The 62 cases in E1010_2 | were assigned the mean value of the provided demographic weight. | ELECTION STUDY NOTES - GREAT BRITAIN (2017): E1010_1 & E1010_2 | | For 20 respondents, no weight value for E1010_1 and E1010_2 was | provided by the British National Election Study because one or | multiple of the variables used for the weight calculation were | missing. These cases are assigned the mean value of the provided | combined sample and demographic weight. | ELECTION STUDY NOTES - GREAT BRITAIN (2019): E1010_2 | | For 196 respondents, no weight value was provided for E1010_2 by | the British National Election Study because one or multiple of | the variables used for the weight calculation were missing. | These cases are assigned the mean value of the provided | demographic weight. | ELECTION STUDY NOTES - ITALY (2018): E1010_3 | | In the original deposited political weight (E1010_3), 671 | respondents were coded as system missing because there was no | information available for them on lower house vote choice | variables. After consulting with the Collaborator, these cases | were recoded to zero such that they will drop out of any analyses | in which the weight is applied. | Because the voting age differs between the lower house (18 years | and older) and the upper house (25 years and older), applying | any of the three weights adjusts the data for the lower house | electorate but not the upper house electorate. | ELECTION STUDY NOTES - LITHUANIA (2020): E1010_2 & E1010_3 | | The sample includes twelve respondents who are Lithuanian | citizens and thus eligible voters, but reside abroad. For these | twelve observations, identified in variable E2020 (Region of | Residence), weights could not be calculated. After consulting | with the Collaborator, the out-of-country respondents were | assigned the average values of the weight variables E1010_2 and | E1010_3, respectively. | ELECTION STUDY NOTES - NETHERLANDS (2017): E1010_2 & E1010_3 | | For 41 respondents in E1010_2 and 90 respondents in E1010_3, | no weight value was provided because one or multiple of the | variables used for calculating the weights were missing. | For example, some respondents did not indicate their vote choice | and a smaller number of respondents also had missing values on | demographic variables such as country of origin. | The 41 cases in E1010_2 were assigned the mean value of the | provided demographic weight. | Following other MODULE 5 studies, the 90 respondents in E1010_3 | were recoded to 0 for the political weight variable and are | hence dropped from analyses upon applying E1010_3. --------------------------------------------------------------------------- E1011_1 >>> FACTOR: MEAN OF SAMPLE WEIGHT E1011_2 >>> FACTOR: MEAN OF DEMOGRAPHIC WEIGHT E1011_3 >>> FACTOR: MEAN OF POLITICAL WEIGHT --------------------------------------------------------------------------- Mean Weight of Weights provided by the national election study .................................................................. | VARIABLE NOTES: E1011 | | E1011_ details the mean weight of each type, within each polity | (election study). The resulting factors are then used to create | the derivative "Polity Weights" in variables E1012_1 through | E1012_3. | | To follow is the STATA code used to create variables | E1011_1, E1011_2, and E1011_3: | | levelsof E1004, local(elec) sep(" ") | | forvalues i=1/3 { | foreach x of local elec { | su E1010_`i' if E1004=="`x'" | replace E1011_`i' = r(mean) if E1004=="`x'" | } | } | | The STATA code to create the derivative variables in the CSES | dataset was run on the original, unrounded version of | the original weight variables (E1010_1-E1010_3). Thereafter | the derivative variables were rounded to four decimal places at | maximum (i.e. 1.1234) using STATA. | | It is due to this rounding that the mean values of derivative | weight variables E1011_1-E1011_3 for individual election studies | and for the full dataset are close to, but not necessarily | exactly equal to, 1.0000. --------------------------------------------------------------------------- E1012_1 >>> POLITY WEIGHT: SAMPLE E1012_2 >>> POLITY WEIGHT: DEMOGRAPHIC E1012_3 >>> POLITY WEIGHT: POLITICAL --------------------------------------------------------------------------- Polity Weight of Weights provided by the national election study .................................................................. | VARIABLE NOTES: E1012 | | See also Variable and Election Study VARIABLE NOTES for E1010- | E1011. | | E1012_ details the standardized versions (with a mean 1 within | the polity) of the original weights provided with the component | election studies, described in E1010. They are the ratio of each | weighting factor to the mean weight (E1011) of each type, | calculated within each polity. | | The derivative "Polity Weight" (E1012) has been created so | that for each weight (sample, demographic, political), each | respondent within the election study has a mean weight of "1". | If you are running a frequency, for instance, this weight | will work so that the N in your frequency table comes out to | approximately the same as the number of interviews in the | study. This derivative weight is created by dividing the | individual weight for each respondent within an election | study by the mean for that weight for all respondents in that | election study. | | To follow is the STATA code used to create variables | E1012_1, E1012_2, and E1012_3: | | replace E1012_1 = E1010_1 / E1011_1 | replace E1012_2 = E1010_2 / E1011_2 | replace E1012_3 = E1010_3 / E1011_3 | | The STATA code to create the derivative variables in the CSES | dataset was run on the original, unrounded version of | the original weight variables (E1010_1-E1010_3). Thereafter | the derivative variables were rounded to four decimal places at | maximum (i.e. 1.1234) using STATA. | | It is due to this rounding that the mean values of derivative | weight variables E1012_1-E1012_3 for individual election studies | and for the full dataset are close to, but not necessarily | exactly equal to, 1.0000. --------------------------------------------------------------------------- E1013 >>> FACTOR: SAMPLE SIZE ADJUSTMENT --------------------------------------------------------------------------- Factor Weight of Weights provided by the national election study .................................................................. | VARIABLE NOTES: E1013 | | E1013 details the ratio of the average sample size to each | election study sample. This factor is calculated on the basis of | the samples appearing in the CSES data files (i.e. does not | incorporate booster samples, panel respondents who did not | participate in the CSES wave of multi-wave studies, etc.). | Further, this factor treats elections, and not political systems, | as the unit of analysis. Analysts wishing to compare across- | countries, instead of across-election studies, should adjust this | weight accordingly. | | The resulting factor is then used to create the derivative | "Dataset Weights" in variables E1014_1 through E1014_3. | | This variable will not be available until the Full Release of | CSES MODULE 5. | | To follow is the STATA code used to create variable E1013: | | gen n=1 | gen tot_obs = _N /*Number of observations*/ | tab E1004, m | gen estudies = r(r) /*Number of election studies*/ | gen mean_res = tot_obs/estudies | gen n_cases = . | | levelsof E1004, local(elec) sep(" ") | | foreach x of local elec { | su n if E1004=="`x'" | replace n_cases = r(sum) if E1004=="`x'" | } | | replace E1013 = mean_res / n_cases | drop n-n_cases | | The STATA code to create the derivative variables in the CSES | dataset was run on the original, unrounded version of | the original weight variables (E1010_1-E1010_3). Thereafter | the derivative variables were rounded to four decimal places at | maximum (i.e. 1.1234) using STATA. | | It is due to this rounding that the mean value of derivative | weight variable E1013 for the full dataset is close | to, but not necessarily exactly equal to, 1.0000. --------------------------------------------------------------------------- E1014_1 >>> DATASET WEIGHT: SAMPLE E1014_2 >>> DATASET WEIGHT: DEMOGRAPHIC E1014_3 >>> DATASET WEIGHT: POLITICAL --------------------------------------------------------------------------- Dataset Weight of Weights provided by the national election study .................................................................. | VARIABLE NOTES: E1014 | | See also Variable and Election Study VARIABLE NOTES for E1010- | E1013. | | E1014_ are intended for micro-level analyses involving the | entire CSES sample. Using the sample size adjustment (E1013), | the centered weights (E1012) are corrected such that each | each election study component contributes equally to the | analysis, regardless of the original sample size. Users are | advised to read the VARIABLE NOTES of the preceding variables | carefully so as to ensure that their analyses will be weighted | appropriately. | | The derivative "Dataset Weight" (E1014) has been created so | that each election study in the dataset will contribute | equally to analyses of respondents, regardless of the number | of interviews in each election study. | | This variable will not be available until the Full Release of | CSES MODULE 5. | | To follow is the STATA code used to create variables | E1014_1, E1014_2, and E1014_3: | | replace E1014_1 = E1012_1 * E1013 | replace E1014_2 = E1012_2 * E1013 | replace E1014_3 = E1012_3 * E1013 | | The STATA code to create the derivative variables in the CSES | dataset was run on the original, unrounded version of | the original weight variables (E1010_1-E1010_3). Thereafter | the derivative variables were rounded to four decimal places at | maximum (i.e. 1.1234) using STATA. | | It is due to this rounding that the mean values of derivative | weight variables E1014_1-E1014_3 for the full dataset are close | to, but not necessarily exactly equal to, 1.0000. --------------------------------------------------------------------------- E1015 >>> ELECTION TYPE --------------------------------------------------------------------------- Type of election. .................................................................. 10. PARLIAMENTARY/LEGISLATIVE 12. PARLIAMENTARY/LEGISLATIVE AND PRESIDENTIAL 13. PARLIAMENTARY/LEGISLATIVE AND PRIME MINISTER 20. PRESIDENTIAL 30. HEAD OF GOVERNMENT | VARIABLE NOTES: E1015 | | The following table gives an overview of which type of elections | are included in CSES MODULE 5 for which polity. | | +++ TABLE: ELECTION STUDIES BY TYPE OF ELECTION | | Presidential Lower House Upper House | POLITY (ELEC YEAR) Election Election Election | ------------------------------------------------------------- | ALBANIA (2017) - X - | AUSTRALIA (2019) - X X | AUSTRIA (2017) - X - | BELGIUM-FLANDERS (2019) - X - | BELGIUM-WALLONIA (2019) - X - | BRAZIL (2018) X X X | CANADA (2019) - X - | CHILE (2017) X X X | COSTA RICA (2018) X X - | CZECHIA (2017) - X - | CZECHIA (2021) - X - | DENMARK (2019) - X - | EL SALVADOR (2019) X - - | FINLAND (2019) - X - | FRANCE (2017) X - - | GERMANY (2017) - X - | GERMANY (2021) - X - | GREAT BRITAIN (2017) - X - | GREAT BRITAIN (2019) - X - | GREECE (2015) - X - | GREECE (2019) - X - | HONG KONG (2016) - X - | HUNGARY (2018) - X - | ICELAND (2016) - X - | ICELAND (2017) - X - | INDIA (2019) - X - | IRELAND (2016) - X - | ISRAEL (2020) - X - | ITALY (2018) - X X | JAPAN (2017) - X - | LATVIA (2018) - X - | LITHUANIA (2016) - X - | LITHUANIA (2020) - X - | MEXICO (2018) X X X | MONTENEGRO (2016) - X - | NETHERLANDS (2017) - X - | NETHERLANDS (2021) - X - | NEW ZEALAND (2017) - X - | NEW ZEALAND (2020) - X - | NORWAY (2017) - X - | PERU (2021) X X - | POLAND (2019) - X X | PORTUGAL (2019) - X - | ROMANIA (2016) - X X | SLOVAKIA (2020) - X - | SOUTH KOREA (2016) - X - | SWEDEN (2018) - X - | SWITZERLAND (2019) - X X | TAIWAN (2016) X X - | TAIWAN (2020) X X - | THAILAND (2019) - X - | TUNISIA (2019) X X - | TURKEY (2018) X X - | UNITED STATES (2016) X X X | UNITED STATES (2020) X X X | URUGUAY (2019) X X X | ------------------------------------------------------------- | KEY: X = yes; - = no. --------------------------------------------------------------------------- E1016 >>> DATE 1ST ROUND ELECTION BEGAN - MONTH E1017 >>> DATE 1ST ROUND ELECTION BEGAN - DAY E1018 >>> DATE 1ST ROUND ELECTION BEGAN - YEAR --------------------------------------------------------------------------- Date [first round] election began. .................................................................. MONTH 01. JANUARY 02. FEBRUARY 03. MARCH 04. APRIL 05. MAY 06. JUNE 07. JULY 08. AUGUST 09. SEPTEMBER 10. OCTOBER 11. NOVEMBER 12. DECEMBER 99. MISSING DAY 01-31. DAY OF MONTH 99. MISSING YEAR 2015-2021. YEAR 9999. MISSING | VARIABLE NOTES: E1016-E1018 | | POTENTIAL TIME BRIDGING IDENTIFIER | | E1016-E1018 represent the start date of the election. | ELECTION STUDY NOTES - CZECHIA (2017): E1016-1018 | | Elections were held on two days, October 20 and 21, 2017. Only | the first date (October 20) is characterized in the dataset. | ELECTION STUDY NOTES - CZECHIA (2021): E1016-1018 | | Elections were held on two days, October 8 and 9, 2021. Only | the first date (October 8) is characterized in the dataset. | ELECTION STUDY NOTES - INDIA (2019): E1016-E1018 | | Elections were held across seven phases from April 11, 2019 to | May 19, 2019. The start date (April 11) is characterized in the | dataset. | The table below lists election dates for the seven phases, and | the number of constituencies in which elections were held | within the respective phase. | | N of Districts | Phase Date of Election Voting in Phase |---------------------------------------------------------------- | Phase 1 April 11, 2019 91 | Phase 2 April 18, 2019 95 | Phase 3 April 23, 2019 116,33* | Phase 4 April 29, 2019 71,33* | Phase 5 May 06, 2019 50,33* | Phase 6 May 12, 2019 59 | Phase 7 May 19, 2019 59 | | * Voting in the Anantnag district in the state of Jammu and | Kashmir was spread across three phases, i.e., Phases 3 to 5. | Each of the three phases featured different polling stations | within the Anantnag district. | ELECTION STUDY NOTES - NETHERLANDS (2021): E1016-E1018 | | Elections were held across three days, March 15-17, 2021, to | facilitate early voting and prevent crowding at polling stations | due to the ongoing COVID-19 pandemic. The election was | originally scheduled for March 17, 2021. The dataset | characterizes this date as the date the election was initially | intended to occur. --------------------------------------------------------------------------- E1018_1 >>> DATE 1ST ROUND ELECTION BEGAN - YYYY-MM-DD --------------------------------------------------------------------------- Date [first round] election began. .................................................................. | VARIABLE NOTES: E1018_1 | | POTENTIAL TIME BRIDGING IDENTIFIER | | E1018_1 details the start date of the election in the format | YYYY-MM-DD. --------------------------------------------------------------------------- E1018_2 >>> DATE 1ST ROUND ELECTION BEGAN - YYYYMM --------------------------------------------------------------------------- Date [first round] election began. .................................................................. | VARIABLE NOTES: E1018_2 | | POTENTIAL TIME BRIDGING IDENTIFIER | | E1018_2 details the start date of the election in the format | YYYYMM. --------------------------------------------------------------------------- E1019 >>> DATE 2ND ROUND ELECTION BEGAN - MONTH E1020 >>> DATE 2ND ROUND ELECTION BEGAN - DAY E1021 >>> DATE 2ND ROUND ELECTION BEGAN - YEAR --------------------------------------------------------------------------- Date [second round] election began. .................................................................. MONTH 01. JANUARY 02. FEBRUARY 03. MARCH 04. APRIL 05. MAY 06. JUNE 07. JULY 08. AUGUST 09. SEPTEMBER 10. OCTOBER 11. NOVEMBER 12. DECEMBER 96. NOT APPLICABLE: NO SECOND ROUND 99. MISSING DAY 01-31. DAY OF MONTH 96. NOT APPLICABLE: NO SECOND ROUND 99. MISSING YEAR 2015-2021. YEAR 9996. NOT APPLICABLE: NO SECOND ROUND 9999. MISSING | VARIABLE NOTES: E1019-E1021 | | POTENTIAL TIME BRIDGING IDENTIFIER | | E1019-E1021 represent the the start date of the second round of | elections (where applicable). | ELECTION STUDY NOTES - LITHUANIA (2016): E1019-E1021 | | The second round of the Lithuanian 2016 Parliamentary election | was held in constituencies where no candidate won a majority | (more than half of votes cast by the voters who participated for | elections, if at least 40 percent of voters turned out) in the | first round of voting. | ELECTION STUDY NOTES - LITHUANIA (2020): E1019-E1021 | | For elections to the unicameral Seimas, Lithuania operates a | mixed electoral system. 71 of the 141 seats are elected in | single-member constituencies, with the 70 remaining seats being | elected in a nationwide constituency via party-list vote. | The second round of the Lithuanian 2020 Parliamentary election | was held in single-member constituencies where no candidate won | a majority in the first round (i.e., more than half of votes | cast by the voters who participated for elections, if at least | 40 percent of voters turned out or at least one fifth of votes | in case of a lower turnout). In 2020, this applied to 68 of the | 71 districts. | ELECTION STUDY NOTES - UNITED STATES (2020): E1019-E1021 | | Users are advised that runoff | elections were held for two Senate seats in Georgia on January | 5, 2021, as none of the candidates achieved a majority of the | vote in the first round. Respondents from Georgia are identified | in variable E2020 (Region of Residence). --------------------------------------------------------------------------- E1021_1 >>> DATE 2ND ROUND ELECTION BEGAN - YYYY-MM-DD --------------------------------------------------------------------------- Date [second round] election began. .................................................................. 9996. NOT APPLICABLE: NO SECOND ROUND | VARIABLE NOTES: E1021_1 | | POTENTIAL TIME BRIDGING IDENTIFIER | | E1021_1 details the start date of the second round of the | election in the format YYYY-MM-DD, if applicable. | | Users are advised to consult ELECTION STUDY NOTES for variables | E1019, E1020, and E1021. --------------------------------------------------------------------------- E1021_2 >>> DATE 2ND ROUND ELECTION BEGAN - YYYYMM --------------------------------------------------------------------------- Date [second round] election began. .................................................................. 999996. NOT APPLICABLE: NO SECOND ROUND | VARIABLE NOTES: E1021_2 | | POTENTIAL TIME BRIDGING IDENTIFIER | | E1021_2 details the start date of the second round of the | election in the format YYYYMM, if applicable. | | Users are advised to consult ELECTION STUDY NOTES for variables | E1019, E1020, and E1021. --------------------------------------------------------------------------- E1022 >>> STUDY TIMING --------------------------------------------------------------------------- Timing of study relative to election. .................................................................. 1. POST-ELECTION STUDY 2. PRE-ELECTION AND POST-ELECTION STUDY | VARIABLE NOTES: E1022 | | E1022 details whether the CSES MODULE 5 was included in a post- | election study or was fielded in a study operating a pre- | and post-election design. | Conventionally, the CSES questionnaire is only included in post- | election surveys. However, a small number of studies fielded | a limited number of questions before the election in cases where | respondents were interviewed before and after the election. | | Wherever possible, variables collected post-election were | selected for CSES MODULE 5. For variables administered prior to | the election, there is a reference in the ELECTION STUDY NOTES, | alerting users to the deviance. Hence, before conducting their | analyses, we advise researchers to read ELECTION STUDY NOTES | carefully for all variables of their interest. --------------------------------------------------------------------------- E1023 >>> STUDY CONTEXT --------------------------------------------------------------------------- Study context in which CSES module was administered. .................................................................. 1. CSES CONDUCTED AS PART OF A LARGER STUDY 2. CSES CONDUCTED AS STAND-ALONE STUDY 9. MISSING | VARIABLE NOTES: E1023 | | E1023 details the circumstances in which CSES was administered | in a polity. | Oftentimes, CSES is included as one component of a more extensive | election study or study of political behavior (for example the | American National Election Study ANES, or the German Longitudinal | Election Study GLES). However, some studies administered CSES | separately from a larger study. | ELECTION STUDY NOTES - SWEDEN (2018): E1023 | | The CSES survey was fielded in Sweden as a standalone component | from the Swedish National Election Study (SNES) post-election | component. However, as this standalone component included | survey questions not part of CSES MODULE 5, it is designated | being conducted as part of a larger study. --------------------------------------------------------------------------- E1024_1 >>> MODE OF INTERVIEW - STUDY - FIRST E1024_2 >>> MODE OF INTERVIEW - STUDY - SECOND E1024_3 >>> MODE OF INTERVIEW - STUDY - THIRD --------------------------------------------------------------------------- Mode(s) of interview used in study. .................................................................. 0. NOT APPLICABLE 1. IN PERSON, FACE-TO-FACE - USING A QUESTIONNAIRE ON PAPER 2. IN PERSON, FACE-TO-FACE - USING AN ELECTRONIC/COMPUTERIZED QUESTIONNAIRE 3. TELEPHONE 4. MAIL OR SELF-COMPLETION SUPPLEMENT 5. INTERNET 6. IN PERSON, USING VIDEO CALL 9. MISSING | VARIABLE NOTES: E1024_ | | E1024_ detail the mode(s) of interview administered in a study | on the study-level. For mixed-mode studies, the different modes | used are classified in E1024_1-E1024_3 in no particular order. | | Further details on the overall sampling design, including the | mode(s) of interview used, are provided in the "Overview of Study | Design and Weights" available for each election study in Part 6 | of the CSES MODULE 5 Codebook. | Additionally, users may consult the Design Reports for even more | comprehensive information. Design Reports for each polity | included in CSES are available on the CSES MODULE 5 Study Page at | https://cses.org/data-download/cses-module-5-2016-2021/. | | Some practitioners may be familiar with other terminology | for different modes of interview. Below, we outline how some | alternative terms map to the classifications used by CSES: | - Face-to-face in-person interviews using a questionnaire on | paper are sometimes referenced as paper-and-pencil interviews | (PAPI). | - Face-to-face in-person interviews using an electronic or | computerized questionnaire are also known as computer-assisted | personal interviews (CAPI). Sometimes, such interviews may | include self-administered components - for e.g. for questions | deemed sensitive. Self-administered parts interviewers give to | respondents as part of a face-to-face protocol are also known | as computer-assisted self-interviewing (CASI). | - Telephone interviews are sometimes labeled computer-assisted | telephone interviews (CATI). | - Internet surveys are sometimes also referred to as computer- | assisted web interviews (CAWI) or computerized self- | administered questionnaire (CSAQ). | ELECTION STUDY NOTES - CANADA (2019): E1024_ | | The CSES questions for the study were distributed across two | different survey components. The first component, the campaign | period survey (CPS), was fielded pre-election via telephone | while the second, the post-election survey (PES) was via | Internet. | Wherever possible, the post-election phone survey was used for | the CSES variables. For variables in which this is not the | case, there is a reference in the Election Study Notes. --------------------------------------------------------------------------- E1025_1 >>> MODE OF INTERVIEW - RESPONDENT - FIRST E1025_2 >>> MODE OF INTERVIEW - RESPONDENT - SECOND E1025_3 >>> MODE OF INTERVIEW - RESPONDENT - THIRD --------------------------------------------------------------------------- Mode(s) of interview used by respondent. .................................................................. 0. NOT APPLICABLE 1. IN PERSON, FACE-TO-FACE - USING A QUESTIONNAIRE ON PAPER 2. IN PERSON, FACE-TO-FACE - USING AN ELECTRONIC/COMPUTERIZED QUESTIONNAIRE 3. TELEPHONE 4. MAIL OR SELF-COMPLETION SUPPLEMENT 5. INTERNET 6. IN PERSON, USING VIDEO CALL 9. MISSING | VARIABLE NOTES: E1025_ | | E1025_ detail the mode(s) of interview administered in a study | on the respondent-level. For mixed-mode studies, the different | modes used are classified in E1025_1-E1025_3 in no particular | order. | | Further details on the overall sampling design, including the | mode(s) of interview used, are provided in the "Overview of Study | Design and Weights" available for each election study in Part 6 | of the CSES MODULE 5 Codebook. | Additionally, users may consult the Design Reports for even more | comprehensive information. Design Reports for each polity | included in CSES are available on the CSES MODULE 5 Study Page at | https://cses.org/data-download/cses-module-5-2016-2021/. | | For alternative terminology referencing to modes sometimes used | among practitioners, see VARIABLE NOTES for variables E1024_ | (Mode of Interview - Study). | ELECTION STUDY NOTES - CANADA (2019): E1025_1 | | E1025_1 distinguishes between modes selected by respondents for | the post-election wave that included most CSES-related questions. | ELECTION STUDY NOTES - GREAT BRITAIN (2017): E1025_1 & E1025_2 | | E1025_1 refers to the principal face-to-face interview using an | electronic questionnaire. E1025_2 provides the mode for the | supplementary self-completion questionnaire that also included | some CSES-related questions. | ELECTION STUDY NOTES - GREAT BRITAIN (2019): E1025_1 & E1025_2 | | E1025_1 refers to the main interview that was originally | scheduled as face-to-face using an electronic questionnaire. | When lockdown restrictions arising from the COVID-19 pandemic | were implemented in Britain in spring 2020, the study adopted a | mixed-mode approach, with a push-to-mail and push-to-Internet | strategy. | Some CSES questions were included in a supplementary, self- | completion questionnaire. E1025_2 refers to the mode of this | supplementary questionnaire. | ELECTION STUDY NOTES - NETHERLANDS (2017): E1025_1 & E1025_2 | | E1025_1 refers to the mode of the main questionnaire, while | E1025_2 refers to the supplementary questionnaire. | ELECTION STUDY NOTES - NETHERLANDS (2021): E1025_1 & E1025_2 | | As the Dutch 2021 study spread CSES-related questions throughout | the pre- and post-election interview, E1025_1 refers to the mode | of the pre-election questionnaire, while E1025_2 refers to the | post-election questionnaire. | Wherever possible, the post-election survey was used for the CSES | variables. For variables in which this is not the case, there is | a reference in the Election Study Notes. | | For further details on the sampling design, users are advised to | consult ELECTION STUDY NOTES for variable E1007 (Sampling | component) and Codebook Part 6. | ELECTION STUDY NOTES - UNITED STATES (2016): E1025_1 | | As questions assessing the respondent's gender (E2001) and | household income (E2010, E2011) were regarded as being sensitive, | respondents assigned to the face-to-face mode answered these | questions privately. For these questions, the respondent used the | interviewer's computer while the interviewer stepped away, such | that the screen was out of the interviewer's view. | ELECTION STUDY NOTES - UNITED STATES (2020): E1025_1 | | In response to challenges related to the COVID-19 pandemic, the | 2020 American National Election Study implemented a contactless, | sequential mixed-mode design. Sampling components for the 2020 | study correspond to the survey mode sequence employed. | For each respondent, E1025_1 provides the mode pre- and post- | election interviews were conducted in. The sampling components | are detailed in variable E1007 (Sampling Component). --------------------------------------------------------------------------- E1026 >>> SELF-SELECTION INTO MODE OF INTERVIEW --------------------------------------------------------------------------- Whether respondent self-selected or was assigned to interview mode. .................................................................. 0. NOT APPLICABLE 1. RESPONDENTS SELF-SELECTED INTO MODE 2. RESPONDENTS WERE ASSIGNED TO MODE, NO SELF-SELECTION 9. MISSING | VARIABLE NOTES: E1026 | | E1026 distinguishes between studies where respondents were | assigned to the study mode and those studies where different | characteristics of respondents led to de-facto self-selection | into a survey mode. The variable operates on the study level | and is only applicable to mixed-mode studies. | | Further details on the overall sampling design, including the | mode(s) of interview used, are provided in the "Overview of Study | Design and Weights" available for each election study in Part 6 | of the CSES MODULE 5 Codebook. | ELECTION STUDY NOTES - NETHERLANDS (2021): E1026 | | The Dutch 2021 election study is comprised of two independent | sampling components differentiated in variable E1007 (Sampling | Component). | The 1,797 respondents sampled from the LISS panel were all | interviewed online and could not self-select into a different | mode. Hence, these respondents are coded 0. NOT APPLICABLE in | E1026. | The 1,688 respondents freshly sampled from population registers | were invited to participate in an Internet survey but could | choose to fill in a mail-back questionnaire as an alternative. | Hence, E1026 is coded 1. RESPONDENT SELF-SELECTED INTO MODE for | them. | ELECTION STUDY NOTES - SWITZERLAND (2019): E1026 | | All selected respondents were first invited to complete the | survey via the Internet. With the second reminder (out of three), | a paper version of the questionnaire was sent to those who | had not yet participated in the survey. | Thus, E1026 codes those respondents as "1. RESPONDENTS SELF- | SELECTED INTO MODE" who had not filled out the Internet survey | by the date of reception of the paper questionnaire. All | respondents who filled out the online questionnaire ahead of | the second reminder did not have the choice to fill in the | paper version and are hence coded "2. RESPONDENTS WERE ASSIGNED | TO MODE, NO SELF-SELECTION" in E1026. | ELECTION STUDY NOTES - UNITED STATES (2020): E1026 | | Upon initial refusal or non-response, parts of the fresh 2020 | sample were shifted to a different mode. These groups are | detailed in Codebook Part 6. However, since cases were randomly | assigned to mode conditions and were shifted only upon refusal | or non-response, E1026 is coded "2. NO SELF-SELECTION" for the | U.S. 2020 study. --------------------------------------------------------------------------- E1027 >>> DURATION OF INTERVIEW --------------------------------------------------------------------------- Duration of interview. .................................................................. 001-500. NUMBER OF MINUTES 99999. MISSING | VARIABLE NOTES: E1027 | | E1027 details the length of the interview in minutes. | | For a small number of cases, the duration of interview exceeds | the limit as specified in the codes provided above. | When probed, Collaborators report a range of potential reasons | for interview duration deviations including the following | technical issues: | - interviewers forgetting to exit the application used for data | collection upon completion of the interview | - respondents interrupting online interviews without closing the | associated application in their web browser, completing | the interview at a later time or day. | - other technical issues during the survey administration not | further specified. | | Data is mostly unavailable for studies that relied solely on | self-completion mail-back studies or respondents that completed | the survey using this mode; although in some instances, self- | estimates by the respondent are provided and are listed in the | below ELECTION STUDY NOTES where appropriate. | | Data are unavailable for AUSTRALIA (2019), AUSTRIA (2017), | CHILE (2017), COSTA RICA (2018), FRANCE (2017), GREAT BRITAIN | (2017 & 2019), ICELAND (2016 & 2017), IRELAND (2016), ISRAEL | (2020), LATVIA (2018), LITHUANIA (2016 & 2020), MEXICO (2018), | PERU (2021), POLAND (2019), SOUTH KOREA (2016), THAILAND (2019) | and TURKEY (2018). | ELECTION STUDY NOTES - DENMARK (2019): E1027 | | The 140 respondents coded "99999. Missing" in E1027 interrupted | the interview and finished it at a later date, making calculation | of interview duration infeasible. | ELECTION STUDY NOTES - GERMANY (2021): E1027 | | For the German 2021 study, E1027 differs by mode of interview: | For respondents interviewed online, E1027 includes the time the | respondent spent filling out the questionnaire as provided by | the survey institute. Respondents who filled in a self- | administered mail-back survey self-reported the time they | spent on the questionnaire. | ELECTION STUDY NOTES - GREECE (2019): E1027 | | For generating E1027 for the Greek 2019 study, Collaborators | provide response times for CSES-related items only. | ELECTION STUDY NOTES - NORWAY (2017): E1027 | | For some respondents, the start time and end time are on | different dates. In these cases, the duration are set to | "99999. Missing" | ELECTION STUDY NOTES - SWITZERLAND (2019): E1027 | | For the Switzerland (2019) study, this variable is only | available for respondents who filled the questionnaire online. | The variable indicates the total amount of time (in minutes) | between the respondents' very first click when logging into the | online questionnaire to the very last click when submitting the | completed questionnaire. | Respondents were explicitly told that they do not have to fill | in the questionnaire in one go but could also take breaks and | resume the questionnaire later on. Swiss Collaborators also sent | specific reminders for those respondents that had already | started the questionnaire but not answered all the questions yet | to tell them that they can easily continue from where they last | stopped filling the questionnaire. | Respondents with unusually high values for the E1027 variable | (i.e., 200 minutes or more) are presumably those respondents who | did not fill in the questionnaire in one go but took breaks when | responding to the questions or resumed the questionnaire after a | few days/weeks when they were reminded that they had not finished | the whole questionnaire yet. | ELECTION STUDY NOTES - TAIWAN (2016): E1027 | | For a small number of cases, the interview time does not exceed | 15 minutes. The Collaborators note these are a result of | technical difficulties during the interview, such as tablet | power failure or unexpected system shutdown. In these situations | interviewer shifted to a paper questionnaire to collect data and | then put in the collected data later in the system. These rare | occasions are the reason why the duration of the interview was | less than 15 minutes for some cases. | ELECTION STUDY NOTES - UNITED STATES (2020): E1027 | | For the U.S. 2020 study, interview length was calculated by | question-level interview session and audit trail data. | Collaborators note in some instances, the source data provided | by the vendor did not contain complete records for all interview | cases, such that the interview length could be very short in some | cases. Specifically, there are several cases where the vendor's | system failed to record part of the interview session timing | data. | Users are advised that missing question-level timing data could | mean either that the respondent was intentionally not asked the | question or that the system failed to record the timing of the | variable due to a system error or similar. Further, an | unrealistically short response time could have been recorded in | certain branching questions by the data collection vendor's | system reloading the survey screen. | Hence, providing an estimate on the case-level of how many | respondents are affected would be misleading. The portion of | records that are incomplete varies - it might be one question | missing, or many. --------------------------------------------------------------------------- E1028 >>> INTERVIEWER ID WITHIN ELECTION STUDY --------------------------------------------------------------------------- A02. Interviewer identification variable, within election study. .................................................................. 00000-999996. INTERVIEWER IDENTIFIER 999997. NOT APPLICABLE: SELF-ADMINISTERED QUESTIONNAIRE 999999. MISSING | VARIABLE NOTES: E1028 | | E1028 details a unique identifer for an interviewer within an | election study. It is not unique across the entire CSES MODULE 5. | | Data are unavailable for ALBANIA (2017), AUSTRALIA (2019), | CHILE (2017), GREAT BRITAIN (2017), GREECE (2015), HUNGARY | (2018), ICELAND (2016 & 2017), INDIA (2019), LATVIA (2018), | MEXICO (2018), NETHERLANDS (2017), POLAND (2019) and PORTUGAL | (2019). | ELECTION STUDY NOTES - FRANCE (2017): E1028 | | The survey institute conducting the French election study did | not assign ID-codes to interviewers. Collaborators created | interviewer IDs ex-post by using the Primary Sampling Units | (electoral districts for lower house elections) that were | available in the original file. IDs were assigned if the | variance of Interviewer experience was equal to 0 within a | PSU. Those for whom this was not the case were deemed missing | (corresponding to four PSUs). | ELECTION STUDY NOTES - UNITED STATES (2016): E1028 | | The deposited dataset contained an interviewer ID variable in | string format. Specifically, each interviewer ID started with | the acronym "ANES", followed by a four-digit number. | For the CSES MODULE 5 dataset, only the digits from the original | interviewer ID were kept. Furthermore, in case the four-digit | code started with one or several zeros, these zeros were | dropped. | Recoding was realized in Stata 14.2 using the following commands: | | gen E1028a = V168301 | gen E1028b = substr(E1028a, 5, 8) /// | if E1028a != "-1. INAP, web interview" | gen E1028 = real(E1028b) | recode E1028 (. = 999999) | drop E1028a E1028b | ELECTION STUDY NOTES - UNITED STATES (2020): E1028 | | The deposited dataset contained an interviewer ID variable in | string format. Specifically, each interviewer ID started with | "DC", followed by a four-digit number. | For the CSES MODULE 5 dataset, only the digits from the original | interviewer IDs were kept. Furthermore, in case the four-digit | code started with a zero, the zero was dropped. | Recoding was realized in Stata 16.1 using the following commands: | | gen E1028a = V203410 | replace E1028a = "999999" if V203410 == "-1. Inapplicable" | replace E1028a = substr(V203410, 3, 4) /// | if V203410 != "-1. Inapplicable" | gen E1028 = real(E1028a) | drop E1028a --------------------------------------------------------------------------- E1029 >>> INTERVIEWER GENDER --------------------------------------------------------------------------- A03. Gender of interviewer. .................................................................. 1. MALE 2. FEMALE 5. OTHER 7. NOT APPLICABLE: SELF-ADMINISTERED QUESTIONNAIRE 9. MISSING | VARIABLE NOTES: E1029 | | E1029 details the interviewer's gender for non-self administered | studies in CSES MODULE 5. | | Data are unavailable for AUSTRALIA (2019), GERMANY (2017), | GREAT BRITAIN (2017 & 2019), GREECE (2015), HUNGARY (2018), | IRELAND (2016), LATVIA (2018), MEXICO (2018), NETHERLANDS (2017), | POLAND (2019), PORTUGAL (2019) and ROMANIA (2016). --------------------------------------------------------------------------- E1030 >>> DAYS FIELDWORK STARTED POST ELECTION --------------------------------------------------------------------------- Number of days after the election fieldwork started. .................................................................. 001.-900. NUMBER OF DAYS 999. MISSING | VARIABLE NOTES: E1030 | | E1030 details the number of days after the election the fieldwork | commences. If the election was held on more than one day or | involved multiple rounds, this variable reports the number of | days from the first day of the election and/or the first round. | E1030 may either refer to the beginning of fieldwork as specified | in variables E1032-E1034, or to the fielding period for the | entire respective national election study as provided in the | corresponding election study's Design Report - available from the | CSES MODULE 5 study page at: | https://cses.org/data-download/cses-module-5-2016-2021/ --------------------------------------------------------------------------- E1031 >>> DURATION OF FIELDWORK --------------------------------------------------------------------------- Duration of fieldwork. .................................................................. 001-900. NUMBER OF DAYS 999. MISSING | VARIABLE NOTES: E1031 | | E1031 details the number of days in total for the fieldwork | including the end day in the calculation. | E1031 may either refer to the fieldwork dates as specified | in variables E1032-E1034, or to the fielding period for the | entire respective national election study as provided in the | corresponding election study's Design Report - available from the | CSES MODULE 5 study page at: | https://cses.org/data-download/cses-module-5-2016-2021/ --------------------------------------------------------------------------- E1032 >>> DATE QUESTIONNAIRE ADMINISTERED - MONTH E1033 >>> DATE QUESTIONNAIRE ADMINISTERED - DAY E1034 >>> DATE QUESTIONNAIRE ADMINISTERED - YEAR --------------------------------------------------------------------------- A04.a-c. Date questionnaire administered. .................................................................. MONTH 01. JANUARY 02. FEBRUARY 03. MARCH 04. APRIL 05. MAY 06. JUNE 07. JULY 08. AUGUST 09. SEPTEMBER 10. OCTOBER 11. NOVEMBER 12. DECEMBER 99. MISSING DAY 01-31. DAY OF MONTH 99. MISSING YEAR 2015-2022. YEAR 9999. MISSING | VARIABLE NOTES: E1032-E1034 | | E1032-E1034 detail the date the questionnaire was administered, | i.e., the date of interview. | In some instances, the fieldwork dates listed in the Design | Report and within the CSES MODULE 5 dataset as reported in | E1032-E1034 may differ. This arises principally because CSES | MODULE 5 reports the fieldwork dates relative to the fielding of | the CSES component of the study and concerning the relevant | observations from an election study included in CSES MODULE 5. | However, the Design Report can refer to fieldwork dates for | non-CSES components of a study. | Wherever possbile, the table below reports fieldwork dates | as provided in variables E1032-E1034. In cases where data for | either E1032, E1033 or E1034 are unavailable, CSES sourced | fieldwork dates from the corresponding election study's Design | Report - available from the CSES MODULE 5 study page at: | https://cses.org/data-download/cses-module-5-2016-2021/ | | Data for E1032 are unavailable for POLAND (2019). | Data for E1033 are unavailable for FINLAND (2019) and POLAND | (2019). | Data for E1032-E1034 are unavailable for LATVIA (2018). | | +++ TABLE: DATES OF FIELDWORK BY POLITY | | POLITY (ELEC YR) Fieldwork Begins Fieldwork Ends | ----------------------------------------------------------- | ALBANIA (2019) Feb 15, 2018 Apr 11, 2018 | AUSTRALIA (2019) Jun 03, 2019 Jun 19, 2019 | AUSTRIA (2017) Oct 19, 2017 Nov 30, 2017 | BEL-FLANDERS (2019) May 29, 2019 Sep 24, 2019 | BEL-WALLONIA (2019) May 29, 2019 Sep 03, 2019 | BRAZIL (2018) Nov 11, 2018 Nov 24, 2018 | CANADA (2019) Oct 22, 2019 Nov 21, 2019 | CHILE (2017) Dec 18, 2017 Jan 31, 2018 | COSTA RICA (2018) Feb 27, 2019 Mar 06, 2019 | CZECHIA (2017) Oct 23, 2017 Nov 12, 2017 | CZECHIA (2021) Oct 11, 2021 Nov 24, 2021 | DENMARK (2019) Jun 06, 2019 Sep 28, 2019 | EL SALVADOR (2019) Jul 04, 2019 Jul 24, 2019 | FINLAND (2019) Apr 17, 2019 Oct 05, 2019 | FRANCE (2017) May 09, 2017 May 23, 2017 | GERMANY (2017) Sep 25, 2017 Nov 30, 2017 | GERMANY (2021) Sep 27, 2021 Nov 21, 2021 | GREAT BRITAIN (2017) Jun 28, 2017 Oct 02, 2017 | GREAT BRITAIN (2019) Dec 28, 2019 Jul 13, 2020 | GREECE (2015) Nov 16, 2015 Feb 29, 2016 | GREECE (2019) Dec 13, 2019 Mar 07, 2020 | HONG KONG (2016) Sep 06, 2016 Sep 18, 2016 | HUNGARY (2018) Apr 23, 2018 May 14, 2018 | ICELAND (2016) Oct 30, 2016 Jan 25, 2017 | ICELAND (2017) Oct 30, 2017 Feb 02, 2018 | INDIA (2019) May 15, 2019 May 26, 2019 | IRELAND (2016) Mar 01, 2016 Mar 06, 2016 | ISRAEL (2020) Jun 07, 2020 Aug 06, 2020 | ITALY (2018) Mar 08, 2018 May 02, 2018 | JAPAN (2017) Jan 12, 2018 Feb 01, 2018 | LATVIA (2018) Nov 14, 2018 Dec 01, 2018 | LITHUANIA (2016) Nov 11, 2016 Dec 10, 2016 | LITHUANIA (2020) Jan 21, 2021 Feb 21, 2021 | MEXICO (2018) Jul 12, 2018 Jul 18, 2018 | MONTENEGRO (2016) Dec 08, 2016 Jan 16, 2017 | NETHERLANDS (2017) Mar 16, 2017 Jul 03, 2017 | NETHERLANDS (2021) Mar 18, 2021 May 16, 2021 | NEW ZEALAND (2017) Sep 27, 2017 Mar 02, 2018 | NEW ZEALAND (2020) Oct 21, 2020 May 01, 2021 | NORWAY (2017) Sep 20, 2017 Oct 26, 2017 | PERU (2021) Dec 22, 2021 Jan 07, 2022 | POLAND (2019) Oct 24, 2019 Nov 17, 2019 | PORTUGAL (2019) Oct 12, 2019 Dec 15, 2019 | ROMANIA (2016) Dec 13, 2016 Feb 20, 2017 | SLOVAKIA (2020) Jun 10, 2020 Aug 31, 2020 | SOUTH KOREA (2016) Apr 14, 2016 Apr 23, 2016 | SWEDEN (2018) Sep 11, 2018 Nov 06, 2018 | SWITZERLAND (2019) Oct 21, 2019 Jan 05, 2020 | TAIWAN (2016) Jan 17, 2016 Apr 21, 2016 | TAIWAN (2020) Jan 14, 2020 May 30, 2020 | THAILAND (2019) Apr 25, 2019 Jun 05, 2019 | TUNISIA (2019) Jul 18, 2020 Jul 30, 2020 | TURKEY (2018) Jul 23, 2018 Sep 09, 2018 | UNITED STATES (2016) SEE ELECTION STUDY NOTES BELOW | UNITED STATES (2020) SEE ELECTION STUDY NOTES BELOW | URUGUAY (2019) Jan 28, 2020 Feb 27, 2020 | ------------------------------------------------------------- | ELECTION STUDY NOTES - FINLAND (2019): E1032 | | According to data available for the E1032 variable, the last | interview for the Finnish study was conducted in July 2019. | However, after the data collection, it was realized that due to | a programming error 288 respondents were not asked several items | from the questionnaire. These respondents were approached again | afterwards in the second round of data collection, which ended on | October 5, 2019. | ELECTION STUDY NOTES - GREAT BRITAIN (2017): E1032-E1034 | | The post-election interviewing started on June 26, 2017, but | the first interview (E1032, E1033, E1034) was conducted on | June 28, 2017. Those dates differ because the start date | originates from the whole British Election Survey sample but | the person interviewed on June 26, 2017, did not take the CSES | Module. | ELECTION STUDY NOTES - GREAT BRITAIN (2019): E1032-E1034 | | The post-election interviewing started on December 21, 2019, but | the first interview (E1032, E1033, E1034) was conducted on | December 28, 2019. Those dates differ because the start date | originates from the whole British Election Survey sample but | the person interviewed on December 21, 2019, did not take the | CSES Module. | ELECTION STUDY NOTES - INDIA (2019): E1032-E1034 | | The 2019 Indian general elections were held in seven phases from | April 11 to May 19, 2019. Hence, fieldwork started ahead of the | last election phase. However, respondents living in one of the | districts entitled to vote in phase seven were all interviewed | after May 19. Hence, all interviews included in the Indian 2019 | dataset were conducted post-election. For further information on | the seven-phase electoral schedule, researchers are advised to | consult ELECTION STUDY NOTES for variables E1016-E1018. | ELECTION STUDY NOTES - NETHERLANDS (2021): E1032-E1034 | | The Dutch 2021 study has a pre- and post-election panel design | consisting of two distinct and independent sampling components: | A fresh random register sample and a sample drawn from the | an ongoing online panel (SEE ELECTION STUDY NOTES - NETHERLANDS | (2017): E1007). | Both components were interviewed at least twice: Once before the | election and once or twice after the election. Pre-election | interviews were conducted between January 26 and March 14, 2021. | While the register sample completed the post-election interview | without interruption, the questionnaire was split in two for | LISS. E1032-E1034 report the end date of the post-election | interview. For LISS panelists, this refers to the end of the | second post-election interview round, i.e., the date on which | LISS-panelists completed the whole questionnaire. | ELECTION STUDY NOTES - UNITED STATES (2016): E1032-E1034 | | The survey was administered between November 9, 2016, and | January 9, 2017. For demographic variables as well as for | respondents who had voted early, the CSES includes questions of | the pre-election questionnaire, administered between | September 7 and November 8, 2016. | Respondents were asked in the pre-election survey whether they | voted early. Respondents who affirmed this were asked the | questions about their voting behavior (E3012_PR_1-E3013_UH_DC) | already in the pre-election survey. All other respondents were | asked the questions about their voting behavior in the post- | election part of the survey. Early voters are indicated as | belonging to a different sample component in variable E1007. | ELECTION STUDY NOTES - UNITED STATES (2020): E1032-E1034 | | The post-election survey was administered between November 6, | 2020, and January 3, 2021. For demographic variables as well as | for respondents who had voted early, the CSES includes questions | from the pre-election questionnaire, administered between | August 18 and November 3, 2020. | Respondents were asked in the pre-election survey whether they | voted early. Respondents who affirmed this were asked the | questions about their voting behavior (E3012_PR_1-E3013_UH_DC) | already in the pre-election survey. All other respondents were | asked the questions about their voting behavior in the post- | election part of the survey. Early voters are indicated as | belonging to a different sample component in variable E1007. | E1032 - E1034 indicate the start date for each interview. | 1,548 respondents (20.8% of post-election interviews) completed | the interview on a later date than the start date. --------------------------------------------------------------------------- E1035_1 >>> DAYS INTERVIEW CONDUCTED POST FIRST ROUND OF ELECTION --------------------------------------------------------------------------- Number of days after the election interview conducted. .................................................................. 001.-900. NUMBER OF DAYS 9995. NOT ASCERTAINED 9999. MISSING | VARIABLE NOTES: E1035_1 | | E1035_1 details the number of days the interview was conducted | after the first day of the election and/or the first round. | | For studies where the election involved multiple rounds, the | number of days the interview was conducted post the second round | is available in E1035_2. | | Data are unavailable for FINLAND (2019), LATVIA (2018) and | POLAND (2019). | ELECTION STUDY NOTES - INDIA (2019): E1035_1 | | The 2019 Indian general elections were held in seven phases from | April 11 to May 19, 2019. Voting in each polling station took | place in one of the seven phases, meaning that voters cast their | vote only once. E1035_1 takes April 11 as election day. | ELECTION STUDY NOTES - SWEDEN (2018): E1035_1 | | One respondent from the mail-back component stated to have been | interviewed on September 7, 2018, two days before the Swedish | 2018 election. As there is no explanation for this irregularity, | E1035 has been recoded to 9995. NOT ASCERTAINED for the affected | respondent. --------------------------------------------------------------------------- E1035_2 >>> DAYS INTERVIEW CONDUCTED POST SECOND ROUND OF ELECTION --------------------------------------------------------------------------- Number of days after the election interview conducted. .................................................................. 001.-900. NUMBER OF DAYS 9995. NOT ASCERTAINED 9996. NOT APPLICABLE: NO SECOND ROUND 9999. MISSING | VARIABLE NOTES: E1035_2 | | E1035_2 details the number of days from the first day of the | election of the second round for studies where the election | featured more than one round. --------------------------------------------------------------------------- E1036 >>> LANGUAGE OF QUESTIONNAIRE ADMINISTRATION --------------------------------------------------------------------------- A06. Language of questionnaire administration. .................................................................. 008. ARABIC, LEVANTINE (ISRAEL) 016. BENGALI, BANGLADESHI, BANGLA (INDIA) 276. CENTRAL THAI 203. CHINESE, CANTONESE 023. CHINESE, HAKKA 024. CHINESE, MANDARIN 028. CZECH 029. DANISH 031. DUTCH 032. ENGLISH 035. FINNISH 036. FRENCH 044. GERMAN, STANDARD 045. GREEK 047. GUJARATI (SOUTH AFRICA, INDIA) 048. HEBREW 049. HUNGARIAN 051. HINDI 050. ICELANDIC 278. ISAN THAI 052. ITALIAN 054. JAPANESE 055. KANNADA (INDIA) 066. KOREAN 277. LANNA THAI 063. LATVIAN 068. LITHUANIAN 076. MALAYALAM (INDIA) 080. MAORI 082. MARATHI (INDIA) 085. MONTENEGRIN 088. NORWEGIAN 092. ORIYA (INDIA) 094. PANJABI, EASTERN (INDIA) 096. POLISH 097. PORTUGUESE 106. ROMANIAN 109. RUSSIAN 117. SLOVAK 281. SOUTHERN THAI 121. SPANISH 123. SWEDISH 124. TAMIL (INDIA) 126. TELUGU (INDIA) 134. TURKISH 980. [SEE ELECTION STUDY NOTES] 981. [SEE ELECTION STUDY NOTES] 982. [SEE ELECTION STUDY NOTES] 983. [SEE ELECTION STUDY NOTES] 996. OTHER: NOT SPECIFIED 999. MISSING | VARIABLE NOTES: E1036 | | E1036 details the language the interview was administered in. | Coding of E1036 follows the scheme of E2019 (language usually | spoken at home). | ELECTION STUDY NOTES - ALBANIA (2017): E1036 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 980. Albanian | | Collaborators did not provide information on which specific | dialect of the Albanian language was used, and if there were | differences for different respondents. Thus, all respondents are | coded 980. | ELECTION STUDY NOTES - HONG KONG (2016): E1036 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 980. Putonghua | ELECTION STUDY NOTES - INDIA (2019): E1036 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 980. Assamese | ELECTION STUDY NOTES - TAIWAN (2016 & 2020): E1036 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 980. Taiwanese | 981. Mandarin and Taiwanese | 982. Mandarin and Hakka | 983. Taiwanese and Hakka | ELECTION STUDY NOTES - THAILAND (2019): E1036 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 980. Hill tribe language | ELECTION STUDY NOTES - TUNISIA (2019): E1036 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 980. Tunisian dialect | ELECTION STUDY NOTES - UNITED STATES (2016 & 2020): E1036 | | Ten respondents in 2016 and seven respondents in the 2020 study | switched languages between the pre- and the post-election survey | from either English to Spanish or vice versa. These respondents | were coded 980 in E1036. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 980. Language of questionnaire administration | switched between pre- and post-election | interview --------------------------------------------------------------------------- E1037 >>> QUESTIONNAIRE VERSION --------------------------------------------------------------------------- Version of the CSES MODULE 5 questionnaire that was fielded. .................................................................. 1. PILOT QUESTIONNAIRE 2. FINALIZED QUESTIONNAIRE | VARIABLE NOTES: E1037 | | E1037 details whether studies administered the pilot version or | the finalized version of the CSES MODULE 5 questionnaire. | | Studies included in the CSES MODULE 5 fielded one of two | versions of the CSES questionnaire. The pilot questionnaire | was fielded among pre-test studies and in cases where national | election studies were administered prior to the finalization of | the CSES MODULE 5 questionnaire in September of 2016. All other | studies fielded the finalized version. | The differences between the two versions are documented | in the VARIABLE NOTES, applicable to variables E2008, E2012, | E3004_, E3005_, E3006_, E3008_, and E3016_1. Users are advised | to consult the VARIABLE NOTES of these variables for further | information. --------------------------------------------------------------------------- E1038 >>> STUDY TIMING WITH RESPECT TO COVID-19 PANDEMIC --------------------------------------------------------------------------- Timing of election/study relative to COVID-19 pandemic. .................................................................. 0. ELECTION/STUDY CONDUCTED ENTIRELY BEFORE COVID-19 PANDEMIC 1. ELECTION/STUDY CONDUCTED BEFORE & DURING COVID-19 PANDEMIC 2. ELECTION/STUDY CONDUCTED ENTIRELY DURING COVID-19 PANDEMIC | VARIABLE NOTES: E1038 | | A pandemic is an epidemic of infectious disease that has spread | across a large region or multiple or worldwide and affecting a | substantial number of individuals. | | At the time of writing, COVID-19 was first discovered in November | 2019. However, it is possible human-to-human transmission of the | disease was occurring before this discovery. On January 11, 2020 | the World Health Organization (WHO) was notified by Chinese | authorities of a virus outbreak in Wuhan, China. On January 30, | 2020, the World Health Organization classified COVID-19 as a | Public Health Emergency of Concern before eventually declaring | the Health situation as a pandemic on March 11, 2020. | | An election (or election study) is classified as taking place | during the COVID-19 pandemic if the election itself took place | and/or the entire study fieldwork was administered on or after | March 11, 2020 to December 31, 2021, the end of the | CSES MODULE 5 fieldwork. March 11, 2020 is the day on which | the World Health Organization (WHO) officially classified the | COVID-19 Health Crisis as a pandemic. | An election (or election study) is classified as taking place | entirely pre the COVID-19 pandemic if the election was held and | the election study fieldwork was completed before March 11, 2020. | An election which took place before March 11, 2020 but in which | the fieldwork took place both before and/or after March 11, 2020 | is classified as an election taking place both pre and during the | COVID-19 pandemic. | | Source of data: World Health Organization (WHO) | https://www.euro.who.int/en/health-topics/health-emergencies/ | coronavirus-covid-19/novel-coronavirus-2019-ncov | (Date accessed: January 11, 2022). | ELECTION STUDY NOTES - GREECE (2019): E1038 | | Fieldwork for the Greek 2019 study was conducted between December | 12, 2019, and March 16, 2020. However, all respondents included | in the CSES sample were interviewed by March 7, 2020, four days | before COVID-19 was declared a pandemic. Hence, E1038 is coded | coded 0 for Greece 2019. --------------------------------------------------------------------------- E1039 >>> ID COMPONENT - WHETHER POLITY ADMINISTERED CSES MODULE 5 MULTIPLE TIMES --------------------------------------------------------------------------- Whether or not a polity administered CSES MODULE 5 multiple times. .................................................................. 0. R IN POLITY THAT DID NOT ADMINISTER MODULE MULTIPLE TIMES 1. R IN POLITY THAT DID ADMINISTER MODULE MULTIPLE TIMES | VARIABLE NOTES: E1039 | | E1039 details whether the CSES MODULE 5 Questionnaire was | administered more than once in a polity or not. | | Conventionally, a CSES Module is intended to be administered | during a consecutive period of five years. Given that most | electoral cycles encompass a regular four to five year period, | 35 out of 45 polities included in CSES MODULE 5 fielded the | Questionnaire once. | | However, in ten polities that experienced more than one election | in the 2016-2021 MODULE 5 administration period, CSES MODULE 5 | was fielded twice. This applies to the following studies: | CZECHIA (2017 & 2021), GERMANY (2017 & 2021), GREAT BRITAIN | (2017 & 2019), GREECE (2015 & 2019), ICELAND (2016 & 2017), | LITHUANIA (2016 & 2020), NETHERLANDS (2017 & 2021), NEW ZEALAND | (2017 & 2020), TAIWAN (2016 & 2020) and UNITED STATES | (2016 & 2020). | | Researchers are advised that in rare circumstances, MODULE 5 | has further been administered multiple times to the same | respondent at different time intervals. These instances are | detailed in variables E1009_P1 and E1009_P2. =========================================================================== ))) CSES MODULE 5 VARIABLES: MICRO-LEVEL (SURVEY) DATA DEMOGRAPHIC DATA =========================================================================== | Users should note that the CSES questionnaire of origin | does not include any filter instructions in the demographic | section. | | The use of filter instructions/variables in the demographic | section follows primary researchers' applications. Where they | appear, an election study note will inform on their use and | function. | | For several variables, instructions for the administration of | the CSES Questionnaire were given. See >>> CSES MODULE 5 | COLLABORATOR INSTRUCTIONS FOR THE ADMINISTRATION OF THE | CSES QUESTIONNAIRE, in Part 1 of the Codebook. --------------------------------------------------------------------------- E2001_Y >>> DATE OF BIRTH OF RESPONDENT - YEAR --------------------------------------------------------------------------- D01.b. Date of birth of respondent. .................................................................. YEAR 1800-2021. YEAR 9997. VOLUNTEERED: REFUSED 9998. VOLUNTEERED: DON'T KNOW 9999. MISSING | VARIABLE NOTES: E2001_Y | | CSES collects information on the month of birth of the respondent | to determine the eligibility of the respondent (i.e., entitlement | to vote). However, this variable is not made publicly available | to preserve respondent confidentiality. | ELECTION STUDY NOTES - ALBANIA (2017): E2001_Y | | The Albanian Election Study asked for age rather than | Month/Year of birth. E2001_Y was approximated by subtracting | respondents' age at the time of the interview from 2017, i.e., | the election year. | ELECTION STUDY NOTES - AUSTRALIA (2019): E2001_Y | | Respondents were not asked their year and month of birth, but | their age as of June 30, 2019. The variable represents the | calculated year of birth, using the year of the interview and | the age of the respondent. For persons whose birthday was | after the interview, the year of birth will hence be incorrect. | ELECTION STUDY NOTES - CANADA (2019): E2001_Y | | This variable is from the pre-election survey. | ELECTION STUDY NOTES - CHILE (2017): E2001_Y | | There are two respondents born in 2000, meaning that they were 17 | at the time of election and interview for the Chilean study, and | thus neither eligible to vote nor to participate in the study. | Data remain unchanged in the dataset. Collaborators note this is | most likely a typo. | ELECTION STUDY NOTES - COSTA RICA (2018): E2001_Y | | For 28 respondents, the year of birth is missing. The eligibility | of those 28 respondents is therefore unknown. | ELECTION STUDY NOTES - FINLAND (2019): E2001_Y | | There is one respondent born in 2002, meaning that she was 17 at | the time of election and interview for the Finnish study, and | thus not eligible to vote nor to participate in the study. Data | remain unchanged in the dataset. Finnish Collaborators note this | is most likely a typo by the surveyor, and this respondent was | most likely born in 2001. | ELECTION STUDY NOTES - GERMANY (2021): E2001_Y | | For 64 respondents, the year of birth is missing. Collaborators | note eligibility of the 64 individuals has been assessed before | the interview, and that data is coded missing because the | respective respondents did not answer the question. | ELECTION STUDY NOTES - GREAT BRITAIN (2019): E2001_Y | | The British Election Study asked for age rather than | Month/Year of birth. E2001_Y was approximated by subtracting | respondents' age at the time of the interview from 2019. | ELECTION STUDY NOTES - GREECE (2019): E2001_Y | | Users are advised that before the 2019 legislative elections, | voting age was reduced from 18 to 17. | For 36 respondents, the year of birth is missing. However, users | are advised Collaborators assessed voting eligibility in a short | screening instrument at the beginning of the interview. | ELECTION STUDY NOTES - HONG KONG (2016): E2001_Y | | The Hong Kong Election Study asked for age rather than | Month/Year of birth. E2001_Y was approximated by subtracting | respondents' age at the time of the interview from 2016. | ELECTION STUDY NOTES - INDIA (2019): E2001_Y | | The Indian Election Study asked for age rather than Month/Year | of birth. E2001_Y was approximated by subtracting respondents' | age at the time of the interview from 2019, i.e., the election | year. | ELECTION STUDY NOTES - LITHUANIA (2020): E2001_Y | | The Lithuanian 2020 study asked for respondents' age rather than | their month/year of birth. E2001_Y was approximated by | subtracting respondents' age at the time of the interview from | 2020, i.e., the election year. | ELECTION STUDY NOTES - MEXICO (2018): E2001_Y | | Respondents were not asked their year and month of birth, but | their age as of the date of interview provided in variables | E1032-E1034. E2001_Y was calculated by subtracting respondents' | age from the election year. | ELECTION STUDY NOTES - NETHERLANDS (2021): E2001_Y | | This variable is from the pre-election survey. | | For 16 respondents, the year of birth is missing. All of them | are from the 2021 fresh register sample component (SEE ELECTION | STUDY NOTES - NETHERLANDS (2017): E1007) and filled in the | mail-back questionnaire. | Collaborators note eligibility of the 16 individuals has been | assessed before the interview, and that data is coded missing | because the respective respondents did not answer the question. | ELECTION STUDY NOTES - NORWAY (2017): E2001_Y | | The Norwegian Election Study asked for age rather than | Month/Year of birth. E2001_Y was approximated by subtracting | respondents' age at the time of the interview from 2017. | ELECTION STUDY NOTES - THAILAND (2019): E2001_Y | | For 153 respondents, the year of birth is missing. The | eligibility of those 153 respondents is therefore unknown. | ELECTION STUDY NOTES - UNITED STATES (2016): E2001_Y | | Respondents who were 90 years or older at the time of the | interview, that is, all respondents born in 1926 or earlier, are | coded as 1926 (N = 22). | ELECTION STUDY NOTES - UNITED STATES (2020): E2001_Y | | The ANES 2020 Time Series study does not disclose respondents' | year and month of birth, but their age as of election day. | E2001_Y was approximated by subtracting respondents' age from | 2020. Respondents who were 80 years or older at the time of the | election, that is, all respondents born before November 3, 1940, | are coded as 1940 (N = 359). --------------------------------------------------------------------------- E2001_A >>> AGE OF RESPONDENT (IN YEARS) --------------------------------------------------------------------------- Age of respondent (in years). .................................................................. 016-120. AGE, IN YEARS 9997. VOLUNTEERED: REFUSED 9998. VOLUNTEERED: DON'T KNOW 9999. MISSING | VARIABLE NOTES: E2001_A | | DERIVATIVE VARIABLE | | E2001_A was calculated by subtracting the year of birth | (variable E2001_Y) from the election year (variable E1008). | | For further information on individual election studies, users are | advised to carefully read the ELECTION STUDY NOTES for E2001_Y. --------------------------------------------------------------------------- E2001_GG >>> BIRTH GENERATION: GREATEST GENERATION (BORN 1927 OR BEFORE) E2001_GS >>> BIRTH GENERATION: SILENT GENERATION (BORN FROM 1928 TO 1945) E2001_GBB >>> BIRTH GENERATION: BABY BOOMERS (BORN FROM 1946 TO 1964) E2001_GX >>> BIRTH GENERATION: GENERATION X (BORN FROM 1965 TO 1980) E2001_GY >>> BIRTH GENERATION: GENERATION Y (BORN FROM 1981 TO 1996) E2001_GZ >>> BIRTH GENERATION: GENERATION Z (BORN FROM 1997 ONWARDS) --------------------------------------------------------------------------- Generations based on the respondent's year of birth. .................................................................. 0. RESPONDENT NOT PART OF GENERATION 1. RESPONDENT PART OF GENERATION 9. MISSING | VARIABLE NOTES: E2001_G | | DERIVATIVE VARIABLE | | The E2001_G variables distinguish six demographic cohorts | of respondents represented in the CSES MODULE 5, namely: | | IMD2001_GG: Generation Greatest, Rs. born before 1927 | IMD2001_GS: Silent Generation, Rs. born from 1928 to 1945 | IMD2001_GBB: Baby Boomers, Rs. born from 1946 to 1964 | IMD2001_GX: Generation X, Rs. born from 1965 to 1980 | IMD2001_GY: Generation Y, Rs. born from 1981 to 1996 | IMD2001_GZ: Generation Z, Rs. born from 1997 onwards | | Users are advised that the generational boundaries as described | above are primarily based on generational classifications | employed in advanced democracies. As generational experiences | are in part determined by social, cultural, political and/or | economic events that might be unique to a polity, users are | advised that generational classifications may differ in | particular polities and these classifications, based on theory, | merely act as a guide. | | Respondents were asked to provide their year of birth directly | (variable E2001_Y). Hence, E2001_Y forms the basis for the | grouping. --------------------------------------------------------------------------- E2002 >>> GENDER --------------------------------------------------------------------------- D02. Gender of Respondent. .................................................................. 1. MALE 2. FEMALE 3. [SEE ELECTION STUDY NOTES] 7. VOLUNTEERED: REFUSED 8. VOLUNTEERED: DON'T KNOW 9. MISSING | ELECTION STUDY NOTES - AUSTRALIA (2019): E2002 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 03. Other | ELECTION STUDY NOTES - CANADA (2019): E2002 | | This variable is from the pre-election survey. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 03. Other | ELECTION STUDY NOTES - FINLAND (2019): E2002 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 03. Other | ELECTION STUDY NOTES - GERMANY (2017): E2002 | | The respondent's gender was not posed as a question but assessed | by the interviewer. Gender was assessed as a binary variable, | such that a third option was not included in the questionnaire. | ELECTION STUDY NOTES - GREAT BRITAIN (2019): E2002 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 03. In another way | ELECTION STUDY NOTES - GREECE (2019): E2002 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 03. Other | ELECTION STUDY NOTES - INDIA (2019): E2002 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 03. Others | ELECTION STUDY NOTES - NETHERLANDS (2021): E2002 | | This variable is from the pre-election survey. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 03. Other | ELECTION STUDY NOTES - NEW ZEALAND (2017 & 2020): E2002 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 03. Gender diverse | ELECTION STUDY NOTES - POLAND (2019): E2002 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 03. Other | ELECTION STUDY NOTES - SLOVAKIA (2020): E2002 | | The fieldwork agency for the Slovakian study notes that female | respondents participated in significantly higher numbers in the | survey than male respondents, especially in smaller communities. | This led to a distorted distribution of the gender variable for | the Slovakian study. | ELECTION STUDY NOTES - UNITED STATES (2016): E2002 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 03. Other --------------------------------------------------------------------------- E2003 >>> EDUCATION --------------------------------------------------------------------------- D03. Education of respondent. .................................................................. 01. ISCED LEVEL 0 - EARLY CHILDHOOD EDUCATION 02. ISCED LEVEL 1 - PRIMARY 03. ISCED LEVEL 2 - LOWER SECONDARY 04. ISCED LEVEL 3 - UPPER SECONDARY 05. ISCED LEVEL 4 - POST-SECONDARY NON-TERTIARY 06. ISCED LEVEL 5 - SHORT-CYCLE TERTIARY 07. ISCED LEVEL 6 - BACHELOR OR EQUIVALENT 08. ISCED LEVEL 7 - MASTER OR EQUIVALENT 09. ISCED LEVEL 8 - DOCTORAL OR EQUIVALENT 96. NONE (NO EDUCATION) 97. VOLUNTEERED: REFUSED 98. VOLUNTEERED: DON'T KNOW 99. MISSING | VARIABLE NOTES: E2003 | | E2003 details respondents' attained level of education based on | categories by the International Standard Classification of | Education (ISCED 2011), provided by the UNESCO. | An English-language description of the ISCED 2011 standard can | be found here: | http://www.uis.unesco.org/Education/Documents/ISCED_2011_EN.pdf | (Date accessed: April 5, 2019) | | Unless specified otherwise in the Election Study Notes, studies | included the original ISCED 2011 scale in their questionnaires | to measure respondents' education. | ELECTION STUDY NOTES - ALBANIA (2017): E2003 | | Respondents' highest educational attainment was provided in the | deposited dataset in accordance with ISCED scale, used by CSES | for E2003. Albanian Collaborators did not provide an explanation | whether the variable was asked in ISCED scale in the survey or it | was asked differently and recoded to the ISCED scale. | ELECTION STUDY NOTES - AUSTRALIA (2019): E2003 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 03. Certificate I and II level | Secondary education, years 9 and below | 04. Secondary education, years 10 and 11 | Secondary education, year 12 | 05. Certificate III and IV level | 06. Advance Diploma and Diploma level | 07. Bachelor diploma level | Graduate diploma and graduate certificate level | 08. Post-graduate degree level | 96. Did not go to school | ELECTION STUDY NOTES - AUSTRIA (2017): E2003 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Did not complete any school | 02. Elementary school or lower | 03. Secondary school, new secondary school, or lower | grade grammar school (AHS) | Special Needs School | Polytechnic | 04. Apprenticeship, vocational school | Vocational School (e.g. HASCH) | Grammar School with Higher Education Entrance | Qualification (Matura) | Higher Vocational School with Higher Education | Entrance Qualification (Matura) | 06. Academy | College | 07. Bachelor | 08. Master | 09. Ph.D./Doctoral | 96. Did not attend any school | 99. Other | ELECTION STUDY NOTES - BELGIUM-FLANDERS (2019): E2003 | | Respondents' highest educational attainment was asked in | accordance with ISCED scale, used by CSES for E2003. | ELECTION STUDY NOTES - BELGIUM-WALLONIA (2019): E2003 | | Respondents' highest educational attainment was asked in | accordance with ISCED scale, used by CSES for E2003. | ELECTION STUDY NOTES - BRAZIL (2018): E2003 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Basic 1 incomplete (up to 3rd grade) | 02. Basic 1 complete (4th grade) | Basic 2 incomplete (7th grade) | 03. Basic 2 complete (8th grade) | High school incomplete (2nd grade) | 04. High school complete (3rd grade) | Undergraduate incomplete or technical | incomplete | 07. Undergraduate | 08. Graduate or more | 96. Illiterate/ Never been to school | ELECTION STUDY NOTES - CANADA (2019): E2003 | | This variable is from the pre-election survey. It was | differently coded in the original study. The original values | were recoded as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Some elementary school | 02. Completed elementary school | 03. Some secondary/high school | 04. Completed secondary/high school | Some technical, community college, CEGEP, | College Classique | Some university | 06. Completed technical, community college, CEGEP, | College Classique | 07. Bachelor's degree | 08. Master's degree | 09. Professional degree or doctorate | 96. No schooling | ELECTION STUDY NOTES - COSTA RICA (2018): E2003 | | The 2018 Costa Rican measure of education deviates somewhat | from the conventional ISCED standards and does not make the | differentiation of lower and upper secondary education. | Respondents who reported secondary education are coded as | "03. ISCED LEVEL 2 - LOWER SECONDARY". | | CSES Code Election Study Code/Category |------------------------------------------------------------ | 01. Unschooled or primary school not completed | 02. Primary school | 03. Secondary school | 07. Bachelor degree; University degree (Licenciatura | Universitaria) | 08. Master degree | 09. Doctorate | ELECTION STUDY NOTES - CZECHIA (2017 & 2021): E2003 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Incomplete primary education | 02. Primary education | 03. Education without matriculation | Secondary education without matriculation | 04. Secondary education with secondary school leaving | certificate; | Full secondary vocational education with a | matriculation diploma; | General secondary education with a secondary | school leaving certificate | 05. Higher education (post-secondary studies, higher | vocational school, 5th and 6th year of | conservatory) | 07. Bachelor's degree in higher education | 08. Master's degree in higher education | 09. Postgraduate education (PhD), scientific training | (CSc., DrSc.) | ELECTION STUDY NOTES - DENMARK (2019): E2003 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 02. Primary school (up to and including 6th grade) | 03. Primary school (7th-10th grade) | 04. General upper secondary education (e.g. HF, | upper secondary school leaving examination) | Vocational high school education (e.g. HTX, HHX) | Vocational training (e.g., EUD, SOSU, trade and | office, construction or agricultural education) | 05. Short-cycle higher education (under three years, | e.g. laboratory technician, dental hygienist) | 07. Medium-term higher education (3 to 4 years, e.g. | bachelor, HD, HA, nurse or teacher) | 08. Long-term higher education (5 years or more, e.g. | master's degree or MBA) | 09. Researcher education (e.g. Ph.d.) | 96. No education | ELECTION STUDY NOTES - EL SALVADOR (2019): E2003 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Did not study or only studies initial education | 02. First grade; Second grade; Third grade; Fourth | grade; Fifth grade; Sixth grade | 03. Seventh grade; Eighth grade; Ninth grade | 04. First year of high school; Second year of high | school | 05. Third year of high school or higher | 06. First year; Second year | 07. Third year; Fourth year; Fifth year or higher | 08. Master's degree | 09. Doctorate | ELECTION STUDY NOTES - FINLAND (2019): E2003 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 02. Primary education | 03. Lower secondary education | 04. Short vocational training | (vocational school or course) | College level vocational education | (post-secondary) | Upper secondary education (general) | 07. Polytechnic degree or equivalent | 08. University degree (Bachelor or Master) | 09. Doctoral degree or equivalent | ELECTION STUDY NOTES - FRANCE (2017): E2003 | | CSES Code Election Study Code/Category |------------------------------------------------------------ | 01. Unschooled or primary school not completed | 02. Primary school only | Primary school certificate | 03. Schooling from 6th to 9th grade | Middle school certificate (Brevet elementaire, | Brevet d'etudes du premier cycle, Brevet des | colleges) | 04. Schooling from 10th to 12th grade | CAP, BEP, completed an apprenticeship | Diploma as a caregiver, childcare assistant | or medical assistant | Professional baccalaureate | Technical Baccalaureate (BEA, BEC, BEI, BES) | General baccalaureate | 06. Diploma granting access to university (DAEU) | General Academic Studies Degree (DEUG), | Preparatory classes for the Grandes Ecoles | Professional certificates in the fields of | social work, pedagogy, and education | Technological university diploma (DUT) | Paramedical diploma (laboratory assistant, | nurse, etc.) | 07. Professional degree (licence professionnelle) | Three-year academic degree (licence) | 08. Engineer's degree | DESS, professional master's degree | Various higher professional qualifications | (notary, architect, journalist,...) | Grandes Ecoles diploma | Maitrise, CAPES, CRPE | DEA, DES, research master, Agregation (competitive | examination for high school teachers) | 09. Doctorate in medicine or equivalent (dentistry, | pharmacy,...) | Doctorate | 99. Others | ELECTION STUDY NOTES - GERMANY (2017 & 2021): E2003 | | For both German studies, Collaborators assigned ISCED codes | based on two survey questions, one covering general schooling | and the other one covering vocational training. | In two instances, the survey instruments used by the German | Election Study allowed a match to more than one ISCED level. | Specifically, respondents with a master craftsman's or a | technician's diploma were coded to ISCED level 6, although they | might have been coded into ISCED level 5. Likewise, respondents | without a school diploma or lower secondary schooling who | obtained a vocational school diploma (Berufsfachschule) were | coded into ISCED level 3, although they could have also been | coded into ISCED level 4. | Respondents who were still attending school at the time of the | interview were coded as missing, as were respondents who stated | to have a school or vocational training diploma other than those | specified in the given answer categories. | | In the German 2021 study, respondents answering the paper-and- | pencil questionnaire were not asked to differentiate between | different academic degrees (ISCED levels 6 to 8), but were asked | whether they obtained a university degree more generally | instead. As the only available information from the mail-back | survey component was the attainment of a university degree in | general, the respective respondents were coded as "07. ISCED | LEVEL 6 - BACHELOR OR EQUIVALENT". | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 02. Neither school diploma nor completed vocational | training; | No school diploma, but internship or traineeship | 03. No school diploma, but certified training | on-the-job or vocational training program | (no full apprenticeship); | Lower secondary schooling only; | Lower secondary schooling with an internship, | traineeship, certified training on-the-job or | vocational training program | (no full apprenticeship); | 04. No school diploma or lower secondary schooling | and vocational school diploma (without dual | system completed); | No school diploma or lower secondary schooling | and apprenticeship in agriculture, industry or | commerce (dual system); | Upper secondary schooling only; | Upper secondary schooling with an internship, | traineeship, certified training on-the-job or | vocational training program | (no full apprenticeship); | 05. No school diploma or lower secondary schooling | and vocational school diploma (with a dual system | completed); | Upper secondary schooling and vocational school | diploma; | Upper secondary schooling and apprenticeship in | agriculture, industry or commerce (dual system) | Vocational college diploma (Fachschule), without | dual system completed | 07. Vocational academy diploma (Fach/Berufsakademie); | Dual system completed and vocational college | diploma (Fachschule); | Master craftsman's diploma (Meister) or | technician's diploma; | Degree from a University of Applied Sciences; | Bachelor's degree | 08. Master's degree or equivalent | 09. Doctorate | ELECTION STUDY NOTES - GREAT BRITAIN (2017): E2003 | | E2003 was differently coded in the original study. The original | values were recoded as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 02. Completed elementary school | 03. GCSE D-G, CSE grades 2-5, O level D-E | City & Guilds level 1, NVQ/ SVQ 1 and equivalent | Clerical and commercial qualifications | Recognized trade apprenticeship | 04. ONC/OND, City & Guilds level 3, NVQ/SVQ 3 | GCSE A*-C, CSE grade 1, O level grade A-C | Scottish Standard grades, Ordinary bands | City & Guilds level 2, NVQ/ SVQ 2 and equivalent | 05. A level or equivalent | Scottish Higher or equivalent | 06. Univ/poly diploma | Teaching qualification | Nursing qualification | HNC/ HND, City & Guilds level 4, NVQ/SVQ 4/5 | College Classique | 07. First degree | 08. Postgraduate degree | ELECTION STUDY NOTES - GREAT BRITAIN (2019): E2003 | | E2003 was differently coded in the original study. The original | values were recoded as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 02. No qualification | 03. GCSE D-G, CSE grades 2-5, O level D-E | City & Guilds level 1, NVQ/ SVQ 1 and equivalent | Clerical and commercial qualifications | Recognized trade apprenticeship | 04. ONC/OND, City & Guilds level 3, NVQ/SVQ 3 | GCSE A*-C, CSE grade 1, O level grade A-C | Scottish Standard grades, Ordinary bands | City & Guilds level 2, NVQ/ SVQ 2 and equivalent | 05. A level or equivalent | Scottish Higher or equivalent | 06. University/Polytechnic diploma | Teaching qualification | Nursing qualification | HNC/ HND, City & Guilds level 4, NVQ/SVQ 4/5 | 07. First degree | 08. Postgraduate degree | ELECTION STUDY NOTES - GREECE (2019): E2003 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Some classes of primary school (Primary | uncompleted) | 02. Primary School (Primary completed) | 03. Partial Secondary Education e.g. some classes of | six-class high school, night high school, lower | school (Secondary uncompleted) | 04. Completed Secondary Education | (Secondary completed) | 05. Technical School | Tertiary (Uncompleted) | 07. Bachelor (University and Technological | Institutions graduated - Tertiary Completed) | 08. Master | 09. Doctoral | 96. Illiterate/ No formal education | | Collaborators note attending 2-5 years of the outdated six-class | high schools approximates lower-secondary education. | Further, "technical school" might either refer to some of the | older post-secondary schools not longer operating, or Vocational | Training Institutes (IEK) and Vocational upper secondary schools | plus a one-year post-secondary apprenticeship class. Based on | these elaborations, "Technical School" was classified as | "05. ISCED LEVEL 4 - POST-SECONDARY NON-TERTIARY". | ELECTION STUDY NOTES - HONG KONG (2016): E2003 | | Respondents' highest educational attainment was asked in | accordance with ISCED 11. Four respondents stated to have | another education level. They were set to missing. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 99. Others (not further specified) | ELECTION STUDY NOTES - ICELAND (2016 & 2017): E2003 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 02. Primary education | 03. Lower secondary education, 2 years | Paramedic | Certificate for working in the fish industry; | processing | Certificate for employers in post or banks or | secretaries | The police academy | House duties | Certificate in cooking (not chef) | Commercial driver's license and equivalent | Other short courses for commerce - not trade | Certificate in commerce for retail and wholesale | The co-op's high school | Certificate in gardening, agriculture | Technical drawing (Taekniteiknun) | 04. High school | Old; teacher certificate | Old; nurse certificate | Old; midwife | 05. Vocational training in trade finished with a | certificate | Vocational training in trade, license to instruct | Certificate for deputy captains for freight and | charters, engine managers | Commercial pilot licenses, airline transport | license | Old; certification in the making of telephones | 06. Diploma, university level | 07. BA, BS-degree or equivalent | 08. MA, MSc-degree or equivalent | 09. PhD or equivalent | 99. Other, not enough information to categorize | ELECTION STUDY NOTES - INDIA (2019): E2003 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Below class 5 | 02. Passed class 5 | 03. Class 10 | 04. Class 12 | 05. Diploma | 06. Vocational course/skill-based training | 07. Graduate | 08. Post-Graduate | 09. Research scholarship/higher studies | ELECTION STUDY NOTES - JAPAN (2017): E2003 | | The education variable for the Japanese study is composed of two | questions from the national election study. The first question | asked about the last level of education a respondent attended or | is attending. The second question asked if the respondent | graduated from that level, withdrew or is still attending. These | questions are recoded in the following way to match ISCED scale: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 03. Graduated Middle school (including ordinary and | higher primary school under the pre-1947 system) | Withdrew High school (including middle school, | girls' high school, and vocational school under | the pre-1947 system) | 04. Graduated High school (including middle school, | girls' high school, and vocational school under | the pre-1947 system) | Withdrew Technical college or junior college | (including high school, normal school, and higher | normal school under the pre-1947 system) | Withdrew Specialized training college | Withdrew Four-year college | 05. Graduated Specialized training college | 06. Graduated Technical college or junior college | (including high school, normal school, and higher | normal school under the pre-1947 system) | 07. Graduated Four-year college | Withdrew Graduate school master's degree program | 08. Graduated Graduate school master's degree program | Withdrew Graduate school doctoral degree program | 09. Graduated Graduate school doctoral degree program | ELECTION STUDY NOTES - LATVIA (2018): E2003 | | Latvian Collaborators provided education variable mostly in the | Latvian language. Having not heard from Latvian Collaborators | CSES team used Google translate for creating E2003 variable. | The following recodes have been applied: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. No education or unfinished basic education | Sakumskolas vai nepabeigta pamatskolas izglitiba | 02. Pamatskolas izglitiba | 03. Arodskolas izglitiba | 04. Vispareja videja izglitiba | Videja profesionala izglitiba | 05. Pec-videja profesionala izglitiba | Profesionala augstaka izglitiba | 07. Bakalaura grads | 08. Magistra grads | 09. Doktora grads (taja skaita zinatnu kandidats) | 97. Atteicas atbildet | 98. Nezina/NA | ELECTION STUDY NOTES - LITHUANIA (2020): E2003 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Incomplete elementary, pre-school | 02. Primary education; | vocational education obtained after primary | school (before completing basic education) | 03. Basic education; | vocational education acquired together with or | after basic education | 04. High school degree; | vocational education acquired together with upper | secondary education | 05. Post-secondary vocational education | 06. Spec. secondary (technical) education; | higher non-university education (college) | 07. Bachelor's degree or equivalent | 08. Master's degree or equivalent or integrated | studies (five years) | 09. Doctorate degree or equivalent | ELECTION STUDY NOTES - MEXICO (2018): E2003 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Primary incomplete | 02. Primary complete | Secondary or technical training incomplete | 03. Secondary or technical training complete | Preparatory or technical training incomplete | 04. Preparatory or technical training complete | 07. University or equivalent | 08. Master's degree or equivalent | 09. Doctorate or equivalent | 96. None | ELECTION STUDY NOTES - NETHERLANDS (2017 & 2021): E2003 | | For respondents from the Dutch 2021 study, this variable is from | the pre-election survey. | | After consultation with Collaborators, respondents with an MBO | degree were classified as "ISCED LEVEL 4 - POST-SECONDARY | NON-TERTIARY". Collaborators note that a completed secondary | education is an entry requirement for MBO programs. | Further, respondents with an HBO degree were coded as "ISCED | LEVEL 6 - BACHELOR OR EQUIVALENT". HBOs resemble universities | of applied science, and they award bachelor's degrees as a | diploma. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 02. Elementary/primary school | 03. Secondary lower vocational (e.g., VMBO-B, VMBO-K, | praktijkonderwijs, VGLO, LAVO, LTS, | Huishoudschool); | Secondary higher vocational (e.g., VMBO-T, MAVO, | MULO, 3-jarige HBS) | 04. Higher secondary (i.e., HAVO, VWO, HBS, | Gymnasium, Atheneum) | 05. Tertiary vocational (i.e., MBO, MTS) | 07. University Bachelor | Tertiary higher vocational (i.e., HBO, HTS, HEAO, | Kweekschool, Sociale of Pedagogische Academie) | 08. University Master | ELECTION STUDY NOTES - NEW ZEALAND (2017): E2003 | | For New Zealand 2017, Collaborators assigned ISCED codes based | on two survey questions, one covering the highest secondary | school qualification and the other one covering any post- | secondary school qualifications. | In one instance, the survey instruments used by the New Zealand | Election Study allowed a match to more than one ISCED level. | Specifically, respondents with a tertiary degree at institute, | polytechnic or Wananga were coded to ISCED level 5, although | they might have been coded into ISCED level 6. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 02. No secondary qualification | 03. NZ School Certificate in one or more subjects or | National Certificate level 1 | 04. NZ Sixth Form Certificate in one or more | subjects or National Certificate level 2; | NZ UE before 1986 in one or more subjects; | NZ Higher School Certificate or Higher Leaving | Certificate; | University Entrance Qualification from NZ | University Bursary; | NZ A or B Bursary, Scholarship, or National | Certificate level 3; | Another secondary school qualification gained in | New Zealand; | Another secondary school qualification gained | overseas; | 05. National Certificate level 4 or other non-degree | qualification; Tertiary Degree at Institute, | Polytechnic or Wananga | 07. University Undergraduate Degree | 08. University Honors or Masters Degree | 09. University Doctorate | ELECTION STUDY NOTES - NEW ZEALAND (2020): E2003 | | The 2020 New Zealand election study includes two survey | questions on education, one covering the highest secondary | school qualification and the other one covering the highest | qualification overall. For E2003, Collaborators assigned ISCED | codes based on the second survey question asking for the highest | qualification overall. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 02. No secondary qualification | 03. Level 1 Certificate; Level 2 Certificate | Level 3 Certificate | 04. Level 4 Certificate | 05. Level 5 Diploma | 06. Level 6 Diploma; Level 7 Qualification | 07. Bachelor's Degree; Honours or Postgraduate | Diploma | 08. Master's Degree | 09. PhD | ELECTION STUDY NOTES - NORWAY (2017): E2003 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 02. Primary school/elementary school | 03. "Realschule"; One or two years of education after | lower secondary school | Upper secondary school with a duration of one | year | Upper secondary school with a duration of two | years | 04. Upper secondary school of three years or more; | University and university college education of | less than two years | 05. Vocational training; Extensions to upper | secondary school | 06. University or university college education with | a duration of two years (e.g. university college | candidate) | 07. University or university college education with a | duration of three to four years (e.g. bachelor | degree, Cand. Mag., teacher, nurse, engineer) | 08. University or university college education with a | duration of more than four years (e.g. master | degree, major, graduate engineer, MBA) | 09. Ph.D./research training program | ELECTION STUDY NOTES - PERU (2021): E2003 | | The 2021 Peruvian election study includes two survey questions | on education. The first question asks respondents "What was the | last year of studies that you completed or passed?". The second | question was only asked if respondents stated to have obtained | a university degree in the previous question "If you completed | a university degree or postgraduate degree, what is your | academic degree?". | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Incomplete initial or primary | 02. Complete primary | 03. Incomplete high school | 04. Complete secondary | 05. Superior technical incomplete | 06. Complete technical superior; Incomplete | university | 07. Bachelor's Degree | 08. Master's Degree | 09. Doctorate | 96. None | ELECTION STUDY NOTES - PORTUGAL (2019): E2003 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Incomplete primary | 02. Complete primary | 03. Incomplete Secondary | 04. Complete Secondary | Incomplete higher education | 07. Complete higher education | 96. None | ELECTION STUDY NOTES - ROMANIA (2016): E2003 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 02. Kindergarten | Primary school unfinished | Primary school | 03. Secondary school unfinished | Secondary school | Apprentice school | Vocational school | High school unfinished | 04. High school | 05. Post-secondary school | 06. Bachelor unfinished | Short cycle tertiary education | 07. Bachelor | 08. Master | 09. Doctorate | ELECTION STUDY NOTES - SLOVAKIA (2020): E2003 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Unfinished primary | 02. Primary | Lower secondary (without matura) | Vocational (without matura) | 03. Higher vocational (without matura) | Vocational (with matura) | 04. Upper secondary vocational (with matura) | Upper secondary general (with matura) | 05. Post-secondary | 07. Bachelor | 08. Master or equivalent | 09. Doctoral | ELECTION STUDY NOTES - SOUTH KOREA (2016): E2003 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 03. Complete /incomplete middle school | 04. Complete/incomplete high school | 06. Complete/incomplete college | 07. Complete university | ELECTION STUDY NOTES - SWEDEN (2018): E2003 | | CSES Code Election Study Code/Category |-------------------------------------------------------- | 01. Not completed primary, or equivalent school | 02. Primary school or corresponding compulsory school | 03. Studies at upper secondary school, | folk high school, junior secondary school (or | equivalent) | 04. Degree from upper secondary school, folk | high school, junior secondary school (or | equivalent); | Studies at college/university | 05. Tertiary education, not college/university | 07. Degree from college/university | 08. Studies or degree at the postgraduate education | ELECTION STUDY NOTES - SWITZERLAND (2019): E2003 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 02. Primary school | 04. Secondary school | Basic voluntary training (with contract) | 05. Apprenticeship or vocational school | Diploma school | Trading school | Secondary school vocational diploma | High school or school preparing for the | baccalaureate | Higher vocational education with master diploma | | Additionally, the Swiss study included three additional | categories for the education variable. These were: | - Higher vocational college for technology, economy, social | issues or similar | - University of Applied Sciences, University of Teacher | Education | - University or Federal Institute of Technology | These respondents got a follow-up question to determine the | level of the highest diploma. Accordingly, they were coded into | the following categories: | - 07. ISCED LEVEL 6 - BACHELOR OR EQUIVALENT | - 08. ISCED LEVEL 7 - MASTER OR EQUIVALENT | - 09. ISCED LEVEL 8 - DOCTORAL OR EQUIVALENT | ELECTION STUDY NOTES - TAIWAN (2016 & 2020): E2003 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Some primary school | 02. Primary school graduate | Some junior high school | Some high school or vocational school | 03. Junior high school graduate | 04. High school or vocational school | graduate | Some technical college | Some university | 06. Technical college graduate | 07. University graduate | 08. Post-graduate education | 96. Illiterate | Literate but no formal schooling | ELECTION STUDY NOTES - THAILAND (2019): E2003 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Early childhood education (Kindergarten) | 02. Graduated from primary school | 03. Graduated from junior high school | (lower secondary level) | 04. Graduated from high school (upper secondary level) | 05. Graduation at the post-secondary level before | tertiary education | 06. Graduated with an associate's degree | 07. Higher education with a bachelor's degree or | equivalent | 08. Higher education at the master's degree or | equivalent | 09. Higher education at the doctoral level or | equivalent | 96. No education | ELECTION STUDY NOTES - TUNISIA (2019): E2003 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Did not finish elementary school | 02. Elementary school | 03. Middle school | 04. Secondary school | 05. Post secondary, no triple | 06. Short courses series | 07. Bachelor's degree and equivalent | 08. Master and equivalent | 09. PhD and equivalent | ELECTION STUDY NOTES - TURKEY (2018): E2003 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 02. Primary school graduate (five years) | 03. Secondary school/elementary school graduate | 04. High school graduate; | High school graduate who continued to higher | education, but could not finish it | 07. University graduate | 08. Master of Arts | 09. Doctorate | 96. Illiterate, no formal education; | Literate, but no formal education | ELECTION STUDY NOTES - UNITED STATES (2016): E2003 | | Respondents who indicated having finished "9th grade" were | classified as only having completed primary education. The | decision is based on the ISCED Mapping of National Educational | Programmes for the U.S., which classifies secondary/high school | education in the U.S. to run from grade 10 to grade 12. For more | information see: | http://www.uis.unesco.org/Education/ISCEDMappings/Pages/ | default.aspx (Date accessed: February 12, 2019). | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Less than 1st grade | 1st, 2nd, 3rd or 4th grade | 5th or 6th grade | 02. 7th or 8th grade | 9th grade | 03. 10th grade | 11th grade | 12th grade no diploma | 04. High school graduate - high school diploma or | equivalent (for example: GED) | Some college but no degree | 06. Associate degree in college - | occupational/vocational program | Associate degree in college - academic program | 07. Bachelor's degree (for example: BA, AB, BS) | 08. Master's degree (for example: MA, MS, MENG, MED, | MSW, MBA) | Professional school degree (for example: MD, DDS, | DVM, LLB, JD) | 09. Doctorate degree (for example: PHD, EDD) | 99. Other (not specified) | ELECTION STUDY NOTES - UNITED STATES (2020): E2003 | | Unlike the 2016 study, the U.S. 2020 study subsumes all | respondents who indicated having obtained "less than a high | school credential" into one general category. These respondents | were classified as having completed primary education. | The decision is based on the ISCED Mapping of National | Educational Programs for the U.S., which classifies | secondary/high school education in the United States to run from | grade 10 to grade 12. For more information, see: | http://www.uis.unesco.org/Education/ISCEDMappings/Pages/ | default.aspx (Date accessed: February 12, 2019). | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 02. Less than high school credential | 04. High school graduate - high school diploma or | equivalent (e.g. GED) | Some college but no degree | 06. Associate degree in college - | occupational/vocational program | Associate degree in college - academic program | 07. Bachelor's degree (e.g. BA, AB, BS) | 08. Master's degree (e.g. MA, MS, MEng, MEd, MSW, MBA) | Professional school degree (e.g. MD, DDS, DVM, | LLB, JD) / Doctoral degree (e.g. PHD, EDD) | 99. Other --------------------------------------------------------------------------- E2004 >>> MARITAL STATUS OR CIVIL UNION STATUS --------------------------------------------------------------------------- D04. Respondent's marital or civil union status. .................................................................. 1. MARRIED OR LIVING TOGETHER AS MARRIED 2. WIDOWED 3. DIVORCED OR SEPARATED (MARRIED BUT SEPARATED/ NOT LIVING WITH LEGAL SPOUSE) 4. SINGLE, NEVER MARRIED 5. [SEE ELECTION STUDY NOTES] 7. VOLUNTEERED: REFUSED 8. VOLUNTEERED: DON'T KNOW 9. MISSING | VARIABLE NOTES: E2004 | | E2004 details the respondent's current marital status. | For instance, a person who is both divorced and living together | as married would be coded 1. | ELECTION STUDY NOTES - FINLAND (2019): E2004 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Living together as married/Co-habiting | ELECTION STUDY NOTES - FRANCE (2017): E2004 | | In the 2017 French election study, the marital status of | respondents was assessed with three survey questions. | The first asked whether respondents were living together with a | partner. | Respondents living with a partner were asked about the | legal status of their relationship in a follow-up question | (married, civil union, cohabiting, divorced). | Respondents not living with a partner received a separate | follow-up question detailing their marital status (married, | civil union, divorced/separated, widowed, single). | | The following table shows how answers were recoded for CSES: | | CSES Code Election Study Code/Category |-------------------------------------------------------- | 01. Married and living together with a partner | Civil Union (PACS) and living together with a | partner | Living together with a partner /Co-habiting | Divorced, but living together with a partner | 02. Widowed, not living together with a partner | 03. Divorced, not living together with a partner | Married / Civil Union (PACS) but not living | together with a partner | 04. Single, never married, never been in a | civil union (PACS) | ELECTION STUDY NOTES - GERMANY (2017 & 2021): E2004 | | E2004 was constructed by Collaborators based on two survey | questions. The first asked for the respondent's marital status | (legally married or civil partnership). | If respondents were not living together with a spouse or civil | union-partner, a follow-up question was asked if they are in an | unmarried relationship and further if they were living together | in this relationship. | ELECTION STUDY NOTES - IRELAND (2016): E2004 | | This variable was differently coded in the original study. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Married/Civil Partnership | Living as married/Co-habiting | 04. Single | 05. Widowed/Divorced/Separated | ELECTION STUDY NOTES - LITHUANIA (2020): E2004 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Married; | Cohabiting but not officially married | ELECTION STUDY NOTES - NETHERLANDS (2017): E2004 | | In the Dutch 2017 study, data on respondents' marital status has | not been collected in the survey but was obtained from | population registers. Respondents provided consent before data | collection. | Generally, register data are based on the most recent available | data, usually the year preceding data collection. | ELECTION STUDY NOTES - NETHERLANDS (2021): E2004 | | This variable is from the pre-election survey and was | constructed using two original items, namely marital status | and a second variable on whether respondents had a partner | living in the same household. | Respondents who indicated not being married in the first item | but in the second item refused to indicate whether they were | living with a partner or not were coded as 'refused'. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Married/living together with a partner | 02. Widowed, not living together with a partner | 03. Divorced or separated, not living together with | a partner | 04. Never married, not living together with a partner | 05. Married but not living together with a | partner | 07. Refused / Not married, refused to say whether | living with a partner | | Additionally, three respondents indicated not living with a | partner but did not provide their marital status. They were set | to missing. | ELECTION STUDY NOTES - NEW ZEALAND (2020): E2004 | | The question wording for E2004 deviates from the CSES MODULE 5 | standards. The question asked respondents whether they were | currently living with a spouse or partner (coded as 1) or not | (coded as 2). In the CSES, respondents who answered "Yes" were | recoded into "1. MARRIED OR LIVING TOGETHER AS MARRIED". | Respondents who answered "No" were recoded into "5. [SEE ELECTION | STUDY NOTES]". This category could thus include respondents who | were widowed, divorced or separated, or single or never married. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Currently living with a spouse or partner | 05. Currently not living with a spouse or partner | ELECTION STUDY NOTES - SWEDEN (2018): E2004 | | The answer categories for E2004 offered to respondents deviated | slightly from CSES MODULE 5 standards. They were recoded as | follows: | | CSES Code Election Study Code/Category |-------------------------------------------------------- | 01. Married/partnership | Cohabitant | 02. Widow/widower | 04. Single | ELECTION STUDY NOTES - UNITED STATES (2016 & 2020): E2004 | | This variable was constructed using the two original items | 'marital status' and 'domestic partnership status.' Respondents | who indicated not being married in the first item but in the | second item refused to indicate whether they were living with a | partner or not were coded as 'refused'. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Married: Spouse present/living together with | a partner | 02. Widowed, not living together with a partner | 03. Divorced or separated, not living together with | a partner | 04. Never married, not living together with a partner | 05. Married: Spouse absent (volunteered, face-to-face, | video and phone interviews only) | 07. Refused / Not married, refused to say whether | living with a partner | | Additionally, four respondents in the 2016 study did indicate | not to live with a partner but refused to name their marital | status. They were set to missing. --------------------------------------------------------------------------- E2005 >>> UNION MEMBERSHIP --------------------------------------------------------------------------- D05. Union membership of respondent. .................................................................. 0. R IS NOT A MEMBER OF A UNION 1. R IS MEMBER OF A UNION 7. VOLUNTEERED: REFUSED 8. VOLUNTEERED: DON'T KNOW 9. MISSING | VARIABLE NOTES: E2005 | | Data are unavailable for SOUTH KOREA (2016). | ELECTION STUDY NOTES - FINLAND (2019): E2005 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 0. I don't belong to any | 1. I belong, but I don't participate in the | activities | I belong and participate in the activities to | some extent | I belong and actively participate in the | activities | ELECTION STUDY NOTES - SLOVAKIA (2020): E2005 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 0. Was a union member but now it is not | It is not and never was a union member | 1. Union member | ELECTION STUDY NOTES - SWEDEN (2018): E2005 | | This variable was constructed using two original items. In the | first, respondents were asked whether they were a member of a | union or any other entrepreneur or professional organization. | In a follow-up question, respondents were invited to give the | name of the organization of which they were a member. | Respondents were coded as being a union member in E2005 if they | stated to be a member of one of the following: LO - The Swedish | Trade Union Confederation, TCO - The Swedish Confederation of | Professional Employees, Saco - The Swedish Confederation of | Professional Associations, or another union organization. | ELECTION STUDY NOTES - UNITED STATES (2016 & 2020): E2005 | | This variable was constructed using two original items. In the | first, the respondent was asked whether anyone in the household | belonged to a labor union. In a follow-up item, the respondent | was asked which household member belonged to a union. | Respondents refusing to answer to the first item or stating not | to know the answer were coded as 'refused' or 'don't know' for | E2005, respectively. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 0. No one, spouse/partner, someone else in household | belongs to a labor union | 1. Respondent belongs to a labor union | 7. Refused to say whether anyone / who in household | belongs to a labor union | 8. Don't know whether anybody in household belongs | to a labor union --------------------------------------------------------------------------- E2006 >>> CURRENT EMPLOYMENT STATUS --------------------------------------------------------------------------- D06. Current employment status of respondent. .................................................................. IN LABOR FORCE: 01. EMPLOYED - FULL-TIME (32 OR MORE HOURS WEEKLY) 02. EMPLOYED - PART-TIME (15-32 HOURS WEEKLY) 03. EMPLOYED - LESS THAN 15 HOURS 04. HELPING FAMILY MEMBER 05. UNEMPLOYED NOT IN LABOR FORCE: 06. STUDENT, IN SCHOOL, IN VOCATIONAL TRAINING 07. RETIRED 08. HOUSEWIFE, HOME DUTIES 09. PERMANENTLY DISABLED 10. OTHERS, NOT IN LABOR FORCE 11. ON TEMPORARY JOB LEAVE (MATERNITY LEAVE, SICK LEAVE, ETC.) 12. CIVIL / MILITARY SERVICE 13. [SEE ELECTION STUDY NOTES] 14. [SEE ELECTION STUDY NOTES] 97. VOLUNTEERED: REFUSED 98. VOLUNTEERED: DON'T KNOW 99. MISSING | VARIABLE NOTES: E2006 | | Respondents who are temporarily unemployed are coded UNEMPLOYED. | Respondents on "workfare" or enrolled in a government job | training program are coded EMPLOYED. | | There is some inconsistency between studies in the way | the responses to the questions about current employment status | (E2006) affected the application of the follow-up occupation | variables (E2007-E2009). The CSES standard is that the | occupation variables are asked from those in labor force. | However, in some cases, for respondents categorized as not in | labor force in E2006 (codes 6-12) the occupation variables may | report respondent's last occupation. Hence, the responses | concerning occupation that belong to respondents not in labor | force presumably reflect their previous or last occupation. | ELECTION STUDY NOTES - AUSTRALIA (2019): E2006 | | The Australian study had an additional option "other" for this | question, followed by the open-ended question where respondents | had a chance to write their current employment status. | These open-ended answers were recoded into the following | categories: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 13. Casual | Casual employment | Casual employment (0-24 hours per week) | Contract when available | Contracted | Semi-retired | Semi-retired but still contracts to government | and industry | Semi-retired self-employed | Very part-time / retired | Work cover | 14. Mainly volunteer work | Teach and edit on a mainly voluntary basis | Volunteer secretary of the body corporate for my | unit block of 39 units | Volunteering work | ELECTION STUDY NOTES - AUSTRIA (2017): E2006 | | In the original study, there was no separate answer category for | "unemployed." Thus respondents who were unemployed at the time | of the study primarily fell into the category "10. OTHERS, NOT | IN LABOR FORCE." | ELECTION STUDY NOTES - BRAZIL (2018): E2006 | | The answer categories for E2006 offered to respondents deviated | from CSES MODULE 5 standards. Answers were coded to the CSES | categories in the following way: | | CSES code Election Study Code/Category |---------------------------------------------------------------- | 01. Registered | Unregistered employee | Autonomous | Liberal professional | Employer | 04. Helps someone in the family and receives | remuneration | Helps someone in the family and does not receive | remuneration | 05. Unemployed (looking for a job) | 06. Apprentice with remuneration | Apprentice without remuneration | Student | 07. Retired (time off work) | Receives pension | 09. Retired (disability) | 08. Housewife | 10. Unemployed (not looking for a job) | ELECTION STUDY NOTES - CANADA (2019): E2006 | | The variable is from the pre-election study. | The codes, which are mentioned below, have a somewhat different | meaning compared to the standard CSES coding. The number of | working hours was not asked and is thus unknown. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Working for pay full-time | Self-employed (with or without employees) | 02. Working for pay part-time | 03. Student and working for pay | 05. Unemployed/ looking for work | 06. Student | 07. Retired | 08. Caring for a family | 09. Disabled | 13. Retired and working for pay | 14. Caring for family and working for pay | ELECTION STUDY NOTES - DENMARK (2019): E2006 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. More than full time (more than 37 hours weekly) | Full time (32 - 37 hours weekly) | 02. Part-time (15 to less than 32 hours weekly) | 03. Less than 15 hours weekly | 04. Helping family member | 05. Unemployed | 06. Student, in school, in vocational training | 07. Retired | 08. Housewife, homemaker, home duties | 09. Permanently disabled | 10. On maternity or parental leave | Long-term sick leave | Military conscription | Others, not in labor force | | Categories summarized under code 10 "OTHERS, NOT IN LABOR FORCE" | were summarized for the CSES deposit and hence could not be | differentiated for E2006. | ELECTION STUDY NOTES - FINLAND (2019): E2006 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 04. Informal career | 05. Unemployed | 06. Student or school-goer | 07. Pensioner/Retired on account of age or working | years | 08. Homemaker | On parental leave or child care leave | 12. Conscripted for military service or in civilian | service | ELECTION STUDY NOTES - GERMANY (2017): E2006 | | The original coding scheme contains a category denoting short- | time working (while being employed in a full-time contract, | "Kurzarbeit"). Since there is no equivalent in CSES, respondents | in this category (N=2) were set to missing by the Collaborators. | | CSES Code Election Study Code/Category |-------------------------------------------------------- | 01. Full-time employment (30 or more hours weekly) | 02. Part-time employment (up to 30 hours weekly) | 05. Unemployed | ELECTION STUDY NOTES - GERMANY (2021): E2006 | | Definitions of full-time and part-time employment slightly | differ between CSES conventions and the German study, as | indicated in the table below. | Furthermore, the original coding scheme includes a category | denoting short-time working (while being employed in a full-time | contract, "Kurzarbeit"). Since there is no equivalent in CSES, | respondents in this category (N=4) were set to code | 13. SEE ELECTION STUDY NOTES. | | CSES Code Election Study Code/Category |-------------------------------------------------------- | 01. Full-time employment (30 or more hours weekly) | 02. Part-time employment (up to 30 hours weekly) | 03. Marginally employed, 450-Euro-Job, Minijob | 04. Helping family member | 05. Currently unemployed | 06. Apprentice/trainee | School student | Studying at a polytechnic or university | Currently on a retraining course | 07. Retirement, on a pension (formerly employed) | 08. Not in full or part-time employment (housewife/ | homemaker) | 11. On maternity leave, parental leave | 12. Community service (("Bundesfreiwilligendienst", | "Freiwilliges Soziales Jahr (FSJ)", | "Freiwilliges Oekologisches Jahr (FOEJ)") | 13. Currently in short-time work ("Kurzarbeit") | 99. Multiple mentions | ELECTION STUDY NOTES - GREAT BRITAIN (2017): E2006 | | The codes, which are mentioned below, have a somewhat different | meaning compared to the standard CSES coding. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Working full time - employee (30+ hours) | Working full time - self-employed (30+ hours) | 02. Working part time - employee (8-29 hours) | Working part time - self-employed (8-29 hours) | 05. Unemployed and actively seeking work | 06. A full-time student or pupil | 07. Retired from paid work | 08. Looking after the family or home | 09. Not working because temporary sick or injured | Not working because long-term sick or disabled | ELECTION STUDY NOTES - GREAT BRITAIN (2019): E2006 | | The codes, which are mentioned below, have a somewhat different | meaning compared to the standard CSES coding. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Working full time - employee (30+ hours) | Working full time - self-employed (30+ hours) | 02. Working part time - employee (8-29 hours) | Working part time - self-employed (8-29 hours) | 05. Unemployed and actively seeking work | 06. A full-time student or pupil | 07. Retired from paid work | 08. Looking after the family or home | 09. Not working because temporary sick or injured | Not working because long-term sick or disabled | ELECTION STUDY NOTES - HONG KONG (2016): E2006 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 10. Others, not further specified | 13. Not applicable (never employed) | ELECTION STUDY NOTES - HUNGARY (2018): E2006 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 11. Maternity leave | 13. Other, inactive earner | ELECTION STUDY NOTES - IRELAND (2016): E2006 | | The answer categories for E2006 offered to respondents deviated | slightly from CSES MODULE 5 standards. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Working full time (30 hours or more) | 02. Working part-time | 05. Unemployed | 06. Full-time student | 07. Retired | 08. Homemaker, housekeeper or house person | ELECTION STUDY NOTES - ITALY (2018): E2006 | | Respondents were first asked if they had a paid job (no | information on working hours available) and if not, were asked | about their current status. The answers to these two questions | were used to code E2006, as shown below. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 1. Respondent has a paid job | 5. Unemployed | Not active (does not work, does not look for a | job) | Looking for the first job | Redundancy payment | 6. Student | 7. Retired | 8. Housework | 9. Not able to work | 10. Working Leave | 12. Military/Civil Service | ELECTION STUDY NOTES - MEXICO (2018): E2006 | | Respondents were asked about their main activity in the week | preceding the interview. Data were recoded as follows (no | information on working hours available): | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Employed | 05. Unemployed (did not work but looked for work) | 06. Student | 07. Retired or pensioned | 08. Home duties | 09. Permanently disabled | 11. Employed but did not work (due to vacations, | incapacity, sick leave) | ELECTION STUDY NOTES - NETHERLANDS (2017): E2006 | | In the Dutch 2017 study, respondents' employment status was | assessed by several successive survey questions. | Respondents were first asked if they currently had a paid job. | Respondents stating to have a paid job were then asked to | indicate the number of their weekly working hours, excluding | unpaid overtime. Respondents without a paid job at the time | of the interview were asked to provide further details on their | current situation. | The answers to these two questions were used to code E2006, as | shown below: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 1. Paid job, more than 32 working hours | 2. Paid job, 15 - 32 working hours | 3. Paid job, less than 15 working hours | 5. No paid job, unemployed | 6. No paid job, study / school | 7. No paid job, (pre-)pension | 8. No paid job, housekeeping / child care | 9. No paid job, illness / disability | 10. No paid job, other | 12. No paid job, volunteer work | 13. Paid job, number of working hours unknown | | Further, respondents stating to have a paid job but refusing to | name their weekly working hours were asked to group their | working hours in one of four broad categories, that have been | recoded as follows (N = 14): | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 1. Paid job, 30 hours a week or more | 2. Paid job, less than 30 hours | 3. Paid job, less than 12 hours | Paid job, less than 4 hours | ELECTION STUDY NOTES - NETHERLANDS (2021): E2006 | | This variable is from the pre-election survey. | | In the Dutch 2021 study, respondents' employment status was | assessed by several successive survey questions. All items were | included in the pre-election survey. | | Respondents were first asked what their main activity (i.e., | employment status) was. Afterward, respondents were asked | whether they currently had a paid job. In a follow-up question, | respondents stating to have a paid job indicated the number of | their weekly working hours, excluding unpaid overtime. | | The answers to these two questions were used to code E2006, as | shown below: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 1. Paid job, more than 32 working hours | 2. Paid job, 15 - 32 working hours | 3. Paid job, less than 15 working hours | 5. Unemployed; | No paid job | 6. Study/school | 7. (Pre-)pension | 8. Housekeeping/childcare | 9. Illness/disability | 10. Other | 12. Volunteer work | 13. Paid job, number of working hours unknown | | Further, respondents stating to have a paid job but refusing to | name their weekly working hours were asked to group their | working hours in one of four broad categories that have been | recoded as follows (N = 55): | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 1. Paid job, 30 hours a week or more | 2. Paid job, less than 30 hours | 3. Paid job, less than 12 hours | Paid job, less than 4 hours | | Finally, some respondents gave inconsistent answers across | questions. For example, some respondents stated to have a job | and gave their weekly working hours, although they grouped | themselves to be out of the labor force (codes 5 to 10 in | E2006). For these respondents, their out-of-the-labor force | status was coded for E2006. Another group of respondents stated | that paid work was their main activity but specified not to | have a paid job in the follow-up question. The first answer | (main activity) was coded for CSES. | ELECTION STUDY NOTES - NEW ZEALAND (2020): E2006 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 13. Unpaid outside home | ELECTION STUDY NOTES - PERU (2021): E2006 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 13. Independent work | ELECTION STUDY NOTES - SLOVAKIA (2020): E2006 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 13. Employed, number of working hours unknown | ELECTION STUDY NOTES - SWEDEN (2018): E2006 | | As the Swedish 2018 study consists of web and postal interviews, | respondents could mark multiple answers. Collaborators classified | these answers into one single variable, which was used for coding | E2006. Following their suggestion, students, pensioners and | respondents on sickness/activity compensation working for pay | were classified as students, pensioners, and being permanently | disabled, respectively. | Further, respondents were asked about their weekly working hours | in a separate survey question. Answers to this follow-up | question were used for specifying working hours of those in the | labor force. | | CSES Code Election Study Code/Category |--------------------------------------------------------------- | 01. Gainfully employed, full time | 02. Gainfully employed, part-time (at least 15 hours | per week) | 03. Gainfully employed, part-time (less than 15 hours | per week) | 05. Unemployed | 06. Student | Student and working for pay | 07. Old age pensioner / retired / agreement pensioner | Pensioner and working for pay | 09. Sickness and activity compensation (former early | retirement pension, sickness allowances) | Sickness/activity compensation and working for pay | 10. Other | 13. Work/training in employment policy measures | 14. Gainfully employed, no information on working | hours available | ELECTION STUDY NOTES - SWITZERLAND (2019): E2006 | | Collaborators note in Switzerland, a full time employment | generally starts from 40 hours per week. Hence, the first two | response categories are slightly different from CSES categories: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 1. Employed: Full Time (40 or more hours weekly) | 2. Employed: Part-Time (15 to 39 hours weekly) | ELECTION STUDY NOTES - UNITED STATES (2016): E2006 | | Coding for E2006 is based on the respondents' initial employment | status (variable V161277 in the original ANES dataset). | The original ANES dataset includes an additional category for | temporary unemployment (code 13). | The weekly working hours were asked separately and combined for | E2006. 12 respondents stated to be working now, but did not | indicate their weekly working hours. These respondents were | coded 14. | Some of the respondents who are coded as unemployed, retired, | permanently disabled, housewife/home duties, or student did | nevertheless indicate certain amounts of working hours per week. | Analysts interested in these data are advised to refer to the | original ANES dataset. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 13. Temporarily laid off | 14. Working, number of working hours unknown | ELECTION STUDY NOTES - UNITED STATES (2020): E2006 | | Coding for E2006 is based on the respondents' 2-digit occupation | status (variable V201533x in the original ANES 2020 dataset). | The original ANES dataset includes an additional category for | temporary unemployment (code 13). | The weekly working hours were asked separately and combined for | E2006. 43 respondents stated to be working now but did not | indicate their weekly working hours. These respondents were | coded 14. | Some of the respondents who are coded as unemployed, retired, | permanently disabled, housewife/home duties, or student did | nevertheless indicate certain amounts of working hours per week. | Analysts interested in these data are advised to refer to the | original ANES dataset. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Working now only, more than 32 hours a week | 02. Working now only, 15 - 32 hours a week | 03. Working now only, 14 hours or less a week | 05. Unemployed, no mention of retired, disabled, | homemaker or student | 06. Student, no other occupation | Student and working now, working <20 hours per | week or DK/RF hours | Working now and student, working 20+ hours/week | 07. Retired, no other occupation | Retired and working now, working <20 hours per | week or DK/RF hours | Working now and retired, working 20+ hours/week | 08. Homemaker, no other occupation | Homemaker and working now, working <20 hours per | week or DK/RF hours | Working now and homemaker, working 20+ hours/week | 09. Permanently disabled, not working | Perm. disabled and working now, working <20 hours | per week or DK/RF hours | Working now and perm. disabled, working 20+ | hours/week | 13. Temporarily laid off | 14. Working, number of working hours unknown | 99. Refused/Don't know/Inapplicable --------------------------------------------------------------------------- E2007 >>> MAIN OCCUPATION --------------------------------------------------------------------------- D07. Main occupation of respondent. .................................................................. ARMED FORCES OCCUPATIONS 00. ARMED FORCES OCCUPATIONS [NOT FURTHER SPECIFIED] 01. COMMISSIONED ARMED FORCES OFFICERS 02. NON-COMMISSIONED ARMED FORCES OFFICERS 03. ARMED FORCES OCCUPATIONS, OTHER RANKS MANAGERS 10. MANAGERS [NOT FURTHER SPECIFIED] 11. CHIEF EXECUTIVES, SENIOR OFFICIALS AND LEGISLATORS 12. ADMINISTRATIVE AND COMMERCIAL MANAGERS 13. PRODUCTION AND SPECIALIZED SERVICES MANAGERS 14. HOSPITALITY, RETAIL AND OTHER SERVICES MANAGERS PROFESSIONALS 20. PROFESSIONALS [NOT FURTHER SPECIFIED] 21. SCIENCE AND ENGINEERING PROFESSIONALS 22. HEALTH PROFESSIONALS 23. TEACHING PROFESSIONALS 24. BUSINESS AND ADMINISTRATION PROFESSIONALS 25. INFORMATION AND COMMUNICATIONS TECHNOLOGY PROFESSIONALS 26. LEGAL, SOCIAL AND CULTURAL PROFESSIONALS TECHNICIANS AND ASSOCIATE PROFESSIONALS 30. TECHNICIANS AND ASSOCIATE PROFESSIONALS [NOT FURTHER SPECIFIED] 31. SCIENCE AND ENGINEERING ASSOCIATE PROFESSIONALS 32. HEALTH ASSOCIATE PROFESSIONALS 33. BUSINESS AND ADMINISTRATION ASSOCIATE PROFESSIONALS 34. LEGAL, SOCIAL, CULTURAL AND RELATED ASSOCIATE PROFESSIONALS 35. INFORMATION AND COMMUNICATIONS TECHNICIANS CLERICAL SUPPORT WORKERS 40. CLERICAL SUPPORT WORKERS [NOT FURTHER SPECIFIED] 41. GENERAL AND KEYBOARD CLERKS 42. CUSTOMER SERVICES CLERKS 43. NUMERICAL AND MATERIAL RECORDING CLERKS 44. OTHER CLERICAL SUPPORT WORKERS SERVICE AND SALES WORKERS 50. SERVICE AND SALES WORKERS [NOT FURTHER SPECIFIED] 51. PERSONAL SERVICE WORKERS 52. SALES WORKERS 53. PERSONAL CARE WORKERS 54. PROTECTIVE SERVICES WORKERS SKILLED AGRICULTURAL, FORESTRY AND FISHERY WORKERS 60. SKILLED AGRICULTURAL, FORESTRY AND FISHERY WORKERS [NOT FURTHER SPECIFIED] 61. MARKET-ORIENTED SKILLED AGRICULTURAL WORKERS 62. MARKET-ORIENTED SKILLED FORESTRY, FISHING AND HUNTING WORKERS 63. SUBSISTENCE FARMERS, FISHERS, HUNTERS AND GATHERERS CRAFT AND RELATED TRADES WORKERS 70. CRAFT AND RELATED TRADES WORKERS [NOT FURTHER SPECIFIED] 71. BUILDING AND RELATED TRADES WORKERS, EXCLUDING ELECTRICIANS 72. METAL, MACHINERY AND RELATED TRADES WORKERS 73. HANDICRAFT AND PRINTING WORKERS 74. ELECTRICAL AND ELECTRONIC TRADES WORKERS 75. FOOD PROCESSING, WOOD WORKING, GARMENT AND OTHER CRAFT AND RELATED TRADES WORKERS PLANT AND MACHINE OPERATORS, AND ASSEMBLERS 80. PLANT AND MACHINE OPERATORS, AND ASSEMBLERS [NOT FURTHER SPECIFIED] 81. STATIONARY PLANT AND MACHINE OPERATORS 82. ASSEMBLERS 83. DRIVERS AND MOBILE PLANT OPERATORS ELEMENTARY OCCUPATIONS 90. ELEMENTARY OCCUPATIONS [NOT FURTHER SPECIFIED] 91. CLEANERS AND HELPERS 92. AGRICULTURAL, FORESTRY AND FISHERY LABORERS 93. LABORERS IN MINING, CONSTRUCTION, MANUFACTURING AND TRANSPORT 94. FOOD PREPARATION ASSISTANTS 95. STREET AND RELATED SALES AND SERVICE WORKERS 96. REFUSE WORKERS AND OTHER ELEMENTARY WORKERS OTHER CSES CODES 996. OTHER OR NON-CLASSIFIABLE OCCUPATIONS (NOT ENOUGH INFORMATION AVAILABLE TO CLASSIFY) 997. VOLUNTEERED: REFUSED 998. VOLUNTEERED: DON'T KNOW 999. MISSING | VARIABLE NOTES: E2007 | | E2007 details the respondent's main occupation; that is, the job | at which the respondent spends the most time or if the respondent | spends an equal amount of time on two jobs, it is the one from | which the respondent earns the most money. | For respondents who are currently employed, this variable reports | their current occupation. For respondents who are retired or not | currently working, E2007 reports respondent's last occupation. | | Coding conventions employ the first two digits of 2008 | ISCO / ILO International Standard Classification of Occupations | Code from the International Labor Office, CH-1211, Geneva 22, | Switzerland. | | An English-language description of the ISCO-08 standard can be | found here: | http:// | www.ilo.org/public/english/bureau/stat/isco/docs/resol08.pdf | (Date accessed: April 5, 2019) | | In some cases, it has not been possible to strictly adhere to the | two-digit ISCO/ILO conventions. Users will find that some | categories have been added to the ISCO/ILO list in order to | accommodate the occupations of respondents who were not easily | classified. These include categories referring to the first digit | of the 2008 ISCO / ILO occupations code. In these cases, zeros | were added to preserve the two-digit structure (e.g., | 90. ELEMENTARY OCCUPATIONS [NOT FURTHER SPECIFIED]). Please | refer to the Election Study Notes for clarification of the | meaning of the additional codes. | | See also VARIABLE NOTES for E2006. | | Data are unavailable for BRAZIL (2018), DENMARK (2019), GREAT | BRITAIN (2017 & 2019), HUNGARY (2018), PERU (2021), UNITED STATES | (2020) and URUGUAY (2019). | ELECTION STUDY NOTES - ALBANIA (2017): E2007 | | Respondents' occupation was provided in the deposited dataset in | accordance with ISCO scale, used by CSES for E2007. Collaborators | did not provide an explanation of whether the variable was asked | in the ISCO scale in the survey, or was it asked differently and | recoded to the ISCO scale. | ELECTION STUDY NOTES - BELGIUM-FLANDERS (2019): E2007 | | Respondents' occupation was asked in a series of open-ended | questions. Respondents were asked to write down their job title, | their most important tasks, and in which branch they work. This | was later recoded to ISCO scale by Collaborators. | ELECTION STUDY NOTES - BELGIUM-WALLONIA (2019): E2007 | | Respondents' occupation was asked in a series of open-ended | questions. Respondents were asked to write down their job title, | their most important tasks, and in which branch they work. This | was later recoded to ISCO scale by Collaborators. | ELECTION STUDY NOTES - CANADA (2019): E2007 | | Students, housewives and retired respondents were set to | missing, as these respondents already indicated their current | employment status in E2006. | ELECTION STUDY NOTES - EL SALVADOR (2019): E2007 | | The study contained the category "77. Never worked." These | respondents are recoded into "999. MISSING" for E2007. | ELECTION STUDY NOTES - GREECE (2019): E2007 | | Respondents' main occupation was assessed with two consecutive | survey questions. Respondents were first asked to provide their | occupation based on two-digit ISCO08 codes. In a follow-up | question, respondents were requested to name their occupation | based on more fine-grained ISCO08 3-digit codes. Both questions | included an open-ended "Other" option, allowing respondents to | provide further details on their occupation. Where possible, | Collaborators assigned open-ended answers manually to ISCO | codes. Respondents providing no or insufficient information | for classification (e.g., "I work in the public sector") were | coded to "996. OTHER NON-CLASSIFIABLE OCCUPATIONS". | ELECTION STUDY NOTES - ICELAND (2016 & 2017): E2007 | | In the original study, 20 respondents were coded as "Sailors." | These were coded into code "83. DRIVERS AND MOBILE PLANT | OPERATORS" which includes ships' deck crews and related workers | according to the ILO coding scheme. | ELECTION STUDY NOTES - INDIA (2019): E2007 | | The Indian 2019 study groups respondents according to the ten | major ISCO-08 groups, the most general groups comprising only | the first digit of the ISCO coding scheme. | ELECTION STUDY NOTES - ITALY (2018): E2007 | | The answer categories for E2007 offered to respondents deviated | from CSES MODULE 5 standards (ISCO codes). These were recoded | accordingly where sufficient information was available to place | respondents in one of the ISCO categories. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 10. Manager | Management Career | 40. High-Level Clerk | Low-Level Clerk | 23. Teacher | 63. Farmer | 996. Skilled Worker | Manual Worker | Entrepreneur (6 or more employees) | Small Entrepreneur (5 or fewer employees) | Shop-Owner | Freelance Worker | Partner in cooperative business | Occasional Freelance Worker | Working in the family business | 997. Refused | 998. Don't know/Don't remember | ELECTION STUDY NOTES - JAPAN (2017): E2007 | | The occupation of respondents was asked using the ISCO-08 scale | in the original Japanese questionnaire. | ELECTION STUDY NOTES - LITHUANIA (2016): E2007 | | The study contained the category "0. Never worked." These | respondents are recoded into "999. MISSING" for E2007. | ELECTION STUDY NOTES - LITHUANIA (2020): E2007 | | The study included the category "99. R was never employed". | The associated respondents were recoded to "999. MISSING" for | E2007 (N = 19). | ELECTION STUDY NOTES - NETHERLANDS (2017 & 2021): E2007 | | For respondents from the Dutch 2021 study, this variable is from | the pre-election survey. | | Both Dutch studies group respondents according to the ten | major ISCO-08 groups, the most general groups comprising only | the first digit of the ISCO coding scheme. | ELECTION STUDY NOTES - ROMANIA (2016): E2007 | | The occupation of respondents was asked using a series of | four questions. These were, in order they were asked in the | original questionnaire: | 1. What is/was the name of the work (position) that you | carry/carried out (at the main workplace)? (Open-ended question) | 2. What is the sector of activity in which you work/have worked? | (Close-ended question) | 3. So, we can say that your occupation is/was...? (Close-ended | question, using ISCO two-digit codes) | 4. What kind of activity do you do/did you do at this job most of | the time? (Open-ended question) | | From these four questions, coders later retrieved new ISCO two | digit codes for the occupation of each respondent. Collaborators | noted several corrections to the coding of ISCO codes were made | using all the available information. | ELECTION STUDY NOTES - SLOVAKIA (2020): E2007 | | In the original Slovakian study, respondents' main occupation | was asked as a set of the following three open-ended questions: | - Title/Name of the occupation | - Area/Field | - Content of your job (describe what you are doing in your job) | | These questions were recoded by Collaborators into a single item | for respondents' occupation, coded based on ISCO. In so doing, | Collaborators created a joint code for non-classifiable | occupations and other missing values reading as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 998. Don't know, no response, cannot be classified | ELECTION STUDY NOTES - SOUTH KOREA (2016): E2007 | | Students and housewives were set to missing, as these | respondents already indicated their current employment status | in E2006. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 50. Sales and service worker | 60. Agricultural, forestry and fishery worker | 996. Public officer, working in public organizations | Manager and professional | Office worker | Labor worker | Own business | 999. Student | Housewife | ELECTION STUDY NOTES - UNITED STATES (2016): E2007 | | In the 2016 American National Election Study, respondents' main | occupation was coded according to the 97 minor groups identified | by the 2010 Standard Occupational Classification (SOC) system. | SOC codes were translated to ISCO 08 with a correspondence | table provided by the U.S. Bureau of Labor Statistics, which can | be accessed here: https://www.bls.gov/soc/soccrosswalks.htm | (Date last accessed: March 17, 2019). | As SOC codes do not translate well into ISCO 08 codes, only 35 | out of 97 SOC-categories could be recoded to ISCO 08. | Therefore, E2007 is available for 830 respondents only. --------------------------------------------------------------------------- E2008 >>> SOCIO ECONOMIC STATUS --------------------------------------------------------------------------- D07a. Respondent's socio economic status. .................................................................. 1. WHITE COLLAR 2. WORKER 3. FARMER 4. SELF-EMPLOYED 5. [SEE ELECTION STUDY NOTES] 7. VOLUNTEERED: REFUSED 8. VOLUNTEERED: DON'T KNOW 9. MISSING | VARIABLE NOTES: E2008 | | The categories provided in E2008 are intended to distinguish | among the following groups: | | 1. White Collar: | Broad occupational grouping of workers engaged in non-manual | labor: Managers, salaried professionals, office workers, | sales personnel, and proprietors are generally included in | the category. | | 2. Worker: | Broad occupational grouping of workers engaged in manual labor. | | 3. Farmer: | Normally persons self-employed in farming. | | 4. Self-Employed: | Self-employed occupations of all kinds, excluding self-employed | farming. Includes, for example entrepreneurs, shop keeper, | professionals like lawyers, medical doctors etc. | | This variable was not part of the CSES MODULE 5 pilot | questionnaire. | | There is some inconsistency between studies in the way | the responses to the questions about current employment status | (E2006) affected the application of the follow-up occupation | variables (E2008, E2009). The CSES standard is that the | occupation variables are asked from those in the labor force. | However, in some cases, for respondents categorized as not in | the labor force in E2006 (codes 6-12) the occupation variables | may report respondent's last occupation. Hence, the responses | concerning occupation that belong to respondents not in the | labor force presumably reflect their previous or last | occupation. | | Data on E2008 for respondents out of labor force are available | for COSTA RICA (2018), CZECHIA (2017 & 2021), DENMARK (2019), | EL SALVADOR (2019), FINLAND (2019), FRANCE (2017), GERMANY (2017 | & 2021), GREAT BRITAIN (2017 & 2019), HUNGARY (2018), ICELAND | (2016 & 2017), ISRAEL (2020), LITHUANIA (2020), MEXICO (2018), | MONTENEGRO (2016), NETHERLANDS (2017 & 2021), NEW ZEALAND (2017 | & 2020), NORWAY (2017), POLAND (2019), ROMANIA (2016), SLOVAKIA | (2020), SWEDEN (2018), THAILAND (2019) and URUGUAY (2019). | | Data are unavailable for AUSTRALIA (2019), BELGIUM-FLANDERS | (2019), BELGIUM-WALLONIA (2019), BRAZIL (2018), CANADA (2019), | CHILE (2017), GREECE (2015), HONG KONG (2016), IRELAND (2016), | PORTUGAL (2019), SWITZERLAND (2019), TAIWAN (2016 & 2020), | TUNISIA (2019) and UNITED STATES (2016 & 2020). | ELECTION STUDY NOTES - ALBANIA (2017): E2008 | | The deposited dataset contained a wild code 0, a value assigned | to 934 respondents. Since Collaborators did not provide an | explanation for this, these respondents are set to "9. missing" | for E2008. | ELECTION STUDY NOTES - COSTA RICA (2018): E2008 | | The Costa Rican study did not apply a skip pattern. This | resulted in 16 respondents who reported not to be in labor | force (E2006) to be asked about their socio-economic status. | ELECTION STUDY NOTES - CZECHIA (2017): E2008 | | For respondents who were not in the labor force, E2008 refers | to their previous occupation resulting in 473 respondents who | reported not to be in the labor force (E2006) to be asked about | their socio-economic status. | ELECTION STUDY NOTES - CZECHIA (2021): E2008 | | For respondents who were not in the labor force, E2008 refers | to their previous occupation resulting in 430 respondents who | reported not to be in the labor force (E2006) to be asked about | their socio-economic status. | ELECTION STUDY NOTES - DENMARK (2019): E2008 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Salaried employee without management | responsibility | Salaried employee with management responsibility | 02. Worker, unskilled (not specialist worker) | Worker, unskilled (specialist worker) | Worker, skilled | 04. Self-employed (including farmers) | | Respondents out of the labor force have been asked this question | concerning their previous occupation. | ELECTION STUDY NOTES - EL SALVADOR (2019): E2008 | | For respondents who were not in the labor force, E2008 refers | to their previous occupation resulting in 478 respondents who | reported not to be in the labor force (E2006) to be asked about | their socio-economic status. | ELECTION STUDY NOTES - FINLAND (2019): E2008 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Lower managerial/professional employee | Intermediate level employee | Higher managerial employee | 02. Worker | 03. Farmer | 04. Employer, self-employed, own account worker | ELECTION STUDY NOTES - FRANCE (2017): E2008 | | Respondents' socio-economic status was pre-coded by Collaborators | based on a combination of respondents' occupation and their | professional status. | All farmers, including those stating to be self-employed, were | coded into the 'farmers' category. All other independent workers | were classified as being self-employed. | | Retired or unemployed respondents were asked this question with | regards to their previous occupation (applies to 708 cases). | ELECTION STUDY NOTES - GERMANY (2017): E2008 | | Only respondents currently employed part-time or full-time were | asked this question although four respondents who reported to be | students report their socio-economic status as well. Respondents | under vocational training and helping family members were set to | missing. | ELECTION STUDY NOTES - GERMANY (2021): E2008 | | For the German 2021 study, E2008 was coded based on respondents' | profession, as detailed in the table below. | Further, only respondents currently employed part-time or full- | time were asked this question. Collaborators set respondents | under vocational training and helping family members to missing. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Employee: | - Foreman and head workman in employment | - Employee with simple duties | - Employee under loose supervision carrying out | complex tasks independently | - Employee carrying out responsible tasks | independently or with limited responsibility | for others | - Employee with wide managerial responsibilities | and decision- making powers | Officials /judges / professional soldier: | - Lower/Middle/Upper/Higher grade of the civil | service, judges | 02. Worker: | - Unskilled and semiskilled worker | - Skilled worker and crafter | - Foreman, master, site foreman | 03. Independent farmer | 04. Independent professional (e.g. doctor in private | practice, lawyer): | - Without employees / 1-9 employees / 10 | employees and more | Self-employed in trade or craft, industry, | service sector, etc.: | - Without employees / 1-9 employees / 10 | employees and more | 09. Family member assisting in family business | In vocational training | ELECTION STUDY NOTES - GREAT BRITAIN (2017): E2008 | | For respondents who were not in the labor force, E2008 refers | to their previous occupation resulting in 446 respondents who | reported not to be in the labor force (E2006) to be asked about | their socio-economic status. | ELECTION STUDY NOTES - GREAT BRITAIN (2019): E2008 | | For respondents who were not in the labor force, E2008 refers | to their previous occupation resulting in 840 respondents who | reported not to be in the labor force (E2006) to be asked about | their socio-economic status. | ELECTION STUDY NOTES - HUNGARY (2018): E2008 | | This variable was derived from three separate variables in the | original Election Study. Firstly, respondents were asked whether | their work involved manual or clerical/non-manual labor. | Respondents engaging primarily in non-manual labor are coded | 1. WHITE COLLAR in E2008, whereas manual laborers are coded as | 2. WORKER. | Furthermore, respondents stating to work in agriculture, | forestry, or water management in another question on the | employment sector are coded as 3. FARMER, as are respondents who | indicated to be self-employed farmers when asked about their | occupation. | Finally, respondents answering to be self-employed white collars | or individual entrepreneurs to the occupation question are coded | 4. SELF-EMPLOYED in CSES. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Clerical or other non-manual labor | 02. Manual labor | 03. (was) self-employed, worker/farmer | Agriculture, forestry, water management | 04. (was) self-employed, white collar (doctors, | lawyers, etc.) | (was) individual entrepreneur | ELECTION STUDY NOTES - ICELAND (2016 & 2017): E2008 | | This variable was derived by the Collaborators from two separate | variables, one asking respondents if they owned a business (and | if yes, if they had employees) and the other one asking about | the respondents' occupation. | ELECTION STUDY NOTES - INDIA (2019): E2008 | | The variable assessing respondents' socio-economic status in the | Indian 2019 study only distinguishes between self-employed and | respondents working part-time or full-time. For E2008, it has | been recoded as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 04. Self-employed | 05. Full time (~30 hours) | Part time (< 30 hours) | ELECTION STUDY NOTES - ISRAEL (2020): E2008 | | The Israeli study did not apply a skip pattern. This resulted | in 203 respondents who reported not to be in labor force (E2006) | to be asked about their socio-economic status. Most likely, | respondents who are retired or unemployed interpreted this | question in terms of their previous occupation. | ELECTION STUDY NOTES - ITALY (2018): E2008 | | This variable was derived from three separate variables in the | original Election Study and its categories were recoded as | follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Manager | Management Career | Teacher | High-level Clerk | Lower-level Clerk | Skilled Worker | 02. Manual worker | 03. Farmer (Self-employed) | 04. Self-employed | ELECTION STUDY NOTES - JAPAN (2017): E2008 | | The high number of missing cases for this variable is because | Collaborators decided not to ask this question to respondents who | said that they did not work for payment. In total 549 respondents | answered that, and are thus classified as missing for E2008. | ELECTION STUDY NOTES - LITHUANIA (2020): E2008 | | Collaborators derived E2008 from three separate variables, two | asking about respondents' specific occupation, and the third one | asking whether respondents were self-employed or salaried. For | respondents out of the labor force, E2008 refers to their | previous occupation. | | E2008 was derived as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Salaried employee working as any of the following: | Senior or mid-level manager | Highly qualified specialist / professional | Office-worker, clerk, institution employee | Trade and services employee | 02. Salaried employee working as any of the following: | Skilled worker | Unskilled worker | 03. Self-employed and working in agricultural sector | (Occupation (E2007) = 61, 63 or 92) | 04. Self-employed | 07. Refused | 08. Don't know | 09. Missing; | Military, police, security or rescue services | personnel | ELECTION STUDY NOTES - MEXICO (2018): E2008 | | For the Mexican 2018 study, E2008 originates from the same | variable as E2009 (Employment Type). In E2008, the variable | distinguishes between self-employed respondents and all other | groups: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 04. Business owner | Independent practice | 05. Government (Federal, State or Municipal) | Government company (parastatal) or decentralized | agency | Private company | Non-profit association, company or institution | Mixed | 09. Currently not working | | The deposited 2018 Mexican study also includes a socio-economic | status measure based on the standardized Niveles Socio | Economicos index (NSE), classifying respondents into seven | levels based on the most important household needs. As this | index was challenging to translate to the CSES coding scheme, it | was not used for coding E2008. Researchers interested in the | NSE measure are hence referred to the source dataset. | | 77 respondents provided their socio economic status, although | they were out of the labor force according to E2006. | Collaborators note some of these discrepancies might result from | "informal jobs", i.e., productive activities not formally | recorded (most notably homemakers selling some food or products | in an informal setting, but classifying themselves as business | owners). | ELECTION STUDY NOTES - MONTENEGRO (2016): E2008 | | The Montenegrin study did not apply a skip pattern due to a high | unemployment rate at the time of the survey. This resulted in | 115 respondents who reported not to be in labor force (E2006) | to be asked about their socio-economic status. | ELECTION STUDY NOTES - NETHERLANDS (2017): E2008 | | The variable assessing respondents' socio-economic status in the | Dutch 2017 study only distinguishes between self-employed and | salaried respondents. For E2008, it has been recoded as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 04. Independent | 05. Salaried employee | ELECTION STUDY NOTES - NETHERLANDS (2021): E2008 | | This variable is from the pre-election survey. | | For the Dutch 2021 study, E2008 originates from the same | variable as E2009 (Employment Type). In E2008, the variable | distinguishes between self-employed respondents and all other | groups: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 04. Independent | 05. Salaried employee in a business | Salaried employee in government institution | Salaried employee in a practice | Salaried employee in a foundation | | Collaborators note the term "practice" (or "praktijk" in Dutch) | may refer to the work by (and for) a lawyer, notary, or doctor. | ELECTION STUDY NOTES - NEW ZEALAND (2017): E2008 | | This variable was derived from three separate variables. Two | from the original Election Study, and E2007. | For respondents who were not in the labor force, E2008 refers | to their previous occupation, resulting in 650 respondents who | reported not to be in the labor force (E2006) to be asked about | their socio-economic status. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Labor (Occupation (E2007) < 60) | 02. Labor (Occupation (E2007) > 60) | 03. (was) self-employed, farmer | 04. (was) self-employed, worker/ white collar | ELECTION STUDY NOTES - NEW ZEALAND (2020): E2008 | | For respondents who were not in the labor force, E2008 refers | to their previous occupation, resulting in 563 respondents who | reported not to be in the labor force (E2006) to be asked about | their socio-economic status. | ELECTION STUDY NOTES - NORWAY (2017): E2008 | | For respondents who were not in the labor force, E2008 refers | to their previous occupation resulting in 389 respondents | who reported not to be in the labor force (E2006) to be asked | about their socio-economic status. | ELECTION STUDY NOTES - PERU (2021): E2008 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 05. Unpaid family worker | ELECTION STUDY NOTES - SLOVAKIA (2020): E2008 | | The deposited variable on respondents' socio-economic status in | the Slovakian study did not match the categories CSES uses for | E2008. Thus, this variable is created from the deposited | variable and ISCO codes for the variable E2007. The following | recodes have been made: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Employee and ISCO occupation codes 59 and lower | 02. Employee and ISCO occupation codes 60 and higher | 04. Self-employed (without employees) | Self-employed/enterpreneur wih employee | ELECTION STUDY NOTES - SOUTH KOREA (2016): E2008 | | Because South Korea ran the pilot questionnaire, E2008 was not | included in the 2016 South Korean election study. However, | E2008 was constructed from E2007, as indicated below. | Students and housewives were set to missing, as these | respondents already indicated their current employment status | in E2006. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Public officer, working in public organizations | Manager and professional | Office worker | Sales and service worker | 02. Labor worker | 03. Agricultural, forestry and fishery worker | 04. Own business | 09. Student | Housewife | ELECTION STUDY NOTES - SWEDEN (2018): E2008 | | Respondents out of the labor force have been asked this question | with respect to their previous occupation. | Further, the coding scheme employed by the Swedish 2018 study to | classify occupational groups is more fine-grained than that | envisaged by CSES. The following table lists how the original | variable has been recoded for E2008: | | CSES Code Election Study Code/Category |-------------------------------------------------------- | 01. White-collar worker | White-collar worker with a leading organizational | function | White-collar worker with an executive function | 02. Blue-collar worker | Blue-collar worker with a leading function | 03. Farmer: no employees | Farmer: one or more employees | 04. Self-employed: no employees | Self-employed: 1-9 employees | Self-employed: 10 or more employees | 05. Other answer | ELECTION STUDY NOTES - THAILAND (2019): E2008 | | Retired or unemployed respondents were asked this question with | respect to their previous occupation (applies to 105 cases). | ELECTION STUDY NOTES - URUGUAY (2019): E2008 | | For respondents who were either "05. UNEMPLOYED" or "07. | RETIRED" (E2006), E2008 refers to their previous occupation | resulting in 307 respondents who reported not to be in the labor | force (E2006) to be asked about their socio-economic status. | Data on 162 respondents who reported to be "06. STUDENT", "08. | HOUSEWIFE" or "10. OTHERS, NOT IN LABOR FORCE" (E2006) are | unavailable and therefore coded as "9. MISSING" for E2008. --------------------------------------------------------------------------- E2009 >>> EMPLOYMENT TYPE - PUBLIC OR PRIVATE --------------------------------------------------------------------------- D08. Whether respondent's employment is private or public. .................................................................. 1. PUBLIC SECTOR 2. PRIVATE SECTOR 3. MIXED 4. "THIRD SECTOR"/NON-PROFIT SECTOR 5. [SEE ELECTION STUDY NOTES] 6. [SEE ELECTION STUDY NOTES] 7. VOLUNTEERED: REFUSED 8. VOLUNTEERED: DON'T KNOW 9. MISSING | VARIABLE NOTES: E2009 | | There is some inconsistency between studies in the way the | responses to the questions about current employment status | (E2006) affected the application of the follow-up occupation | variables (E2008, E2009). The CSES standard is that the | occupation variables are asked from those in the labor force. | However, in some cases, for respondents categorized as not in | the labor force in E2006 (codes 6-12) the occupation variables | may report respondent's last occupation. Hence, the responses | concerning occupation that belong to respondents not in the | labor force presumably reflect their previous or last occupation. | | See also VARIABLE NOTES for E2006. | | Data on E2009 for respondents out of labor force are available | for BELGIUM-FLANDERS (2019), BELGIUM-WALLONIA (2019), | BRAZIL (2018), CANADA (2019), CHILE (2017), COSTA RICA (2018), | CZECHIA (2017 & 2021), DENMARK (2019), FINLAND (2019), FRANCE | (2017), GERMANY (2017 & 2021), GREAT BRITAIN (2019), GREECE | (2015), HUNGARY (2018), ICELAND (2016), ISRAEL (2020), LATVIA | (2018), LITHUANIA (2020), MEXICO (2018), MONTENEGRO (2016), | NETHERLANDS (2017 & 2021), NEW ZEALAND (2017 & 2020), PERU | (2021), POLAND (2019), PORTUGAL (2019), ROMANIA (2016), SWEDEN | (2018), SWITZERLAND (2019), TAIWAN (2016 & 2020), THAILAND | (2019), UNITED STATES (2020) and URUGUAY (2019). | | Data are unavailable for GREAT BRITAIN (2017), SLOVAKIA (2020), | SOUTH KOREA (2016) and UNITED STATES (2016). | ELECTION STUDY NOTES - ALBANIA (2017): E2009 | | The deposited dataset contained a wild code 0, a value assigned | to 934 respondents. Since Collaborators did not provide an | explanation for this, these respondents are set to "9. missing" | for E2009. | ELECTION STUDY NOTES - AUSTRALIA (2019): E2009 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 05. Self-employed | 06. An employee in a family business or farm | ELECTION STUDY NOTES - BRAZIL (2018): E2009 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Employee/public sector | 02. Owner/employee/private sector | 04. Owner/employee/third sector/NGO | 05. Autonomous | 06. Agricultural worker | Registered home stay employee | Unregistered home stay employee | ELECTION STUDY NOTES - CHILE (2017): E2009 | | For respondents not in the labor force (E2006), the question was | asked with respect to their previous employment. | ELECTION STUDY NOTES - COSTA RICA (2018): E2009 | | The Costa Rican study did not apply a skip pattern. This | resulted in 11 respondents who reported not being in the labor | force (E2006) to be asked about their employment type. | ELECTION STUDY NOTES - CZECHIA (2017 & 2021): E2009 | | For respondents not in the labor force (E2006), the question was | asked with respect to their previous employment. | ELECTION STUDY NOTES - DENMARK (2019): E2009 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Public: state | Public: region | Public: municipality | 02. Private | 03. Mixed | 04. Non-profit organization | | Respondents out of the labor force have been asked this question | concerning their previous occupation. | ELECTION STUDY NOTES - FRANCE (2017): E2009 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. State worker | Employee in public firm | 02. Independent worker | Head of business, auto-entrepreneur | Collaborator in the family business | Employee in private firm | 04. Employee in an association or nonprofit | organization | | Retired or unemployed respondents were asked this question | with regards to their previous occupation (applies to 705 | cases). | ELECTION STUDY NOTES - GERMANY (2017 & 2021): E2009 | | This variable only includes respondents who were at least part- | time employed or in vocational training based on E2006 and those | that were not self-employed according to E2008. | ELECTION STUDY NOTES - GREAT BRITAIN (2019): E2009 | | For respondents not in the labor force (E2006), the question was | asked with respect to their previous employment. | ELECTION STUDY NOTES - ISRAEL (2020): E2009 | | The Israeli study did not apply a skip pattern. This resulted | in 210 respondents who reported not to be in the labor force | (E2006) to be asked about their employment type. Most likely, | respondents who are retired or unemployed interpreted this | question in terms of their previous occupation. | ELECTION STUDY NOTES - LITHUANIA (2020): E2009 | | For respondents out of the labor force, E2009 refers to their | previous occupation. | ELECTION STUDY NOTES - MEXICO (2018): E2009 | | For the Mexican 2018 study, E2009 originates from the same | variable as E2008 (Socio Economic Status). E2009 was coded as | follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Government (Federal, State or Municipal) | Government company (parastatal) or decentralized | agency | 02. Private company | Business owner | Independent practice | 03. Mixed | 04. Non-profit association, company or institution | 09. Currently not working | | 77 respondents provided their employment type, although they | were out of the labor force according to E2006. | Collaborators note some of these discrepancies might result from | "informal jobs", i.e., productive activities not formally | recorded (most notably homemakers selling some food or products | in an informal setting, but classifying themselves as business | owners). | ELECTION STUDY NOTES - NETHERLANDS (2017): E2009 | | The variable assessing respondents' employment type in the | Dutch 2017 study only distinguishes between respondents employed | in government and respondents employed in the private sector by | a company or an institution. Other answer options were not | available to respondents. | ELECTION STUDY NOTES - NETHERLANDS (2021): E2009 | | This variable is from the pre-election survey. | | For the Dutch 2021 study, E2009 originates from the same | variable as E2008 (Socio-Economic Status). E2009 was coded as | follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Salaried employee in government institution | 02. Salaried employee in a business | Salaried employee in a practice | Independent | 04. Salaried employee in a foundation | | Collaborators note the term "practice" (or "praktijk" in Dutch) | may refer to the work by (and for) a lawyer, notary, or doctor. | ELECTION STUDY NOTES - NEW ZEALAND (2017 & 2020): E2009 | | For respondents not in the labor force (E2006), the question was | asked with respect to their previous employment. | ELECTION STUDY NOTES - HUNGARY (2018): E2009 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. (was) employee of state-owned company (state | ownership min. 50%) | (was) employee in public administration, law | enforcement or armed forces | (was) employee in the public sector (e.g. health, | education, etc.) | 02. (was) employee of a private company with no | shares in the firm exceeding 1% | (was) owner or shareholder of a company | (was) self-employed, white-collar (doctors, | lawyers, etc.) | (was) self-employed, worker/farmer | (was) individual entrepreneur | 03. (was) member of a cooperative | ELECTION STUDY NOTES - MONTENEGRO (2016): E2009 | | The Montenegrin study did not apply a skip pattern due to a high | unemployment rate at the time of the survey. | ELECTION STUDY NOTES - PERU (2021): E2009 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 05. Independent or other occupation | | The distribution of this variable shows that 396 respondents | chose "Volunteered: Don't know." This number is likely so high | because work in the informal sector in Peru does not fit into | any of the response categories. Informal work in Peru is defined | as a business that is not legally established and whose workers | do not receive work benefits such as vacation or health | insurance. The informal sector in Peru generates 19% of GDP and | informal workers account for 73% of the labor force. | ELECTION STUDY NOTES - PORTUGAL (2019): E2009 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Public worker (local or central administration/ | public entities/ public enterprise) | 02. Private sector worker (employee) | Private sector worker (self-employed) | 03. Mixed sector work (public-private) | 04. Non-profit worker | ELECTION STUDY NOTES - SWEDEN (2018): E2009 | | Respondents out of the labor force have been asked this question | with respect to their previous occupation. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. State service | Local government service | Regional government service | 02. Private sector | 04. Non-profit organization or foundation | ELECTION STUDY NOTES - TAIWAN (2016 & 2020): E2009 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 05. Others | ELECTION STUDY NOTES - THAILAND (2019): E2009 | | Retired or unemployed respondents were asked this question with | respect to their previous occupation (applies to 35 cases). | ELECTION STUDY NOTES - UNITED STATES (2020): E2009 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Local government (for example: city or county | school district) | State government (including state colleges/ | universities) | Federal government civilian employee | 02. For-profit company or organization | Owner of non-incorporated business, professional | practice, or farm | Owner of incorporated business, professional | practice, or farm | Worked without pay in a for-profit family | business or farm for 15 hours or more | 04. Non-profit organization (including tax-exempt and | charitable organizations) | 05. Active duty U.S. Armed Forces or Commissioned | Corps | 07. Refused | 09. Inapplicable | ELECTION STUDY NOTES - URUGUAY (2019): E2009 | | For respondents who were either "05. UNEMPLOYED" or "07. | RETIRED" (E2006), E2009 refers to their previous occupation | resulting in 307 respondents who reported not to be in the labor | force (E2006) to be asked about their employment type. | Data on 162 respondents who reported to be "06. STUDENT", "08. | HOUSEWIFE" or "10. OTHERS, NOT IN LABOR FORCE" (E2006) are | unavailable and therefore coded as "9. MISSING" for E2009. --------------------------------------------------------------------------- E2010 >>> HOUSEHOLD INCOME - QUINTILES --------------------------------------------------------------------------- Household income quintile appropriate to the respondent. .................................................................. 1. LOWEST HOUSEHOLD INCOME QUINTILE 2. SECOND HOUSEHOLD INCOME QUINTILE 3. THIRD HOUSEHOLD INCOME QUINTILE 4. FOURTH HOUSEHOLD INCOME QUINTILE 5. HIGHEST HOUSEHOLD INCOME QUINTILE 6. [SEE ELECTION STUDY NOTES] 7. VOLUNTEERED: REFUSED 8. VOLUNTEERED: DON'T KNOW 9. MISSING | VARIABLE NOTES: E2010 | | E2010 details respondents' household income in quintiles, where | ranges shown represent sample quintiles (not population | quintiles). | | Where data were deposited in this format, income ranges shown | are as originally reported by Collaborators including gaps | between contiguous sets of ranges. | | Where deposited income data were not grouped into sample | quintiles, the data have been recoded into quintiles, according | to sample proportions (not national statistics). For cases where | it was not possible to compute sample quintiles, the income | categories approximating sample quintiles the closest have been | used. Consequently, this variable may contain distributions that | do not really represent quintiles. | | Depending on how the income data was deposited, the variable | reports either monthly or annual income. The table below shows | which of the two applies to the election studies: | | +++ TABLE: INCOME MEASURE TYPE BY ELECTION STUDY | | POLITY (ELEC YEAR) MONTHLY INCOME ANNUAL INCOME | ------------------------------------------------------------- | ALBANIA (2017) X - | AUSTRIA (2017) X - | BRAZIL (2018) X - | BELGIUM-FLANDERS (2019) X - | BELGIUM-WALLONIA (2019) X - | CANADA (2019) X - | CHILE (2017) X - | COSTA RICA (2018) X - | CZECHIA (2017) X - | CZECHIA (2021) X - | DENMARK (2019) - X | EL SALVADOR (2019) X - | FINLAND (2019) - X | FRANCE (2017) X - | GERMANY (2017) X - | GERMANY (2021) X - | GREAT BRITAIN (2017) - X | GREAT BRITAIN (2019) - X | GREECE (2015) - X | GREECE (2019) - X | HONG KONG (2016) X - | HUNGARY (2018) X - | IRELAND (2016) - X | ICELAND (2016) X - | ICELAND (2017) X - | INDIA (2019) X - | ISRAEL (2020) X - | ITALY (2018) - X | JAPAN (2017) - X | LATVIA (2018) X - | LITHUANIA (2016) X - | LITHUANIA (2020) X - | MEXICO (2018) X - | MONTENEGRO (2016) X - | NEW ZEALAND (2017) - X | NEW ZEALAND (2020) - X | NORWAY (2017) - X | PERU (2021) X - | POLAND (2019) X - | PORTUGAL (2019) X - | ROMANIA (2016) X - | SLOVAKIA (2020) X - | SOUTH KOREA (2016) X - | SWEDEN (2018) - X | SWITZERLAND (2019) - X | TAIWAN (2016) X - | TAIWAN (2020) X - | THAILAND (2019) - X | TUNISIA (2019) - X | TURKEY (2018) X - | UNITED STATES (2016) - X | UNITED STATES (2020) - X | URUGUAY (2019) X - | ------------------------------------------------------------- | KEY: X = yes; - = no. | | In the Election Study Notes below, currency abbreviations are | given in the three-letter alphabetical ISO-4217 format as | described by the International Organization for Standardization. | An English-language description of the ISO-4217 standard can be | found here: | https://www.iso.org/iso-4217-currency-codes.html | (Date accessed: April 5, 2019) | | Data are unavailable for AUSTRALIA (2019) and NETHERLANDS (2017). | ELECTION STUDY NOTES - ALBANIA (2017): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Less than 10,000 ALL | 02. 10,000 - 19,000 ALL | 03. 20,000 - 29,999 ALL | 04. 30,000 - 39,999 ALL | 05. More than 39,999 ALL | ELECTION STUDY NOTES - AUSTRIA (2017): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 1,350 EUR | 02. 1,350 - 1,950 EUR | 03. 1,950 - 2,400 EUR | 04. 2,400 - 3,300 EUR | 05. more than 3,300 EUR | ELECTION STUDY NOTES - BELGIUM-FLANDERS (2019): E2010 | | CSES Code Election Study Code/Category |------------------------------------------------------------------ | 01. up to 1,500 EUR | 02. 1,501 - 2,000 EUR | 03. 2,001 - 3,000 EUR | 04. 3,001 - 4,000 EUR | 05. more than 4,000 EUR | ELECTION STUDY NOTES - BELGIUM-WALLONIA (2019): E2010 | | CSES Code Election Study Code/Category |------------------------------------------------------------------ | 01. up to 1,500 EUR | 02. 1,501 - 2,000 EUR | 03. 2,001 - 3,000 EUR | 04. 3,001 - 4,000 EUR | 05. more than 4,000 EUR | ELECTION STUDY NOTES - BRAZIL (2018): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. up to 954 BRL | 02. 955 - 1,500 BRL | 03. 1,501 - 2,000 BRL | 04. 2,001 - 3,200 BRL | 05. more than 3,200 BRL | ELECTION STUDY NOTES - CANADA (2019): E2010 | | The variable is from the pre-election study. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 40,001 CAD | 02. 40,001 - 67,000 CAD | 03. 67,001 - 100,000 CAD | 04. 100,001 - 150,000 CAD | 05. more than 150,000 CAD | ELECTION STUDY NOTES - CHILE (2017): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 224,000 CLP | 02. 224,001 - 358,000 CLP | 03. 358,001 - 448,000 CLP | 04. 448,001 - 1,000,000 CLP | 05. more than 1,000,000 CLP | ELECTION STUDY NOTES - COSTA RICA (2018): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 200,001 CRC | 02. 200,001 - 310,000 CRC | 03. 310,001 - 500,000 CRC | 04. 500,001 - 1,000,000 CRC | 05. more than 1,000,001 CRC | ELECTION STUDY NOTES - CZECHIA (2017): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 16,000 CZK | 02. 16,000 - 25,999 CZK | 03. 26,000 - 34,999 CZK | 04. 35,000 - 39,999 CZK | 05. more than 40,000 CZK | ELECTION STUDY NOTES - CZECHIA (2021): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 20,000 CZK | 02. 20,000 - 29,999 CZK | 03. 30,000 - 39,999 CZK | 04. 40,000 - 49,999 CZK | 05. more than 49,999 CZK | ELECTION STUDY NOTES - DENMARK (2019): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 200,000 DKK | 02. 200,000 - 299,999 DKK | 03. 300,000 - 399,999 DKK | 04. 400,000 - 499,999 DKK | 05. more than 499,999 DKK | ELECTION STUDY NOTES - EL SALVADOR (2019): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. up to 145 USD | 02. 150 - 240 USD | 03. 250 - 300 USD | 04. 310 - 500 USD | 05. more than 525 USD | ELECTION STUDY NOTES - FINLAND (2019): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. up to 20,000 EUR | 02. 21,000 - 35,000 EUR | 03. 36,000 - 50,000 EUR | 04. 51,000 - 80,000 EUR | 05. more than 80,000 EUR | ELECTION STUDY NOTES - FRANCE (2017): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 1501 EUR | 02. 1501 - 2000 EUR | 03. 2001 - 3000 EUR | 04. 3001 - 4000 EUR | 05. more than 4000 EUR | ELECTION STUDY NOTES - GERMANY (2017): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 1250 EUR | 02. 1250 - less than 2000 EUR | 03. 2000 - less than 3000 EUR | 04. 3000 - less than 4000 EUR | 05. more than 4000 EUR | ELECTION STUDY NOTES - GERMANY (2021): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 2,000 EUR | 02. 2,000 - 2,999 EUR | 03. 3,000 - 3,999 EUR | 04. 4,000 - 4,999 EUR | 05. 5,000 or more EUR | ELECTION STUDY NOTES - GREAT BRITAIN (2017): E2010 | | Quintiles were calculated on the basis of an originally | 15-scaled variable. The resulting distributions are not even. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 15,600 GBP | 02. 15,600 - 25,999 GBP | 03. 26,000 - 36,399 GBP | 04. 36,400 - 59,999 GBP | 05. more than 59,999 GBP | ELECTION STUDY NOTES - GREAT BRITAIN (2019): E2010 | | Quintiles were calculated on the basis of an originally | 15-scaled variable. The resulting distributions are not even. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 15,600 GBP | 02. 15,600 - 25,999 GBP | 03. 26,000 - 36,399 GBP | 04. 36,400 - 51,999 GBP | 05. more than 52,000 GBP | ELECTION STUDY NOTES - GREECE (2015): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 10,000 EUR | 02. 10,001 - 15,000 EUR | 03. 15,001 - 25,000 EUR | 04. 25,001 - 40,000 EUR | 05. more than 40,000 EUR | ELECTION STUDY NOTES - GREECE (2019): E2010 | | Respondents were asked to indicate their yearly family income | without taxes. As the original survey question is composed of | five income brackets, E2010 equals E2011 (Household Income: | Original variable), although the resulting distribution does not | equal sample quintiles. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Up to 10,000 EUR | 02. 10,001 - 15,000 EUR | 03. 15,001 - 25,000 EUR | 04. 25,001 - 40,000 EUR | 05. more than 40,000 EUR | ELECTION STUDY NOTES - HONG KONG (2016): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 10,000 HKD | 02. 10,000 - 29,999 HKD | 03. 30,000 - 39,999 HKD | 04. 40,000 - 59,999 HKD | 05. more than 59,999 HKD | 06. No fixed income | ELECTION STUDY NOTES - HUNGARY (2018): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 136,000 HUF | 02. 137,000 - 200,000 HUF | 03. 201,000 - 275,000 HUF | 04. 276,000 - 350,000 HUF | 05. more than 350,000 HUF | ELECTION STUDY NOTES - ICELAND (2016): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 380,000 ISK | 02. 381,000 - 600,000 ISK | 03. 601,000 - 899,000 ISK | 04. 900,000 - 1,190,000 ISK | 05. more than 1,200,000 ISK | ELECTION STUDY NOTES - ICELAND (2017): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 400,000 ISK | 02. 401,000 - 650,000 ISK | 03. 651,000 - 900,000 ISK | 04. 901,000 - 1,200,000 ISK | 05. more than 1,200,000 ISK | ELECTION STUDY NOTES - INDIA (2019): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 8,501 INR | 02. 8,501 - 14,600 INR | 03. 14,601 - 20,000 INR | 04. 20,001 - 39,000 INR | 05. more than 39,000 INR | ELECTION STUDY NOTES - IRELAND (2016): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 20,000 EUR | 02. 20,000 - 34,999 EUR | 03. 35,000 - 49,999 EUR | 04. 50,000 - 74,999 EUR | 05. more than 75,000 EUR | ELECTION STUDY NOTES - ISRAEL (2020): E2010 | | Quintiles were calculated on the basis of an originally | 10-scaled variable. The resulting distributions are not even. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 7,501 NIS | 02. 7,501 - 12,500 NIS | 03. 12,501 - 16,000 NIS | 04. 16,001 - 22,000 NIS | 05. more than 22,000 NIS | ELECTION STUDY NOTES - ITALY (2018): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 9,990 EUR | 02. 10,000 - 19,990 EUR | 03. 20,000 - 29,990 EUR | 04. 30,000 - 39,990 EUR | 05. more than 40,000 EUR | ELECTION STUDY NOTES - JAPAN (2017): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. up to 2 million JPY | 02. 2-4 million JPY | 03. 4-6 million JPY | 04. 6-10 million JPY | 05. more than 10 million JPY | ELECTION STUDY NOTES - LATVIA (2018): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. up to 400 EUR | 02. 401 - 600 EUR | 03. 601 - 900 EUR | 04. 901 - 1,300 EUR | 05. more than 1,300 EUR | ELECTION STUDY NOTES - LITHUANIA (2016): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 300 EUR | 02. 301 - 500 EUR | 03. 501 - 800 EUR | 04. 801 - 1,000 EUR | 05. more than 1,000 EUR | ELECTION STUDY NOTES - LITHUANIA (2020): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. up to 500 EUR | 02. 501 - 700 EUR | 03. 701 - 1,000 EUR | 04. 1,001 - 1,401 EUR | 05. more than 1,401 EUR | ELECTION STUDY NOTES - MEXICO (2018): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Up to 2,900 MXN | 02. 2,901 - 4,500 MXN | 03. 4,501 - 6,500 MXN | 04. 6,501 - 9,000 MXN | 05. more than 9,000 MXN | | In the Mexican election study, Collaborators asked respondents to | name their monthly household income twice: Once in an open-ended | question, and once in a follow-up question, asking them to place | their income in one of seven income brackets. | Income quintiles provided in E2010 are based on the 734 | respondents who provided continuous data. | For the additional 157 respondents for whom only categorical | data is available, data were imputed by using the midpoint of | their stated income category. For example, a respondent stating | to have a monthly household income between 0 and 2,650 MXN | is assumed to have a household income of 1,325 MXN - thus | falling into the first quintile. | | Stated Income Imputed income | CSES Code (Categorical) (Midpoint) |---------------------------------------------------------------- | 01. 0 - 2,650 MXN 1,325 MXN | 03. 2,651 - 7,952 MXN 5,302 MXN | 05. 7,953 - 13,254 MXN 10,604 MXN | 13,255 - 18,555 MXN 15,905 MXN | | Also SEE ELECTION STUDY NOTES - MEXICO (2018): E2011. | ELECTION STUDY NOTES - MONTENEGRO (2016): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 201 EUR | 02. 201 - 350 EUR | 03. 351 - 550 EUR | 04. 551 - 800 EUR | 05. more than 800 EUR | ELECTION STUDY NOTES - NETHERLANDS (2021): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 2,001 EUR | 02. 2,001 - 2,500 EUR | 03. 2,501 - 3,500 EUR | 04. 3,501 - 5,000 EUR | 05. more than 5,000 EUR | 06. No income | | Also SEE ELECTION STUDY NOTES - NETHERLANDS (2021): E2011 for | further details on divergences in income measures between the | two sampling components. | ELECTION STUDY NOTES - NEW ZEALAND (2017): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 35,699 NZD | 02. 35,700 - 62,199 NZD | 03. 62,200 - 93,599 NZD | 04. 93,600 - 180,199 NZD | 05. more than 180,200 NZD | ELECTION STUDY NOTES - NEW ZEALAND (2020): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 38,000 NZD | 02. 38,001 - 67,000 NZD | 03. 67,001 - 102,000 NZD | 04. 102,001 - 149,000 NZD | 05. more than 149,000 NZD | ELECTION STUDY NOTES - NORWAY (2017): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 370,000 NOK | 02. 370,001 - 620,000 NOK | 03. 620,001 - 900,000 NOK | 04. 900,001 - 1,200,000 NOK | 05. more than 1,200,000 NOK | ELECTION STUDY NOTES - PERU (2021): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. up to 300 PEN | 02. 301 - 1,000 PEN | 03. 1,001 - 1,500 PEN | 04. 1,501 - 2,000 PEN | 05. more than 3,000 PEN | ELECTION STUDY NOTES - POLAND (2019): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. up to 2,250 PLN | 02. 2,251 - 3,000 PLN | 03. 3,001 - 4,000 PLN | 04. 4,001 - 5,000 PLN | 05. more than 5,000 PLN | ELECTION STUDY NOTES - PORTUGAL (2019): E2010 | | Respondents were asked to indicate their average monthly net | income. As the original survey question is composed of five | income brackets, E2010 equals E2011 (Household Income: Original | variable), although the resulting distribution does not equal | sample quintiles. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 301 EUR | 02. 301 - 750 EUR | 03. 751 - 1,500 EUR | 04. 1,501 - 2,500 EUR | 05. more than 2,500 EUR | ELECTION STUDY NOTES - ROMANIA (2016): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. up to 600 RON | 02. 601 - 1,300 RON | 03. 1,301 - 2,000 RON | 04. 2,001 - 3,000 RON | 05. more than 3,000 RON | ELECTION STUDY NOTES - SLOVAKIA (2020): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Less than 550 EUR | 02. 551 - 850 EUR | 03. 850 - 1,050 EUR | 04. 1,051 - 1,400 EUR | 05. More than 1,400 EUR | ELECTION STUDY NOTES - SOUTH KOREA (2016): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 3,000,000 KRW | 02. 3,000,000 - 3,990,000 KRW | 03. 4,000,000 - 4,990,000 KRW | 04. 5,000,000 - 5,990,000 KRW | 05. more than 5,990,000 KRW | ELECTION STUDY NOTES - SWEDEN (2018): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 300,001 SEK | 02. 300,001 - 500,000 SEK | 03. 500,001 - 700,000 SEK | 04. 700,001 - 900,000 SEK | 05. more than 900,000 SEK | ELECTION STUDY NOTES - SWITZERLAND (2019): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. up to 60,000 CHF | 02. 60,001 - 84,000 CHF | 03. 84,001 - 108,000 CHF | 04. 108,001 - 156,000 CHF | 05. more than 156,000 CHF | ELECTION STUDY NOTES - TAIWAN (2016): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 39,000 TWD | 02. 39,001 - 59,000 TWD | 03. 59,001 - 80,000 TWD | 04. 80,001 - 111,000 TWD | 05. more than 111,000 TWD | ELECTION STUDY NOTES - TAIWAN (2020): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 30,000 TWD | 02. 30,001 - 53,000 TWD | 03. 53,001 - 74,000 TWD | 04. 74,001 - 100,000 TWD | 05. more than 100,000 TWD | ELECTION STUDY NOTES - THAILAND (2019): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 65,000 THB | 02. 65,000 - 100,000 THB | 03. 100,001 - 120,000 THB | 04. 120,001 - 190,000 THB | 05. more than 190,000 THB | ELECTION STUDY NOTES - TUNISIA (2019): E2010 | | Respondents were asked to indicate their annual net income. | As the original survey question is composed of eight very | unequally distributed income brackets, E2010 results in | distributions that do not equal sample quintiles. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 500 TND | 02. 500 - 999 TND | 03. 1,000 - 1,499 TND | 04. 1,500 - 1,999 TND | 05. more than 2,000 TND | ELECTION STUDY NOTES - TURKEY (2018): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Up to 1600 TRY | 02. 1601 - 2000 TRY | 03. 2001 - 2900 TRY | 04. 2901 - 3500 TRY | 05. more than 3500 TRY | | In the 2018 Turkish election study, Collaborators asked | respondents to name their monthly household income in an open | question. However, 60 respondents refusing to name their | income received a follow-up question, asking them to place their | income in one of fifteen categories. | Income quintiles provided in E2010 are based on the continuous | data. For the 60 respondents for whom continuous data is not | available, data were imputed by using the midpoint of their | stated income category. For example, a respondent stating to | have a monthly household income between 1.501 and 2.000 TRY | is assumed to have a household income of 1.750 TRY - thus | falling into the second quintile. | | Stated Income Imputed income | CSES Code (Categorical) (Midpoint) |---------------------------------------------------------------- | 01. 751 - 1.000 TRY 875 TRY | 1.001 - 1.500 TRY 1.250 TRY | 02. 1.501 - 2.000 TRY 1.750 TRY | 03. 2.001 - 3.000 TRY 2.500 TRY | 05. 3.001 - 5.000 TRY 4.000 TRY | 5.001 - 7.000 TRY 6.000 TRY | | Also SEE ELECTION STUDY NOTES - TURKEY (2018): E2011. | ELECTION STUDY NOTES - UNITED STATES (2016): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 22,500 USD | 02. 22,500 - 44,999 USD | 03. 45,000 - 74,999 USD | 04. 75,000 - 109,999 USD | 05. more than 110,000 USD | ELECTION STUDY NOTES - UNITED STATES (2020): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 25,000 USD | 02. 25,000 - 49,999 USD | 03. 50,000 - 79,999 USD | 04. 80,000 - 124,999 USD | 05. 125,000 or more USD | ELECTION STUDY NOTES - URUGUAY (2019): E2010 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 22,001 UYU | 02. 22,001 - 30,000 UYU | 03. 30,001 - 42,000 UYU | 04. 42,001 - 60,000 UYU | 05. more than 60,000 UYU --------------------------------------------------------------------------- E2011 >>> HOUSEHOLD INCOME - ORIGINAL VARIABLE --------------------------------------------------------------------------- D09. Household income for the respondent's household. .................................................................. 0-99999999. [SEE ELECTION STUDY NOTES] 99999997. VOLUNTEERED: REFUSED 99999998. VOLUNTEERED: DON'T KNOW 99999999. MISSING | VARIABLE NOTES: E2011 | | E2011 details the original data for household income in the | format collected by the Collaborators. | | In the Election Study Notes below, currency abbreviations are | given in the three-letter alphabetical ISO-4217 format as | described by the International Organization for Standardization. | An English-language description of the ISO-4217 standard can be | found here: | https://www.iso.org/iso-4217-currency-codes.html | (Date accessed: April 5, 2019) | | Data are unavailable for AUSTRALIA (2019). | ELECTION STUDY NOTES - ALBANIA (2017): E2011 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Less than 10,000 ALL | 02. 10,000 - 19,000 ALL | 03. 20,000 - 29,999 ALL | 04. 30,000 - 39,999 ALL | 05. 40,000 - 49,999 ALL | 06. 50,000 - 59,999 ALL | 07. 60,000 - 69,999 ALL | 08. 70,000 - 79,999 ALL | 09. 80,000 - 89,999 ALL | 10. 90,000 - 99,999 ALL | 11. 100,000 - 109,999 ALL | 12. 110,000 - 119,999 ALL | 13. 120,000 - 129,999 ALL | 14. 140,000 - 149,999 ALL | 15. 180,000 - 189,999 ALL | 16. 200,000 - 209,999 ALL | 17. More than 300,000 ALL | ELECTION STUDY NOTES - AUSTRIA (2017): E2011 | | CSES Code Election Study Category |---------------------------------------------------------------- | 01. Less than 400 EUR | 02. 450 - 600 EUR | 03. 600 - 750 EUR | 04. 750 - 900 EUR | 05. 900 - 1,050 EUR | 06. 1,050 - 1,200 EUR | 07. 1,200 - 1,350 EUR | 08. 1,350 - 1,500 EUR | 09. 1,500 - 1,650 EUR | 10. 1,650 - 1,800 EUR | 11. 1,800 - 1,950 EUR | 12. 1,950 - 2,100 EUR | 13. 2,100 - 2,250 EUR | 14. 2,250 - 2,400 EUR | 15. 2,400 - 2,700 EUR | 16. 2,700 - 3,000 EUR | 17. 3,000 - 3,300 EUR | 18. 3,300 - 3,600 EUR | 19. 3,600 - 3,900 EUR | 20. 3,900 or more EUR | ELECTION STUDY NOTES - BELGIUM-FLANDERS (2019): E2011 | | CSES Code Election Study Code/Category |------------------------------------------------------------------ | 01. Less than 1,000 EUR | 02. 1,001 - 1,500 EUR | 03. 1,501 - 2,000 EUR | 04. 2,001 - 3,000 EUR | 05. 3,001 - 4,000 EUR | 06. 4,001 - 5,000 EUR | 07. More than 5,000 EUR | ELECTION STUDY NOTES - BELGIUM-WALLONIA (2019): E2011 | | CSES Code Election Study Code/Category |------------------------------------------------------------------ | 01. Less than 1,000 EUR | 02. 1,001 - 1,500 EUR | 03. 1,501 - 2,000 EUR | 04. 2,001 - 3,000 EUR | 05. 3,001 - 4,000 EUR | 06. 4,001 - 5,000 EUR | 07. More than 5,000 EUR | ELECTION STUDY NOTES - BRAZIL (2018): E2011 | | Brazil (2018) provides household income, original variable, as | continuous variable, measured in Brazilian Real (BRL). | ELECTION STUDY NOTES - CHILE (2017): E2011 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Less than 35,000 CLP | 02. 35,001 - 56,000 CLP | 03. 56,001 - 78,000 CLP | 04. 78,001 - 101,000 CLP | 05. 101,001 - 134,000 CLP | 06. 134,001 - 179,000 CLP | 07. 179,001 - 224,000 CLP | 08. 224,001 - 291,000 CLP | 09. 291,001 - 358,000 CLP | 10. 358,001 - 448,000 CLP | 11. 448,001 - 1,000,000 CLP | 12. 1,000,001 - 2,000,000 CLP | 13. 2,000,001 - 3,000,000 CLP | 14. More than 3,000,000 CLP | ELECTION STUDY NOTES - CANADA (2019): E2011 | | The variable is from the pre-election study. | The monthly household income is provided as a continuous | variable, measured in Canadian dollar (CAD). | ELECTION STUDY NOTES - COSTA RICA (2018): E2011 | | The monthly household income is provided as a continuous | variable, measured in Costa Rican Colon (CRC). | ELECTION STUDY NOTES - CZECHIA (2017): E2011 | | CSES Code Election Study Category |---------------------------------------------------------------- | 01. less than 8,000 CZK | 02. 8,000 - 9,999 CZK | 03. 10,000 - 11,999 CZK | 04. 12,000 - 13,999 CZK | 05. 14,000 - 15,999 CZK | 06. 16,000 - 17,999 CZK | 07. 18,000 - 19,999 CZK | 08. 20,000 - 22,999 CZK | 09. 23,000 - 25,999 CZK | 10. 26,000 - 29,999 CZK | 11. 30,000 - 34,999 CZK | 12. 35,000 - 39,999 CZK | 13. 40,000 - 49,999 CZK | 14. 50,000 - 59,999 CZK | 15. 60,000 - 74,999 CZK | 16. 75,000 - 89,999 CZK | 17. more than 90,000 CZK | ELECTION STUDY NOTES - CZECHIA (2021): E2011 | | CSES Code Election Study Category |---------------------------------------------------------------- | 01. less than 8,000 CZK | 02. 8,000 - 9,999 CZK | 03. 10,000 - 11,999 CZK | 04. 12,000 - 13,999 CZK | 05. 14,000 - 15,999 CZK | 06. 16,000 - 17,999 CZK | 07. 18,000 - 19,999 CZK | 08. 20,000 - 22,999 CZK | 09. 23,000 - 25,999 CZK | 10. 26,000 - 29,999 CZK | 11. 30,000 - 34,999 CZK | 12. 35,000 - 39,999 CZK | 13. 40,000 - 49,999 CZK | 14. 50,000 - 59,999 CZK | 15. 60,000 - 74,999 CZK | 16. 75,000 - 89,999 CZK | 17. more than 90,000 CZK | ELECTION STUDY NOTES - DENMARK (2019): E2011 | | Respondents were asked to provide their annual gross income. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 100,000 DKK | 02. 100,000 - 149,999 DKK | 03. 150,000 - 199,999 DKK | 04. 200,000 - 249,999 DKK | 05. 250,000 - 299,999 DKK | 06. 300,000 - 349,999 DKK | 07. 350,000 - 399,999 DKK | 08. 400,000 - 449,999 DKK | 09. 450,000 - 499,999 DKK | 10. 500,000 - 599,999 DKK | 11. 600,000 - 699,999 DKK | 12. 700,000 - 799,999 DKK | 13. 800,000 - 999,999 DKK | 14. 1,000,000 - 1,199,999 DKK | 15. 1,200,000 DKK or more | ELECTION STUDY NOTES - EL SALVADOR (2019): E2011 | | The monthly household income is provided as a continuous | variable, measured in US Dollar (USD). | ELECTION STUDY NOTES - FINLAND (2019): E2011 | | Finland (2019) provides household income, original variable, as | continuous variable, measured in Euros (EUR). | Some respondents reported an annual income of "0" or "1" EUR. | Collaborators note it is very likely these respondents were not | willing to report their annual income in the survey. Data remain | unchanged in the dataset. | ELECTION STUDY NOTES - FRANCE (2017): E2011 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 1000 EUR | 02. 1001 - 1500 EUR | 03. 1501 - 1750 EUR | 04. 1751 - 2000 EUR | 05. 2001 - 2500 EUR | 06. 2501 - 3000 EUR | 07. 3001 - 4000 EUR | 08. 4001 - 5000 EUR | 09. 5001 - 7000 EUR | 10. more than 7000 EUR | ELECTION STUDY NOTES - GERMANY (2017 & 2021): E2011 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 500 EUR | 02. 500 to less than 750 EUR | 03. 750 to less than 1,000 EUR | 04. 1,000 to less than 1,250 EUR | 05. 1,250 to less than 1,500 EUR | 06. 1,500 to less than 2,000 EUR | 07. 2,000 to less than 2,500 EUR | 08. 2,500 to less than 3,000 EUR | 09. 3,000 to less than 4,000 EUR | 10. 4,000 to less than 5,000 EUR | 11. 5,000 to less than 7,500 EUR | 12. 7,500 to less than 10,000 EUR | 13. 10,000 EUR and above | ELECTION STUDY NOTES - GREAT BRITAIN (2017): E2011 | | The annual household income is provided as a continuous | variable, measured in Great Britain Pound (GBP). | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Less than 2,600 GBP | 02. 2,600 - 5,199 GBP | 03. 5,200 - 10,399 GBP | 04. 10,400 - 15,599 GBP | 05. 15,600 - 20,799 GBP | 06. 20,800 - 25,999 GBP | 07. 26,000 - 31,199 GBP | 08. 31,200 - 36,399 GBP | 09. 36,400 - 39,999 GBP | 10. 40,000 - 44,999 GBP | 11. 45,000 - 49,999 GBP | 12. 50,000 - 59,999 GBP | 13. 60,000 - 74,999 GBP | 14. 75,000 - 99,999 GBP | 15. More than 99,999 GBP | ELECTION STUDY NOTES - GREAT BRITAIN (2019): E2011 | | Respondents had the opportunity to choose between 15 income | categories. In each category, the respective annual, weekly and | monthly income was indicated. To review all three types of | income, please consult the questionnaire. Below we list the | annual household income measured in Great Britain Pound (GBP). | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Less than 2,600 GBP | 02. 2,600 - 5,199 GBP | 03. 5,200 - 10,399 GBP | 04. 10,400 - 15,599 GBP | 05. 15,600 - 20,799 GBP | 06. 20,800 - 25,999 GBP | 07. 26,000 - 31,199 GBP | 08. 31,200 - 36,399 GBP | 09. 36,400 - 41,599 GBP | 10. 41,600 - 46,799 GBP | 11. 46,800 - 51,999 GBP | 12. 52,000 - 74,999 GBP | 13. 75,000 - 99,999 GBP | 14. 100,000 - 149,999 GBP | 15. More than 150,000 GBP | ELECTION STUDY NOTES - GREECE (2015): E2011 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Less than 10,000 EUR | 02. 10,001 - 15,000 EUR | 03. 15,001 - 25,000 EUR | 04. 25,001 - 40,000 EUR | 05. More than 40,000 EUR | ELECTION STUDY NOTES - GREECE (2019): E2011 | | Respondents were asked to indicate their yearly family income | without taxes, including salaries, wages, pensions, other public | insurance benefits, etc. As the original survey question is | composed of five income brackets, E2010 equals E2011 (Household | Income: Quintiles). | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Up to 10,000 EUR | 02. 10,001 - 15,000 EUR | 03. 15,001 - 25,000 EUR | 04. 25,001 - 40,000 EUR | 05. more than 40,000 EUR | ELECTION STUDY NOTES - HONG KONG (2016): E2011 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. no income | 02. 5,999 or less HKD | 03. 6,000 - 9,999 HKD | 04. 10,000 - 19,999 HKD | 05. 20,000 - 29,999 HKD | 06. 30,000 - 39,999 HKD | 07. 40,000 - 49,999 HKD | 08. 50,000 - 59,999 HKD | 09. 60,000 or more HKD | 10. No fixed income | ELECTION STUDY NOTES - HUNGARY (2018): E2011 | | Hungary (2018) provides household income, original variable, as | continuous variable, measured in Hungarian Forints (HUF). | ELECTION STUDY NOTES - ICELAND (2016 & 2017): E2011 | | The monthly household income is provided as a continuous | variable, measured in Icelandic Crowns (ISK). | ELECTION STUDY NOTES - INDIA (2019): E2011 | | The monthly household income is provided as a continuous | variable, measured in Indian Rupees (INR). | ELECTION STUDY NOTES - IRELAND (2016): E2011 | | Respondents were asked two questions with respect to household | income. First, they were asked in an open-ended question what | their annual household income was before taxes. If respondents | refused to answer, they were asked in a follow-up question to | place themselves in one of ten income brackets provided in the | questionnaire. For CSES, respondents who provided an answer to | the open-ended income question were recoded to match the income | brackets in the follow-up question. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Less than 20,000 EUR | 02. 20,000 - 24,999 EUR | 03. 25,000 - 29,999 EUR | 04. 30,000 - 34,999 EUR | 05. 35,000 - 39,999 EUR | 06. 40,000 - 49,999 EUR | 07. 50,000 - 74,999 EUR | 08. 75,000 - 99,999 EUR | 09. 100,000 - 149,000 EUR | 10. 150,000 or more EUR | ELECTION STUDY NOTES - ISRAEL (2020): E2011 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 5,001 NIS | 02. 5,001 - 7,500 NIS | 03. 7,501 - 10,000 NIS | 04. 10,001 - 12,500 NIS | 05. 12,501 - 14,500 NIS | 06. 14,501 - 16,000 NIS | 07. 16,001 - 19,500 NIS | 08. 19,501 - 22,000 NIS | 09. 22,001 - 25,500 NIS | 10. more than 25,500 NIS | ELECTION STUDY NOTES - ITALY (2018): E2011 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 9,990 EUR | 02. 10,000 - 19,990 EUR | 03. 20,000 - 29,990 EUR | 04. 30,000 - 39,990 EUR | 05. 40,000 - 49,990 EUR | 06. 50,000 - 59,990 EUR | 07. 60,000 - 69,990 EUR | 08. 70,000 - 79,990 EUR | 09. 80,000 - 89,990 EUR | 10. 90,000 - 99,990 EUR | 11. more than 100,000 EUR | ELECTION STUDY NOTES - JAPAN (2017): E2011 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Less than 2 million JPY | 02. 2-4 million JPY | 03. 4-6 million JPY | 04. 6-8 million JPY | 05. 8-10 million JPY | 06. 10-12 million JPY | 07. More than 12 million JPY | ELECTION STUDY NOTES - LATVIA (2018): E2011 | | Latvia (2018) provides household income, original variable, as | continuous variable, measured in Euro (EUR). | ELECTION STUDY NOTES - LITHUANIA (2016): E2011 | | CSES Code Election Study Category |---------------------------------------------------------------- | 01. Up to 150 EUR | 02. 151 - 200 EUR | 03. 201 - 250 EUR | 04. 251 - 300 EUR | 05. 301 - 350 EUR | 06. 351 - 400 EUR | 07. 401 - 450 EUR | 08. 451 - 500 EUR | 09. 501 - 550 EUR | 10. 551 - 600 EUR | 11. 601 - 700 EUR | 12. 701 - 800 EUR | 13. 801 - 900 EUR | 14. 901 - 1,000 EUR | 15. 1,001 - 1,200 EUR | 16. 1,201 - 1,400 EUR | 17. 1,401 - 1,600 EUR | 18. 1,601 - 1,800 EUR | 19. 1,801 - 2,000 EUR | 20. More than 2,000 EUR | ELECTION STUDY NOTES - LITHUANIA (2020): E2011 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. up to 300 EUR | 02. 301 - 500 EUR | 03. 501 - 700 EUR | 04. 701 - 1,000 EUR | 05. 1,001 - 1,401 EUR | 06. more than 1,401 EUR | ELECTION STUDY NOTES - MEXICO (2018): E2011 | | In the Mexican election study, Collaborators asked respondents to | name their monthly household income twice: Once in an open-ended | question, and once in a follow-up question, asking them to place | their income in one of seven income brackets. | | Where available, the continuous measure was used for coding | E2011 (N = 734). | An additional 157 respondents placed themselves in one of the | categories rather than naming their detailed household income. | The seven categories were coded as follows: | | CSES Code Election Study Code/Category |--------------------------------------------------------- | 01. Less than 2,651 MXN | 02. 2,651 - 7,952 MXN | 03. 7,953 - 13,254 MXN | 04. 13,255 - 18,555 MXN | 05. 18,556 - 26,508 MXN | 06. 26,509 - 79,524 MXN | 07. 79,525 or more MXN | | The 157 respondents who placed themselves in one of the | categories rather than naming their detailed household income | all placed themselves in categories 1 to 4. | ELECTION STUDY NOTES - MONTENEGRO (2016): E2011 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. no income | 02. less than 100 EUR | 03. 101 - 125 EUR | 04. 126 - 150 EUR | 05. 151 - 200 EUR | 06. 201 - 250 EUR | 07. 251 - 300 EUR | 08. 301 - 350 EUR | 09. 351 - 400 EUR | 10. 401 - 450 EUR | 11. 451 - 500 EUR | 12. 501 - 550 EUR | 13. 551 - 600 EUR | 14. 601 - 650 EUR | 15. 651 - 700 EUR | 16. 700 - 800 EUR | 17. 801 - 900 EUR | 18. 901 - 1,050 EUR | 19. 1,051 - 1,200 EUR | 20. more than 1,200 EUR | ELECTION STUDY NOTES - NETHERLANDS (2017): E2011 | | For the Dutch 2017 study, income measures differ considerably | between the two sampling components, that is, the face-to-face | sample drawn from population registers (N = 723) and the sample | drawn from the ongoing "LISS" online panel (N = 1,180). | In what follows, data generation processes are described | separately for each component. Researchers interested in | differentiating between sample components are referred to | variable E1007 (Sampling Component) for further information. | | Data in E2011 for the face-to-face component have not been | collected in the survey but were obtained from population | registers. Respondents provided consent before data collection. | Generally, register data are based on the most recent available | data, usually the year preceding data collection. | | Further, the vendor split register data into quintiles, | which are coded as follows in E2011: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Lowest Household Income Quintile ( 0- 20%) | 02. Second Household Income Quintile (21- 40%) | 03. Third Household Income Quintile (41- 60%) | 04. Fourth Household Income Quintile (61- 80%) | 05. Highest Household Income Quintile (81-100%) | | As the cutoff values for the above scale remain unknown, data | have not been transferred to E2010. | | Data for the online-panel component are based on survey | responses from the LISS-Panel. For this purpose, respondents | were asked to report their gross household income in EUR on | a continuous scale. If gross income was missing but net income | was reported to LISS, E2011 was imputed based on the group that | reported both gross and net income, and for whom both were non- | zero and non-bracketed. For respondents who only provided | bracketed net income information, LISS imputed the midpoint | value of the bracket. The imputed values have been rounded. | For a small percentage of the respondents, both gross and net | income were unavailable. In these cases, no imputation was done. | ELECTION STUDY NOTES - NETHERLANDS (2021): E2011 | | This variable is from the pre-election survey. | | Further, researchers are advised that the income measures differ | considerably between the two sampling components, that is, the | fresh 2021 sample drawn from population registers (N = 1,688) | and the sample drawn from the ongoing "LISS" online panel | (N = 1,797). | | Data for the fresh 2021 sample are based on a survey question | asking respondents to place their monthly net household income | into one of the following 15 income brackets: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. no income | 02. 500 or less EUR | 03. 501 - 1,000 EUR | 04. 1,001 - 1,500 EUR | 05. 1,501 - 2,000 EUR | 06. 2,001 - 2,500 EUR | 07. 2,501 - 3,000 EUR | 08. 3,001 - 3,500 EUR | 09. 3,501 - 4,000 EUR | 10. 4,001 - 5,500 EUR | 11. 5,001 - 5,500 EUR | 12. 5,501 - 6,000 EUR | 13. 6,001 - 7,000 EUR | 14. 7,001 - 8,000 EUR | 15. 8,001 or more EUR | | Code 10 was intended to refer to incomes ranging between 4,001 - | 5,000 EUR, but was mistakenly displayed as 4,001 - 5,500 EUR to | respondents from the register sample. | | Data for the online-panel component are based on survey | responses from the LISS-Panel. For this purpose, respondents | were asked to report their absolute net household income in EUR | on a continuous scale. Collaborators grouped the continuous | variable into the 15 categories outlined above to obtain a | common combined income measure across the two sample components. | ELECTION STUDY NOTES - NEW ZEALAND (2017): E2011 | | CSES Code Election Study Category |---------------------------------------------------------------- | 01. no income | 02. less than 23,800 NZD | 03. 23,801 - 35,699 NZD | 04. 35,700 - 62,199 NZD | 05. 62,200 - 76,999 NZD | 06. 77,000 - 93,599 NZD | 07. 93,600 - 136,599 NZD | 08. 136,600 - 180,199 NZD | 09. more than 180,200 NZD | ELECTION STUDY NOTES - NEW ZEALAND (2020): E2011 | | CSES Code Election Study Category |---------------------------------------------------------------- | 01. no income | 02. less than 38,000 NZD | 03. 38,001 - 67,000 NZD | 04. 67,001 - 102,000 NZD | 05. 102,001 - 149,000 NZD | 06. 149,001 - 196,000 NZD | 07. more than 196,000 NZD | ELECTION STUDY NOTES - NORWAY (2017): E2011 | | The annual household income is provided as a continuous | variable, measured in Norwegian Krone (NOK). | ELECTION STUDY NOTES - PERU (2021): E2011 | | CSES Code Election Study Category |---------------------------------------------------------------- | 01. up to 300 PEN | 02. 301 - 600 PEN | 03. 601 - 1,000 PEN | 04. 1,001 - 1,500 PEN | 05. 1,501 - 2,000 PEN | 06. 2,001 - 3,000 PEN | 07. 3,001 - 5,000 PEN | 08. 5,001 - 10,000 PEN | 09. 10,001 - 15,000 PEN | 10. more than 15,000 PEN | ELECTION STUDY NOTES - POLAND (2019): E2011 | | CSES Code Election Study Category |---------------------------------------------------------------- | 01. up to 300 PLN | 02. 301 - 500 PLN | 03. 501 - 750 PLN | 04. 751 - 1,000 PLN | 05. 1,001 - 1,250 PLN | 06. 1,251 - 1,500 PLN | 07. 1,501 - 1,750 PLN | 08. 1,751 - 2,000 PLN | 09. 2,001 - 2,250 PLN | 10. 2,251 - 2,500 PLN | 11. 2,501 - 2,750 PLN | 12. 2,751 - 3,000 PLN | 13. 3,001 - 3,500 PLN | 14. 3,501 - 4,000 PLN | 15. 4,001 - 4,500 PLN | 16. 4,501 - 5,000 PLN | 17. 5,001 - 7,000 PLN | 18. 7,001 - 8,000 PLN | 19. 8,001 - 10,000 PLN | 20. more than 10,000 PLN | ELECTION STUDY NOTES - PORTUGAL (2019): E2011 | | Respondents were asked to indicate their average monthly net | income. As the original survey question was composed of five | income brackets, E2011 equals E2010 (Household Income: | Quintiles). | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 301 EUR | 02. 301 - 750 EUR | 03. 751 - 1,500 EUR | 04. 1,501 - 2,500 EUR | 05. more than 2,500 EUR | ELECTION STUDY NOTES - ROMANIA (2016): E2011 | | Romania (2016) provides household income, original variable, as | continuous variable, measured in Romanian leu (RON). | ELECTION STUDY NOTES - SLOVAKIA (2020): E2011 | | The Slovakian 2020 study included separate questions for | respondents' personal and household income. Respondents living | in single-member households were not asked about their household | income, as their household income is assumed to be equal to their | personal income. Hence, for these respondents from single-member | households, E2011 includes data originating from the personal | income question. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Less than 350 EUR | 02. 351 - 550 EUR | 03. 551 - 850 EUR | 04. 851 - 1,050 EUR | 05. 1,051 - 1,400 EUR | 06. 1,401 - 2,500 EUR | 07. 2,501 - 3,500 EUR | 08. 3,501 - 4,500 EUR | 09. More than 4,500 EUR | ELECTION STUDY NOTES - SOUTH KOREA (2016): E2011 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 1,000,000 KRW | 02. 1,000,000 - 1,990,000 KRW | 03. 2,000,000 - 2,990,000 KRW | 04. 3,000,000 - 3,990,000 KRW | 05. 4,000,000 - 4,990,000 KRW | 06. 5,000,000 - 5,990,000 KRW | 07. 6,000,000 - 6,990,000 KRW | 08. more than 7,000,000 KRW | ELECTION STUDY NOTES - SWEDEN (2018): E2011 | | The question used in the Swedish survey asked respondents to | provide a rough estimate of the total annual income of all | individuals in their household before taxes, including pensions, | student grants, etc. The following 12 categories were offered | to respondents: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. 100,000 or less SEK | 02. 100,001 - 200,000 SEK | 03. 200,001 - 300,000 SEK | 04. 300,001 - 400,000 SEK | 05. 400,001 - 500,000 SEK | 06. 500,001 - 600,000 SEK | 07. 600,001 - 700,000 SEK | 08. 700,001 - 800,000 SEK | 09. 800,001 - 900,000 SEK | 10. 900,001 - 1,000,000 SEK | 11. 1,000,001 - 1,100,000 SEK | 12. more than 1,100,000 SEK | ELECTION STUDY NOTES - SWITZERLAND (2019): E2011 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Less than 24,000 CHF | 02. 24,001 - 36,000 CHF | 03. 36,001 - 48,000 CHF | 04. 48,001 - 60,000 CHF | 05. 60,001 - 72,000 CHF | 06. 72,001 - 84,000 CHF | 07. 84,001 - 96,000 CHF | 08. 96,001 - 108,000 CHF | 09. 108,001 - 120,000 CHF | 10. 120,001 - 132,000 CHF | 11. 132,001 - 144,000 CHF | 12. 144,001 - 156,000 CHF | 13. 156,001 - 168,000 CHF | 14. 168,001 - 180,000 CHF | 15. More than 180,000 CHF | ELECTION STUDY NOTES - TAIWAN (2016): E2011 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Less than 28,000 TWD | 02. 28,001 - 39,000 TWD | 03. 39,001 - 49,000 TWD | 04. 49,001 - 59,000 TWD | 05. 59,001 - 69,000 TWD | 06. 69,001 - 80,000 TWD | 07. 80,001 - 93,000 TWD | 08. 93,001 - 111,000 TWD | 09. 111,001 - 141,000 TWD | 10. More than 141,001 TWD | ELECTION STUDY NOTES - TAIWAN (2020): E2011 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Less than 30,000 TWD | 02. 30,001 - 42,000 TWD | 03. 42,001 - 53,000 TWD | 04. 53,001 - 63,000 TWD | 05. 63,001 - 74,000 TWD | 06. 74,001 - 86,000 TWD | 07. 86,001 - 100,000 TWD | 08. 100,001 - 120,000 TWD | 09. 120,001 - 156,000 TWD | 10. More than 156,000 TWD | ELECTION STUDY NOTES - THAILAND (2019): E2011 | | The annual household income is provided as a continuous | variable, measured in Thai baht (THB). | ELECTION STUDY NOTES - TUNISIA (2019): E2011 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Less than 500 TND | 02. 500 - 999 TND | 03. 1,000 - 1,499 TND | 04. 1,500 - 1,999 TND | 05. 2,000 - 2,499 TND | 06. 2,500 - 2,999 TND | 07. 3,000 - 5,000 TND | 08. More than 5,000 TND | ELECTION STUDY NOTES - TURKEY (2018): E2011 | | In the 2018 Turkish election study, Collaborators asked | respondents to name their monthly household income in an open | question. However, 60 respondents refusing to name their | income received a follow-up question, asking them to place their | income in one of the following fifteen categories, which were | coded as follows: | | CSES Code Election Study Code/Category |--------------------------------------------------------- | 01. Less than 150 TRY | 02. 151 - 250 TRY | 03. 251 - 350 TRY | 04. 351 - 450 TRY | 05. 451 - 550 TRY | 06. 551 - 750 TRY | 07. 751 - 1,000 TRY | 08. 1,001 - 1,500 TRY | 09. 1,501 - 2,000 TRY | 10. 2,001 - 3,000 TRY | 11. 3,001 - 5,000 TRY | 12. 5,001 - 7,000 TRY | 13. 7,001 - 9,000 TRY | 14. 9,001 - 11,000 TRY | 15. 11,001 or more TRY | | The 60 respondents who placed themselves in one of the | categories rather than naming their detailed household income | all placed themselves in categories 7 to 12. | For all other respondents in the sample, E2011 provides the | monthly household income on a continuous scale, as indicated by | respondents. | ELECTION STUDY NOTES - UNITED STATES (2016): E2011 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 5,000 USD | 02. 5,000 - 9,999 USD | 03. 10,000 - 12,499 USD | 04. 12,500 - 14,999 USD | 05. 15,000 - 17,499 USD | 06. 17,500 - 19,999 USD | 07. 20,000 - 22,499 USD | 08. 22,500 - 24,999 USD | 09. 25,000 - 27,499 USD | 10. 27,500 - 29,999 USD | 11. 30,000 - 34,999 USD | 12. 35,000 - 39,999 USD | 13. 40,000 - 44,999 USD | 14. 45,000 - 49,999 USD | 15. 50,000 - 54,999 USD | 16. 55,000 - 59,999 USD | 17. 60,000 - 64,999 USD | 18. 65,000 - 69,999 USD | 19. 70,000 - 74,999 USD | 20. 75,000 - 79,999 USD | 21. 80,000 - 89,999 USD | 22. 90,000 - 99,999 USD | 23. 100,000 - 109,999 USD | 24. 110,000 - 124,999 USD | 25. 125,000 - 149,999 USD | 26. 150,000 - 174,999 USD | 27. 175,000 - 249,999 USD | 28. more than 250,000 USD | ELECTION STUDY NOTES - UNITED STATES (2020): E2011 | | Respondents were asked to provide the combined gross income of | all family members during the past 12 months. This included | money from jobs, net income from business, farm or rent, | pensions, dividends, interest, Social Security payments and any | other money income received by family members being 15 years of | age or older. | Further, the ANES 2020 includes two variable groups measuring | household income, one from the pre-election interview and | another one combining information from pre- and post-election | interviews. CSES uses the latter variable for E2011 (V202468x). | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. less than 9,999 USD | 02. 10,000 - 14,999 USD | 03. 15,000 - 19,999 USD | 04. 20,000 - 24,999 USD | 05. 25,000 - 29,999 USD | 06. 30,000 - 34,999 USD | 07. 35,000 - 39,999 USD | 08. 40,000 - 44,999 USD | 09. 45,000 - 49,999 USD | 10. 50,000 - 59,999 USD | 11. 60,000 - 64,999 USD | 12. 65,000 - 69,999 USD | 13. 70,000 - 74,999 USD | 14. 75,000 - 79,999 USD | 15. 80,000 - 89,999 USD | 16. 90,000 - 99,999 USD | 17. 100,000 - 109,999 USD | 18. 110,000 - 124,999 USD | 19. 125,000 - 149,999 USD | 20. 150,000 - 174,999 USD | 21. 175,000 - 249,999 USD | 22. 250,000 or more USD | ELECTION STUDY NOTES - URUGUAY (2019): E2011 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Less than 15,001 UYU | 02. 15,001 - 22,000 UYU | 03. 22,001 - 30,000 UYU | 04. 30,001 - 42,000 UYU | 05. 42,001 - 60,000 UYU | 06. 60,001 - 95,000 UYU | 07. More than 95,000 UYU --------------------------------------------------------------------------- E2012 >>> NUMBER IN HOUSEHOLD --------------------------------------------------------------------------- D20. Total number of persons in household. .................................................................. 01.-90. NUMBER OF PERSONS 97. VOLUNTEERED: REFUSED 98. VOLUNTEERED: DON'T KNOW 99. MISSING | VARIABLE NOTES: E2012 | | E2012 details the total number of persons living in a household - | that is, the number of persons living together in the housing | unit excluding paid employees and persons who pay rent for a | room. | | E2012 was not part of the CSES MODULE 5 pilot questionnaire. | | Data are unavailable for AUSTRALIA (2019), GREAT BRITAIN (2017), | GREECE (2015), HONG KONG (2016), IRELAND (2016), MEXICO (2018), | SOUTH KOREA (2016), SWEDEN (2018) and TAIWAN (2016 & 2020). | ELECTION STUDY NOTES - BELGIUM-FLANDERS (2019): E2012 | | There is one respondent who answered "zero," although the | question was asked correctly in the questionnaire. | ELECTION STUDY NOTES - GREAT BRITAIN (2019): E2012 | | The number of missing responses is high for E2012 as the study | had to omit some questions from the paper survey, and this was | one of them. | ELECTION STUDY NOTES - CANADA (2019): E2012 | | This variable is from the pre-election survey. | ELECTION STUDY NOTES - FINLAND (2019): E2012 | | There are five respondents who answered "0" to this question, | even though this question has been asked correctly in the survey. | Finnish Collaborators note this is most likely the case of | insincere responses. Data remain unchanged in the dataset. | ELECTION STUDY NOTES - FRANCE (2017): E2012 | | In the French 2017 study, code 7 refers to "seven household | members or more." | ELECTION STUDY NOTES - GERMANY (2017 & 2021): E2012 | | Respondents were asked to report the number of people living in | their household, including themselves and all children. However, | there was no reference to the CSES convention that paid | employees and people paying rent for a room should be excluded. | ELECTION STUDY NOTES - INDIA (2019): E2012 | | Respondents were asked to indicate the number of adults | living in their household (i.e., persons aged 18 or above). | Hence, children living in the household were disregarded for | E2012. | ELECTION STUDY NOTES - NETHERLANDS (2021): E2012 | | This variable is from the pre-election survey. Further, code 9 | refers to "nine household members or more." | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 9. Nine household members or more | ELECTION STUDY NOTES - NEW ZEALAND (2020): E2012 | | Respondents were asked to indicate the number of adults and | children living in their household in two consecutive survey | questions. Both variables were added together to create E2012. | Respondents who left the question on the number of children | living in their household blank are assumed not to have any | children living with them. For these cases, E2012 has been | coded based on the indicated number of adults only. | Further, there are 16 respondents who answered "0", "nil" or | "none" to the number of adults living in their household, | even though this question has been asked correctly in the survey. | Data remain unchanged. | ELECTION STUDY NOTES - SWITZERLAND (2019): E2012 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 7. 7 household members or more | ELECTION STUDY NOTES - UNITED STATES (2016): E2012 | | E2012 was constructed using two original survey questions: As | part of the screening interview, respondents were asked to | indicate the number of adults in their household, while they | named the number of children living in their household in the | pre-election interview. Both variables were added to create | E2012. While the number of adults living in the household was | topcoded at "8. eight or more people", the number of children | was topcoded at "9. More than eight children." That applies to | the following four respondents: | | Respondent-ID (E1005) Election Study Code/Category |---------------------------------------------------------------- | 840020160000000920. Eight or more adults in household | 840020160000003101. Eight or more adults in household | 840020160000000373. Eight or more children in household | 840020160000002884. Eight or more children in household | ELECTION STUDY NOTES - UNITED STATES (2020): E2012 | | Respondents were asked how many family members were living with | them at the time of the pre-election interview. E2012 adds 1 | to each of these answers for counting the respondent. | Code 6 refers to "Five or more". | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 06. R lives with five family members or more --------------------------------------------------------------------------- E2013 >>> RELIGIOUS DENOMINATION --------------------------------------------------------------------------- D10. Religious denomination. .................................................................. CHRISTIAN 1000. CHRISTIAN (NO DENOMINATION GIVEN) CATHOLIC 1101. ROMAN CATHOLIC 1102. EASTERN (GREEK RITE) CATHOLIC CHURCHES 1199. CATHOLIC, OTHER [SEE ELECTION STUDY NOTES] PROTESTANT 1200. PROTESTANT, NO DENOMINATION GIVEN 1201. ADVENTIST 1203. BAPTIST 1204. CONGREGATIONAL 1205. EUROPEAN FREE CHURCH (ANABAPTISTS, MENNONITES) 1206. HOLINESS 1207. FUNDAMENTALIST 1208. LUTHERAN 1209. METHODIST 1210. PENTECOSTAL 1211. PRESBYTERIAN 1212. CALVINIST 1213. SALVATION ARMY/SALVATIONIST 1214. CHRISTIAN BRETHREN 1215. CHURCHES OF CHRIST 1216. REFORMED CHURCHES 1217. PROTESTANT CHURCH OF THE NETHERLANDS 1298. PROTESTANT, OTHER [SEE ELECTION STUDY NOTES] 1299. PROTESTANT, OTHER [SEE ELECTION STUDY NOTES] ANGLICAN 1300. EPISCOPALIAN, ANGLICAN, CHURCH OF ENGLAND, CHURCH OF IRELAND INDEPENDENTS-NON-AFFILIATED 1401. INDEPENDENT-FUNDAMENTALIST 1410. APOSTOLIC 1420. UNITED CHURCHES 1499. INDEPENDENT, OTHER [SEE ELECTION STUDY NOTES] NON-TRADITIONAL PROTESTANTS 1501. CHRISTIAN SCIENTISTS 1502. MORMONS, CHURCH OF LATTER-DAY SAINTS 1503. UNITARIAN UNIVERSALISTS 1504. JEHOVAH'S WITNESSES 1599. NON-TRADITIONAL PROTESTANT, OTHER [SEE ELECTION STUDY NOTES] ORTHODOX 1600. EASTERN ORTHODOX 1698. ORTHODOX, OTHER [SEE ELECTION STUDY NOTES] 1699. ORTHODOX, OTHER [SEE ELECTION STUDY NOTES] JEWISH 2000. JEWISH ISLAM 3000. MUSLIM; MOHAMMEDAN; ISLAM (NO DENOMINATION GIVEN) 3100. SUNNI 3200. SHI'ISM 3210. ISMA'ILIS 3211. DRUSE BUDDHISM 4000. BUDDHIST 4100. THERAVADA 4200. MAHAYANA HINDUISM AND OTHER RELIGIONS OF INDIA 5000. HINDU 5010. PARSIISM 5020. VAISHNAVISM 5030. SHAIVISM 5040. SHAKTISM 5500. JAINISM 5600. SIKHISM INDIGENOUS RELIGIONS OF EAST ASIA 6100. CONFUCIANISM 6200. TAOISM 6300. SHINTO 6400. NEW RELIGIONSISTS 6401. I-KUAN-TAO 6500. TRADITIONAL FOLK BELIEF/NICHIREN SHSHU ETHNORELIGIONS/OTHER BELIEVER 7100. PAGAN, HEATHEN, TRIBAL RELIGIONSIST, TRADITIONAL RELIGIONIST, ANIMISM, SHAMANISM 7110. RATANA, MAORI 7200. SPIRITISM 7500. BAHAI 7900. EHTNORELIGIONIST, OTHER [SEE ELECTION STUDY NOTES] 7901. EHTNORELIGIONIST, OTHER [SEE ELECTION STUDY NOTES] NON BELIEVERS 8100. AGNOSTIC 8200. ATHEIST 8300. NONE OTHERS 9001. [SEE ELECTION STUDY NOTES] 9002. [SEE ELECTION STUDY NOTES] 9003. [SEE ELECTION STUDY NOTES] 9004. [SEE ELECTION STUDY NOTES] 9005. [SEE ELECTION STUDY NOTES] 9006. [SEE ELECTION STUDY NOTES] 9600. OTHER: NOT SPECIFIED 9997. VOLUNTEERED: REFUSED 9998. VOLUNTEERED: DON'T KNOW 9999. MISSING | VARIABLE NOTES: E2013 | | Data are unavailable for HUNGARY (2018). | ELECTION STUDY NOTES - ALBANIA (2017): E2013 | | The deposited dataset contained a wild code 0, a value assigned | to 205 respondents. Since Collaborators did not provide an | explanation for this, these respondents are set to | "9999. missing" for E2013. | ELECTION STUDY NOTES - AUSTRALIA (2019): E2013 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 1420. Uniting Church in Australia | ELECTION STUDY NOTES - BRAZIL (2018): E2013 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 1599. Mormon Church, Jehovah Witness | 7100. Candombla (African religion) | Umbanda | 7200. Espiritualism | 7900. Seisho-No-Ie, World Messianic Church, Perfect | Liberty | 7901. Santo Daime, Esoteric | 8300. Atheist/agnostic/ Doesn't believe in God | ELECTION STUDY NOTES - CANADA (2019): E2013 | | This variable is from the pre-election survey. | ELECTION STUDY NOTES - DENMARK (2019): E2013 | | Respondents stating to identify as Sunni or Shia were coded | as 3000. MUSLIM; MOHAMMEDAN; ISLAM (NO DENOMINATION GIVEN). | ELECTION STUDY NOTES - GERMANY (2017 & 2021): E2013 | | CSES-Code Election study code/category |---------------------------------------------------------------- | 1298. Evangelical Church in Germany (excluding Free | Churches) | 1299. Protestant Free Church | ELECTION STUDY NOTES - GREAT BRITAIN (2017): E2013 | | CSES-Code Election study code/category |---------------------------------------------------------------- | 1298. Other - Protestant | 9001. Other - non-Christian | ELECTION STUDY NOTES - GREAT BRITAIN (2019): E2013 | | CSES-Code Election study code/category |---------------------------------------------------------------- | 1298. Other Protestant | 1299. Evangelical; | Quaker | 1699. Orthodox | 9001. Other non-Christian | ELECTION STUDY NOTES - HONG KONG (2016): E2013 | | Before being asked about their religious denomination, | respondents were asked to specify whether they hold any religious | beliefs. Only respondents reporting to hold such beliefs answered | to E2013. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 1199. Catholics (not further specified) | 9001. Local religions (ancestor worship, guanyin - tudi worship, etc.) | ELECTION STUDY NOTES - IRELAND (2016): E2013 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 1298. Quaker | 9001. Humanist | 9002. Jedi Knight | 9003. Pastafarianism | ELECTION STUDY NOTES - ITALY (2018): E2013 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 9001. Asian Religion | ELECTION STUDY NOTES - LATVIA (2018): E2013 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 1698. Old believers | ELECTION STUDY NOTES - MEXICO (2018): E2013 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 1199. Catholic | 1298. Evangelical | 1299. Nazarene | 8300. Respondent doesn't have a religion | ELECTION STUDY NOTES - NETHERLANDS (2021): E2013 | | This variable is from the pre-election survey. | ELECTION STUDY NOTES - MONTENEGRO (2016): E2013 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 1698. Montenegrin Orthodox | 1699. Serbian Orthodox | ELECTION STUDY NOTES - PERU (2021): E2013 | | CSES-Code Election study code/category |---------------------------------------------------------------- | 1298. Universal New Pact Israelite | ELECTION STUDY NOTES - SOUTH KOREA (2016): E2013 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 1199. Catholic (not further specified) | 8300. Do not belong to any religious denomination | ELECTION STUDY NOTES - SWEDEN (2018): E2013 | | Respondents were only asked to specify their religious | denomination if they previously stated to "have a belief, creed | or religious affiliation". Respondents answering not to have | such a religious affiliation have been coded to "8300. None". | Further, respondents stating to have a Catholic or Orthodox | denomination without further specification were coded as | follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 1199. Catholic, not further specified | 1699. Orthodox, not further specified | ELECTION STUDY NOTES - TAIWAN (2016): E2013 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 9001. Buddhist and Taoist | 9002. Confucianism, Buddhism and Taoism | ELECTION STUDY NOTES - TAIWAN (2020): E2013 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 9001. Buddhist and Taoist | 9002. Falun Gong | 9003. Buddhism and Christianity | 9004. Nine Lotus Sacred Path | ELECTION STUDY NOTES - TURKEY (2018): E2013 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 9001. Zoroastrian | ELECTION STUDY NOTES - UNITED STATES (2016 & 2020): E2013 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 1000. Christian, not further specified, inter- or non- | denominational | 1298. Evangelical Churches (Evangelical Covenant | Church, Evangelical Free Church, EFC, or EFCA) | 1299. Quakers; Friends | 1699. Syrian Orthodox, Armenian Orthodox | 7900. American Indian religions; Native American | religions | 9001. Catholic and Protestant | 9002. Messianic Judaism; Jews for Jesus | 9003. More than one major religion (e.g., Christian, | Jewish, Muslim, etc.) | 9004. Religious Science; Science of Mind (not | Scientology; not Christian Scientists); Centers | for Spiritual Living | 9005. Unity; Unity Church; Christ Church Unity | 9006. Scientology | 9600. Other non-Christian/non-Jewish, other tradition | not codable, R indicates having an affiliation | but does not specify one | ELECTION STUDY NOTES - URUGUAY (2019): E2013 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 9001. Believers without religion --------------------------------------------------------------------------- E2014 >>> RELIGIOUS SERVICES ATTENDANCE --------------------------------------------------------------------------- D11. Attendance at religious services. .................................................................. 1. NEVER 2. ONCE A YEAR 3. TWO TO ELEVEN TIMES A YEAR 4. ONCE A MONTH 5. TWO OR MORE TIMES A MONTH 6. ONCE A WEEK/MORE THAN ONCE A WEEK 7. VOLUNTEERED: REFUSED 8. VOLUNTEERED: DON'T KNOW 9. MISSING | VARIABLE NOTES: E2014 | | E2014 is asked irrespective of individuals' religious | denomination, as the CSES questionnaire of origin does not | include filter instructions in the demographic section. | | Data are unavailable for SOUTH KOREA (2016). | ELECTION STUDY NOTES - BRAZIL (2018): E2014 | | The answer categories for E2014 offered to respondents deviated | slightly from CSES MODULE 5 standards. The variable was recoded | as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Never goes to a church | 02. Rarely | 03. Sometimes a year | 04. Once or twice a month | 06. More than once a week | ELECTION STUDY NOTES - FRANCE (2017): E2014 | | The answer categories for E2014 offered to respondents deviated | from CSES MODULE 5 standards. The variable was recoded as | follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Never | 02. Only for special ceremonies | 03. Sometimes | 04. Once or twice a month | 06. Once a week | Several times a week | ELECTION STUDY NOTES - GERMANY (2017 & 2021): E2014 | | In the 2017 German questionnaire, the interviewer instruction | refers to religious service in a church, mosque or synagogue, | excluding prayer during Ramadan. No instruction not to count | special occasions such as funerals and weddings was provided. | | Two answer categories for E2014 offered to respondents deviated | slightly from CSES MODULE 5 standards (see below): | | CSES-Code Election study code/category |---------------------------------------------------------------- | 03. Several times a year | 05. Two to three times a month | ELECTION STUDY NOTES - GREAT BRITAIN (2019): E2014 | | The number of missing responses is high for E2014 as the study | had to omit some questions from the paper survey, and this was | one of them. | ELECTION STUDY NOTES - HUNGARY (2018): E2014 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 03. Only for family events or major holidays | ELECTION STUDY NOTES - LITHUANIA (2020): E2014 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Never | 02. Once a year or less | 03. More than once a year (2 to 11 times a year) | 04. Once a month | 05. 2 to 3 times a month | 06. Once a week; | More than once a week | ELECTION STUDY NOTES - NETHERLANDS (2017): E2014 | | Only respondents indicating a religious denomination in a | preceding question were asked about their religious service | attendance. | Further, the answer categories for E2014 offered to respondents | deviated slightly from CSES MODULE 5 standards. The variable was | recoded as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. (Almost) never | 03. Several times a year | 04. Once a month | 05. Two or three times a month | 06. Once a week or more | ELECTION STUDY NOTES - NETHERLANDS (2021): E2014 | | This variable is from the pre-election survey. | | Further, the answer categories for E2014 offered to respondents | deviated slightly from CSES MODULE 5 standards. The variable was | recoded as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. (Almost) never | 03. Several times a year | 04. Once a month | 05. Two or three times a month | 06. Once a week or more | ELECTION STUDY NOTES - NORWAY (2017): E2014 | | The answer categories for E2014 offered to respondents deviated | slightly from CSES MODULE 5 standards. Specifically, a category | for "two or more times a month" (CSES code 5) was not included in | the Norwegian questionnaire. The variable was recoded in the | following way: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Never | 02. More rarely | 03. Only on special occasions | 04. At least once a month | 06. Once a week/ more than once a week | ELECTION STUDY NOTES - PORTUGAL (2019): E2014 | | Only respondents indicating a religious denomination in a | preceding question were asked about their religious service | attendance. | ELECTION STUDY NOTES - SLOVAKIA (2020): E2014 | | For the E2014 variable, the Slovakian study included one | additional category - "Less often than once a year." This | category has been recoded to CSES category "2. Once a year." | ELECTION STUDY NOTES - SWEDEN (2018): E2014 | | The answer categories for E2014 offered to respondents deviated | from CSES MODULE 5 standards. The variable was recoded as | follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Never | 02. About once in the last 12 months | 03. About once every six months | About once every three months | 04. About once every month | 06. About once every week | Several times a week | ELECTION STUDY NOTES - UNITED STATES (2016 & 2020): E2014 | | The answer categories for E2014 offered to respondents deviated | slightly from CSES MODULE 5 standards. Specifically, a category | for "once a year" (CSES code 2) was not included. | Further, respondents stating in a preceding question that they | never attended religious services apart from occasional | weddings, baptisms or funerals were coded "01. NEVER" for E2014. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Never | 03. A few times a year | 04. Once or twice a month | 05. Almost every week | 06. Every Week | ELECTION STUDY NOTES - URUGUAY (2019): E2014 | | Two answer categories for E2014 offered to respondents deviated | slightly from CSES MODULE 5 standards. The CSES convention | differentiates between the two categories "4. Once a month" and | "5. Two or more times a month". In the Uruguayan election study, | both categories were combined into "4. Once or more times a | month" (see below). | | CSES-Code Election study code/category |---------------------------------------------------------------- | 04. Once or more times a month --------------------------------------------------------------------------- E2015 >>> RACE --------------------------------------------------------------------------- D12. This item reports the respondent's race. .................................................................. 001.-995. RACE CODES [SEE ELECTION STUDY NOTES] 996. OTHER: NOT SPECIFIED 997. VOLUNTEERED: REFUSED 998. VOLUNTEERED: DON'T KNOW 999. MISSING | VARIABLE NOTES: E2015 | | E2015 is coded according to national standards. | | See also VARIABLE NOTES for variable E2016. | | Data are unavailable for ALBANIA (2017), AUSTRALIA (2019), | AUSTRIA (2017), BELGIUM-FLANDERS (2019), BELGIUM-WALLONIA (2019), | CANADA (2019), CHILE (2017), CZECHIA (2017 & 2021), DENMARK | (2019), FINLAND (2019), FRANCE (2017), GERMANY (2017 & 2021), | GREAT BRITAIN (2017 & 2019), GREECE (2015 & 2019), HONG KONG | (2016), HUNGARY (2018), INDIA (2019), IRELAND (2016), ISRAEL | (2020), ITALY (2018), JAPAN (2017), LATVIA (2018), LITHUANIA | (2020), NETHERLANDS (2017 & 2021), NORWAY (2017), PERU (2021), | POLAND (2019), PORTUGAL (2019), SLOVAKIA (2020), SOUTH KOREA | (2016), SWEDEN (2018), SWITZERLAND (2019), TAIWAN (2016 & 2020), | TUNISIA (2019) and TURKEY (2018). | ELECTION STUDY NOTES - BRAZIL (2018): E2015 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. White | 002. Black | 003. Brown | 004. Yellow | 005. Indigenous | ELECTION STUDY NOTES - COSTA RICA (2018): E2015 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. Black or African Descent | 002. Mulatto | 003. Chinese | 004. White or mestizo | ELECTION STUDY NOTES - EL SALVADOR (2019): E2015 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. White | 002. Mestizo | 003. Indigenous | 004. Black | 005. Mulatto | ELECTION STUDY NOTES - ICELAND (2016 & 2017): E2015 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. White | 002. Other | ELECTION STUDY NOTES - LITHUANIA (2016): E2015 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. White | ELECTION STUDY NOTES - LITHUANIA (2020): E2015 | | In the Lithuanian 2020 study, Collaborators coded all respondents | as being "White" for E2015. However, as this variable is not | based on respondent answers, E2015 was set to missing. | ELECTION STUDY NOTES - MEXICO (2018): E2015 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. Indigenous | 002. Mestizo | 003. White | 996. Other | ELECTION STUDY NOTES - MONTENEGRO (2016): E2015 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. White | ELECTION STUDY NOTES - NEW ZEALAND (2017 & 2020): E2015 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. Maori Descent | 002. Not Maori | ELECTION STUDY NOTES - ROMANIA (2016): E2015 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. White | 002. Asian | ELECTION STUDY NOTES - THAILAND (2019): E2015 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. Thai | 002. Chinese | ELECTION STUDY NOTES - UNITED STATES (2016): E2015 | | For E2015, respondents were allowed to name more than one race | they considered themselves to belong to. The answers were | precoded by the ANES as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. White, non-Hispanic | 002. Black, non-Hispanic | 003. Asian, native Hawaiian or other Pacific Islander, | non-Hispanic | 004. Native American or Alaska Native, non-Hispanic | 005. Hispanic | 006. Other non-Hispanic including multiple races; | Web-interviews: blank 'Other' counted as a race | | Respondents in web-interviews who indicated to identify with | another race than those given in the survey question, but who | did not specify which one, were coded as "06. Other." | ELECTION STUDY NOTES - UNITED STATES (2020): E2015 | | For E2015, respondents were allowed to name more than one race | they considered themselves to belong to. The answers were | pre-coded by the ANES as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. White, non-Hispanic | 002. Black, non-Hispanic | 003. Hispanic | 004. Asian or Native Hawaiian/other Pacific Islander, | non-Hispanic alone | 005. Native American/Alaska Native or other race, | non-Hispanic alone | 006. Multiple races, non-Hispanic | ELECTION STUDY NOTES - URUGUAY (2019): E2015 | | For E2015, respondents were allowed to name more than one race | they considered themselves to belong to. The answers were | precoded as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. White | 002. Afro/Black | 003. Indigenous | 004. Asiatic/ Yellow | 005. Mixed-White/Black | 006. Mixed-White/Indigenous | 007. Mixed-White/Asiatic | 008. Mixed-Black/Indigenous | 009. Mixed-Black/Asiatic --------------------------------------------------------------------------- E2016 >>> ETHNICITY --------------------------------------------------------------------------- D13. This variable reports the ethnic identity of respondents. .................................................................. 001.-995. ETHNICITY CODES [SEE ELECTION STUDY NOTES] 996. OTHER: NOT SPECIFIED 997. VOLUNTEERED: REFUSED 998. VOLUNTEERED: DON'T KNOW 999. MISSING | VARIABLE NOTES: E2016 | | E2016 is coded according to national standards. | | See also VARIABLE NOTES for variable E2015. | | Data are unavailable for AUSTRALIA (2019), AUSTRIA (2017), | BELGIUM-FLANDERS (2019), BELGIUM-WALLONIA (2019), BRAZIL (2018), | COSTA RICA (2018), CZECHIA (2017 & 2021), DENMARK (2019), EL | SALVADOR (2019), FINLAND(2019), FRANCE (2017), GERMANY (2017 & | 2021), HONG KONG (2016), ICELAND (2016 & 2017), IRELAND (2016), | ITALY (2018), JAPAN (2017), MEXICO (2018), NETHERLANDS (2017 & | 2021), NORWAY (2017), SOUTH KOREA (2016), SWEDEN (2018), | SWITZERLAND (2019), TURKEY (2018) and UNITED STATES (2016 & | 2020). | ELECTION STUDY NOTES - ALBANIA (2017): E2016 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. Albanian | 002. Greek | 003. Vlach | 004. Roma | 005. Egyptian | ELECTION STUDY NOTES - CANADA (2019): E2016 | | The variable is from the pre-election study. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. Canadian | 002. English | 003. Irish | 004. British | 005. French | 006. Italian | 007. Chinese | 008. German | 009. Polish | 010. Dutch | 011. Indian | 012. Scottish | 013. Ukrainian | 014. French Canadian | 015. Inuit, Metis, Aboriginal | 016. Quebecois | 017. Greek | 018. Haitian | 019. Portuguese | 020. Pakistani | 021. Austrian | 022. Hungarian | 023. Philippines | 024. US American | 025. Korean | 026. Danish | 027. Icelandic | 028. Turkish | 029. Jamaican | 030. Somalian | 031. Swiss | 032. Egyptian | 033. Romanian | 034. Spanish | 035. Russian | 036. Belgian | 037. Swedish | 038. Norwegian | 039. Lebanese | 040. Finish | 041. Czech | 042. Mexican | 043. Armenian | 044. Serbian | ELECTION STUDY NOTES - CHILE (2017): E2016 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. Alacalufe (Kawashkar) | 002. Atacameno | 003. Aimara | 004. Colla | 005. Mapuche | 006. Quechua | 007. Rapa Nui | 008. Diaguita | ELECTION STUDY NOTES - GREAT BRITAIN (2017): E2016 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. English/Welsh/Scottish/Northern Irish/British | 002. Irish | 003. Gypsy or Irish traveler | 004. White and Black Caribbean | 005. White and Black African | 006. White and Asian | 007. Indian | 008. Pakistani | 009. Bangladeshi | 010. Chinese | 011. African | 012. Caribbean | 013. Arab | 014. Polish | 015. Any other ethnic group | ELECTION STUDY NOTES - GREAT BRITAIN (2019): E2016 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. English/Welsh/Scottish/Northern Irish/British | 002. Irish | 003. Gypsy or Irish traveler | 004. Any other White background | 005. White and Black Caribbean | 006. White and Black African | 007. White and Asian | 008. Any other Mixed/Multiple ethnic background | 009. Indian | 010. Pakistani | 011. Bangladeshi | 012. Chinese | 013. Any other Asian background | 014. African | 015. Caribbean | 016. Any other Black/African/Caribbean background | 017. Arab | ELECTION STUDY NOTES - GREECE (2015): E2016 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. Greek | ELECTION STUDY NOTES - GREECE (2019): E2016 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. Greek | 996. Other | ELECTION STUDY NOTES - HUNGARY (2018): E2016 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. Hungarian | 002. Romany (Gypsy) | 003. Serbian, Croatian, Slovenian | 004. German (Swabian) | 005. Romanian | 006. Slovakian | ELECTION STUDY NOTES - INDIA (2019): E2016 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. Scheduled Caste (SC) | 002. Scheduled Tribe (ST) | 003. Other Backward Classes (OBC) | 004. General/Other | | For the Indian 2019 study, E2016 reports respondents' caste | group rather than ethnicity. The four groups coded in E2016 | reflect one of the official classifications of the population of | India used by public authorities, differentiating socio-economic | segments in the Indian society. | Further, Collaborators advise caste is arguably the most | important variable in Indian elections. At every stage, politics | is organized around caste identities - from local interest | groups to leaders to factions within parties to parties. Caste | is also a complex identity, drawing from ancient ideas of | ethnicity, and the 'Varna system', which organized society into | occupational groups. | | Additionally, Collaborators report the following characteristics | of caste groups: | 1. Scheduled Castes (also referred to as Dalits) constitute | the former "untouchables", forming the lowest strata of the | traditional Indian society. | 2. Scheduled Tribes refer to India's aboriginal population. They | include nomadic communities or communities living in forest | areas and are concentrated mainly in central and north- | eastern India. | 3. Other Backward Classes form the majority of the population in | most if not all Indian states. As such, OBC is a heterogeneous | category in terms of social status. Collaborators note albeit | not voting uniformly, most states have dominant OBC castes | covering a substantial amount of votes. | 4. General Category refers to the upper castes, i.e., the | traditional elites or privileged sections of society who | enjoyed "ritual" privileges of education and social status, | although not necessarily wealth. | ELECTION STUDY NOTES - ISRAEL (2020): E2016 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. Jewish | 002. Arab | ELECTION STUDY NOTES - LATVIA (2018): E2016 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. Latvian | 002. Russian | 003. Belorussian | 004. Ukrainian | ELECTION STUDY NOTES - LITHUANIA (2016 & 2020): E2016 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. Lithuanian | 002. Russian | 003. Pole | 004. Belorussian | 005. Ukrainian | 006. Latvian | 007. German | 996. Other | ELECTION STUDY NOTES - MONTENEGRO (2016): E2016 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. Montenegrin | 002. Serbian | 003. Albanian | 004. Bosniak | 005. Muslim | 006. Croatian | 007. Other | ELECTION STUDY NOTES - NEW ZEALAND (2017): E2016 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. NZ European | 002. Maori | 003. Maori and European | 004. Chinese | 005. Samoan | 006. Cook Island | 007. Tongan | 008. Nuie | 009. Other Pacific | 010. UK Irish | 011. Other European | 012. Indian | 013. Other Asian | 014. Kiwi NZ | 015. Others | ELECTION STUDY NOTES - NEW ZEALAND (2020): E2016 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. European | 002. Maori | 003. Pasifika | 004. Chinese | 005. Indian | ELECTION STUDY NOTES - PERU (2021): E2016 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. Quechua | 002. Aymara | 003. Native to the amazon | 004. Black | 005. Mulatto/ Zambo | 006. White | 007. Mestizo | ELECTION STUDY NOTES - POLAND (2019): E2016 | | 118 respondents answered this question with "none". These | respondents were recoded into "999. MISSING". | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. Polish | 002. Christian/ Catholic | 003. European | 004. White | 005. Silesian | 006. Slavic | ELECTION STUDY NOTES - PORTUGAL (2019): E2016 | | In the Portuguese 2019 study, respondents could select multiple | ethnicities they identified with from a list. Data were recoded | as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. White | 002. Black | 003. Roma | 004. White and Roma | 005. None of the above | | Additional to the answer options listed above, respondents could | choose an Asian or "Other" ethnicity. However, none of the | respondents in the sample selected any of these two options. | ELECTION STUDY NOTES - ROMANIA (2016): E2016 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. Romanian | 002. Hungarian | 003. Roma | 004. German | ELECTION STUDY NOTES - SLOVAKIA (2020): E2016 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. Slovak | 002. Hungarian | 003. Roma | 004. Czech | ELECTION STUDY NOTES - TAIWAN (2016): E2016 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. Taiwanese Hakka | 002. Taiwanese Min-Nan | 003. Mainlander | 004. Aboriginal | 005. Recent mainland immigrant | 006. Recent foreign immigrant | 007. Vietnamese | 008. Indonesian | ELECTION STUDY NOTES - TAIWAN (2020): E2016 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. Taiwanese Hakka | 002. Taiwanese Min-Nan | 003. Mainlander | 004. Aboriginal | 005. Recent mainland immigrant | 006. Recent foreign immigrant | 007. Vietnamese | 008. Indonesian | 009. Burmese | 010. Japanese | ELECTION STUDY NOTES - THAILAND (2019): E2016 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. Thai | 002. Chinese | 003. Lao | 004. Karen | 005. Lisu | 996. Others | ELECTION STUDY NOTES - TUNISIA (2019): E2016 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. Arabic | 002. African | 003. Berber | 004. Spanish | 005. Persian | 006. Aloui | 007. Tunisian | 008. Turkish | 009. Moroccan | 010. European | ELECTION STUDY NOTES - URUGUAY (2019): E2016 | | For the previous variable E2015, respondents were allowed to | name more than one race they considered themselves to belong to. | E2016 consists of the race that the respondent considered as | the main one. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 001. White | 002. Afro/Black | 003. Indigenous | 004. Asiatic/ Yellow --------------------------------------------------------------------------- E2017 >>> COUNTRY OF BIRTH --------------------------------------------------------------------------- D14. Respondent's country of birth. .................................................................. 004. AFGHANISTAN 008. ALBANIA 012. ALGERIA 024. ANGOLA 032. ARGENTINA 036. AUSTRALIA 040. AUSTRIA 050. BANGLADESH 056. BELGIUM 068. BOLIVIA (PLURINATIONAL STATE OF) 070. BOSNIA AND HERZEGOVINA 072. BOTSWANA 076. BRAZIL 100. BULGARIA 104. MYANMAR 112. BELARUS 116. CAMBODIA 120. CAMEROON 124. CANADA 144. SRI LANKA 152. CHILE 156. CHINA 158. TAIWAN 170. COLOMBIA 178. CONGO 184. COOK ISLANDS 188. COSTA RICA 191. CROATIA 192. CUBA 196. CYPRUS 200. CZECHOSLOVAKIA 203. CZECHIA 204. BENIN 208. DENMARK 214. DOMINICAN REPUBLIC 218. ECUADOR 222. EL SALVADOR 232. ERITREA 234. FAROE ISLANDS 238. FALKLAND ISLANDS (MALVINAS) 242. FIJI 246. FINLAND 250. FRANCE 275. STATE OF PALESTINE 276. GERMANY 288. GHANA 300. GREECE 304. GREENLAND 320. GUATEMALA 328. GUYANA 332. HAITI 340. HONDURAS 344. CHINA, HONG KONG SPECIAL ADMINISTRATIVE REGION 348. HUNGARY 352. ICELAND 356. INDIA 360. INDONESIA 364. IRAN (ISLAMIC REPUBLIC OF) 368. IRAQ 372. IRELAND 376. ISRAEL 380. ITALY 384. COTE D'IVOIRE 388. JAMAICA 392. JAPAN 398. KAZAKHSTAN 404. KENYA 410. REPUBLIC OF KOREA 414. KUWAIT 422. LEBANON 428. LATVIA 434. LIBYA 438. LIECHTENSTEIN 440. LITHUANIA 442. LUXEMBOURG 446. CHINA, MACAO SPECIAL ADMINISTRATIVE REGION 454. MALAWI 458. MALAYSIA 480. MAURITIUS 484. MEXICO 498. REPUBLIC OF MOLDOVA 499. MONTENEGRO 504. MOROCCO 516. NAMIBIA 524. NEPAL 528. NETHERLANDS 554. NEW ZEALAND 558. NICARAGUA 566. NIGERIA 578. NORWAY 586. PAKISTAN 591. PANAMA 598. PAPUA NEW GUINEA 600. PARAGUAY 604. PERU 608. PHILIPPINES 616. POLAND 620. PORTUGAL 630. PUERTO RICO 642. ROMANIA 643. RUSSIAN FEDERATION 682. SAUDI ARABIA 688. SERBIA 702. SINGAPORE 703. SLOVAKIA 704. VIET NAM 705. SLOVENIA 706. SOMALIA 710. SOUTH AFRICA 716. ZIMBABWE 724. SPAIN 740. SURINAME 752. SWEDEN 756. SWITZERLAND 760. SYRIAN ARAB REPUBLIC 764. THAILAND 776. TONGA 788. TUNISIA 792. TURKEY 795. TURKMENISTAN 804. UKRAINE 807. NORTH MACEDONIA 810. USSR 818. EGYPT 826. UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND 840. UNITED STATES OF AMERICA 858. URUGUAY 860. UZBEKISTAN 862. VENEZUELA (BOLIVARIAN REPUBLIC OF) 882. SAMOA 887. YEMEN 890. SOCIALIST FEDERAL REPUBLIC OF YUGOSLAVIA 891. SERBIA AND MONTENEGRO 894. ZAMBIA 900. [SEE ELECTION STUDY NOTES] 901. [SEE ELECTION STUDY NOTES] 902. [SEE ELECTION STUDY NOTES] 903. [SEE ELECTION STUDY NOTES] 904. [SEE ELECTION STUDY NOTES] 905. [SEE ELECTION STUDY NOTES] 906. [SEE ELECTION STUDY NOTES] 907. [SEE ELECTION STUDY NOTES] 996. OTHER: NOT SPECIFIED 997. VOLUNTEERED: REFUSED 998. VOLUNTEERED: DON'T KNOW 999. MISSING | VARIABLE NOTES: E2017 | | E2017 details respondents' country of birth based on country | codes provided by the United Nations Statistics Division | ("countries or areas, codes and abbreviations", revised | February 13, 2002), similar to E1003 and E1006_UN. | | Whenever this is not possible, due to referring to a country | that does not exist anymore, earlier country codes, according to | https://unstats.un.org/unsd/methods/m49/m49chang.htm were | employed. | | As long as a question on respondents' country of birth was | included in the questionnaire, native-born citizens were coded | according to the country code of the appropriate state. | | Data are unavailable for FINLAND (2019), NORWAY (2017), SOUTH | KOREA (2016) and UNITED STATES (2016). | ELECTION STUDY NOTES - AUSTRALIA (2019): E2017 | | The Australian study did not ask about specific country of birth | of respondents for all those born outside of Australia. They have | grouped all other countries into two following categories: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 900. Mainly Non-English speaking background | 901. Mainly English speaking background | ELECTION STUDY NOTES - CANADA (2019): E2017 | | The variable is from the pre-election study. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 901. China, Hong Kong, Taiwan | ELECTION STUDY NOTES - FRANCE (2017): E2017 | | The French 2017 study only distinguishes between respondents | being born in vs. outside of France. Persons who were born | outside of France were coded to 996. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 996. Born outside of France | ELECTION STUDY NOTES - GERMANY (2017): E2017 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 900. Former German Territories in Eastern EU | 901. Denmark, Sweden, Norway, Finland | ELECTION STUDY NOTES - GERMANY (2021): E2017 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 200. Slovakia, Czech Republic, former Czechoslovakia | 810. Russian Federation, former Soviet Union | 890. Croatia, Serbia, Bosnia and Herzegovina, former | Yugoslavia | 900. Former German Territories in Eastern Europe | ELECTION STUDY NOTES - HUNGARY (2018): E2017 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 996. Not in Hungary | ELECTION STUDY NOTES - INDIA (2019): E2017 | | According to E2017, all respondents in the Indian 2019 study | were born in India, such that there is no variability in country | of birth in the data. Collaborators confirm E2017 was included in | the survey and explain that numbers are plausible: India has a | very small immigrant population, with immigrants rarely obtaining | voting rights. Further, Collaborators note the political context | may induce respondents to report Indian origin. | ELECTION STUDY NOTES - IRELAND (2016): E2017 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 900. Africa | Other (Not further specified) | ELECTION STUDY NOTES - JAPAN (2017): E2017 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 996. Not Japan | ELECTION STUDY NOTES - MONTENEGRO (2016): E2017 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 900. Kosovo | ELECTION STUDY NOTES - NETHERLANDS (2017): E2017 | | In the Dutch 2017 study, data on respondents' country of birth | has not been collected in the survey but was obtained from | population registers. Respondents provided consent before data | collection. | Generally, register data are based on the most recent available | data, usually the year preceding data collection. | | Further, the study only distinguishes between respondents with | Dutch, Western, and non-Western origin. For E2017, data have | been recoded as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 528. Dutch origin | 900. Western origin | 901. Non-Western origin | ELECTION STUDY NOTES - NETHERLANDS (2021): E2017 | | The Dutch 2021 election study is comprised of two independent | sampling components: a simple random sample drawn from | population registers self-administered either online or via | mail-back, and a sample drawn from the ongoing "LISS" online | panel. | Data in E2017 are available for respondents from the first | sampling component (register sample) only. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 900. Dutch Antilles | 901. Other MENA | 902. Other Africa | 903. Other Asia | 904. Other Latin America | 905. Other Europe | 906. North America | 907. Oceania | ELECTION STUDY NOTES - NEW ZEALAND (2017): E2017 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 900. Channel Islands | 901. Nive Islands | ELECTION STUDY NOTES - NEW ZEALAND (2020): E2017 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 900. Other Europe | 901. Other Africa | 902. Other Asia | 903. Latin America | 904. Middle East | 905. Pacific | ELECTION STUDY NOTES - PERU (2021): E2017 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 996. Born outside of Peru | ELECTION STUDY NOTES - PORTUGAL (2019): E2017 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 900. Former Portuguese Colony (Angola, Cabo Verde, | Guinea-Bissau, Goa, Macao, Mozambique, Sao Tome) | ELECTION STUDY NOTES - SLOVAKIA (2020): E2017 | | The Slovakian 2020 study only distinguishes between respondents | being born in Slovakia, Czechia or other countries. Respondents | born outside of Slovakia and Czechia were coded to 996. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 996. Born outside of both Slovakia and Czechia | ELECTION STUDY NOTES - SWEDEN (2018): E2017 | | The answer categories for E2017 offered to respondents deviated | from CSES MODULE 5 standards. Rather than stating their country | of birth, respondents were asked where they primarily grew up, | distinguishing between several areas in Sweden, Europe and | outside of Europe. These answer categories have been recoded as | follows for the Swedish 2018 study: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 752. In the countryside in Sweden | In a small urban area in Sweden | In a city or larger urban area in Sweden | In Stockholm, Gothenburg or Malmo | 900. In another country in the Nordics | 901. In another country in Europe | 902. In another country outside of Europe | ELECTION STUDY NOTES - SWITZERLAND (2019): E2017 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 900. Kosovo | ELECTION STUDY NOTES - UNITED STATES (2020): E2017 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 840. A U.S. state or Washington D.C. | 630. Puerto Rico | 900. Another U.S. territory (Guam, American Samoa, | U.S. Virgin Islands) --------------------------------------------------------------------------- E2018 >>> WAS EITHER BIOLOGICAL PARENT BORN OUTSIDE OF THE COUNTRY --------------------------------------------------------------------------- D15. Was either biological parent born outside of [COUNTRY]? .................................................................. 0. NO 1. YES 7. VOLUNTEERED: REFUSED 8. VOLUNTEERED: DON'T KNOW 9. MISSING | VARIABLE NOTES: E2018 | | Data are unavailable for AUSTRALIA (2019), JAPAN (2017), | NETHERLANDS (2017), NORWAY (2017), SOUTH KOREA (2016) and URUGUAY | (2019). | ELECTION STUDY NOTES - DENMARK (2019): E2018 | | In the 2019 Danish election study, respondents were asked | separately for each parent whether they were born in Denmark. | The following table lists how answers to both questions were | combined for E2018: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 0. Both father and mother were born in Denmark | 1. At least one parent born outside of Denmark | 7. Refused to answer for both mother and father | whether born in or outside of Denmark | 8. Don't know for both parents whether born in or | outside of Denmark | First parent born in Denmark, don't know whether | second parent born in or outside of Denmark | ELECTION STUDY NOTES - FRANCE (2017): E2018 | | The French election study asked respondents whether they had | one or more foreign parents. Answers were coded as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 0. None of the parents | 1. Yes, one parent | Yes, both parents | ELECTION STUDY NOTES - HONG KONG (2016): E2018 | | In the 2016 Hong Kong election study, interviewers asked | respondents separately for each parent whether they were | born in Hong Kong. The following table lists how answers to both | questions were combined for E2018: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 0. Both father and mother born in Hong Kong | 1. At least one parent born outside of Hong Kong | 7. Refused to answer for both mother and father | whether born in or outside of Hong Kong | 8. Don't know for both parents whether born in or | outside of Hong Kong | First parent born in Hong Kong, don't know whether | second parent born in or outside of Hong Kong | ELECTION STUDY NOTES - INDIA (2019): E2018 | | According to E2018, the biological parents of all respondents in | the Indian 2019 study were born in India, such that there is no | variability on parental origin in the data. Collaborators confirm | E2018 was included in the survey and explain numbers are | plausible: India has a very small immigrant population, with | immigrants rarely obtaining voting rights. Further, Collaborators | note the political context may induce respondents to report | Indian origin. | ELECTION STUDY NOTES - MEXICO (2018): E2018 | | In the Mexican 2018 study, E2018 was only asked to those | respondents stating to have been born outside of Mexico in | variable E2017 (N = 2). | ELECTION STUDY NOTES - NETHERLANDS (2021): E2018 | | The Dutch 2021 election study is comprised of two independent | sampling components: a simple random sample drawn from | population registers self-administered either online or via | mail-back, and a sample drawn from the ongoing "LISS" online | panel. | Data in E2018 is available for respondents from the first | sampling component (register sample) only. | | Further, the study collected data on each parent's country of | birth separately. The following table lists how answers to both | questions were combined for E2018: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 0. Both father and mother born in the Netherlands | 1. At least one parent born outside of the | Netherlands | 7. Refused to answer for both mother and father | whether born in or outside of the Netherlands; | Data missing for first parent, won't say whether | second parent born in or outside of the | Netherlands | 8. Don't know for both parents whether born in or | outside of the Netherlands | ELECTION STUDY NOTES - PORTUGAL (2019): E2018 | | The Portuguese study asked respondents whether either biological | parent was born outside of Portugal. Answers were coded as | follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 0. No | 1. Yes, one of them | Yes, both | ELECTION STUDY NOTES - SLOVAKIA (2020): E2018 | | In the 2020 Slovakian study, interviewers asked respondents | separately for each parent whether they were born in or outside | of Slovakia. The following table lists how answers to both | questions were combined for E2018: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 0. Both father and mother born in Slovakia | 1. At least one parent born outside of Slovakia | 8. Don't know for both parents whether born in or | outside of Slovakia | First parent born in Slovakia, don't know whether | second parent born in or outside of Slovakia | ELECTION STUDY NOTES - SWEDEN (2018): E2018 | | In the 2018 Swedish election study, respondents were not asked | about their parent's country of birth, but where their parents | mainly grew up. Specifically, respondents were asked separately | for each parent whether they grew up in Sweden or any other | country, distinguishing between the Nordics, Europe and | countries outside of Europe. The following table lists how | answers to both questions were combined for E2018: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 0. Both father and mother grew up in Sweden | 1. At least one parent grew up outside of Sweden | 9. First parent grew up in Sweden, R did not | provide information on second parent | R did not answer question for any of the parents | ELECTION STUDY NOTES - UNITED STATES (2020): E2018 | | The ANES 2020 study asked respondents whether they had one or | more parents born in the U.S. Answers were coded as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 0. Both parents born in the US | 1. One parent born in the US | Both parents born in another country | 7. Refused | 8. Don't know --------------------------------------------------------------------------- E2019 >>> LANGUAGE USUALLY SPOKEN AT HOME --------------------------------------------------------------------------- D16. Language usually spoken in the respondent's household. .................................................................. 001. AFRIKAANS 002. ALBANIAN, ARVANITIKA 003. ALBANIAN, GHEG 004. ALBANIAN, TOSK 007. ARABIC, JUDEO-MOROCCAN 008. ARABIC, LEVANTINE (ISRAEL) 012. AYMARA, CENTRAL (ARGENTINA, PERU) 014. BELORUSSIAN 016. BENGALI, BANGLADESHI, BANGLA (INDIA) 017. BHOJPURI (INDIA) 018. BOSNIAN 020. BULGARIAN 276. CENTRAL THAI 203. CHINESE, CANTONESE 023. CHINESE, HAKKA 024. CHINESE, MANDARIN 025. CHINESE, MIN NAN 027. CROATIAN 028. CZECH 029. DANISH 031. DUTCH 032. ENGLISH 034. ESTONIAN 035. FINNISH 036. FRENCH 044. GERMAN, STANDARD 045. GREEK 047. GUJARATI (SOUTH AFRICA, INDIA) 048. HEBREW 049. HUNGARIAN 051. HINDI 050. ICELANDIC 278. ISAN THAI 052. ITALIAN 054. JAPANESE 055. KANNADA (INDIA) 066. KOREAN 232. KURDISH 277. LANNA THAI 063. LATVIAN 068. LITHUANIAN 074. MAITHILI (INDIA) 075. MALAY 076. MALAYALAM (INDIA) 080. MAORI 082. MARATHI (INDIA) 085. MONTENEGRIN 092. ORIYA (INDIA) 246. PANGASINENSE (PHILIPPINES) 094. PANJABI, EASTERN (INDIA) 096. POLISH 097. PORTUGUESE 098. PROVENCAL 219. PUSHTO (PAKISTAN) 099. QUECHUA, ANCASH, HUAYLAS 103. ROMANI, BALKAN 104. ROMANI, CARPATHIAN 106. ROMANIAN 109. RUSSIAN 111. SCHWYZERDUTSCH (SWITZERLAND) 112. SERB 113. SERBO-CROATIAN 117. SLOVAK 281. SOUTHERN THAI 121. SPANISH 123. SWEDISH 240. TAGALOG (PHILIPPINES) 124. TAMIL (INDIA) 126. TELUGU (INDIA) 128. TICANESE (SWITZERLAND) 129. TONGA (ZAMBIA) 134. TURKISH 135. UKRAINIAN 136. URDU (INDIA) 225. VIETNAMESE 139. WELSH 980. [SEE ELECTION STUDY NOTES] 981. [SEE ELECTION STUDY NOTES] 982. [SEE ELECTION STUDY NOTES] 983. [SEE ELECTION STUDY NOTES] 984. [SEE ELECTION STUDY NOTES] 985. [SEE ELECTION STUDY NOTES] 986. [SEE ELECTION STUDY NOTES] 987. [SEE ELECTION STUDY NOTES] 988. [SEE ELECTION STUDY NOTES] 989. [SEE ELECTION STUDY NOTES] 996. OTHER: NOT SPECIFIED 997. VOLUNTEERED: REFUSED 998. VOLUNTEERED: DON'T KNOW 999. MISSING | VARIABLE NOTES: E2019 | | E2019 details the language usually spoken in the respondent's | household. If more than one language is spoken at home, E2019 | reports the language spoken most of the time. | | Coding of E2019 follows the scheme of E1035 (language of | questionnaire administration). | | Data are unavailable for IRELAND (2016), JAPAN (2017), | NETHERLANDS (2017 & 2021), NORWAY (2017), SLOVAKIA (2020), SOUTH | KOREA (2016), SWEDEN (2018) and UNITED STATES (2016 & 2020). | ELECTION STUDY NOTES - AUSTRALIA (2019): E2019 | | The question in the Australian study was "Do you speak a language | other than English at home?" | Respondents answering "No" are coded as those speaking English. | Respondents answering "Yes" are coded as "996. Other language | (not specified)" since there was not a follow-up question about | what other language they speak at home. | ELECTION STUDY NOTES - BRAZIL (2018): E2019 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 980. Esperanto | 981. Indigenous language / "caipanga" / "tupi guarani" | ELECTION STUDY NOTES - FRANCE (2017): E2019 | | The French 2017 study only distinguishes between respondents | who speak French or any other language at home. Persons who | stated not to speak French at home were coded to 996. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 996. Another language than French | ELECTION STUDY NOTES - GERMANY (2017): E2019 | | In the German 2017 study, E2019 was assessed by two survey | questions. In a first question, respondents were asked whether | they usually speak either German or any other language at home. | Only respondents stating to speak a language other than German | at home were asked to specify that language in a follow-up | question. | ELECTION STUDY NOTES - GREAT BRITAIN (2017): E2019 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 980. Other (not English and not Welsh) | ELECTION STUDY NOTES - ICELAND (2016): E2019 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 980. Icelandic and English | 981. Faroese | 982. Sign Language | 983. Icelandic and Bulgarian | 984. Icelandic and Danish | 985. Icelandic and Norwegian | ELECTION STUDY NOTES - ICELAND (2017): E2019 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 980. Nepalese | 981. Faroese | ELECTION STUDY NOTES - INDIA (2019): E2019 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 980. Assamese | 981. Bundeli | 982. Chhattisgarhi | 983. Haryanvi | 984. Khortha | 985. Lodhi | 986. Nepali | 987. Sadri | 988. Santali | ELECTION STUDY NOTES - ITALY (2018): E2019 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 980. Dialect/Regional language | ELECTION STUDY NOTES - NEW ZEALAND (2017): E2019 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 980. Amharic | 981. Khmer | 982. Fijian | 983. Nepali | 984. Samoan | ELECTION STUDY NOTES - NEW ZEALAND (2020): E2019 | | The question wording deviates from the CSES MODULE 5 standards. | The question was "In which language(s) could you have a | conversation about a lot of everyday things?" | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 980. Samoan, Nuiean, Tongan, and the native language | of Vanuatu | ELECTION STUDY NOTES - PORTUGAL (2019): E2019 | | The Portuguese 2019 study only distinguishes between respondents | who speak Portuguese or any other language at home. Persons who | stated not to speak Portuguese at home were coded to 996. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 996. Language other than Portuguese | ELECTION STUDY NOTES - SWITZERLAND (2019): E2019 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 980. Romansh (Switzerland) | ELECTION STUDY NOTES - TAIWAN (2016): E2019 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 980. Taiwanese | 981. Both Mandarin and Taiwanese | 982. Both Mandarin and Hakka | 983. Both Mandarin and other Chinese dialect | 984. Both Taiwanese and Hakka | 985. Aboriginal language | 986. Other Chinese dialect | 987. Both Mandarin and Aboriginal language | 988. Mandarin, Taiwanese and Hakka | 989. Burmese | ELECTION STUDY NOTES - TAIWAN (2020): E2019 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 980. Taiwanese | 981. Aboriginal language | 982. Other Chinese dialect | 983. Both Mandarin and Taiwanese | 984. Both Mandarin and Hakka | 985. Both Taiwanese and Hakka | 986. Both Mandarin and other Chinese dialect | 987. Mandarin, Taiwanese and English | 988. Both Mandarin and English | 989. Mandarin, Taiwanese and Hakka | ELECTION STUDY NOTES - THAILAND (2019): E2019 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 980. Hill tribe language | ELECTION STUDY NOTES - TUNISIA (2019): E2019 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 980. Tunisian dialect | 981. Berber language | ELECTION STUDY NOTES - TURKEY (2018): E2019 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 980. Uzbek | 981. Turkmen | ELECTION STUDY NOTES - URUGUAY (2019): E2019 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 980. Portunol (mixed Spanish and Portuguese) --------------------------------------------------------------------------- E2020 >>> REGION OF RESIDENCE --------------------------------------------------------------------------- D17. Respondent's region of residence. .................................................................. 01.-80. REGION CODES [SEE ELECTION STUDY NOTES] 99. MISSING | VARIABLE NOTES: E2020 | | E2020 details the respondent's region of residence. Regions are | usually (but not always) based upon the social, cultural, or | historical differences (though some correspond to administrative | regions) that manifest themselves in political cleavages. | | Data are unavailable for BELGIUM-FLANDERS (2019), | BELGIUM-WALLONIA (2019), HONG KONG (2016) and ISRAEL (2020). | ELECTION STUDY NOTES - ALBANIA (2017): E2020 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Berat | 02. Diber | 03. Durres | 04. Elbasan | 05. Fier | 06. Gjirokaster | 07. Korce | 08. Kukes | 09. Lezhe | 10. Shkoder | 11. Tirane | 12. Vlore | ELECTION STUDY NOTES - AUSTRALIA (2019): E2020 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. New South Wales | 02. Victoria | 03. Queensland | 04. South Australia | 05. Western Australia | 06. Tasmania | 07. Northern Territory | 08. Australian Capital Territory | ELECTION STUDY NOTES - AUSTRIA (2017): E2020 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Vorarlberg | 02. Tyrol | 03. Salzburg | 04. Upper Austria | 05. Carinthia | 06. Styria | 07. Burgenland | 08. Lower Austria | 09. Vienna | ELECTION STUDY NOTES - BRAZIL (2018): E2020 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. North | 02. Northeast | 03. Southeast | 04. South | 05. Midwest | ELECTION STUDY NOTES - CANADA (2019): E2020 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Alberta | 02. British Columbia | 03. Manitoba | 04. New Brunswick | 05. Newfoundland and Labrador | 06. Nova Scotia | 07. Ontario | 08. Prince Edward Island | 09. Saskatchewan | 10. Quebec | ELECTION STUDY NOTES - CHILE (2017): E2020 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Tarapaca | 02. Antofagasta | 03. Atacama | 04. Coquimbo | 05. Valparaiso | 06. O'Higgins | 07. Maule | 08. Bio Bio | 09. Araucania | 10. Los Lagos | 11. Aysen | 12. Magallanes | 13. Metropolitana | 14. Los Rios | 15. Artica y Parinacota | ELECTION STUDY NOTES - COSTA RICA (2018): E2020 | | For the Costa Rican 2018 election study, the region of residence | categories are the same as the primary electoral district | categories (E2021). | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Alajuela | 02. Cartago | 03. Guanacaste | 04. Heredia | 05. Limon | 06. Puntarenas | 07. San Jose | ELECTION STUDY NOTES - CZECHIA (2017): E2020 | | CSES-Code Election study code/category |---------------------------------------------------------------- | 01. Hlavni mesto Praha | 02. Benesov | 03. Kladno | 04. Kolin | 05. Kutna Hora | 06. Mlada Boleslav | 07. Nymburk | 08. Praha | 09. Pribram | 10. Rakovnik | 11. Ceske Budejovice | 12. Cesky Krumlov | 13. Jindrichuv Hradec | 14. Pisek | 15. Prachatice | 16. Strakonice | 17. Tabor | 18. Klatovy | 19. Plzen - mesto | 20. Plzen - sever | 21. Tachov | 22. Cheb | 23. Karlovy Vary | 24. Sokolov | 25. Decin | 26. Chomutov | 27. Litomerice | 28. Louny | 29. Most | 30. Teplice in Bohemia | 31. Usti nad Labem | 32. Ceska Lipa | 33. Jablonec nad Nisou | 34. Liberec | 35. Semily | 36. Hradec Kralove | 37. Jicin | 38. Nachod | 39. Rychnov nad Kneznou | 40. Chrudim | 41. Pardubice | 42. Svitavy | 43. Usti nad Orlici | 44. Havlickuv Brod | 45. Jihlava | 46. Pelhrimov | 47. Trebic | 48. Zdar nad Sazavou | 49. Blansko | 50. Brno - mesto | 51. Brno - venkov | 52. Breclav | 53. Hodonin | 54. Vyskov | 55. Znojmo | 56. Jesenik | 57. Olomouc | 58. Prostejov | 59. Prerov | 60. Sumperk | 61. Kromeriz | 62. Uherske Hradiste | 63. Vsetin | 64. Zlin | 65. Bruntal | 66. Frydek | 67. Karvina | 68. Novy Jicin | 69. Opava | 70. Ostrava | ELECTION STUDY NOTES - CZECHIA (2021): E2020 | | CSES-Code Election study code/category |---------------------------------------------------------------- | 01. Hlavni mesto Praha | 02. Benesov | 03. Melnik | 04. Mlada Boleslav | 05. Nymburk | 06. Pribram | 07. Rakovnik | 08. Ceske Budejovice | 09. Pisek | 10. Prachatice | 11. Strakonice | 12. Tabor | 13. Plzen - mesto | 14. Plzen - sever | 15. Tachov | 16. Cheb | 17. Karlovy Vary | 18. Sokolov | 19. Decin | 20. Litomerice | 21. Louny | 22. Most | 23. Teplice in Bohemia | 24. Usti nad Labem | 25. Semily | 26. Jicin | 27. Nachod | 28. Rychnov nad Kneznou | 29. Chrudim | 30. Pardubice | 31. Usti nad Orlici | 32. Havlickuv Brod | 33. Jihlava | 34. Pelhrimov | 35. Trebic | 36. Brno - mesto | 37. Brno - venkov | 38. Vyskov | 39. Znojmo | 40. Olomouc | 41. Prerov | 42. Sumperk | 43. Kromeriz | 44. Uherske Hradiste | 45. Vsetin | 46. Zlin | 47. Frydek | 48. Karvina | 49. Opava | 50. Ostrava - mesto | ELECTION STUDY NOTES - DENMARK (2019): E2020 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Capital Region of Denmark (Hovedstaden) | 02. Zealand Region (Sjaelland) | 03. Region of Southern Denmark (Syddanmark) | 04. Central Denmark Region (Midtjylland) | 05. North Denmark Region (Nordjylland) | ELECTION STUDY NOTES - EL SALVADOR (2019): E2020 | | CSES-Code Election study code/category |---------------------------------------------------------------- | 01. Occidental | 02. Central | 03. Paracentral | 04. Oriental | ELECTION STUDY NOTES - FINLAND (2019): E2020 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Uusimaa | 02. Southwest Finland | 04. Satakunta | 05. Kanta-Hame | 06. Pirkanmaa | 07. Paijaet-Hame | 08. Kymenlaakso | 09. South Karelia | 10. South Savo | 11. North Savo | 12. North Karelia | 13. Central Finland | 14. South Ostrobothnia | 15. Ostrobothnia | 16. Central Ostrobothnia | 17. North Ostrobothnia | 18. Kainuu | 19. Lapland | | The region Aland Islands was not sampled. Approximately 0.65% of | the population are therefore not included in the sample frame. | | Region of residence was not asked in the survey. The data for | E2020 were derived from municipality codes. The original | municipality variable was removed from the data because of | confidentiality issues. | ELECTION STUDY NOTES - FRANCE (2017): E2020 | | The codes documented below refer to the strata used for sampling. | These strata are larger than any French administrative region. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. West | 02. South West | 03. South East | 04. Center | 05. East | 06. Paris Area | 07. North | ELECTION STUDY NOTES - GERMANY (2017 & 2021): E2020 | | Respondents were not asked a question regarding their region of | residence. Instead, the variable was created using the | respective information from the interviewer protocols (2017 | study) or the register sample (2021 study). | | CSES-Code Election study code/category |---------------------------------------------------------------- | 01. Baden-Wuerttemberg | 02. Bavaria | 03. Berlin | 04. Brandenburg | 05. Bremen | 06. Hamburg | 07. Hesse | 08. Mecklenburg-Western Pomerania | 09. Lower Saxony | 10. North Rhine-Westphalia | 11. Rhineland Palatinate | 12. Saarland | 13. Saxony | 14. Saxony-Anhalt | 15. Schleswig-Holstein | 16. Thuringia | ELECTION STUDY NOTES - GREAT BRITAIN (2017 & 2019): E2020 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. East Midlands | 02. Eastern | 03. London | 04. North East | 05. North West | 06. Scotland | 07. South East | 08. South West | 09. Wales | 10. West Midlands | 11. Yorkshire & Humber | ELECTION STUDY NOTES - GREECE (2015): E2020 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 02. Prefecture of Aitoloakarnania | 03. Prefecture of Argolida | 04. Prefecture of Arcadia | 05. Prefecture of Arta | 06. Prefecture of Attica | 07. Prefecture of Achaia | 08. Prefecture of Voiotia | 10. Prefecture of Drama | 11. Prefecture of Dodecanese | 12. Prefecture of Evros | 13. Prefecture of Evoia | 15. Prefecture of Zakynthos | 16. Prefecture of Ilia | 17. Prefecture of Imathia | 18. Prefecture of Heracleion | 19. Prefecture of Thesprotia | 20. Prefecture of Thessaloniki | 21. Prefecture of Ioannina | 22. Prefecture of Kavala | 23. Prefecture of Karditsa | 24. Prefecture of Kastoria | 25. Prefecture of Kerkyra | 26. Prefecture of Kefallinia | 27. Prefecture of Kilkis | 28. Prefecture of Kozani | 29. Prefecture of Corithia | 30. Prefecture of Cyclades | 31. Prefecture of Lakonia | 32. Prefecture of Larisa | 33. Prefecture of Lasithi | 34. Prefecture of Lesbos | 36. Prefecture of Magnesia | 37. Prefecture of Messinia | 38. Prefecture of Xanthi | 39. Prefecture of Pella | 40. Prefecture of Pieria | 41. Prefecture of Preveza | 42. Prefecture of Rethimnon | 43. Prefecture of Rodopi | 44. Prefecture of Samos | 45. Prefecture of Serres | 46. Prefecture of Trikala | 47. Prefecture of Fthiotida | 48. Prefecture of Florina | 49. Prefecture of Fokida | 50. Prefecture of Chalkidiki | 51. Prefecture of Chania | 52. Prefecture of Chios | ELECTION STUDY NOTES - GREECE (2019): E2020 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Anatoliki Makedonia, Thraki | 02. Kentriki Makedonia | 03. Dytiki Makedonia | 04. Thessalia | 05. Ipeiros | 06. Ionia Nisia | 07. Dytiki Ellada | 08. Sterea Ellada | 09. Peloponnisos | 10. Attiki | 11. Voreio Aigaio | 12. Notio Aigaio | 13. Kriti | ELECTION STUDY NOTES - HUNGARY (2018): E2020 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Budapest | 02. Baranya | 03. Bacs-Kiskun | 04. Bekes | 05. BAZ | 06. Csongrad | 07. Fejer | 08. Gyor-Moson-Sopron | 09. Hajdu-Bihar | 10. Heves | 11. Komarom-Eszter | 12. Nograd | 13. Pest | 14. Somogy | 15. Szabolcs-Szatmar-Bereg | 16. Jasz-Nagykun-Szolnok | 17. Tolna | 18. Vas | 19. Veszprem | 20. Zala | ELECTION STUDY NOTES - ICELAND (2016 and 2017): E2020 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Capital area | 02. Reykjanes Peninsula | 03. West | 04. Westfjords | 05. North-West | 06. North-East | 07. East | 08. South | ELECTION STUDY NOTES - INDIA (2019): E2020 | | E2020 reports the state or union territory a respondent was | living in at the time of the interview. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Andhra Pradesh | 03. Assam | 04. Bihar | 06. Gujarat | 07. Haryana | 10. Karnataka | 11. Kerala | 12. Madhya Pradesh | 13. Maharashtra | 18. Odisha | 19. Punjab | 20. Rajasthan | 22. Tamil Nadu | 24. Uttar Pradesh | 25. West Bengal | 30. Delhi | 33. Jharkhand | 34. Chhattisgarh | 36. Telangana | ELECTION STUDY NOTES - IRELAND (2016): E2020 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Carlow | 02. Cavan | 03. Clare | 04. Cork | 05. Donegal | 06. Dublin | 07. Galway | 08. Kerry | 09. Kildare | 10. Kilkenny | 11. Laois | 12. Leitrim | 13. Limerick | 14. Longford | 15. Louth | 16. Mayo | 17. Meath | 18. Monaghan | 19. Offaly | 20. Roscommon | 21. Sligo | 22. Tipperary | 23. Waterford | 24. Westmeath | 25. Wexford | 26. Wicklow | ELECTION STUDY NOTES - ITALY (2018): E2020 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Piemonte | 02. Lombardia | 03. Trentino Alto Adige | 04. Veneto | 05. Friuli Venezia Giulia | 06. Liguria | 07. Emilia Romagna | 08. Toscana | 09. Umbria | 10. Marche | 11. Lazio | 12. Abruzzo | 13. Molise | 14. Campania | 15. Puglia | 16. Calabria | 17. Sicilia | 18. Sardegna | ELECTION STUDY NOTES - JAPAN (2017): E2020 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Hokkaido | 02. Aomori | 03. Iwate | 04. Miyagi | 05. Akita | 06. Yamagata | 07. Fukushima | 08. Ibaraki | 09. Tochigi | 10. Gunma | 11. Saitama | 12. Chiba | 13. Tokyo | 14. Kanagawa | 15. Niigata | 16. Toyama | 17. Ishikawa | 18. Fukui | 19. Yamanashi | 20. Nagano | 21. Gifu | 22. Shizuoka | 23. Aichi | 24. Mie | 25. Shiga | 26. Kyoyo | 27. Osaka | 28. Hyogo | 29. Nara | 30. Wakayama | 31. Tottori | 32. Shimane | 33. Okayama | 34. Hiroshima | 35. Yamaguchi | 36. Tokushima | 37. Kagawa | 38. Ehime | 39. Kochi | 40. Fukuoka | 41. Saga | 42. Nagasaki | 43. Kumamoto | 44. Oita | 45. Miyazaki | 46. Kagoshima | 47. Okinawa | ELECTION STUDY NOTES - LATVIA (2018): E2020 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Riga | 02. Pieriga | 03. Vidzeme | 04. Kurzeme | 05. Zemgale | 06. Latgale | ELECTION STUDY NOTES - LITHUANIA (2016 & 2020): E2020 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Altyus county | 02. Kaunas county | 03. Klaipeda county | 04. Marijampole county | 05. Panevezys county | 06. Siauliai county | 07. Taurage county | 08. Telsiai county | 09. Utena county | 10. Vilnus county | 11. Non-Lithuania (living abroad) | | The Lithuanian 2020 study includes twelve respondents residing | outside of Lithuania. These respondents were eligible to vote | in 2020 and are identified with code 11 in E2020. | Collaborators note working and living abroad while returning to | Lithuania regularly is common for some Lithuanian citizens. In | instances where expatriates do not register as emigrants, they | remain listed in the voting registers in Lithuania based on their | former residency or the address of their owned real estate, if | applicable. | ELECTION STUDY NOTES - MEXICO (2018): E2020 | | For the Mexican 2018 study, E2018 denotes the state a respondent | resided in. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 02. Baja California | 03. Baja California Sur | 04. Campeche | 05. Coahuila | 07. Chiapas | 08. Chihuahua | 09. Ciudad De Mexico | 10. Durango | 11. Guanajuato | 12. Guerrero | 13. Hidalgo | 14. Jalisco | 15. Mexico | 16. Michoacan | 17. Morelos | 18. Nayarit | 19. Nuevo Leon | 20. Oaxaca | 21. Puebla | 22. Queretaro | 23. Quintana Roo | 24. San Luis Potosi | 25. Sinaloa | 26. Sonora | 27. Tabasco | 28. Tamaulipas | 29. Tlaxcala | 30. Veracruz | 31. Yucatan | ELECTION STUDY NOTES - MONTENEGRO (2016): E2020 | | The regions of residence listed below correspond to the three | geographical regions used as primary sampling units for the 2016 | Montenegrin election study. For further information, see | Codebook Part 6, and the Design Report for Montenegro 2016. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. South | 02. Center | 03. North | ELECTION STUDY NOTES - NETHERLANDS (2017 & 2021): E2020 | | In the Dutch 2017 and 2021 studies, data on respondents' region | of residence has not been collected in the survey but was | obtained from population registers. Respondents provided consent | before data collection. | Generally, register data are based on the most recent available | data, usually the year preceding data collection. | | The Dutch 2021 election study is comprised of two independent | sampling components: a simple random sample drawn from | population registers self-administered either online or via | mail-back, and a sample drawn from the ongoing "LISS" online | panel. For the 2021 study, data in E2020 are available for | respondents from the first sampling component (register sample) | only. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. North | 02. East | 03. West | 04. South | ELECTION STUDY NOTES - NEW ZEALAND (2017 & 2020): E2020 | | CSES-Code Election study code/category |---------------------------------------------------------------- | 01. Northland | 02. Auckland | 03. Waikato | 04. Bay of Plenty | 05. Gisborne | 06. Hawke's Bay | 07. Taranaki | 08. Manawatu-Wanganui | 09. Wellington | 12. West Coast | 13. Canterbury | 14. Otago | 15. Southland | 16. Tasman | 17. Nelson | 18. Marlborough | ELECTION STUDY NOTES - NORWAY (2017): E2020 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Oslofjord | 02. Inner East of Norway | 03. Southern Norway | 04. Western Norway | 05. Trondelag | 06. Northern Norway | ELECTION STUDY NOTES - PERU (2021): E2020 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Lima | 02. Amazonas | 03. Ancash | 04. Apurimac | 05. Arequipa | 06. Ayacucho | 07. Cajamarca | 08. Cusco | 09. Huanuco | 10. Ica | 11. Junin | 12. La Libertad | 13. Lambayeque | 14. Loreto | 15. Moquegua | 16. Pasco | 17. Piura | 18. Puno | 19. San Martin | 20. Tacna | 21. Tumbes | 22. Ucayali | 23. Madre de Dios | 24. Huancavelica | 25. Lima Provincias | ELECTION STUDY NOTES - POLAND (2019): E2020 | | CSES-Code Election study code/category |---------------------------------------------------------------- | 01. Dolnoslaskie | 02. Kujawsko-Pomorskie | 03. Lubelskie | 04. Lubuskie | 05. Lodzkie | 06. Malopolskie | 07. Mazowieckie | 08. Opolskie | 09. Podkarpackie | 10. Podlaskie | 11. Pomorskie | 12. Slaskie | 13. Swietokrzyskie | 14. Warminsko-Mazurskie | 15. Wielkopolskie | 16. Zachodniopomorskie | ELECTION STUDY NOTES - PORTUGAL (2019): E2020 | | The regions of residence listed below correspond to EU NUTS II | regions, used as primary sampling units for the 2019 Portuguese | election study. For further information, see Codebook Part 6, | and the Design Report for Portugal 2019. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Norte | 02. Centro | 03. Grande Lisboa | 04. Alentejo | 05. Algarve | ELECTION STUDY NOTES - ROMANIA (2016): E2020 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. North-East | 02. South-East | 03. South-Muntenia | 04. South-West Oltenia | 05. West | 06. North-West | 07. Centre | 08. Bucharest-Ilfov | ELECTION STUDY NOTES - SLOVAKIA (2020): E2020 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Bratislavsky | 02. Trnavsky | 03. Treneiansky | 04. Nitriansky | 05. Zilinsky | 06. Banskobystricky | 07. Presovsky | 08. Kosicky | ELECTION STUDY NOTES - SOUTH KOREA (2016): E2020 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Seoul | 02. Busan | 03. Daegu | 04. Incheon | 05. Gwangju | 06. Daejeon | 07. Ulsan | 08. Sejong | 09. Gyeonggi | 10. Gangwon | 11. Chungbuk | 12. Chungnam | 13. Jeonbuk | 14. Jeonnam | 15. Gyeongbuk | 16. Gyeongnam | ELECTION STUDY NOTES - SWEDEN (2018): E2020 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Stockholm county | 03. Uppsala county | 04. Sodermanland county | 05. Ostergotland county | 06. Jonkoping county | 07. Kronoberg county | 08. Kalmar county | 09. Gotland county | 10. Blekinge county | 12. Skane county | 13. Halland county | 14. Vastra Gotaland county | 17. Varmland county | 18. Orebro county | 19. Vastmanland county | 20. Dalarna county | 21. Gavleborg county | 22. Vasternorrland county | 23. Jamtland county | 24. Vasterbotten county | 25. Norrbotten county | ELECTION STUDY NOTES - SWITZERLAND (2019): E2020 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Zurich | 02. Bern | 03. Lucerne | 04. Uri | 05. Schwyz | 06. Obwalden | 07. Nidwalden | 08. Glarus | 09. Zug | 10. Fribourg | 11. Solothurn | 12. Basel-Stadt | 13. Basel-Landschaft | 14. Schaffhausen | 15. Appenzell Ausserrhoden | 16. Appenzell Innerrhoden | 17. St. Gallen | 18. Graubuenden | 19. Aargau | 20. Thurgau | 21. Ticino | 22. Vaud | 23. Valais | 24. Neuchatel | 25. Geneva | 26. Jura | ELECTION STUDY NOTES - TAIWAN (2016 & 2020): E2020 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Taipei, New Taipei, Keelung and Ilan | 02. Taoyuan, Hsinchu and Miaoly | 03. Taichung, Changhua and Nantou | 04. Yunlin, Chiayi and Tainan | 05. Kaoshiung, Pingtung and Penghu | 06. Hualien, Taitung and Offshore Islands | ELECTION STUDY NOTES - THAILAND (2019): E2020 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. North | 02. Northeast | 03. Central | 04. South | 05. Bangkok | ELECTION STUDY NOTES - TUNISIA (2019): E2020 | | For the Tunisian 2019 election study, the regions of residence | are almost identical to the primary electoral districts (E2021). | The only difference is that the governorates Tunis, Nabeul and | Sfax are subdivided into Tunis 1 and Tunis 2, Nabeul 1 and | Nabeul 2, and Sfax 1 and Sfax 2 in the primary electoral | districts (E2021). | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Beja | 02. Ben Arous | 03. Bizerte | 04. Gabes | 05. Gafsa | 06. Jendouba | 07. Kairouan | 08. Kasserine | 09. Kebili | 10. Ariana | 11. Mahdia | 12. Manouba | 13. Medenine | 14. Monastir | 15. Nabeul | 16. Sfax | 17. Sidi Bouzid | 18. Siliana | 19. Sousse | 20. Tataouine | 21. Tozeur | 22. Tunis | 23. Zaghouan | 24. Kef | ELECTION STUDY NOTES - TURKEY (2018): E2020 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Istanbul | 02. Western Marmara | 03. Aegean | 04. Eastern Marmara | 05. Western Anatolia | 06. Mediterranean | 07. Central Anatolia | 08. Western Black Sea | 09. Eastern Black Sea | 10. North-Eastern Anatolia | 11. Central Eastern Anatolia | 12. South-Eastern Anatolia | ELECTION STUDY NOTES - UNITED STATES (2016 & 2020): E2020 | | E2020 reports the federal state a respondent is living in, | according to US-FIPS codes. | District data for CSES MODULE 5 were collected for the U.S. | Presidential Elections, i.e., the main elections. The United | States use an electoral college system for Presidential | elections operating on the state level. Hence, users are advised | to use E2020 for linking district data provided in variables | E4001 - E4007 to individual respondents, as E2020 corresponds | to the U.S. states. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Alabama | 02. Alaska | 04. Arizona | 05. Arkansas | 06. California | 08. Colorado | 09. Connecticut | 10. Delaware | 11. Washington, D.C. | 12. Florida | 13. Georgia | 15. Hawaii | 16. Idaho | 17. Illinois | 18. Indiana | 19. Iowa | 20. Kansas | 21. Kentucky | 22. Louisiana | 23. Maine | 24. Maryland | 25. Massachusetts | 26. Michigan | 27. Minnesota | 28. Mississippi | 29. Missouri | 30. Montana | 31. Nebraska | 32. Nevada | 33. New Hampshire | 34. New Jersey | 35. New Mexico | 36. New York | 37. North Carolina | 38. North Dakota | 39. Ohio | 40. Oklahoma | 41. Oregon | 42. Pennsylvania | 44. Rhode Island | 45. South Carolina | 46. South Dakota | 47. Tennessee | 48. Texas | 49. Utah | 50. Vermont | 51. Virginia | 53. Washington | 54. West Virginia | 55. Wisconsin | 56. Wyoming | ELECTION STUDY NOTES - URUGUAY (2019): E2020 | | For the Uruguayan 2019 election study, the region of residence | categories are the same as the primary electoral district | categories (E2021). However, as people can register in | departments other than their place of residence, E2020 and E2021 | can show slight deviations in their distributions. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Artigas | 02. Canelones | 03. Cerro Largo | 04. Colonia | 05. Durazno | 06. Flores | 07. Florida | 08. Lavalleja | 09. Maldonado | 10. Montevideo | 11. Paysandu | 12. Rio Negro | 13. Rivera | 14. Rocha | 15. Salto | 16. San Jose | 17. Soriano | 18. Tacuarembo | 19. Treinta y Tres --------------------------------------------------------------------------- E2021 >>> PRIMARY ELECTORAL DISTRICT --------------------------------------------------------------------------- D18. Primary electoral district of respondent. .................................................................. 00001.-90000. [SEE CODEBOOK PART 4 FOR CODE VALUE LABELS] 99996. NATIONWIDE DISTRICT 99999. MISSING | VARIABLE NOTES: E2021 | | E2021 details respondents' primary electoral districts, using | official district identification numbers wherever possible. | Deviances from this CSES convention are detailed when applicable | in the ELECTION STUDY NOTES. | | In some cases, not all districts in a polity are sampled by | the election study. More specific information regarding this | is detailed in the tables in the District Data section of the | Codebook. | | In some cases, respondents' electoral districts were identified | "indirectly," through postal codes, etc., by the CSES Secretariat | (always with the help of the appropriate Collaborator(s)). Where | postal codes, etc., were ambiguous, cases are coded missing. | Refusals and "don't know" are coded missing. | | Data are unavailable for HUNGARY (2018). | ELECTION STUDY NOTES - AUSTRIA (2017): E2021 | | The data represents the first electoral tier (Regionalwahlkreis). | Seats in Austria are distributed across three tiers | (Regionalwahlkreis-tier 1; Landwahlkreis-tier 2; and the | federal level-tier 3). | ELECTION STUDY NOTES - BELGIUM-FLANDERS (2019): E2021 | | Respondents were not asked to provide their electoral district | in the survey. Instead, E2021 was coded based on the National | Register used for sampling. However, due to privacy regulations, | Collaborators were neither granted access to respondents' | addresses, nor allowed to ask respondents for full (four-digit) | postal codes. Therefore, the National Register was provided with | envelopes including the survey, mailing them on Collaborators' | behalf. | By design, the National Register was instructed to mail only | Dutch-language questionnaires out to respondents with addresses | in Flanders. Although some interviewees reported two-digit postal | codes belonging to Brussels (not sampled) or Wallonia, | Collaborators relied on the language of the questionnaire to | divide respondents into regions, as that information was regarded | as more reliable than self-reports from survey answers. However, | the number of cases that do not adhere to this strict logic is | minimal. | ELECTION STUDY NOTES - BELGIUM-WALLONIA (2019): E2021 | | Respondents were not asked to provide their electoral district | in the survey. Instead, E2021 was coded based on the National | Register used for sampling. However, due to privacy regulations, | Collaborators were neither granted access to respondents' | addresses, nor allowed to ask respondents for full (four-digit) | postal codes. Therefore, the National Register was provided with | envelopes including the survey, mailing them on collaborators' | behalf. | By design, the National Register was instructed to mail only | French-language questionnaires out to respondents with addresses | in Wallonia. Although some interviewees reported two-digit postal | codes belonging to Brussels (not sampled) or Flanders, | Collaborators relied on the language of the questionnaire to | divide respondents into regions, as that information was regarded | as more reliable than self-reports from survey answers. However, | the number of cases that do not adhere to this strict logic is | minimal. | ELECTION STUDY NOTES - FINLAND (2019): E2021 | | The primary electoral district identifier was not asked in the | survey. The data for E2021 were derived from municipality codes. | The original municipality variable was removed from the data | because of confidentiality issues. | ELECTION STUDY NOTES - HONG KONG (2016): E2021 | | As interviews were conducted via telephone, respondents were | asked to name their electoral district in a survey question. | However, only respondents who said to have voted in the 2016 | geographical constituency elections for the Legislative Council | were requested to name their district (E3012_LH). Therefore, | those respondents who either claimed not to have voted or who | refused to answer to E3012_LH were coded missing in E2021 | (N = 132). | ELECTION STUDY NOTES - NEW ZEALAND (2020): E2021 | | The size of New Zealand's electorates is determined such that | all electorates have approximately the same population. The | number of electorates increases at regular intervals in line | with national population growth. Beginning with the 2020 general | election, the number of electorates increased from 71 to 72. | Thus, the number of primary electoral districts varies between | 2017 and 2020. Apart from the additional electoral district, | some electorates have been renamed by the Representation | Commission, which determines the names of each electorate | following the most recent census. | ELECTION STUDY NOTES - SWEDEN (2018): E2021 | | Sweden has two electoral segments: The lower tier returns 310 | seats from 29 multi-member districts, the upper tier consists of | 39 adjustment seats. District data on the number of seats | per district (E4001) and the number of seats won by PARTY A-I | in each district (E4005_A-I) refer to the lower tier. | ELECTION STUDY NOTES - TUNISIA (2019): E2021 | | The Tunisian parliament consists of 217 seats. 27 constituencies | are based on the governorates of Tunisia. However, there are six | additional overseas constituencies representing Tunisians abroad | and electing 18 of those 217 seats. These overseas constituencies | are located in Europe, America and Arabia. The Tunisian election | study solely consists of the constituencies located in Tunisia. | ELECTION STUDY NOTES - UNITED STATES (2016 & 2020): E2021 | | This variable reports the electoral districts for the U.S. Lower | House elections, the House of Representatives. The first two | digits of the district codes indicate the federal state (U.S.- | FIPS-codes as used in E2020). | However, the district data for CSES MODULE 5 were collected for | the U.S. Presidential Elections, i.e., the main elections. | Considering that the United States uses an electoral college | system for Presidential elections that operates on the U.S. | state level, the data was collected accordingly. Hence, to link | district data to respondents in the CSES dataset, users are | advised to make use of the variable E2020 (Region of Residence) | which corresponds to the U.S. states. | ELECTION STUDY NOTES - URUGUAY (2019): E2021 | | The Lower Chamber (Camara de Representantes; House of | Representatives) of the Uruguayan General Assembly consists | of 99 members. Seats are assigned between parties in a single | nationwide district, based on a proportional (d'Hondt) system. | The system uses closed lists and Double Simultaneous Vote (DSV) | in regional districts. | The 19 districts classified in variable E2021 matter for the | distribution of seats within each party, as parties may compete | with different lists within regions. --------------------------------------------------------------------------- E2022 >>> RURAL OR URBAN RESIDENCE --------------------------------------------------------------------------- D19. Rural/Urban Residence. .................................................................. 1. RURAL AREA OR VILLAGE 2. SMALL OR MIDDLE-SIZED TOWN 3. SUBURBS OF LARGE TOWN OR CITY 4. LARGE TOWN OR CITY 7. VOLUNTEERED: REFUSED 8. VOLUNTEERED: DON'T KNOW 9. MISSING | VARIABLE NOTES: E2022 | | Instead of using the CSES-schema, some countries employ the | amount of inhabitants for the size of respondent's place of | residence. These measurements do not fit the categories | generally used for E2022. Consequently, we advise users to | carefully read the ELECTION STUDY NOTES of the current variable. | | Data are unavailable for AUSTRALIA (2019), GREAT BRITAIN (2017 & | 2019), HONG KONG (2016), ITALY (2018), LATVIA (2018) and TAIWAN | (2016 & 2020). | ELECTION STUDY NOTES - BELGIUM-FLANDERS (2019): E2022 | | CSES Code Election Study Code/Category |------------------------------------------------------------------ | 01. Rural area or village | 02. A small or mid-sized town | 03. A city with less than 100.000 inhabitants | 04. A large city with more than 100.000 inhabitants | ELECTION STUDY NOTES - BELGIUM-WALLONIA (2019): E2022 | | CSES Code Election Study Code/Category |------------------------------------------------------------------ | 01. Rural area or village | 02. A small or mid-sized town | 03. A city with less than 100.000 inhabitants | 04. A large city with more than 100.000 inhabitants | ELECTION STUDY NOTES - BRAZIL (2018): E2022 | | The answer categories offered to respondents deviated from CSES | MODULE 5 standards, including only two response options for | E2022. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Rural | 04. Urban | ELECTION STUDY NOTES - DENMARK (2019): E2022 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 1. A small village with less than 200 inhabitants | or farm / house in the countryside | A town with 200 - 999 inhabitants | A town with 1,000 - 2,999 inhabitants | 2. A town with 3,000 - 9,999 inhabitants | A town with 10,000 - 19,999 inhabitants | A town with 20,000 - 39,999 inhabitants | A town with over 40,000 inhabitants | 3. In a suburb of Aarhus / Aalborg / Odense | In a suburb of Copenhagen / Greater Copenhagen | 4. Aarhus / Aalborg / Odense | Copenhagen / Greater Copenhagen | ELECTION STUDY NOTES - EL SALVADOR (2019): E2022 | | The answer categories offered to respondents deviated from CSES | MODULE 5 standards, including only two response options for | E2022. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Rural | 04. Urban | ELECTION STUDY NOTES - FINLAND (2019): E2022 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. In a sparsely populated rural area | In a municipal center or other population centers | in a rural area | 02. In the center of a smaller town | 03. In a city/town suburb | 04. In the center of a large town | ELECTION STUDY NOTES - GERMANY (2017): E2022 | | This question was part of the interviewer protocol and therefore | answered by the interviewer and not the respondent. | ELECTION STUDY NOTES - HUNGARY (2018): E2022 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Village | 02. Other city | 04. Budapest | ELECTION STUDY NOTES - INDIA (2019): E2022 | | CSES Code Election Study Code/Category |----------------------------------------------------------------- | 01. Village | 02. Town | 03. City | 04. Metro city | ELECTION STUDY NOTES - JAPAN (2017): E2022 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Towns and Villages | 02. Cities with a population of less than 100,000 | Cities with a population 100,000-200,000 | 03. Cities with a population of more than 200,000 | 04. 21 big cities | ELECTION STUDY NOTES - LITHUANIA (2020): E2022 | | CSES Code Election Study Code/Category |----------------------------------------------------------------- | 01. Up to 2,000 residents | 02. 2,001 - 10,000 residents | 10,001 - 50,000 residents | Marijampole; Alytus | 04. Panevezys; Siauliai; Klaipeda; Kaunas; Vilnius | ELECTION STUDY NOTES - MEXICO (2018): E2022 | | In the 2018 Mexican study, data on respondents' rural or urban | residence has not been collected in the survey but was obtained | from the Instituto Nacional Electoral (INE), Mexico's federal | electoral commission. INE classifies precincts into three | categories: Rural, urban, or mixed precincts. | E2022 was hence coded on the precinct level as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Rural | 02. Mixed | 04. Urban | ELECTION STUDY NOTES - NETHERLANDS (2017 & 2021): E2022 | | For the Dutch 2017 and 2021 studies, data on E2022 has not been | collected in the survey, but was obtained from population | registers. Respondents provided consent before data collection. | Generally, register data are based on the most recent available | data, usually the year preceding data collection. | | Further, E2022 measures the degree of urbanization in terms of | the number of addresses per square kilometer rather than rural | or urban residence. For E2022, data were recoded as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Very low - fewer than 500 addresses per square | kilometer | Low - 500 to 1,000 addresses per square kilometer | 02. Medium - 1,000 to 1,500 addresses per square | kilometer | High - 1500 to 2,000 addresses per square | kilometer | 04. Very high - 2,500 addresses or more per square | kilometer | ELECTION STUDY NOTES - NEW ZEALAND (2017): E2022 | | The answer categories for E2022 offered to respondent deviated | from CSES MODULE 5 standards. | In the original survey question, respondents were offered | five response categories: rural area or settlement, country | town, larger country town, large town, and major city. As the | CSES coding only includes four categories, large town and | major city were collapsed into the fourth category (large town | or city). | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Rural area or settlement | 02. Country town (under 10,000) | 03. Larger country town (10,000-25,000) | 04. Large town (25,000-99,999), | Major city (over 100,000) | ELECTION STUDY NOTES - SOUTH KOREA (2016): E2022 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Rural area or village | 03. Small or middle-sized city | 04. Seoul, metropolitan city | ELECTION STUDY NOTES - SWEDEN (2018): E2022 | | For E2022, Swedish respondents were asked in which type of area | they lived. The answer categories offered to respondents deviated | from CSES MODULE 5 standards and were recoded as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Rural area | Village | 02. Town | City: outer area | City: central area | 03. Large city: outer area/suburb | 04. Large city: central area | ELECTION STUDY NOTES - SWITZERLAND (2019): E2022 | | Respondents in the Swiss study were not asked this question | directly. Instead, the variable was calculated based on | respondents' residence using classification schemes of the | Federal Statistical Office (FSO). | ELECTION STUDY NOTES - UNITED STATES (2016): E2022 | | Rural or urban residence of respondents was assessed by | interviewers and is therefore available only for respondents who | were interviewed face-to-face. Respondents interviewed on the | web were coded missing. | Furthermore, answer options for E2022 differ from the CSES | standard, as listed below: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Rural farm or undeveloped land | 02. Rural town | 03. Suburban | 04. Urban =========================================================================== ))) CSES MODULE 5 VARIABLES: MICRO-LEVEL (SURVEY) DATA THE CSES MODULE 5 QUESTIONNAIRE =========================================================================== --------------------------------------------------------------------------- E3001 >>> Q01. POLITICAL INTEREST --------------------------------------------------------------------------- Q01. How interested would you say you are in politics? Are you very interested, somewhat interested, not very interested, or not at all interested? .................................................................. 1. VERY INTERESTED 2. SOMEWHAT INTERESTED 3. NOT VERY INTERESTED 4. NOT AT ALL INTERESTED 7. VOLUNTEERED: REFUSED 8. VOLUNTEERED: DON'T KNOW 9. MISSING | CSES QUESTION CLASSIFICATION: CORE | ELECTION STUDY NOTES - CANADA (2019): E3001 | | The 2019 Canadian election study asked respondents to rate | their political interest on an 11-point scale. Hence, the answer | categories offered to respondents deviated from CSES MODULE 5 | standards with response options ranging from 1 to 4. The 11-point | scale runs from "0. No interest at all" to "10. A great deal of | interest". The categories were assigned as listed below. Please | note that the middle category 5 was assigned to "3. NOT VERY | INTERESTED". The decision is based on the comparison of | distributions between the Canadian political interest variable | and the political interest variable of other MODULE 5 election | studies. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Codes 8 to 10 | 02. Codes 6 to 7 | 03. Codes 3 to 5 | 04. Codes 0 to 2 | ELECTION STUDY NOTES - GERMANY (2017 & 2021): E3001 | | The answer categories for E3001 offered to respondent deviated | from CSES MODULE 5 standards. The German election studies asked | respondents to rate their interest in politics on a 5-point | scale, additionally differentiating between a "very strong" and | "strong" interest in politics. To match the CSES 4-point scale, | these two original categories were collapsed into the CSES code 1 | ("VERY INTERESTED"). The remaining categories were assigned as | listed below. According to Collaborators, the resulting | distribution is overall consistent with those seen in other | studies that have used the 4-point scale in Germany (e.g., | European Election Study 2014), assuring the recode does not | adversely impact the data's validity. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Very strongly/ strongly | 02. Moderately | 03. Less strongly | 04. Not at all | ELECTION STUDY NOTES - ICELAND (2016 & 2017): E3001 | | The question wording for E3001 deviates slightly from the CSES | MODULE 5 standards. The question reads: "Do you consider your | interest in politics very great, great, some, little, or are you | not interested in politics at all?" The five answer categories | were recoded as below to match CSES conventions. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Very great | Great | 02. Some | 03. Little | 04. None | ELECTION STUDY NOTES - LATVIA (2018): E3001 | | The question wording for E3001 deviates slightly from the CSES | MODULE 5 standards: "How would you characterize your interest in | politics?" Data were recoded as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Very high | 02. Rather high | 03. Rather low | 04. Not interested in politics | ELECTION STUDY NOTES - SOUTH KOREA (2016): E3001 | | The question wording for E3001 deviates from the CSES MODULE 5 | standards. Instead of stating their interest in politics, | respondents were asked about their interest in the upcoming | election. --------------------------------------------------------------------------- E3002 >>> Q02. FOLLOWS POLITICS IN THE MEDIA --------------------------------------------------------------------------- Q02. And how closely do you follow politics on TV, radio, newspapers, or the Internet? Very closely, fairly closely, not very closely, or not at all? .................................................................. 1. VERY CLOSELY 2. FAIRLY CLOSELY 3. NOT VERY CLOSELY 4. NOT AT ALL 7. VOLUNTEERED: REFUSED 8. VOLUNTEERED: DON'T KNOW 9. MISSING | CSES QUESTION CLASSIFICATION: MODULE THEME | ELECTION STUDY NOTES - HUNGARY (2018): E3002 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Regularly | 02. Often | 03. Occasionally | 04. Never | ELECTION STUDY NOTES - INDIA (2019): E3002 | | Respondents in the Indian study were not asked one single | question about attention to politics across different media | sources. Instead, four questions were used, covering the | following media separately: | - TV | - Radio | - Newspapers | - Internet | The answer scales for the four items correspond to the four-point | scale envisaged by CSES. | The variable E3002 was constructed by calculating the mean | of these four questions. For the E3002 variable, CSES took | all respondents into consideration who answered at least to one | of the four items. Respondents with a mean value of 1.5, | 2.5 or 3.5 were rounded downwards since the lowest value (1) | indicates the most attention to politics in the media and the | highest value (4) indicates the least attention. | Respondents not answering any of the four items were coded | to missing. | ELECTION STUDY NOTES - NETHERLANDS (2021): E3002 | | This variable is from the pre-election survey. | ELECTION STUDY NOTES - SWITZERLAND (2019): E3002 | | Respondents in the Swiss study were not asked one single | question about attention to politics across different media | sources. Instead, six questions were used to cover the following | media separately: | - TV | - Newspapers (print or e-paper) | - Free newspapers (print or e-paper) | - Social media (e.g., Facebook, Twitter) | - Online news sites (e.g., watson.ch, srf.ch, 20min.ch) | - Radio | The answer scales for the six items were 4-point Likert scales | and respondents had to indicate for each item whether they are | "very attentive", "rather attentive", "rather not attentive", or | "not at all attentive" to each media item. | The variable E3002 was thus constructed by calculating the mean | of these six questions. For the E3002 variable, Collaborators | took everyone into consideration who answered at least one of | the six items, i.e., mean values were calculated for all | respondents. Respondents who had a mean value of 1.5, 2.5 or 3.5 | were rounded downwards since the lowest value (1) indicates the | most attention to politics in the media and the highest value (4) | indicates the least attention. --------------------------------------------------------------------------- E3003 >>> Q03. INTERNAL EFFICACY --------------------------------------------------------------------------- Q03. Please tell me whether you strongly agree, somewhat agree, neither agree nor disagree, somewhat disagree, or strongly disagree with each of the following statements: You feel you understand the most important political issues of this country. .................................................................. 1. STRONGLY AGREE 2. SOMEWHAT AGREE 3. NEITHER AGREE NOR DISAGREE 4. SOMEWHAT DISAGREE 5. STRONGLY DISAGREE 7. VOLUNTEERED: REFUSED 8. VOLUNTEERED: DON'T KNOW 9. MISSING | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3003 | | Data for E3003 are unavailable for ROMANIA (2016). | ELECTION STUDY NOTES - FRANCE (2017): E3003 | | The question wording for E3003 deviates from the CSES MODULE 5 | standards. While the CSES item "You feel you understand the most | important political issues of this country" is worded positively, | the item employed by the French study translates to "Politics is | too complicated for people like me", being negatively worded. | Therefore, the scale for E3003 was reversed before integrating | the question into the CSES dataset. | ELECTION STUDY NOTES - GERMANY (2017 & 2021): E3003 | | The question wording for E3003 deviates from the CSES MODULE 5 | standards. While the CSES item "You feel you understand the most | important political issues of this country" is worded positively, | the item employed by the German study translates to "I often have | difficulties in understanding political issues", being negatively | worded. Therefore, the scale for E3003 was reversed before | integrating the question into the CSES dataset. | ELECTION STUDY NOTES - HUNGARY (2018): E3003 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Completely | 02. Rather yes | 03. Neither yes, nor no | 04. Rather no | 05. Not at all --------------------------------------------------------------------------- E3004_1 >>> Q04a. ATTITUDES ABOUT ELITES: COMPROMISE IS SELLING OUT ONE'S PRINCIPLES E3004_1_PT >>> Q04a_PT. ATTITUDES ABOUT ELITES: IMPORTANT TO SEEK COMPROMISE - PRE-TEST E3004_2 >>> Q04b. ATTITUDES ABOUT ELITES: DO NOT CARE ABOUT THE PEOPLE E3004_3 >>> Q04c. ATTITUDES ABOUT ELITES: ARE TRUSTWORTHY E3004_4 >>> Q04d. ATTITUDES ABOUT ELITES: ARE THE MAIN PROBLEM E3004_5 >>> Q04e. ATTITUDES ABOUT ELITES: STRONG LEADER BENDS THE RULES E3004_6 >>> Q04f. ATTITUDES ABOUT ELITES: PEOPLE SHOULD MAKE POLICY DECISIONS E3004_7 >>> Q04g. ATTITUDES ABOUT ELITES: RICH AND POWERFUL E3004_8_PT >>> Q04h_PT. ATTITUDES ABOUT ELITES: POOR PEOPLE SHOULD HAVE GREATER VOICE - PRE-TEST --------------------------------------------------------------------------- (Do you strongly agree, somewhat agree, neither agree nor disagree, somewhat disagree, or strongly disagree with the following statement?) Q04a. What people call compromise in politics is really just selling out on one's principles. HELP: At their discretion, the interviewer may use the optional phrase (the phrase which is in parentheses) if they perceive it would be helpful to the respondent in remembering the possible answer choices. Q04a_PT. In a democracy, it is important to seek compromise among different viewpoints. HELP: At their discretion, the interviewer may use the optional phrase (the phrase which is in parentheses) if they perceive it would be helpful to the respondent in remembering the possible answer choices. Q04b. Most politicians do not care about the people. HELP: At their discretion, the interviewer may use the optional phrase (the phrase which is in parentheses) if they perceive it would be helpful to the respondent in remembering the possible answer choices. Q04c. Most politicians are trustworthy. HELP: At their discretion, the interviewer may use the optional phrase (the phrase which is in parentheses) if they perceive it would be helpful to the respondent in remembering the possible answer choices. Q04d. Politicians are the main problem in [COUNTRY]. HELP: At their discretion, the interviewer may use the optional phrase (the phrase which is in parentheses) if they perceive it would be helpful to the respondent in remembering the possible answer choices. Q04e. Having a strong leader in government is good for [COUNTRY] even if the leader bends the rules to get things done. HELP: At their discretion, the interviewer may use the optional phrase (the phrase which is in parentheses) if they perceive it would be helpful to the respondent in remembering the possible answer choices. Q04f. The people, and not politicians, should make our most important policy decisions. HELP: At their discretion, the interviewer may use the optional phrase (the phrase which is in parentheses) if they perceive it would be helpful to the respondent in remembering the possible answer choices. Q04g. Most politicians care only about the interests of the rich and powerful. HELP: At their discretion, the interviewer may use the optional phrase (the phrase which is in parentheses) if they perceive it would be helpful to the respondent in remembering the possible answer choices. Q04h_PT. Poor people should have a greater voice in politics. HELP: At their discretion, the interviewer may use the optional phrase (the phrase which is in parentheses) if they perceive it would be helpful to the respondent in remembering the possible answer choices. .................................................................. 1. STRONGLY AGREE 2. SOMEWHAT AGREE 3. NEITHER AGREE NOR DISAGREE 4. SOMEWHAT DISAGREE 5. STRONGLY DISAGREE 7. VOLUNTEERED: REFUSED 8. VOLUNTEERED: DON'T KNOW 9. MISSING | CSES QUESTION CLASSIFICATION: MODULE THEME | VARIABLE NOTES: E3004_ | | E3004_1_PT was principally collected in election studies which | fielded the CSES MODULE 5 pilot questionnaire. Its initial | wording was changed to create E3004_1, which was fielded by | studies using the CSES MODULE 5 finalized version of the | questionnaire. | | E3004_8_PT was principally collected in election studies which | fielded the CSES MODULE 5 pilot questionnaire. The item was | dropped for the final version of the CSES MODULE 5 questionnaire. | | Data for E3004_1 are unavailable for SWEDEN (2018) and URUGUAY | (2019). | ELECTION STUDY NOTES - NORWAY (2017): E3004_3 | | The question wording for E3004_3 deviates slightly from the CSES | MODULE 5 standards and reads as: "What proportion of our | politicians do you believe are trustworthy?" | Furthermore, there are three reply categories instead of five | as in the CSES questionnaire. These three categories were coded | as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Most are trustworthy | 02. Generally trustworthy | 05. Few trustworthy politicians | ELECTION STUDY NOTES - THAILAND (2019): E3004_ | | For some variables in the Thai 2019 election study, such as | E3004_, an unusually high share of respondents did not provide | substantive answers (> 20% of data coded refused, don't know, or | missing). Collaborators note two potential reasons for this | peculiarity: | | At the time of the election, Thailand's incumbent Prime | Minister was Prayut Chan-o-cha, leader of the State Power Party | (PPRP, PARTY A). As Commander-in-Chief of the Royal Thai Army, | Prayut headed a coup d'etat in May 2014. The 2019 election was | conducted under the new 2017 constitution designed by the | military junta government. Collaborators note parts of the | population dissatisfied with the current situation might have | been reluctant or cautious to provide information on party | preferences and political attitudes closely before or after the | election day. This situation was amplified by official election | results being published only weeks after the election. | | Further, other parts of the population might have been less | knowledgeable concerning political issues such as parties' | ideological classifications and hence might have had difficulties | answering related questions. --------------------------------------------------------------------------- E3005_1 >>> Q05a. OUT-GROUP ATTITUDES: MINORITIES - CUSTOMS AND TRADITIONS E3005_2 >>> Q05b. OUT-GROUP ATTITUDES: MINORITIES - WILL OF THE MAJORITY E3005_3 >>> Q05c. OUT-GROUP ATTITUDES: IMMIGRANTS GOOD FOR ECONOMY E3005_4 >>> Q05d. OUT-GROUP ATTITUDES: CULTURE HARMED BY IMMIGRANTS E3005_5 >>> Q05e. OUT-GROUP ATTITUDES: IMMIGRANTS INCREASE CRIME --------------------------------------------------------------------------- Q05a. Now thinking about minorities in [COUNTRY]. (Do you strongly agree, somewhat agree, neither agree nor disagree, somewhat disagree, or strongly disagree with the following statement?) Minorities should adapt to the customs and traditions of [COUNTRY]. HELP: At their discretion, the interviewer may use the optional phrase (the phrase which is in parentheses) if they perceive it would be helpful to the respondent in remembering the possible answer choices. Q05b. The will of the majority should always prevail, even over the rights of minorities. HELP: At their discretion, the interviewer may use the optional phrase (the phrase which is in parentheses) if they perceive it would be helpful to the respondent in remembering the possible answer choices. Q05c. And now thinking specifically about immigrants: (Do you strongly agree, somewhat agree, neither agree nor disagree, somewhat disagree, or strongly disagree with the following statement?) Immigrants are generally good for [COUNTRY]'s economy. HELP: At their discretion, the interviewer may use the optional phrase (the phrase which is in parentheses) if they perceive it would be helpful to the respondent in remembering the possible answer choices. Q05d. [COUNTRY]'s culture is generally harmed by immigrants. HELP: At their discretion, the interviewer may use the optional phrase (the phrase which is in parentheses) if they perceive it would be helpful to the respondent in remembering the possible answer choices. Q05e. Immigrants increase crime rates in [COUNTRY]. HELP: At their discretion, the interviewer may use the optional phrase (the phrase which is in parentheses) if they perceive it would be helpful to the respondent in remembering the possible answer choices. .................................................................. 1. STRONGLY AGREE 2. SOMEWHAT AGREE 3. NEITHER AGREE NOR DISAGREE 4. SOMEWHAT DISAGREE 5. STRONGLY DISAGREE 7. VOLUNTEERED: REFUSED 8. VOLUNTEERED: DON'T KNOW 9. MISSING | CSES QUESTION CLASSIFICATION: MODULE THEME | VARIABLE NOTES: E3005_ | | The wording for E3005_1 in the pilot version of the CSES MODULE 5 | questionnaire differed from the final wording above and read as | follows: "Ethnic minorities should adapt to [COUNTRY]'s way of | life." In addition, E3005_2 and E3005_5 were not part of the | CSES MODULE 5 pre-test questionnaire and are missing for all | studies in which the pre-test version of the CSES MODULE 5 | questionnaire was administered (see variable E1037). | | Data for E3005_2 and E3005_5 are unavailable for TAIWAN (2020). | ELECTION STUDY NOTES - ITALY (2018): E3005_1 | | Collaborators note in the Design Report the concept of "ethnic | minority" in Italy commonly refers to people residing near the | borders to Austria, France, and Slovenia (page 6 in the Design | Report). The concept is not used much in other contexts, and it | is more common to use the term "foreigners." To ensure | consistency across CSES studies, however, the Italian Study used | the terms "ethnic minority" ("minoranze etniche"). | ELECTION STUDY NOTES - THAILAND (2019): E3005_ | | For some variables in the Thai 2019 election study, such as | E3005_, an unusually high share of respondents did not provide | substantive answers (> 20% of data coded refused, don't know, or | missing). Collaborators note two potential reasons for this | peculiarity: | | At the time of the election, Thailand's incumbent Prime | Minister was Prayut Chan-o-cha, leader of the State Power Party | (PPRP, PARTY A). As Commander-in-Chief of the Royal Thai Army, | Prayut headed a coup d'etat in May 2014. The 2019 election was | conducted under the new 2017 constitution designed by the | military junta government. Collaborators note parts of the | population dissatisfied with the current situation might have | been reluctant or cautious to provide information on party | preferences and political attitudes closely before or after the | election day. This situation was amplified by official election | results being published only weeks after the election. | | Further, other parts of the population might have been less | knowledgeable concerning political issues such as parties' | ideological classifications and hence might have had difficulties | answering related questions. --------------------------------------------------------------------------- E3006_1 >>> Q06a. NATIONAL IDENTITY: TO HAVE BEEN BORN IN COUNTRY E3006_2 >>> Q06b. NATIONAL IDENTITY: ANCESTRY E3006_3 >>> Q06c. NATIONAL IDENTITY: TO BE ABLE TO SPEAK COUNTRY LANGUAGES E3006_4 >>> Q06d. NATIONAL IDENTITY: TO FOLLOW CUSTOMS AND TRADITIONS COUNTRY E3006_5_PT >>> Q06e_PT NATIONAL IDENTITY: TO HAVE LIVED IN COUNTRY FOR MOST OF LIFE - PRE-TEST E3006_6_PT >>> Q06f_PT NATIONAL IDENTITY: TO BE COUNTRY DOMINANT RELIGION - PRE-TEST E3006_7_PT >>> Q06g_PT NATIONAL IDENTITY: TO RESPECT POLITICAL INSTITUTIONS AND LAWS - PRE-TEST E3006_8_PT >>> Q06h_PT NATIONAL IDENTITY: TO FEEL COUNTRY NATIONALITY - PRE-TEST --------------------------------------------------------------------------- Q06a. Now changing the topic. Some people say that the following things are important for being truly [NATIONALITY]. Others say they are not important. How important do you think the following is for being truly [NATIONALITY]... very important, fairly important, not very important, or not important at all? To have been born in [COUNTRY]. Q06b. (How important do you think the following is for being truly [NATIONALITY]... very important, fairly important, not very important, or not important at all?) To have [NATIONALITY] ancestry. HELP: At their discretion, the interviewer may use the optional phrase (the phrase which is in parentheses) if they perceive it would be helpful to the respondent in remembering the possible answer choices. Q06c. (How important do you think the following is for being truly [NATIONALITY]... very important, fairly important, not very important, or not important at all?) To be able to speak [COUNTRY NATIONAL LANGUAGES]. HELP: At their discretion, the interviewer may use the optional phrase (the phrase which is in parentheses) if they perceive it would be helpful to the respondent in remembering the possible answer choices. Q06d. (How important do you think the following is for being truly [NATIONALITY]... very important, fairly important, not very important, or not important at all?) To follow [COUNTRY]'s customs and traditions. HELP: At their discretion, the interviewer may use the optional phrase (the phrase which is in parentheses) if they perceive it would be helpful to the respondent in remembering the possible answer choices. Q06e_PT. (How important do you think the following is for being truly [NATIONALITY]... very important, fairly important, not very important, or not important at all?) To have lived in [COUNTRY] for most of one's life. HELP: At their discretion, the interviewer may use the optional phrase (the phrase which is in parentheses) if they perceive it would be helpful to the respondent in remembering the possible answer choices. Q06f_PT. (How important do you think the following is for being truly [NATIONALITY]... very important, fairly important, not very important, or not important at all?) To be [COUNTRY DOMINANT RELIGION]. HELP: At their discretion, the interviewer may use the optional phrase (the phrase which is in parentheses) if they perceive it would be helpful to the respondent in remembering the possible answer choices. Q06g_PT. (How important do you think the following is for being truly [NATIONALITY]... very important, fairly important, not very important, or not important at all?) To respect [COUNTRY NATIONALITY] political institutions and laws. HELP: At their discretion, the interviewer may use the optional phrase (the phrase which is in parentheses) if they perceive it would be helpful to the respondent in remembering the possible answer choices. Q06h_PT. (How important do you think the following is for being truly [NATIONALITY]... very important, fairly important, not very important, or not important at all?) To feel [COUNTRY NATIONALITY]. HELP: At their discretion, the interviewer may use the optional phrase (the phrase which is in parentheses) if they perceive it would be helpful to the respondent in remembering the possible answer choices. .................................................................. 1. VERY IMPORTANT 2. FAIRLY IMPORTANT 3. NOT VERY IMPORTANT 4. NOT IMPORTANT AT ALL 6. [SEE ELECTION STUDY NOTES] 7. VOLUNTEERED: REFUSED 8. VOLUNTEERED: DON'T KNOW 9. MISSING | CSES QUESTION CLASSIFICATION: MODULE THEME | VARIABLE NOTES: E3006_ | | E3006_5_PT, E3006_6_PT, E3006_7_PT and E3006_8_PT detail national | identity items that were asked in the pilot version of the | CSES MODULE 5 questionnaire. These items were generally not | fielded as part of the final version of the CSES MODULE 5 | questionnaire, although some studies did include selected items | (see table below). | E3006_4 was only part of the finalized questionnaire version and | hence is missing for all studies that fielded the pre-test | version (see variable E1037). | | The table below details the languages (E3006_3) and religions | (E3006_6_PT) respondents were asked about: | | +++ TABLE: LANGUAGES (E3006_3) AND RELIGIONS (E3006_6_PT) ASKED | ABOUT IN THE ELECTION STUDIES | | E3006_3 E3006_6_PT | POLITY (ELEC YEAR) Language Religion | ----------------------------------------------------------- | ALBANIA (2017) Albanian - | AUSTRALIA (2019) English - | AUSTRIA (2017) German - | BELGIUM-FLANDERS (2019) Dutch - | French | German | BELGIUM-WALLONIA (2019) Dutch - | French | German | BRAZIL (2018) Portuguese - | CANADA (2019) French - | English | CHILE (2017) Spanish - | COSTA RICA (2018) Spanish - | CZECHIA (2017) Czech - | CZECHIA (2021) Czech - | DENMARK (2019) Danish - | EL SALVADOR (2019) Spanish - | FINLAND (2019) Finnish - | FRANCE (2017) French - | GERMANY (2017) German - | GERMANY (2021) German - | GREAT BRITAIN (2017) English - | GREAT BRITAIN (2019) English - | GREECE (2015) Greek Christian Orthodox | GREECE (2019) Greek - | HONG KONG (2016) Putonghua - | HUNGARY (2018) Hungarian Christian | ICELAND (2016) Icelandic - | ICELAND (2017) Icelandic - | INDIA (2019) Hindi - | IRELAND (2016) Irish Roman Catholic | ISRAEL (2020) Hebrew - | ITALY (2018) Italian - | JAPAN (2017) Japanese - | LATVIA (2018) Latvian - | LITHUANIA (2016) Lithuanian - | LITHUANIA (2020) Lithuanian - | MEXICO (2018) Spanish - | MONTENEGRO (2016) Montenegrin - | NETHERLANDS (2017) Dutch - | NETHERLANDS (2021) Dutch - | NEW ZEALAND (2017) English - | NEW ZEALAND (2020) English - | NORWAY (2017) Norwegian - | PERU (2021) Spanish - | POLAND (2019) Polish Catholic | PORTUGAL (2019) Portuguese - | ROMANIA (2016) Romanian - | SLOVAKIA (2020) Slovak - | SOUTH KOREA (2016) Korean - | SWEDEN (2018) Swedish Christian | SWITZERLAND (2019) French - | German | Italian | TAIWAN (2016) Chinese, Religion* | Taiwanese, | Hakka, | or aboriginal* | TAIWAN (2020) Chinese, - | Taiwanese, | Hakka, | or aboriginal* | THAILAND (2019) Thai - | TUNISIA (2019) Tunisian - | Arabic (Derja) | TURKEY (2018) Turkish - | UNITED STATES (2016) English - | UNITED STATES (2020) English - | ----------------------------------------------------------- | KEY: - = not available; * = see Election Study Notes. | | Data for E3006_ are unavailable for URUGUAY (2019). Data for | E3006_6_PT are unavailable for HONG KONG (2016) and SOUTH KOREA | (2016). | ELECTION STUDY NOTES - BELGIUM-FLANDERS (2019): E3006_3 | | This item was asked in the Belgium-Flanders questionnaire as: "to | speak Dutch, French, or German" - i.e., referring to the three | official languages in Belgium, and using "or" to indicate any | of the languages. | ELECTION STUDY NOTES - BELGIUM-WALLONIA (2019): E3006_3 | | This item was asked in the Belgium-Wallonia questionnaire as: "to | speak Dutch, French, or German" - i.e., referring to the three | official languages in Belgium, and using "or" to indicate any | of the languages. | ELECTION STUDY NOTES - COSTA RICA (2018): E3006_2 | | The questionnaire contained two items regarding the | importance of ancestry. To be a true Costa Rican, it is | important (1) for one's grandparents to have been born in | Costa Rica, and (2) to have Costa Rican ancestry. The coding of | E3006_2 relies on the ancestry version (2) of the question. | ELECTION STUDY NOTES - HONG KONG (2016): E3006_ | | Before answering to E3006_, respondents were asked whether | they identified as Chinese. Only respondents who affirmed | to regard themselves as Chinese were asked E3006_. | ELECTION STUDY NOTES - MEXICO (2018): E3006_ | | The answer categories for E3006_ offered to respondents deviated | from CSES MODULE 5 standards. Instead of employing the four-point | scale envisaged by CSES, the study includes a five-point scale | for all E3006_ variables. Collaborators note the middle category | "of average importance" ("regular de importante") results from | spontaneous responses, with 20-25% of participants preferring | this option. For CSES, data were recoded as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Very important ("Muy importante") | 02. Somewhat important ("Algo importante") | 03. Not very important ("Poco importante") | 04. Not important at all ("Nada importante") | 06. Of average importance ("Regular de importante") | ELECTION STUDY NOTES - MONTENEGRO (2016): E3006_ | | E3006_ refers to Montenegrin nationality. Collaborators report | translating E3006_ to the Montenegrin context was challenging | because the main political cleavage in Montenegro is "pro- | Montenegrin" vs. "pro-Serbian". Thus, asking respondents what is | important for being truly Montenegrin might have alienated parts | of the population who do not identify as Montenegrin (at least | 30% of the population). | ELECTION STUDY NOTES - NEW ZEALAND (2017): E3006_2 | | The questionnaire contained two items regarding the | importance of ancestry. To be a true New Zealander, it is | important (1) for one's grandparents to have been born in | New Zealand, and (2) to have Maori ancestry. The coding of | E3006_2 relies on the grandparent version (1) of the question. | ELECTION STUDY NOTES - POLAND (2019): E3006_6_PT & E3006_7_PT | | The Polish 2019 election study used the final version of the | CSES MODULE 5 questionnaire. However, the study did also ask two | national identity items (E3006_6_PT & E3006_7_PT) from the pilot | version of the questionnaire. | ELECTION STUDY NOTES - SOUTH KOREA (2016): E3006_6_PT | | E3006_6_PT was not part of the South Korean questionnaire | because according to Collaborators, there is no dominant | religion in South Korea. Instead, several religions are | evenly spread among the population. | ELECTION STUDY NOTES - TAIWAN (2016): E3006_3 & E3006_6_PT | | For E3006_3, respondents were asked about multiple languages | (Chinese, Taiwanese, Hakka, or aboriginal languages). For | E3006_6_PT, respondents were asked about "the country's dominant | religion" without further specification and reference to any | particular religion. | ELECTION STUDY NOTES - TAIWAN (2020): E3006_3 | | For E3006_3, respondents were asked about multiple languages | (Chinese, Taiwanese, Hakka, or aboriginal languages). --------------------------------------------------------------------------- E3007 >>> Q07. HOW WIDESPREAD IS CORRUPTION --------------------------------------------------------------------------- Q07. Now on to another topic. How widespread do you think corruption such as bribe taking is among politicians in [COUNTRY]: very widespread, quite widespread, not very widespread, or it hardly happens at all? .................................................................. 1. VERY WIDESPREAD 2. QUITE WIDESPREAD 3. NOT VERY WIDESPREAD 4. IT HARDLY HAPPENS AT ALL 7. VOLUNTEERED: REFUSED 8. VOLUNTEERED: DON'T KNOW 9. MISSING | CSES QUESTION CLASSIFICATION: MODULE THEME | VARIABLE NOTES: E3007 | | Data are unavailable for INDIA (2019). | ELECTION STUDY NOTES - NEW ZEALAND (2020): E3007 | | The answer categories for E3007 offered to respondents deviated | slightly from CSES MODULE 5 standards. They were the following: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Very widespread | 02. Quite widespread | 03. Quite unusual | 04. Very unusual | ELECTION STUDY NOTES - THAILAND (2019): E3007 | | For some variables in the Thai 2019 election study, such as | E3007, an unusually high share of respondents did not provide | substantive answers (> 20% of data coded refused, don't know, or | missing). Collaborators note two potential reasons for this | peculiarity: | | At the time of the election, Thailand's incumbent Prime | Minister was Prayut Chan-o-cha, leader of the State Power Party | (PPRP, PARTY A). As Commander-in-Chief of the Royal Thai Army, | Prayut headed a coup d'etat in May 2014. The 2019 election was | conducted under the new 2017 constitution designed by the | military junta government. Collaborators note parts of the | population dissatisfied with the current situation might have | been reluctant or cautious to provide information on party | preferences and political attitudes closely before or after the | election day. This situation was amplified by official election | results being published only weeks after the election. | | Further, other parts of the population might have been less | knowledgeable concerning political issues such as parties' | ideological classifications and hence might have had difficulties | answering related questions. --------------------------------------------------------------------------- E3008 >>> Q08. GOVERNMENT ACTION - DIFFERENCES IN INCOME LEVELS --------------------------------------------------------------------------- Q08. Please say to what extent you agree or disagree with the following statement: "The government should take measures to reduce differences in income levels." Do you strongly agree, somewhat agree, neither agree nor disagree, somewhat disagree, or strongly disagree? .................................................................. 1. STRONGLY AGREE 2. SOMEWHAT AGREE 3. NEITHER AGREE NOR DISAGREE 4. SOMEWHAT DISAGREE 5. STRONGLY DISAGREE 7. VOLUNTEERED: REFUSED 8. VOLUNTEERED: DON'T KNOW 9. MISSING | CSES QUESTION CLASSIFICATION: MODULE THEME | VARIABLE NOTES: E3008 | | E3008 was not asked in the pilot version of the CSES MODULE 5 | questionnaire (see variable E1037). | | Data are unavailable for TAIWAN (2020). | ELECTION STUDY NOTES - LATVIA (2018): E3008 | | The question wording for E3008 deviates from the CSES MODULE 5 | standard and reads as follows: "The state has to carry out | measures to reduce income inequality among population." --------------------------------------------------------------------------- E3008_PT >>> Q08_PT. GOVERNMENT ACTION - ATTITUDES TOWARDS REDISTRIBUTION - PRE-TEST --------------------------------------------------------------------------- Q08_PT. Some people think that the government should cut taxes even if it means spending less on social services such as health and education. Other people feel that the government should spend more on social services such as health and education even if it means raising taxes. Where would you place yourself on this scale where 0 is "Governments should decrease taxes and spend less on services" and 10 is "Governments should increase taxes and spend more on services"? .................................................................. 00. GOVERNMENTS SHOULD DECREASE TAXES AND SPEND LESS ON SERVICES 01. 02. 03. 04. 05. 06. 07. 08. 09. 10. GOVERNMENTS SHOULD INCREASE TAXES AND SPEND MORE ON SERVICES 97. VOLUNTEERED: REFUSED 98. VOLUNTEERED: DON'T KNOW 99. MISSING | CSES QUESTION CLASSIFICATION: MODULE THEME | VARIABLE NOTES: E3008_PT | | E3008_PT was only asked in the pilot version of the CSES MODULE 5 | questionnaire. The item was not fielded as part of the final | version of the CSES MODULE 5 questionnaire (see variable E1037). --------------------------------------------------------------------------- E3009 >>> Q09. GOVERNMENT PERFORMANCE: GENERAL --------------------------------------------------------------------------- Q09. Now thinking about the performance of the [government in [CAPITAL]/President] in general, how good or bad a job do you think the [government/President in [CAPITAL]] did over the past [NUMBER OF YEARS SINCE LAST GOVERNMENT TOOK OFFICE, BEFORE THE CURRENT ELECTION] years? Has [it/he/she] done a very good job? A good job? A bad job? A very bad job? .................................................................. 1. VERY GOOD JOB 2. GOOD JOB 3. BAD JOB 4. VERY BAD JOB 6. [SEE ELECTION STUDY NOTES] 7. VOLUNTEERED: REFUSED 8. VOLUNTEERED: DON'T KNOW 9. MISSING | CSES QUESTION CLASSIFICATION: CORE | ELECTION STUDY NOTES - BELGIUM-FLANDERS (2019): E3009 | | In the answers on the paper survey, some respondents wrote a | cross between two numbers instead of indicating a number on the | offered scale. To avoid losing any information, these respondents | were coded as respondents in-between the previous and following | number. These respondents wrote a cross between numbers "2. GOOD | JOB" and "3. BAD JOB" and are recoded to value 6 for E3009. | ELECTION STUDY NOTES - BELGIUM-WALLONIA (2019): E3009 | | In the answers on the paper survey, one respondent wrote a | cross between two numbers instead of indicating a number on the | offered scale. To avoid losing any information, this respondent | was coded as respondent in-between the previous and following | number. This respondent wrote a cross between numbers "2. GOOD | JOB" and "3. BAD JOB" and is recoded to value 6 for E3009. | ELECTION STUDY NOTES - BRAZIL (2018): E3009 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 06. Regular | ELECTION STUDY NOTES - EL SALVADOR (2019): E3009 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 06. Neither good nor bad job | ELECTION STUDY NOTES - FINLAND (2019): E3009 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 06. Neither good nor bad job | ELECTION STUDY NOTES - FRANCE (2017): E3009 | | The question wording for E3009 deviates from the CSES MODULE 5 | standards, asking about satisfaction with the government rather | than government performance: "Overall, are you very satisfied, | quite satisfied, not satisfied or not satisfied at all by | Francois Hollande's actions during his presidency?" | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 1. Very satisfied | 2. Satisfied | 3. Not satisfied | 4. Not satisfied at all | ELECTION STUDY NOTES - ITALY (2018): E3009 | | The question wording for E3009 deviates slightly from the CSES | MODULE 5 standards. Collaborators note in the Design Report that | the reference to "CAPITAL" was not included in the questionnaire | to avoid that respondents would conflate their rating of the | governments' performance with the performance of the city | government of Rome (Design Report, page 6). | ELECTION STUDY NOTES - JAPAN (2017): E3009 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 06. Other | ELECTION STUDY NOTES - NETHERLANDS (2017): E3009 | | The question wording for E3009 deviates from the CSES MODULE 5 | standards, asking about satisfaction with the government rather | than government performance: "How satisfied or dissatisfied are | you with what the last government has done in the past four | years. Are you: very satisfied; satisfied, neither satisfied nor | dissatisfied; dissatisfied or very dissatisfied?" | Hence, the question wording included a middle category, diverging | from the CSES standard. For CSES MODULE 5, data has been recoded | as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 1. Very satisfied | 2. Satisfied | 3. Dissatisfied | 4. Very dissatisfied | 6. Neither satisfied nor dissatisfied | | Furthermore, respondents were asked to indicate government | satisfaction twice: Once in the main questionnaire and once in | the supplementary questionnaire. E3009 is based on answers from | the supplementary questionnaire, as it contains most of the CSES | questions. | ELECTION STUDY NOTES - NETHERLANDS (2021): E3009 | | The question wording for E3009 deviates from the CSES MODULE 5 | standards, asking about satisfaction with the government rather | than government performance: "In general, how satisfied or | dissatisfied are you with what the government has done in the | past four years?" | For CSES MODULE 5, data has been coded as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 1. Very satisfied | 2. Satisfied | 3. Dissatisfied | 4. Very dissatisfied | ELECTION STUDY NOTES - NEW ZEALAND (2020): E3009 | | The answer categories for E3009 offered to respondents deviated | slightly from CSES MODULE 5 standards. They were the following: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Very good job | 02. Fairly good job | 03. Fairly bad job | 04. Very bad job | ELECTION STUDY NOTES - NORWAY (2017): E3009 | | The question wording for E3009 deviates from the CSES MODULE 5 | standards and reads as follows: "We have for the last four years | had a government consisting of The Conservative Party and The | Progress Party. How good a job do you think this government in | general has done?" | Furthermore, there are five reply categories instead of four | as in the CSES questionnaire, and the wording is the following: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Very good job | 02. Good job | 03. Bad job | 04. Very bad job | 06. Neither good nor bad | ELECTION STUDY NOTES - SWEDEN (2018): E3009 | | The question wording for E3009 deviates slightly from the CSES | MODULE 5 standards and reads as: "How do you think that the | Social Democrats and the Green Party have performed as governing | parties during the 2014-2018 election period?" | Answer categories are similar to those envisaged by CSES, as | listed below: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Very good | 02. Good | 03. Bad | 04. Very bad | ELECTION STUDY NOTES - TAIWAN (2016 & 2020 ): E3009 | | The questions refer to the performance of President Ma (2016) | and President Tsai (2020), respectively. --------------------------------------------------------------------------- E3010_1 >>> Q10a. IS THERE A PARTY THAT REPRESENTS RESPONDENT'S VIEWS --------------------------------------------------------------------------- Q10a. Would you say that any of the parties in [COUNTRY] represent your views reasonably well? .................................................................. 0. NO -> GO TO Q11 1. YES 7. VOLUNTEERED: REFUSED 8. VOLUNTEERED: DON'T KNOW 9. MISSING | CSES QUESTION CLASSIFICATION: MODULE THEME | VARIABLE NOTES: E3010_1 | | Data are unavailable for HUNGARY (2018) and SWITZERLAND (2019). | | +++ TABLE: FREQUENCIES ON E3010_2 FOR RESPONDENTS REPORTING NOT | TO HAVE A PARTY REPRESENTING THEIR VIEWS BEST | | POLITY (ELEC YEAR) NUMBER | ------------------------------------------------------------- | BELGIUM-FLANDERS (2019) 18 | BELGIUM-WALLONIA (2019) 5 | COSTA RICA (2018) 16 | GREAT BRITAIN (2017) 285 | MONTENEGRO (2016) 3 | NETHERLANDS (2017) 17 | ------------------------------------------------------------- | ELECTION STUDY NOTES - NEW ZEALAND (2020): E3010_1 | | The question wording for E3010_ deviates from the CSES MODULE 5 | standards, combining E3010_1 and E3010_2 into one single survey | question. The question reads: "Would you say that any of the | parties in New Zealand represent your views reasonably well? | If so, which one represents your views best?" | In the answer options, respondents were offered a list of | parties to choose from, or state "Don't know". | Code "0. No" was not a valid answer option and hence has not | been awarded to respondents from the New Zealand 2020 study. --------------------------------------------------------------------------- E3010_2 >>> Q10b. PARTY THAT REPRESENTS RESPONDENT'S VIEWS BEST --------------------------------------------------------------------------- Q10b. Which party represents your views best? .................................................................. 000001-999987. [SEE CODEBOOK PART 3 FOR PARTY AND LEADER CODES] 999988. NONE OF THE PARTIES 999989. INDEPENDENT CANDIDATE 999990. OTHER LEFT WING CANDIDATE/PARTY 999991. OTHER RIGHT WING CANDIDATE/PARTY 999992. OTHER CANDIDATE/PARTY (NOT FURTHER SPECIFIED) 999997. VOLUNTEERED: REFUSED 999998. VOLUNTEERED: DON'T KNOW 999999. MISSING | CSES QUESTION CLASSIFICATION: MODULE THEME | VARIABLE NOTES: E3010_2 | | Parties/coalitions and their numerical & alphabetical | classifications for each election study are detailed in Part 3 | of the CSES Codebook. | | Data are unavailable for HUNGARY (2018) and SWITZERLAND (2019). | ELECTION STUDY NOTES - CZECHIA (2021): E3010_2 | | NUMERICAL CODE 203101 refers to Civic Democratic Party (ODS) | as the largest member of the SPOLU alliance, as well as to the | SPOLU alliance directly for E3010_2 as respondents could choose | ODS as well as the electoral alliance SPOLU. | NUMERICAL CODE 203103 refers to the Czech Pirate Party (Pi) as | the largest member of the PirStan alliance, as well as to the | PirStan alliance directly for E3010_2 as respondents could | choose Pi as well as the electoral alliance PirStan. | NUMERICAL CODE 203108 refers to the Tricolour Citizen's Movement | (Trikolora) for E3010_2. The Trikolora is the largest member of | the Trikolora-Svobodni-Soukromnici alliance. | ELECTION STUDY NOTES - EL SALVADOR (2019): E3010_2 | | NUMERICAL CODE 222002 refers to the Nationalist Republican | Alliance (ARENA) for E3010_2. ARENA is the largest member of the | ARENA-PCN-PDC-DS alliance. | ELECTION STUDY NOTES - FINLAND (2019): E3010_2 | | For all survey variables including numeric party codes, the | Finnish questionnaire included the open-ended option "Other | party or group", allowing respondents to specify a party | otherwise not included in the survey. Collaborators classified | these open-ended answers into the following codes adopted for | CSES: | | NUMERICAL CODE Election Study Code/Category |---------------------------------------------------------------- | 999990. Animal Justice Party of Finland | Feminist Party | Communist Party of Finland | 999991. Liberal Party | Movement Now | Finnish People First | 999992. Seven Star Movement | R did not further specify party in open-ended | "Other party or group" option | ELECTION STUDY NOTES - GERMANY (2017): E3010_2 | | NUMERICAL CODE 276001 refers to the Union, the unofficial | political alliance between the Christian Democratic Union (CDU) | and the Christian Social Union in Bavaria (CSU). | 238 respondents initially named the CDU as the party representing | their views best. These answers are subsumed under NUMERICAL CODE | 276001 together with respondents who stated to feel best | represented by the Union. NUMERICAL CODE 276007 identifies | respondents stating to feel best represented by the CSU. | ELECTION STUDY NOTES - GERMANY (2021): E3010_2 | | NUMERICAL CODE 276102 refers to the Union, the unofficial | political alliance between the Christian Democratic Union (CDU) | and the Christian Social Union in Bavaria (CSU). | 96 respondents initially named the CDU as the party representing | their views best. These answers are subsumed under NUMERICAL CODE | 276102 together with respondents who stated to feel best | represented by the Union. NUMERICAL CODE 276106 identifies | respondents stating to feel best represented by CSU. | ELECTION STUDY NOTES - LITHUANIA (2016): E3010_2 | | NUMERICAL CODE 440005 refers to Lithuanian Center Party for | E3010_2. This is the largest member of the Anti-Corruption | Coalition. | ELECTION STUDY NOTES - POLAND (2019): E3010_2 | | For E3010_2, numerical codes refer to the following | parties/alliances: | - NUMERICAL CODE 616001: Law and Justice Party (PiS), the largest | member of the United Right alliance. | - NUMERICAL CODE 616002: Civic Coalition alliance | - NUMERICAL CODE 616003: Polish People's Party (PSL), the largest | member of the Polish Coalition alliance. | - NUMERICAL CODE 616004: Left alliance | - NUMERICAL CODE 616010: Confederation alliance | Consult Part 3 of the CSES Codebook for more information. | ELECTION STUDY NOTES - TAIWAN (2016): E3010_2 | | NUMERICAL CODE 158004 refers to Green Party for E3010_2. | The Green Party is the largest member of the Green Party - | Social Democratic Party alliance. --------------------------------------------------------------------------- E3011 >>> Q11. STATE OF THE ECONOMY --------------------------------------------------------------------------- Q11. Would you say that over the past twelve months, the state of the economy in [COUNTRY] has gotten much better, gotten somewhat better, stayed about the same, gotten somewhat worse, or gotten much worse? .................................................................. 1. GOTTEN MUCH BETTER 2. GOTTEN SOMEWHAT BETTER 3. STAYED ABOUT THE SAME 4. GOTTEN SOMEWHAT WORSE 5. GOTTEN MUCH WORSE 7. VOLUNTEERED: REFUSED 8. VOLUNTEERED: DON'T KNOW 9. MISSING | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3011 | | E3011 details respondents' assessment of the economy in the | 12 months preceding the interview - the economic valence. | ELECTION STUDY NOTES - GREAT BRITAIN (2019): E3011 | | The number of missing responses is high for E3011, as the study | had to omit some questions from the paper survey, and this was | one of them. | ELECTION STUDY NOTES - MEXICO (2018): E3011 | | The answer categories for E3011 offered to respondents deviated | from CSES MODULE 5 standards. Instead of a 5-point scale, the | state of the economy was measured on a 4-point scale, omitting | the middle category. Data were recoded as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Gotten better | 02. Stayed just as well | 04. Stayed just as bad | 05. Gotten worse | ELECTION STUDY NOTES - NEW ZEALAND (2020): E3011 | | The answer categories for E3011 offered to respondents deviated | slightly from CSES MODULE 5 standards. They were the following: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Got a lot better | 02. Got a little better | 03. Stayed the same | 04. Got a little worse | 05. Got a lot worse | ELECTION STUDY NOTES - NORWAY (2017): E3011 | | The answer categories for E3011 offered to respondents deviated | from CSES MODULE 5 standards. Instead of a 5-point scale, the | state of the economy was measured on a 3-point scale, | distinguishing between gotten better, stayed the same, and gotten | worse. These categories were recoded as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 02. Gotten better | 03. Stayed the same | 04. Gotten worse | ELECTION STUDY NOTES - SOUTH KOREA (2016): E3011 | | The answer categories for E3011 offered to respondents deviated | from CSES MODULE 5 standards. Instead of a 5-point scale, the | state of the economy was measured on a 3-point scale, | distinguishing between "gotten better", "stayed the same", and | "gotten worse". These categories were recoded as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 02. Gotten better | 03. Stayed the same | 04. Gotten worse --------------------------------------------------------------------------- E3012 >>> TURNOUT: MAIN ELECTION --------------------------------------------------------------------------- Whether or not the respondent cast a ballot in the main election. .................................................................. 0. RESPONDENT DID NOT CAST A BALLOT 1. RESPONDENT CAST A BALLOT 93. VOLUNTEERED: RESPONDENT NOT REGISTERED ON ELECTORAL LISTS [IF APPLICABLE] 97. VOLUNTEERED: REFUSED 98. VOLUNTEERED: DON'T KNOW 99. MISSING | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3012 | | E3012 ascertains whether or not the respondent cast a ballot | in the main election, regardless of whether or not it was valid. | The wording of this item, which is to record voting in the | national election, follows national standards. | | In case of a single election taking place, e.g., a lower house | election only, then E3012 reports the turnout decision for that | particular election. In cases where multiple elections took | place, e.g., a Presidential and a lower house election, E3012 | reports the turnout decision in the main election. | | CSES classifies the main election based on the regime | (executive) type and the election in which the CSES survey has | been administered. For polities rated as parliamentary systems, | CSES classifies the main election as elections to the lower house | for most studies. It deviates for a few cases when elections to | the upper house constitutes the main election, usually due to the | respective CSES study focusing on the upper house contest. | For polities rated as Presidential systems, CSES conventionally | classifies the main election as the Presidential election. It | sometimes deviates when data for the Presidential election is | unavailable (e.g., when the CSES survey was administered in a | midterm election). For polities rated as mixed systems, CSES | has tended to classify the main election as elections to the | lower house. However, it sometimes deviates depending on data | availability. Users are advised to consult the table below | specifying the main election for each study in CSES for specific | details. | | +++ TABLE: ELECTION STUDIES BY TYPE OF MAIN ELECTION | | Presidential Lower House Upper House | POLITY (ELEC YEAR) Election Election Election | ------------------------------------------------------------- | ALBANIA (2017) - X - | AUSTRALIA (2019) - X - | AUSTRIA (2017) - X - | BELGIUM-FLANDERS (2019) - X - | BELGIUM-WALLONIA (2019) - X - | BRAZIL (2018) X - - | CANADA (2019) - X - | CHILE (2017) X - - | COSTA RICA (2018) X - - | CZECHIA (2017) - X - | CZECHIA (2021) - X - | DENMARK (2019) - X - | EL SALVADOR (2019) X - - | FINLAND (2019) - X - | FRANCE (2017) X - - | GERMANY (2017) - X - | GERMANY (2021) - X - | GREAT BRITAIN (2017) - X - | GREAT BRITAIN (2019) - X - | GREECE (2015) - X - | GREECE (2019) - X - | HONG KONG (2016) - X - | HUNGARY (2018) - X - | ICELAND (2016) - X - | ICELAND (2017) - X - | INDIA (2019) - X - | IRELAND (2016) - X - | ISRAEL (2020) - X - | ITALY (2018) - X - | JAPAN (2017) - X - | LATVIA (2018) - X - | LITHUANIA (2016) - X - | LITHUANIA (2020) - X - | MEXICO (2018) X - - | MONTENEGRO (2016) - X - | NETHERLANDS (2017) - X - | NETHERLANDS (2021) - X - | NEW ZEALAND (2017) - X - | NEW ZEALAND (2020) - X - | NORWAY (2017) - X - | PERU (2021) X - - | POLAND (2019) - X - | PORTUGAL (2019) - X - | ROMANIA (2016) - X - | SLOVAKIA (2020) - X - | SOUTH KOREA (2016) - X - | SWEDEN (2018) - X - | SWITZERLAND (2019) - X - | TAIWAN (2016) X - - | TAIWAN (2020) X - - | THAILAND (2019) - X - | TUNISIA (2019) - X - | TURKEY (2018) X - - | UNITED STATES (2016) X - - | UNITED STATES (2020) X - - | URUGUAY (2019) X - - | ------------------------------------------------------------- --------------------------------------------------------------------------- E3012_PR_1 >>> Q12P1-a. CURRENT PRESIDENTIAL ELECTION: DID RESPONDENT CAST A BALLOT - 1ST ROUND --------------------------------------------------------------------------- Whether or not the respondent cast a ballot in the first round of the Presidential elections. .................................................................. 0. RESPONDENT DID NOT CAST A BALLOT/WILL NOT CAST A BALLOT 1. RESPONDENT CAST A BALLOT/WILL CAST A BALLOT 93. VOLUNTEERED: RESPONDENT NOT REGISTERED ON ELECTORAL LISTS / NOT ELIGIBLE [IF APPLICABLE] 95. NOT APPLICABLE: NO ROLE OF PRESIDENT 96. NOT APPLICABLE: NO PRESIDENTIAL ELECTIONS 97. VOLUNTEERED: REFUSED 98. VOLUNTEERED: DON'T KNOW 99. MISSING | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3012_PR_1 | | E3012_PR_1 ascertains whether or not the respondent cast a ballot | in the first round of the Presidential elections, regardless of | whether or not it was valid. Hence, E3012_PR_1 details reported | turnout, irrespective of whether respondents voted on election | day or participated in early/advance voting. | | The wording of E3012_PR_1, which is to record voting in the | national election, follows national standards. | ELECTION STUDY NOTES - BRAZIL (2018): E3012_PR_1 | | The question of whether respondents voted in the "first round" | of the current election did not differentiate between the | Presidential, lower house and upper house elections. Since | voting is compulsory, it can be assumed that most persons who | answered "yes" voted in all of the elections, and those who | answered "no" did not vote in any of the elections, which took | place simultaneously. Furthermore, there were different kinds of | "no" answers in the original dataset which showed why | respondents did not vote. These values were recoded as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 0. No, more than 70 years old (voluntary) | No, 16-17 years old (voluntary) | No, showed justification in 1st round | Neither voted nor showed justification at first | round | No, didn't have the necessary documentation | 1. Yes, voted | ELECTION STUDY NOTES - UNITED STATES (2016): E3012_PR_1 | | Only respondents who indicated that they were registered to vote | and who indicated that they voted in the General Elections 2016 | were asked this question. 'Refused' answers to the registration | question were coded as 'refused' in E3012_PR_1. 'Don't know' | answers to the registration question were coded as 'missing' in | E3012_PR_1. 'Refused' answers to the general elections question | were coded as 'refused' in E3012_PR_1. 'Don't know' answers | to the general turnout question were coded as 'don't know'. | | The original data show that 25 respondents reported their | voting behavior inconsistently. When asked before the elections | whether they had already participated in early voting, they | answered yes. However, when asked after the elections, they | reported not to have voted early. For the CSES coding, the | answer given before the elections is assumed to be valid. | ELECTION STUDY NOTES - UNITED STATES (2020): E3012_PR_1 | | Only respondents who indicated that they were registered to vote | and who indicated that they voted in the General Elections 2020 | were asked this question. 'Refused' answers to the registration | question were coded as 'refused' in E3012_PR_1. | 'Refused' answers to the general elections question were coded | as 'refused' in E3012_PR_1. | | The original data show that 20 respondents reported their voting | behavior inconsistently. When asked before the elections whether | they had already participated in early voting, they answered yes. | However, when asked after the elections, they reported having | voted on election day. For the CSES coding, the answer given | before the elections is assumed to be valid. --------------------------------------------------------------------------- E3012_PR_2 >>> Q12P2-a. CURRENT PRESIDENTIAL ELECTION: DID RESPONDENT CAST A BALLOT - 2ND ROUND --------------------------------------------------------------------------- Whether or not the respondent cast a ballot in the second round of the Presidential elections. .................................................................. 0. RESPONDENT DID NOT CAST A BALLOT/WILL NOT CAST A BALLOT 1. RESPONDENT CAST A BALLOT/WILL CAST A BALLOT 93. VOLUNTEERED: RESPONDENT NOT REGISTERED ON ELECTORAL LISTS / NOT ELIGIBLE [IF APPLICABLE] 95. NOT APPLICABLE: NO ROLE OF PRESIDENT 96. NOT APPLICABLE: NO PRESIDENTIAL ELECTIONS / NO SECOND ROUND 97. VOLUNTEERED: REFUSED 98. VOLUNTEERED: DON'T KNOW 99. MISSING | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3012_PR_2 | | E3012_PR_2 ascertains whether or not the respondent cast a ballot | in the second round of the Presidential elections, regardless of | whether or not it was valid. Hence, E3012_PR_2 details reported | turnout, irrespective of whether respondents voted on election | day or participated in early/advance voting. | | The wording of E3012_PR_2, which is to record voting in the | national election, follows national standards. | ELECTION STUDY NOTES - BRAZIL (2018): E3012_PR_2 | | The Brazilian study differentiates between various kinds of "no" | answers in the original dataset, showing why respondents did not | vote. These values were recoded as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 0. No, more than 70 years old (voluntary) | No, 16-17 years old (voluntary) | No, showed justification in 1st round | Neither voted nor showed justification at first | round | No, didn't have the necessary documentation | 1. Yes, voted --------------------------------------------------------------------------- E3012_LH >>> Q12LH-a. CURRENT LOWER HOUSE ELECTION: DID RESPONDENT CAST A BALLOT --------------------------------------------------------------------------- Whether or not the respondent cast a ballot in the lower house election. .................................................................. 0. RESPONDENT DID NOT CAST A BALLOT/WILL NOT CAST A BALLOT 1. RESPONDENT CAST A BALLOT/WILL CAST A BALLOT 93. VOLUNTEERED: RESPONDENT NOT REGISTERED ON ELECTORAL LISTS / NOT ELIGIBLE [IF APPLICABLE] 96. NOT APPLICABLE: NO LOWER HOUSE ELECTION 97. VOLUNTEERED: REFUSED 98. VOLUNTEERED: DON'T KNOW 99. MISSING | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3012_LH | | E3012_LH ascertains whether or not the respondent cast a ballot | in the lower house election, regardless of whether or not it was | valid. Hence, E3012_LH details reported turnout, irrespective of | whether respondents voted on election day or participated in | early/advance voting. | | The wording of E3012_LH, which is to record voting in the | national election, follows national standards. | | Data are unavailable for MEXICO (2018). | ELECTION STUDY NOTES - AUSTRALIA (2019): E3012_LH | | Several respondents reported voting for "No party" in the | Australian study. Following the advice of Collaborators, these | are recoded to non-voters in the turnout variable. | ELECTION STUDY NOTES - BRAZIL (2018): E3012_LH | | The question of whether respondents voted in the "first round" of | the current election did not differentiate between Presidential, | lower house and upper house elections. Since voting is | compulsory, it can be assumed that most persons who answered | "yes" voted in all of the elections, and those who answered "no" | did not vote in any of the elections, which took place | simultaneously. Furthermore, there were different kinds of "no" | answers in the original dataset which showed why respondents did | not vote. These values were recoded as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 0. No, more than 70 years old (voluntary) | No, 16-17 years old (voluntary) | No, showed justification in 1st round | Neither voted nor showed justification at first | round | No, didn't have the necessary documentation | 1. Yes, voted | ELECTION STUDY NOTES - FINLAND (2019): E3012_LH | | The data collection organization programmed the questionnaire | incorrectly and consequently, 288 respondents were not asked | several items in the Finnish study. This affected two CSES | items: turnout and vote choice variables. | The error was detected after the data collection had concluded. | To amend the problem, the data collection organization attempted | to re-contact the affected respondents by phone and ask the | questions that had not been included during the initial | interview. The affected respondents did not retake the entire | interview. | Variable E1007 (Sample component) includes information that | enables users to distinguish these respondents in the Finland | (2019) study. SEE ELECTION STUDY NOTES - FINLAND (2019): E1007 | for further information. | ELECTION STUDY NOTES - GREECE (2019): E3012_LH | | Turnout for the 2019 Greek legislative election is significantly | higher in the sample than expected given the official election | results. Collaborators name several potential explanations for | this discrepancy: | Firstly, Collaborators note the electoral rolls might be outdated | in some instances, hence inflating the number of voters deemed | eligible. For example, electoral registers sometimes still | include Greek citizens who moved abroad or who were deceased | (together amounting to 10% of persons listed in electoral rolls | according to various estimates). | Secondly, non-voters either not interested in politics or of | high age were presumably also less likely to participate in | an electoral survey. | Finally, Collaborators note voting in Greece is compulsory, | suggesting that some actual non-voters might have claimed to | have turned out in the survey (social-desirability bias). | ELECTION STUDY NOTES - HONG KONG (2016): E3012_LH | | E3012_LH reflects turnout for the geographical constituency | election, which returns 35 out of 70 seats for the unicameral | legislature of Hong Kong, the Legislative Council (LegCo). | ELECTION STUDY NOTES - ITALY (2018): E3012_LH | | Turnout for the lower (E3012_LH) and upper (E3012_UH) house | elections was derived from a single question asking respondents | whether they had cast a ballot in the current elections. | ELECTION STUDY NOTES - MEXICO (2018): E3012_LH | | In Mexico, 2018 elections for the Presidency, the lower house | and the upper house were all held on July 1, 2018, and hence on | the same day. Collaborators only asked respondents about their | turnout in the Presidential election, as this contest was deemed | to be most salient. | Respondents' turnout in the 2018 Presidential election is | available in variable E3012_PR_1. | ELECTION STUDY NOTES - PORTUGAL (2019): E3012_LH | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 0. I did not vote because I couldn't find the time to | I thought about voting this time but didn't | Usually I vote, but this time I didn't | 1. I voted in the 2019 elections | | While 48.6 percent of voters turned out in the 2019 Portuguese | lower house 2019 election according to official election | results, 66.6 percent of respondents in the sample claim to | have voted. Apart from social desirability bias, Collaborators | note the observed discrepancy may partly originate from the | sample design and a change in electoral rules preceding the 2019 | election: In 2019, eligible voters living abroad were added | automatically to the electoral registers for the first time, | resulting in an increase of 1.2 million registered voters. | However, these newly registered voters, whose turnout is | traditionally low, were not part of the sampling frame. | Collaborators note turnout within the national territory of | Portugal, the study's universe, was 54.6 percent in 2019 and | thus considerably higher than the overall turnout. | ELECTION STUDY NOTES - UNITED STATES (2016): E3012_LH | | Only respondents who indicated that they were registered to vote | and who indicated that they voted in the General Elections 2016 | were asked this question. 'Refused' answers to the registration | question were coded as 'refused' in E3012_LH. 'Don't know' | answers to the registration question were coded as 'missing' in | E3012_LH. 'Refused' answers to the general elections question | were coded as 'refused' in E3012_LH. 'Don't know' answers | to the general turnout question were coded as 'don't know'. | | The original data show that 25 respondents reported their | voting behavior inconsistently. When asked before the elections | whether they had already participated in early voting they | answered yes. However, when asked after the elections they | reported not to have voted early. For the CSES coding, the | answer given before the elections is assumed to be valid. | ELECTION STUDY NOTES - UNITED STATES (2020): E3012_LH | | Only respondents who indicated that they were registered to vote | and who indicated that they voted in the General Elections 2020 | were asked this question. 'Refused' answers to the registration | question were coded as 'refused' in E3012_LH. | 'Refused' answers to the general elections question were coded | as 'refused' in E3012_LH. | | The original data show that 20 respondents reported their | voting behavior inconsistently. When asked before the elections | whether they had already participated in early voting they | answered yes. However, when asked after the elections they | reported having voted on election day. For the CSES coding, the | answer given before the elections is assumed to be valid. --------------------------------------------------------------------------- E3012_UH >>> Q12LH-a. CURRENT UPPER HOUSE ELECTION: DID RESPONDENT CAST A BALLOT --------------------------------------------------------------------------- Whether or not the respondent cast a ballot in the upper house election. .................................................................. 0. RESPONDENT DID NOT CAST A BALLOT/WILL NOT CAST A BALLOT 1. RESPONDENT CAST A BALLOT/WILL CAST A BALLOT 93. VOLUNTEERED: RESPONDENT NOT REGISTERED ON ELECTORAL LISTS / NOT ELIGIBLE [IF APPLICABLE] 95. NOT APPLICABLE: UNICAMERAL SYSTEM 96. NOT APPLICABLE: NO UPPER HOUSE ELECTION 97. VOLUNTEERED: REFUSED 98. VOLUNTEERED: DON'T KNOW 99. MISSING | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3012_UH | | E3012_UH ascertains whether or not the respondent cast a ballot | in the upper house election, regardless of whether or not it was | valid. Hence, E3012_UH details reported turnout, irrespective of | whether respondents voted on election day or participated in | early/advance voting. | | The wording of E3012_UH, which is to record voting in the | national election, follows national standards. | | Data are unavailable for MEXICO (2018). | ELECTION STUDY NOTES - AUSTRALIA (2019): E3012_UH | | Several respondents reported voting for "No party" in the | Australian study. Following the advice of Collaborators, these | are recoded to non-voters in the turnout variable. | ELECTION STUDY NOTES - BRAZIL (2018): E3012_UH | | The question of whether respondents voted in the "first round" of | the current election did not differentiate between Presidential, | lower house and upper house elections. Since voting is | compulsory, it can be assumed that most persons who answered | "yes" voted in all of the elections, and those who answered "no" | did not vote in any of the elections, which took place | simultaneously. Furthermore, there were different kinds of "no" | answers in the original dataset which showed why respondents did | not vote. These values were recoded as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 0. No, more than 70 years old (voluntary) | No, 16-17 years old (voluntary) | No, showed justification in 1st round | Neither voted nor showed justification at first | round | No, didn't have the necessary documentation | 1. Yes, voted | ELECTION STUDY NOTES - ITALY (2018): E3012_UH | | Turnout for the lower (E3012_LH) and upper (E3012_UH) house | elections was derived from a single question asking respondents | whether they had cast a ballot in the current elections. | Because the voting age for Italian Upper House Elections is | 25, respondents younger than that were coded as "999993. | VOLUNTEERED: RESPONDENT NOT REGISTERED ON ELECTORAL LISTS [IF | APPLICABLE]" (N=114) for E3012_UH. | ELECTION STUDY NOTES - MEXICO (2018): E3012_UH | | In Mexico, 2018 elections for the Presidency, the lower house | and the upper house were all held on July 1, 2018, and hence on | the same day. Collaborators only asked respondents about their | turnout in the Presidential election, as this contest was deemed | to be most salient. | Respondents' turnout in the 2018 Presidential election is | available in variable E3012_PR_1. | ELECTION STUDY NOTES - UNITED STATES (2016): E3012_UH | | Only respondents who indicated that they were registered to vote | and who indicated that they voted in the General Elections 2016 | were asked this question. 'Refused' answers to the registration | question were coded as 'refused' in E3012_UH. 'Don't know' | answers to the registration question were coded as 'missing' in | E3012_UH. 'Refused' answers to the general elections question | were coded as 'refused' in E3012_UH. 'Don't know' answers | to the general turnout question were coded as 'don't know'. | | The original data show that 25 respondents reported their | voting behavior inconsistently. When asked before the elections | whether they had already participated in early voting they | answered yes. However, when asked after the elections they | reported not to have voted early. For the CSES coding, the | answer given before the elections is assumed to be valid. | ELECTION STUDY NOTES - UNITED STATES (2020): E3012_UH | | Only respondents who indicated that they were registered to vote | and who indicated that they voted in the General Elections 2020 | were asked this question. 'Refused' answers to the registration | question were coded as 'refused' in E3012_UH. | 'Refused' answers to the general elections question were coded | as 'refused' in E3012_UH. | | The original data show that 20 respondents reported their | voting behavior inconsistently. When asked before the elections | whether they had already participated in early voting they | answered yes. However, when asked after the elections they | reported having voted on election day. For the CSES coding, the | answer given before the elections is assumed to be valid. --------------------------------------------------------------------------- E3012_TS >>> TURNOUT SWITCHER BETWEEN CURRENT ELECTION AND PREVIOUS ELECTION --------------------------------------------------------------------------- Whether or not the respondent reports voting in the current and previous election. .................................................................. 0. RESPONDENT ABSTAINED IN BOTH ELECTIONS 1. RESPONDENT ABSTAINED IN CURRENT ELECTION BUT VOTED IN PREVIOUS ELECTION 2. RESPONDENT VOTED IN CURRENT ELECTION BUT ABSTAINED IN PREVIOUS ELECTION 3. RESPONDENT VOTED IN BOTH CURRENT AND PREVIOUS ELECTION 5. RESPONDENT ABSTAINED IN CURRENT ELECTION BUT INELIGIBLE TO VOTE IN PREVIOUS ELECTION 6. RESPONDENT VOTED IN CURRENT ELECTION BUT INELIGIBLE TO VOTE IN PREVIOUS ELECTION 9. MISSING | CSES QUESTION CLASSIFICATION: DERIVATIVE VARIABLE (BASED ON CORE) | VARIABLE NOTES: E3012_TS | | E3012_TS is constructed based on the respondent's reported | turnout in the current and previous main election. | In polities where multiple elections took place simultaneously, | E3012_TS reports the turnout decision in the main election. | The classifications of the main election by election study are | listed in the variable notes for variable E3013_OUTGOV. | | CSES classifies the main election based on the regime | (executive) type and the election in which the CSES survey has | been administered. For polities rated as parliamentary systems, | CSES classifies the main election as elections to the lower house | for most studies. It deviates for a few cases when elections to | the upper house constitutes the main election, usually due to the | respective CSES study focusing on the upper house contest. | For polities rated as Presidential systems, CSES conventionally | classifies the main election as the Presidential election. It | sometimes deviates when data for the Presidential election is | unavailable (e.g., when the CSES survey was administered in a | midterm election). For polities rated as mixed systems, CSES | has tended to classify the main election as elections to the | lower house. However, it sometimes deviates depending on data | availability. Users are advised to consult the table listed in | VARIABLE NOTES for E3013_OUTGOV specifying the main election for | each study in CSES for specific details. | | In instances when the previous turnout refers to a different type | of election, e.g., current main elections are Presidential but | previous turnout variable refers to lower house election only, | these studies are set to missing for E3012_TS. | | Data are unavailable for TAIWAN (2016). | ELECTION STUDY NOTES - COSTA RICA (2018): E3012_TS | | This variable is based on the turnout variables of the first | round of the current and previous Presidential election | (E3012_PR_1 and E3014_PR_1). | ELECTION STUDY NOTES - TAIWAN (2020): E3012_TS | | The main election in Taiwan is the Presidential election. Data | on respondents' turnout of the second round of the Presidential | election was, however, not available. Therefore, E3012_TS is | based on turnout variables of the current and previous lower | house election. --------------------------------------------------------------------------- E3012_FTV >>> FIRST TIME VOTER IN CURRENT MAIN ELECTION --------------------------------------------------------------------------- Whether or not the respondent is a first-time voter in the current main election. .................................................................. 0. R IS NOT A FIRST-TIME VOTER IN CURRENT MAIN ELECTION 1. R IS A FIRST-TIME VOTER IN CURRENT MAIN ELECTION 6. NOT ASCERTAINABLE [SEE VARIABLE NOTES] 9. MISSING | CSES QUESTION CLASSIFICATION: DERIVATIVE VARIABLE (BASED ON CORE) | VARIABLE NOTES: E3012_FTV | | E3012_FTV ascertains whether or not the respondent is a | first-time voter in the current main election. | Following the ACE Electoral Knowledge Network, CSES defines | first-time voters as "those young people who are reaching voting | age and therefore are facing their first opportunity to vote" | in the main election. | (see https://aceproject.org/ace-en/topics/ve/vee/vee05/vee05h, | Date accessed: February 05, 2023). | | Consequently, E3012_FTV classifies observations as first time | voters based on respondent age (variable E2001_Y). | | Respondents are classified as "1. R IS A FIRST-TIME VOTER" if | they attained voting age between the dates of the previous and | current main election. | Respondents who were eligible at the preceding main | election are coded "0. R IS NOT A FIRST-TIME VOTER". | | As CSES collects respondents' year and month of birth only (for | further information see VARIABLE NOTES for E2001_Y), there are a | few instances in the dataset that could not be classified based | on the above definition and are hence coded "6. NOT | ASCERTAINABLE". This applies to the following observations: | - Respondents who reached voting age in the month of the | previous main election. | - Respondents who reached voting age in the year of the previous | main election and for whom data on the month of birth is | unavailable. | | Data are coded "9. MISSING" primarily in instances where | respondents' year of birth (E2001_Y) is unavailable. | | In polities where multiple elections took place simultaneously, | this variable classifies first voters based on the main election. | The classifications of the main elections by election study are | listed in the VARIABLE NOTES for variable E3013_OUTGOV. | | CSES classifies the main election based on the regime | (executive) type and the election in which the CSES survey has | been administered. For polities rated as parliamentary systems, | CSES classifies the main election as elections to the lower house | for most studies. It deviates for a few cases when elections to | the upper house constitutes the main election, usually due to the | respective CSES study focusing on the upper house contest. | For polities rated as Presidential systems, CSES conventionally | classifies the main election as the Presidential election. It | sometimes deviates when data for the Presidential election is | unavailable (e.g., when the CSES survey was administered in a | midterm election). For polities rated as mixed systems, CSES | has tended to classify the main election as elections to the | lower house. However, it sometimes deviates depending on data | availability. Users are advised to consult the table listed in | VARIABLE NOTES for E3013_OUTGOV specifying the main election for | each study in CSES for specific details. | ELECTION STUDY NOTES - GREECE (2015): E3012_FTV | | Users are advised that Greece has a policy in place specifying | citizens are permitted to vote in parliamentary elections if they | will be of voting age in the year the election is held. | Since the previous election was held in 2012, respondents born in | 1994 or earlier, where the voting age was 18, were eligible to | vote in the 2012 election. | Therefore, respondents born in 1994 were coded as "0. R IS NOT A | FIRST-TIME VOTER" in E3012_FTV. | ELECTION STUDY NOTES - GREECE (2019): E3012_FTV | | Users are advised that Greece has a policy in place specifying | citizens are permitted to vote in parliamentary elections if they | will be of voting age in the year the election is held. | Since the previous election was held in 2015, respondents born in | 1997 or earlier, where the voting age was 18, were eligible to | vote in the 2015 election. | Therefore, respondents born in 1997 were coded as "0. R IS NOT A | FIRST-TIME VOTER" in E3012_FTV. | ELECTION STUDY NOTES - ISRAEL (2020): E3012_FTV | | Israel has a policy specifying 17-year-olds can also vote in | national elections held after their 18th Hebrew calendar | birthday. Respondents who were aged 17 at the previous election | year (2019) were coded to 6. NOT ASCERTAINABLE in E3012_FTV. | ELECTION STUDY NOTES - NORWAY (2017): E3012_FTV | | Users are advised that Norway has a policy in place specifying | citizens are permitted to vote in parliamentary elections if they | will be of voting age in the year the election is held. | Since the previous election was held in 2013, respondents born in | 1995 or earlier were eligible to vote in the 2013 election. | Therefore, respondents born in 1995 were coded as "0. R IS NOT A | FIRST-TIME VOTER" in E3012_FTV. --------------------------------------------------------------------------- E3013_PR_1 >>> Q12P1-b. CURRENT PRESIDENTIAL ELECTION: VOTE CHOICE - 1ST ROUND --------------------------------------------------------------------------- Respondent's vote choice for President in the first round of election. .................................................................. 000001-999987. [SEE PART 3 OF CODEBOOK FOR NUMERICAL PARTY/ COALITION CODES] 999988. NONE OF THE CANDIDATES/PARTIES 999989. INDEPENDENT CANDIDATE 999990. OTHER LEFT WING CANDIDATE/PARTY 999991. OTHER RIGHT WING CANDIDATE/PARTY 999992. OTHER CANDIDATE/PARTY (NOT FURTHER SPECIFIED) 999993. INVALID/BLANK BALLOT 999995. NOT APPLICABLE: NO ROLE OF PRESIDENT 999996. NOT APPLICABLE: NO PRESIDENTIAL ELECTION 999997. VOLUNTEERED: REFUSED 999998. VOLUNTEERED: DON'T KNOW 999999. MISSING/ABSTAINED (DID NOT VOTE) | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3013_PR_1 | | E3013_PR_1 details the respondent's vote choice for President | in the first round of election, if applicable and a respondent | cast a ballot in the Presidential election. Hence, E3013_PR_1 | details reported vote choice, irrespective of whether respondents | voted on election day or participated in early/advance voting. | | Parties/coalitions and their numerical & alphabetical | classifications for each election study are detailed in Part 3 | of the CSES Codebook. | ELECTION STUDY NOTES - BRAZIL (2018): E3013_PR_1 | | Presidential candidates were supported by their own as well as | other parties. | | Jair Bolsonaro, the Presidential candidate of the Social Liberal | Party (PSL) was also endorsed by the Brazilian Labor Renewal | Party (PRTB). | | Fernando Haddad, the Presidential candidate of the Workers' | Party (PT) was also endorsed by the Republican Party of the | Social Order (PROS) and the Communist Party of Brazil (PCdoB). | | Ciro Gomes, the Presidential candidate of the Democratic Labor | Party (PDT) was also endorsed by the Forward (Avante). | | Henrique Meirelles, the Presidential candidate of the Brazilian | Democratic Movement (MDB) was also endorsed by the Humanist | Party of Solidarity (PHS). | | Marina Silva, the Presidential candidate of the Sustainability | Network (REDE) was also endorsed by the Green Party (PV). | | Alvaro Dias, the Presidential candidate of the We Can (PODE) | was also endorsed by Social Christian Party (PSC), the Christian | Labor Party (PTC) and the Progressive Republican Party (PRP). | | Geraldo Alckmin, the Presidential candidate of the Brazilian | Social Democracy Party (PSDB) was also endorsed by the Democrats | (DEM), the Progressives (PP), the Liberal Party (PL), the | Republicans (PRB), the Solidarity (SD), the Brazilian Labor | Party (PTB), the Social Democratic Party (PSD), and the | Citizenship (PPS). | | Guilherme Boulos, the Presidential candidate of the Socialism | and Liberty Party (PSOL) was also endorsed by the Brazilian | Communist Party (PCB). | ELECTION STUDY NOTES - EL SALVADOR (2019): E3013_PR_1 | | NUMERICAL CODE 222002 refers to the ARENA-PCN-PDC-DS alliance for | E3013_PR_1. | ELECTION STUDY NOTES - FRANCE (2017): E3013_PR_1 | | Four Presidential Candidates were endorsed by more than their | own party: | | Emmanuel Macron, the Presidential candidate of the Republic | Onwards! (LaREM) was endorsed by the Democratic Movement (MoDem). | | Francois Fillon, the Presidential candidate of the Republicans | (LR) was endorsed by the Union of Democrats and Independents | (Union des democrates et independants, UDI) and the Christian | Democratic Party (Parti Chretien-Democrate, PCD). | | Jean-Luc Melenchon, the Presidential candidate of Indomitable | France (FI) was endorsed by the French Communist Party (PCF). | | Benoit Hamon, the Presidential candidate of the Socialist Party | (PS) was endorsed by Europe Ecology - The Greens (EELV), after | their own candidate, Yannick Jadot, withdrew his candidacy on | February 23, 2017. Hamon was also supported by the Radical Party | of the Left (Parti radical de gauche, PRG). | ELECTION STUDY NOTES - MEXICO (2018): E3013_PR_1 | | Numerical codes in E3013_PR_1 refer to the following candidates: | | NUMERICAL CODE Election Study Code/Category |---------------------------------------------------------------- | 484001. Andres Manuel Lopez Obrador (MORENA) | 484002. Ricardo Anaya Cortes (PAN) | 484003. Jose Antonio Meade Kuribrena (PRI) | 484089. Jaime Heliodoro Rodriguez Calderon | (Independent) | | Presidential candidates were backed by the following three | alliances: | | "Together We Will Make History" was an electoral alliance in | support of Andres Manuel Lopez Obrador and consisted of | the National Regeneration Movement (MORENA, PARTY A), the Labor | Party (PT, PARTY G), and the Social Encounter Party | (PES, PARTY I). | | "For Mexico to the Front" was an electoral alliance supporting | Ricardo Anaya Cortes and encompassed the National Action Party | (PAN, PARTY B), the Party of the Democratic Revolution (PRD, | PARTY D), and Citizens' Movement (MC, PARTY F). | | "Everyone for Mexico" associated with Jose Antonio Meade | Kuribrena was made up of the Institutional Revolutionary Party | (PRI, PARTY C), the Ecologist Green Party of Mexico (PVEM, | PARTY E), and the New Alliance Party (PNA, PARTY H). | | One respondent claimed to have voted for Margarita Zavala. | Zavala contested the campaign as an independent candidate, but | withdrew her candidacy in May 2018. As votes for Zavala were | counted as invalid votes ("nulos"), the respective respondent | was coded as 999993. INVALID/BLANK BALLOT. | ELECTION STUDY NOTES - TUNISIA (2019): E3013_PR_1 | | The following candidates contested in the 2019 Tunisian | Presidential election: | | NUMERICAL CODE Election Study Code/Category |---------------------------------------------------------------- | 788001. Abdelfattah Mourou (Ennahda Movement) | 788002. Nabil Karoui (Heart of Tunisia) | 788003. Abir Moussi (Free Destourian Party) | 788004. Mohamed Abbou (Democratic Current) | 788005. Seifeddine Makhlouf (Dignity Coalition) | 788007. Youssef Chahed (Long Live Tunisia) | 788008. Lotfi Mraihi (Republican People's Union) | 788010. Mehdi Jomaa (Tunisian Alternative) | 788013. Mongi Rahoui (Popular Front) | 788016. Hechmi Hamdi (Current of Love) | 788019. Moncef Marzouki (Movement Party) | 788020. Kais Saied (Independent) | 788021. Abdelkrim Zbidi (Independent) | 788022. Safi Said (Independent) | 788023. Hamma Hammami (Independent) | 788024. Elyes Fakhfakh (Democratic Forum for Labor | and Liberties) | ELECTION STUDY NOTES - TURKEY (2018): E3013_PR_1 | | The following candidates contested in the 2018 Turkish | Presidential election: | | NUMERICAL CODE Election Study Code/Category |---------------------------------------------------------------- | 792001. Recep Tayyip Erdogan (AKP) | 792002. Muharrem Ince (CHP) | 792003. Selahattin Demirtas (HDP) | 792005. Meral Aksener (IYI) | 792006. Temel Karamollaoglu (SP) | 792008. Dogu Perincek (VP) | | Recep Tayyip Erdogan and his party, the Justice and Development | Party (PARTY A) fared considerably better in the sample than | expected given official election results for both the | Presidential and the Lower House election. | Collaborators state respondents might have been more inclined to | pick the winner in the post-election phase, a trend they also | observed in an additional panel survey not included in CSES. | Further, they suggest that Erdogan's and the AKP's popularity in | the sample might be a misrepresentation of party preferences | rather than a sampling mistake since vote switching appeared | primarily across the opposition parties in the separate panel | study. | ELECTION STUDY NOTES - UNITED STATES (2020): E3013_PR_1 | | Respondents were asked in the pre-election survey whether they | had voted already. Respondents who affirmed this were asked the | questions about their voting behavior (E3012_PR_1-E3013_UH_DC) | already in the pre-election survey. All other respondents were | asked the questions about their voting behavior in the post- | election part of the survey. Early voters are indicated as | belonging to a different sample component in variable E1007. | | The original data show that 20 respondents reported their | voting behavior inconsistently. When asked before the elections | whether they had already participated in early voting they | answered yes. However, when asked after the elections they | reported having voted on election day. For the CSES coding, the | answer given before the elections is assumed to be valid. --------------------------------------------------------------------------- E3013_PR_2 >>> Q12P2-b. CURRENT PRESIDENTIAL ELECTION: VOTE CHOICE - 2ND ROUND --------------------------------------------------------------------------- Respondent's vote choice for President in the second round of election. .................................................................. 000001-999987. [SEE PART 3 OF CODEBOOK FOR NUMERICAL PARTY/ COALITION CODES] 999988. NONE OF THE CANDIDATES/PARTIES 999989. INDEPENDENT CANDIDATE 999990. OTHER LEFT WING CANDIDATE/PARTY 999991. OTHER RIGHT WING CANDIDATE/PARTY 999992. OTHER CANDIDATE/PARTY (NOT FURTHER SPECIFIED) 999993. INVALID/BLANK BALLOT 999995. NOT APPLICABLE: NO ROLE OF PRESIDENT 999996. NOT APPLICABLE: NO PRESIDENTIAL ELECTION / NO SECOND ROUND 999997. VOLUNTEERED: REFUSED 999998. VOLUNTEERED: DON'T KNOW 999999. MISSING/ABSTAINED (DID NOT VOTE) | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3013_PR_2 | | E3013_PR_2 details the respondent's vote choice for President | in the second round of election, if applicable and a respondent | cast a ballot in the Presidential election. Hence, E3013_PR_2 | details reported vote choice, irrespective of whether respondents | voted on election day or participated in early/advance voting. | | Parties/coalitions and their numerical & alphabetical | classifications for each election study are detailed in Part 3 | of the CSES Codebook. --------------------------------------------------------------------------- E3013_LH_PL >>> Q12LH-b. CURRENT LOWER HOUSE ELECTION: VOTE CHOICE - PARTY LIST --------------------------------------------------------------------------- Respondent's vote choice for party list in Lower House elections. .................................................................. 000001-999987. [SEE PART 3 OF CODEBOOK FOR NUMERICAL PARTY/ COALITION CODES] 999988. NONE OF THE CANDIDATES/PARTIES 999989. INDEPENDENT CANDIDATE 999990. OTHER LEFT WING CANDIDATE/PARTY 999991. OTHER RIGHT WING CANDIDATE/PARTY 999992. OTHER CANDIDATE/PARTY (NOT FURTHER SPECIFIED) 999993. INVALID/BLANK BALLOT 999995. NOT APPLICABLE: NOT A LIST SYSTEM 999996. NOT APPLICABLE: NO LOWER HOUSE ELECTION 999997. VOLUNTEERED: REFUSED 999998. VOLUNTEERED: DON'T KNOW 999999. MISSING/ABSTAINED (DID NOT VOTE) | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3013_LH_PL | | E3013_LH_PL details the respondent's vote choice for party list | in Lower House elections, if applicable and a respondent cast a | ballot in the Lower House legislative election. | Hence, E3013_LH_PL details reported vote choice, irrespective of | whether respondents voted on election day or participated in | early/advance voting. | | If more than one candidate have one party's affiliation, | Collaborators were advised to provide vote choice for individual | candidates. For preferential voting systems, Collaborators were | asked to provide the first two preferences (Q12LH-c1 and | Q12LH-c2). | | Parties/coalitions and their numerical & alphabetical | classifications for each election study are detailed in Part 3 | of the CSES Codebook. | | Respondents that mentioned not casting a ballot in the current | lower house election (E3012_LH) but report a vote choice | are included, as it is not possible to identify why this | inconsistency occurred. Users may identify these cases by | cross-tabulating E3012_LH and E3013_LH_PL in their statistical | software. | ELECTION STUDY NOTES - CHILE (2017): E3013_LH_PL | | Even though voters in Chile cast votes for candidates in an open | list proportional system, alliances play the most important role | in the work of parliament and government formation. Some | respondents reported voting for an electoral alliance or an | independent candidate affiliated with the electoral coalition. | These respondents are coded as voting for the coalition, which is | the reason why coalitions are assigned a separate code. For more | information about coalitions in Chile, see Part 3 of the CSES | Codebook - Parties and Leaders. | ELECTION STUDY NOTES - COSTA RICA (2018): E3013_LH_PL | | In the Costa Rican election study, four respondents reported a | vote choice although they stated that they did not vote. | Users can detect these respondents if they look at the | cross-tabulation between turnout (E3012_LH) and vote choice | (E3013_LH_PL). | ELECTION STUDY NOTES - CZECHIA (2021): E3013_LH_PL | | For E3013_LH_PL, numerical codes refer to the following | alliances: | - NUMERICAL CODE 203101: SPOLU alliance | - NUMERICAL CODE 203103: PirStan alliance | - NUMERICAL CODE 203108: Trikolora-Svobodni-Soukromnici alliance | Consult Part 3 of the CSES Codebook for more information. | ELECTION STUDY NOTES - FINLAND (2019): E3013_LH_PL | | The data collection organization programmed the questionnaire | incorrectly and consequently, 288 respondents were not asked | several items in the Finnish study. This affected two CSES | items: turnout and vote choice variables. | The error was detected after the data collection had concluded. | To amend the problem, the data collection organization attempted | to re-contact the affected respondents by phone and ask the | questions that had not been included during the initial | interview. The affected respondents did not retake the entire | interview. | Variable E1007 (Sample component) includes information that | enables users to distinguish these respondents in the Finland | (2019) study. SEE ELECTION STUDY NOTES - FINLAND (2019): E1007 | for further information. | | Further, for all survey variables including numeric party codes, | the Finnish questionnaire included the open-ended option "Other | party or group", allowing respondents to specify a party | otherwise not included in the survey. Collaborators classified | these open-ended answers into the following codes adopted for | CSES: | | NUMERICAL CODE Election Study Code/Category |---------------------------------------------------------------- | 999990. Animal Justice Party of Finland | Feminist Party | Communist Party of Finland | 999991. Liberal Party | Movement Now | Finnish People First | 999992. Seven Star Movement | R did not further specify party in open-ended | "Other party or group" option | ELECTION STUDY NOTES - GERMANY (2021): E3013_LH_PL | | Researchers are advised that the Social Democratic Party | (PARTY A) and the Greens (PARTY C) fared better in the sample | than expected given official election results. At the same time, | the Union (PARTY B) and the AfD (PARTY E) did slightly worse in | the sample than in the actual election. | Collaborators note although they used to have issues with the | overrepresentation of Green Party voters and underrepresentation | of AfD voters in past surveys, these distortions seem to be more | pronounced in 2021. They assume the reasons for this to be | twofold: | On the one hand, there are challenges in reaching AfD voters, | who appear to have lower-than-average participation rates, while | Green and SPD voters can be reached with ease due to, for | example, higher political interest. On the other hand, there may | be distortions in socio-demographics, particularly in the | underrepresentation of those with lower education levels and | overrepresentation of those with higher education levels, whose | influence on vote choice cannot be fully compensated for by | weighting. | ELECTION STUDY NOTES - GREECE (2019): E3013_LH_PL | | One respondent claimed to have voted for a party that did not | contest in the 2019 legislative election. Collaborators coded | this respondent to 999999. MISSING. | ELECTION STUDY NOTES - HONG KONG (2016): E3013_LH_PL | | E3013_LH_PL reflects vote choice for geographical constituency | elections, which return 35 out of 70 seats for the unicameral | legislature of Hong Kong, the Legislative Council (LegCo). | Voters cast one vote for closed party lists, which are compiled | separately for each of the five electoral districts and in some | instances feature more than one list per party per district. | The original vote choice variable assigned an individual code to | each party list. E3013_LH_PL summarizes vote choice for each | combination of parties forming a joint party list. | | 22 respondents stated to have voted for a party list that did | not compete in their electoral district. As it could not be | assessed with certainty which lists these respondents actually | voted for, E3013_LH_PL was set to missing for these cases. | | Further, the 2016 Hong Kong study employed additional codes for | missing values, which were recoded as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 999988. Did not vote for any candidate list | 999998. Forgotten | Don't know | ELECTION STUDY NOTES - HUNGARY (2018): E3013_LH_PL | | For all vote choice variables, the Hungarian study had a category | "Will not say which party I voted for." These respondents are | recoded into CSES category "999997. Volunteered: Refused." | ELECTION STUDY NOTES - ITALY (2018): E3013_LH_PL | | In the 2018 lower house elections, voters could vote for a party | list only, a party list and a district candidate, or a district | candidate only. For voters who voted for a party list and a | district candidate, split-ticket voting was not permitted. The | ballots of voters who voted for either a party list or a | district candidate were treated as a fused vote, i.e., the vote | for a party list was automatically extended to the lists' | respective district candidate (and vice-versa, i.e., a vote for | a district candidate was extended to the candidate's party | list). E3013_LH_PL reports the votes of those reporting to have | cast a list vote and those who reported voting for both a party | list and a district candidate. Respondents' vote choices for | those who reported voting only for a district candidate were | coded in E3013_LH_DC. | The original wording for what is coded here as "999997. REFUSED" | was "I would rather not say." | ELECTION STUDY NOTES - POLAND (2019): E3013_LH_PL | | For E3013_LH_PL, numerical codes refer to the following | alliances: | - NUMERICAL CODE 616001: United Right alliance | - NUMERICAL CODE 616002: Civic Coalition alliance | - NUMERICAL CODE 616003: Polish Coalition alliance | - NUMERICAL CODE 616004: The Left alliance | - NUMERICAL CODE 616010: Confederation alliance | Consult Part 3 of the CSES Codebook for more information. | ELECTION STUDY NOTES - SLOVAKIA (2020): E3013_LH_PL | | NUMERICAL CODE 703001: OLaNO contested the 2020 Slovakian | Parliamentary election as biggest and dominant member of an | electoral alliance consisting of the following additional | parties: | - NUMERICAL CODE 703019: Christian Union | - NOVA | - Change from Bottom, Democratic Union of Slovakia | ELECTION STUDY NOTES - SWITZERLAND (2019): E3013_LH_PL | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 999992. Voted for persons, not parties | Voted for several parties | ELECTION STUDY NOTES - THAILAND (2019): E3013_LH_PL | | In the 2019 election to the Thai House of Representatives, | 350 members were elected by plurality vote in single-member | constituencies (district candidate vote) and 150 members | were elected through a closed-list proportional representation | system (party-list vote). However, voters cast a single fused | vote for both segments. Hence, citizens are unable to split | their vote among the candidates or lists of different parties. | As variables E3013_LH_PL and E3013_LH_DC indicate respondents' | vote choice based on this single fused vote cast, they can be | used interchangeably. | ELECTION STUDY NOTES - TURKEY (2018): E3013_LH_PL | | Recep Tayyip Erdogan and his party, the Justice and Development | Party (PARTY A) fared considerably better in the sample than | expected given official election results for both the | Presidential and the Lower House election. | Collaborators state respondents might have been more inclined to | pick the winner in the post-election phase, a trend they also | observed in an additional panel survey not included in CSES. | Further, they suggest that Erdogan's and the AKP's popularity in | the sample might be a misrepresentation of party preferences | rather than a sampling mistake since vote switching appeared | primarily across the opposition parties in the separate panel | study. --------------------------------------------------------------------------- E3013_LH_DC >>> Q12LH-c. CURRENT LOWER HOUSE ELECTION: VOTE CHOICE - DISTRICT CANDIDATE --------------------------------------------------------------------------- Respondent's vote choice for district candidate in Lower House elections. .................................................................. 000001-999987. [SEE PART 3 OF CODEBOOK FOR NUMERICAL PARTY/ COALITION CODES] 999988. NONE OF THE CANDIDATES/PARTIES 999989. INDEPENDENT CANDIDATE 999990. OTHER LEFT WING CANDIDATE/PARTY 999991. OTHER RIGHT WING CANDIDATE/PARTY 999992. OTHER CANDIDATE/PARTY (NOT FURTHER SPECIFIED) 999993. INVALID/BLANK BALLOT 999995. NOT APPLICABLE: NO DISTRICT CANDIDATE VOTE 999996. NOT APPLICABLE: NO LOWER HOUSE ELECTION 999997. VOLUNTEERED: REFUSED 999998. VOLUNTEERED: DON'T KNOW 999999. MISSING/ABSTAINED (DID NOT VOTE) | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3013_LH_DC | | E3013_LH_DC details the respondent's vote choice for district | candidate in Lower House elections, if applicable and a | respondent cast a ballot in the Lower House legislative election. | Hence, E3013_LH_DC details reported vote choice, irrespective of | whether respondents voted on election day or participated in | early/advance voting. | | If more than one candidate have one party's affiliation, | Collaborators were advised to provide vote choice for individual | candidates. For preferential voting systems, Collaborators were | asked to provide the first two preferences (Q12LH-c1 and | Q12LH-c2). | | Parties/coalitions and their numerical & alphabetical | classifications for each election study are detailed in Part 3 | of the CSES Codebook. | | Respondents that mentioned not casting a ballot in the current | lower house election (E3012_LH) but report a vote choice | are included, as it is not possible to identify why this | inconsistency occurred. Users may identify these cases by | cross-tabulating E3012_LH and E3013_LH_DC in their statistical | software. | ELECTION STUDY NOTES - AUSTRALIA (2019): E3013_LH_DC | | The Australian study included a category "no party" for the vote | choice variable. Since that was not an option on the ballot, | the Australian voting system does not allow this possibility, | and following Collaborators' advice, these respondents were | recoded to missing. | ELECTION STUDY NOTES - HUNGARY (2018): E3013_LH_DC | | For all vote choice variables, the Hungarian study had a category | "Will not say which party I voted for." These respondents are | recoded into CSES category "999997. Volunteered: Refused." | ELECTION STUDY NOTES - IRELAND (2016): E3013_LH_DC | | Three respondents reported having voted for a candidate of the | Independent Alliance (IA). These respondents were coded as | "999989. INDEPENDENT CANDIDATE" because the IA was not formally | registered as a political party. | ELECTION STUDY NOTES - ITALY (2018): E3013_LH_DC | | In the 2018 lower house elections, voters could vote for a party | list only, a party list and a district candidate, or a district | candidate only. For those who voted for a party list and a | district candidate, split-ticket voting was not permitted. The | ballots of voters who voted for either a party list or a | district candidate were treated as a fused vote, i.e., the vote | for a party list was automatically extended to the lists' | respective district candidate (and vice-versa, i.e., a vote for | a district candidate was extended to the candidate's party | list). E3013_LH_DC reports the votes of those reporting to have | cast a district candidate vote. Respondents' vote choices for | those who reported having cast a party list vote or both a party | list and a district candidate vote were coded in E3013_LH_PL. | Respondents who reported a district candidate vote were asked to | to name the party list or coalition of the candidate they voted | for which was used to code E3013_LH_DC. | 56 Respondents named a candidate of one of the two large | coalitions, i.e., the center-right and the center-left | coalition. They were further asked which of the coalition | members they liked most. The answer to the latter was coded as | the respondent's vote choice in E3013_LH_DC as coalitions were | not assigned numerical party codes. Finally, 13 respondents who | reported to have voted for one of the two coalitions did not | like any particular party from the coalition. These respondents | were coded to have voted for the leading party of the respective | coalition, namely, Lega (LN - NUMERICAL CODE: 380003) for the | center-right coalition and the Democratic Party (PD - NUMERICAL | CODE: 380002) for the center-left coalition. | ELECTION STUDY NOTES - LITHUANIA (2016): E3013_LH_DC | | The data refers to the first round of the elections, held on | October 9, 2016. | | CSES Code Election Study Code/Category | --------------------------------------------------------------- | 999988. Did not vote for a candidate | ELECTION STUDY NOTES - LITHUANIA (2020): E3013_LH_DC | | Data refer to the first round of the lower house elections, held | on October 11, 2020. | ELECTION STUDY NOTES - THAILAND (2019): E3013_LH_DC | | In the 2019 election to the Thai House of Representatives, | 350 members were elected by plurality vote in single-member | constituencies (district candidate vote) and 150 members | were elected through a closed-list proportional representation | system (party-list vote). However, voters cast a single fused | vote for both segments. Hence, citizens are unable to split | their vote among the candidates or lists of different parties. | As variables E3013_LH_PL and E3013_LH_DC indicate respondents' | vote choice based on this single fused vote cast, they can be | used interchangeably. | ELECTION STUDY NOTES - UNITED STATES (2020): E3013_LH_DC | | Respondents were asked in the pre-election survey whether they | had voted already. Respondents who affirmed this were asked the | questions about their voting behavior (E3012_PR_1-E3013_UH_DC) | already in the pre-election survey. All other respondents were | asked the questions about their voting behavior in the post- | election part of the survey. Early voters are indicated as | belonging to a different sample component in variable E1007. | | The original data show that 20 respondents reported their | voting behavior inconsistently. When asked before the elections | whether they had already participated in early voting they | answered yes. However, when asked after the elections they | reported having voted on election day. For the CSES coding, the | answer given before the elections is assumed to be valid. --------------------------------------------------------------------------- E3013_LH_PF >>> Q12LH-d. CURRENT LOWER HOUSE ELECTION: DID RESPONDENT CAST CANDIDATE PREFERENCE VOTE --------------------------------------------------------------------------- Whether a respondent cast a preference vote in Lower House elections. .................................................................. 1. RESPONDENT CAST PREFERENCE VOTE IN PR-LIST SYSTEM 2. RESPONDENT CAST PREFERENCE VOTE IN AV/STV SYSTEM 5. RESPONDENT DID NOT CAST PREFERENCE VOTE 6. RESPONDENT CAST INVALID BALLOT 95. NOT APPLICABLE: NOT A PREFERENCE VOTE SYSTEM 96. NOT APPLICABLE: NO LOWER HOUSE ELECTION 97. VOLUNTEERED: REFUSED 98. VOLUNTEERED: DON'T KNOW 99. MISSING | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3013_LH_PF | | For more detailed information on how CSES codes | parties/coalitions, please see Part 3 of the CSES Codebook. | | There are two different types of preference vote. The first is | associated with open PR-List systems. These systems allow | citizens to vote for a party list and to mark a "preference" for | one or more candidates within the party list. In these systems, | this type of vote is known as a preference vote (or a candidate | vote). The second is associated with STV and AV systems, where | citizens rank-order candidates in descending order of their | preference. In these systems, a distinction is made between a | voter's first preference (i.e., who voters allocate their | "number 1" preference to) and their subsequent lower preferences. | These latter preferences (i.e., all the voter's preferences aside | from their first preference) are also known as preference votes. | We distinguish between these two different types of preference | votes in the above categorization. | | In party list systems, the question asked of respondents should | read like this: | "Did you simply vote for a party or did you also express a | candidate preference?" | | In party list systems where voters have to vote directly for a | candidate and cannot cast a vote for the party list only (e.g., | Estonia, Finland, and Poland), the question asked of respondents | should read like this: | "Do you consider the vote that you cast merely a vote for the | party, or did you also mean it as a vote for a particular | candidate?" | | In STV/AV systems, the question asked of respondents should be | akin to this: | "Which of the parties/candidates did you give your | preference vote to?" | or | "To whom did you give your second (or lower) preference vote to?" | | Respondents that mentioned not casting a ballot in the current | lower house election (E3012_LH) but reported a preference vote | are included, as it is not possible to identify why this | inconsistency occurred. Users may identify these cases by | cross-tabulating E3012_LH and E3013_LH_PF in their statistical | software. | | Data are unavailable for ALBANIA (2017), IRELAND (2016) and | FINLAND (2019). | ELECTION STUDY NOTES - CHILE (2017): E3013_LH_PF | | One respondent reported having cast a preference vote after | also indicating not to have voted in the lower house election | (E3012_LH). Data remain unchanged. | ELECTION STUDY NOTES - LITHUANIA (2016): E3013_LH_PF | | Voters in Lithuania can cast a preference vote in the | multi-member constituency, proportional segment (party list | vote). Under the Lithuanian electoral law, a "voter shall mark | the list of candidates whom he is voting for and, expressing his | opinion about the candidates on the list, shall enter the | election numbers of the 5 chosen candidates in the designated | spaces of the ballot paper. In this way preference votes are | given for the candidates." Voters are not required to express | preferences regarding the candidates. | ELECTION STUDY NOTES - SWEDEN (2018): E3013_LH_PF | | 14 respondents reported whether they cast a preference vote | after also indicating they did not vote in the lower house | election (E3012_LH). Data remain unchanged. --------------------------------------------------------------------------- E3013_UH_PL >>> Q12UH-b. CURRENT UPPER HOUSE ELECTION: VOTE CHOICE - PARTY LIST --------------------------------------------------------------------------- Respondent's vote choice for party list in Upper House elections. .................................................................. 000001-999987. [SEE PART 3 OF CODEBOOK FOR NUMERICAL PARTY/ COALITION CODES] 999988. NONE OF THE CANDIDATES/PARTIES 999989. INDEPENDENT CANDIDATE 999990. OTHER LEFT WING CANDIDATE/PARTY 999991. OTHER RIGHT WING CANDIDATE/PARTY 999992. OTHER CANDIDATE/PARTY (NOT FURTHER SPECIFIED) 999993. INVALID/BLANK BALLOT 999995. NOT APPLICABLE: UNICAMERAL SYSTEM 999996. NOT APPLICABLE: NO UPPER HOUSE ELECTION OR LIST VOTE 999997. VOLUNTEERED: REFUSED 999998. VOLUNTEERED: DON'T KNOW 999999. MISSING/ABSTAINED (DID NOT VOTE) | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3013_UH_PL | | E3013_UH_PL details the respondent's vote choice for party list | in Upper House elections, if applicable and a respondent cast a | ballot in the Upper House legislative election. | Hence, E3013_UH_PL details reported vote choice, irrespective of | whether respondents voted on election day or participated in | early/advance voting. | | Parties/coalitions and their numerical & alphabetical | classifications for each election study are detailed in Part 3 | of the CSES Codebook. | ELECTION STUDY NOTES - ITALY (2018): E3013_UH_PL | | In the 2018 upper house elections, voters could vote for a party | list only, a party list and a district candidate, or a district | candidate only. For those who voted for a party list and a | district candidate, split-ticket voting was not permitted. The | ballots of voters who voted for either a party list or a | district candidate were treated as a fused vote, i.e., the vote | for a party list was automatically extended to the lists' | respective district candidate (and vice-versa, i.e., a vote for | a district candidate was extended to the candidate's party | list). E3013_UH_PL reports the votes of those reporting to have | cast a list vote and those who reported voting for both a party | list and a district candidate. | ELECTION STUDY NOTES - POLAND (2019): E3013_UH_PL | | For E3013_UH_PL, numerical codes refer to the following | alliances: | - NUMERICAL CODE 616001: United Right alliance | - NUMERICAL CODE 616002: Civic Coalition alliance | - NUMERICAL CODE 616003: Polish Coalition alliance | - NUMERICAL CODE 616004: The Left alliance | - NUMERICAL CODE 616010: Confederation alliance | Consult Part 3 of the CSES Codebook for more information. --------------------------------------------------------------------------- E3013_UH_DC_1 >>> Q12UH-c. CURRENT UPPER HOUSE ELECTION: VOTE CHOICE - DISTRICT CANDIDATE 1 E3013_UH_DC_2 >>> Q12UH-c. CURRENT UPPER HOUSE ELECTION: VOTE CHOICE - DISTRICT CANDIDATE 2 --------------------------------------------------------------------------- Respondent's vote choice for district candidate/s in Upper House elections. .................................................................. 000001-999987. [SEE PART 3 OF CODEBOOK FOR NUMERICAL PARTY/ COALITION CODES] 999988. NONE OF THE CANDIDATES/PARTIES 999989. INDEPENDENT CANDIDATE 999990. OTHER LEFT WING CANDIDATE/PARTY 999991. OTHER RIGHT WING CANDIDATE/PARTY 999992. OTHER CANDIDATE/PARTY (NOT FURTHER SPECIFIED) 999993. INVALID/BLANK BALLOT 999995. NOT APPLICABLE: UNICAMERAL SYSTEM 999996. NOT APPLICABLE: NO UPPER HOUSE ELECTION OR CANDIDATE VOTE 999997. VOLUNTEERED: REFUSED 999998. VOLUNTEERED: DON'T KNOW 999999. MISSING/ABSTAINED (DID NOT VOTE) | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3013_UH_DC_ | | E3013_UH_DC_ detail the respondent's vote choice for district | candidate/s in Upper House elections, if applicable and a | respondent cast a ballot in the Upper House legislative election. | Hence, E3013_UH_DC_ detail reported vote choice, irrespective of | whether respondents voted on election day or participated in | early/advance voting. | | Parties/coalitions and their numerical & alphabetical | classifications for each election study are detailed in Part 3 | of the CSES Codebook. | ELECTION STUDY NOTES - ITALY (2018): E3013_UH_DC_1 | | In the 2018 upper house elections, voters could vote for a party | list only, a party list and a district candidate, or a district | candidate only. For those who voted for a party list and a | district candidate, split-ticket voting was not permitted. The | ballots of voters who voted for either a party list or a | district candidate were treated as a fused vote, i.e., the vote | for a party list was automatically extended to the lists' | respective district candidate (and vice-versa, i.e., a vote for | a district candidate was extended to the candidate's party | list). E3013_UH_DC_1 reports the votes of those reporting to | have cast a district candidate vote. Respondents' vote choices | for those who reported having cast a party list vote or both a | party list and a district candidate vote were coded in | E3013_UH_PL. | Respondents who reported a district candidate vote were asked to | to name the party list or coalition of the candidate they voted | for which was used to code E3013_UH_DC_1. | 48 Respondents named a candidate of one of the two large | coalitions, i.e., the center-right and the center-left | coalition. They were further asked which of the coalition | members they liked most. The answer to the latter was coded as | the respondent's vote choice in E3013_LH_DC_1 as coalitions were | not assigned numerical party codes. | ELECTION STUDY NOTES - UNITED STATES (2020): E3013_UH_DC_1 | | Respondents were asked in the pre-election survey whether they | had voted already. Respondents who affirmed this were asked the | questions about their voting behavior (E3012_PR_1-E3013_UH_DC) | already in the pre-election survey. All other respondents were | asked the questions about their voting behavior in the post- | election part of the survey. Early voters are indicated as | belonging to a different sample component in variable E1007. | | The original data show that 20 respondents reported their | voting behavior inconsistently. When asked before the elections | whether they had already participated in early voting they | answered yes. However, when asked after the elections they | reported having voted on election day. For the CSES coding, the | answer given before the elections is assumed to be valid. --------------------------------------------------------------------------- E3013_UH_PF >>> Q12UH-d. CURRENT UPPER HOUSE ELECTION: DID RESPONDENT CAST CANDIDATE PREFERENCE VOTE --------------------------------------------------------------------------- Whether a respondent cast a preference vote in Upper House elections. .................................................................. 1. RESPONDENT CAST PREFERENCE VOTE IN PR-LIST SYSTEM 2. RESPONDENT CAST PREFERENCE VOTE IN AV/STV SYSTEM 5. RESPONDENT DID NOT CAST PREFERENCE VOTE 6. RESPONDENT CAST INVALID BALLOT 95. NOT APPLICABLE: UNICAMERAL SYSTEM 96. NOT APPLICABLE: NO UPPER HOUSE ELECTION OR PREFERENCE VOTE SYSTEM 97. VOLUNTEERED: REFUSED 98. VOLUNTEERED: DON'T KNOW 99. MISSING | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3013_UH_PF | | For more detailed information on how CSES codes | parties/coalitions, please see Part 3 of the CSES Codebook. | | There are two different types of preference vote. The first is | associated with open PR-List systems. These systems allow | citizens to vote for a party list and to mark a "preference" for | one or more candidates within the party list. In these systems, | this type of vote is known as a preference vote (or a candidate | vote). The second is associated with STV and AV systems, where | citizens rank-order candidates in descending order of their | preference. In these systems, a distinction is made between a | voter's first preference (i.e., who voters allocate their | "number 1" preference to) and their subsequent lower preferences. | These latter preferences (i.e., all the voter's preferences aside | from their first preference) are also known as preference votes. | We distinguish between these two different types of preference | votes in the above categorization. | | In party list systems, the question asked of respondents should | read like this: | "Did you simply vote for a party or did you also express a | candidate preference?" | | In party list systems where voters have to vote directly for a | candidate and cannot cast a vote for the party list only (e.g., | Estonia, Finland, & Poland), the question asked of respondents | should read like this: | "Do you consider the vote that you cast merely a vote for the | party, or did you also mean it as a vote for a particular | candidate?" | | In STV/AV systems, the question asked of respondents should be | akin to this: | "Which of the parties/candidates did you give your preference | vote to?" | or | "To whom did you give your second (or lower) preference vote to?" | | Respondents that mentioned not casting a ballot in the current | upper house election (E3012_UH) but reported a vote choice are | included as it is not possible to identify why this | inconsistency occurred. Users may identify these cases by | cross-tabulating E3012_UH and E3013_UH_PF in their statistical | software. | ELECTION STUDY NOTES - BRAZIL (2018): E3013_UH_PF | | 479 respondents reported having cast a preference vote after | also indicating they had not voted in the upper house election | (E3012_UH). Data remain unchanged. --------------------------------------------------------------------------- E3013_OUTGOV >>> CURRENT MAIN ELECTION - VOTE CHOICE - OUTGOING GOVERNMENT (INCUMBENT) --------------------------------------------------------------------------- Whether or not the respondent cast a ballot for the outgoing incumbent. .................................................................. 0. DID NOT VOTE FOR THE OUTGOING GOVERNMENT (INCUMBENT) 1. VOTED FOR THE OUTGOING GOVERNMENT (INCUMBENT) 999996. NOT ASCERTAINED / INCUMBENT CANDIDATE/PARTY DID NOT CONTEST 999997. VOLUNTEERED: REFUSED 999998. VOLUNTEERED: DON'T KNOW 999999. MISSING/ABSTAINED (DID NOT VOTE) | CSES QUESTION CLASSIFICATION: DERIVATIVE VARIABLE (BASED ON CORE) | VARIABLE NOTES: E3013_OUTGOV | | E3013_OUTGOV ascertains whether or not the respondent cast a | ballot for the outgoing incumbent, regardless of whether or not | it was valid. | | In case of a single election taking place, e.g., a lower house | election only, E3013_OUTGOV reports the voting decision for | that particular election. In cases where multiple elections took | place, e.g., a Presidential and a lower house election, | E3013_OUTGOV reports the voting decision in the main election. | | CSES classifies the main election based on the regime | (executive) type and the election in which the CSES survey has | been administered. For polities rated as parliamentary systems, | CSES classifies the main election as elections to the lower house | for most studies. It deviates for a few cases when elections to | the upper house constitutes the main election, usually due to the | respective CSES study focusing on the upper house contest. | For polities rated as Presidential systems, CSES conventionally | classifies the main election as the Presidential election. It | sometimes deviates when data for the Presidential election is | unavailable (e.g., when the CSES survey was administered in a | midterm election). For polities rated as mixed systems, CSES | has tended to classify the main election as elections to the | lower house. However, it sometimes deviates depending on data | availability. Users are advised to consult the table below | specifying the main election for each study in CSES for specific | details. | | In case of a Presidential election as main election, E3013_OUTGOV | refers to the incumbent President and/or the incumbent | President's party. In all other cases, E3013_OUTGOV refers to | the party/parties which was/were part of the outgoing cabinet. | | In mixed electoral systems where voters have a list vote and a | district candidate vote, the list vote was used to determine if | the respondent voted for the outgoing government or not. | | In case of a caretaker government, the party affiliations of its | members were used to code E3013_OUTGOV. Cabinet members without | a formal party affiliation were not considered for E3013_OUTGOV. | | Respondents who reported to have cast an invalid ballot are coded | as "0. DID NOT VOTE FOR THE OUTGOING GOVERNMENT (INCUMBENT)." | | +++ TABLE: ELECTION STUDIES BY TYPE OF MAIN ELECTION | | Presidential Lower House Upper House | POLITY (ELEC YEAR) Election Election Election | ------------------------------------------------------------- | ALBANIA (2017) - X - | AUSTRALIA (2019) - X - | AUSTRIA (2017) - X - | BELGIUM-FLANDERS (2019) - X - | BELGIUM-WALLONIA (2019) - X - | BRAZIL (2018) X - - | CANADA (2019) - X - | CHILE (2017) X - - | COSTA RICA (2018) X - - | CZECHIA (2017) - X - | CZECHIA (2021) - X - | DENMARK (2019) - X - | EL SALVADOR (2019) X - - | FINLAND (2019) - X - | FRANCE (2017) X - - | GERMANY (2017) - X - | GERMANY (2021) - X - | GREAT BRITAIN (2017) - X - | GREAT BRITAIN (2019) - X - | GREECE (2015) - X - | GREECE (2019) - X - | HONG KONG (2016) - X* - | HUNGARY (2018) - X - | ICELAND (2016) - X - | ICELAND (2017) - X - | INDIA (2019) - X - | IRELAND (2016) - X - | ISRAEL (2020) - X - | ITALY (2018) - X - | JAPAN (2017) - X - | LATVIA (2018) - X - | LITHUANIA (2016) - X - | LITHUANIA (2020) - X - | MEXICO (2018) X - - | MONTENEGRO (2016) - X - | NETHERLANDS (2017) - X - | NETHERLANDS (2021) - X - | NEW ZEALAND (2017) - X - | NEW ZEALAND (2020) - X - | NORWAY (2017) - X - | PERU (2021) X - - | PORTUGAL (2019) - X - | ROMANIA (2016) - X* - | SLOVAKIA (2020) - X - | SOUTH KOREA (2016) - X - | SWEDEN (2018) - X - | SWITZERLAND (2019) - X* - | TAIWAN (2016) X - - | TAIWAN (2020) X - - | THAILAND (2019) - X* - | TUNISIA (2019) - X - | TURKEY (2018) X - - | UNITED STATES (2016) X - - | UNITED STATES (2020) X - - | URUGUAY (2019) X - - | ------------------------------------------------------------- | KEY: X = yes; - = no | * = Incumbent not identified - see ELECTION STUDY NOTES | below. | | The incumbent could not be identified for HONG KONG (2016), | ROMANIA (2016), SWITZERLAND (2019) and THAILAND (2019). | Further explanations are provided in the ELECTION STUDY NOTES | below. | ELECTION STUDY NOTES - BELGIUM-FLANDERS (2019): E3013_OUTGOV | | This variable is coded for outgoing incumbents in the Belgium | national government. Thus, all respondents who reported voting | for "Christian Democratic and Flemish (CD&V)" or "Open Flemish | Liberals and Democrats (Open Vld)" are set to "1. VOTED FOR THE | OUTGOING GOVERNMENT (INCUMBENT)" for E3013_OUTGOV for the | Belgium-Flanders study. | The Belgium Government was also composed of "Reformist Movement | (MR)" from Wallonia. | ELECTION STUDY NOTES - BELGIUM-WALLONIA (2019): E3013_OUTGOV | | This variable is coded for outgoing incumbents in the Belgium | national government. Thus, all respondents who reported voting | for "Reformist Movement (MR)" are set to "1. VOTED FOR THE | OUTGOING GOVERNMENT (INCUMBENT)" for E3013_OUTGOV for the | Belgium-Wallonia study. | The Belgium Government was also composed of "Christian Democratic | and Flemish (CD&V)" and "Open Flemish Liberals and Democrats | (Open Vld)" from Flanders. | ELECTION STUDY NOTES - BRAZIL (2018): E3013_OUTGOV | | For Brazil 2018, respondents are coded as having voted for the | incumbent if they voted for Dilma Rousseff's party, the Workers' | Party (PT), in the current Presidential election. | Rousseff was elected as President of Brazil in the 2014 election. | However, she was impeached in 2016. Former Vice President Michel | Temer (Brazilian Democratic Movement Party) succeeded Rousseff | in office. | Nevertheless, E3013_OUTGOV is coded based on voters for the | Workers' Party because more respondents reported having voted for | the PT, and because Dilma Rousseff was the elected leader in the | 2014 election. | ELECTION STUDY NOTES - CZECHIA (2021): E3013_OUTGOV | | For Czechia 2021, respondents are coded as having voted for the | incumbent if they voted for the Action of Dissatisfied Citizens | party (ANO 2011) or the Czech Social Democratic Party (CSSD) | which formed a minority government ahead of the 2021 election. | While the minority government was backed by the Communist Party | of Bohemia and Moravia (KSCM), this party was not formally part | of the cabinet and hence, is not included as an incumbent party. | ELECTION STUDY NOTES - FINLAND (2019): E3013_OUTGOV | | Finland went through a government crisis in 2017 when the Finns | Party split. The Finns Party was a member of the governing | coalition in Finland. In 2017, after Jussi Halla-aho was elected | as the Finns Party President, other coalition members (Center | Party and National Coalition Party) declared that they did not | want to continue cooperation with the Finns Party. As a result, | the Finns Party went into opposition. However, 20 MPs abandoned | the Finns Party and formed a new parliamentary group, which | continued to support the governing coalition and hold ministers | in Finland's government. This group became a new political party | in Finland - Blue Reform. | Thus, supporters of the Center Party, National Coalition Party | and Blue Reform are coded as voters of outgoing incumbents. | Voters of the Finns Party were coded as those who did not vote | for the outgoing incumbent government. | ELECTION STUDY NOTES - GREECE (2019): E3013_OUTGOV | | After the September 2015 Greek legislative election, the | Coalition of the Radical Left (Syriza) formed a coalition | government headed by Alexis Tsipras with the Independent | Greeks - National Patriotic Alliance (ANEL). However, ANEL | left the coalition in early 2019 after disagreements over the | Macedonian naming dispute. As ANEL further did not participate | in the 2019 legislative elections, only respondents voting for | Syriza are coded as incumbent voters in E3013_OUTGOV. | ELECTION STUDY NOTES - HONG KONG (2016): E3013_OUTGOV | | The Chief Executive (CE) in Hong Kong is the highest government | official, but they do not belong to any political party. Hence, | E3013_OUTGOV was coded as "9999996. NOT ASCERTAINED /INCUMBENT | CANDIDATE/PARTY DID NOT CONTEST." | ELECTION STUDY NOTES - ISRAEL (2020): E3013_OUTGOV | | The March 2020 election was the third general election in Israel | in the space of 12 months. Previous elections in April 2019 and | September 2019 resulted in a hung parliament, where no new | coalition government could be formed. Consequently, from April | 9, 2019, Israel was governed by a caretaker coalition led by | Benjamin Netanyahu as caretaker Prime Minister, comprising the | following parties: Likud, Kulanu, Shas, United Torah Judaism, | Jewish Home, and the New Right. The outgoing government variable | for Israel classifies this caretaker government as the incumbent | administration for the 2020 contest. | Respondents who are classified as "999992. OTHER CANDIDATE/PARTY | (NOT FURTHER SPECIFIED)" in variable E3013_LH_PL are coded as | "999996. NOT ASCERTAINED/INCUMBENT CANDIDATE/PARTY DID NOT | CONTEST" in E3013_OUTGOV. | ELECTION STUDY NOTES - ITALY (2018): E3013_OUTGOV | | In the 2018 lower house elections, voters could vote for a party | list only, a party list and a district candidate, or a district | candidate only. For those respondents reporting to have cast a | list vote and those who reported voting for both a party list | and a district candidate, E3013_OUTGOV was coded based on | E3013_LH_PL. For respondents who reported voting for a district | candidate only, E3013_OUTGOV was coded based on E3013_LH_DC. | Users are advised to consult ELECTION STUDY NOTES on E3013_LH_PL | and E3013_LH_DC for further details on the Italian electoral | system. | ELECTION STUDY NOTES - LATVIA (2018): E3013_OUTGOV | | After the 2014 Parliamentary elections in Latvia, a coalition was | formed by Unity, the Union of Greens and Farmers and the | National Alliance with Laimdota Straujuma from Unity as Prime | Minister. A year later, she resigned following increasing | tensions within the ruling coalition. The same coalition formed | a new government with Maris Kucinskis of the Union of Greens and | Farmers as the new Prime Minister. Even though it was a turbulent | term, the same coalition governed Latvia from 2014 to 2018, and | those who voted for one of these parties in the 2018 elections | are coded as voters of outgoing incumbents for the E3013_OUTGOV | variable. | ELECTION STUDY NOTES - MEXICO (2018): E3013_OUTGOV | | For Mexico 2018, respondents are coded as having voted for the | incumbent if they voted for Enrique Pena Nieto's party, the | Institutional Revolutionary Party (PRI), in the current | Presidential election. | Pena Nieto was elected as Mexican President to serve a six-year | term in the previous 2012 election. However, since all Mexican | Presidents are constitutionally limited to a single term, Pena | Nieto was not eligible for re-election. | For the 2018 Presidential election, PRI nominated Jose Antonio | Meade Kuribrena (LEADER C). | ELECTION STUDY NOTES - PERU (2021): E3013_OUTGOV | | For Peru 2021, respondents are coded as having voted for the | incumbent if they voted for Francisco Sagasti's party, the | Purple Party (PM), in the current Presidential election. | However, Francisco Sagasti was not elected President of Peru in | the 2016 elections. While there were many changes in the | presidency, Sagasti finished the 2016-2021 term from November | 16, 2020, to July 28, 2021, which was started by Pedro Pablo | Kuczynski of the Peruvians for Change party on July 28, 2016. | Nevertheless, users should be aware that only 12 respondents | voted for the Purple Party (PM) in the current Presidential | election, so the meaningfulness is limited. For more information | on the election, see the Election Summaries in Codebook Part 5. | ELECTION STUDY NOTES - ROMANIA (2016): E3013_OUTGOV | | In November 2015, Romanian Prime Minister Victor Ponta resigned | following protests sparked by a fire in a nightclub in Bucharest, | Romania, in which 64 people died. President Klaus Iohannis | appointed Dacias Ciolos as the new Prime Minister. Ciolos | proposed a technocratic cabinet, which was approved in the | Parliament, through votes from all major Romanian parties, | including the two biggest: Social Democrats (PSD) and | National Liberals (PNL). However, in all these parties, | including the two biggest, a number of legislators defied the | leadership to vote against the cabinet. | E3013_OUTGOV was coded as "9999996. NOT ASCERTAINED /INCUMBENT | CANDIDATE/PARTY DID NOT CONTEST." | ELECTION STUDY NOTES - SWITZERLAND (2019): E3013_OUTGOV | | The Federal Council of Switzerland functions as the collective | executive in Switzerland. Because the Federal President rotates | among its members from each of the parties on a fixed, annual | basis, no incumbent was coded. | ELECTION STUDY NOTES - THAILAND (2019): E3013_OUTGOV | | At the time of the election, Thailand's incumbent Prime Minister | was Prayut Chan-o-cha, leader of the State Power Party (PPRP). | As Commander-in-Chief of the Royal Thai Army, Prayut headed a | coup d'etat in May 2014. Since the outset of the resulting | junta government, Prayut acted as Prime Minister. As Prayut | was not a popularly elected leader at the time of the 2019 | election, E3013_OUTGOV is coded "999996. NOT ASCERTAINED / | INCUMBENT CANDIDATE/PARTY DID NOT CONTEST". --------------------------------------------------------------------------- E3013_VS_1 >>> VOTE SWITCHER BETWEEN CURRENT ELECTION AND PREVIOUS ELECTION --------------------------------------------------------------------------- Whether or not the respondent reports voting for the same party/coalition in the current and previous election. .................................................................. 0. DID NOT SWITCH (VOTED FOR SAME PARTY/COALITION IN CURRENT & PREVIOUS ELECTION) 1. SWITCHER (CHANGED VOTE IN CURRENT ELECTION FROM PREVIOUS ELECTION) 9. MISSING | CSES QUESTION CLASSIFICATION: DERIVATIVE VARIABLE (BASED ON CORE) | VARIABLE NOTES: E3013_VS_1 | | E3013_VS_1 ascertains whether or not the respondent reports | voting for the same party/coalition in the current and previous | election or whether the respondent reports voting for a different | party/ coalition in the current election from the previous | election. | E3013_VS_1 is constructed based on the respondent's reported | vote choice in the current and previous main election. | In polities where multiple elections took place simultaneously, | E3013_VS_1 reports the vote-switching behavior in the main | election. | | CSES classifies the main election based on the regime | (executive) type and the election in which the CSES survey has | been administered. For polities rated as parliamentary systems, | CSES classifies the main election as elections to the lower house | for most studies. It deviates for a few cases when elections to | the upper house constitutes the main election, usually due to the | respective CSES study focusing on the upper house contest. | For polities rated as Presidential systems, CSES conventionally | classifies the main election as the Presidential election. It | sometimes deviates when data for the Presidential election is | unavailable (e.g., when the CSES survey was administered in a | midterm election). For polities rated as mixed systems, CSES | has tended to classify the main election as elections to the | lower house. However, it sometimes deviates depending on data | availability. Users are advised to consult the table listed in | VARIABLE NOTES for E3013_OUTGOV specifying the main election for | each study in CSES for specific details. | | Respondents are classified as "0. DID NOT SWITCH" when they | expressed a vote choice for the same party/coalition in the | current and previous election. In instances where a coalition is | competing in the current or previous election, and the parties | that comprise that coalition are competing individually in the | previous/current election, respondents who report voting for | the coalition and/or one of the parties comprising the coalition | are classified as "0. DID NOT SWITCH." Details of these cases | are specified in ELECTION STUDY NOTES below. | | Respondents are classified as "1. SWITCHER" when their reported | vote in the current election differs from their reported vote | in the previous election. Further, respondents are classified as | "1. SWITCHER" when they report voting in one election (current | or previous) for a party/coalition that did not exist or | contest in the other (current or previous) election. | | Respondents are classified as "9. MISSING" when data about | their vote choice in the current and/or previous election is | unavailable, if they report that they don't know who they | voted for, or if they refused to answer the question. | Additionally, respondents who report voting for an independent | candidate or other parties without further specification are | classified as "9. MISSING." | In instances where current and previous vote choice refer to | different types of elections, e.g., a current main election is | Presidential but previous vote choice refers to the lower | house election only, these studies are set to "9. MISSING". | | Data are unavailable for MEXICO (2018) and TAIWAN (2016). | ELECTION STUDY NOTES - AUSTRIA (2017): E3013_VS_1 | | NUMERICAL CODE 040008: Communist Party of Austria and Platform | PLUS - Open List was a joint party list between Communist Party | of Austria (KPOE, NUMERICAL CODE: 040013) and an independent | political youth organization, the Young Greens, formed for the | current lower house election. | Respondents who reported voting for the KPOE in the previous | election, and for the joint list in the current election are | classified as "0. DID NOT SWITCH" for E3013_VS_1. | ELECTION STUDY NOTES - BRAZIL (2018): E3013_VS_1 | | In the current 2018 Presidential election, Social Liberal Party | (PSL, NUMERICAL CODE: 076001) formed an alliance with | Brazilian Labor Renewal Party (PRTB, NUMERICAL CODE: 076027). | Respondents who reported voting for the Brazilian Labor Renewal | Party in the previous election, and for the Social Liberal Party | in the current election are classified as "0. DID NOT SWITCH" for | E3013_VS_1. | ELECTION STUDY NOTES - CHILE (2017): E3013_VS_1 | | In the current 2017 Presidential election, Independent Democratic | Union (UDI, NUMERICAL CODE: 152002) formed a coalition with | National Renewal (RN, NUMERICAL CODE: 152001), in support of RN's | Presidential candidate Sebastian Pinera. | Respondents who reported voting for the Independent Democratic | Union in the previous election, and for National Renewal in the | current election are classified as "0. DID NOT SWITCH" for | E3013_VS_1. | | In the current 2017 Presidential election, Equality Party | (NUMERICAL CODE: 152012) and the Green Ecologist Party (NUMERICAL | CODE: 152013) formed an alliance "Broad Front" with Democratic | Revolution (RD, NUMERICAL CODE: 152006). | Respondents who reported voting for one of these parties in the | previous election, and for Democratic Revolution in the current | election are classified as "0. DID NOT SWITCH" for E3013_VS_1. | ELECTION STUDY NOTES - COSTA RICA (2018): E3013_VS_1 | | This variable is based on the vote choice variables of the | first round of the current and previous Presidential election | (E3013_PR_1 and E3015_PR_1). | ELECTION STUDY NOTES - CZECHIA (2021): E3013_VS_1 | | In the current 2021 parliamentary election, Civic Democratic | Party (ODS, NUMERICAL CODE: 203101) formed an alliance with TOP | 09 (NUMERICAL CODE: 203196) and Christian and Democratic Union- | Czechoslovak People's Party (KDU-CSL, NUMERICAL CODE: 203197). | Respondents who reported voting for TOP 09 or KDU-CSL in the | previous election, and for the SPOLU alliance in the current | election are classified as "0. DID NOT SWITCH" for E3013_VS_1. | In the current 2021 parliamentary election, The Czech Pirate | Party (Pi, NUMERICAL CODE: 203103) formed an alliance with Mayors | and Independents (STAN, NUMERICAL CODE: 203198). Respondents who | reported voting for STAN in the previous election, and for the | PirStan alliance in the current election are classified as | "0. DID NOT SWITCH" for E3013_VS_1. | In the current 2021 parliamentary election, Tricolour Citizen's | Movement (Trikolora, NUMERICAL CODE: 203108) formed an alliance | with Party of Free Citizens (Svobodni, NUMERICAL CODE: 203199). | Respondents who reported voting for Svobodni in the previous | election, and for the Trikolora-Svobodni-Soukromnici alliance in | the current election are classified as "0. DID NOT SWITCH" for | E3013_VS_1. | ELECTION STUDY NOTES - FRANCE (2017): E3013_VS_1 | | In the current 2017 Presidential election, Democratic Movement | (MoDem, NUMERICAL CODE: 250012) supported The Republic Onwards' | candidate, Emmanuel Macron (NUMERICAL CODE: 250001). | Respondents who reported voting for the Democratic Movement in | the previous election, and for The Republic Onwards in the | current election are classified as "0. DID NOT SWITCH" for | E3013_VS_1. | | Jean-Luc Melenchon, the former head of the Left Party (PG) | competed for the newly founded Indomitable France (FI, NUMERICAL | CODE: 250004) in the current 2017 Presidential election. | Respondents who reported voting for Indomitable France in the | current election and for Left Front (FG, NUMERICAL CODE: 250015), | Melenchon's preceding platform, in the previous election are | classified as "0. DID NOT SWITCH" for E3013_VS_1. | | After withdrawing their own candidate from the current 2017 | Presidential election, Europe Ecology - The Greens (EELV, | NUMERICAL CODE: 250014) supported Benoit Hamon from the Socialist | Party (PS, NUMERICAL CODE: 250005). | Respondents who reported voting for the Greens in the previous | election, and for the Socialist Party in the current election | are classified as "0. DID NOT SWITCH" for E3013_VS_1. | ELECTION STUDY NOTES - GREECE (2015): E3013_VS_1 | | Democratic Coalition (PASOK-DIMAR, NUMERICAL CODE: 300004) was an | electoral coalition that formed for the current 2015 lower house | election. This coalition was comprised of the following parties: | Panhellenic Socialist Movement (PASOK, NUMERICAL CODE: 300016) | and Democratic Left (DIMAR, NUMERICAL CODE: 300017). | Respondents who reported voting for one of these parties in the | previous election, and for the Democratic Coalition in the | current election are classified as "0. DID NOT SWITCH" for | E3013_VS_1. | ELECTION STUDY NOTES - GREECE (2019): E3013_VS_1 | | Democratic Coalition (DISI, NUMERICAL CODE: 300114) was an | electoral alliance formed for the previous lower house election. | This coalition was composed of the Panhellenic Socialist Movement | (PASOK) and the Democratic Left (DIMAR). | Together with other smaller parties, PASOK and DIMAR merged into | Movement for Change (KINAL, NUMERICAL CODE: 300103) in 2018. | Respondents who reported voting for the Democratic Coalition in | the previous election, and for KINAL in the current election are | classified as "0. DID NOT SWITCH" for E3013_VS_1. | However, researchers are advised that DIMAR left KINAL in early | 2019, affiliating to Coalition of the Radical Left (Syriza, | NUMERICAL CODE: 300103). | ELECTION STUDY NOTES - HONG KONG (2016): E3013_VS_1 | | People Power - League of Social Democrats (PP - LSD, NUMERICAL | CODE: 344006) was a joint list by People Power (NUMERICAL CODE: | 344007) and League of Social Democrats (LSD, NUMERICAL CODE: | 344008) for the current 2016 election. | Respondents who reported voting for one of these parties in the | previous election, and for the joint list in the current election | are classified as "0. DID NOT SWITCH" for E3013_VS_1. | ELECTION STUDY NOTES - HUNGARY (2018): E3013_VS_1 | | Unity (NUMERICAL CODE: 348010) was an electoral coalition that | formed for the previous lower house election. This coalition was | composed of the following parties: Hungarian Socialist Party | (MSZP) - Dialogue for Hungary (NUMERICAL CODE: 348003), | Democratic Coalition (DK, NUMERICAL CODE: 348005) and the | Hungarian Liberal Party (MLP). | Respondents who reported voting for one of these parties in the | current election, and for Unity in the previous election are | classified as "0. DID NOT SWITCH" for E3013_VS_1. | ELECTION STUDY NOTES - ISRAEL (2020): E3013_VS_1 | | Labor-Gesher-Meretz (NUMERICAL CODE: 376006) was a joint | electoral list formed to run in the 2020 Israeli legislative | election. The list was composed of three parties: The Israeli | Labor Party, Gesher and Meretz. Respondents who reported voting | for Labor-Gesher (NUMERICAL CODE: 376010) or Democratic Union | (NUMERICAL CODE: 376011) in the previous election, and for the | electoral list in the current election are classified as "0. DID | NOT SWITCH" for E3013_VS_1 because Democratic Union (NUMERICAL | CODE: 376011) included party Meretz in their electoral alliance | in 2019 that was part of the electoral list Labor-Gesher-Meretz | in the 2020 election. | ELECTION STUDY NOTES - ITALY (2018): E3013_VS_1 | | In the 2018 Italian lower house elections, voters could vote for | a party list only, a party list and a district candidate, or a | district candidate only. However, in the previous 2013 election, | Italy used a list vote system only, such that there is no data | on district candidate vote for the previous election. Therefore, | E3013_VS_1 is based on party-list votes only for Italy (2018). | | Us with Italy - Christian Democratic Union (NcI-UdC, NUMERICAL | CODE: 380008) was an electoral alliance for the current 2018 | lower house election formed between Us with Italy (NcI) and Union | of the Centre (UdC, NUMERICAL CODE: 380017). | Respondents who reported voting for one of these parties in the | previous election, and for Us with Italy - Christian Democratic | Union in the current election are classified as "0. DID NOT | SWITCH" for E3013_VS_1. | | Left Ecology Freedom (SEL, NUMERICAL CODE: 380019) merged into | Italian Left (SI) before the current 2018 lower house election, | a member of the joint list Free and Equal (LeU, NUMERICAL CODE: | 380006). | Respondents who reported voting for Left Ecology Freedom in the | previous election, and for Free and Equal in the current election | are classified as "0. DID NOT SWITCH" for E3013_VS_1. | ELECTION STUDY NOTES - LITHUANIA (2016): E3013_VS_1 | | Before the current 2016 lower house election, Liberal and Centre | Union (LiCS, NUMERICAL CODE: 440015) and Political Party "Yes" | (NUMERICAL CODE: 440016) merged to form Lithuanian Freedom Union | (Liberals) (LLS, NUMERICAL CODE: 440009). | Respondents who reported voting for LiCS or "Yes" in the previous | election and for the Lithuanian Freedom Union in the current | election are classified as "0. DID NOT SWITCH" for E3013_VS_1. | | Coalition of Anti-Corruption and Poverty (JL-LTS, NUMERICAL CODE: | 440013) was an electoral alliance formed by Young Lithuania (JL, | NUMERICAL CODE: 440018) and the Lithuanian Nationalist and | Republican Union (LTS). | Respondents who reported voting for one of these parties in the | previous election, and for the Coalition of Anti-Corruption and | Poverty in the current election are classified as "0. DID NOT | SWITCH" for E3013_VS_1. | ELECTION STUDY NOTES - LITHUANIA (2020): E3013_VS_1 | | Before the current 2020 lower house election, Order and Justice | (TT, NUMERICAL CODE: 440120) and Lithuanian Freedom Union | (Liberals, LLS, NUMERICAL CODE: 440121) merged to form Freedom | and Justice (LT, NUMERICAL CODE: 440111). | Respondents who reported voting for TT or LLS in the previous | election and for Freedom and Justice in the current election are | classified as "0. DID NOT SWITCH" for E3013_VS_1. | | Anti-Corruption Coalition (LCP-LPP, NUMERICAL CODE: 440119) was | an electoral alliance formed by Lithuanian Centre Party - | Nationalists (CPT, NUMERICAL CODE: 440109) and the Lithuanian | Pensioners' Party (LPP) for the previous 2016 Lithuanian | parliamentary election. | Respondents who reported voting for one of these parties in the | current election, and for the Anti-Corruption Coalition in the | previous election are classified as "0. DID NOT SWITCH" for | E3013_VS_1. | ELECTION STUDY NOTES - MONTENEGRO (2016): E3013_VS_1 | | Key Coalition (NUMERICAL CODE: 499003) was an electoral coalition | participating in the current 2016 lower house election. This | coalition consisted of the following parties: Democratic Alliance | (DEMOS, NUMERICAL CODE: 499018), Socialist Peoples Party of | Montenegro (SNP, NUMERICAL CODE: 499019) and United Reform Action | (URA, NUMERICAL CODE: 499020). | Respondents who reported voting for one of these parties in the | previous election, and for the Key Coalition in the current | election are classified as "0. DID NOT SWITCH" for E3013_VS_1. | | Albanians Decisively (FORCA-DUA-AA, NUMERICAL CODE: 499008) was | an electoral coalition that formed for the current lower house | election. This coalition was composed of the following member | parties: New Democratic Power - Forca (NUMERICAL CODE: 499022), | Democratic Union of Albanians (DUA, NUMERICAL CODE: 499023), and | Albanian Alternative (AA, NUMERICAL CODE: 499021). | Respondents who reported voting for one of these parties in the | previous election, and for Albanians Decisively in the current | election are classified as "0. DID NOT SWITCH" for E3013_VS_1. | | Coalition "For a European Montenegro" (NUMERICAL CODE: 499026) | was an electoral coalition formed for the previous lower house | election. This coalition was composed of the following parties: | Democratic Party of Socialists of Montenegro (DPS, NUMERICAL | CODE: 499001), Social Democratic Party of Montenegro (SDP, | NUMERICAL CODE: 499005) and the Liberal Party (LP). | Respondents who reported voting for one of these parties in the | current election, and for "For a European Montenegro" in the | previous election are classified as "0. DID NOT SWITCH" for | E3013_VS_1. | ELECTION STUDY NOTES - POLAND (2019): E3013_VS_1 | | In the current 2019 parliamentary election, several parties | formed alliances which were taken into account when coding | E3013_VS_1. | | Civic Platform (PO, NUMERICAL CODE: 616002) formed an alliance | with Modern (Nowo, NUMERICAL CODE: 616008). Respondents who | reported voting for Modern (Nowo) in the previous election, and | for Civic Platform (PO) in the current election are classified as | "0. DID NOT SWITCH" for E3013_VS_1. | The Polish People's Party (PSL, NUMERICAL CODE: 616003) formed an | alliance with Kukiz'15 (NUMERICAL CODE: 616005). Respondents who | reported voting for Kukiz'15 in the previous election, and for | the Polish People's Party in the current election are classified | as "0. DID NOT SWITCH". | The Democratic Left Alliance (SLD, NUMERICAL CODE: 616004) formed | an alliance with Left Together (NUMERICAL CODE: 616006) and | Spring (Wiosna, NUMERICAL CODE: 616007). Respondents who reported | voting for either Left Together or Spring (Wiosna) in the | previous election, and for the Democratic Left Alliance (SLD) in | the current election are classified as "0. DID NOT SWITCH". | The Confederation Liberty and Independence Party (Konfederacia, | NUMERICAL CODE: 616010) formed an alliance with New Hope (KORWiN, | NUMERICAL CODE: 616009). Respondents who reported voting for New | Hope (KORWiN) in the previous election, and for the Confederation | Liberty and Independence Party in the current election are | classified as "0. DID NOT SWITCH". | ELECTION STUDY NOTES - ROMANIA (2016): E3013_VS_1 | | Social Liberal Union (NUMERICAL CODE: 642017) was an electoral | alliance of the Social Democratic Party (PSD, NUMERICAL CODE: | 642001), the National Liberal Party (PNL, NUMERICAL CODE: | 642002), the National Union for Romania's Progress Party (UNPR, | NUMERICAL CODE: 642014) and the Conservative Party (PC). This | coalition contested in the Romanian 2012 elections (previous | elections). | Respondents who reported voting for one of these parties in the | current election, and for the Social Liberal Union in the | previous election are classified as "0. DID NOT SWITCH" for | E3013_VS_1. | Users are advised that Romania changed its electoral system. | Whilst previous vote choice was based on the district candidate | vote, current vote choice is based on the party list vote. | ELECTION STUDY NOTES - SLOVAKIA (2020): E3013_VS_1 | | Hungarian Community Togetherness (NUMERICAL CODE: 703009) was an | electoral coalition participating in the current 2020 lower house | election. This coalition consisted of the following parties: | Party of the Hungarian Community (SMK-MKP, NUMERICAL CODE: | 703026), Hungarian Forum (MF), and Osszefogas-Spolupatricnost. | Respondents who reported voting for SMK-MKP in the previous | election, and for Hungarian Community Togetherness in the | current election are classified as "0. DID NOT SWITCH" for | E3013_VS_1. | ELECTION STUDY NOTES - SOUTH KOREA (2016): E3013_VS_1 | | Before the current 2016 lower house election, Democratic United | Party (DUP, NUMERICAL CODE: 410005) and the New Political Vision | Party (NPVP) merged to form the Democratic Party of Korea (DP, | NUMERICAL CODE: 410002). | Respondents who reported voting for the DUP in the previous | election and for the DP in the current election are classified | as "0. DID NOT SWITCH" for E3013_VS_1. --------------------------------------------------------------------------- E3013_LR_CSES >>> CURRENT MAIN ELECTION - VOTE FOR LEFTIST/CENTER/RIGHTIST - CSES --------------------------------------------------------------------------- Whether or not the respondent reports voting for a leftist/center/ rightist party/candidate of the party, based on CSES Collaborators experts' judgment of parties' ideology. .................................................................. 1. VOTED FOR LEFTIST PARTY/CANDIDATE 2. VOTED FOR CENTER PARTY/CANDIDATE 3. VOTED FOR RIGHTIST PARTY/CANDIDATE 9. MISSING | CSES QUESTION CLASSIFICATION: DERIVATIVE VARIABLE (BASED ON CORE) | VARIABLE NOTES: E3013_LR_CSES | | E3013_LR_CSES details whether or not the respondent reports | voting for a leftist/center/rightist party/candidate of the | party. The classification is based on CSES Collaborators experts' | judgment of parties' ideology and the respondents' reported vote | choice. | | E3013_LR_CSES is available for voters who reported voting for a | party where expert judgments are available (i.e., for parties | receiving an alphabetical classification by CSES). For more | details on which parties/coalitions receive alphabetical | classification, see "CSES MODULE 5 CODING OF PARTIES/COALITIONS | & LEADERS" in Codebook Part 3. | | E3013_LR_CSES differentiates voters based on expert judgments | of the CSES Collaborators on the left-right ideology scale. | Collaborators assign parties scores on an 11-point scale ranging | from "0. LEFT" to "10. RIGHT" for all parties assigned an | alphabetical code by CSES. The expert judgment data by party | is available in variable E5018_. | | The coding of E3013_LR_CSES is based on E3100_LR_CSES. | For E3100_LR_CSES, CSES linked the CSES Collaborator expert | judgment with the reported vote choice of the respondent in the | main election. A respondent who reports voting for a party/ | candidate of PARTY A is assigned the value the CSES Collaborator | gave to PARTY A in the said election on the left-right scale | (and so on for PARTY B, PARTY C etc...). CSES reports these | values in variable E3100_LR_CSES. | | These scores provided in E3100_LR_CSES have then been | re-classified for E3013_LR_CSES to establish whether a | respondent voted for a leftist, center or rightist party/ | candidate. Scores assigned by Collaborators are recoded into a | trichotomy as follows: | | E3013_LR_CSES CSES Collaborators Rating |----------------------------------------------------------------- | 01. 0 - 3 | 02. 4 - 6 | 03. 6 - 10 | | In polities where multiple elections took place simultaneously, | this variable reports the vote choice in the main election. | | CSES classifies the main election based on the regime | (executive) type and the election in which the CSES survey has | been administered. For polities rated as parliamentary systems, | CSES classifies the main election as elections to the lower house | for most studies. It deviates for a few cases when elections to | the upper house constitutes the main election, usually due to the | respective CSES study focusing on the upper house contest. | For polities rated as Presidential systems, CSES conventionally | classifies the main election as the Presidential election. It | sometimes deviates when data for the Presidential election is | unavailable (e.g., when the CSES survey was administered in a | midterm election). For polities rated as mixed systems, CSES | has tended to classify the main election as elections to the | lower house. However, it sometimes deviates depending on data | availability. Users are advised to consult the table listed in | VARIABLE NOTES for E3013_OUTGOV specifying the main election for | each study in CSES for specific details. | | Data are unavailable primarily because Collaborator expert | judgments of parties were not provided for certain election | studies. --------------------------------------------------------------------------- E3013_LR_MARPOR >>> CURRENT MAIN ELECTION - VOTE FOR LEFTIST/RIGHTIST (RILE) - MARPOR/CMP --------------------------------------------------------------------------- Whether or not the respondent reports voting for a leftist or rightist party or candidate of the party, based on MARPOR's "RILE" index value. .................................................................. 0. VOTED FOR LEFTIST PARTY/CANDIDATE 1. VOTED FOR RIGHTIST PARTY/CANDIDATE 9. MISSING | CSES QUESTION CLASSIFICATION: DERIVATIVE VARIABLE (BASED ON CORE) | VARIABLE NOTES: E3013_LR_MARPOR | | E3013_LR_MARPOR details whether or not the respondent reports | voting for a leftist or rightist party or candidate of the party. | The classification is based on MARPOR's "RILE" index value | assigned to the party based on the manifesto the party contested | the election on and the respondents' reported vote choice. | | E3013_LR_MARPOR is available for voters who reported voting for a | party receiving an alphabetical classification by CSES, and for | which MARPOR "rile" index data is available. For more details on | which parties/coalitions receive alphabetical classification, | see "CSES MODULE 5 CODING OF PARTIES/COALITIONS & LEADERS" in | Codebook Part 3. | | E3013_LR_MARPOR differentiates voters who voted for a leftist/ | rightist party/candidate of a party based on the Manifesto | Research on Political Representation (MARPOR/CMP) data. | E3013_LR_MARPOR is based on the "RILE" index. The index was | developed by Laver and Budge (1992). It takes 24 categories (12 | are defined as right-wing and 12 as left-wing) and subtracts the | sum of all right-wing items from the sum of all left-wing items. | The RILE index ranges from -100 (if a party only mentions left- | wing issues in its program) and +100 (if a party only mentions | right-wing issues in its program). However, these are the | theoretical maximum and minimum values which are empirically | rare. | | More information about MARPOR/CMP data and RILE index can | be found at https://manifestoproject.wzb.eu/ | (Date accessed: May 03, 2023). | | For E3100_LR_MARPOR, CSES linked the MARPOR/CMP data with the | reported vote choice of the respondent in the main election. | A respondent who reports voting for a party/candidate of PARTY A | is assigned the value the MARPOR/CMP RILE index gives to PARTY A | in the said election (and so on for PARTY B, PARTY C etc...). | CSES reports these values in variable E3100_LR_MARPOR. | | These scores provided in E3100_LR_MARPOR have then been | re-classified for E3013_LR_MARPOR to establish whether a | respondent voted for a leftist/rightist party/candidate. Scores | assigned by Collaborators are recoded into a dichotomy as | follows: | | E3013_LR_MARPOR MARPOR RILE index |----------------------------------------------------------------- | 00. -100 - -0.01 | 01. 0.01 - 100.0 | | When a party scores 0.00 on the RILE index, that usually means | that there is not enough data on the dimensions available to | construct a reliable RILE estimate. These cases have been set to | "9. MISSING". | | In polities where multiple elections took place simultaneously, | this variable reports the vote choice in the main election. | | CSES classifies the main election based on the regime | (executive) type and the election in which the CSES survey has | been administered. For polities rated as parliamentary systems, | CSES classifies the main election as elections to the lower house | for most studies. It deviates for a few cases when elections to | the upper house constitutes the main election, usually due to the | respective CSES study focusing on the upper house contest. | For polities rated as Presidential systems, CSES conventionally | classifies the main election as the Presidential election. It | sometimes deviates when data for the Presidential election is | unavailable (e.g., when the CSES survey was administered in a | midterm election). For polities rated as mixed systems, CSES | has tended to classify the main election as elections to the | lower house. However, it sometimes deviates depending on data | availability. Users are advised to consult the table listed in | VARIABLE NOTES for E3013_OUTGOV specifying the main election for | each study in CSES for specific details. | | CSES and MARPOR/CMP have different scopes of parties/coalitions | in elections and thus corresponding values assigned to | parties/coalitions by CSES Collaborators may be unavailable in | MARPOR/CMP and vice versa. | In this variable, the L-R classifications assigned by MARPOR/CMP | (originally available in E3100_MARPOR) are transformed into a | dichotomous variable. | Meanwhile, the L-R classifications assigned by CSES Collaborators | (available in E3013_LR_CSES and originally in E3100_LR_CSES and | E5018_ respectively) are transformed into a three-category | variable. Consequently, users are advised that this results in | some parties/coalitions falling into different categorizations | on E3013_LR_CSES and E3013_LR_MARPOR. | | Users are advised that CSES and MARPOR/CMP sometimes classify | coalitions differently in elections and across polities. For | example, CSES sometimes has data solely on coalitions and not | the parties comprising the alliance, while MARPOR/CMP may have | data concerning the individual parties in the coalition, or | vice versa. Consequently, some parties may have multiple | identifiers within the MARPOR/CMP dataset across time. A non | comprehensive list of these deviations are noted in Part 3 | of the CSES Module Codebook in ELECTION STUDY NOTES. | | In certain elections, there can be little intra-study variation | on this variable as all the main parties (i.e., those receiving | most votes) are classified in one category (e.g., they are | all designated by MARPOR/CMP to have minus scores, and | consequently, all are deemed to be on the left of the ideological | spectrum). In CSES MODULE 5, this occurs for the following | studies: | - Australia (2019) | - Iceland (2017) | - Japan (2017) | - Lithuania (2020) | - South Korea (2016) | - Turkey (2018) | Intra-study variation can be obtained by consulting variable | E3100_LR_MARPOR. | | Data are unavailable primarily because some polities which are | in the CSES are not represented in the MARPOR/CMP dataset. | Data are unavailable for AUSTRALIA (2019), BRAZIL (2018), CANADA | (2019), CHILE (2017), COSTA RICA (2018), FRANCE (2017), HONG | KONG (2016), ISRAEL (2020), SLOVAKIA (2020), TAIWAN (2016, 2020), | THAILAND (2019), TUNISIA (2019) and URUGUAY (2019). --------------------------------------------------------------------------- E3013_IF_CSES >>> CURRENT MAIN ELECTION - VOTE CHOICE BY IDEOLOGICAL FAMILY CLASSIFICATION - CSES --------------------------------------------------------------------------- Respondents' reported vote choice by the ideological family of the party/candidate of the party, based on CSES Collaborators experts' classifications. .................................................................. 01. VOTED FOR A SOCIALIST PARTY 02. VOTED FOR AN ECOLOGY PARTY 03. VOTED FOR A SOCIAL DEMOCRATIC PARTY 04. VOTED FOR A LIBERAL PARTY 05. VOTED FOR A CHRISTIAN DEMOCRAT PARTY 06. VOTED FOR A CONSERVATIVE PARTY 07. VOTED FOR A NATIONAL PARTY 10. VOTED FOR A PARTY OF OTHER CLASSIFICATION 97. NOT APPLICABLE 98. NO IDEOLOGICAL FAMILY MENTIONED 99. MISSING | CSES QUESTION CLASSIFICATION: DERIVATIVE VARIABLE (BASED ON CORE) | VARIABLE NOTES: E3013_IF_CSES | | E3013_IF_CSES details respondents' reported vote choice by the | ideological family of the party/candidate of the party. | The classification is based on CSES Collaborators experts' | judgments of the party's ideological family and the respondents' | reported vote choice. | | E3013_IF_CSES is available for voters who reported voting for a | party where expert judgments are available (i.e., for parties | receiving an alphabetical classification by CSES). For more | details on which parties/coalitions receive alphabetical | classification see "CSES MODULE 5 CODING OF PARTIES/COALITIONS | & LEADERS" in Codebook Part 3. | | E3013_IF_CSES differentiates voters based on the expert judgment | of the CSES Collaborators on the ideological family | classification. The expert judgment data by party is available | in variable E5017_. | | The coding of E3013_IF_CSES is based on E3100_IF_CSES. | For E3100_IF_CSES, CSES linked the CSES Collaborator expert | judgment with the reported vote choice of the respondent in the | main election. A respondent who reports voting for a party/ | candidate of PARTY A is assigned the value the CSES Collaborator | gave to PARTY A in the said election on the ideological family | classification (and so on for PARTY B, PARTY C etc...). | CSES reports these values in variable E3100_IF_CSES. | | These classifications provided in E3100_IF_CSES have then been | re-classified for E3013_IF_CSES to establish an ideological | family a respondent voted for. Scores assigned by Collaborators | are recoded as follows: | | E3013_IF_CSES CSES Collaborators score |----------------------------------------------------------------- | 01. Socialist parties | 02. Ecology parties | 03. Social Democratic parties | 04. Left Liberal parties | Liberal parties | Right Liberal parties | 05. Christian Democratic parties | 06. Conservative parties | 07. National parties | 10. Communist parties | Agrarian parties | Ethnic parties | Regional parties | Independent parties | Other | | In polities where multiple elections took place simultaneously, | E3013_IF_CSES reports the vote choice in the main election. | | CSES classifies the main election based on the regime | (executive) type and the election in which the CSES survey has | been administered. For polities rated as parliamentary systems, | CSES classifies the main election as elections to the lower house | for most studies. It deviates for a few cases when elections to | the upper house constitutes the main election, usually due to the | respective CSES study focusing on the upper house contest. | For polities rated as Presidential systems, CSES conventionally | classifies the main election as the Presidential election. It | sometimes deviates when data for the Presidential election is | unavailable (e.g., when the CSES survey was administered in a | midterm election). For polities rated as mixed systems, CSES | has tended to classify the main election as elections to the | lower house. However, it sometimes deviates depending on data | availability. Users are advised to consult the table listed in | VARIABLE NOTES for E3013_OUTGOV specifying the main election for | each study in CSES for specific details. | | Data are unavailable primarily because Collaborator expert | judgments of parties were not provided for certain election | studies. --------------------------------------------------------------------------- E3014_PR_1 >>> Q13a. PREVIOUS PRESIDENTIAL ELECTION: DID RESPONDENT CAST A BALLOT - 1ST ROUND --------------------------------------------------------------------------- Whether or not the respondent cast a ballot in the first round of the PREVIOUS Presidential elections. .................................................................. 0. RESPONDENT DID NOT CAST A BALLOT 1. RESPONDENT CAST A BALLOT 93. VOLUNTEERED: RESPONDENT NOT REGISTERED ON ELECTORAL LISTS / NOT ELIGIBLE [IF APPLICABLE] 95. NOT APPLICABLE: NO ROLE OF PRESIDENT 96. NOT APPLICABLE: NO PRESIDENTIAL ELECTIONS 97. VOLUNTEERED: REFUSED 98. VOLUNTEERED: DON'T KNOW 99. MISSING | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3014_PR_1 | | E3014_PR_1 ascertains whether or not the respondent cast a ballot | in the first round of the PREVIOUS Presidential elections, | regardless of whether or not it was valid. | | +++ TABLE: PREVIOUS PRESIDENTIAL ELECTION (1ST ROUND) | AND THE YEAR IN WHICH IT WAS HELD | | Presidential | POLITY (ELEC YEAR) Election | ----------------------------------------------------------- | BRAZIL (2018) 2014 | CHILE (2017) 2013 | COSTA RICA (2018) 2014 | EL SALVADOR (2019) 2014 | FRANCE (2017) 2012 | MEXICO (2018) 2012 | PERU (2021) 2016 | SOUTH KOREA (2016) 2012 | TAIWAN (2020) 2016 | TURKEY (2018) 2014 | UNITED STATES (2016) 2012 | UNITED STATES (2020) 2016 | URUGUAY (2019) 2014 | ----------------------------------------------------------- | | Data are unavailable for TAIWAN (2016) and TUNISIA (2019). | ELECTION STUDY NOTES - BRAZIL (2018): E3014_PR_1 | | The question if respondents voted in the "first round" of the | previous election did not differentiate between the | Presidential, lower house and upper house elections. Since | voting is compulsory, it can be assumed that most persons who | answered "yes" voted in all of the elections, and those who | answered "no" did not vote in any of the elections, which took | place simultaneously. Furthermore, there were different kinds of | "no" answers in the original dataset which showed why | respondents did not vote. These values were recoded as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 0. No, more than 70 years old (voluntary) | No, 16-17 years old (voluntary) | No, showed justification in 1st round | Neither voted nor showed justification at first | round | No, didn't have the necessary documentation | 1. Yes, voted | ELECTION STUDY NOTES - EL SALVADOR (2019): E3014_PR_1 | | Respondents were not given the answer option "not eligible to | vote." As a consequence, respondents who were ineligible to vote | in the 2014 Presidential Election were coded as "didn't vote" | in the original study and 0. RESPONDENT DID NOT CAST A BALLOT | in CSES, respectively. 223 respondents born after 1996 reported | having cast a vote in 2014, even though they were below voting | age. Data remain unchanged. | ELECTION STUDY NOTES - PERU (2021): E3014_PR_1 | | Turnout for the previous lower house (E3014_LH) and the first | round of the Presidential (E3014_PR_1) elections was derived | from a single question asking respondents whether they had cast | a ballot in the previous general elections in 2016. | ELECTION STUDY NOTES - UNITED STATES (2016): E3014_PR_1 | | Respondents were not given the answer option "not eligible to | vote." As a consequence, respondents who were ineligible to vote | in the 2012 Presidential Election were coded as "didn't vote" | in the original study and 0. RESPONDENT DID NOT CAST A BALLOT | in CSES, respectively. | ELECTION STUDY NOTES - UNITED STATES (2020): E3014_PR_1 | | Respondents were not given the answer option "not eligible to | vote." Therefore, respondents who were ineligible to vote | in the 2016 Presidential Election could report turnout. | Six respondents born after 1998 reported having cast a vote | in 2016, even though they were below voting age. Data remain | unchanged. --------------------------------------------------------------------------- E3014_PR_2 >>> Q13a. PREVIOUS PRESIDENTIAL ELECTION: DID RESPONDENT CAST A BALLOT - 2ND ROUND --------------------------------------------------------------------------- Whether or not the respondent cast a ballot in the second round of the PREVIOUS Presidential elections. .................................................................. 0. RESPONDENT DID NOT CAST A BALLOT 1. RESPONDENT CAST A BALLOT 93. VOLUNTEERED: RESPONDENT NOT REGISTERED ON ELECTORAL LISTS / NOT ELIGIBLE [IF APPLICABLE] 95. NOT APPLICABLE: NO ROLE OF PRESIDENT 96. NOT APPLICABLE: NO PRESIDENTIAL ELECTIONS / NO SECOND ROUND 97. VOLUNTEERED: REFUSED 98. VOLUNTEERED: DON'T KNOW 99. MISSING | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3014_PR_2 | | E3014_PR_2 ascertains whether or not the respondent cast a ballot | in the second round of the PREVIOUS Presidential elections, | regardless of whether or not it was valid. | | Data are unavailable for COSTA RICA (2018), EL SALVADOR (2019), | MEXICO (2018), PERU (2021) and TUNISIA (2019). | ELECTION STUDY NOTES - BRAZIL (2018): E3014_PR_2 | | The Brazilian study differentiates between various kinds of "no" | answers in the original dataset, showing why respondents did not | vote. These values were recoded as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 0. No, more than 70 years old (voluntary) | No, 16-17 years old (voluntary) | No, showed justification in 1st round | Neither voted nor showed justification at first | round | No, didn't have the necessary documentation | 1. Yes, voted --------------------------------------------------------------------------- E3014_LH >>> Q13a. PREVIOUS LOWER HOUSE ELECTION: DID RESPONDENT CAST A BALLOT --------------------------------------------------------------------------- Whether or not the respondent cast a ballot in the PREVIOUS lower house elections. .................................................................. 0. RESPONDENT DID NOT CAST A BALLOT 1. RESPONDENT CAST A BALLOT 93. VOLUNTEERED: RESPONDENT NOT REGISTERED ON ELECTORAL LISTS / NOT ELIGIBLE [IF APPLICABLE] 96. NOT APPLICABLE: NO LOWER HOUSE ELECTION 97. VOLUNTEERED: REFUSED 98. VOLUNTEERED: DON'T KNOW 99. MISSING | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3014_LH | | E3014_LH ascertains whether or not the respondent cast a ballot | in the PREVIOUS lower house elections, regardless of whether or | not it was valid. | | +++ TABLE: PREVIOUS LOWER HOUSE ELECTION AND THE YEAR IN | WHICH IT WAS HELD | | Lower House | POLITY (ELEC YEAR) Election | ----------------------------------------------------------- | ALBANIA (2017) 2013 | AUSTRALIA (2019) 2016 | AUSTRIA (2017) 2013 | BELGIUM-FLANDERS (2019) 2014 | BELGIUM-WALLONIA (2019) 2014 | BRAZIL (2018) 2014 | CANADA (2019) 2015 | CZECHIA (2017) 2013 | CZECHIA (2021) 2017 | DENMARK (2019) 2015 | EL SALVADOR (2019) 2018 | FINLAND (2019) 2015 | GERMANY (2017) 2013 | GERMANY (2021) 2017 | GREAT BRITAIN (2017) 2015 | GREAT BRITAIN (2019) 2017 | GREECE (2015) 2015 | GREECE (2019) 2015 | HONG KONG (2016) 2012 | HUNGARY (2018) 2014 | ICELAND (2016) 2013 | ICELAND (2017) 2016 | INDIA (2019) 2014 | IRELAND (2016) 2011 | ISRAEL (2020) 2019 | ITALY (2018) 2013 | JAPAN (2017) 2014 | LATVIA (2018) 2014 | LITHUANIA (2016) 2012 | LITHUANIA (2020) 2016 | MONTENEGRO (2016) 2012 | NETHERLANDS (2017) 2012 | NETHERLANDS (2021) 2017 | NEW ZEALAND (2017) 2014 | NEW ZEALAND (2020) 2017 | NORWAY (2017) 2013 | PERU (2021) 2016 | POLAND (2019) 2015 | PORTUGAL (2019) 2015 | ROMANIA (2016) 2012 | SLOVAKIA (2020) 2016 | SOUTH KOREA (2016) 2012 | SWEDEN (2018) 2014 | SWITZERLAND (2019) 2015 | TAIWAN (2016) 2012 | TAIWAN (2020) 2016 | THAILAND (2019) 2011 | TUNISIA (2019) 2014 | TURKEY (2018) 2015 | URUGUAY (2019) 2014 | ----------------------------------------------------------- | | Data are unavailable for CHILE (2017), COSTA RICA (2018), | FRANCE (2017), MEXICO (2018) and UNITED STATES (2016 & 2020). | ELECTION STUDY NOTES - BRAZIL (2018): E3014_LH | | The question if respondents voted in the "first round" of the | previous election did not differentiate between the | Presidential, lower house and upper house elections. Since | voting is compulsory, it can be assumed that most persons who | answered "yes" voted in all of the elections, and those who | answered "no" did not vote in any of the elections, which took | place simultaneously. Furthermore, there were different kinds of | "no" answers in the original dataset which showed why | respondents did not vote. These values were recoded as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 0. No, more than 70 years old (voluntary) | No, 16-17 years old (voluntary) | No, showed justification in 1st round | Neither voted nor showed justification at first | round | No, didn't have the necessary documentation | 1. Yes, voted | ELECTION STUDY NOTES - CANADA (2019): E3014_LH | | This variable is from the pre-election survey. | ELECTION STUDY NOTES - EL SALVADOR (2019): E3014_LH | | Respondents were not given the answer option "not eligible to | vote." As a consequence, respondents who were ineligible to vote | in the 2018 Legislative Election were coded as "didn't vote" | in the original study and 0. RESPONDENT DID NOT CAST A BALLOT | in CSES, respectively. 23 respondents born after 2000 reported | having cast a vote in 2018, even though they were below voting | age. Data remain unchanged. | ELECTION STUDY NOTES - GREECE (2015): E3014_LH | | The data refer to the election held on January 25, 2015. | ELECTION STUDY NOTES - GREECE (2019): E3014_LH | | The data refer to the election held on September 20, 2015. | ELECTION STUDY NOTES - HONG KONG (2016): E3014_LH | | E3014_LH reflects turnout for geographical constituency | elections in 2012, which returned 35 out of 70 seats for the | unicameral legislature of Hong Kong, the Legislative Council | (LegCo). | ELECTION STUDY NOTES - INDIA (2019): E3014_LH | | For the 2014 Indian Lok Sabha elections, turnout and vote choice | were assessed simultaneously, such that there was no standalone | question assessing turnout. Respondents were coded as having | voted if they stated to have voted for any of the candidates. | ELECTION STUDY NOTES - NETHERLANDS (2021): E3014_LH | | This variable is from the pre-election survey. | ELECTION STUDY NOTES - PERU (2021): E3014_LH | | Turnout for the previous lower house (E3014_LH) and the first | round of the Presidential (E3014_PR_1) elections was derived | from a single question asking respondents whether they had cast | a ballot in the previous general elections in 2016. | ELECTION STUDY NOTES - PORTUGAL (2019): E3014_LH | | The Portuguese 2019 study asked respondents how certain they | were about their turnout in the previous lower house election | on a four-point scale. For CSES, data were recoded as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 0. I am sure that I did not vote in the 2015 | legislative elections | I am not sure if I voted, but it is more likely | that I did not vote | 1. I am not sure if I voted, but it is more likely | that I voted | I am sure I voted in the 2015 legislative | elections | | Further, respondents were not given the answer option "not | eligible to vote." As a consequence, respondents who were | ineligible to vote in the 2015 election are coded as | 0. RESPONDENT DID NOT CAST A BALLOT in E3014_LH. | ELECTION STUDY NOTES - SOUTH KOREA (2016): E3014_LH | | For the 2012 South Korean legislative elections, turnout and | vote choice were assessed simultaneously, such that there was | no standalone question assessing turnout. Respondents were | coded as having voted in case they stated to have cast a vote | for a district candidate, a party list, or both. | ELECTION STUDY NOTES - THAILAND (2019): E3014_LH | | Turnout and vote choice for the previous lower house election | refer to the Thai 2011 general election. The February 2, 2014 | election for the House of Representatives was disrupted | by protests against the government and invalidated by the | Constitutional Court almost two months after the election. | The caretaker government installed in early May 2014 was deposed | two weeks later, following a coup d'etat by the Thai armed | forces. | ELECTION STUDY NOTES - TURKEY (2018): E3014_LH | | In 2015, parliamentary elections were held twice in Turkey, | the first time on June 7. After unsuccessful attempts to | form a coalition government, early elections were held on | November 1. | The variable E3014_LH refers to the 2015 Turkish election which | took place on November 1, 2015. --------------------------------------------------------------------------- E3014_UH >>> Q13a. PREVIOUS UPPER HOUSE ELECTION: DID RESPONDENT CAST A BALLOT --------------------------------------------------------------------------- Whether or not the respondent cast a ballot in the PREVIOUS upper house elections. .................................................................. 0. RESPONDENT DID NOT CAST A BALLOT 1. RESPONDENT CAST A BALLOT 93. VOLUNTEERED: RESPONDENT NOT REGISTERED ON ELECTORAL LISTS / NOT ELIGIBLE [IF APPLICABLE] 95. NOT APPLICABLE: UNICAMERAL SYSTEM 96. NOT APPLICABLE: NO UPPER HOUSE ELECTION 97. VOLUNTEERED: REFUSED 98. VOLUNTEERED: DON'T KNOW 99. MISSING | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3014_UH | | E3014_UH ascertains whether or not the respondent cast a ballot | in the PREVIOUS upper house elections, regardless of whether or | not it was valid. | | +++ TABLE: PREVIOUS UPPER HOUSE ELECTION AND THE YEAR IN | WHICH IT WAS HELD | | Upper House | POLITY (ELEC YEAR) Election | ----------------------------------------------------------- | BRAZIL (2018) 2014 | POLAND (2019) 2015 | URUGUAY (2019) 2014 | ----------------------------------------------------------- | | Data are unavailable for AUSTRALIA (2019), CHILE (2017), | ITALY (2018), MEXICO (2018), POLAND (2019), SWITZERLAND (2019) | and UNITED STATES (2016 & 2020). | ELECTION STUDY NOTES - BRAZIL (2018): E3014_UH | | The question if respondents voted in the "first round" of the | previous election did not differentiate between the | Presidential, lower house and upper house elections. Since | voting is compulsory, it can be assumed that most persons who | answered "yes" voted in all of the elections, and those who | answered "no" did not vote in any of the elections, which took | place simultaneously. Furthermore, there were different kinds of | "no" answers in the original dataset which showed why | respondents did not vote. These values were recoded as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 0. No, more than 70 years old (voluntary) | No, 16-17 years old (voluntary) | No, showed justification in 1st round | Neither voted nor showed justification at first | round | No, didn't have the necessary documentation | 1. Yes, voted --------------------------------------------------------------------------- E3015_PR_1 >>> Q13b. PREVIOUS PRESIDENTIAL ELECTION: VOTE CHOICE - 1ST ROUND --------------------------------------------------------------------------- Respondent's vote choice in the first round of the PREVIOUS Presidential election. .................................................................. 000001-999987. [SEE PART 3 OF CODEBOOK FOR NUMERICAL PARTY/ COALITION CODES] 999988. NONE OF THE CANDIDATES/PARTIES 999989. INDEPENDENT CANDIDATE 999990. OTHER LEFT WING CANDIDATE/PARTY 999991. OTHER RIGHT WING CANDIDATE/PARTY 999992. OTHER CANDIDATE/PARTY (NOT FURTHER SPECIFIED) 999993. INVALID/BLANK BALLOT 999995. NOT APPLICABLE: NO ROLE OF PRESIDENT 999996. NOT APPLICABLE: NO PRESIDENTIAL ELECTION 999997. VOLUNTEERED: REFUSED 999998. VOLUNTEERED: DON'T KNOW 999999. MISSING/ABSTAINED (DID NOT VOTE) | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3015_PR_1 | | E3015_PR_1 details the respondent's vote choice for President | in the first round of the PREVIOUS election, if applicable and | the respondent cast a ballot in the Presidential election. | | Parties/coalitions and their numerical & alphabetical | classifications for each election study are detailed in Part 3 | of the CSES Codebook. | To see which election this variable refers to, see VARIABLE NOTES | for E3014_PR_1. | | Respondents that mentioned not casting a ballot in the first | round of the previous Presidential election (E3014_PR_1) but | report a vote choice are included as it is not possible to | identify why this inconsistency occurred. Users may identify | these cases by cross-tabulating E3014_PR_1 and E3015_PR_1 in | their statistical software. | | Data are unavailable for TUNISIA (2019). | ELECTION STUDY NOTES - BRAZIL (2018): E3015_PR_1 | | Codes in E3015_PR_1 refer to the Brazilian 2014 Presidential | elections and to the following candidates: | | NUMERICAL CODE Election Study Code/Category |---------------------------------------------------------------- | 076001. Luciana Genro | 076002. Dilma Rousseff | 076003. Aecio Neves | 076007. Marina Silva | 076019. Everaldo Pereira | 076020. Eduardo Jorge | 076027. Levy Fidelix | 076031. Jose Maria Eymael | 076033. Mauro Iasi | 076034. Jose Maria de Almeida | 076035. Rui Costa Pimenta | ELECTION STUDY NOTES - EL SALVADOR (2019): E3015_PR_1 | | NUMERICAL CODE 222002 refers to the Nationalist Republican | Alliance (ARENA) for E3015_PR_1. ARENA is the largest member of | the ARENA-PCN-PDC-DS alliance. | ELECTION STUDY NOTES - FRANCE (2017): E3015_PR_1 | | Codes in E3015_PR_1 refer to the French 2012 Presidential | elections and to the following candidates: | | NUMERICAL CODE Election Study Code/Category |---------------------------------------------------------------- | 250002. Marine Le Pen | 250003. Nicolas Sarkozy | 250005. Francois Hollande | 250006. Nicolas Dupont-Aignan | 250008. Philippe Poutou | 250010. Nathalie Arthaud | 250011. Jacques Cheminade | 250012. Francois Bayrou | 250014. Eva Joly | 250015. Jean-Luc Melenchon | ELECTION STUDY NOTES - MEXICO (2018): E3015_PR_1 | | Codes in E3015_PR_1 refer to the Mexican 2012 Presidential | elections and to the following candidates: | | NUMERICAL CODE Election Study Code/Category |---------------------------------------------------------------- | 484002. Josefina Vazquez Mota (PAN) | 484003. Enrique Pena Nieto (PRI) | 484004. Andres Manuel Lopez Obrador (PRD) | 484008. Gabriel Quadri de la Torre (PNA) | | Two alliances formed for the Mexican 2012 Presidential elections: | | "Commitment to Mexico" was an electoral alliance in support of | Enrique Pena Nieto and was comprised of the Institutional | Revolutionary Party (PRI) and the Ecological Green Party of | Mexico (PVEM). | | The "Progressive Movement" was an electoral alliance supporting | Andres Manuel Lopez Obrador, consisting of the Party of the | Democratic Revolution (PRD), the Labor Party (PT), and Citizens' | Movement (MC). | | Andres Manuel Lopez Obrador (LEADER A) contested the 2012 | Mexican Presidential elections as a PRD member. For the 2018 | contest, Lopez Obrador changed party affiliations and contested | for the National Regeneration Movement (MORENA), a party he | founded ahead of the 2015 legislative elections. | ELECTION STUDY NOTES - SOUTH KOREA (2016): E3015_PR_1 | | Codes in E3015_PR_1 refer to the South Korean 2012 Presidential | elections and to the following candidates: | | NUMERICAL CODE Election Study Code/Category |---------------------------------------------------------------- | 410001. Geun-hye Park | 410005. Jae-in Moon | 999989. Ji-won Kang | ELECTION STUDY NOTES - TURKEY (2018): E3015_PR_1 | | The following candidates contested in the 2014 Turkish | Presidential election: | | NUMERICAL CODE Election Study Code/Category |---------------------------------------------------------------- | 792001. Recep Tayyip Erdogan (AKP) | 792002. Ekmeleddin Ihsanoglu (CHP) | 792003. Selahattin Demirtas (HDP) | ELECTION STUDY NOTES - UNITED STATES (2016): E3015_PR_1 | | Codes in E3015_PR_1 refer to the U.S. 2012 Presidential | elections and to the following candidates: | | NUMERICAL CODE Election Study Code/Category |---------------------------------------------------------------- | 840001. Barack Obama | 840002. Mitt Romney | ELECTION STUDY NOTES - UNITED STATES (2020): E3015_PR_1 | | Codes in E3015_PR_1 refer to the U.S. 2016 Presidential | elections and to the following candidates: | | NUMERICAL CODE Election Study Code/Category |---------------------------------------------------------------- | 840101. Hillary Clinton | 840102. Donald Trump --------------------------------------------------------------------------- E3015_PR_2 >>> Q13b. PREVIOUS PRESIDENTIAL ELECTION: VOTE CHOICE - 2ND ROUND --------------------------------------------------------------------------- Respondent's vote choice in the second round of the PREVIOUS Presidential election. .................................................................. 000001-999987. [SEE PART 3 OF CODEBOOK FOR NUMERICAL PARTY/ COALITION CODES] 999988. NONE OF THE CANDIDATES/PARTIES 999989. INDEPENDENT CANDIDATE 999990. OTHER LEFT WING CANDIDATE/PARTY 999991. OTHER RIGHT WING CANDIDATE/PARTY 999992. OTHER CANDIDATE/PARTY (NOT FURTHER SPECIFIED) 999993. INVALID/BLANK BALLOT 999995. NOT APPLICABLE: NO ROLE OF PRESIDENT 999996. NOT APPLICABLE: NO PRESIDENTIAL ELECTION / NO SECOND ROUND 999997. VOLUNTEERED: REFUSED 999998. VOLUNTEERED: DON'T KNOW 999999. MISSING/ABSTAINED (DID NOT VOTE) | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3015_PR_2 | | E3015_PR_2 details the respondent's vote choice for President | in the second round of the PREVIOUS election, if applicable and | the respondent cast a ballot in the Presidential election. | | Parties/coalitions and their numerical & alphabetical | classifications for each election study are detailed in Part 3 | of the CSES Codebook. | To see which election this variable refers to, see VARIABLE NOTES | E3014_PR_2. | | Data are unavailable for COSTA RICA (2018), EL SALVADOR (2019), | MEXICO (2018), PERU (2021) and TUNISIA (2019). | ELECTION STUDY NOTES - BRAZIL (2018): E3015_PR_2 | | Codes in E3015_PR_2 refer to the second round of the Brazilian | 2014 Presidential elections and to the following candidates: | | NUMERICAL CODE Election Study Code/Category |---------------------------------------------------------------- | 076002. Dilma Rousseff | 076003. Aecio Neves --------------------------------------------------------------------------- E3015_LH_PL >>> Q13b. PREVIOUS LOWER HOUSE ELECTION: VOTE CHOICE - PARTY LIST --------------------------------------------------------------------------- Respondent's vote choice for party list in the PREVIOUS lower house election. .................................................................. 000001-999987. [SEE PART 3 OF CODEBOOK FOR NUMERICAL PARTY/ COALITION CODES] 999988. NONE OF THE CANDIDATES/PARTIES 999989. INDEPENDENT CANDIDATE 999990. OTHER LEFT WING CANDIDATE/PARTY 999991. OTHER RIGHT WING CANDIDATE/PARTY 999992. OTHER CANDIDATE/PARTY (NOT FURTHER SPECIFIED) 999993. INVALID/BLANK BALLOT 999995. NOT APPLICABLE: NOT A LIST SYSTEM 999996. NOT APPLICABLE: NO LOWER HOUSE ELECTION 999997. VOLUNTEERED: REFUSED 999998. VOLUNTEERED: DON'T KNOW 999999. MISSING/ABSTAINED (DID NOT VOTE) | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3015_LH_PL | | E3015_LH_PL details the respondent's vote choice for party list | in the PREVIOUS Lower House legislative election, if applicable | and the respondent cast a ballot. | | Parties/coalitions and their numerical & alphabetical | classifications for each election study are detailed in Part 3 | of the CSES Codebook. | To see which election this variable refers to, see VARIABLE NOTES | E3014_LH. | | Respondents that mentioned not casting a ballot in the previous | lower house election (E3014_LH) but report a vote choice | are included, as it is not possible to identify why this | inconsistency occurred. Users may identify these cases by | cross-tabulating E3014_LH and E3015_LH_PL in their statistical | software. | | Data are unavailable for COSTA RICA (2018), MEXICO (2018) and | PERU (2021). | ELECTION STUDY NOTES - CZECHIA (2021): E3015_LH_PL | | For E3015_LH_PL, numerical codes refer to the following | parties: | - NUMERICAL CODE 203101: Civic Democratic Party (ODS), the | largest member of the SPOLU alliance. | - NUMERICAL CODE 203103: Czech Pirate Party (Pi), the largest | member of the PirStan alliance. | Consult Part 3 of the CSES Codebook for more information. | ELECTION STUDY NOTES - EL SALVADOR (2019): E3015_LH_PL | | NUMERICAL CODE 222002 refers to the Nationalist Republican | Alliance (ARENA) for E3015_LH_PL. ARENA is the largest member of | the ARENA-PCN-PDC-DS alliance that formed for the Presidential | election in 2019. | Parties National Coalition Party (PCN, NUMERICAL CODE: 222007) | and Christian Democratic Party (PDC, NUMERICAL CODE: 222008) were | also members of this alliance but did not contest jointly with | the Nationalist Republican Alliance (ARENA) in all electoral | districts in the 2018 legislative election. | For this contest, El Salvador operated an open list proportional | representation system, with 14 multi-member constituencies | based on departments. Alliances did not form on a national level, | but regionally within departments. | ELECTION STUDY NOTES - FINLAND (2019): E3015_LH_PL | | For all survey variables including numeric party codes, the | Finnish questionnaire included the open-ended option "Other | party or group", allowing respondents to specify a party | otherwise not included in the survey. Collaborators classified | these open-ended answers into the following codes adopted for | CSES: | | NUMERICAL CODE Election Study Code/Category |---------------------------------------------------------------- | 999990. Animal Justice Party of Finland | Feminist Party | Communist Party of Finland | 999991. Liberal Party | Movement Now | Finnish People First | 999992. Seven Star Movement | R did not further specify party in open-ended | "Other party or group" option | ELECTION STUDY NOTES - HONG KONG (2016): E3015_LH_PL | | E3015_LH_PL reflects vote choice for the 2012 geographical | constituency elections, which returned 35 out of 70 seats for the | unicameral legislature of Hong Kong, the Legislative Council | (LegCo). | Voters cast one vote for closed party lists, which were compiled | separately for each of the five electoral districts and in some | instances featured more than one list per party per district. | The original vote choice variable assigned each party list an | individual code. E3015_LH_PL summarizes vote choice for each | combination of parties forming a joint party list. | | Further, the 2016 Hong Kong study employed additional codes for | missing values, which were recoded as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 999988. Did not vote for any candidate list | 999993. Cast invalid ballot or abstained | 999998. Forgotten | Don't know | ELECTION STUDY NOTES - HUNGARY (2018): E3015_LH_PL | | For all vote choice variables, the Hungarian study had a category | "Will not say which party I voted for." These respondents are | recoded into CSES category "999997. Volunteered: Refused." | ELECTION STUDY NOTES - ITALY (2018): E3015_LH_PL | | In the previous election in 2013, Italy used a list vote system | only, which is why there is no data for E3015_LH_DC. | | NUMERICAL CODE Election Study Code/Category |---------------------------------------------------------------- | 999991. A center-right party (N=1) | 999990. Socialist Party, Greens (N=2) | A left party (N=2) | ELECTION STUDY NOTES - MONTENEGRO (2016): E3015_LH_PL | | Two respondents reported a party list vote choice after also | indicating they had not voted in the previous lower house | election (E3014_LH). Data remain unchanged. | ELECTION STUDY NOTES - NETHERLANDS (2021): E3015_LH_PL | | This variable is from the pre-election survey. | ELECTION STUDY NOTES - SWITZERLAND (2019): E3015_LH_PL | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 999992. Voted for persons, not parties | Voted for several parties | ELECTION STUDY NOTES - POLAND (2019): E3015_LH_PL | | For E3015_LH_PL, numerical codes refer to the following | parties/alliances: | - NUMERICAL CODE 616001: Law and Justice Party (PiS), the largest | member of the United Right alliance. | - NUMERICAL CODE 616002: Civic Platform Party (PO), the largest | member of the Civic Coalition alliance. | - NUMERICAL CODE 616003: Polish People's Party (PSL), the largest | member of the Polish Coalition alliance. | - NUMERICAL CODE 616004: Left alliance | Consult Part 3 of the CSES Codebook for more information. --------------------------------------------------------------------------- E3015_LH_DC >>> Q13c. PREVIOUS LOWER HOUSE ELECTION: VOTE CHOICE - DISTRICT CANDIDATE --------------------------------------------------------------------------- Respondent's vote choice for district candidate in the PREVIOUS lower house election. .................................................................. 000001-999987. [SEE PART 3 OF CODEBOOK FOR NUMERICAL PARTY/ COALITION CODES] 999988. NONE OF THE CANDIDATES/PARTIES 999989. INDEPENDENT CANDIDATE 999990. OTHER LEFT WING CANDIDATE/PARTY 999991. OTHER RIGHT WING CANDIDATE/PARTY 999992. OTHER CANDIDATE/PARTY (NOT FURTHER SPECIFIED) 999993. INVALID/BLANK BALLOT 999995. NOT APPLICABLE: NO DISTRICT CANDIDATE VOTE 999996. NOT APPLICABLE: NO LOWER HOUSE ELECTION 999997. VOLUNTEERED: REFUSED 999998. VOLUNTEERED: DON'T KNOW 999999. MISSING/ABSTAINED (DID NOT VOTE) | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3015_LH_DC | | E3015_LH_DC details the respondent's vote choice for district | candidate in the PREVIOUS Lower House legislative election, if | applicable and the respondent cast a ballot. | | Parties/coalitions and their numerical & alphabetical | classifications for each election study are detailed in Part 3 | of the CSES Codebook. | To see which election this variable refers to, see VARIABLE NOTES | E3014_LH. | | Respondents that mentioned not casting a ballot in the previous | lower house election (E3014_LH) but report a vote choice | are included, as it is not possible to identify why this | inconsistency occurred. Users may identify these cases by | cross-tabulating E3014_LH and E3015_LH_DC in their statistical | software. | | Data are unavailable for FRANCE (2017), MEXICO (2018), UNITED | STATES (2016 & 2020) and URUGUAY (2019). | ELECTION STUDY NOTES - CANADA (2019): E3015_LH_DC | | This variable is from the pre-election survey. | ELECTION STUDY NOTES - HUNGARY (2018): E3015_LH_DC | | For all vote choice variables, the Hungarian study had a category | "Will not say which party I voted for." These respondents are | recoded into CSES category "999997. Volunteered: Refused." | ELECTION STUDY NOTES - ITALY (2018): E3015_LH_DC | | In the previous election in 2013, Italy used a list vote system | only, which is why there is no data for E3015_LH_DC. | ELECTION STUDY NOTES - LITHUANIA (2016): E3015_LH_DC | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 999988. Did not vote for a candidate | ELECTION STUDY NOTES - LITHUANIA (2020): E3015_LH_DC | | Data refer to the first round of the previous lower house | elections, held on October 9, 2016. | ELECTION STUDY NOTES - NEW ZEALAND (2017): E3015_LH_DC | | One respondent reported a district candidate vote choice after | also indicating not to have voted in the previous lower house | election (E3014_LH). Data remain unchanged. | ELECTION STUDY NOTES - ROMANIA (2016): E3015_LH_DC | | Social Democratic Party (PSD, NUMERICAL CODE: 642001) and the | National Liberal Party (PNL, NUMERICAL CODE: 642002) were both | members of the electoral alliance Social Liberal Union (NUMERICAL | CODE: 642017) in 2012. A tabulation of E3015_LH_DC nevertheless | shows that voters reported that they cast ballots for the | individual member parties in the previous 2012 election, even | though these were alliance members. Since the coalition no longer | existed and the question referred to the last election, which was | almost five years ago at the time of the survey, respondents | probably still indicated that they voted for their favorite party | and not for the coalition that no longer existed. --------------------------------------------------------------------------- E3015_UH_PL >>> PREVIOUS UPPER HOUSE ELECTION: VOTE CHOICE - PARTY LIST --------------------------------------------------------------------------- Respondent's vote choice for party list in the PREVIOUS upper house election. .................................................................. 000001-999987. [SEE PART 3 OF CODEBOOK FOR NUMERICAL PARTY/ COALITION CODES] 999988. NONE OF THE CANDIDATES/PARTIES 999989. INDEPENDENT CANDIDATE 999990. OTHER LEFT WING CANDIDATE/PARTY 999991. OTHER RIGHT WING CANDIDATE/PARTY 999992. OTHER CANDIDATE/PARTY (NOT FURTHER SPECIFIED) 999993. INVALID/BLANK BALLOT 999995. NOT APPLICABLE: UNICAMERAL SYSTEM 999996. NOT APPLICABLE: NO UPPER HOUSE ELECTION OR LIST VOTE 999997. VOLUNTEERED: REFUSED 999998. VOLUNTEERED: DON'T KNOW 999999. MISSING/ABSTAINED (DID NOT VOTE) | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3015_UH_PL | | E3015_UH_PL details the respondent's vote choice for party list | in the PREVIOUS Upper House legislative election, if applicable | and the respondent cast a ballot. | | Parties/coalitions and their numerical & alphabetical | classifications for each election study are detailed in Part 3 | of the CSES Codebook. | To see which election this variable refers to, see VARIABLE NOTES | E3014_UH. | | Data are unavailable for MEXICO (2018) and POLAND (2019). --------------------------------------------------------------------------- E3015_UH_DC_1 >>> PREVIOUS UPPER HOUSE ELECTION: VOTE CHOICE - DISTRICT CANDIDATE 1 E3015_UH_DC_2 >>> PREVIOUS UPPER HOUSE ELECTION: VOTE CHOICE - DISTRICT CANDIDATE 2 --------------------------------------------------------------------------- Respondent's vote choice for district candidate/s in the PREVIOUS upper house election. .................................................................. 000001-999988. [SEE PART 3 OF CODEBOOK FOR NUMERICAL PARTY/ COALITION CODES] 999988. NONE OF THE CANDIDATES/PARTIES 999989. INDEPENDENT CANDIDATE 999990. OTHER LEFT WING CANDIDATE/PARTY 999991. OTHER RIGHT WING CANDIDATE/PARTY 999992. OTHER CANDIDATE/PARTY (NOT FURTHER SPECIFIED) 999993. INVALID/BLANK BALLOT 999995. NOT APPLICABLE: UNICAMERAL SYSTEM 999996. NOT APPLICABLE: NO UPPER HOUSE ELECTION OR CANDIDATE VOTE 999997. VOLUNTEERED: REFUSED 999998. VOLUNTEERED: DON'T KNOW 999999. MISSING/ABSTAINED (DID NOT VOTE) | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3015_UH_DC_ | | E3015_UH_DC_ detail the respondent's vote choice for district | candidate/s in the PREVIOUS Upper House legislative election, | if applicable and the respondent cast a ballot. | | Parties/coalitions and their numerical & alphabetical | classifications for each election study are detailed in Part 3 | of the CSES Codebook. | | Respondents that mentioned not casting a ballot in the previous | upper house election (E3014_UH) but report a vote choice | are included, as it is not possible to identify why this | inconsistency occurred. Users may identify these cases by | cross-tabulating E3014_UH and E3015_UH_DC_ in their statistical | software. | | Data are unavailable for MEXICO (2018), UNITED STATES (2016 & | 2020) and URUGUAY (2019). | ELECTION STUDY NOTES - BRAZIL (2018): E3015_UH_DC_ | | 543 respondents reported a district candidate vote choice after | also indicating they had not voted in the previous upper house | election (E3014_UH). Data remain unchanged. --------------------------------------------------------------------------- E3016_1 >>> Q14a. WHO IS IN POWER CAN MAKE DIFFERENCE --------------------------------------------------------------------------- Q14a. Some people say that it doesn't make any difference who is in power. Others say that it makes a big difference who is in power. Using the scale on this card, (where ONE means that it doesn't make any difference who is in power and FIVE means that it makes a big difference who is in power), where would you place yourself? .................................................................. 1. IT DOESN'T MAKE ANY DIFFERENCE WHO IS IN POWER 2. 3. 4. 5. IT MAKES A BIG DIFFERENCE WHO IS IN POWER 7. VOLUNTEERED: REFUSED 8. VOLUNTEERED: DON'T KNOW 9. MISSING | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3016_1 | | E3016_1 was not part of the CSES MODULE 5 pilot questionnaire. | | Data are unavailable for EL SALVADOR (2019) and TAIWAN (2020). | ELECTION STUDY NOTES - THAILAND (2019): E3016_1 | | For some variables in the Thai 2019 election study, such as | E3016_, an unusually high share of respondents did not provide | substantive answers (> 20% of data coded refused, don't know, or | missing). Collaborators note two potential reasons for this | peculiarity: | | At the time of the election, Thailand's incumbent Prime | Minister was Prayut Chan-o-cha, leader of the State Power Party | (PPRP, PARTY A). As Commander-in-Chief of the Royal Thai Army, | Prayut headed a coup d'etat in May 2014. The 2019 election was | conducted under the new 2017 constitution designed by the | military junta government. Collaborators note parts of the | population dissatisfied with the current situation might have | been reluctant or cautious to provide information on party | preferences and political attitudes closely before or after the | election day. This situation was amplified by official election | results being published only weeks after the election. | | Further, other parts of the population might have been less | knowledgeable concerning political issues such as parties' | ideological classifications and hence might have had difficulties | answering related questions. --------------------------------------------------------------------------- E3016_2 >>> Q14b. WHO PEOPLE VOTE FOR MAKES A DIFFERENCE --------------------------------------------------------------------------- Q14b. Some people say that no matter who people vote for, it won't make any difference to what happens. Others say that who people vote for can make a big difference to what happens. Using the scale on this card, (where ONE means that voting won't make any difference to what happens and FIVE means that voting can make a big difference), where would you place yourself? .................................................................. 1. WHO PEOPLE VOTE FOR WON'T MAKE ANY DIFFERENCE 2. 3. 4. 5. WHO PEOPLE VOTE FOR CAN MAKE A BIG DIFFERENCE 7. VOLUNTEERED: REFUSED 8. VOLUNTEERED: DON'T KNOW 9. MISSING | CSES QUESTION CLASSIFICATION: CORE | ELECTION STUDY NOTES - NEW ZEALAND (2017): E3016_2 | | The wording of the answer categories for E3016_2 offered to | respondents slightly deviated from CSES MODULE 5 standards. | | CSES Code Election Study Code/Category | --------------------------------------------------------------- | 01. Voting won't make any difference to what happens | ... | 05. Voting can make a big difference to what happens | ELECTION STUDY NOTES - TAIWAN (2016 & 2020): E3016_2 | | The wording of the answer categories for E3016_2 offered to | respondents slightly deviated from CSES MODULE 5 standards. | | CSES Code Election Study Code/Category | --------------------------------------------------------------- | 01. Voting won't make any difference to what happens | ... | 05. Voting can make a big difference | ELECTION STUDY NOTES - THAILAND (2019): E3016_2 | | For some variables in the Thai 2019 election study, such as | E3016_, an unusually high share of respondents did not provide | substantive answers (> 20% of data coded refused, don't know, or | missing). Collaborators note two potential reasons for this | peculiarity: | | At the time of the election, Thailand's incumbent Prime | Minister was Prayut Chan-o-cha, leader of the State Power Party | (PPRP, PARTY A). As Commander-in-Chief of the Royal Thai Army, | Prayut headed a coup d'etat in May 2014. The 2019 election was | conducted under the new 2017 constitution designed by the | military junta government. Collaborators note parts of the | population dissatisfied with the current situation might have | been reluctant or cautious to provide information on party | preferences and political attitudes closely before or after the | election day. This situation was amplified by official election | results being published only weeks after the election. | | Further, other parts of the population might have been less | knowledgeable concerning political issues such as parties' | ideological classifications and hence might have had difficulties | answering related questions. --------------------------------------------------------------------------- E3017_A >>> Q15a. LIKE-DISLIKE - PARTY A E3017_B >>> Q15b. LIKE-DISLIKE - PARTY B E3017_C >>> Q15c. LIKE-DISLIKE - PARTY C E3017_D >>> Q15d. LIKE-DISLIKE - PARTY D E3017_E >>> Q15e. LIKE-DISLIKE - PARTY E E3017_F >>> Q15f. LIKE-DISLIKE - PARTY F E3017_G >>> Q15g. LIKE-DISLIKE - ADDITIONAL - PARTY G E3017_H >>> Q15h. LIKE-DISLIKE - ADDITIONAL - PARTY H E3017_I >>> Q15i. LIKE-DISLIKE - ADDITIONAL - PARTY I --------------------------------------------------------------------------- Q15a-i. I'd like to know what you think about each of our political parties. After I read the name of a political party, please rate it on a scale from 0 to 10, where 0 means you strongly dislike that party and 10 means that you strongly like that party. If I come to a party you haven't heard of or you feel you do not know enough about, just say so. The first party is [PARTY A]. Using the same scale, where would you place, [PARTY B]? Using the same scale, where would you place, [PARTY C]? Using the same scale, where would you place, [PARTY D]? Using the same scale, where would you place, [PARTY E]? Using the same scale, where would you place, [PARTY F]? .................................................................. 00. STRONGLY DISLIKE 01. 02. 03. 04. 05. 06. 07. 08. 09. 10. STRONGLY LIKE 96. HAVEN'T HEARD OF PARTY 97. VOLUNTEERED: REFUSED 98. DON'T KNOW ENOUGH ABOUT/DON'T KNOW WHERE TO RATE 99. MISSING | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3017_ | | Parties and their alphabetical classifications for each election | study are detailed in Part 3 of the CSES Codebook. | | In some cases, parties were assigned an alphabetical CSES code | but data for E3017_ is not available for these parties. These | instances are documented in an election study note below the | party/leader table of the Election Study to which this applies | in Part 3 of the CSES Codebook. | | Several respondents mentioned not to know a certain party | in one of the appropriate variables on E3017_, E3019_ or E3021_ | but evaluated even this party on any other scale. These data | remain unchanged. | | +++ TABLE: FREQUENCIES OF RESPONDENTS REPORTING THAT THEY HAD | NOT HEARD OF A SPECIFIC PARTY BUT PROVIDE AN | EVALUATION OF THE PARTY ON ANY OTHER SCALE | | POLITY (ELEC YEAR) _A _B _C _D _E _F _G _H _I | ---------------------------------------------------------------- | AUSTRALIA (2019) 6 4 5 27 - 15 - - - | BRAZIL (2018) 366 95 280 413 456 381 409 432 461 | CANADA (2017) - - 1 - 1 18 - - - | CHILE (2017) 77 87 76 90 93 147 83 207 135 | COSTA RICA (2018) 1 3 2 2 7 9 - - - | CZECHIA (2017) 12 11 39 35 11 9 14 19 31 | CZECHIA (2021) 2 4 2 8 5 2 5 9 3 | DENMARK (2019) - 2 2 2 3 1 4 4 3 | EL SALVADOR (2019) 12 1 2 174 - - 19 - - | FINLAND (2019) 1 2 - - 3 - 1 1 6 | FRANCE (2017) 7 1 3 13 5 - - - - | HONG KONG (2016) 2 4 2 3 5 - - - 13 | HUNGARY (2018) 18 27 34 37 36 - - - - | ICELAND (2016) 4 12 43 8 75 36 17 - - | ICELAND (2017) 9 20 20 113 21 68 170 76 - | INDIA (2019) 311 314 29 157 28 18 29 24 92 | IRELAND (2016) 1 2 2 1 14 18 6 - - | ISRAEL (2020) 1 3 4 3 9 7 4 9 - | ITALY (2018) 25 17 23 16 42 101 - - - | JAPAN (2017) 1 5 1 1 1 3 - - - | LATVIA (2018) 3 10 13 13 6 3 10 26 26 | LITHUANIA (2016) 9 10 8 14 28 22 17 12 - | LITHUANIA (2020) 11 10 7 6 13 13 14 - - | MONTENEGRO (2016) 16 14 20 16 13 12 11 - - | NETHERLANDS (2017) 15 29 13 16 20 16 13 36 48 | PERU (2021) 37 26 90 94 38 73 49 64 76 | POLAND (2019) 1 - 4 4 7 - 17 - 17 | PORTUGAL (2019) 5 6 5 6 8 46 - - - | ROMANIA (2016) 9 8 66 37 31 35 102 - 152 | SLOVAKIA (2020) 2 3 2 4 8 3 3 - - | TUNISIA (2019) 11 43 68 112 93 124 - - - | TURKEY (2018) 1 1 1 1 2 1 - - - | ---------------------------------------------------------------- | KEY: - = Alphabetical code not assigned to party/No cases. | | Data are unavailable for SWITZERLAND (2019). | ELECTION STUDY NOTES - COSTA RICA (2018): E3017_ | | In the Costa Rican 2018 election study, 109 respondents | evaluated all parties equally on the like/dislike scale. | One potential reason is that in Cost Rica, the support of | political parties has eroded in the last two decades. Therefore, | individuals are less likely to identify with parties. Asking | them to evaluate parties or leaders can thus show odd results. | ELECTION STUDY NOTES - INDIA (2019): E3017_ | | PARTY A (Indian People's Party) and PARTY B (Indian National | Congress) are the two major parties in India with national | significance. All other parties contest in selected states only, | where party organizations tend to be state-specific. | Consequently, Collaborators advise conducting analyses on the | state rather than the national level for PARTIES C - I. | Further information on data availability for E3017_C-I and | details on parties' regional concentrations are available in | Codebook Part 3 (Parties and Leaders). | ELECTION STUDY NOTES - NEW ZEALAND (2017): E3017_ | | The wording of answer categories for E3017_ offered to | respondents deviated slightly from CSES MODULE 5 standards. | The original questionnaire labeled category 05. as 'neutral'. | In the CSES questionnaire, there is no such label assigned. | ELECTION STUDY NOTES - THAILAND (2019): E3017_ | | For some variables in the Thai 2019 election study, such as | E3017_, an unusually high share of respondents did not provide | substantive answers (> 20% of data coded refused, don't know, or | missing). Collaborators note two potential reasons for this | peculiarity: | | At the time of the election, Thailand's incumbent Prime | Minister was Prayut Chan-o-cha, leader of the State Power Party | (PPRP, PARTY A). As Commander-in-Chief of the Royal Thai Army, | Prayut headed a coup d'etat in May 2014. The 2019 election was | conducted under the new 2017 constitution designed by the | military junta government. Collaborators note parts of the | population dissatisfied with the current situation might have | been reluctant or cautious to provide information on party | preferences and political attitudes closely before or after the | election day. This situation was amplified by official election | results being published only weeks after the election. | | Further, other parts of the population might have been less | knowledgeable concerning political issues such as parties' | ideological classifications and hence might have had difficulties | answering related questions. --------------------------------------------------------------------------- E3018_A >>> Q16a. LIKE-DISLIKE - LEADER A E3018_B >>> Q16b. LIKE-DISLIKE - LEADER B E3018_C >>> Q16c. LIKE-DISLIKE - LEADER C E3018_D >>> Q16d. LIKE-DISLIKE - LEADER D E3018_E >>> Q16e. LIKE-DISLIKE - LEADER E E3018_F >>> Q16f. LIKE-DISLIKE - LEADER F E3018_G >>> Q16g. LIKE-DISLIKE - ADDITIONAL - LEADER G E3018_H >>> Q16h. LIKE-DISLIKE - ADDITIONAL - LEADER H E3018_I >>> Q16i. LIKE-DISLIKE - ADDITIONAL - LEADER I --------------------------------------------------------------------------- Q16a-i. And what do you think of the Presidential candidates/party leaders? After I read the name of a Presidential candidate/party leader, please rate them on a scale from 0 to 10, where 0 means you strongly dislike that candidate and 10 means that you strongly like that candidate. If I come to a Presidential candidate/party leader you haven't heard of or you feel you do not know enough about, just say so. The first is [LEADER A]. Using the same scale, where would you place, [LEADER B]? Using the same scale, where would you place, [LEADER C]? Using the same scale, where would you place, [LEADER D]? Using the same scale, where would you place, [LEADER E]? Using the same scale, where would you place, [LEADER F]? .................................................................. 00. STRONGLY DISLIKE 01. 02. 03. 04. 05. 06. 07. 08. 09. 10. STRONGLY LIKE 96. HAVEN'T HEARD OF LEADER 97. VOLUNTEERED: REFUSED 98. DON'T KNOW ENOUGH ABOUT/DON'T KNOW WHERE TO RATE 99. MISSING | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3018_ | | Leader alphabetical classifications and relevant numerical and | alphabetical classifications of the party they are associated | with for each election study are detailed in Part 3 of the | CSES Codebook. | | In some instances, leader alphabetical and party alphabetical | classification may not align. These instances are highlighted in | ELECTION STUDY NOTES in Part 3 of the CSES Codebook. | ELECTION STUDY NOTES - COSTA RICA (2018): E3018_ | | In the Costa Rican 2018 election study, 68 respondents | evaluated all leaders equally on the like/dislike scale. | SEE ELECTION STUDY NOTES - COSTA RICA (2018): E3017_ for more | information. | ELECTION STUDY NOTES - EL SALVADOR (2019): E3018_ | | LEADER A (Nayib Bukele), which refers to E3018_A, was the | Presidential candidate of the Grand Alliance for National Unity | (GANA). He is the only Presidential candidate included in | E3018_. | | LEADER B (Norman Quijano), LEADER C (Oscar Ortiz), LEADER G | (Guillermo Gallegos), and LEADER H (Mario Ponce) have been | Presidents or Vice Presidents of the Legislative Assembly from | the four major political parties between 2014 and 2021. | The Presidents and Vice Presidents are members of the | Legislative Assembly, but they are not party leaders. | Given the interaction between the President of the Executive | Branch and the political parties represented in the legislature, | Collaborators considered it relevant to include them, since the | President did not have a majority in the legislature at that | time. | ELECTION STUDY NOTES - FRANCE (2017): E3018_ | | To increase response rates, respondents were shown pictures of | candidates and were asked to rate the respective candidate on | the picture. Those respondents declaring not to know the | candidate after seeing the picture were told the candidate's | name. | For variables E3018_A to E3018_E, Collaborators combined both | modes (picture and name) into one variable per candidate. | ELECTION STUDY NOTES - GERMANY (2017 & 2021): E3018_ | | The question wording for E3018_ deviates slightly from the CSES | MODULE 5 standards, using an 11-point scale ranging from -5 to | +5. It translates to: | | "And what do you think of some of the leading politicians? | Please rate them using again the scale from -5 to +5, where -5 | means you strongly dislike that politician and +5 means that you | strongly like that politician. If you feel you do not know | enough about a politician you do not need to evaluate him/her. | What do you think of ... ". | | In the original 2017 study, respondents were asked to evaluate 10 | politicians of 6 parties. Adhering to the CSES scheme, only one | leader for each party was chosen by Collaborators to be included | in E3018_. For further information about party and leader | codes, see Codebook Part 3. | ELECTION STUDY NOTES - GREAT BRITAIN (2019): E3018_E & E3018_H | | The number of missing responses is high for the two Green Party | leaders (LEADER E, Sian Berry, and LEADER H, Jonathan Bartley), | as the study had to omit some questions from the paper survey, | and these were some of them. | ELECTION STUDY NOTES - ITALY (2018): E3018_A/E3018_I | | LEADER I (Paolo Gentiloni) replaced Matteo Renzi (LEADER A) as | Prime Minister of Italy on December 12, 2016. Renzi, however, | remained leader of the Democratic Party. Data for E3018_ (LIKE- | DISLIKE LEADER A/I) is available for both. | ELECTION STUDY NOTES - LATVIA (2018): E3018_B | | Aldis Gobzems (LEADER B) was the Prime Ministerial candidate for | the Who Owns the State? party in the 2018 Latvian parliamentary | elections. Gobzems was expelled from the party in 2019 after | internal leadership disputes. | ELECTION STUDY NOTES - NEW ZEALAND (2017): E3018_ | | The wording of answer categories for E3018_ offered to | respondents deviated slightly from CSES MODULE 5 standards. | The original questionnaire labeled category 05. as 'neutral'. | In the CSES questionnaire, there is no such label assigned. | ELECTION STUDY NOTES - ROMANIA (2016): E3018_H | | LEADER H (Klaus Iohannis) was Romanian President at the time of | elections. He was Head of the National Liberal Party (PNL) | before being elected President of Romania in November 2014. | ELECTION STUDY NOTES - SLOVAKIA (2020): E3018_ | | LEADER B (Peter Pellegrini) was the leader of SMER-Social | Democracy. However, he left the party after the election and | formed a new party, "Voice-Social Democracy" (numerical code | 703025). | | LEADER H (Robert Fico) is a former Prime Minister of Slovakia. | He is from SMER-Social Democracy and has been the first leader | of that political party since 1999. | ELECTION STUDY NOTES - SWITZERLAND (2019): E3018_ | | LEADER A (Guy Parmelin), LEADER B (Alain Berset), LEADER C | (Karin-Keller Sutter), and LEADER E (Viola Amherd) are Federal | Councilors from the four parties represented in the outgoing | federal government. The Federal Councilors are members and | ministers of the government, but they are not party leaders. | Collaborators asked the question about Federal Councilors rather | than party leaders because citizens know Federal Councilors much | better than party leaders - a lot of citizens do not even know | the party leaders. Additionally, the Swiss Election Study has | always asked about the Federal Councilors and not party leaders, | which allows for comparisons over time. | | The exception is E3018_D, which refers to Regula Rytz, the party | leader of the Green Party. | ELECTION STUDY NOTES - TAIWAN (2016 & 2020): E3018_ | | The answer categories for E3018_ offered to respondents deviated | from CSES MODULE 5 standards. The Taiwan studies, apart from | "Don't know", offered the category "No opinion" to respondents | for leader evaluations. This category was recoded into CSES | category "99. Missing." | ELECTION STUDY NOTES - THAILAND (2019): E3018_ | | For some variables in the Thai 2019 election study, such as | E3018_, an unusually high share of respondents did not provide | substantive answers (> 20% of data coded refused, don't know, or | missing). Collaborators note two potential reasons for this | peculiarity: | | At the time of the election, Thailand's incumbent Prime | Minister was Prayut Chan-o-cha, leader of the State Power Party | (PPRP, PARTY A). As Commander-in-Chief of the Royal Thai Army, | Prayut headed a coup d'etat in May 2014. The 2019 election was | conducted under the new 2017 constitution designed by the | military junta government. Collaborators note parts of the | population dissatisfied with the current situation might have | been reluctant or cautious to provide information on party | preferences and political attitudes closely before or after the | election day. This situation was amplified by official election | results being published only weeks after the election. | | Further, other parts of the population might have been less | knowledgeable concerning political issues such as parties' | ideological classifications and hence might have had difficulties | answering related questions. --------------------------------------------------------------------------- E3019_A >>> Q17a. IDEOLOGY: LEFT-RIGHT - PARTY A E3019_B >>> Q17b. IDEOLOGY: LEFT-RIGHT - PARTY B E3019_C >>> Q17c. IDEOLOGY: LEFT-RIGHT - PARTY C E3019_D >>> Q17d. IDEOLOGY: LEFT-RIGHT - PARTY D E3019_E >>> Q17e. IDEOLOGY: LEFT-RIGHT - PARTY E E3019_F >>> Q17f. IDEOLOGY: LEFT-RIGHT - PARTY F E3019_G >>> Q17g. IDEOLOGY: LEFT-RIGHT - ADDITIONAL - PARTY G E3019_H >>> Q17h. IDEOLOGY: LEFT-RIGHT - ADDITIONAL - PARTY H E3019_I >>> Q17i. IDEOLOGY: LEFT-RIGHT - ADDITIONAL - PARTY I --------------------------------------------------------------------------- Q17a-i. In politics people sometimes talk of left and right. Where would you place [PARTY A] on a scale from 0 to 10 where 0 means the left and 10 means the right? Using the same scale, where would you place [PARTY B]? Where would you place [PARTY C]? Where would you place [PARTY D]? Where would you place [PARTY E]? Where would you place [PARTY F]? .................................................................. 00. LEFT 01. 02. 03. 04. 05. 06. 07. 08. 09. 10. RIGHT 95. VOLUNTEERED: HAVEN'T HEARD OF LEFT-RIGHT 96. VOLUNTEERED: HAVEN'T HEARD OF PARTY 97. VOLUNTEERED: REFUSED 98. VOLUNTEERED: DON'T KNOW WHERE TO PLACE 99. MISSING | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3019_ | | Parties and their alphabetical classifications for each election | study are detailed in Part 3 of the CSES Codebook. | | In some cases, parties were assigned an alphabetical CSES code | but data for E3019_ is not available for these parties. These | instances are documented in ELECTION STUDY NOTES below the | party/leader table of the Election Study to which this applies | in Part 3 of the CSES Codebook. | | Note that the CSES asks Collaborators to ask the left-right | scale questions even if left-right is not considered to be | meaningful/important/widely understood in the area being | studied. However, it was possible to add an optional | alternative scale question. See E3021_ and E3022. | | Several respondents mentioned not to know the left-right scale | in one of the appropriate variables on E3019_ or E3020, but | evaluated the other parties on even that scale. | These data remain unchanged. | | +++ TABLE: FREQUENCIES ON E3019_ AND E3020 FOR RESPONDENTS | REPORTING THAT THEY DID NOT KNOW OF THE LEFT-RIGHT | SCALE BUT PROVIDE AN EVALUATION OF A PARTY ON THE | LEFT-RIGHT SCALE | | PARTY _A _B _C _D _E _F _G _H _I self | POLITY (ELEC YEAR) | ---------------------------------------------------------------- | ALBANIA (2016) 9 18 8 13 21 17 - - - 3 | BRAZIL (2018) 99 99 99 99 99 99 99 99 99 66 | COSTA RICA (2018) 1 3 2 2 3 1 - - - 4 | CZECHIA (2017) 7 11 8 8 13 12 11 11 8 8 | CZECHIA (2021) 25 25 21 12 24 25 23 17 19 25 | DENMARK (2019) 3 3 3 2 3 3 2 4 4 2 | EL SALVADOR (2019) 69 85 85 5 - - 71 - - 87 | FINLAND (2019) 6 5 7 3 3 3 2 3 6 4 | HUNGARY (2018) 8 12 11 19 15 - - - - 19 | INDIA (2019) 76 75 8 25 8 12 6 5 15 719 | IRELAND (2016) 2 2 5 6 7 5 6 - - 3 | ISRAEL (2020) 4 4 8 9 9 8 6 9 - 2 | JAPAN (2017) 5 11 8 7 5 10 - - - 4 | LATVIA (2018) - - - - - - - - - 4 | LITHUANIA (2020) - - - - - - - - - 10 | MONTENEGRO (2016) 3 3 2 3 4 3 6 - - 6 | PERU (2021) - - - - - - - - - 6 | POLAND (2019) 46 40 32 46 24 - 19 - 17 34 | SLOVAKIA (2020) 14 7 6 11 11 12 11 - - - | TUNISIA (2019) 30 23 25 31 28 23 - - - 13 | TURKEY (2018) 1 1 2 1 7 2 - - - 1 | ---------------------------------------------------------------- | KEY: - = Alphabetical code not assigned to party/No cases. | | Data are unavailable for TAIWAN (2016 & 2020). | ELECTION STUDY NOTES - COSTA RICA (2018): E3019_ | | In the Costa Rican 2018 election study, 43 respondents rated | all parties equally on the left/right scale. | SEE ELECTION STUDY NOTES - COSTA RICA (2018): E3017_ for more | information. | Furthermore, some respondents are split on whether to rate a | party as left or right. An overview of mean voter and expert | placements shows that voters and experts disagree significantly | on average where to place parties on the left-right scale. | Those divergences in party placements are based on various | factors. Individuals in Costa Rica have very ambivalent ideas | or opinions regarding parties' ideologies. Mean voters have | serious difficulties classifying parties based on ideological | principles. Furthermore, parties do not have clear policy | positions that would help respondents to evaluate what parties | stand for. This has been this way since the 1980s. In part, the | transformation of the party system in the last two decades (from | a two-party system into a multi-party one) is related to the | erosion of parties' ideological principles. | Experts' opinions are quite different from mean voters. Experts | use their judgments and professional knowledge to label parties. | In sum, ideology is not a straightforward factor among | respondents for classifying parties. | ELECTION STUDY NOTES - FRANCE (2017): E3019_ | | Left-Right party placements for the 2017 French election study | are available for PARTY C (The Republicans) and PARTY E | (Socialist Party). | For PARTY A (The Republic Onwards), PARTY B (National Front) and | PARTY D (Indomitable France) respondents were asked to place | Presidential candidates, not parties, on the left-right scale. | These placements of Presidential candidates are available in | E3021_ (Optional Alternative Scale). | Collaborators state the reasoning behind that decision is the | empirical observation that respondents do not differentiate | between party and leader placements in France | (Presidentialization of parties). However, Collaborators | expected respondents to differentiate between the candidates | of the Republicans and the Socialist Party and their parties, | which is why they included party placements for these two | parties. | | For E3019_ - E3021_, answers coded as 99 "Missing" apply to all | missing respondents or blank answers (no additional precision in | the data). | ELECTION STUDY NOTES - INDIA (2019): E3019_ | | Collaborators note the left-right ideological scale is not | applicable to the Indian party system and question whether most | respondents understand the scale's meaning. | Additionally, they state that there is no consensus on whether | ideology matters for Indian elections, which is why they did not | employ an alternative scale either. Rather, there is an argument | that caste identity is most relevant in analyzing vote choice | for Indian elections. | | For further information on the role of ideology in India, | Collaborators recommend the following literature: | | Chhibber, P. K., and R. Verma. 2018. Ideology and identity: The | changing party systems of India. Oxford University Press. | | Chhibber, P., and R. Verma. 2019. "The rise of the second | dominant party system in India: BJP's new social coalition in | 2019." Studies in Indian Politics 7 (2): 131-148. | DOI: 10.1177/2321023019874628 | | PARTY A (Indian People's Party) and PARTY B (Indian National | Congress) are the two major parties in India with national | significance. All other parties contest in selected states only, | where party organizations tend to be state-specific. | Consequently, Collaborators advise conducting analyses on the | state rather than the national level for PARTIES C - I. | Further information on data availability for E3019_C-I and | details on parties' regional concentrations are available in | Codebook Part 3 (Parties and Leaders). | ELECTION STUDY NOTES - MEXICO (2018): E3019_ | | Pointing to previous research, Collaborators note there might be | a clear and marked discrepancy in Mexico between the way people | place themselves on the left-right and liberal-conservative | scales and their objective location on these scales based on | policy positions. This discrepancy might be one explanation for | the occurence of rare or contradictory responses to party or | leader placements. For more information, see Bertran, U. 2012. | "De izquierda o de derecha? Liberales o conservadores?" Nexos. | Available at: https://www.nexos.com.mx/?p=14629 (Date accessed: | March 15, 2023). | ELECTION STUDY NOTES - NETHERLANDS (2021): E3019_A-I | | These variables are from the pre-election survey. | ELECTION STUDY NOTES - NEW ZEALAND (2017): E3019_ | | The wording of answer categories for E3019_ offered to | respondents deviated slightly from CSES MODULE 5 standards. | The original questionnaire labeled category 05. as 'center'. | In the CSES questionnaire, there is no such label. | ELECTION STUDY NOTES - THAILAND (2019): E3019_ | | For some variables in the Thai 2019 election study, such as | E3019_, an unusually high share of respondents did not provide | substantive answers (> 20% of data coded refused, don't know, or | missing). Collaborators note two potential reasons for this | peculiarity: | | At the time of the election, Thailand's incumbent Prime | Minister was Prayut Chan-o-cha, leader of the State Power Party | (PPRP, PARTY A). As Commander-in-Chief of the Royal Thai Army, | Prayut headed a coup d'etat in May 2014. The 2019 election was | conducted under the new 2017 constitution designed by the | military junta government. Collaborators note parts of the | population dissatisfied with the current situation might have | been reluctant or cautious to provide information on party | preferences and political attitudes closely before or after the | election day. This situation was amplified by official election | results being published only weeks after the election. | | Further, other parts of the population might have been less | knowledgeable concerning political issues such as parties' | ideological classifications and hence might have had difficulties | answering related questions. --------------------------------------------------------------------------- E3020 >>> Q18. IDEOLOGY: LEFT-RIGHT - SELF --------------------------------------------------------------------------- Q18. Where would you place yourself on this scale? .................................................................. 00. LEFT 01. 02. 03. 04. 05. 06. 07. 08. 09. 10. RIGHT 95. VOLUNTEERED: HAVEN'T HEARD OF LEFT-RIGHT 97. VOLUNTEERED: REFUSED 98. VOLUNTEERED: DON'T KNOW WHERE TO PLACE 99. MISSING | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3020 | | The CSES asks Collaborators to ask the left-right scale | questions even if left-right is not considered to be | meaningful/important/widely understood in the area being | studied. However, it was possible to add an optional | alternative scale question. See E3021_ and E3022. | | Several respondents mentioned not to know the left-right scale | in one of the appropriate variables on E3019_ or E3020, but | evaluated the other parties on even that scale. These data | remain unchanged. For further information, see VARIABLE NOTES | on E3019_. | | Data are unavailable for TAIWAN (2016 & 2020). | ELECTION STUDY NOTES - FRANCE (2017): E3020 | | For E3019_ - E3021_, answers coded as 99 "Missing" apply to all | missing respondents or blank answers (no additional precision in | the data). | ELECTION STUDY NOTES - ITALY (2018): E3020 | | 180 respondents said they would not place themselves on the | left-right scale ("I don't place myself on left-right"). These | respondents are coded as "97. VOLUNTEERED: REFUSED." | ELECTION STUDY NOTES - NETHERLANDS (2021): E3020 | | Users are advised that E3020 has been collected in the | post-election study, although party placements on the left-right | scale (E3019_A-I) were collected in the pre-election survey. | For a pre-election left-right self-placement measure, | please refer to the 2021 Dutch Parliamentary Election Study | (DPES). | ELECTION STUDY NOTES - NEW ZEALAND (2017): E3020 | | The wording of answer categories for E3020 offered to | respondents deviated slightly from CSES MODULE 5 standards. | The original questionnaire labeled category 05. as 'center'. | In the CSES questionnaire, there is no such label. --------------------------------------------------------------------------- E3021_A >>> Q19a. OPTIONAL ALTERNATIVE SCALE - PARTY A E3021_B >>> Q19b. OPTIONAL ALTERNATIVE SCALE - PARTY B E3021_C >>> Q19c. OPTIONAL ALTERNATIVE SCALE - PARTY C E3021_D >>> Q19d. OPTIONAL ALTERNATIVE SCALE - PARTY D E3021_E >>> Q19e. OPTIONAL ALTERNATIVE SCALE - PARTY E E3021_F >>> Q19f. OPTIONAL ALTERNATIVE SCALE - PARTY F E3021_G >>> Q19g. OPTIONAL ALTERNATIVE SCALE - ADDITIONAL - PARTY G E3021_H >>> Q19h. OPTIONAL ALTERNATIVE SCALE - ADDITIONAL - PARTY H E3021_I >>> Q19i. OPTIONAL ALTERNATIVE SCALE - ADDITIONAL - PARTY I --------------------------------------------------------------------------- Q19a-i. In politics people sometimes talk of [SCALE VALUE AT POINT 0] and [SCALE VALUE AT POINT 10]. Where would you place [PARTY A] on a scale from 0 to 10 where 0 means [SCALE VALUE AT POINT 0] and 10 means [SCALE VALUE AT POINT 10]? Using the same scale, where would you place [PARTY B]? Where would you place [PARTY C]? Where would you place [PARTY D]? Where would you place [PARTY E]? Where would you place [PARTY F]? .................................................................. 00. [SCALE VALUE AT POINT 0] 01. 02. 03. 04. 05. 06. 07. 08. 09. 10. [SCALE VALUE AT POINT 10] 95. VOLUNTEERED: HAVEN'T HEARD OF [SCALE] 96. VOLUNTEERED: HAVEN'T HEARD OF PARTY 97. VOLUNTEERED: REFUSED 98. VOLUNTEERED: DON'T KNOW WHERE TO PLACE 99. MISSING | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3021_ | | In contexts where left-right is not considered | meaningful/important/widely understood, IN ADDITION TO ASKING | THE LEFT-RIGHT QUESTION, the Collaborator had the option of also | administering the optional alternative question, which is thought | to best summarize the main ideological division in the country. | | Parties and their alphabetical classifications for each election | study are detailed in Part 3 of the CSES Codebook. | | In some cases, parties were assigned an alphabetical | CSES code but data for E3021_ is not available for these | parties. These instances are documented in an election study | note below the party/leader table of the election study to | which this applies in Part 3 of the CSES Codebook. | | Several respondents mentioned not to know the alternative scale | in one of the appropriate variables on E3021_ or E3022, but | evaluated the other parties on even that scale. | These data remain unchanged. | | +++ TABLE: FREQUENCIES ON E3021_ AND E3022 FOR RESPONDENTS WHO | SAID THEY DID NOT KNOW OF THE ALTERNATIVE SCALE IN ONE | VARIABLE, BUT EVALUATING OTHER PARTIES ON THE | ALTERNATIVE SCALE | | PARTY _A _B _C _D _E _F _G _H _I self | ------------------------------------------------------------- | DENMARK (2019) 9 9 9 13 12 12 11 16 13 - | JAPAN (2017) - 4 2 3 4 4 - - - 3 | MONTENEGRO (2016) 1 1 3 5 1 2 - - - 2 | SLOVAKIA (2020) 10 10 11 10 14 10 14 - - 2 | TUNISIA (2019) 18 19 17 18 19 21 - - - 2 | ------------------------------------------------------------- | KEY: - = Alphabetical code not assigned to party/No cases. | | Data are available for DENMARK (2019), FRANCE (2017), GREAT | BRITAIN (2017 & 2019), HONG KONG (2016), JAPAN (2017), LATVIA | (2018), MEXICO (2018), MONTENEGRO (2016), PERU (2021), SLOVAKIA | (2020), TAIWAN (2016 & 2020), THAILAND (2019) and TUNISIA (2019). | ELECTION STUDY NOTES - DENMARK (2019): E3021_ | | In this item battery, respondents were asked to place parties on | a value-oriented left-right scale. The question was worded as | follows: | "In politics people sometimes talk about a value-based | left-right scale, where 'left' represents being open to | immigrants, focusing on prevention over strict punishment as a | solution to crime, and focusing on the climate and protection of | the environment, while 'right' represents a strict judicial | policy and immigration policy, as well as economic issues being | prioritized over the environment and the climate. | Where would you place the following parties on a scale of 0-10, | where 0 means most left and 10 means most right?" | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 00. Being open to immigrants, strict punishment is | not a solution to crime, as well as protection | climate and environment (Left) | ... | 10. A strict judicial and immigration policy as well | as prioritization of economic issues over the | environment and the climate (Right) | ELECTION STUDY NOTES - FRANCE (2017): E3021_ | | E3021_A, E3021_B and E3021_D refer to respondents' placements | of Presidential candidates on the left-right scale. | For PARTY A (The Republic Onwards), PARTY B (National Front) and | PARTY D (Indomitable France) respondents were asked to place | Presidential candidates, not parties, on the left-right scale. | Collaborators state the reasoning behind that decision is the | empirical observation that respondents do not differentiate | between party and leader placements in France | (Presidentialization of parties). However, Collaborators | expected respondents to differentiate between the candidates | of the Republicans and the Socialist Party and their parties, | which is why they included party placements for these two | parties. | Left-Right party placements are available for PARTY C (The | Republicans) and PARTY E (Socialist Party) in E3019_C and | E3019_E, respectively. | | For E3019_ - E3021_, answers coded as 99 "Missing" apply to all | missing respondents or blank answers (no additional precision in | the data). | ELECTION STUDY NOTES - GREAT BRITAIN (2017): E3021_ | | In this item battery, respondents were asked about the party | placement related to redistribution. This is the original | question wording: "Some people feel that government should | make much greater efforts to make people's incomes more equal. | Other people feel that government should be much less concerned | about how equal people's incomes are. On a scale where 0 | means the government should make much greater efforts to make | people's incomes more equal, and 10 means that government should | be much less concerned about how equal people's incomes are, | where would you place the policies of the following parties on | this scale?" | The alternative scale placements are available for PARTY A | (Conservative Party), PARTY B (Labor Party), PARTY C | (Liberal Democrats), PARTY E (UKIP) and PARTY F (Green Party). | ELECTION STUDY NOTES - GREAT BRITAIN (2019): E3021_ | | In this item battery, respondents were asked about the party | placement related to redistribution. This is the original | question wording: "Some people feel that government should | make much greater efforts to make people's incomes more equal. | Other people feel that government should be much less concerned | about how equal people's incomes are. On a scale where 0 | means the government should make much greater efforts to make | people's incomes more equal, and 10 means that government should | be much less concerned about how equal people's incomes are | where would you place the policies of the following parties on | this scale?" | The alternative scale placements are available for PARTY A | (Conservative Party), PARTY B (Labor Party), PARTY C | (Liberal Democrats), PARTY D (Scottish National Party), PARTY E | (Green Party), PARTY F (Brexit Party) and PARTY G (Plaid Cymru). | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 00. Government should make much greater efforts to | make people's income more equal | ... | 10. Government should be much less concerned about | how equal people's incomes are | ELECTION STUDY NOTES - HONG KONG (2016): E3021_ | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 00. pro Hong-Kong | ... | 10. pro Beijing | ELECTION STUDY NOTES - JAPAN (2017): E3021_ | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 00. Liberal | ... | 10. Conservative | ELECTION STUDY NOTES - LATVIA (2018): E3021_ | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 00. Advocates interests of the Russophone population | ... | 10. Advocates interests of ethnic Latvians | ELECTION STUDY NOTES - MEXICO (2018): E3021_ | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 00. Liberal | ... | 10. Conservative | | Also SEE ELECTION STUDY NOTES - MEXICO (2018): E3019_ | (respondents' party placements on the left-right scale). | ELECTION STUDY NOTES - MONTENEGRO (2016): E3021_ | | Respondents were not asked to rank PARTY G (Bosniak Party) on | this dimension because the Bosniak Party is an ethnic party that | represents interests of another national minority, Bosniaks, in | Montenegro. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 00. Pro-Montenegrin | ... | 10. Pro-Serbian | ELECTION STUDY NOTES - PERU (2021): E3021_ | | In this item battery, respondents were asked about the party | placement related to a free market economy. This is the original | question wording: "In politics, people often talk about "an | economy with more state intervention" and "a free market | economy". Using the scale, where 0 means an "economy with | greatest state intervention" and 10 means a "free market | economy", where would you place the position of [POLITICAL | PARTY]?" | The alternative scale placement is not available for PARTY I | (Purple Party). | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 00. Economy with greater state intervention | ... | 10. Free market economy | ELECTION STUDY NOTES - SLOVAKIA (2020): E3021_ | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 00. Liberal views | ... | 10. Conservative views | ELECTION STUDY NOTES - TAIWAN (2016 & 2020): E3021_ | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 00. Independence | ... | 10. Unification with China | 99. It's hard to say | ELECTION STUDY NOTES - THAILAND (2019): E3021_ | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 00. Red shirt group | ... | 10. Yellow shirt group | | For some variables in the Thai 2019 election study, such as | E3021_, an unusually high share of respondents did not provide | substantive answers (> 20% of data coded refused, don't know, or | missing). Collaborators note two potential reasons for this | peculiarity: | | At the time of the election, Thailand's incumbent Prime | Minister was Prayut Chan-o-cha, leader of the State Power Party | (PPRP, PARTY A). As Commander-in-Chief of the Royal Thai Army, | Prayut headed a coup d'etat in May 2014. The 2019 election was | conducted under the new 2017 constitution designed by the | military junta government. Collaborators note parts of the | population dissatisfied with the current situation might have | been reluctant or cautious to provide information on party | preferences and political attitudes closely before or after the | election day. This situation was amplified by official election | results being published only weeks after the election. | | Further, other parts of the population might have been less | knowledgeable concerning political issues such as parties' | ideological classifications and hence might have had difficulties | answering related questions. | ELECTION STUDY NOTES - TUNISIA (2019): E3021_ | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 00. Secular | ... | 10. Islamist --------------------------------------------------------------------------- E3022 >>> Q20. OPTIONAL ALTERNATIVE SCALE - SELF --------------------------------------------------------------------------- Q20. Where would you place yourself on this scale? .................................................................. 00. [SCALE VALUE AT POINT 0] 01. 02. 03. 04. 05. 06. 07. 08. 09. 10. [SCALE VALUE AT POINT 10] 95. VOLUNTEERED: HAVEN'T HEARD OF [SCALE] 97. VOLUNTEERED: REFUSED 98. VOLUNTEERED: DON'T KNOW WHERE TO PLACE 99. MISSING | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3022 | | In contexts where left-right is not considered | meaningful/important/widely understood, IN ADDITION TO ASKING | THE LEFT-RIGHT QUESTION, the Collaborator had the option of also | administering the optional alternative question, which is thought | to best summarize the main ideological division in the country. | | Several respondents mentioned not to know the alternative scale | in one of the appropriate variables on E3021_ or E3022, but | evaluated the other parties on even that scale. These data | remain unchanged. For further information, see VARIABLE NOTES | on E3021_. | | Data are available for DENMARK (2019), HONG KONG (2016), JAPAN | (2017), LATVIA (2018), MEXICO (2018), MONTENEGRO (2016), PERU | (2021), SLOVAKIA (2020), TAIWAN (2016 & 2020), THAILAND (2019) | and TUNISIA (2019). | ELECTION STUDY NOTES - DENMARK (2019): E3022 | | Respondents were asked to place themselves on a value-oriented | left-right scale. | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 00. Being open to immigrants, strict punishment is | not a solution to crime, as well as protection | climate and environment (Left) | ... | 10. A strict judicial and immigration policy as well | as prioritization of economic issues over the | environment and the climate (Right) | ELECTION STUDY NOTES - HONG KONG (2016): E3022 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 00. pro Hong-Kong | ... | 10. pro Beijing | ELECTION STUDY NOTES - JAPAN (2017): E3022 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 00. Liberal | ... | 10. Conservative | ELECTION STUDY NOTES - LATVIA (2018): E3022 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 00. Advocates interests of the Russophone population | ... | 10. Advocates interests of ethnic Latvians | ELECTION STUDY NOTES - MEXICO (2018): E3022 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 00. Liberal | ... | 10. Conservative | ELECTION STUDY NOTES - MONTENEGRO (2016): E3022 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 00. Pro-Montenegrin | ... | 10. Pro-Serbian | ELECTION STUDY NOTES - PERU (2021): E3022 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 00. Economy with greater state intervention | ... | 10. Free market economy | ELECTION STUDY NOTES - SLOVAKIA (2020): E3022 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 00. Liberal views | ... | 10. Conservative views | ELECTION STUDY NOTES - TAIWAN (2016 & 2020): E3022 | | CSES Code Election Study Code/Category | --------------------------------------------------------------- | 00. Independence | ... | 10. Unification with China | 99. It's hard to say | ELECTION STUDY NOTES - THAILAND (2019): E3022 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 00. Red shirt group | ... | 10. Yellow shirt group | ELECTION STUDY NOTES - TUNISIA (2019): E3022 | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 00. Secular | ... | 10. Islamist --------------------------------------------------------------------------- E3023 >>> Q21. SATISFACTION WITH DEMOCRACY --------------------------------------------------------------------------- Q21. On the whole, are you very satisfied, fairly satisfied, not very satisfied, or not at all satisfied with the way democracy works in [COUNTRY]? .................................................................. 1. VERY SATISFIED 2. FAIRLY SATISFIED 4. NOT VERY SATISFIED 5. NOT AT ALL SATISFIED 6. [SEE ELECTION STUDY NOTES] 7. VOLUNTEERED: REFUSED 8. VOLUNTEERED: DON'T KNOW 9. MISSING | CSES QUESTION CLASSIFICATION: CORE | ELECTION STUDY NOTES - AUSTRALIA (2019): E3023 | | CSES Code Election Study Code/Category | --------------------------------------------------------------- | 06. Neither satisfaction nor dissatisfied | ELECTION STUDY NOTES - BRAZIL (2018): E3023 | | CSES Code Election Study Code/Category | --------------------------------------------------------------- | 06. Neither satisfied nor dissatisfied --------------------------------------------------------------------------- E3024_1 >>> Q22a. PARTY ID: ARE YOU CLOSE TO ANY POLITICAL PARTY --------------------------------------------------------------------------- Q22a. Do you usually think of yourself as close to any particular party? .................................................................. 0. NO 1. YES -> GO TO Q22c 7. VOLUNTEERED: REFUSED 8. VOLUNTEERED: DON'T KNOW 9. MISSING | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3024_1 | | Data are unavailable for LATVIA (2018) and TUNISIA (2019). | ELECTION STUDY NOTES - MEXICO (2018): E3024_1 | | The question wording for E3024_1 deviates slightly from the CSES | MODULE 5 standards. It reads: "Regardless of which party you | voted for in the last election, in general, do you sympathize | with any particular political party?" | ELECTION STUDY NOTES - NEW ZEALAND (2017): E3024_1 | | The answer categories for E3024_1 offered to respondents deviated | from CSES MODULE 5 standards. | Response categories were not simple 0. (no) and 1. (yes) but | respondents were asked to tick the box of the party that | they think of close to. If they had ticked the box with | no, they were coded as 0. Whereas, if they had ticked a | box with any party, they were coded as 1. | ELECTION STUDY NOTES - NORWAY (2017): E3024_1 | | The Norwegian survey asked respondents if they supported a | party (E3024_1), and which one (E3024_3) within one question. | The wording of the question is the following: "Some people feel | like supporters of one specific party, while others feel less | tied to any of the parties. Would you say that you think of | yourself as a Hoyremann [Conservative party supporter], an | Arbeiderpartimann [Labor party supporter] and so on, or do you | not feel attached to any of the parties?" Reply categories | included each possible party and "not attached to any party". | | Collaborators precoded E3024_1 for CSES based on the above | survey question. Respondents mentioning a party they felt | attached to were coded 1 in E3024_1. Those respondents not | naming a party affiliation were coded 0 in E3024_1, respectively. | Respondents' party affiliations (if applicable) are coded in | variable E3024_3. --------------------------------------------------------------------------- E3024_2 >>> Q22b. PARTY ID: DO YOU FEEL CLOSER TO ONE PARTY --------------------------------------------------------------------------- Q22b. Do you feel yourself a little closer to one of the political parties than the others? .................................................................. 0. NO -> GO TO QUESTION AFTER Q22d 1. YES 7. VOLUNTEERED: REFUSED -> GO TO QUESTION AFTER Q22d 8. VOLUNTEERED: DON'T KNOW -> GO TO QUESTION AFTER Q22d 9. MISSING | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3024_2 | | Data are unavailable for INDIA (2019), NORWAY (2017), TUNISIA | (2019) and URUGUAY (2019). | ELECTION STUDY NOTES - MEXICO (2018): E3024_2 & E3024_3 | | The question wording for E3024_2 and E3024_3 deviates from the | CSES MODULE 5 standards. | Respondents were first asked whether they sympathized with any | political party (E3024_1). | Respondents answering "yes" in E3024_1 were subsequently asked | which party they identify with, allowing up to three mentions. | In case of multiple mentions, interviewees ought to specify | with which of these parties they sympathized a bit more. This | respective favorite party was coded into E3024_3. | Respondents not mentioning any party or answering "no" to E3024_1 | were asked whether there was any party they sympathized a bit | more with than the others (E3024_2). If they affirmed this, | they were asked which party this was (this party was coded into | E3024_3). | ELECTION STUDY NOTES - MONTENEGRO (2016): E3024_2 | | There are 18 respondents who were asked this question despite | answering with "1. YES" to E3024_1. Data remain unchanged. | ELECTION STUDY NOTES - NEW ZEALAND (2017): E3024_2 | | The answer categories for E3024_2 offered to respondents deviated | from CSES MODULE 5 standards. | Response categories were not simple 0. (no) and 1. (yes) but | respondents were asked to tick the box of the party that | they feel themselves a little closer to than the other parties. | If they had ticked the box with no, they were coded as 0. | Whereas, if they had ticked a box with any party, they | were coded as 1. | ELECTION STUDY NOTES - UNITED STATES (2016): E3024_2 | | For E3024_2, the 2016 ANES adopted the exact question wording | from the CSES MODULE 5 questionnaire. However, unlike suggested | by the CSES convention, the ANES directly coded the party a | respondent leaned to as answer to E3024_2. Therefore, | respondents who stated not to feel a little closer to one of the | political parties were not coded separately and cannot be | distinguished from refusals in E3024_2 (N = 59). Party mentions | as answer to E3024_2 were coded into E3024_3 (WHICH PARTY DO YOU | FEEL CLOSEST TO). --------------------------------------------------------------------------- E3024_3 >>> Q22c. PARTY ID: WHICH PARTY DO YOU FEEL CLOSEST TO --------------------------------------------------------------------------- Q22c. Which party do you feel closest to? .................................................................. 000001-999995. [PLEASE PROVIDE PARTY CODES] 999988. NONE OF THE CANDIDATES/PARTIES 999989. INDEPENDENT CANDIDATE 999990. OTHER LEFT WING CANDIDATE/PARTY (NOT FURTHER SPECIFIED) 999991. OTHER RIGHT WING CANDIDATE/PARTY (NOT FURTHER SPECIFIED) 999992. OTHER CANDIDATE/PARTY (NOT FURTHER SPECIFIED) 999997. VOLUNTEERED: REFUSED 999998. VOLUNTEERED: DON'T KNOW 999999. MISSING | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3024_3 | | Parties are identified in Part 3 of the CSES Codebook. | | Respondents' party mentions in E3024_3 depend on the two former | questions (E3024_1 and E3024_2). The party mention in E3024_3 | should have only been asked for those respondents that reported | to be close (E3024_1) or at least closer (E3024_2) to a party. | However, there are several respondents that mentioned a party | (E3024_3), without feeling close (E3024_1) or closer (E3024_2) | to a party. These data remained unchanged. | | +++ TABLE: FREQUENCIES ON E3024_3 FOR RESPONDENTS THAT DO NOT | FEEL CLOSE (E3024_1) OR AT LEAST CLOSER (E3024_2) TO | A PARTY | | POLITY (ELEC YEAR) NUMBER | ---------------------------------------------------------------- | BELGIUM-FLANDERS (2019) 33 | BELGIUM-WALLONIA (2019) 23 | COSTA RICA (2018) 4 | MONTENEGRO (2016) 6 | NETHERLANDS (2017) 30 | SWEDEN (2018) 167 | THAILAND (2019) 2 | TURKEY (2018) 5 | URUGUAY (2019) 125 | ---------------------------------------------------------------- | | Data are unavailable for TUNISIA (2019). | ELECTION STUDY NOTES - CZECHIA (2021): E3024_3 | | NUMERICAL CODE 203101 refers to the Civic Democratic Party (ODS) | as the largest member of the SPOLU alliance, as well as to the | SPOLU alliance directly for E3024_3 as respondents could choose | ODS as well as the electoral alliance SPOLU. | NUMERICAL CODE 203103 refers to the Czech Pirate Party (Pi) as | the largest member of the PirStan alliance, as well as to the | PirStan alliance directly for E3024_3 as respondents could | choose Pi as well as the electoral alliance PirStan. | NUMERICAL CODE 203108 refers to the Tricolour Citizen's Movement | (Trikolora) for E3024_3. The Trikolora is the largest member of | the Trikolora-Svobodni-Soukromnici alliance. | ELECTION STUDY NOTES - EL SALVADOR (2019): E3024_3 | | NUMERICAL CODE 222002 refers to the Nationalist Republican | Alliance (ARENA) for E3024_3. ARENA is the largest member of the | ARENA-PCN-PDC-DS alliance. | ELECTION STUDY NOTES - FINLAND (2019): E3024_3 | | For all survey variables including numeric party codes, the | Finnish questionnaire included the open-ended option "Other | party or group", allowing respondents to specify a party | otherwise not included in the survey. Collaborators classified | these open-ended answers into the following codes adopted for | CSES: | | NUMERICAL CODE Election Study Code/Category |---------------------------------------------------------------- | 999990. Animal Justice Party of Finland | Feminist Party | Communist Party of Finland | 999991. Liberal Party | Movement Now | Finnish People First | 999992. Seven Star Movement | R did not further specify party in open-ended | "Other party or group" option | ELECTION STUDY NOTES - GERMANY (2017): E3024_3 | | NUMERICAL CODE 276001 refers to the unofficial political alliance | between the Christian Democratic Union (CDU) and the Christian | Social Union in Bavaria (CSU). 292 respondents initially named | the CDU as the party they felt closest to. These answers were | coded into NUMERICAL CODE 276001. NUMERICAL CODE 276007 | identifies respondents stating to feel closest to the CSU. | ELECTION STUDY NOTES - GERMANY (2021): E3024_3 | | NUMERICAL CODE 276102 refers to the unofficial political alliance | between the Christian Democratic Union (CDU) and the Christian | Social Union in Bavaria (CSU). 194 respondents initially named | the CDU as the party they felt closest to. These answers were | coded into NUMERICAL CODE 276102. NUMERICAL CODE 276106 | identifies respondents stating to feel closest to the CSU. | ELECTION STUDY NOTES - IRELAND (2016): E3024_3 | | Respondents were not given the answer option for the | alliance between the Anti-Austerity Alliance (AAA) and the | People Before Profit (PBP) party. Instead, they were given a | separate answer option for each party of the coalition. | The two parties were thus assigned two separate codes, NUMERICAL | CODE 372011: Anti-Austerity Alliance and NUMERICAL CODE 372012: | People Before Profit. | ELECTION STUDY NOTES - LITHUANIA (2016): E3024_3 | | NUMERICAL CODE 440005 refers to Lithuanian Center Party for the | variable E3024_3. This party is the largest member of Anti- | Corruption Coalition. | | NUMERICAL CODE 440013 refers to Young Lithuania (JL) for the | variable E3024_3. This party is the largest constituting member | of the Coalition of Anti-Corruption and Poverty. | ELECTION STUDY NOTES - MEXICO (2018): E3024_2 & E3024_3 | | The question wording for E3024_2 and E3024_3 deviates from the | CSES MODULE 5 standards. | Respondents were first asked whether they sympathized with any | political party (E3024_1). | Respondents answering "yes" in E3024_1 were subsequently asked | which party they identify with, allowing up to three mentions. | In case of multiple mentions, interviewees ought to specify | with which of these parties they sympathized a bit more. This | respective favorite party was coded into E3024_3. | Respondents not mentioning any party or answering "no" to E3024_1 | were asked whether there was any party they sympathized a bit | more with than the others (E3024_2). If they affirmed this, | they were asked which party this was (this party was coded into | E3024_3). | ELECTION STUDY NOTES - NORWAY (2017): E3024_3 | | The Norwegian survey asked respondents if they supported a | party (E3024_1), and which one (E3024_3) within one question. | The wording of the question is the following: "Some people feel | like supporters of one specific party, while others feel less | tied to any of the parties. Would you say that you think of | yourself as a Hoyremann [Conservative party supporter], an | Arbeiderpartimann [Labor party supporter] and so on, or do you | not feel attached to any of the parties?" Reply categories | included each possible party and "not attached to any party". | | Respondents' party affiliation mentioned as an answer to the | above question was coded for E3024_3. E3024_1 distinguishes | party adherents from respondents not feeling close to a party, | as precoded by Collaborators. | ELECTION STUDY NOTES - POLAND (2019): E3024_3 | | For E3024_3, numerical codes refer to the following parties/ | alliances: | - NUMERICAL CODE 616001: Law and Justice Party (PiS), the largest | member of the United Right alliance. | - NUMERICAL CODE 616002: Civic Coalition alliance | - NUMERICAL CODE 616003: Polish People's Party (PSL), the largest | member of the Polish Coalition alliance. | - NUMERICAL CODE 616004: Left alliance | - NUMERICAL CODE 616010: Confederation alliance | Consult Part 3 of the CSES Codebook for more information. | ELECTION STUDY NOTES - TAIWAN (2016): E3024_3 | | For E3024_3, NUMERICAL CODE 158004 refers to the Green Party, | the largest member of the Green Party - Social Democratic Party | alliance. | ELECTION STUDY NOTES - THAILAND (2019): E3024_3 | | For some variables in the Thai 2019 election study, such as | E3024_, an unusually high share of respondents did not provide | substantive answers (> 20% of data coded refused, don't know, or | missing). Collaborators note two potential reasons for this | peculiarity: | | At the time of the election, Thailand's incumbent Prime | Minister was Prayut Chan-o-cha, leader of the State Power Party | (PPRP, PARTY A). As Commander-in-Chief of the Royal Thai Army, | Prayut headed a coup d'etat in May 2014. The 2019 election was | conducted under the new 2017 constitution designed by the | military junta government. Collaborators note parts of the | population dissatisfied with the current situation might have | been reluctant or cautious to provide information on party | preferences and political attitudes closely before or after the | election day. This situation was amplified by official election | results being published only weeks after the election. | | Further, other parts of the population might have been less | knowledgeable concerning political issues such as parties' | ideological classifications and hence might have had difficulties | answering related questions. | ELECTION STUDY NOTES - UNITED STATES (2016): E3024_3 | | Unlike suggested by the CSES convention, the 2016 ANES directly | coded the party a respondent stated to feel a little closer to | as answer to E3024_2 (also SEE ELECTION STUDY NOTES - UNITED | STATES (2016): E3024_2). | Party mentions as answer to E3024_2 were coded into E3024_3. --------------------------------------------------------------------------- E3024_4 >>> Q22d. PARTY ID: DEGREE OF CLOSENESS TO THIS PARTY --------------------------------------------------------------------------- Q22d. Do you feel very close to this party, somewhat close, or not very close? .................................................................. 1. VERY CLOSE 2. SOMEWHAT CLOSE 3. NOT VERY CLOSE 7. VOLUNTEERED: REFUSED 8. VOLUNTEERED: DON'T KNOW 9. MISSING | CSES QUESTION CLASSIFICATION: CORE | VARIABLE NOTES: E3024_4 | | E3024_4 details the degree of closeness to a party and should | have only been asked for those respondents that mentioned a party | in E3024_3. However, there are several respondents that reported | the degree of closeness (E3024_4), without mentioning a party | (E3024_3). These data remained unchanged. | | Also see VARIABLE NOTES on E3024_3. | | +++ TABLE: FREQUENCIES ON E3024_4 FOR RESPONDENTS THAT DO NOT | MENTION A PARTY IN E3024_3 | | ---------------------------------------------------------------- | POLITY (YEAR) NUMBER | ---------------------------------------------------------------- | ALBANIA (2017) 38 | BELGIUM-FLANDERS (2019) 79 | BELGIUM-WALLONIA (2019) 25 | CHILE (2017) 10 | COSTA RICA (2018) 3 | DENMARK (2019) 28 | FINLAND (2019) 42 | GREECE (2015) 22 | HONG KONG (2016) 10 | ITALY (2018) 104 | JAPAN (2017) 1 | MONTENEGRO (2016) 3 | NETHERLANDS (2017) 7 | NEW ZEALAND (2020) 35 | POLAND (2019) 4 | SLOVAKIA (2020) 43 | SWEDEN (2018) 107 | THAILAND (2019) 6 | TURKEY (2018) 1 | URUGUAY (2019) 4 | ---------------------------------------------------------------- | | Data are unavailable for INDIA (2019) and TUNISIA (2019). | ELECTION STUDY NOTES - FINLAND (2019): E3024_4 | | Collaborators note only respondents who answered "1. Yes" to | E3024_1 received the question about the degree of closeness to | the party (E3024_4). | ELECTION STUDY NOTES - FRANCE (2017): E3024_4 | | The answer categories for E3024_4 offered to respondents deviated | from CSES MODULE 5 standards. In the French election study, | E3024_4 included four categories ("very close", "somewhat | close", "not very close", "not close at all") while the CSES | standard question only differentiates between "very close", | "somewhat close", and "not very close". For E3024_4, the | original answer categories "not very close" and "not close at | all" were summarized into "not very close": | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 1. Very close | 2. Somewhat close | 3. Not very close | Not close at all | ELECTION STUDY NOTES - NORWAY (2017): E3024_4 | | The question wording for E3024_4 deviates from the CSES MODULE 5 | standards, reading as: "Do you consider yourself as a strongly | convinced supporter of this party, or are you not very convinced | by this party?" | Furthermore, the wording of the reply categories is different | and they consist of two instead of three categories as in the | CSES questionnaire. These two categories were coded as follows: | | CSES Code Election Study Code/Category |---------------------------------------------------------------- | 01. Strongly convinced | 03. Not very convinced --------------------------------------------------------------------------- E3100_LR_CSES >>> CURRENT MAIN ELECTION - VOTE CHOICE LINKED WITH CSES COLLABORATOR EXPERT JUDGMENT L-R --------------------------------------------------------------------------- Respondents' reported party choice in the main election linked with the CSES Collaborators experts' judgment of the party on the left-right scale (0-10). .................................................................. 00. VOTED FOR PARTY SCORED 0 L-R SCALE 01. 02. 03. 04. 05. 06. 07. 08. 09. 10. VOTED FOR PARTY SCORED 10 L-R SCALE 97. NOT APPLICABLE 99. MISSING | CSES QUESTION CLASSIFICATION: DERIVATIVE VARIABLE (BASED ON CORE) | VARIABLE NOTES: E3100_LR_CSES | | E3100_LR_CSES links the respondents' reported vote choice in the | main election with the CSES Collaborators experts' judgment of | the party the respondent reported voting for on the ideological | left-right scale (0-10). | | E3100_LR_CSES is available for voters who reported voting for a | party where expert judgments are available (i.e., for parties | receiving an alphabetical classification by CSES). For more | details on which parties/coalitions receive alphabetical | classification see "CSES MODULE 5 CODING OF PARTIES/COALITIONS | & LEADERS" in Codebook Part 3. | | E3100_LR_CSES assigns respondents a score based on respondent | reported vote choice and the corresponding expert judgment | of the CSES Collaborators on the left-right ideology scale for | the party the respondent reports voting for. | Collaborators assign parties scores on an 11-point scale ranging | from "0. LEFT" to "10. RIGHT" for all parties assigned an | alphabetical code by CSES. The expert judgment data by party | is available in variable E5018_. | | Some parties/coalitions have scores that are not round numbers, | e.g., 1.5 or 3.5. These scores can reflect Collaborator | judgments or reflect the classification of a coalition. | Sometimes respondents report voting for a coalition, but | Collaborators score parties that comprise this coalition | separately on the L-R scale. The score used for E3100_LR_CSES | is the mean of L-R scores of parties that comprise the given | coalition. | All of these instances are detailed in ELECTION STUDY NOTES | below. | | E3100_LR_CSES links the CSES Collaborator expert judgment with | the reported vote of the respondent in the main election. Here, | a respondent who reports voting for a party/candidate of PARTY A | is assigned the value the CSES Collaborator gave to PARTY A in | the said election on the left-right scale (and so on for PARTY B, | PARTY C etc...). | | CSES classifies the main election based on the regime | (executive) type and the election in which the CSES survey has | been administered. For polities rated as parliamentary systems, | CSES classifies the main election as elections to the lower house | for most studies. It deviates for a few cases when elections to | the upper house constitutes the main election, usually due to the | respective CSES study focusing on the upper house contest. | For polities rated as Presidential systems, CSES conventionally | classifies the main election as the Presidential election. It | sometimes deviates when data for the Presidential election is | unavailable (e.g., when the CSES survey was administered in a | midterm election). For polities rated as mixed systems, CSES | has tended to classify the main election as elections to the | lower house. However, it sometimes deviates depending on data | availability. Users are advised to consult the table listed in | VARIABLE NOTES for E3013_OUTGOV specifying the main election for | each study in CSES for specific details. | ELECTION STUDY NOTES - CZECHIA (2021): E3100_LR_CSES | | NUMERICAL CODE 203101: Together (SPOLU) was an electoral | coalition for the 2021 election between the following parties: | - NUMERICAL CODE 203101: Civic Democratic Party (ODS) | (L-R score = 9) | - NUMERICAL CODE 203196: TOP 09 (L-R score = 9) | - NUMERICAL CODE 203197: Christian and Democratic Union - | Czechoslovak People's Party (KDU-CSL) | (L-R score = 6) | | Thus, the score for the coalition in 2021 for E3100_LR_CSES is 8. | | NUMERICAL CODE 203103: Pirates and Mayors (PirStan) was an | electoral coalition for the 2021 election between the following | parties: | - NUMERICAL CODE 203103: Czech Pirate Party (Pi) (L-R score = 5) | - NUMERICAL CODE 203198: Mayors and Independents (STAN) | (L-R score = 8) | | Thus, the score for the coalition in 2021 for E3100_LR_CSES is | 6.5. | ELECTION STUDY NOTES - GERMANY (2017): E3100_LR_CSES | | NUMERICAL CODE 276001: Christian Democratic Union / Christian | Social Union is a long-standing unofficial political alliance of | the Christian Democratic Union of Germany (CDU) and the Christian | Social Union in Bavaria (CSU). | | In CSES MODULE 5, Collaborators rated each coalition member | separately on the L-R scale. | | For the 2017 study, Collaborators assigned the following | L-R scores: | - NUMERICAL CODE 276001: Christian Democratic Union | (L-R score = 6) | - NUMERICAL CODE 276007: Christian Social Union in Bavaria | (L-R score = 7) | | Thus, the score for the Union in 2017 for the E3100_LR_CSES is | 6.5. | ELECTION STUDY NOTES - GERMANY (2021): E3100_LR_CSES | | NUMERICAL CODE 276102: Christian Democratic Union / Christian | Social Union is a long-standing unofficial political alliance of | the Christian Democratic Union of Germany (CDU) and the Christian | Social Union in Bavaria (CSU). | | In CSES MODULE 5, Collaborators rated each coalition member | separately on the L-R scale. | | For the 2021 study, Collaborators assigned the following | L-R scores: | - NUMERICAL CODE 276102: Christian Democratic Union | (L-R score = 6) | - NUMERICAL CODE 276106: Christian Social Union in Bavaria | (L-R score = 7) | | Thus, the score for the Union in 2021 for the E3100_LR_CSES is | 6.5. | ELECTION STUDY NOTES - HUNGARY (2018): E3100_LR_CSES | | There are 11 respondents in the Hungarian dataset, coded "97. Not | applicable" for E3100_LR_CSES. These respondents are voters | of PARTY G (Hungarian Two-tailed Dog Party; MKKP), which is coded | "97. Not applicable" for the variable E5018_G (Left-Right - | Party G). The MKKP was described in the Macro Report as a | 'Joke party', and therefore was not evaluated on the left-right | scale. | ELECTION STUDY NOTES - ITALY (2018): E3100_LR_CSES | | In the 2018 lower house elections, voters could vote for a party | list only, a party list and a district candidate, or a district | candidate only. For those respondents reporting to have cast a | list vote and those who reported voting for both a party list | and a district candidate, E3100_LR_CSES was coded based on | E3013_LH_PL. For respondents who reported voting for a district | candidate only, E3100_LR_CSES was coded based on E3013_LH_DC. | Users are advised to consult ELECTION STUDY NOTES on E3013_LH_PL | and E3013_LH_DC for further details on the Italian electoral | system. | ELECTION STUDY NOTES - MONTENEGRO (2016): E3100_LR_CSES | | NUMERICAL CODE 499003: Key Coalition was an alliance formed for | the 2016 Montenegrin lower house election. Its members were: | - NUMERICAL CODE 499018: Democratic Alliance (DEMOS) | (L-R score = 5) | - NUMERICAL CODE 499019: Socialist Peoples Party of Montenegro | (SNP) (L-R score = 4) | - NUMERICAL CODE 499020: Civic Movement - United Reform Action | (URA) (L-R score = 4) | | Thus, the score for the Key Coalition for E3100_LR_CSES is 4.3. | ELECTION STUDY NOTES - POLAND (2019): E3100_LR_CSES | | NUMERICAL CODE 616002: Civic Coalition (KO) was an electoral | coalition between the following parties: | - NUMERICAL CODE 616002: Civic Platform (PO) (L-R score = 6) | - NUMERICAL CODE 616008: Modern (Nowo) (L-R score = 9) | - and other smaller parties for the 2019 election. | | Thus, the score for the coalition in 2019 for E3100_LR_CSES is | 7.5. | | NUMERICAL CODE 616003: Polish Coalition (KP) was an electoral | coalition between the following parties: | - NUMERICAL CODE 616003: Polish People's Party (PSL) | (L-R score = 6) | - NUMERICAL CODE 616005: Kukiz'15 (K'15) (L-R score = 8) | - and other smaller parties for the 2019 election. | | Thus, the score for the coalition in 2019 for E3100_LR_CSES is 7. | | NUMERICAL CODE 616004: The Left was an alliance for the 2019 | election between several smaller parties and the following | members: | - NUMERICAL CODE 616004: Democratic Left Alliance (SLD) | (L-R score = 3) | - NUMERICAL CODE 616006: Left Together (Razem) (L-R score = 2) | - NUMERICAL CODE 616007: Spring (Wiosna) (L-R score = 3) | | Thus, the score for The Left for E3100_LR_CSES is 2.67. --------------------------------------------------------------------------- E3100_LR_MARPOR >>> CURRENT MAIN ELECTION - VOTE CHOICE LINKED WITH MARPOR/CMP RILE --------------------------------------------------------------------------- Respondents' reported party choice in the main election linked with the MARPOR/CMP "RILE" index assigned to the party. .................................................................. -100 - +100. RILE INDEX SCORES 999. MISSING | CSES QUESTION CLASSIFICATION: DERIVATIVE VARIABLE (BASED ON CORE) | VARIABLE NOTES: E3100_LR_MARPOR | | E3100_LR_MARPOR links the respondents' reported vote choice in | the main election with the MARPOR/CMP "RILE" index assigned to | the party the respondent reported voting for based on the | manifesto the party contested the election on. | | E3100_LR_MARPOR is available for voters who reported voting for a | party receiving an alphabetical classification by CSES. For more | details on which parties/coalitions receive alphabetical | classification see "CSES MODULE 5 CODING OF PARTIES/COALITIONS | & LEADERS" in Codebook Part 3. | | E3100_LR_MARPOR assigns respondents a score based on respondent | reported vote choice and the corresponding value of that party | on the MARPOR "rile" index. The index was developed by Laver and | Budge (1992). It takes 24 categories (12 are defined as right- | wing and 12 as left-wing) and subtracts the sum of all right-wing | items from the sum of all left-wing items. The RILE index ranges | from -100 (if a party only mentions left-wing issues in its | program) and +100 (if a party only mentions right-wing issues in | its program). However, these are the theoretical maximum and | minimum values which are empirically rare. | | More information about MARPOR/CMP data and RILE index can be | found at https://manifestoproject.wzb.eu/ | (Date accessed: May 03, 2023). | | E3100_LR_MARPOR links the MARPOR "rile" index value with the | reported vote of the respondent in the main election. Here, a | respondent who reports voting for a party/candidate of PARTY A | is assigned the value MARPOR "rile" index gave to PARTY A in | the said election (and so on for PARTY B, PARTY C etc...). | | CSES classifies the main election based on the regime | (executive) type and the election in which the CSES survey has | been administered. For polities rated as parliamentary systems, | CSES classifies the main election as elections to the lower house | for most studies. It deviates for a few cases when elections to | the upper house constitutes the main election, usually due to the | respective CSES study focusing on the upper house contest. | For polities rated as Presidential systems, CSES conventionally | classifies the main election as the Presidential election. It | sometimes deviates when data for the Presidential election is | unavailable (e.g., when the CSES survey was administered in a | midterm election). For polities rated as mixed systems, CSES | has tended to classify the main election as elections to the | lower house. However, it sometimes deviates depending on data | availability. Users are advised to consult the table listed in | VARIABLE NOTES for E3013_OUTGOV specifying the main election for | each study in CSES for specific details. | | Users are advised that CSES and MARPOR/CMP sometimes classify | coalitions differently in elections and across polities. For | example CSES sometimes has data solely on coalitions and not | the parties comprising the alliance, while MARPOR/CMP may have | data concerning the individual parties in the coalition, or | vice versa. Consequently, some parties may have multiple | identifiers within the MARPOR/CMP dataset across time. A non | comprehensive list of these deviations are noted in Part 3 | of the CSES MODULE 5 Codebook in ELECTION STUDY NOTES. | | Data are unavailable primarily because some polities, which are | in the CSES, are not represented in the MARPOR/CMP dataset. | Data are unavailable for AUSTRALIA (2019), BRAZIL (2018), CANADA | (2019), CHILE (2017), COSTA RICA (2018), FRANCE (2017), HONG | KONG (2016), ISRAEL (2020), SLOVAKIA (2020), TAIWAN (2016, 2020), | THAILAND (2019), TUNISIA (2019) and URUGUAY (2019). | ELECTION STUDY NOTES - GREECE (2015): E3100_LR_MARPOR | | NUMERICAL CODE 300004: Democratic Coalition (PASOK-DIMAR) was an | electoral coalition formed for the September 2015 lower house | election. This coalition was comprised of the following parties: | - NUMERICAL CODE 300016: Panhellenic Socialist Movement (PASOK) | - NUMERICAL CODE 300017: Democratic Left (DIMAR). | For this contest, MARPOR/CMP does not include data on the | alliance. Instead, individual parties are classified. The below | table lists MARPOR/CMP codes for these parties for this contest, | together with their rile score assigned by MARPOR/CMP. | | Party MARPOR Party Code RILE Score |----------------------------------------------------------------- | Panhellenic Socialist Movement 34313 -24.45 | Democratic Left 34213 NOT AVAILABLE | ELECTION STUDY NOTES - HUNGARY (2018): E3100_LR_MARPOR | | NUMERICAL CODE 348003: Hungarian Socialist Party - Dialogue for | Hungary was an electoral coalition between the following parties | for the 2018 election: | - Hungarian Socialist Party (MSZP) | - Dialogue for Hungary | For this contest, MARPOR/CMP does not include data on the | alliance. Instead, individual parties are classified. The below | table lists MARPOR/CMP codes for these parties for this contest, | together with their rile score assigned by MARPOR/CMP. | | Party MARPOR Party Code RILE Score |----------------------------------------------------------------- | Hungarian Socialist Party 86220 -19.82 | Dialogue for Hungary 86111 -36.05 | ELECTION STUDY NOTES - IRELAND (2016): E3100_LR_MARPOR | | NUMERICAL CODE 372005: Anti-Austerity Alliance-People Before | Profit (AAA-PBP) was an electoral alliance formed for the 2016 | election between the following parties: | - Anti-Austerity Alliance (AAA) | - People Before Profit (PBP) | - Anti-Water Tax Socialist Party (SP) | For this contest, MARPOR/CMP does not include data on the | alliance. Instead, individual parties are classified. The below | table lists MARPOR/CMP codes for these parties for this contest, | together with their rile score assigned by MARPOR/CMP. | | Party MARPOR Party Code RILE Score |----------------------------------------------------------------- | Anti-Austerity Alliance 53240 -32.16 | People Before Profit 53231 -47.92 | ELECTION STUDY NOTES - ITALY (2018): E3100_LR_MARPOR | | In the 2018 lower house elections, voters could vote for a party | list only, a party list and a district candidate, or a district | candidate only. For those respondents reporting to have cast a | list vote and those who reported voting for both a party list | and a district candidate, E3100_LR_MARPOR was coded based on | E3013_LH_PL. For respondents who reported voting for a district | candidate only, E3100_LR_MARPOR was coded based on E3013_LH_DC. | Users are advised to consult ELECTION STUDY NOTES on E3013_LH_PL | and E3013_LH_DC for further details on the Italian electoral | system. | ELECTION STUDY NOTES - POLAND (2019): E3100_LR_MARPOR | | Five coalitions formed for the Polish 2019 legislative election. | Alliances and how RILE scores were mapped to E3100_LR_MARPOR are | listed below. | | NUMERICAL CODE 616001: United Right (ZP) was an alliance between | Law and Justice (PiS) and various smaller parties. The RILE score | as reported in E3100_LR_CSES refers to PiS, which was the | dominant member of the alliance. | | NUMERICAL CODE 616002: Civic Coalition (KO) was an alliance | between Civic Platform (PO), Modern (Nowo) and various smaller | parties. The RILE score as reported in E3100_LR_CSES refers to | the alliance, that is, the Civic Coalition (KO). | | NUMERICAL CODE 616003: Polish Coalition (KP) was an alliance | between the Polish People's Party (PSL), Kukiz'15 (K'15) and | various smaller parties. The RILE score as reported in | E3100_LR_CSES refers to the alliance, that is, the Polish | Coalition (KP). | | NUMERICAL CODE 616004: The Left was an alliance between the | Democratic Left Alliance (SLD), Left Together (Razem), | Spring (Wiosna), and various smaller parties. The RILE score as | reported in E3100_LR_CSES refers to the alliance, that is, | The Left. | | However, researchers are advised that MARPOR/CMP does not regard | Spring (Wiosna) to be a part of The Left alliance. Instead, a | separate RILE score is assigned to Wiosna. | The below table lists MARPOR/CMP codes for The Left and Wiosna | for the 2019 contest, together with their rile score assigned by | MARPOR/CMP. | | Party MARPOR Party Code RILE Score |----------------------------------------------------------------- | The Left 92023 -28.18* | Spring (Wiosna) 92455 -20.66 | | * Value used for coding E3100_LR_CSES for voters of The Left | (NUMERICAL CODE 616004) in E3013_LH_PL. | | NUMERICAL CODE 616010: Confederation was an alliance between New | Hope (KORWiN) and various smaller parties. The RILE score as | reported in E3100_LR_CSES refers to the Confederation Alliance. | ELECTION STUDY NOTES - PORTUGAL (2018): E3100_LR_MARPOR | | NUMERICAL CODE 620004: Unitarian Democratic Coalition (CDU) is | an electoral coalition founded in 1987 between the Communist | Party (PCP) and the Ecologist Party "The Greens" (PEV). | For the 2019 legislative election, MARPOR/CMP does not include | data on the alliance. Instead, individual parties are classified. | The below table lists MARPOR/CMP codes for these parties for this | contest, together with their rile score assigned by MARPOR/CMP. | | Party MARPOR Party Code RILE Score |----------------------------------------------------------------- | Ecologist Party "The Greens" 35110 -31.28 | Portuguese Communist Party 35220 -31.77 --------------------------------------------------------------------------- E3100_POP_CSES >>> CURRENT MAIN ELECTION - VOTE CHOICE LINKED WITH CSES COLLABORATOR EXPERT JUDGMENT ON POPULISM --------------------------------------------------------------------------- Respondents' reported party choice in the main election linked with the CSES Collaborators experts' judgment of the party on the populism scale (0-10). .................................................................. 00. VOTED FOR PARTY SCORED 0 ON POPULISM SCALE 01. 02. 03. 04. 05. 06. 07. 08. 09. 10. VOTED FOR PARTY SCORED 10 ON POPULISM SCALE 97. NOT APPLICABLE 98. NO POPULISM SCORE ASSIGNED 99. MISSING | CSES QUESTION CLASSIFICATION: DERIVATIVE VARIABLE (BASED ON CORE) | VARIABLE NOTES: E3100_POP_CSES | | E3100_POP_CSES links the respondents' reported vote choice in the | main election with the CSES Collaborators experts' judgment of | the party the respondent reported voting for on the populism | scale (0-10). | | E3100_POP_CSES is available for voters who reported voting for a | party where expert judgments are available (i.e., for parties | receiving an alphabetical classification by CSES). For more | details on which parties/coalitions receive alphabetical | classification see "CSES MODULE 5 CODING OF PARTIES/COALITIONS | & LEADERS" in Codebook Part 3. | | E3100_POP_CSES assigns respondents a score based on respondents' | reported vote choice and the corresponding CSES Collaborators | expert placement of the party voted for on the populism scale. | This variable hence links the CSES Collaborator expert judgment | with the reported vote of the respondent in the main election. | Here, a respondent who reports voting for a party/candidate of | PARTY A is assigned the value the CSES Collaborator gave to | PARTY A in the said election on the populism scale (and so on | for PARTY B, PARTY C etc...). | | Collaborators assign parties scores on an 11-point scale ranging | from "0. NOT AT ALL POPULIST" to "10. VERY POPULIST" for all | parties assigned an alphabetical code by CSES. The expert | judgment data by party used for coding E3100_POP_CSES is | available in variable E5020_. | | For classifying parties on the populism scale, Collaborators were | provided with the following definition: | "Definition: Populism can be defined as a thin-centered ideology | that pits a virtuous and homogeneous people against a set of | elites and dangerous 'others' who are depicted as depriving | "the people" of their rights, values, prosperity, identity, and | voice. The emphasis on anti-elite/ anti-establishment rhetoric | and the contrast between the "pure people" and the "corrupt | elite" are thus indications of the degree to which a party is | populist. Populist parties can be found across the left-right | ideological spectrum." | | E3100_POP_CSES is coded based on respondents' vote choice in the | main election. | | CSES classifies the main election based on the regime | (executive) type and the election in which the CSES survey has | been administered. For polities rated as parliamentary systems, | CSES classifies the main election as elections to the lower house | for most studies. It deviates for a few cases when elections to | the upper house constitutes the main election, usually due to the | respective CSES study focusing on the upper house contest. | For polities rated as Presidential systems, CSES conventionally | classifies the main election as the Presidential election. It | sometimes deviates when data for the Presidential election is | unavailable (e.g., when the CSES survey was administered in a | midterm election). For polities rated as mixed systems, CSES | has tended to classify the main election as elections to the | lower house. However, it sometimes deviates depending on data | availability. Users are advised to consult the table listed in | VARIABLE NOTES for E3013_OUTGOV specifying the main election for | each study in CSES for specific details. | | Some parties/coalitions have scores in E3100_POP_CSES that are | not round numbers, e.g., 1.5 or 5.5. These scores can reflect | Collaborator judgments or reflect the classification of a | coalition. Sometimes respondents report voting for a coalition, | but Collaborators score parties that comprise this coalition | separately on the populism scale. The score used for | E3100_POP_CSES is the mean of populism scores of parties that | comprise the given coalition. All of these instances are detailed | in ELECTION STUDY NOTES below. | | Sometimes parties' levels of populism are hard to determine. | These instances are detailed in ELECTION STUDY NOTES for | variable E5020_. | ELECTION STUDY NOTES - GERMANY (2017): E3100_POP_CSES | | NUMERICAL CODE 276001: Christian Democratic Union / Christian | Social Union is a long-standing unofficial political alliance of | the Christian Democratic Union of Germany (CDU) and the Christian | Social Union in Bavaria (CSU). | | In CSES MODULE 5, Collaborators rated each coalition member | separately on the populism scale. | | For the 2017 study, Collaborators assigned the following | populism scores: | - NUMERICAL CODE 276001: Christian Democratic Union | (populism score = 1) | - NUMERICAL CODE 276007: Christian Social Union in Bavaria | (populism score = 2) | | Thus, the score for the Union in 2017 for E3100_POP_CSES is 1.5. | ELECTION STUDY NOTES - GERMANY (2021): E3100_POP_CSES | | NUMERICAL CODE 276102: Christian Democratic Union / Christian | Social Union is a long-standing unofficial political alliance of | the Christian Democratic Union of Germany (CDU) and the Christian | Social Union in Bavaria (CSU). | | In CSES MODULE 5, Collaborators rated each coalition member | separately on the populism scale. | | For the 2021 study, Collaborators assigned the following | populism scores: | - NUMERICAL CODE 276102: Christian Democratic Union | (populism score = 1) | - NUMERICAL CODE 276106: Christian Social Union in Bavaria | (populism score = 2) | | Thus, the score for the Union in 2021 for E3100_POP_CSES is 1.5. | ELECTION STUDY NOTES - HUNGARY (2018): E3100_POP_CSES | | NUMERICAL CODE 348003: Hungarian Socialist Party - Dialogue for | Hungary was an electoral coalition between the Hungarian | Socialist Party (MSZP) and Dialogue for Hungary formed for the | 2018 election. | | In CSES MODULE 5, Collaborators rated each coalition member | separately on the populism scale by assigning the following | scores: | - Hungarian Socialist Party (populism score = 5) | - Dialogue for Hungary (populism score = 6) | Thus, the score for the coalition in 2018 for E3100_POP_CSES is | 5.5. | ELECTION STUDY NOTES - ITALY (2018): E3100_POP_CSES | | In the 2018 lower house elections, voters could vote for a party | list only, a party list and a district candidate, or a district | candidate only. For those respondents reporting to have cast a | list vote and those who reported voting for both a party list | and a district candidate, E3100_POP_CSES was coded based on | E3013_LH_PL. For respondents who reported voting for a district | candidate only, E3100_POP_CSES was coded based on E3013_LH_DC. | Users are advised to consult ELECTION STUDY NOTES on E3013_LH_PL | and E3013_LH_DC for further details on the Italian electoral | system. | ELECTION STUDY NOTES - MONTENEGRO (2016): E3100_POP_CSES | | NUMERICAL CODE 499003: Key Coalition was an alliance formed for | the 2016 Montenegrin lower house election. Its members were: | - NUMERICAL CODE 499018: Democratic Alliance (DEMOS) | (populism score = 6) | - NUMERICAL CODE 499019: Socialist Peoples Party of Montenegro | (SNP) (populism score = 6) | - NUMERICAL CODE 499020: Civic Movement - United Reform Action | (URA) (populism score = 3) | | Thus, the score for the Key Coalition for E3100_POP_CSES is 5. | ELECTION STUDY NOTES - POLAND (2019): E3100_POP_CSES | | NUMERICAL CODE 616002: Civic Coalition (KO) was an electoral | coalition between the following parties: | - NUMERICAL CODE 616002: Civic Platform (PO) (populism score = 3) | - NUMERICAL CODE 616008: Modern (Nowo) (populism score = 4) | - and other smaller parties for the 2019 election. | | Thus, the score for the coalition in 2019 for E3100_POP_CSES is | 3.5. | | NUMERICAL CODE 616003: Polish Coalition (KP) was an electoral | coalition between the following parties: | - NUMERICAL CODE 616003: Polish People's Party (PSL) | (populism score = 5) | - NUMERICAL CODE 616005: Kukiz'15 (K'15) (populism score = 10) | - and other smaller parties for the 2019 election. | | Thus, the score for the coalition in 2019 for E3100_POP_CSES is | 7.5. | | NUMERICAL CODE 616004: The Left was an alliance for the 2019 | election between several smaller parties and the following | members: | - NUMERICAL CODE 616004: Democratic Left Alliance (SLD) | (populism score = 3) | - NUMERICAL CODE 616006: Left Together (Razem) | (populism score = 4) | - NUMERICAL CODE 616007: Spring (Wiosna) (populism score = 4) | | Thus, the score for The Left for E3100_POP_CSES is 3.67. --------------------------------------------------------------------------- E3100_IF_CSES >>> CURRENT MAIN ELECTION - VOTE CHOICE LINKED WITH CSES COLLABORATOR EXPERT JUDGMENT IDEOLOGICAL FAMILY --------------------------------------------------------------------------- Respondents' reported party choice in the main election linked with the CSES Collaborators experts' judgment of the party's ideological family. .................................................................. 01. VOTED PARTY CLASSIFIED AS ECOLOGY 02. VOTED PARTY CLASSIFIED AS COMMUNIST 03. VOTED PARTY CLASSIFIED AS SOCIALIST 04. VOTED PARTY CLASSIFIED AS SOCIAL DEM 05. VOTED PARTY CLASSIFIED AS LEFT LIBERAL 06. VOTED PARTY CLASSIFIED AS LIBERAL 07. VOTED PARTY CLASSIFIED AS RIGHT LIBERAL 08. VOTED PARTY CLASSIFIED AS CHRISTIAN DEM 09. VOTED PARTY CLASSIFIED AS CONSERVATIVE 10. VOTED PARTY CLASSIFIED AS NATIONAL 11. VOTED PARTY CLASSIFIED AS AGRARIAN 12. VOTED PARTY CLASSIFIED AS ETHNIC 13. VOTED PARTY CLASSIFIED AS REGIONAL 14. VOTED PARTY CLASSIFIED AS INDEPENDENT 90. VOTED PARTY CLASSIFIED AS OTHER 97. NOT APPLICABLE 98. NO IDEOLOGICAL FAMILY MENTIONED 99. MISSING | CSES QUESTION CLASSIFICATION: DERIVATIVE VARIABLE (BASED ON CORE) | VARIABLE NOTES: E3100_IF_CSES | | E3100_IF_CSES links the respondents' reported vote choice in the | main election with the CSES Collaborators experts' judgment of | the ideological family of the party the respondent reported | voting for. | | E3100_IF_CSES is available for voters who reported voting for a | party where expert judgments are available (i.e., for parties | receiving an alphabetical classification by CSES). For more | details on which parties/coalitions receive alphabetical | classification see "CSES MODULE 5 CODING OF PARTIES/COALITIONS | & LEADERS" in Codebook Part 3. | | E3100_IF_CSES assigns respondents a score based on respondent | reported vote choice and the corresponding CSES Collaborators | expert judgments of the party's ideological family. | The expert judgment data by party is available in variable | E5017_. | | E3100_IF_CSES links the CSES Collaborator expert judgment with | the reported vote of the respondent in the main election. Here, | a respondent who reports voting for a party/candidate of PARTY A | is assigned the value the CSES Collaborator gave to PARTY A in | the said election on the left-right scale (and so on for PARTY B, | PARTY C etc...). | | CSES classifies the main election based on the regime | (executive) type and the election in which the CSES survey has | been administered. For polities rated as parliamentary systems, | CSES classifies the main election as elections to the lower house | for most studies. It deviates for a few cases when elections to | the upper house constitutes the main election, usually due to the | respective CSES study focusing on the upper house contest. | For polities rated as Presidential systems, CSES conventionally | classifies the main election as the Presidential election. It | sometimes deviates when data for the Presidential election is | unavailable (e.g., when the CSES survey was administered in a | midterm election). For polities rated as mixed systems, CSES | has tended to classify the main election as elections to the | lower house. However, it sometimes deviates depending on data | availability. Users are advised to consult the table listed in | VARIABLE NOTES for E3013_OUTGOV specifying the main election for | each study in CSES for specific details. | | In some instances, CSES Collaborators provide additional | information to the characterization, and when applicable, these | are detailed in the ELECTION STUDY NOTES for variable E5017_. | | Users are advised that the same party might have been coded as | belonging to different party families across different | elections. These differences may reflect actual changes in | parties' ideological positions across time. | Alternatively, they might reflect disagreement on different | experts on which ideological family the respective party | belongs to, whenever national Collaborators changed between | election studies. | | Data are unavailable primarily because Collaborator expert | judgments of parties were not provided for certain election | studies. | ELECTION STUDY NOTES - ITALY (2018): E3100_IF_CSES | | In the 2018 lower house elections, voters could vote for a party | list only, a party list and a district candidate, or a district | candidate only. For those respondents reporting to have cast a | list vote and those who reported voting for both a party list | and a district candidate, E3100_IF_CSES was coded based on | E3013_LH_PL. For respondents who reported voting for a district | candidate only, E3100_IF_CSES was coded based on E3013_LH_DC. | Users are advised to consult ELECTION STUDY NOTES on E3013_LH_PL | and E3013_LH_DC for further details on the Italian electoral | system. =========================================================================== ))) CSES MODULE 5 VARIABLES: DISTRICT-LEVEL DATA =========================================================================== | VARIABLE NOTES: | | (1) Respondents' electoral districts are reported in E2021, | with labels listed in Part 4 of the CSES Codebook. | | (2) According to the different types of elections included in | this CSES release, the tables below provide an overview of | each polity and to which election the district data | pertains to, detail the number of districts in total in | each state and the number of these districts which are | sampled by studies included in CSES, and provide information | about the electoral tier (where applicable) to which the | district data pertain to. Users are advised to consult these | tables carefully to decide which data is appropriate for | their analyses. | | (3) In mixed systems, such as Germany or New Zealand, district | data refers to the constituency vote (as opposed to the | list-PR vote). | | (4) There are two versions of each district-level variable. | Most election studies are coded into E4001-E4007. For | polities that operate one nationwide electoral district, | district data are coded into variables E4001_N-E4007_N | to specifically highlight one nationwide district polities. | | +++ TABLE: SUMMARY OF POLITY AND WHICH ELECTION IN THAT POLITY | THAT THE DISTRICT DATA REFERS TO | | Presidential Lower House Upper House | POLITY (ELEC YEAR) Election Election Election | ------------------------------------------------------------- | ALBANIA (2017) - X - | AUSTRALIA (2019) - X - | AUSTRIA (2017) - X - | BELGIUM-FLANDERS (2019) - X - | BELGIUM-WALLONIA (2019) - X - | BRAZIL (2018) - X - | CANADA (2019) - X - | CHILE (2017) - X - | COSTA RICA (2018) - X - | CZECHIA (2017) - X - | CZECHIA (2021) - X - | DENMARK (2019) - X - | EL SALVADOR (2019) X - - | FINLAND (2019) - X - | FRANCE (2017) X - - | GERMANY (2017) - X - | GERMANY (2021) - X - | GREAT BRITAIN (2017) - X - | GREAT BRITAIN (2019) - X - | GREECE (2015) - X - | GREECE (2019) - X - | HONG KONG (2016) - X - | ICELAND (2016) - X - | ICELAND (2017) - X - | INDIA (2019) - X - | IRELAND (2016) - X - | ISRAEL (2020) - X - | ITALY (2018) - X - | JAPAN (2017) - X - | LATVIA (2018) - X - | LITHUANIA (2016) - X - | LITHUANIA (2020) - X - | MEXICO (2018) - X - | MONTENEGRO (2016) - X - | NETHERLANDS (2017) - X - | NETHERLANDS (2021) - X - | NEW ZEALAND (2017) - X - | NEW ZEALAND (2020) - X - | NORWAY (2017) - X - | PERU (2021) - X - | POLAND (2019) - X - | PORTUGAL (2019) - X - | ROMANIA (2016) - X - | SLOVAKIA (2020) - X - | SOUTH KOREA (2016) - X - | SWEDEN (2018) - X - | SWITZERLAND (2019) - X - | TAIWAN (2016) - X - | TAIWAN (2020) - X - | THAILAND (2019) - X - | TUNISIA (2019) - X - | TURKEY (2018) - X - | UNITED STATES (2016) X - - | UNITED STATES (2020) X - - | URUGUAY (2019) - X - | ------------------------------------------------------------- | KEY: X = yes; - = no. | | | +++ TABLE: TOTAL NUMBER OF ELECTORAL DISTRICTS PER POLITY AND | TOTAL NUMBER OF ELECTORAL DISTRICTS REPRESENTED IN | CSES DATA | | Total number of Total number of | POLITY (ELEC YEAR) Electoral Districts Electoral Districts | in Polity in CSES (%) | ------------------------------------------------------------- | ALBANIA (2017) 12 12 (100%) | AUSTRALIA (2019) 151 150 (99%) | AUSTRIA (2017) 39 39 (100%) | BELGIUM-FLANDERS (2019) 5 5 (100%) | BELGIUM-WALLONIA (2019) 5 5 (100%) | BRAZIL (2018) 27 27 (100%) | CANADA (2019) 338 327 (97%) | CHILE (2017) 28 28 (100%) | COSTA RICA (2018) 7 7 (100%) | CZECHIA (2017) 14 14 (100%) | CZECHIA (2021) 14 14 (100%) | DENMARK (2019) 10 10 (100%) | EL SALVADOR (2019) 14 14 (100%) | FINLAND (2019) 13 12 (92%) | FRANCE (2017) 1 1 (100%) | GERMANY (2017) 299 167 (56%) | GERMANY (2021) 299 164 (55%) | GREAT BRITAIN (2017) 650 222 (34%) | GREAT BRITAIN (2019) 650 399 (61%) | GREECE (2015) 56 54 (96%) | GREECE (2019) 59 59 (100%) | HONG KONG (2016) 5 5 (100%) | ICELAND (2016) 6 6 (100%) | ICELAND (2017) 6 6 (100%) | INDIA (2019) 543 304 (56%) | IRELAND (2016) 40 40 (100%) | ISRAEL (2020) 1 1 (100%) | ITALY (2018) 232 120 (52%) | JAPAN (2017) 289 183 (63%) | LATVIA (2018) 5 5 (100%) | LITHUANIA (2016) 71 65 (92%) | LITHUANIA (2020) 71 71 (100%) | MEXICO (2018) 300 121 (40%) | MONTENEGRO (2016) 1 1 (100%) | NETHERLANDS (2017) 1 1 (100%) | NETHERLANDS (2021) 1 1 (100%) | NEW ZEALAND (2017) 71 71 (100%) | NEW ZEALAND (2020) 72 72 (100%) | NORWAY (2017) 19 19 (100%) | PERU (2021) 26 26 (100%) | POLAND (2019) 41 40 (98%) | PORTUGAL (2019) 22 15 (68%) | ROMANIA (2016) 41 39 (95%) | SLOVAKIA (2020) 1 1 (100%) | SOUTH KOREA (2016) 253 116 (46%) | SWEDEN (2018) 29 29 (100%) | SWITZERLAND (2019) 26 26 (100%) | TAIWAN (2016) 74 37 (50%) | TAIWAN (2020) 74 36 (49%) | THAILAND (2019) 350 60 (17%) | TUNISIA (2019) 27 27 (100%) | TURKEY (2018) 87 47 (54%) | UNITED STATES (2016) 51 51 (100%) | UNITED STATES (2020) 51 51 (100%) | URUGUAY (2019) 19 19 (100%) | ------------------------------------------------------------- | | District identifier and data are unavailable for HUNGARY (2018). | | In polities using more than one electoral tier, district data | refer to the lower tier. (see variable E5056 for information | about the number of electoral tiers and further details about | the tiers). | | District data are unavailable for HUNGARY (2018). | ISRAEL (2020), MONTENEGRO (2016), the NETHERLANDS (2017 & 2021) | and SLOVAKIA (2020) use a single, nationwide district. | ALBANIA (2017), AUSTRALIA (2019), BELGIUM-FLANDERS (2019), | BELGIUM-WALLONIA (2019), BRAZIL (2018), CANADA (2019), | CHILE (2017), COSTA RICA (2018), FINLAND (2019), | GREAT BRITAIN (2017 & 2019), INDIA (2019), IRELAND (2016), | PORTUGAL (2019), ROMANIA (2016), SWITZERLAND (2019), TUNISIA | (2019), TURKEY (2018) and URUGUAY (2019) have only one electoral | tier. | The district data for EL SALVADOR (2019), FRANCE (2017) and | UNITED STATES (2016 & 2020) refer to the Presidential Election. | | | Used Sources on Election District Variables, if possible | including URL and date accessed. | [For more details on sources, see CODEBOOK INTRODUCTION]. | | ALBANIA (2017) | State Election Commissioner (the Commissioner) | http://results2017.cec.org.al/Parliamentary/Results?cs=en-US&r= | r&rd=r14&eu=3&m=All&ps=All&vc=All | Date accessed: December 21, 2022 | | AUSTRALIA (2019) | Australian Electoral Commission (AEC) | https://results.aec.gov.au/24310/Website/HouseDivisionalResults | -24310.htm | Date accessed: February 08, 2021 | | AUSTRIA (2017) | Austrian Minister of Interior | https://wahl17.bmi.gv.at/ | Date accessed: March 19, 2019 | | BELGIUM-FLANDERS (2019) | Federal Public Services Home Affairs | IBZ Official Results | https://elections2019.belgium.be/en | Date accessed: June 02, 2021 | | BELGIUM-WALLONIA (2019) | Federal Public Services Home Affairs | IBZ Official Results | https://elections2019.belgium.be/en | Date accessed: June 02, 2021 | | BRAZIL (2018) | Federal Electoral Court | http://www.tse.jus.br | Date accessed: March 30, 2020 | | CANADA (2019) | Elections Canada | https://www.elections.ca/content.aspx?section=ele&document=index | &dir=pas/43ge&lang=e | Date accessed: February 20, 2021 | | CHILE (2017) | Chile Electoral Commission - Servicio Electoral (SERVEL) | https://historico.servel.cl/ | Date accessed: March 25, 2019 | | COSTA RICA (2018) | Tribunal Supremo De Elecciones (TSE) - Republica de Costa Rica | https://www.tse.go.cr/zip/elecciones/computovotos_febrero_abril_ | 2018.zip | Date accessed: February 09, 2021 | | Czechia (2017) | Czech Statistical Office | https://volby.cz/pls/ps2017nss/ps?xjazyk=EN | Date accessed: November 11, 2022 | | CZECHIA (2021) | Czech Statistical Office | https://www.volby.cz/pls/ps2021/ps?xjazyk=EN | Date accessed: November 24, 2022 | | DENMARK (2019) | Statistics Denmark | https://www.dst.dk/valg/Valg1684447/other/startside.htm | Date accessed: December 10, 2021 | | FINLAND (2019) | Ministry of Justice | Information and Results Service | https://tulospalvelu.vaalit.fi/EKV-2019/en/lasktila.html | Date accessed: June 02, 2021 | | EL SALVADOR (2019) | Supreme Electoral Tribunal of El Salvador: | https://www.tse.gob.sv/elecci%C3%B3n-2019/inicio | Date accessed: January 25, 2023 | | FRANCE (2017) | French Ministry of the Interior | https://www.interieur.gouv.fr/Elections/Les- | resultats/Presidentielles/elecresult__presidentielle- | 2017/(path)/presidentielle-2017/FE.html | Date accessed: January 16, 2020 | | GERMANY (2017) | The Federal Returning Officer | https://www.bundeswahlleiter.de/en/bundestagswahlen/2017/ | ergebnisse.html | Date accessed: January 21, 2019 | | GERMANY (2021) | The Federal Returning Officer | https://www.bundeswahlleiter.de/en/bundestagswahlen/2021/ | ergebnisse.html | Date accessed: November 30, 2022 | | GREAT BRITAIN (2017) | House of Commons Library | https://commonslibrary.parliament.uk/research-briefings/cbp-7979/ | Date accessed: April 15, 2021 | | GREAT BRITAIN (2019) | House of Commons Library | https://commonslibrary.parliament.uk/research-briefings/cbp- | 8749/ | Date accessed: March 15, 2023 | | GREECE (2015) | Greek Ministry of Interior | http://ekloges.ypes.gr/current/v/public/index.html#{%22cls%22:% | 22eps%22,%22params%22:{}} | Date accessed: March 29, 2019 | | GREECE (2019) | Kollman, K., Hicken, A., Caramani, D., Backer, D., & Lublin, D. | 2020. Constituency-Level Elections Archive [Data set and | codebook]. Ann Arbor, MI: Center for Political Studies, | University of Michigan [producer and distributor]. Retrieved | from http://www.electiondataarchive.org. | Date accessed: March 06, 2023 | | HONG KONG (2016) | Registration and Electoral Office Hong Kong (2016). 2016 | Legislative Council Election - Election Results. | https://www.elections.gov.hk/legco2016/eng/rs_ | gc.html?1557348070641 | Date accessed: April 03, 2019 | | Registration and Electoral Office Hong Kong (2016). 2016 | Legislative Council Election - Introduction to Candidates. | https://www.elections.gov.hk/legco2016/eng/intro_to_can.html | Date accessed: April 03, 2019 | | ICELAND (2016) | Statistics Iceland (n.d.). Results of general elections to the | Althingi by constituency 2016. Available at: https://px. | hagstofa.is/pxen/pxweb/en/Ibuar/Ibuar__kosningar__althingi__ | althurslit/KOS02118b.px/?rxid=e8953ff6-758f-48f2-a403- | 836c64d6302f | Date accessed: June 27, 2019 | | Statistics Iceland (2016): General elections to the Althingi 29 | October 2016. Statistical Series, Vol.101(35). Available at: | https://statice.is/publications/publication/elections/general- | elections-to-the-althingi-29-october-2016/ | Date accessed: June 29, 2019 | | ICELAND (2017) | Statistics Iceland (n.D.): Participation by sex, age and | constituency in general elections 2016 and 2017. Available at: | https://px.hagstofa.is/pxen/pxweb/en/Ibuar/Ibuar__kosningar__ | althingi__althkjosendur/KOS02101a.px/?rxid=535ef7b1-ee20- | Date accessed: September 10, 2019 | | Statistics Iceland (n.D.): Results of general elections to the | Althingi by constituency 2017, available at: https://px.hagstofa | .is/pxen/pxweb/en/Ibuar/Ibuar__kosningar__althingi__althurslit/ | KOS02118a.px/?rxid=535ef7b1-ee20-41c0- | Date accessed: September 10, 2019 | | INDIA (2019) | Kollman, K., Hicken, A., Caramani, D., Backer, D., & Lublin, D. | 2020. Constituency-Level Elections Archive [Data set and | codebook]. Ann Arbor, MI: Center for Political Studies, | University of Michigan [producer and distributor]. Retrieved | from http://www.electiondataarchive.org. | Date accessed: February 23, 2023 | | IRELAND (2016) | Houses of the Oireachtas (2016): Election 2016. 32nd Dail | General Election 26 February 2016. Election Results. | https://data.oireachtas.ie/ie/oireachtas/electoralProcess/ | electionResults/dail/2016/2016-04-28_32nd-dail-general-election- | results_en.pdf | Date accessed: January 28, 2019 | | Elections Ireland (n.D.): General Election of 26 February 2016. | https://www.electionsireland.org/results/general/32dail.cfm | Date accessed: January 18, 2019 | | ITALY (2018) | Italian Department of Internal and Territorial Affairs | https://elezionistorico.interno.gov.it/index.php?tpel=C&dtel=04/ | 03/2018&tpa=I&tpe=I&lev0=0&levsut0=0&lev1=1&levsut1=1&ne1=1&es0= | S&es1=S&ms=S | Date accessed: February 10, 2019 | | JAPAN (2017) | Japan Ministry of Internal Affairs and Communications | https://www.soumu.go.jp/senkyo/48sansokuhou/ | Date accessed: December 17, 2021 | | LATVIA (2018) | Central Election Commission of Latvia | https://www.cvk.lv/en | Date accessed: May 06, 2023 | | LITHUANIA (2016) | The Central Electoral Commission of the Republic of Lithuania | https://www.vrk.lt/en/2016-seimo/rezultatai | Date accessed: March 24, 2019 | | LITHUANIA (2020) | The Central Electoral Commission of the Republic of Lithuania and | Residents' Register Service under the Ministry of the Interior of | the Republic of Lithuania - Voter's Page | https://www.rinkejopuslapis.lt/ataskaitos62 | Date accessed: May 17, 2022 | | The Central Electoral Commission of the Republic of Lithuania | https://www.vrk.lt/en/2020-seimo/rezultatai | Date accessed: May 17, 2022 | | MEXICO (2018) | Instituto Nacional Electoral (Mexican Electoral Commission). | 2018. "Computos Distritales 2018. Elecciones Federales. | Diputaciones - Distritos por Entidad." | https://computos2018.ine.mx/#/diputaciones/distrito/1/3/4/1 | Date accessed: March 15, 2023 | | MONTENEGRO (2016) | Electoral Commission of Montenegro | http://www.dik.co.me/ | Date accessed: January 19, 2019 | | NETHERLANDS (2017) | Kiesraad (Dutch Electoral Council) | Uitslag van de verkiezing van de leden van de Tweede Kamer van | 15 maart 2017. Kerngegevens. | https://www.kiesraad.nl/adviezen-en-publicaties/rapporten/2017/3/ | kerngegevens-tweede-kamerverkiezing-2017/kerngegevens-tweede- | kamerverkiezing-2017 | Date accessed: October 13, 2021 | | NETHERLANDS (2021) | Kiesraad (Dutch Electoral Council) | Databank Verkiezingsuitslagen. Tweede Kamer 17 maart 2021. | https://www.verkiezingsuitslagen.nl/verkiezingen/detail/ | TK20210317 | Date accessed: October 31, 2022 | | Kiesraad (Dutch Electoral Council) | Elections of the House of Representatives. | https://english.kiesraad.nl/latest-news/news/2021/3/11/ | elections-of-the-house-of-representatives | Date accessed: October 31, 2022 | | NEW ZEALAND (2017) | New Zealand Electoral Commission | https://www.electionresults.org.nz/electionresults_2017/ | Date accessed: October 29, 2019 | | NEW ZEALAND (2020) | New Zealand Electoral Commission | https://www.electionresults.govt.nz/electionresults_2020/ | Date accessed: November 30, 2021 | | NORWAY (2017) | Norwegian Directorate of Elections (VALG) | https://valgresultat.no/(menu:navigate)?type=ko&year=2017 | Date accessed: January 15, 2020 | | PERU (2021) | Peruvian National Office of Electoral Processes | https://resultadoshistorico.onpe.gob.pe/EG2021/ | Date accessed: November 09, 2022 | | POLAND (2019) | National Electoral Commission | https://sejmsenat2019.pkw.gov.pl/sejmsenat2019/en | Date accessed: December 15, 2022 | | PORTUGAL (2019) | Portuguese National Election Commission (CNE) | https://www.cne.pt/content/eleicoes-para-assembleia-da- | republica-2019 | Date accessed: April 06, 2021 | | ROMANIA (2016) | Constituency-Level Elections Archive (CLEA) | http://electiondataarchive.org/datacenter.html | Date accessed: February 19, 2023 | | SLOVAKIA (2020) | National Council of the Slovak Republic | https://volby.statistics.sk/nrsr/nrsr2020/en/index.html | Date accessed: September 29, 2021 | | SOUTH KOREA (2016) | Republic of Korea National Election Commission | http://info.nec.go.kr/electioninfo/electionInfo_report.xhtml | Date accessed: April 05, 2019 | | SWEDEN (2018) | Swedish Election Authority (Valmyndigheten) | https://data.val.se/val/val2018/slutresultat/R/rike/index.html | Date accessed: March 05, 2021 | | SWITZERLAND (2019) | Federal Statistical Office | https://www.bfs.admin.ch/bfs/de/home/statistiken/politik/wahlen | /eidg-wahlen-2019.html | Date accessed: March 12, 2021 | | TAIWAN (2016) | Constituency-Level Elections Archive (CLEA) | http://www.electiondataarchive.org/ | Date accessed: March 26, 2019 | | TAIWAN (2020) | Election Study Center, NCCU | http://vote.nccu.edu.tw/engcec/cechead.asp | Date accessed: June 01, 2021 | | THAILAND (2019) | Election Commission of Thailand | https://www.ect.go.th/ect_th/download/article/article_ | 20201002121233.pdf | Date accessed: March 28, 2023 | | TUNISIA (2019) | Instance Superieure Independante pour les Elections | http://www.isie.tn/actualites/2019/11/08/les-resultats- | definitifs-des-elections-legislatives-2019/ | Date accessed: November 17, 2021 | | TURKEY (2018) | Turkish Supreme Election Council | http://www.ysk.gov.tr/tr/24-haziran-2018-secimleri/77536 | Date accessed: December 16, 2019 | | UNITED STATES (2016) | Federal Election Commission | https://transition.fec.gov/general/FederalElections2016.shtml | Date accessed: May 08, 2019 | | United States Elections Project | http://www.electproject.org/2016g | Date accessed: March 17, 2019 | | UNITED STATES (2020) | Federal Election Commission | https://www.fec.gov/resources/cms-content/documents/ | 2020presgeresults.pdf | Date accessed: September 16, 2021 | | United States Elections Project | http://www.electproject.org/2020g | Date accessed: September 17, 2021 | | URUGUAY (2019) | Electoral Court of Uruguay | https://www.corteelectoral.gub.uy/ | Date accessed: September 14, 2021 --------------------------------------------------------------------------- E4001 >>> NUMBER OF SEATS IN DISTRICT --------------------------------------------------------------------------- The number of seats contested in district. .................................................................. 001-900. NUMBER OF SEATS CONTESTED IN ELECTORAL DISTRICT 997. NOT APPLICABLE 999. MISSING | VARIABLE NOTES: E4001 | | E4001 details the number of seats contested in each district of | the first segment of the lower house of the legislature. | ELECTION STUDY NOTES - AUSTRIA (2017): E4001 | | The data represents the first electoral tier (Regionalwahl- | kreis). Seats in Austria are distributed across three tiers | (Regionalwahlkreis-tier 1; Landwahlkreis-tier 2; and the | federal level-tier 3). To win seats (the constituencies at the | Regionalwahlkreis are multi-seat constituencies), a party | must reach a quota(s). The quota is calculated by dividing | the number of valid votes cast in the Landwahlkreis (tier 2) | that the said Regionalwahlkreis is in, by the number of seats | allocated to the Landwahlkreis (tier 2) in total. If no party | surpasses this quota, no seat is allocated at tier 1 and these | votes go into the mix in deciding the allocation of seats at | the Landwahlkreis (tier 2). Hence, the number of seats that | parties may have won (E4005_A-E4005_F) in a district may differ | from the number of seats which parties compete for at the lowest | tier (E4001). | ELECTION STUDY NOTES - UNITED STATES (2016 & 2020): E4001 | | E4001 reports the number of electoral college votes | allocated to each state in the U.S. Presidential election and not | the number of congressional seats in each district. | Considering that the United States uses an electoral college | system that operates on the state level, district data was | collected accordingly. The U.S. state a respondent lives in is | coded in E2020 (REGION OF RESIDENCE). Variable E2021 reports the | respondent's lower house district. --------------------------------------------------------------------------- E4001_N >>> NUMBER OF SEATS IN DISTRICT - NATIONWIDE ELECTORAL DISTRICT --------------------------------------------------------------------------- The number of seats contested in nationwide electoral district. .................................................................. 001-900. NUMBER OF SEATS CONTESTED IN ELECTORAL DISTRICT 997. NOT APPLICABLE: NO NATIONWIDE DISTRICT 999. MISSING | VARIABLE NOTES: E4001_N | | E4001_N details the number of seats contested in each district | in the first tier of the lower house elections for polities | operating a nationwide electoral district. --------------------------------------------------------------------------- E4002 >>> NUMBER OF CANDIDATES IN DISTRICT --------------------------------------------------------------------------- The number of candidates contesting seats in district. .................................................................. 0001-9000. NUMBER OF CANDIDATES WHO CONTESTED THE ELECTION IN THIS ELECTORAL DISTRICT 9997. NOT APPLICABLE 9999. MISSING | VARIABLE NOTES: E4002 | | E4002 details the number of candidates who contested seats in | each district. Data are reported for electoral systems where | voters cast ballots for candidates directly and in PR-list | systems where voters may cast a candidate preference vote (i.e., | where a voter can indicate a candidate from a party list, in | addition to casting a ballot for a party list). | | Data are unavailable for URUGUAY (2019). | ELECTION STUDY NOTES - EL SALVADOR (2019): E4002 | | This variable reports the number of Presidential candidates in | each electoral district. | ELECTION STUDY NOTES - UNITED STATES (2016): E4002 | | This variable reports the number of candidates in the federal | state instead of in respondents' electoral district. | | For some states, the official election results | published by the Federal Election Commission | (https://transition.fec.gov/general/FederalElections2016.shtml; | Date accessed: May 08, 2019) indicate that there were more | candidates than named in the document by including a 'scattered', | 'others', or 'miscellaneous' category. | This is the case for the states of Alabama, Alaska, | Delaware, the District of Columbia, Iowa, Maryland, | Massachusetts, Minnesota, Nebraska, Nevada, New Hampshire, | New York, North Carolina, North Dakota, Oregon, Pennsylvania, | Rhode Island, Vermont, Virginia, Washington, Wisconsin, and | Wyoming. Such candidates are not included in E4002. | ELECTION STUDY NOTES - UNITED STATES (2020): E4002 | | This variable reports the number of candidates in the federal | state instead of in respondents' electoral district. | | For some states, the official election results | published by the Federal Election Commission | (https://www.fec.gov/resources/cms-content/documents/ | 2020presgeresults.pdf; Date accessed: September 16, 2021) | indicate that there were more candidates than named in the | document by including a 'scattered' category summarizing | write-in votes. Such candidates are not included in E4002. --------------------------------------------------------------------------- E4002_N >>> NUMBER OF CANDIDATES IN DISTRICT - NATIONWIDE ELECTORAL DISTRICT --------------------------------------------------------------------------- The number of candidates contesting seats in nationwide district. .................................................................. 0001-9000. NUMBER OF CANDIDATES WHO CONTESTED THE ELECTION IN THIS ELECTORAL DISTRICT 9997. NOT APPLICABLE: NO NATIONWIDE DISTRICT 9999. MISSING | VARIABLE NOTES: E4002_N | | E4002_N details the number of candidates who contested seats for | for countries operating only one nationwide electoral district. | These data are reported for electoral systems where voters cast | ballots for candidates directly and in PR-list systems where | voters may cast a candidate preference vote (i.e., where a voter | can indicate a candidate from a party list, in addition to | casting a ballot for a party list) nationwide. --------------------------------------------------------------------------- E4003 >>> NUMBER OF PARTY LISTS IN DISTRICT --------------------------------------------------------------------------- The number of parties presenting lists in district. .................................................................. 001-900. NUMBER OF PARTIES THAT PRESENTED A LIST OF CANDIDATES IN THE ELECTION IN THIS ELECTORAL DISTRICT 997. NOT APPLICABLE 999. MISSING | VARIABLE NOTES: E4003 | | E4003 details the number of parties that presented lists and, | thereby, contested seats in each district. | These data are only relevant for PR-list electoral systems | where voters cast ballots for party lists. Countries that do not | employ a pure PR-list system or any form of mixed electoral | system are classified as "997. NOT APPLICABLE". | ELECTION STUDY NOTES - SWEDEN (2018): E4003 | | For Sweden 2018, this variable provides the number of parties | which registered participation before the election, as required | by the Swedish Election Authority. | The Swedish system allows for apparentment in which multiple | lists with the same party label in a given constituency can form | a cartel. In these cases, parties were only counted once, in | line with this variable's intention to count the parties that | presented lists rather than the total number of lists provided | by parties. --------------------------------------------------------------------------- E4003_N >>> NUMBER OF PARTY LISTS IN DISTRICT - NATIONWIDE ELECTORAL DISTRICT --------------------------------------------------------------------------- The number of parties presenting lists in nationwide district. .................................................................. 001-900. NUMBER OF PARTIES THAT PRESENTED A LIST OF CANDIDATES IN THE ELECTION IN THIS ELECTORAL DISTRICT 997. NOT APPLICABLE: NO NATIONWIDE DISTRICT 999. MISSING | VARIABLE NOTES: E4003_N | | E4003_N details the number of parties that presented lists and, | thereby, contested seats for polities operating a nationwide | electoral district. | These data are only relevant for PR-list electoral systems where | voters cast ballots for party lists and where the country has a | single electoral constituency with the country operating as a | nationwide district. Countries that do not employ a PR-list | system are classified as "997. NOT APPLICABLE." --------------------------------------------------------------------------- E4004_A >>> PERCENT VOTE IN DISTRICT - PARTY A E4004_B >>> PERCENT VOTE IN DISTRICT - PARTY B E4004_C >>> PERCENT VOTE IN DISTRICT - PARTY C E4004_D >>> PERCENT VOTE IN DISTRICT - PARTY D E4004_E >>> PERCENT VOTE IN DISTRICT - PARTY E E4004_F >>> PERCENT VOTE IN DISTRICT - PARTY F E4004_G >>> PERCENT VOTE IN DISTRICT - PARTY G E4004_H >>> PERCENT VOTE IN DISTRICT - PARTY H E4004_I >>> PERCENT VOTE IN DISTRICT - PARTY I --------------------------------------------------------------------------- The proportion of votes cast in favor of PARTY [A/B/C/D/E/F/G/H/I] in district (first round). .................................................................. 000.00-100.00 PERCENT (0.00% TO 100.00%) OF THE VALID BALLOTS CAST IN THIS DISTRICT THAT WERE CAST IN FAVOR OF PARTY [A/B/C/D/E/F] 997.00 NOT APPLICABLE 999.00. MISSING | VARIABLE NOTES: E4004_ | | Parties and their alphabetical classifications for each election | study are detailed in Part 3 of the CSES Codebook. | | E4004_ details the proportion of votes cast in favor of PARTIES | A-I in each district. In majoritarian systems in which more than | one round of elections are held, E4004_ refers to the FIRST | round. | | Data are unavailable for TUNISIA (2019). | ELECTION STUDY NOTES - AUSTRALIA (2019): E4004_ | | E4004_ report the percentage of first preference votes by | district in the election. | ELECTION STUDY NOTES - CZECHIA (2021): E4004_ | | E4004_A refers to the SPOLU alliance. E4004_C refers to the | PirStan alliance. | Parties 203196. TOP 09 (PARTY G), and 203197. Christian and | Democratic Union- Czechoslovak People's Party - KDU-CSL (PARTY | H), and 203198. Mayors and Independents - STAN (PARTY I) are | coded "997. Not applicable" for E4004_G, E4004_H and E4004_I as | they contested as part of the electoral alliances SPOLU and | PirStan in the 2021 election. | ELECTION STUDY NOTES - LITHUANIA (2016): E4004_E | | District data for PARTY E refers to the Lithuanian Center Party | for the variable E4004_E. This party is the biggest constituting | member of the Anti-Corruption Coalition. They competed | independently in single-member constituencies, and as a member | of the Anti-Corruption Coalition in Nationwide constituency. | ELECTION STUDY NOTES - TAIWAN (2016): E4004_F & E4004_G | | Parties 158006. People First Party - PFP (PARTY F), and | 158007. Taiwan Solidarity Union - TSU (PARTY G) did not | contest in the districts sampled for the Taiwan (2016) study. | Hence E4004_F and E4004_G are coded "997. Not applicable." | ELECTION STUDY NOTES - UNITED STATES (2016): E4004_ | | E4004_ reports the results of the Presidential election | in the federal states. The results published reflect those | as published by the Federal Election Commission | (https://transition.fec.gov/general/FederalElections2016.shtml). | (Date accessed: April 30, 2020) | ELECTION STUDY NOTES - UNITED STATES (2020): E4004_ | | E4004_ reports the results of the Presidential election | in the federal states. The results published reflect those | as published by the Federal Election Commission | (https://www.fec.gov/resources/cms-content/documents/ | 2020presgeresults.pdf, Date accessed: September 16, 2021) --------------------------------------------------------------------------- E4004_A_N >>> PERCENT VOTE IN DISTRICT - PARTY A - NATIONWIDE ELECTORAL DISTRICT E4004_B_N >>> PERCENT VOTE IN DISTRICT - PARTY B - NATIONWIDE ELECTORAL DISTRICT E4004_C_N >>> PERCENT VOTE IN DISTRICT - PARTY C - NATIONWIDE ELECTORAL DISTRICT E4004_D_N >>> PERCENT VOTE IN DISTRICT - PARTY D - NATIONWIDE ELECTORAL DISTRICT E4004_E_N >>> PERCENT VOTE IN DISTRICT - PARTY E - NATIONWIDE ELECTORAL DISTRICT E4004_F_N >>> PERCENT VOTE IN DISTRICT - PARTY F - NATIONWIDE ELECTORAL DISTRICT E4004_G_N >>> PERCENT VOTE IN DISTRICT - PARTY G - NATIONWIDE ELECTORAL DISTRICT E4004_H_N >>> PERCENT VOTE IN DISTRICT - PARTY H - NATIONWIDE ELECTORAL DISTRICT E4004_I_N >>> PERCENT VOTE IN DISTRICT - PARTY I - NATIONWIDE ELECTORAL DISTRICT --------------------------------------------------------------------------- The proportion of votes cast in favor of PARTY [A/B/C/D/E/F/G/H/I] in nationwide district (first round). .................................................................. 000.00-100.00 PERCENT (0.00% TO 100.00%) OF THE VALID BALLOTS CAST IN THIS DISTRICT THAT WERE CAST IN FAVOR OF PARTY [A/B/C/D/E/F] 997.00 NOT APPLICABLE: NO NATIONWIDE DISTRICT 999.00. MISSING | VARIABLE NOTES: E4004_A-I_N | | Parties and their alphabetical classifications for each election | study are detailed in Part 3 of the CSES Codebook. | | E4004_A-I_N details the proportion of votes cast in favor of | PARTIES A-I for polities operating a nationwide district. In | majoritarian systems in which more than one round of elections | are held, E4004_A-I_N refers to the FIRST round. --------------------------------------------------------------------------- E4005_A >>> SEATS IN DISTRICT - PARTY A E4005_B >>> SEATS IN DISTRICT - PARTY B E4005_C >>> SEATS IN DISTRICT - PARTY C E4005_D >>> SEATS IN DISTRICT - PARTY D E4005_E >>> SEATS IN DISTRICT - PARTY E E4005_F >>> SEATS IN DISTRICT - PARTY F E4005_G >>> SEATS IN DISTRICT - PARTY G E4005_H >>> SEATS IN DISTRICT - PARTY H E4005_I >>> SEATS IN DISTRICT - PARTY I --------------------------------------------------------------------------- The number of seats gained by PARTY [A/B/C/D/E/F/G/H/I] in district. .................................................................. 00-99. SEATS 997. NOT APPLICABLE 999. MISSING | VARIABLE NOTES: E4005_ | | Parties and their alphabetical classifications for each election | study are detailed in Part 3 of the CSES Codebook. | ELECTION STUDY NOTES - AUSTRALIA (2019): E4005_ | | For the Australian 2019 lower house election, there are five | districts in which candidates not affiliated with PARTY A-F won: | Clark, Indi, Kennedy, Mayo, and Warringah. | Hence, variables E4005_A-F are coded 0 for all respondents from | these five districts. The table below lists the winning | candidates in these districts and their party affiliation, if | applicable: | | E2021 Code and District Winning Candidate (Party) |---------------------------------------------------------------- | 00144. Clark Andrew Wilkie (Independent) | 00069. Indi Helen Haines (Independent) | 00102. Kennedy Bob Katter (Katter's Australia Party) | 00123. Mayo Rebekha Sharkie (Centre Alliance) | 00043. Warringah Zali Steggall (Independent) | ELECTION STUDY NOTES - CZECHIA (2021): E4005_ | | E4005_A refers to the SPOLU alliance. E4005_C refers to the | PirStan alliance. | Parties 203196. TOP 09 (PARTY G), and 203197. Christian and | Democratic Union- Czechoslovak People's Party - KDU-CSL (PARTY | H), and 203198. Mayors and Independents - STAN (PARTY I) are | coded "997. Not applicable" for E4005_G, E4005_H and E4005_I as | they contested as part of the electoral alliances SPOLU and | PirStan in the 2021 election. | ELECTION STUDY NOTES - ITALY (2018): E4005_A-E4005_F | | Parties which fielded a district candidate as part of one of the | two alliances were coded as having won the district seat if the | alliance candidate won. Consequently, districts with only | one seat will classify all parties members of the alliance | as having won the district. For example, if a candidate from the | Centre-Right coalition won a district, all members of the | alliance are classified as having won the district and assigned a | score of 1 on this variable. | ELECTION STUDY NOTES - LITHUANIA (2016): E4005_E | | District data for PARTY E refer to Lithuanian Center Party for | the variable E4005_E. This party is the largest party comprising | the Anti-Corruption Coalition. They competed independently | in single-member constituencies, and as a member of the Anti- | Corruption Coalition in the nationwide constituency. | ELECTION STUDY NOTES - SWEDEN (2018): E4005_ | | These data report the number of seats won by PARTY A to PARTY I | in the lower electoral tier that returns 310 seats from 29 | multi-member districts. The Swedish Election Authority | refers to these seats as "fasta mandaten" ("fixed seats"). | ELECTION STUDY NOTES - UNITED STATES (2016): E4005_ | | Instead of the number of seats gained by party, E4005_ reports | the number of electoral college votes obtained by the | Presidential candidates of the 2016 U.S. Presidential Election. | Instead of voting for a nominated candidate, ten electors | deviated by voting for John Kasich (Texas, one vote), | Ron Paul (Texas, one vote), Bernie Sanders (Hawaii, one vote), | Colin Powell (Washington, three votes) and Faith Spotted Eagle | (Washington, one vote). These votes were disregarded for E4005_. | ELECTION STUDY NOTES - UNITED STATES (2020): E4005_ | | Instead of the number of seats gained by party, E4005_ reports | the number of electoral college votes obtained by the | Presidential candidates of the 2020 U.S. Presidential Election. | Unlike in 2016, there were no faithless electors for the 2020 | election. --------------------------------------------------------------------------- E4005_A_N >>> SEATS IN DISTRICT - PARTY A - NATIONWIDE ELECTORAL DISTRICT E4005_B_N >>> SEATS IN DISTRICT - PARTY B - NATIONWIDE ELECTORAL DISTRICT E4005_C_N >>> SEATS IN DISTRICT - PARTY D - NATIONWIDE ELECTORAL DISTRICT E4005_E_N >>> SEATS IN DISTRICT - PARTY E - NATIONWIDE ELECTORAL DISTRICT E4005_F_N >>> SEATS IN DISTRICT - PARTY F - NATIONWIDE ELECTORAL DISTRICT E4005_G_N >>> SEATS IN DISTRICT - PARTY G - NATIONWIDE ELECTORAL DISTRICT E4005_H_N >>> SEATS IN DISTRICT - PARTY H - NATIONWIDE ELECTORAL DISTRICT E4005_I_N >>> SEATS IN DISTRICT - PARTY I - NATIONWIDE ELECTORAL DISTRICT --------------------------------------------------------------------------- The number of seats gained by party [A/B/C/D/E/F/G/H/I] in nationwide district. .................................................................. 00-99. SEATS 997. NOT APPLICABLE: NO NATIONWIDE DISTRICT 999. MISSING | VARIABLE NOTES: E4005_A-I_N | | Parties and their alphabetical classifications for each election | study are detailed in Part 3 of the CSES Codebook. | | E4005_A-I_N details the number of seats gained by PARTIES A-I | for polities operating a nationwide electoral district. --------------------------------------------------------------------------- E4006 >>> TURNOUT IN DISTRICT --------------------------------------------------------------------------- The official voter turnout in district. .................................................................. 000.00-100.00 PERCENT OF VOTER TURNOUT BY DISTRICT 997.00. NOT APPLICABLE 999.00. MISSING | VARIABLE NOTES: E4006 | | Users should note that official turnout figures are calculated | using different formulas. For instance, the denominator sometimes | includes the total number of the voting age population, while | other times it is the total number of registered voters. | | Data are unavailable for TUNISIA (2019). | ELECTION STUDY NOTES - AUSTRALIA (2019): E4006 | | For the 2019 Australian legislative election, turnout by district | is calculated with the denominator being the number of enrolled | voters, as provided by the Australian Electoral Commission: | https://results.aec.gov.au/24310/Website/Downloads/HouseTurnout | ByDivisionDownload-24310.csv (Date accessed: February 08, 2021). | ELECTION STUDY NOTES - NEW ZEALAND (2017): E4006 | | This variable indicates the turnout in the parliamentary | election by district. | | The turnout is calculated with the denominator being | the electoral population. | | Data from the New Zealand Electoral Commission is used | (see: https://www.electionresults.org.nz/electionresults_2017/, | Date accessed: October 17, 2019). | The webpage also provides information on the electors on | master roll on which their calculated turnout is based. | However, we want to consider the complete electoral | population. Analysts may refer to the website link above to | access this data. | ELECTION STUDY NOTES - TURKEY (2018): E4006 | | On the electoral district level, data on the number of | registered voters for the 2018 general Turkish election slightly | differ between the Supreme Electoral Council, Turkey's electoral | management body, and the Turkish Statistical Institute, the | Turkish government agency publishing official statistics. | Consequently, estimates for turnout based on the percentage of | registered voters (ER) also differ between the two sources. | Our estimates for E4006 and E4007 are based on data from the | Supreme Electoral Council. | ELECTION STUDY NOTES - UNITED STATES (2016): E4006 | | This variable indicates the turnout in the Presidential | election by federal state. | | The turnout is calculated with the denominator being | the Voting Age Population (VAP). | | A different source other than the Federal Election Commission | had to be consulted for E4006 as the Federal Election | Commission does not provide an estimate of the size of the | the electorate, hence making an estimate of turnout impossible. | Instead, data from the United States Elections | Project by Michael McDonald is used | (see: http://www.electproject.org/2016g, Date accessed: March | 17, 2019). For some states, the total number of votes in the | Presidential elections differed from the numbers indicated by | the U.S. Federal Election Commission. | The American Elections Project also provides information | on the voting eligible population (VEP), which calculates | turnout based on eligibility, rather than the Voting Age | Population. Analysts may refer to the website link above to | access this data. | ELECTION STUDY NOTES - UNITED STATES (2020): E4006 | | This variable indicates the turnout in the Presidential | election by federal state. The turnout is calculated with the | denominator being the voting age population (VAP). | | A different source other than the Federal Election Commission | had to be consulted for E4006 as the Federal Election | Commission does not provide an estimate of the size of the | the electorate, hence making an estimate of turnout impossible. | Instead, data from the United States Elections Project by Michael | McDonald is used (see: http://www.electproject.org/2020g, | Date accessed: September 17, 2021). | | For some states, the total number of votes in the Presidential | election differed from the numbers indicated by the U.S. Federal | Election Commission. | Users are advised that for Montana, McDonald reported turnout for | the U.S. Senate election as the highest office since that race | had the highest turnout. Further, turnout for Pennsylvania does | not yet include write-in votes, while Kansas reported write-in | votes for Sedgwick and Wyandotte counties only in their precinct | results, which are included in the highest office vote total. | | The American Elections Project also provides information | on the voting eligible population (VEP), which calculates | turnout based on eligibility, rather than the Voting Age | Population. Analysts may refer to the website link above to | access this data. --------------------------------------------------------------------------- E4006_N >>> TURNOUT IN DISTRICT - NATIONWIDE ELECTORAL DISTRICT --------------------------------------------------------------------------- The official voter turnout in nationwide district. .................................................................. 000.00-100.00 PERCENT OF VOTER TURNOUT BY DISTRICT 997.00. NOT APPLICABLE: NO NATIONWIDE DISTRICT 999.00. MISSING | VARIABLE NOTES: E4006_N | | E4006_N details official voter turnout for polities operating a | nationwide electoral district. | | Users should note that official turnout figures are calculated | using different formulas. For instance, the denominator sometimes | includes the total number of the voting age population, while | other times it is the total number of registered voters. --------------------------------------------------------------------------- E4007 >>> SIZE OF ELECTORATE OR POPULATION IN DISTRICT --------------------------------------------------------------------------- The size of the electorate in district. .................................................................. 00,000,000.-90,000,000. SIZE OF ELECTORATE 99,999,997. NOT APPLICABLE 99,999,999. MISSING | ELECTION STUDY NOTES - AUSTRALIA (2017): E4007 | | Data refers to the number of enrolled voters in each electoral | district. | ELECTION STUDY NOTES - AUSTRIA (2017): E4007 | | Data refers to the number of eligible voters in each electoral | district. | ELECTION STUDY NOTES - EL SALVADOR (2019): E4007 | | Data refers to the number of registered voters in each electoral | district. | ELECTION STUDY NOTES - TURKEY (2018): E4007 | | On the electoral district level, data on the number of | registered voters for the 2018 general Turkish election slightly | differ between the Supreme Electoral Council, Turkey's electoral | management body, and the Turkish Statistical Institute, the | Turkish government agency publishing official statistics. | Our estimates for E4007 are based on data from the | Supreme Electoral Council. | ELECTION STUDY NOTES - UNITED STATES (2016): E4007 | | This variable indicates the Voting Age Population (VAP) in the | 2016 Presidential election by federal state. | | A different source other than the Federal Election Commission | had to be consulted for E4007 as the Federal Election | Commission does not provide an estimate of the size of the | the electorate. Instead, data from the United States Elections | Project by Michael McDonald is used | (see: http://www.electproject.org/2016g, Date accessed: March | 17, 2019). | The American Elections Project also provides information | on the Voting Eligible Population (VEP). Analysts may refer to | the website link above to access this data. | ELECTION STUDY NOTES - UNITED STATES (2020): E4007 | | This variable indicates the Voting Age Population (VAP) in the | 2020 Presidential election by federal state. | | A different source other than the Federal Election Commission | had to be consulted for E4007 as the Federal Election | Commission does not provide an estimate of the size of the | the electorate. Instead, data from the United States Elections | Project by Michael McDonald is used | (see: http://www.electproject.org/2020g, Date accessed: | September 17, 2021). | The American Elections Project also provides information | on the Voting Eligible Population (VEP). Analysts may refer to | the website link above to access this data. --------------------------------------------------------------------------- E4007_N >>> SIZE OF ELECTORATE OR POPULATION IN DISTRICT - NATIONWIDE ELECTORAL DISTRICT --------------------------------------------------------------------------- The size of the electorate in nationwide district. .................................................................. 00,000,000.-90,000,000. SIZE OF ELECTORATE 99,999,997. NOT APPLICABLE: NO NATIONWIDE DISTRICT 99,999,999. MISSING | VARIABLE NOTES: E4007_N | | E4007_N details the size of the electorate for polities operating | a nationwide electoral district. =========================================================================== ))) CSES MODULE 5 VARIABLES: MACRO-LEVEL DATA =========================================================================== I. RELATIONAL DATA - ALPHABETICAL IDENTIFIERS --------------------------------------------------------------------------- E5000_A >>> PARTY A IDENTIFIER - NUMERICAL E5000_B >>> PARTY B IDENTIFIER - NUMERICAL E5000_C >>> PARTY C IDENTIFIER - NUMERICAL E5000_D >>> PARTY D IDENTIFIER - NUMERICAL E5000_E >>> PARTY E IDENTIFIER - NUMERICAL E5000_F >>> PARTY F IDENTIFIER - NUMERICAL E5000_G >>> PARTY G IDENTIFIER - NUMERICAL E5000_H >>> PARTY H IDENTIFIER - NUMERICAL E5000_I >>> PARTY I IDENTIFIER - NUMERICAL --------------------------------------------------------------------------- Numeric Party Code Identifier for Parties A-I (see variable notes). .................................................................. 008001-858009. PARTY/COALITION NUMERICAL IDENTIFIER [SEE PART 3 OF CODEBOOK FOR NUMERICAL PARTY/ COALITION CODES] 999999. MISSING | VARIABLE NOTES: E5000_ | | CSES policy is that for alphabetical codes, parties A through F | are the six most popular parties/coalitions, ordered in | descending order of their share of the popular vote in the | parliamentary election (unless otherwise stated). Parties G, H, | and I are supplemental parties. They may, but do not have to, | accord with how parties A-F are ordered and often reflect | important or notable parties within a country or members of | party coalitions. | As codes in E5000_ are labeled with the corresponding party | names, they allow for easy identification of the relational data. | | For the CSES MODULE 5 dataset, alphabetical codes are used to | identify the following: | - Respondent's likability of the party/coalition | (variable E3017_). | - Respondent's left-right placement of the party/coalition | (variable E3019_). | - Respondent's placement of the party/coalition on alternative | scale (variable E3021_). | - District data: percentage of vote for each party/coalition | in district (variable E4004_). | - District data: number of seats for each party/coalition | in district (variable E4005_). | - Election Results: percentage of vote for each party/coalition | in lower house (variable E5001_). | - Election Results: percentage of seats for each party/coalition | in lower house (variable E5002_). | - Election Results: percentage of vote for each party/coalition | in upper house (variable E5003_). | - Election Results: percentage of seats for each party/coalition | in upper house (variable E5004_). | - Election Results: percentage of vote for each party/coalition | in Presidential election (variable E5005_). | - Number of cabinet portfolios held by each party/coalition | before the election (variable E5011_). | - Number of cabinet portfolios held by each party/coalition after | the election (variable E5015_). | - Expert judgments by the national Collaborators of the said | party/coalition's ideological family placement | (variable E5017_). | - Expert judgments by the national Collaborators of the | said party/coalition's left-right placement (variable | E5018_). | - Expert judgments by the national Collaborators of the | said party/coalition's placement on alternative scale | (variable E5019_). | - Expert judgments by the national Collaborators of the | said party/coalition's placement on populism scale | (variable E5020_). | - Manifesto research on political representation identifier | for each party/coalition (variable E5200_). | - Parliaments and Governments (ParlGov) identifier for each | party/coalition (variable E5201_). | - The said party/coalition's Chapel Hill Expert Survey (CHES) | Identifier (variable E5202). | - The said party/coalition's Party Facts Identifier | (variable E5203). | | In most cases, the alphabetical party codes correspond to the | alphabetical code for the leader of that same party (e.g., | LEADER A is the leader of PARTY A). However, there are | exceptions, such as in instances in which data is available for | two leaders of the same party. | Parties/coalitions and their numerical and alphabetical | classifications for each election study are detailed in Part 3 of | the CSES Codebook. --------------------------------------------------------------------------- E5000_L_A >>> LEADER A IDENTIFIER - NUMERICAL E5000_L_B >>> LEADER B IDENTIFIER - NUMERICAL E5000_L_C >>> LEADER C IDENTIFIER - NUMERICAL E5000_L_D >>> LEADER D IDENTIFIER - NUMERICAL E5000_L_E >>> LEADER E IDENTIFIER - NUMERICAL E5000_L_F >>> LEADER F IDENTIFIER - NUMERICAL E5000_L_G >>> LEADER G IDENTIFIER - NUMERICAL E5000_L_H >>> LEADER H IDENTIFIER - NUMERICAL E5000_L_I >>> LEADER I IDENTIFIER - NUMERICAL --------------------------------------------------------------------------- Numeric Party Code Identifier for Leaders A-I (see variable notes). .................................................................. 008001-858003. PARTY/COALITION NUMERICAL IDENTIFIER & LEADER NAME [SEE PART 3 OF CODEBOOK FOR NUMERICAL PARTY/ COALITION CODES] 999999. MISSING | VARIABLE NOTES: E5000_L_ | | CSES policy is that for alphabetical codes, leaders A through F | tend to be the leaders of the six most popular parties/ | coalitions or the Presidential candidates of these parties. | They correspond to parties A-F (i.e., Leader A will be related to | Party A in some way, Leader B will be related to Party B, etc.). | Leaders G, H, and I are supplemental leaders. They may be related | to parties G, H, or I, but they do not have to be. These leaders | are voluntarily provided by each country's election study and | often include data about additional personalities of interest. | For example, in a parliamentary system, data about a President | might be provided, even if the Presidency is not being contested. | On many occasions, slots Leader G, H, and I will include | additional data for parties/coalitions that have multiple | leaders. | As codes in E5000_L_ are labeled with the corresponding leader | surnames and acronyms of their associated parties, they allow for | easy identification of the relational data. | | For the CSES M5 dataset, alphabetical leader codes are used to | identify the following: | - Respondent's likeability of the leader/personality in question | (variable E3018_). | | Parties/coalitions and their numerical and alphabetical | classifications for each election study are detailed in Part 3 of | the CSES Codebook. II. ELECTION-SPECIFIC AND ELECTORAL RULES DATA --------------------------------------------------------------------------- E5001_A >>> PERCENT VOTE - LOWER HOUSE - PARTY A E5001_B >>> PERCENT VOTE - LOWER HOUSE - PARTY B E5001_C >>> PERCENT VOTE - LOWER HOUSE - PARTY C E5001_D >>> PERCENT VOTE - LOWER HOUSE - PARTY D E5001_E >>> PERCENT VOTE - LOWER HOUSE - PARTY E E5001_F >>> PERCENT VOTE - LOWER HOUSE - PARTY F E5001_G >>> PERCENT VOTE - LOWER HOUSE - PARTY G E5001_H >>> PERCENT VOTE - LOWER HOUSE - PARTY H E5001_I >>> PERCENT VOTE - LOWER HOUSE - PARTY I --------------------------------------------------------------------------- Percent of popular vote received by PARTY [A/B/C/D/E/F/G/H/I] in current (lower house) legislative election. .................................................................. 000.00-100.00 PERCENT OF THE POPULAR VOTE THAT PARTY/COALITION [A/B/C/D/E/F/G/H/I] RECEIVED 997.00 NOT APPLICABLE: NO LOWER HOUSE ELECTION 999.00. MISSING | VARIABLE NOTES: E5001_ | | Parties/coalitions and their numerical and alphabetical | classifications for each election study are detailed in Part 3 of | the CSES Codebook. | | For preferential electoral systems (e.g., Australia, Ireland), | E5001_ report the first preference vote share of each | party/coalition, unless otherwise stated in the ELECTION STUDY | NOTES below. | For mixed electoral systems (e.g., Germany, Italy, Japan, | New Zealand), E5001_ report the vote share of the "party list" | segment for each party/coalition, unless otherwise stated in the | ELECTION STUDY NOTES below. | | Source of data: Publicly available sources such as National | Election Commissions. | ELECTION STUDY NOTES - AUSTRALIA (2019): E5001_A & E5001_D | | PARTY A (The Liberal Party) combines the results for | Liberal National Party (who ran only in Queensland state) and | the Liberal Party (who ran in all other states). | PARTY D (National Party) combines the results for the Nationals | and the Country Liberals, as the latter only ran in the | Northern Territory. | The Liberal Party competes in an alliance (the Coalition) with | the National Party, and in most instances, the two parties do | not field candidates against one another. The combined vote | share of the Liberal Party and National Party (i.e., the | Coalition) is 41.2%. | ELECTION STUDY NOTES - BELGIUM-FLANDERS (2019): E5001 | | Almost all Belgian parties are divided into linguistic groups, | and therefore, few parties compete on a national basis (those | that do and that are assigned an alphabetical classification by | CSES are noted below). Instead, most parties compete in one of | two predominant linguistic regions of the country, namely | Belgium-Flanders (Dutch-speaking region) and Belgium-Wallonia | (French-speaking region). There is also a German-speaking region | which for elections to the Belgian Parliament (Chamber of | Representatives) is located within the Belgium-Wallonia | of Liege. Thus, elections to Belgium's national parliament | essentially operate as two distinct elections for one chamber. | Accordingly, the data represents the percentage of votes | received by parties standing in the Flanders regions only, | namely: Antwerp, East Flanders, Flemish Brabant, Limburg, and | West Flanders. Parties are allocated alphabetical classifications | on this basis. | | The percentage of votes achieved by each party standing in | the Belgium-Flanders region in Belgium as a unified entity is | as follows: | | PARTY A (New Flemish Alliance, N-VA) - 16.0% | PARTY B (Vlaams Belangm, VB) - 12.0% | PARTY C (Christen-Democratisch en Vlaams, CD&V) - 8.9% | PARTY D (Open Vlaamse Liberalen den Democratsen, Open-VLD) - 8.5% | PARTY E (Socialistische Partij Anders, Spa) - 6.7% | PARTY F (Green, Groen) - 6.1% | PARTY G (Workers Party of Belgium, PVDA/PTB) - 8.6% | | PARTY G (Workers Party of Belgium, PVDA/PTB) competed in both | the Belgian Flanders and Belgian Wallonia regions. | ELECTION STUDY NOTES - BELGIUM-WALLONIA (2019): E5001 | | Almost all Belgian parties are divided into linguistic groups, | and therefore, few parties compete on a national basis (those | that do and that are assigned an alphabetical classification by | CSES are noted below). Instead, most parties compete in one of | two predominant linguistic regions of the country, namely | Belgium-Flanders (Dutch-speaking region) and Belgium-Wallonia | (French-speaking region). There is also a German-speaking region | which for elections to the Belgian Parliament (Chamber of | Representatives) is located within the Belgium-Wallonia | of Liege. Thus, elections to Belgium's national parliament | essentially operate as two distinct elections for one chamber. | Accordingly, the data represents the percentage of votes | received by parties standing in the Wallonia region only, | namely: Brabant, Hainaut, Liege, Luxembourg, and Namur. Data from | the Brussels Capital Region is not included. Parties are | allocated alphabetical classifications on this basis. | | The percentage of votes achieved by each party standing in | the Belgium-Wallonia region in Belgium as a unified entity is | as follows: | | PARTY A (Socialist Party, PS) - 9.5% | PARTY B (Reformist Movement, MR) - 7.6% | PARTY C (Ecolo) - 6.1% | PARTY D (Workers Party of Belgium, PVDA/PTB) - 8.6% | PARTY E (Humanist Democratic Centre, cdH) - 3.7% | PARTY F (Democrate, Federaliste, Independent, DeFi) - 2.2% | PARTY G (People's Party, PP) - 1.1% | | PARTY D (Workers Party of Belgium, PVDA/PTB) competed in both | the Belgian Flanders and Belgian Wallonia regions. | ELECTION STUDY NOTES - CZECHIA (2021): E5001_A | | The data represents the combined vote share of the Together | (SPOLU) alliance comprising the following parties: | - Civic Democratic Party (Obcanska demokraticka strana, ODS). | - Tradition, Responsibility, Prosperity (Tradice Odpovednost | Prosperita, TOP09). | - Christian and Democratic Union/People's Party (Krestanska a | Demokraticka Unie - Strana lidova, KDU-CSL). | ELECTION STUDY NOTES - CZECHIA (2021): E5001_C | | The data represents the combined vote share of an alliance | comprising the following parties: | - Pirati - Czech Pirate Party (Ceska Piratska Strana). | - STAN - Mayors and Independents (Starostove a nezavisli) | ELECTION STUDY NOTES - DENMARK (2019): E5001 | | Total share of the vote is calculated including the votes cast | in the Faroe Islands and Greenland, two autonomous territories in | the Kingdom of Denmark. | | The percentage of votes achieved by each party standing in | mainland Denmark (excluding Greenland and Faroe Islands) is | as follows: | | PARTY A (Social Democratic Party, Sd - A) - 25.9% | PARTY B (Venstre, V) - 23.4% | PARTY C (Danish People's Party, DF - O) - 8.7% | PARTY D (Social Liberals, RV - B) - 8.6% | PARTY E (Socialist People's Party, SF - F) - 7.7% | PARTY F (Red Green Alliance, Rod/Green - En O) - 6.9% | PARTY G (Conservative People's Party, KF - C) - 6.6% | PARTY H (The Alternative, AI) - 3.0% | PARTY I (New Right, NB - D) - 2.4% | ELECTION STUDY NOTES - GERMANY (2017): E5001_A & E5001_G | | Data in E5001_A represent the vote share of the Christian | Democratic Union (CDU), which competes in an alliance | (Unionsparteien) with the Christian Social Union (CSU, PARTY G), | the latter competing only in the state (laender) of Bavaria, | whereas the CDU competes in the other fifteen states. | Vote share for the CSU is provided in E5001_G. The combined | vote share of the CDU and CSU is 32.9%. | ELECTION STUDY NOTES - GERMANY (2021): E5001_B & E5001_F | | Data in E5001_B represent the vote share of the Christian | Democratic Union (CDU), which competes in an alliance | (Unionsparteien) with the Christian Social Union (CSU, PARTY F), | the latter competing only in the state (laender) of Bavaria, | whereas the CDU competes in the other fifteen states. | Vote share for the CSU is provided in E5001_F. The combined vote | share of the CDU and CSU is 24.1%. | ELECTION STUDY NOTES - GREAT BRITAIN (2017): E5001 | | These data represent the national share of the vote attained by | parties who fielded candidates in England, Scotland, and Wales. | Northern Ireland data is not included as the 2017 British | Election Study did not include respondents from Northern | Ireland. | | The share of votes achieved by each party standing in the United | Kingdom, thus including Northern Ireland seats (n=18), and | totaling n=650 seats is as follows: | | PARTY A (Conservative Party, Con) - 42.5% | PARTY B (Labor Party, Lab) - 40.0% | PARTY C (Liberal Democrats, LibDem) - 7.4% | PARTY D (Scottish National Party) - 3.0% | PARTY E (United Kingdom Independence Party, UKIP) - 1.8% | PARTY F (Green Party, GP) - 1.6% | PARTY G (Plaid Cymru, PC) - 0.5% | ELECTION STUDY NOTES - GREAT BRITAIN (2017): E5001_A | | These data include the votes received by Speaker John Bercow | originally a Conservative, who was standing in the Buckingham | constituency. | ELECTION STUDY NOTES - GREAT BRITAIN (2019): E5001 | | These data represent the national share of the vote attained by | parties who fielded candidates in England, Scotland, and Wales. | Northern Ireland data is not included as the 2019 British | Election Study did not include respondents from Northern | Ireland. | | The share of votes achieved by each party standing in the United | Kingdom, thus including Northern Ireland seats (n=18), and | totaling n=650 seats is as follows: | | PARTY A (Conservative Party, Con) - 43.6% | PARTY B (Labor Party, Lab) - 32.1% | PARTY C (Liberal Democrats, LibDem) - 11.6% | PARTY D (Scottish National Party) - 3.9% | PARTY E (Green Party, GP) - 2.7% | PARTY F (Brexit Party, BP) - 2.0% | PARTY G (Plaid Cymru, PC) - 0.5% | ELECTION STUDY NOTES - GREAT BRITAIN (2019): E5001_B | | These data include the votes received by Speaker Lindsay Hoyle | originally a Labor member, who was standing in the Chorley | constituency. | ELECTION STUDY NOTES - HONG KONG (2016): E5001 | | These data represent the vote share from the geographical | constituency segment. | ELECTION STUDY NOTES - HUNGARY (2018): E5001_C | | The data refers to the Hungarian Socialist Party (MSZP, PARTY C). | The junior partner in the coalition is the Dialogue - Green Party | (Parbeszed). | ELECTION STUDY NOTES - MEXICO (2018): E5001 | | The Lower House or the Mexican Congress is composed of 500 | deputies with 300 elected in single-member districts | (distritos uninominales - tier 1) using a plurality first past | the post system. The remaining 200 are elected from five | multi-member districts (circunscripciones plurinominales - tier | 2) by proportional representation. A voter casts one vote which | simultaneously counts for electing members of parliament in both | tier 1 and tier 2. | ELECTION STUDY NOTES - POLAND (2019): E5001 | | Most Polish parties competed in the 2019 election as part of | electoral alliances. These data refer to the vote share achieved | by constituent parties within each alliance - consult Part 3 of | the CSES Codebook for more information. | | The share of votes achieved by each alliance is as follows: | | United Right (ZP) - 43.6% | The following parties contesting as part of this alliance are: | - Law and Justice (PiS) - PARTY A | - Solidary Poland (SP) | - Republican Party | - Freedom and Solidarity (WiS) | - Piast party | | Civic Coalition (KO) - 27.4% | The following parties contesting as part of this alliance are: | - Civic Platform (PO) - PARTY B | - Modern (Nowo) | - Greens (PZ) | - Polish Initiative (iPL) | - Silesian Autonomy Movement (RAS) | - Social Democracy of Poland (SDPL). | | Polish Coalition (KP) - 8.5% | The following parties contesting as part of this alliance are: | - Polish People's Party (PSL) - PARTY C | - Kukiz'15 (K'15) - PARTY E | - Union of European Democrats (UED) | - Alliance of Democrats (SD) | - Silesians Together | - Poland Needs Us | - One-PL. | | The Left (Lewica) - 12.6% | The following parties contesting as part of this alliance are: | - Democratic Left Alliance (SLD) - PARTY D | - Left Together (Razem) - PARTY F | - Spring (Wiosna) - PARTY G | - Your Movement (TR) | - Polish Socialist Party (PPS) | | Confederation (Konfederacja) - 6.8% | The following parties contesting as part of this alliance are: | - New Hope (KORWiN) | - National Movement (RN) | - Confederation of the Polish Crown (KKP) | - Union of Christian Families (ZchR) | - Party of Drivers | - National League (LN). | ELECTION STUDY NOTES - PORTUGAL (2019): E5001_D | | These data refer to the Unitary Democratic Coalition (CDU). CDU | is an electoral alliance of the Portuguese Communist Party (PCP) | and the Ecologist Party - The Greens (PEV), in place since 1987. | ELECTION STUDY NOTES - SOUTH KOREA (2016): E5001 | | These data refer to the national-level vote share from the | 253 single-member districts, which constitute 84% of the seats in | the National Assembly (the South Korean parliament). | ELECTION STUDY NOTES - TAIWAN (2016) & TAIWAN (2020): E5001 | | These data refer to the national-level vote share from the | 73 geographical single-member districts, which constitute 65% of | the seats in the Legislative Yuan (the Taiwan parliament). | ELECTION STUDY NOTES - THAILAND (2019): E5001 | | These data refer to the single vote that counts for two tiers of | the Lower House - majoritarian and proportional. | ELECTION STUDY NOTES - UNITED STATES (2016 & 2020): E5001 | | Multiple estimates of the national election results are | available from a wide variety of sources. These sources | often differ in the final vote tallies provided for each | party, most likely a consequence of the fact that counting | is done at a state level, and accordingly, votes are sometimes | reported in different ways and at different time points. The | estimates of party vote share in the US House of Representative | elections are based on the data reported by the US Congressional | Election Information Statistics of the Presidential and | Congressional Elections 2016 and 2020. | | Sources of data: | US Congressional Election Information Statistics of the | Presidential and Congressional Elections 2016 | https://history.house.gov/Institution/Election-Statistics/ | 2016election (Date accessed: January 03, 2023). | US Congressional Election Information Statistics of the | Presidential and Congressional Elections 2020 | http://clerk.house.gov/member_info/electionInfo/2012election.pdf | (Date accessed: December 14, 2021). --------------------------------------------------------------------------- E5002_A >>> PERCENT SEATS - LOWER HOUSE - PARTY A E5002_B >>> PERCENT SEATS - LOWER HOUSE - PARTY B E5002_C >>> PERCENT SEATS - LOWER HOUSE - PARTY C E5002_D >>> PERCENT SEATS - LOWER HOUSE - PARTY D E5002_E >>> PERCENT SEATS - LOWER HOUSE - PARTY E E5002_F >>> PERCENT SEATS - LOWER HOUSE - PARTY F E5002_G >>> PERCENT SEATS - LOWER HOUSE - PARTY G E5002_H >>> PERCENT SEATS - LOWER HOUSE - PARTY H E5002_I >>> PERCENT SEATS - LOWER HOUSE - PARTY I --------------------------------------------------------------------------- Percent of seats in lower house received by PARTY [A/B/C/D/E/F/G/H/I] in current (lower house) election. .................................................................. 000.00-100.00 PERCENT OF THE SEATS THAT PARTY/COALITION [A/B/C/D/E/F/G/H/I] RECEIVED 997.00 NOT APPLICABLE: NO LOWER HOUSE ELECTION 999.00. MISSING | VARIABLE NOTES: E5002_ | | Parties/coalitions and their numerical and alphabetical | classifications for each election study are detailed in Part 3 of | the CSES Codebook. | | For mixed electoral systems (e.g., Germany, Italy, Japan, | New Zealand), E5002_ report the total seat share for each | party/coalition - i.e., the seats an entity won from both the | "party list" segment and the "constituency" segment, unless | otherwise stated in the ELECTION STUDY NOTES below. | | Source of data: Publicly available sources such as National | Election Commissions. | ELECTION STUDY NOTES - AUSTRALIA (2019): E5002_A & E5002_D | | PARTY A (The Liberal Party) combines the results for the Liberal | National Party (who ran only in Queensland state) and the | Liberal Party (who ran in all other states). | PARTY D (National Party) combines the results for the Nationals | and the Country Liberals, as the latter only ran in the | Northern Territory. | The Liberal Party competes in an alliance (the Coalition) with | the National Party and in most instances, the two parties do | not field candidates against one another. The combined seat | share of the Liberal Party and National Party (i.e., the | Coalition) is 51.0%. | ELECTION STUDY NOTES - BELGIUM-FLANDERS (2019): E5002 | | Almost all Belgian parties are divided into linguistic groups, | and therefore, few parties compete on a national basis (those | that do and that are assigned an alphabetical classification by | CSES are noted below). Instead, most parties compete in one of | two predominant linguistic regions of the country, namely | Belgium-Flanders (Dutch-speaking region) and Belgium-Wallonia | (French-speaking region). There is also a German-speaking region | which for elections to the Belgian Parliament (Chamber of | Representatives) is located within the Belgium-Wallonia area of | of Liege. Thus, elections to Belgium's national parliament | essentially operate as two distinct elections for one chamber. | Accordingly, the data represents the percentage of seats | contested in the Flanders regions only (87 of the 150 seats in | total in the Chamber of Representatives), namely: Antwerp, East | Flanders, Flemish Brabant, Limburg, and West Flanders. | | The percentage of seats achieved by each party standing in | the Belgium-Flanders region in Belgium as a unified entity is | as follows: | | PARTY A (New Flemish Alliance, N-VA) - 16.7% | PARTY B (Vlaams Belangm, VB) - 12.0% | PARTY C (Christen-Democratisch en Vlaams, CD&V) - 8.0% | PARTY D (Open Vlaamse Liberalen den Democratsen, Open-VLD) - 8.0% | PARTY E (Socialistische Partij Anders, Spa) - 6.0% | PARTY F (Green, Groen) - 5.3% | PARTY G (Workers Party of Belgium, PVDA/PTB) - 8.0% | | PARTY G (Workers Party of Belgium, PVDA/PTB) competed in both | the Belgian Flanders and Belgian Wallonia regions. | ELECTION STUDY NOTES - BELGIUM-WALLONIA (2019): E5002 | | Almost all Belgian parties are divided into linguistic groups, | and therefore, few parties compete on a national basis (those | that do and that are assigned an alphabetical classification by | CSES are noted below). Instead, most parties compete in one of | two predominant linguistic regions of the country, namely | Belgium-Flanders (Dutch-speaking region) and Belgium-Wallonia | (French-speaking region). There is also a German-speaking region | which for elections to the Belgian Parliament (Chamber of | Representatives) is located within the Belgium-Wallonia area | of Liege. Thus, elections to Belgium's national parliament | essentially operate as two distinct elections for one chamber. | Accordingly, the data represents the percentage of seats | contested in the Wallonia regions only (48 of the 150 seats in | total in the Chamber of Representatives), namely: Brabant, | Hainaut, Liege, Luxembourg, and Namur. Data from the Brussels | Capital Region is not included. Parties are allocated | alphabetical classifications on this basis. | | The percentage of seats achieved by each party standing in | the Belgium-Wallonia region in Belgium as a unified entity is | as follows: | | PARTY A (Socialist Party, PS) - 13.3% | PARTY B (Reformist Movement, MR) - 9.3% | PARTY C (Ecolo) - 8.7% | PARTY D (Workers Party of Belgium, PVDA/PTB) - 8.0% | PARTY E (Humanist Democratic Centre, cdH) - 3.3% | PARTY F (Democrate, Federaliste, Independent, DeFi) - 1.3% | PARTY G (People's Party, PP) - 0.0% | | PARTY D (Workers Party of Belgium, PVDA/PTB) competed in both | the Belgian Flanders and Belgian Wallonia regions. | ELECTION STUDY NOTES - CZECHIA (2021): E5002_A | | The data represents the combined seat share of the Together | (SPOLU) alliance comprising the following parties: | - Civic Democratic Party (Obcanska demokraticka strana, ODS). | - Tradition, Responsibility, Prosperity (Tradice Odpovednost | Prosperita, TOP09). | - Christian and Democratic Union/People's Party (Krestanska a | Demokraticka Unie - Strana lidova, KDU-CSL). | ELECTION STUDY NOTES - CZECHIA (2021): E5002_C | | The data represents the combined seat share of an alliance | comprising the following parties: | - Pirati - Czech Pirate Party (Ceska Piratska Strana). | - STAN - Mayors and Independents (Starostove a nezavisli) | ELECTION STUDY NOTES - DENMARK (2019): E5002 | | Total share of seats is calculated including the seats (n=4) | in the Faroe Islands and Greenland, two autonomous territories in | the Kingdom of Denmark, making a total of 179 seats. | The two seats in the Faroe Islands were won by the Union Party | and the Social Democratic Party. The two seats in Greenland | were won by the Inuit Ataqatiguut and Siumut parties. | | The percentage of seats achieved by each party standing in | mainland Denmark (excluding Greenland and Faroe Islands, i.e., | n=175 seats) is as follows: | | PARTY A (Social Democratic Party, Sd - A) - 27.4% | PARTY B (Venstre, V) - 24.6% | PARTY C (Danish People's Party, DF - O) - 9.1% | PARTY D (Social Liberals, RV - B) - 9.1% | PARTY E (Socialist People's Party, SF - F) - 8.0% | PARTY F (Red Green Alliance, Rod/Green - En O) - 7.4% | PARTY G (Conservative People's Party, KF - C) - 6.9% | PARTY H (The Alternative, AI) - 2.9% | PARTY I (New Right, NB - D) - 2.3% | ELECTION STUDY NOTES - GERMANY (2017): E5002_A & E5002_G | | Data in E5002_A represent the seat share of the Christian | Democratic Union (CDU), which competes in an alliance | (Unionsparteien) with the Christian Social Union (CSU, PARTY G), | the latter competing only in the state (laender) of Bavaria, | whereas the CDU competes in the other fifteen states. | Seat share for the CSU is provided in E5002_G. The combined seat | share of the CDU and CSU is 34.7%. | ELECTION STUDY NOTES - GERMANY (2021): E5002_B & E5002_F | | Data in E5002_B represent the seat share of the Christian | Democratic Union (CDU), which competes in an alliance | (Unionsparteien) with the Christian Social Union (CSU, PARTY F), | the latter competing only in the state (laender) of Bavaria, | whereas the CDU competes in the other fifteen states. | Seat share for the CSU is provided in E5002_F. The combined seat | share of the CDU and CSU is 26.8%. | ELECTION STUDY NOTES - GREAT BRITAIN (2017): E5002 | | These data represent the national share of the vote attained by | parties who fielded candidates in England, Scotland, and Wales. | Northern Ireland data is not included as the 2017 British | Election Study did not include respondents from Northern | Ireland. | | While the Conservative Party achieved a majority of seats | in Great Britain (318/632=50.2%), including the seats | from Northern Ireland (n=18 seats), the party fell short of | a parliamentary majority (318/650=48.9%), necessitating a | confidence and supply deal with the Democratic Unionist Party | (DUP). They are a religious party who contests seats in Northern | Ireland only, and had won 10 of the province's 18 seats. | Nonetheless, as Sinn Fein, an Irish Nationalist Party, won the | province's remaining seven seats on an abstentions policy of not | taking their seats in the House of Commons, to obtain a working | parliamentary majority in the House of Commons required control | of 322 seats, not the conventional 326. | | The share of seats achieved by each party standing in the United | Kingdom, thus including Northern Ireland seats (n=18), and | totaling n=650 seats is as follows: | | PARTY A (Conservative Party, Con) - 48.9% | PARTY B (Labor Party, Lab) - 40.3% | PARTY C (Liberal Democrats, LibDem) - 1.9% | PARTY D (Scottish National Party) - 5.4% | PARTY E (United Kingdom Independence Party, UKIP) - 0.0% | PARTY F (Green Party, GP) - 0.2% | PARTY G (Plaid Cymru, PC) - 0.6% | ELECTION STUDY NOTES - GREAT BRITAIN (2017): E5002_A | | These data include the votes received by Speaker John Bercow | originally a Conservative, who was standing in the Buckingham | constituency. | ELECTION STUDY NOTES - GREAT BRITAIN (2019): E5002 | | These data represent the national share of the vote attained by | parties who fielded candidates in England, Scotland, and Wales. | Northern Ireland data is not included as the 2019 British | Election Study did not include respondents from Northern | Ireland. | | The share of seats achieved by each party standing in the United | Kingdom, thus including Northern Ireland seats (n=18), and | totaling n=650 seats is as follows: | | PARTY A (Conservative Party, Con) - 56.1% | PARTY B (Labor Party, Lab) - 31.2% | PARTY C (Liberal Democrats, LibDem) - 1.7% | PARTY D (Scottish National Party) - 7.4% | PARTY E (Green Party, GP) - 2.7% | PARTY F (Brexit Party, BP) - 2.0% | PARTY G (Plaid Cymru, PC) - 0.5% | ELECTION STUDY NOTES - GREAT BRITAIN (2019): E5002_B | | These data include the votes received by Speaker Lindsay Hoyle | originally a Labor member, who was standing in the Chorley | constituency. | ELECTION STUDY NOTES - HUNGARY (2018): E5002_C | | The data refers to the Hungarian Socialist Party (MSZP, PARTY C). | The junior partner in the coalition is the Dialogue - Green Party | (Parbeszed). | ELECTION STUDY NOTES - ITALY (2018): E5002 | | These data include the proportional district for Italians | residing abroad. | ELECTION STUDY NOTES - NEW ZEALAND (2017): E5002_G | | PARTY G (ACT) were ineligible for seats based on the party list | but achieved parliamentary representation having won the | electorate of Epsom. | ELECTION STUDY NOTES - POLAND (2019): E5002 | | Most Polish parties competed in the 2019 election as part of | electoral alliances. These data refer to the seat share achieved | by constituent parties within each alliance - consult Part 3 of | the CSES Codebook for more information. | | The share of seats achieved by each alliance is as follows: | | United Right (ZP) - 51.1% | The following parties contesting as part of this alliance are: | - Law and Justice (PiS) - PARTY A | - Solidary Poland (SP) | - Republican Party | - Freedom and Solidarity (WiS) | - Piast party | | Civic Coalition (KO) - 29.1% | The following parties contesting as part of this alliance are: | - Civic Platform (PO) - PARTY B | - Modern (Nowo) | - Greens (PZ) | - Polish Initiative (iPL) | - Silesian Autonomy Movement (RAS) | - Social Democracy of Poland (SDPL). | | Polish Coalition (KP) - 6.5% | The following parties contesting as part of this alliance are: | - Polish People's Party (PSL) - PARTY C | - Kukiz'15 (K'15) - PARTY E | - Union of European Democrats (UED) | - Alliance of Democrats (SD) | - Silesians Together | - Poland Needs Us | - One-PL. | | The Left (Lewica) - 10.7% | The following parties contesting as part of this alliance are: | - Democratic Left Alliance (SLD) - PARTY D | - Left Together (Razem) - PARTY F | - Spring (Wiosna) - PARTY G | - Your Movement (TR) | - Polish Socialist Party (PPS) | | Confederation (Konfederacja) - 2.4% | The following parties contesting as part of this alliance are: | - New Hope (KORWiN) | - National Movement (RN) | - Confederation of the Polish Crown (KKP) | - Union of Christian Families (ZchR) | - Party of Drivers | - National League (LN). | ELECTION STUDY NOTES - PORTUGAL (2019): E5002_D | | These data refer to the Unitary Democratic Coalition (CDU). CDU | is an electoral alliance of the Portuguese Communist Party (PCP) | and the Ecologist Party - The Greens (PEV), in place since 1987. | ELECTION STUDY NOTES - SLOVAKIA (2020): E5002_E | | PARTY E (Progressive Slovakia-Together, PS-SPOLU) failed to | surpass the 7% electoral threshold imposed on 2-3 parties | competing together as an alliance and hence were ineligible to | receive seats. --------------------------------------------------------------------------- E5003_A >>> PERCENT VOTE - UPPER HOUSE - PARTY A E5003_B >>> PERCENT VOTE - UPPER HOUSE - PARTY B E5003_C >>> PERCENT VOTE - UPPER HOUSE - PARTY C E5003_D >>> PERCENT VOTE - UPPER HOUSE - PARTY D E5003_E >>> PERCENT VOTE - UPPER HOUSE - PARTY E E5003_F >>> PERCENT VOTE - UPPER HOUSE - PARTY F E5003_G >>> PERCENT VOTE - UPPER HOUSE - PARTY G E5003_H >>> PERCENT VOTE - UPPER HOUSE - PARTY H E5003_I >>> PERCENT VOTE - UPPER HOUSE - PARTY I --------------------------------------------------------------------------- Percent of popular vote received by PARTY [A/B/C/D/E/F/G/H/I] in current (upper house) legislative election. .................................................................. 000.00-100.00 PERCENT OF THE POPULAR VOTE THAT PARTY/COALITION [A/B/C/D/E/F/G/H/I] RECEIVED 996.00 NOT APPLICABLE: UNICAMERAL SYSTEM 997.00 NOT APPLICABLE: NO UPPER HOUSE ELECTION 999.00. MISSING | VARIABLE NOTES: E5003_ | | Parties/coalitions and their numerical and alphabetical | classifications for each election study are detailed in Part 3 of | the CSES Codebook. | | For preferential electoral systems (e.g., Australia, Ireland), | E5003_ report the first preference vote share of each | party/coalition, unless otherwise stated in the ELECTION STUDY | NOTES below. | For mixed electoral systems (e.g., Germany, Italy, Japan, | New Zealand), E5003_ report the vote share of the "party list" | segment for each party/coalition, unless otherwise stated in the | ELECTION STUDY NOTES below. | | Data are unavailable for SWITZERLAND (2019). | ELECTION STUDY NOTES - AUSTRALIA (2019): E5003 | | A half Senate election, where approximately 50% of the seats are | contested each electoral cycle was held. In 2019, 40 of the 76 | seats were contested: six for each of the six states (36 seats), | and two seats in each of the two territories (4 seats). | ELECTION STUDY NOTES - AUSTRALIA (2019): E5003_A & E5003_D | | The Liberal Party (Lib, PARTY A) competes in an alliance (the | Coalition) with the National Party (NP, PARTY D). For Senate | elections, the two parties often field joint tickets. | Many Senate candidates for the Nationals contest under a joint | Liberal-National ticket or under the banner of the Liberal | National Party (in Queensland). The vote share of these | candidates are included in the Liberal Party total (PARTY A). | Senators contesting for the National Party or the Country | Liberals are included in the National Party total (PARTY D). | The combined vote share of the Liberal Party and National Party | (i.e., the Coalition) in the seats contested was 37.3%. | ELECTION STUDY NOTES - BRAZIL (2018): E5003 | | Members of the Brazilian Senate (Senado Federal) are elected | for an 8-year term with the chamber composed of 81 members, | with each state in Brazil having three Senators each. Members are | elected in alternative electoral cycles: two-thirds of seats | seats (n=54) are contested in one cycle; the remaining one third | in the other cycle. The 2018 elections saw 54 Senate seats | contested. The data represents the percentage of votes won by | each Party/Coalition on the basis of the 54 seats contested. | ELECTION STUDY NOTES - CHILE (2017): E5003 | | Members of the Chilean Senate are elected for an 8-year term with | the chamber composed of 43 members in 2017. Members are | elected in alternative electoral cycles: one-half of seats | seats are contested in each cycle. The 2018 elections saw 23 | Senate seats contested. The data represents the percentage of | votes won by each Party/Coalition on the basis of the 23 seats | contested. | ELECTION STUDY NOTES - MEXICO (2018): E5003 | | The Mexican Senate is composed of 128 members serving six-year | terms, coinciding with the Presidential term. Ninety-six members | are elected via the 32 regions (31 States and the Federal | District with the party receiving the most votes winning two | seats and the party receiving the second most votes receiving | one (tier 1). The remaining 32 members are elected in a single | nationwide district by proportional representation (tier 2). | These data refer to the national vote share in tier 1. | ELECTION STUDY NOTES - POLAND (2019): E5003 | | Most Polish parties competed in the 2019 election as part of | electoral alliances. These data refer to the seat share achieved | by constituent parties within each alliance - consult Part 3 of | the CSES Codebook for more information. | | The share of vote achieved by each alliance is as follows: | | United Right (ZP) - 44.6% | The following parties contesting as part of this alliance are: | - Law and Justice (PiS) - PARTY A | - Solidary Poland (SP) | - Republican Party | - Freedom and Solidarity (WiS) | - Piast party | | Civic Coalition (KO) - 35.7% | The following parties contesting as part of this alliance are: | - Civic Platform (PO) - PARTY B | - Modern (Nowo) | - Greens (PZ) | - Polish Initiative (iPL) | - Silesian Autonomy Movement (RAS) | - Social Democracy of Poland (SDPL). | | Polish Coalition (KP) - 5.7% | The following parties contesting as part of this alliance are: | - Polish People's Party (PSL) - PARTY C | - Kukiz'15 (K'15) - PARTY E | - Union of European Democrats (UED) | - Alliance of Democrats (SD) | - Silesians Together | - Poland Needs Us | - One-PL. | | The Left (Lewica) - 2.3% | The following parties contesting as part of this alliance are: | - Democratic Left Alliance (SLD) - PARTY D | - Left Together (Razem) - PARTY F | - Spring (Wiosna) - PARTY G | - Your Movement (TR) | - Polish Socialist Party (PPS) | | Confederation (Konfederacja) - 0.8% | The following parties contesting as part of this alliance are: | - New Hope (KORWiN) | - National Movement (RN) | - Confederation of the Polish Crown (KKP) | - Union of Christian Families (ZchR) | - Party of Drivers | - National League (LN). | ELECTION STUDY NOTES - SWITZERLAND (2019): E5003 | | The Upper House (Council of States, Staenderat) has 46 members. | Twenty of the country's cantons are represented by two | Councilors each. Six cantons, traditionally called "half | cantons", are represented by one Councilor each. | The electoral rules (except the number of seats to be filled) | are subject to cantonal regulations, so the electoral system | varies. Most cantons have two-round majoritarian elections, | where an absolute majority is required in the first round. | However, two cantons use a PR system for their two seats (Jura | and Neuchatel). | Since the elections to the Upper House are cantonal elections, | no national-level vote share results are available. | ELECTION STUDY NOTES - UNITED STATES (2016): E5003 | | The US Senate is composed of 100 members with members | elected for a six-year term. One-third of the Senate seats | (conventional n=33-34) are contested in election cycles every | two years. The 2016 elections saw 34 Senate seats contested. | The data represents the percentage of votes won by | each Party on the basis of the 34 seats contested. | | The Republicans (GOP, PARTY B) retained control of the | United States Senate, with a total of 52 seats, with Democrats | (DEM, PARTY A) holding 46 seats, and two Independents, who | caucus with the Democrats. | ELECTION STUDY NOTES - UNITED STATES (2020): E5003 | | The US Senate is composed of 100 members with members | elected for a six-year term. One-third of the Senate seats | (conventional n=33-34) are contested in election cycles every | two years. The 2020 elections saw 35 Senate seats contested - the | conventional 33 seats and two special Senate elections (in | Arizona and Georgia) caused by the death/retirement of sitting | members. | The data represents the percentage of votes won by | each Party on the basis of the 35 seats contested. | | Control of the United States Senate was not decided until | January 2021 when two special run-off elections were held in | Georgia. | The Democrats (DEM, PARTY A), with the support of two | Independents, who caucus with the Democrats in the Senate, | gained control of the Senate on the casting vote of the United | States Vice President, Kamala Harris (PARTY A), who was elected | on a ticket with Democratic President Joe Biden in November 2020. | ELECTION STUDY NOTES - URUGUAY (2019): E5003 | | The Uruguayan Senate (Camara de Senadores) is composed of 30 | members serving five-year terms, coinciding with the Presidential | term. Members are elected in a nationwide constituency using | closed list proportional representation, with seats allocated | using the D'hondt system. Uruguay uses a Multiple Simultaneous | Vote (MVS) system, where voters cast a single vote for all | elections occurring - in this instance the Presidential, the | Chamber of Representatives (lower house) and the Senate (upper | house). --------------------------------------------------------------------------- E5004_A >>> PERCENT SEATS - UPPER HOUSE - PARTY A E5004_B >>> PERCENT SEATS - UPPER HOUSE - PARTY B E5004_C >>> PERCENT SEATS - UPPER HOUSE - PARTY C E5004_D >>> PERCENT SEATS - UPPER HOUSE - PARTY D E5004_E >>> PERCENT SEATS - UPPER HOUSE - PARTY E E5004_F >>> PERCENT SEATS - UPPER HOUSE - PARTY F E5004_G >>> PERCENT SEATS - UPPER HOUSE - PARTY G E5004_H >>> PERCENT SEATS - UPPER HOUSE - PARTY H E5004_I >>> PERCENT SEATS - UPPER HOUSE - PARTY I --------------------------------------------------------------------------- Percent of seats in upper house received by PARTY/COALITION [A/B/C/D/E/F/G/H/I] in current (upper house) election. .................................................................. 000.00-100.00 PERCENT OF THE SEATS THAT PARTY/COALITION [A/B/C/D/E/F/G/H/I] RECEIVED 996.00 NOT APPLICABLE: UNICAMERAL SYSTEM 997.00 NOT APPLICABLE: NO UPPER HOUSE ELECTION 999.00. MISSING | VARIABLE NOTES: E5004_ | | Parties/coalitions and their numerical and alphabetical | classifications for each election study are detailed in Part 3 of | the CSES Codebook. | | For mixed electoral systems (e.g., Germany, Italy, Japan, | New Zealand), E5004_ report the total seat share for each | party/coalition - i.e., the seats an entity won from both the | "party list" segment and the "constituency" segment, unless | otherwise stated in the ELECTION STUDY NOTES below. | In polities where only a portion of the Upper House seats are | contested in an electoral cycle (e.g., Australia, Brazil, the | United States, E5004_ represent the share of seats won by each | party among the contested seats (holdover seats are not included | in the classification). | | Source of data: Publicly available sources such as National | Election Commissions. | ELECTION STUDY NOTES - AUSTRALIA (2019): E5003 | | A half Senate election, where approximately 50% of the seats are | contested each electoral cycle was held. In 2019, 40 of the 76 | seats were contested: six for each of the six states (36 seats), | and two seats in each of the two territories (4 seats). | ELECTION STUDY NOTES - AUSTRALIA (2019): E5004_A & E5004_D | | The Liberal Party (Lib, PARTY A) competes in an alliance (the | Coalition) with the National Party (NP, PARTY D). For Senate | elections, the two parties often field joint tickets. | Many Senate candidates for the Nationals contest under a joint | Liberal-National ticket or under the banner of the Liberal | National Party (in Queensland). The seat share of these | candidates are included in the Liberal Party total (PARTY A). | Senators contesting for the National Party or the Country | Liberals are included in the National Party total (PARTY D). | The combined seat share of the Liberal Party and National Party | (i.e., the Coalition) of the seats contested was 47.5%. | | Including holdover seats, the proportion of seats in the full | Senate held by each party post the 2019 elections were: | | PARTY A (Liberal Party, LP) - 43.4% | PARTY B (Labor, ALP) - 34.2% | PARTY C (Green Party, GP) - 11.8% | PARTY D (National Party, NP) - 2.6% | PARTY E (United Australia Party, UAP) - 0.0% | PARTY F (Pauline Hanson's One Nation, PHON) - 2.6% | Senators sitting for the Liberal National Party (who were elected | on a joint Liberal (PARTY A) and National (PARTY D) ticket in | Queensland state) are included in the Liberal Party total. The | remaining seats were held by smaller parties and Independents. | ELECTION STUDY NOTES - POLAND (2019): E5004 | | Most Polish parties competed in the 2019 election as part of | electoral alliances. These data refer to the seat share achieved | by constituent parties within each alliance - consult Part 3 of | the CSES Codebook for more information. | | The share of seats achieved by each alliance is as follows: | | United Right (ZP) - 48.0% | The following parties contesting as part of this alliance are: | - Law and Justice (PiS) - PARTY A | - Solidary Poland (SP) | - Republican Party | - Freedom and Solidarity (WiS) | - Piast party | | Civic Coalition (KO) - 43.0% | The following parties contesting as part of this alliance are: | - Civic Platform (PO) - PARTY B | - Modern (Nowo) | - Greens (PZ) | - Polish Initiative (iPL) | - Silesian Autonomy Movement (RAS) | - Social Democracy of Poland (SDPL). | | Polish Coalition (KP) - 3.0% | The following parties contesting as part of this alliance are: | - Polish People's Party (PSL) - PARTY C | - Kukiz'15 (K'15) - PARTY E | - Union of European Democrats (UED) | - Alliance of Democrats (SD) | - Silesians Together | - Poland Needs Us | - One-PL. | | The Left (Lewica) - 2.0% | The following parties contesting as part of this alliance are: | - Democratic Left Alliance (SLD) - PARTY D | - Left Together (Razem) - PARTY F | - Spring (Wiosna) - PARTY G | - Your Movement (TR) | - Polish Socialist Party (PPS) | | Confederation (Konfederacja) - 0.0% | The following parties contesting as part of this alliance are: | - New Hope (KORWiN) | - National Movement (RN) | - Confederation of the Polish Crown (KKP) | - Union of Christian Families (ZchR) | - Party of Drivers | - National League (LN). | ELECTION STUDY NOTES - UNITED STATES (2016): E5004 | | The 2016 elections saw 34 Senate seats contested of the 100 | total. The data represents the percentage of seats won by each | party (n=34) in the 2016 contest and does not include | holdover seats. | | Including holdover seats, the proportion of seats in the full | Senate held by each party post the 2016 elections were: | | PARTY A (Democratic Party, DEM) - 46.0% (48.0% with Independents) | PARTY B (Republican Party, GOP) - 52.0% | PARTY C (Libertarian Party, LP) - 0.0% | PARTY D (Green Party, GP) - 0.0% | | Two Independent Senators, Angus King and Bernie Sanders, caucus | with the Democrats. | ELECTION STUDY NOTES - UNITED STATES (2020): E5004 | | The 2020 elections saw 35 Senate seats contested of the 100 | total. The data represents the percentage of seats won by each | party (n=35) in the 2020 contest and does not include | holdover seats. | | Including holdover seats, the proportion of seats in the full | Senate held by each party post the run-off elections in Georgia | in January 2021 is as follows: | | PARTY A (Democratic Party, DEM) - 48.0% | PARTY B (Republican Party, GOP) - 50.0% | PARTY C (Libertarian Party, LP) - 0.0% | | The Democrats (PARTY A), with the support of two Independents, | who caucus with the Democrats in the Senate, gained control of | the Senate on the casting vote of the United States Vice | President, Kamala Harris (PARTY A), who was elected on a ticket | with Democratic President Joe Biden in November 2020. --------------------------------------------------------------------------- E5005_A >>> PERCENT VOTE - PRESIDENT - PARTY A E5005_B >>> PERCENT VOTE - PRESIDENT - PARTY B E5005_C >>> PERCENT VOTE - PRESIDENT - PARTY C E5005_D >>> PERCENT VOTE - PRESIDENT - PARTY D E5005_E >>> PERCENT VOTE - PRESIDENT - PARTY E E5005_F >>> PERCENT VOTE - PRESIDENT - PARTY F E5005_G >>> PERCENT VOTE - PRESIDENT - PARTY G E5005_H >>> PERCENT VOTE - PRESIDENT - PARTY H E5005_I >>> PERCENT VOTE - PRESIDENT - PARTY I --------------------------------------------------------------------------- Percent of popular vote received by candidate of PARTY/COALITION [A/B/C/D/E/F/G/H/I] in current Presidential election. .................................................................. 000.00-100.00 PERCENT OF THE POPULAR VOTE THAT PARTY/COALITION [A/B/C/D/E/F/G/H/I] RECEIVED 996.00. NOT APPLICABLE: NO ROLE OF PRESIDENT 997.00. NOT APPLICABLE: NO PRESIDENTIAL ELECTION 999.00. MISSING | VARIABLE NOTES: E5005_ | | Parties/coalitions and their numerical and alphabetical | classifications for each election study are detailed in Part 3 of | the CSES Codebook. | | If multiple rounds were held, E5005_ reports the percent of vote | obtained in Round 1. Where applicable, results for Round 2 are | reported in ELECTION STUDY NOTES below. | | Source of data: Publicly available sources such as National | Election Commissions. | ELECTION STUDY NOTES - BRAZIL (2018): E5005 | | No candidate achieved an absolute majority of the vote in Round | 1. The top two candidates from Round 1 advanced to Round 2. | In the second round, Jair Bolsonaro (PSL, PARTY A) won the | contest with 55.1%, against Fernando Haddad (PT, PARTY B), | who won 44.9% of the vote. | ELECTION STUDY NOTES - CHILE (2017): E5005_ | | Most Presidential candidates nominally contest Presidential | contests as Independents, but they are supported by various | parties and/or coalitions. | | No candidate achieved an absolute majority of the vote in Round | 1. The top two candidates from Round 1 advanced to Round 2, held | on December 17, 2017. In Round 2, Sebastian Pinera (Let's Go | Chile Coalition, an alliance spearheaded by the National Renewal | (RN, PARTY A) won the presidency, with 54.6% of the vote against | Alejandro Guillier, representing the Force of Majority Coalition | comprising the Socialist Party (PSCH, PARTY D), the Party for | Democracy (PPD, PARTY E), the Communist Party (PCCH, PARTY G), | and the Social Democrat Radical Party (PRSD, PARTY I). | ELECTION STUDY NOTES - FRANCE (2017): E5005_ | | No candidate achieved an absolute majority of the vote in Round | 1. The top two candidates from Round 1 advanced to Round 2, held | on May 7, 2017. In the second round, Emmanuel Macron of La | Republique En Marche! ("The Republic on the Move!"; coded here | as Party A) won the presidency with 66.1% of the vote against | Marine Le Pen (33.9%) of the Front national (National Front, | coded here as Party B). | ELECTION STUDY NOTES - PERU (2021): E5005_ | | No candidate achieved an absolute majority of the vote in Round | 1. The top two candidates from Round 1 advanced to Round 2. In | Round 2, Pedro Castillo (Free Peru, PARTY A) won 50.3% of the | vote, defeating Keiko Fujimori (Popular Force, PARTY B), who won | 49.7%. | ELECTION STUDY NOTES - TUNISIA (2019): E5005_ | | No candidate achieved an absolute majority of the vote in Round | 1. The top two candidates from Round 1 advanced to Round 2. In | Round 2, Kais Saied (Independent) won 72.7% of the vote, | defeating Nabil Karoui (Heart of Tunisia, PARTY B), who won | 27.3%. | ELECTION STUDY NOTES - TUNISIA (2019): E5005_A | | The Ennahda Movement (PARTY A) supported Kais Saied in Round 2, | the eventual winner. In Round 1, their candidate was Abdelfattah | Mourou, who failed to advance to the run-off election. | ELECTION STUDY NOTES - TUNISIA (2019): E5005_F | | The People's Movement (PARTY F) supported Kais Saied in Round 2, | the eventual winner. In Round 1, they did not endorse any | candidate. | ELECTION STUDY NOTES - URUGUAY (2019): E5005 | | No candidate achieved an absolute majority of the vote in Round | 1. The top two candidates from Round 1 advanced to Round 2 | In the second round, Luis Lacalle Pou (National Party, PARTY B) | won the contest with 50.8% of the vote against Daniel Martinez | (Broad Front, PARTY A), who won 49.2%. --------------------------------------------------------------------------- E5006_1 >>> ELECTORAL TURNOUT - TURNOUT AS A PERCENTAGE OF REGISTERED VOTERS (ER) --------------------------------------------------------------------------- Official voter turnout - Percentage of registered voters (ER). .................................................................. 000.00-100.00 PERCENT OF REGISTERED VOTERS WHO VOTED 999.00 MISSING | VARIABLE NOTES: E5006_1 | | E5006_1 details The Electoral Register (ER) turnout, which is the | total number of votes cast (valid and invalid) divided by the | number of names on the voters' register, expressed as a | percentage. | | Turnout data refers to lower house elections unless otherwise | specified in the ELECTION STUDY NOTES below. | In cases where E5006_1 refers to Presidential elections with two | rounds of voting, turnout data refers to Round 1. Where | applicable, ELECTION STUDY NOTES below provide data for Round 2. | | Turnout data primarily comes from the International Institute | for Democracy and Electoral Assistance (IDEA) Voter Turnout | Database: http://www.idea.int/data-tools/data/voter-turnout | (Date accessed: May 17, 2018). | | If the source deviates from the above, it is detailed in the | ELECTION STUDY NOTES. | ELECTION STUDY NOTES - BELGIUM-FLANDERS (2019): E5006_1 | | These data refer to turnout in the Belgian-Flanders region only. | The ER turnout for Belgium based on the percentage of registered | voters was 88.4%. | ELECTION STUDY NOTES - BELGIUM-WALLONIA (2019): E5006_1 | | These data refer to turnout in the Belgian-Wallonia region only. | The ER turnout for Belgium based on the percentage of registered | voters was 88.4%. | ELECTION STUDY NOTES - BRAZIL (2018): E5006_1 | | In the Presidential election, the ER turnout in Round 1 was | 79.7%, and 78.7% in Round 2. | ELECTION STUDY NOTES - CHILE (2017): E5006_1 | | The estimate for Electoral Register (ER) turnout in Chile is | based on the total number of votes (including spoilt) cast as | being 6,673,831. | | Source of data: Electoral Service of Chile | https://historico.servel.cl/ (Date accessed: March 04, 2019). | | In the Presidential election, the ER turnout in Round 1 was | 46.7%, and 49.0% in Round 2. | ELECTION STUDY NOTES - CANADA (2019): E5006_1 | | The estimate for Electoral Register (ER) turnout in Canada is | based on the total number of votes (including spoilt) cast as | being 27,373,058. | | Source of data: Elections Canada | https://www.elections.ca/res/rep/off/ovr2019app/home.html#3 | (Date accessed: February 24, 2021). | ELECTION STUDY NOTES - DENMARK (2019): E5006_1 | | These data refer to turnout in Denmark including votes cast in | the Faroe Islands and Greenland, two autonomous territories in | the Kingdom of Denmark. The official voter turnout for mainland | Denmark based on the percentage of registered voters was 84.6%. | ELECTION STUDY NOTES - COSTA RICA (2018): E5006_1 | | In the Presidential election, the ER turnout was 65.7%. | ELECTION STUDY NOTES - EL SALVADOR (2019): E5006_1 | | These data refer to the Presidential election. | ELECTION STUDY NOTES - FINLAND (2019): E5006_1 | | These data refer to the ER turnout based on all Finish citizens | including those who live abroad. | ELECTION STUDY NOTES - FRANCE (2017): E5006_1 | | These data refer to turnout in Round 1 of the Presidential | election. The ER turnout in Round 2 was 74.6%. | ELECTION STUDY NOTES - GREAT BRITAIN (2017 & 2019): E5006_1 | | These data refer to the turnout in Great Britain only, that is, | the turnout in England, Scotland, and Wales combined. | Northern Ireland data is not included as the 2017 and 2019 | British Election Studies did not include respondents from | Northern Ireland. | ELECTION STUDY NOTES - HONG KONG (2016): E5006_1 | | These data refer to turnout in the geographical constituency | tier. | ELECTION STUDY NOTES - MEXICO (2018): E5006_1 | | In the Presidential election, the ER turnout was 63.4%. | ELECTION STUDY NOTES - PERU (2021): E5006_1 | | These data refer to turnout in Round 1 of the Presidential | election. ER Turnout in Round 2 of the Presidential elections was | 74.6%. ER Turnout in the Congressional elections was 70.1%. | ELECTION STUDY NOTES - SOUTH KOREA (2016): E5006_1 | | E5006_1 refers to the turnout in the majoritarian segment. | ELECTION STUDY NOTES - TAIWAN (2016): E5006_1 | | These data refer to the turnout in the geographical constituency | tier. ER Turnout in the Presidential election was 66.3%. | ELECTION STUDY NOTES - TAIWAN (2020): E5006_1 | | These data refer to the turnout in the geographical constituency | tier. ER Turnout in the Presidential election was 74.9%. | ELECTION STUDY NOTES - TUNISIA (2019): E5006_1 | | In the Presidential election, the ER turnout in Round 1 was | 49.0%, and 55.0% in Round 2. | ELECTION STUDY NOTES - TURKEY (2018): E5006_1 | | In the Presidential election, the ER turnout was 86.2%. | ELECTION STUDY NOTES - UNITED STATES (2016 & 2020): E5006_1 | | These data refer to turnout in the Presidential elections. | Percentage of registered voters estimate is taken from the IDEA. | | Source of data: | IDEA Voter Turnout for the United States | https://www.idea.int/data-tools/country-view/295/40 | (Date accessed: December 10, 2021). | ELECTION STUDY NOTES - URUGUAY (2019): E5006_1 | | Uruguay uses a Multiple Simultaneous Vote (MVS) system, where | voters cast a single vote for all elections, meaning turnout is | the same for the Presidential, Lower, and Upper House elections. | ER Turnout in Round 2 of the Presidential election was 96.2%. --------------------------------------------------------------------------- E5006_2 >>> ELECTORAL TURNOUT - TURNOUT AS A PERCENTAGE OF THE VOTING AGE POPULATION (VAP) --------------------------------------------------------------------------- Official voter turnout - Percentage of voting age population (VAP). .................................................................. 000.00-100.00 PERCENT OF VOTING AGE POPULATION 999.00 MISSING | VARIABLE NOTES: E5006_2 | | E5006_2 details the Voting Age Population (VAP), which includes | all citizens above the legal voting age in a country. It is not | intended to be a precise measure of the number of citizens | entitled to vote as it does not take into account legal or | systematic impediments such as resident non-citizens. Rather, its | intent is to provide an estimate of turnout besides estimates | based solely on an electoral register. Voter registers are often | outdated or inaccurate or in some circumstances are not used | for elections (e.g., 1994 South African elections). | | In some polities, voters are registered automatically and hence | it might be expected that the electoral register measure and the | voting age population can be identical. This is not always the | case for the reasons set out above. However, and unless we can | verify the accuracy, CSES reports the Voting Age Population as | listed by the IDEA. However, ELECTION STUDY NOTES below do alert | users to instances where voter registration is automatic and | thus to cases in which in theory the ER and VAP estimates could | be identical. | | Turnout data refers to lower house elections unless otherwise | specified in the ELECTION STUDY NOTES below. | | In cases where E5006_2 refers to Presidential elections with two | rounds of voting, turnout data refer to the first round. Where | applicable, ELECTION STUDY NOTES below provide data for the | second round. | | Turnout data primarily comes from the International Institute | for Democracy and Electoral Assistance (IDEA) Voter Turnout | Database: http://www.idea.int/data-tools/data/voter-turnout | (Date accessed: May 17, 2018). | | If the source deviates from the above, it is detailed in the | ELECTION STUDY NOTES. | | Data are unavailable for JAPAN (2017). | ELECTION STUDY NOTES - BELGIUM-FLANDERS (2019): E5006_2 | | These data refer to turnout in Belgium, as voting age population | data for the Belgium-Flanders region is unavailable. | ELECTION STUDY NOTES - BELGIUM-WALLONIA (2019): E5006_2 | | These data refer to turnout in Belgium, as voting age population | data for the Belgium-Wallonia region is unavailable. | ELECTION STUDY NOTES - BRAZIL (2018): E5006_2 | | In the Presidential election, the VAP turnout in Round 1 was | 76.8%, and 75.9% in Round 2. | ELECTION STUDY NOTES - CHILE (2017): E5006_2 | | In the Presidential election, the VAP turnout in Round 1 was | 49.8%, and 52.2% in Round 2. | ELECTION STUDY NOTES - COSTA RICA (2018): E5006_2 | | In the Presidential election, the VAP turnout was 59.9%. | ELECTION STUDY NOTES - DENMARK (2019): E5006_2 | | These data refer to turnout in mainland Denmark, as voting age | population data for Greenland and Faroe Islands region are | unavailable. | ELECTION STUDY NOTES - EL SALVADOR (2019): E5006_2 | | These data refer to the Presidential election. | ELECTION STUDY NOTES - FINLAND (2019): E5006_2 | | Voter registration in Finland is compulsory, so the data for | E5006_1 and E5006_2 are identical. | ELECTION STUDY NOTES - FRANCE (2017): E5006_2 | | These data refer to VAP turnout in Round 1 of the Presidential | election. VAP turnout in Round 2 was 67.9%. | ELECTION STUDY NOTES - GREAT BRITAIN (2017 & 2019): E5006_2 | | These data refer to the Voting Age Population of the United | Kingdom - England, Scotland, Wales, and Northern Ireland. | ELECTION STUDY NOTES - HONG KONG (2016): E5006_2 | | These data refer to the turnout in the geographical constituency | tier. The VAP turnout is calculated by CSES using data from the | Hong Kong Census. | | Source of data: | http://www.censtatd.gov.hk/hkstat/sub/sp150.jsp?tableID=002&ID= | 0&productType=8; | (Date accessed: May 08, 2019). | ELECTION STUDY NOTES - MEXICO (2018): E5006_2 | | This data refers to the turnout at the parliamentary elections | of 1 July 2018. The VAP turnout at the Presidential election, | that took part on the same day (single round), was 65.983%. | ELECTION STUDY NOTES - NEW ZEALAND (2017): E5006_2 | | The estimate for VAP turnout in New Zealand is based on | the total electoral population (including Maori electorates) | of 3,582,270 from Statistics NZ published in June 2017. | ELECTION STUDY NOTES - NEW ZEALAND (2020): E5006_2 | | The estimate for VAP turnout in New Zealand is based on | the total electoral population (including Maori electorates) | of 4,694,214 from the NZ Electoral Commission. | | Source of data: | New Zealand Election Commission 2020 Results | https://www.electionresults.govt.nz/electionresults_2020/ | statistics/party-votes-and-turnout-by-electorate.html | (Date accessed: October 19, 2021) | ELECTION STUDY NOTES - PERU (2021): E5006_2 | | These data refer to turnout in Round 1 of the Presidential | election. Turnout in Round 2 of the Presidential elections was | 83.4%. Turnout in the Congressional elections was 78.6%. | ELECTION STUDY NOTES - SOUTH KOREA (2016): E5006_2 | | The data refers to the turnout in the majoritarian segment. | ELECTION STUDY NOTES - TAIWAN (2016): E5006_2 | | These data refer to the turnout in the geographical | constituencies, which employ the first-past-the-post system. | In the Presidential election, the VAP turnout was 65.8%. | ELECTION STUDY NOTES - TAIWAN (2020): E5006_2 | | These data refer to the turnout in the geographical | constituencies, which employ the first-past-the-post system. | In the Presidential election, the VAP turnout was 74.4% based | on IDEA's VAP estimate. | ELECTION STUDY NOTES - TUNISIA (2019): E5006_2 | | VAP turnout in the Presidential election was 41.0% in Round 1 and | 47.4% in Round 2. | ELECTION STUDY NOTES - TURKEY (2018): E5006_2 | | In the Presidential election, the VAP turnout was 89.0%. | ELECTION STUDY NOTES - UNITED STATES (2016): E5006_2 | | Turnout data is based on turnout in the Presidential election. | Voting Age Population estimate is taken from the American | Federal Election Commission. | | Source of data: | American Federal Election Commission: | https://transition.fec.gov/pubrec/fe2016/ | federalelections2016.pdf | (Date accessed: March 23, 2019). | ELECTION STUDY NOTES - UNITED STATES (2020): E5006_2 | | Turnout data is based on turnout in the Presidential election. | The Voting Age Population estimate comes from the United States | Elections Project. The Voting Age Population estimate often | includes citizens who are ineligible to vote (for example, | felons). The United States Elections Project also calculates | an estimate of the Voting Age Population excluding ineligible | citizens from the estimate, known as the Voting Eligible | Population (VEP). These data represent the VAP estimate to | ensure cross-national comparability. | | The Voting Eligible Population (VEP) estimate is based on a | denominator of 239,247,182 and yields a VEP turnout rate of | 66.2%. | | Source of data: | United States Elections Project | http://www.electproject.org/2020g | (Date accessed: December 10, 2021). | ELECTION STUDY NOTES - URUGUAY (2019): E5006_1 | | Uruguay uses a Multiple Simultaneous Vote (MVS) system, where | voters cast a single vote for all elections, meaning turnout is | the same for the Presidential, Lower, and Upper House elections. | VAP Turnout in Round 2 of the Presidential election was 94.9%. --------------------------------------------------------------------------- E5007_1 >>> ELECTORAL MANAGEMENT: ELECTORAL ADMINISTRATION MODEL --------------------------------------------------------------------------- Electoral Administration Model. .................................................................. 1. INDEPENDENT BODY 2. GOVERNMENT 3. MIXED 6. INFORMATION UNAVAILABLE 9. MISSING | VARIABLE NOTES: E5007_1 | | E5007_1 details whether the administration of an election is | conducted by an independent body, a government body, or whether | it is a mixed/hybrid system. | | Source of data: | ACE Electoral Knowledge Network - see: http://aceproject. | org/epic-en/CDTable?view=country&question=EM012 | (Date accessed: October 30, 2018) --------------------------------------------------------------------------- E5007_2 >>> ELECTORAL MANAGEMENT: COMPULSORY VOTER REGISTRATION --------------------------------------------------------------------------- Compulsory Voter Registration. .................................................................. 1. YES 5. NO 9. MISSING | VARIABLE NOTES: E5007_2 | | E5007_2 details whether voter registration is compulsory or not. | | Source of data: | ACE Electoral Knowledge Network - see: http://aceproject. | org/epic-en/CDTable?view=country&question=EM012 | (Date accessed: October 30, 2018) --------------------------------------------------------------------------- E5008_1 >>> VOTING OPERATIONS: EARLY/ADVANCE VOTING --------------------------------------------------------------------------- M04c. Can voters cast a ballot before Election Day(s)? (i.e., Is early voting possible)? .................................................................. 1. YES, FOR THE WHOLE ELECTORATE 2. YES, BUT ONLY FOR SOME OF THE ELECTORATE [SEE ELECTION STUDY NOTES FOR SPECIFICATION] 5. NO 9. MISSING | VARIABLE NOTES: E5008_1 | | E5008_1 details whether early voting is possible for some or | the whole of the electorate. | | Source of data: CSES Macro Report Q4c. | ELECTION STUDY NOTES - EL SALVADOR (2019): E5008_1 | | Early/advance voting is available for citizens residing overseas | (mainly Salvadorans in the United States). | ELECTION STUDY NOTES - GREAT BRITAIN (2017 & 2019): E5008_1 | | Early/advance voting available for citizens with a postal ballot. | ELECTION STUDY NOTES - HUNGARY (2018): E5008_1 | | Early/advance voting is available for citizens residing overseas. | ELECTION STUDY NOTES - IRELAND (2016): E5008_1 | | Some citizens are eligible for a postal vote, namely: | Serving members of the Irish police and the army, an Irish | diplomat (or their family members) posted abroad, students | studying full-time at an educational institute in Ireland | which is away from their residential address, and if a voter | has a physical illness or disability which prevents them from | attending a polling station. | | Source of data: | Citizens Information Ireland | https://www.citizensinformation.ie/en/government_in_ireland/ | elections_and_referenda/voting/registering_to_vote.html | (Date accessed: April 18, 2020). | ELECTION STUDY NOTES - ISRAEL (2020): E5008_1 | | Early/advance voting is available for soldiers and official | representatives of the Israeli state abroad at the time of the | poll. | ELECTION STUDY NOTES - ITALY (2018): E5008_1 | | Early/advance voting is available for citizens residing overseas. | ELECTION STUDY NOTES - MEXICO (2018): E5008_1 | | Early/advance voting is available for citizens residing overseas. | ELECTION STUDY NOTES - NETHERLANDS (2017): E5008_1 | | Early/advance voting is available for citizens residing overseas. | ELECTION STUDY NOTES - NETHERLANDS (2021): E5008_1 | | Early/advance voting is traditionally available for citizens | residing overseas. For the 2021 election, advance voting was | temporarily introduced for all the electorate due to the ongoing | COVID-19 pandemic. | ELECTION STUDY NOTES - POLAND (2019): E5008_1 | | Early/advance voting is available for citizens with moderate/ | severe disabilities. | ELECTION STUDY NOTES - ROMANIA (2016): E5008_1 | | Early/advance voting is available for citizens residing overseas. | ELECTION STUDY NOTES - THAILAND (2019): E5008_1 | | Early/advance voting is available for citizens registered to | vote by close of registration for the March 24, 2019 election. | ELECTION STUDY NOTES - TURKEY (2018): E5008_1 | | Early/advance voting is available for citizens residing overseas. | Citizens traveling on election day could vote at the airport. | ELECTION STUDY NOTES - UNITED STATES (2016): E5008_1 | | Early/advance voting in person is allowed without excuse in | 26 states and the District of Columbia. The states that do | not allow this are: AL, CO, CT, DE, KY, MA, MI, ME, MN, MO, MS, | MT, NH, NJ, OH, OK, PA, RI, SC, SD, VA, WA, WI, WY, although in | some of the aforementioned states within a certain period of | time before election day, provisions exist allowing a voter to | apply in person for an absentee ballot (referred to as absentee | ballot without excuse) where a voter will cast the ballot in | an election office prior to election day. The count above, | however, only includes states that have the formal early | voting provisions in place. | | Source of data: | National Conference of State Legislatures: | http://www.ncsl.org/research/elections-and-campaigns/ | early-voting-in-state-elections.aspx | (Date accessed: March 25, 2019). --------------------------------------------------------------------------- E5008_2 >>> VOTING OPERATIONS: VOTE BY MAIL/POSTAL --------------------------------------------------------------------------- M04d. Can voters cast a ballot by mail? .................................................................. 1. YES, FOR THE WHOLE ELECTORATE 2. YES, BUT ONLY FOR SOME OF THE ELECTORATE [SEE ELECTION STUDY NOTES FOR SPECIFICATION] 5. NO 9. MISSING | VARIABLE NOTES: E5008_2 | | E5008_2 details whether mail voting is possible for some or | the whole of the electorate. | | Source of data: CSES Macro Report Q4d. | ELECTION STUDY NOTES - EL SALVADOR (2019): E5008_2 | | Mail voting is available only for citizens residing overseas | (mainly Salvadorans in the United States). | ELECTION STUDY NOTES - FINLAND (2019): E5008_2 | | Mail voting is available for citizens residing overseas or | citizens out of the country on election day. | ELECTION STUDY NOTES - HUNGARY (2018): E5008_2 | | Mail voting is available for citizens residing overseas. | ELECTION STUDY NOTES - INDIA (2019): E5008_2 | | Mail voting is available for citizens residing overseas and | active duty military service personnel. | ELECTION STUDY NOTES - IRELAND (2016): E5008_2 | | Some citizens are eligible for a mail (postal) vote, namely: | Serving members of the Irish police and the army, an Irish | diplomat (or their family members) posted abroad, students | studying full-time at an educational institute in Ireland | which is away from their residential address, and if a voter | has a physical illness or disability which prevents them from | attending a polling station. | | Source of data: | Citizens Information Ireland | https://www.citizensinformation.ie/en/government_in_ireland/ | elections_and_referenda/voting/registering_to_vote.html | (Date accessed: April 18, 2020). | ELECTION STUDY NOTES - ITALY (2018): E5008_2 | | Mail voting is available for citizens residing overseas. | ELECTION STUDY NOTES - JAPAN (2017): E5008_2 | | Mail voting is available for citizens with disabilities. | ELECTION STUDY NOTES - LATVIA (2018): E5008_2 | | Mail voting is available for citizens residing overseas. | ELECTION STUDY NOTES - LITHUANIA (2016 & 2020): E5008_2 | | Mail voting is available for citizens residing overseas and | institutionalized persons. | ELECTION STUDY NOTES - MONTENEGRO (2016): E5008_2 | | A procedure called mobile voting involves a voter who is ill | can request that an Electoral Commission representative visit | them so they can cast a ballot. | ELECTION STUDY NOTES - NETHERLANDS (2017): E5008_2 | | Mail voting is available for citizens residing overseas. | ELECTION STUDY NOTES - NETHERLANDS (2021): E5008_2 | | Mail voting is available for citizens residing overseas. For the | 2021 election, the opportunity to vote by mail was granted | temporarily to older citizens, due to the ongoing COVID-19 | pandemic as older cohorts were considered especially vulnerable | to the COVID-19 virus. | ELECTION STUDY NOTES - NEW ZEALAND (2017 & 2020): E5008_2 | | Mail voting is available for citizens residing overseas, disabled | citizens, and citizens hospitalized at the time of the election. | ELECTION STUDY NOTES - POLAND (2019): E5008_2 | | Mail voting is available for citizens with moderate/severe | disabilities. | ELECTION STUDY NOTES - PORTUGAL (2019): E5008_2 | | Mail voting is available for citizens residing overseas. | ELECTION STUDY NOTES - ROMANIA (2016): E5008_2 | | Mail voting is available for citizens residing overseas. | ELECTION STUDY NOTES - SLOVAKIA (2020): E5008_2 | | Mail voting is available for citizens residing overseas. | ELECTION STUDY NOTES - SWEDEN (2018): E5008_2 | | Mail voting is available for citizens residing overseas. | ELECTION STUDY NOTES - UNITED STATES (2016): E5008_2 | | Colorado (CO), Oregon (OR), and Washington (WA) implement | mail-only voting in their states and all implemented this | policy for the 2016 Presidential elections. Elsewhere, | Certain elections in certain states may be held entirely by | mail. The circumstances under which all-mail elections are | permitted to vary from state to state. The states which have | provisions for voting by mail in certain circumstances are: | AL, AK, AZ, CA, FL, HA, ID, KS, MD, MN, MO, MT, NB, NV, NJ, | NM, ND, and UT. Not all of these states implemented this | policy for the 2016 election. | | Source of data: | National Conference of State Legislatures | http://www.ncsl.org/research/elections-and-campaigns/ | early-voting-in-state-elections.aspx | (Date accessed: March 25, 2019). --------------------------------------------------------------------------- E5008_3 >>> VOTING OPERATIONS: VOTE ONLINE/INTERNET --------------------------------------------------------------------------- M04e. Can voters cast a ballot online? .................................................................. 1. YES, FOR THE WHOLE ELECTORATE 2. YES, BUT ONLY FOR SOME OF THE ELECTORATE [SEE ELECTION STUDY NOTES FOR SPECIFICATION] 5. NO 9. MISSING | VARIABLE NOTES: E5008_3 | | E5008_3 details whether online voting is possible for some or | the whole of the electorate. | | Source of data: CSES Macro Report Q4e. | ELECTION STUDY NOTES - NEW ZEALAND (2017 & 2020): E5008_3 | | Online/Internet voting is available for citizens residing | overseas. --------------------------------------------------------------------------- E5009 >>> PARTY OF THE PRESIDENT BEFORE --------------------------------------------------------------------------- M02a. Party/Coalition of the President before the election. .................................................................. 000001-999987. [SEE PART 3 OF CODEBOOK FOR NUMERICAL PARTY/ COALITION CODES] 999989. INDEPENDENT CANDIDATE 999997. NOT APPLICABLE 999999. MISSING | VARIABLE NOTES: E5009 | | E5009 details the party/coalition holding the role of President | before the election, regardless of whether there was a | Presidential election or not. | | Parties/coalitions and their numerical and alphabetical | classifications for each election study are detailed in Part 3 of | the CSES Codebook. | | Source of data: CSES Macro Report M2a. | ELECTION STUDY NOTES - AUSTRIA (2017): E5009 | | The incumbent President Alexander Van der Bellen was elected | as an Independent candidate. However, he is the former leader of | the Green Party, and suspended his membership of the party | while President. | ELECTION STUDY NOTES - BRAZIL (2018): E5009 | | The incumbent President was Michel Temer of the MDB (Brazilian | Democratic Movement, PARTY F). Dilma Rousseff of the Workers' | Party (PT, PARTY B) who was elected President in 2014, was | impeached in 2016. | ELECTION STUDY NOTES - CZECHIA (2017): E5009 | | Since 2013, the President of Czechia has been elected | directly by popular vote, having previously been selected by the | Czech Parliament. Milos Zeman (Party of Civic Rights) was | elected President in January 2013 for a five-year term. The | President's party held no seats in the Czech lower house of | parliament before or after the 2017 elections. As President, | Mr. Zeman cooperated with several parties, especially the | anti-establishment parties, including the Action of Dissatisfied | Citizens/Yes (Akce Nespokojenych Obcanu, ANO 2011, PARTY A). | ELECTION STUDY NOTES - CZECHIA (2021): E5009 | | Since 2013, the President of Czechia has been elected directly | by popular vote, having previously been selected by the Czech | Parliament. Milos Zeman (Party of Civic Rights) was re-elected | President in January 2018 for a second consecutive term. | While none of the major parties contesting the 2017 or 2021 | parliamentary elections ran an official candidate in the | Presidential contest, several parties endorsed candidates. | President Zeman received some support from anti-establishment | parties, including the Action of Dissatisfied Citizens/Yes | (Akce Nespokojenych Obcanu, ANO 2011, PARTY B) and the | Freedom and Direct Democracy (Svoboda a Prima Demokracie, SPD, | PARTY D). | ELECTION STUDY NOTES - HONG KONG (2016): E5009 | | The Chief Executive (CE) in Hong Kong, the highest selected | government official in the Hong Kong executive, can be seen as | an equivalent of President elsewhere. They are elected by | 1200-member Election Committee, an electoral college consisting | of individuals (i.e. private citizens) and bodies (i.e. special | interest groups) selected or elected within 28 Functional | Constituencies. According to Chapter 569 of the Laws of Hong Kong | the CE cannot be a member of any political party. | ELECTION STUDY NOTES - PERU (2021): E5009 | | Francisco Sagasti assumed the presidency in November 2020 after | President Martin Vizcarra, elected as Vice President in 2016 as | the running mate of the 2016 election winner, Pedro Pablo | Kuczynski, was impeached. In March 2018, facing the likelihood | of impeachment over corruption allegations involving the bankrupt | Brazilian construction firm Odebrecht, Pedro Kuczynski resigned | as President. He was replaced by Martin Vizcarra, whom Congress | impeached in November 2020 on the grounds of "moral | incompetence." Initially, the President of Congress and | Opposition leader Manuel Merino became acting President. The | impeachment of Vizcarra was considered by many to be frivolous | and led to nationwide protests, resulting in the resignation of | Merino as acting President after six days in office. Due to | vacancies in the position of President and Vice President, | Sagasti (Purple Party) as President of Congress became President | by the line of succession. | ELECTION STUDY NOTES - ROMANIA (2016): E5009 | | Officially, the President is not allowed to be a member of a | political party during his term in office. | However, he/she may be publicly endorsed by a specific | party. In February 2013, Klaus Iohannis joined the National | Liberal Party (PNL, PARTY B). --------------------------------------------------------------------------- E5010 >>> PARTY OF THE PRIME MINISTER BEFORE --------------------------------------------------------------------------- M02b. Party of the Prime Minister before the election. .................................................................. 000001-999987. [SEE PART 3 OF CODEBOOK FOR NUMERICAL PARTY/ COALITION CODES] 999989. INDEPENDENT CANDIDATE 999997. NOT APPLICABLE 999999. MISSING | VARIABLE NOTES: E5010 | | E5010 details the party holding the role of Prime Minister before | the election, regardless of whether there was a parliamentary | election or not. | | Parties/coalitions and their numerical and alphabetical | classifications for each election study are detailed in Part 3 of | the CSES Codebook. | | Source of data: CSES Macro Report M2b. | ELECTION STUDY NOTES - BELGIUM-FLANDERS (2019): E5010 | | The Prime Minister of Belgium before the 2019 elections was | Charles Michel of the Reformist Movement (MR). This party | does not contest elections in Flanders, instead contesting | elections in the Wallonia and the Brussels regions. | ELECTION STUDY NOTES - ISRAEL (2020): E5010 | | A new government failed to be formed after the March and | September 2019 elections, respectively. Post the September 2019 | contest, incumbent Prime Minister Benjamin Netanyahu (Likud, | National Liberal Party, PARTY A) and Benny Gantz (Kahol Lavan, | Blue and White, PARTY B) failed in their attempts to put | together majority coalition governments. On December 11, 2019 | the Israeli Parliament (the Knesset) voted to dissolve itself, | with new elections scheduled for March 2020. During this period, | Benjamin Netanyahu remained caretaker Prime Minister, and the | data characterizes him as the incumbent Prime Minister. | ELECTION STUDY NOTES - SOUTH KOREA (2016): E5010 | | Note from the Collaborator: "The Prime Minister of Korea is not | affiliated to any party by law. (Note: He/she is usually not a | political figure. The Prime Minister is appointed by the | President. In a broad sense, you could say that the Prime | Minister tends to be politically close to the ruling party | because he/she was chosen by the President. In other words, | the Prime Minister of Korea probably has the similar political | views with the President)." | ELECTION STUDY NOTES - TUNISIA (2019): E5010 | | Youssef Chahed served as the 14th Prime Minister of Tunisia from | 27 August 2016 to 27 February 2020. He used to be a member of | Nidaa Tounes/Tunisia's Call, while in June 2019 he formed a new | political party, under the name of Tahya Tounes/Long live | Tunisia, and became its President. --------------------------------------------------------------------------- E5011_A >>> NUMBER OF PORTFOLIOS BEFORE ELECTION - PARTY A E5011_B >>> NUMBER OF PORTFOLIOS BEFORE ELECTION - PARTY B E5011_C >>> NUMBER OF PORTFOLIOS BEFORE ELECTION - PARTY C E5011_D >>> NUMBER OF PORTFOLIOS BEFORE ELECTION - PARTY D E5011_E >>> NUMBER OF PORTFOLIOS BEFORE ELECTION - PARTY E E5011_F >>> NUMBER OF PORTFOLIOS BEFORE ELECTION - PARTY F E5011_G >>> NUMBER OF PORTFOLIOS BEFORE ELECTION - PARTY G E5011_H >>> NUMBER OF PORTFOLIOS BEFORE ELECTION - PARTY H E5011_I >>> NUMBER OF PORTFOLIOS BEFORE ELECTION - PARTY I --------------------------------------------------------------------------- M02c. Number of cabinet posts (portfolios) held by PARTY/COALITION [A/B/C/D/E/F/G/H/I] before the election. .................................................................. 00.00-99.00 NUMBER OF CABINET POSTS BEFORE ELECTION 999.00 MISSING | VARIABLE NOTES: E5011_ | | Parties/coalitions and their numerical and alphabetical | classifications for each election study are detailed in Part 3 of | the CSES Codebook. | | Ministers are considered those members of government who are | members of the Cabinet and who have Cabinet voting rights. This | includes the Prime Minister. | | Cabinet members listed in E5011_ represent parties/coalitions | receiving an alphabetical classification by CSES. | Cabinet members who represent parties/coalitions not receiving | such a classification or those who are Independents are | classified by variable E5012, which classifies the total size | of the cabinet before the election. Users are advised to consult | the ELECTION STUDY NOTES of variable E5012. | | Source of data: CSES Macro Report M2c. | | Data are unavailable for EL SALVADOR (2019) and UNITED STATES | (2016 & 2020). | ELECTION STUDY NOTES - HONG KONG (2016): E5011 | | In Hong Kong, the Executive Council (ExCo), which is established | to assist the Chief Executive (CE; equivalent to Prime Minister | or President) in policy-making, is equivalent to the cabinet | elsewhere. However, the majority views of the ExCo, if any, are | not binding, and it remains the CE's prerogative to accept | recommendations or not. Thus, it can be argued the ExCo members | do not have voting rights per se. | ExCo consisted of the CE and 30 members (16 official members and | 14 non-official members) prior to the 2016 LegCo Election (as of | December 31, 2015). Only five of the ExCo members have a party | affiliation, reported in this variable. | Source of data: Compiled from Hong Kong Year Book 2015, | Appendix 1. | https://www.yearbook.gov.hk/2015/en/pdf/Appendices.pdf | (Date accessed: August 21, 2017). | ELECTION STUDY NOTES - ISRAEL (2020): E5011_H | | The cabinet positions occupied by Habavit Hayehudi (The Jewish | Home) and the New Right are included in the Yamina total as | these parties contested the 2020 elections in the Yamina | (PARTY H) alliance. | ELECTION STUDY NOTES - MEXICO (2018): E5011 | | These data include the members of the expanded cabinet, that | is, it includes the heads of fundamental institutions for the | Mexican State who are also appointed by the President of the | Republic. These are the Mexican Institute of Social Security | (IMSS), the Institute of Security and Social Services for State | Workers (ISSSTE), Petroleos Mexicanos (PEMEX), the Federal | Electricity Commission (CFE) and the National Water Commission | (CONAGUA). | ELECTION STUDY NOTES - MONTENEGRO (2016): E5011_C | | These data refer to DEMOS (Democratic Alliance; Demokratski | Savez), the leading party in the coalition Kljuc (Key Coalition). | ELECTION STUDY NOTES - SOUTH KOREA (2016): E5011_A | | Collaborator advises most of the Ministers are not affiliated to | political parties, but they can be considered as the members of | the Saenuri Party (SP, PARTY A) as they were chosen by the | President, a member of this party, implying ministers likely | have similar views to the President. --------------------------------------------------------------------------- E5012 >>> SIZE OF THE CABINET BEFORE ELECTION --------------------------------------------------------------------------- M02d. The size of the cabinet before the election. .................................................................. 00.00-99.00 SIZE OF THE CABINET 999.00 MISSING | VARIABLE NOTES: E5012 | | E5012 details total cabinet size before the election, based on | the following definition adopted by CSES: | a) Parliamentary and Semi-Presidential Regimes: | Cabinet size is defined by the total number of ministers | (persons, not posts) in a defined government. Ministers are | considered members of a cabinet when they exercise voting | rights. This number includes both ministers with and without | portfolio and the Prime Minister, but excludes deputy | ministers, undersecretaries, parliamentary secretaries, | ministerial alternates, given that in the majority of cases, | they do not exercise full voting rights. | b) Presidential Regimes: | Cabinet size is defined by the total number of ministers or | secretaries who head a ministry. | | Source of data: CSES Macro Report M2d. | | Data are unavailable for EL SALVADOR (2019) and UNITED STATES | (2016 & 2020). | ELECTION STUDY NOTES - AUSTRIA (2017): E5012 | | Two additional posts were held by independents, although they | were nominated by the OVP (PARTY A), bringing the total | number to 14. | ELECTION STUDY NOTES - BELGIUM-FLANDERS (2019): E5012 | | The Reformist Movement (MR) who only contests elections in | Wallonia (PARTY B, Belgium-Wallonia) occupied the remaining seven | cabinet positions, including the Prime Minister, bringing the | total number to 13. | ELECTION STUDY NOTES - BELGIUM-WALLONIA (2019): E5012 | | The remaining cabinet ministries were occupied by the | Christen-Democratisch en Vlaams (CD&V, 5) and Open Vlaamse | Liberalen den Democratsen (Open-VLD, 3), both of whom primarily | contest elections in Flanders only (CD&V, PARTY C; Open-VLD, | PARTY D), bringing the total number to 13. | ELECTION STUDY NOTES - BRAZIL (2018): E5012 | | Independents occupied 16 cabinet positions, with one cabinet | position each for the Partido Verde (PV) and Podemos (PODE), | bringing the total number to 29. | ELECTION STUDY NOTES - CHILE (2017): E5012 | | Six additional posts were held by five independents, and one | by the Citizens Left (Izquierda Ciudadana), bringing the total | number to 23. | ELECTION STUDY NOTES - COSTA RICA (2018): E5012 | | Independents occupied the remaining four cabinet positions, | bringing the total to 22. | ELECTION STUDY NOTES - DENMARK (2019): E5012 | | The remaining six cabinet posts were held by the Liberal | Alliance, bringing the total to 22. | ELECTION STUDY NOTES - FRANCE (2017): E5012 | | Two additional posts were held by Parti Radical de Gauche | (Radical left), and one by Parti Ecologiste (Ecologists), | bringing the total to 18. | ELECTION STUDY NOTES - GREECE (2019): E5012 | | One additional post was held by DIMAR (Democratic Left), bringing | the total to 23. From 2019, DIMAR was affiliated with SYRIZA. | ELECTION STUDY NOTES - HONG KONG (2016): E5012 | | The Executive Council (ExCo) had 30 members (16 official members | and 14 non-official members). However, both the official and | non-official members do not have voting rights in the ExCo (SEE | ELECTION STUDY NOTES - HONG KONG (2016): E5011. | In addition to the four ExCo members with party affiliations, | listed in E5011, one additional member was affiliated with BPA - | Business and Professionals Alliance for HK (party coded 344011). | ELECTION STUDY NOTES - INDIA (2019): E5012 | | Bharatiya Janata Party (BJP, PARTY A) held 37 out of 39 posts. | Two additional posts were held by Shiromani Akali Dal (SAD) | party and The Lok Janshakti Party (LJP). | ELECTION STUDY NOTES - ITALY (2018): E5012 | | Additional posts were held by the New Center Right (2 posts), and | the Christian Democratic Union (1 post), bringing the total | number to 19. | ELECTION STUDY NOTES - MEXICO (2018): E5012 | | The cabinet of the Federal Government is made up of 18 | Secretaries of State plus the Legal Adviser to the Federal | Executive, the Attorney General and the Head of the Office | of the President. | In total it is 21 members, including the members of the | expanded cabinet, that is, it includes the heads of fundamental | institutions for the Mexican State who are also appointed by | the President of the Republic. These are the Mexican Institute | of Social Security (IMSS), the Institute of Security and | Social Services for State Workers (ISSSTE), Petroleos Mexicanos | (PEMEX), the Federal Electricity Commission (CFE) and the | National Water Commission (CONAGUA). One additional cabinet post | was held by an independent. | ELECTION STUDY NOTES - MONTENEGRO (2016): E5012 | | Independents held four additional posts, bringing the total to | 21. | ELECTION STUDY NOTES - POLAND (2019): E5012 | | Party A (Law and Justice, Prawo i Sprawiedliwosc, PiS) held 15 | out of 22 posts. The remaining 7 posts were held by PiS' | coalition partners (Agreement/Porozumienie and United | Poland/Solidarna Polska held two positions each), or Independent | (but close to PiS) members. | ELECTION STUDY NOTES - PERU (2021): E5012 | | Independents occupied the remaining cabinet positions, bringing | the total to 19. | ELECTION STUDY NOTES - PORTUGAL (2019): E5012 | | Independents held four additional posts, bringing the total to | 18. | ELECTION STUDY NOTES - ROMANIA (2016): E5012 | | Twenty-one posts were held by independents, bringing the total | to 22. | ELECTION STUDY NOTES - SLOVAKIA (2020): E5012 | | The remaining cabinet ministries were occupied by the Slovak | National Party (SNS, one position), Bridge (Most-Hid, three | positions), and two Independents (albeit one nominated by | Direction - Slovak Social Democracy (Smer-SD); and the other by | the SNS), but who were not members of the respective parties, | bringing the total number to 15. | ELECTION STUDY NOTES - THAILAND (2019): E5012 | | Additional portfolios were held by Phalang Chon Party (one | post) and Chart Pattana Party (one post), bringing the total to | 36. | ELECTION STUDY NOTES - TUNISIA (2019): E5012 | | The remaining 24 posts were held by independents (9 positions), | and members of various other parties and organizations that do | not have an alphabetic code in the CSES categorization. --------------------------------------------------------------------------- E5013 >>> PARTY OF THE PRESIDENT AFTER ELECTION --------------------------------------------------------------------------- M03a. PARTY/COALITION of the President AFTER the election. .................................................................. 000001-999987. [SEE PART 3 OF CODEBOOK FOR NUMERICAL PARTY /COALITION CODES] 999989. INDEPENDENT CANDIDATE 999997. NOT APPLICABLE 999999. MISSING | VARIABLE NOTES: E5013 | | E5013 details the party/coalition holding the role of President | after the election, regardless of whether there was a | Presidential election or not. | | Parties/coalitions and their numerical and alphabetical | classifications for each election study are detailed in Part 3 of | the CSES Codebook. | | Source of data: CSES Macro Report M3a. | ELECTION STUDY NOTES - CZECHIA (2017): E5013 | | SEE ELECTION STUDY NOTES - CZECHIA (2017): E5009. | ELECTION STUDY NOTES - CZECHIA (2021): E5013 | | SEE ELECTION STUDY NOTES - CZECHIA (2021): E5009. | ELECTION STUDY NOTES - EL SALVADOR (2019): E5013 | | Newly elected President of El Salvador became Nayib Bukele, of | GANA party (Grand Alliance for National Unity; Party A). Note | that before the election, Nayib Bukele formed his own party | Nuevas Ideas. This new political party could not complete its | registration on time to participate in the 2019 election. Hence, | Bukele participated in and won the election with the political | party GANA. Nuevas Ideas is coded as Party G in CSES MODULE 5. | ELECTION STUDY NOTES - HONG KONG (2016): E5013 | | SEE ELECTION STUDY NOTES - HONG KONG (2016): E5009. | ELECTION STUDY NOTES - SLOVAKIA (2020): E5013 | | SEE ELECTION STUDY NOTES - SLOVAKIA (2020): E5009. | ELECTION STUDY NOTES - TUNISIA (2019): E5013 | | Kais Saied, the new President, was supported by the Ennahda | Movement (PARTY A) in Round 2 of the contest. --------------------------------------------------------------------------- E5014 >>> PARTY OF THE PRIME MINISTER AFTER ELECTION --------------------------------------------------------------------------- M03b. Party/Coalition of the Prime Minister AFTER the election. .................................................................. 000001-999987. [SEE PART 3 OF CODEBOOK FOR NUMERICAL PARTY/ COALITION CODES] 999989. INDEPENDENT CANDIDATE 999997. NOT APPLICABLE 999999. MISSING | VARIABLE NOTES: E5014 | | E5014 details the party holding the role of Prime Minister after | the election, regardless of whether there was a parliamentary | election or not. | | Parties/coalitions and their numerical and alphabetical | classifications for each election study are detailed in Part 3 of | the CSES Codebook. | | Source of data: CSES Macro Report M3b. | ELECTION STUDY NOTES - BELGIUM-FLANDERS (2019): E5014 | | The Prime Minister of Belgium after the 2019 elections was | Sophie Wilmes of the Reformist Movement (MR), who led a | caretaker government in the aftermath of the 2019 elections | after Charles Michel, the previous caretaker incumbent, resigned | to become President of the European Council. The Wilmes caretaker | administration lasted until October 2020 when Alexander De Croo | from the Open-VLD (PARTY D, Flanders) became Prime Minister, | leading a Vivaldi coalition comprising the Open-VLD (PARTY D), | CD&V (PARTY C), and Groen (PARTY F) from Flanders, and the PS, | MRm and Ecolo parties from Wallonia. | ELECTION STUDY NOTES - BELGIUM-WALLONIA (2019): E5014 | | The Prime Minister of Belgium after the 2019 elections was | Sophie Wilmes of the Reformist Movement (MR, PARTY B), who led a | caretaker government in the aftermath of the 2019 elections | after Charles Michel, the previous caretaker incumbent, resigned | to become President of the European Council. The Wilmes caretaker | administration lasted until October 2020 when Alexander De Croo | from the Open-VLD (PARTY D, Flanders) became Prime Minister, | leading a Vivaldi coalition comprising the Open-VLD (PARTY D), | CD&V (PARTY C), and Groen (PARTY F) from Flanders, and the | Socialist Party (PS, PARTY A), Reformist Movement (MR, PARTY B), | and Ecolo (PARTY C) from Wallonia. | ELECTION STUDY NOTES - CZECHIA (2021): E5014 | | The Prime Minister was Petr Fiala from the Civic Democratic Party | (ODS), one of three parties in the Together (SPOLU) alliance. | ELECTION STUDY NOTES - FRANCE (2017): E5014 | | The new Prime Minister Edouard Philippe was appointed while a | member of Les Republicains (LR, PARTY C). He was later expelled | from the party, having accepted the position of Prime Minister, | and subsequently joined La Republique En Marche! (PARTY A). | ELECTION STUDY NOTES - ISRAEL (2020): E5014 | | Shortly after the 2020 election, the COVID-19 pandemic ramped up | globally, including Israel. Supposedly, this contributed to one | of the leaders of the Kahol Lavan (Blue and White, PARTY B) | alliance, Benny Gantz, reversing his position in the campaign | not to coalesce with Likud (National Liberal Party, PARTY A) | outgoing Prime Minister, Benjamin Netanyahu. In April 2020, | the Gantz faction of Kahol Lavan formed a national unity | government with Likud and other parties, with a rotating | Prime Ministership arrangement, akin to a similar arrangement | in Israel in the 1980s between Yitzak Shamir (Likud) and Shimon | Peres (Labor). Incumbent Premier Netanyahu (Likud, National | Liberal Party, PARTY A) would continue to serve as Prime Minister | for 18 months, with Gantz serving as Defense Minister. Later | Gantz was scheduled to replace Netanyahu as Prime Minister, with | himself also serving for 18 months. The national unity government | was sworn into office on May 17, 2020. However, the government | was short-lived and collapsed in December 2020 over failure to | agree on a new budget, with further elections taking place in | March 2021. | ELECTION STUDY NOTES - ITALY (2018): E5014 | | The Prime Minister Guiseppe Conte was an Independent but | supported by the Five Star Movement (PARTY A) and the League | (PARTY C). | ELECTION STUDY NOTES - SOUTH KOREA (2016): E5014 | | SEE ELECTION STUDY NOTES - SOUTH KOREA (2016): E5010. --------------------------------------------------------------------------- E5015_A >>> NUMBER OF PORTFOLIOS AFTER ELECTION - PARTY A E5015_B >>> NUMBER OF PORTFOLIOS AFTER ELECTION - PARTY B E5015_C >>> NUMBER OF PORTFOLIOS AFTER ELECTION - PARTY C E5015_D >>> NUMBER OF PORTFOLIOS AFTER ELECTION - PARTY D E5015_E >>> NUMBER OF PORTFOLIOS AFTER ELECTION - PARTY E E5015_F >>> NUMBER OF PORTFOLIOS AFTER ELECTION - PARTY F E5015_G >>> NUMBER OF PORTFOLIOS AFTER ELECTION - PARTY G E5015_H >>> NUMBER OF PORTFOLIOS AFTER ELECTION - PARTY H E5015_I >>> NUMBER OF PORTFOLIOS AFTER ELECTION - PARTY I --------------------------------------------------------------------------- M03c. Number of cabinet posts (portfolios) held by PARTY [A/B/C/D/E/F/G/H/I] after the election. .................................................................. 00.00-99.00 NUMBER OF CABINET POSTS AFTER ELECTION 999.00 MISSING | VARIABLE NOTES: E5015_ | | Parties/coalitions and their alphabetical classifications for | each election study are detailed in Part 3 of the CSES Codebook. | | Ministers are considered those members of government who are | members of the Cabinet and who have Cabinet voting rights. This | includes the Prime Minister. | | Cabinet members listed in this variable represent parties | /coalitions receiving an alphabetical classification by CSES. | Cabinet members who represent parties/coalitions not receiving | such a classification or those who are Independents are | classified by variable E5012, which classifies the total size | of the cabinet before the election. Users are advised to consult | the ELECTION STUDY NOTES of variable E5012. | | Source of data: CSES Macro Report M3c. | | Data are unavailable for EL SALVADOR (2019). | ELECTION STUDY NOTES - CZECHIA (2021): E5015_A, E5015_G, E5015_H | | The Together (SPOLU) alliance comprises three parties: | - PARTY A - Civic Democratic Party (Obcanska Demokraticka | Strana, ODS). | - PARTY G - Tradition, Responsibility, Prosperity | (Tradice Odpovednost Prosperita, TOP09). | - PARTY H - Christian and Democratic Union/People's Party | (Krestanska a Demokraticka Unie - Strana lidova, | KDU-CSL). | | The number of cabinet seats for this alliance is provided | separately for each party in the alliance. The complete | distribution of cabinet portfolios for the Together (SPOLU) | alliance is obtained by summing E5015_A, E5015_G, and E5015_H | for Czechia (2021). | ELECTION STUDY NOTES - CZECHIA (2021): E5015_C & E5015_I | | The Pirati - Czech Pirate Party (PARTY A) and STAN - Mayors and | Independents (PARTY I) competed as an alliance. | The number of cabinet seats for this alliance is provided | separately for each party. The complete distribution of cabinet | portfolios for the alliance is obtained by summing E5015_C and | E5015_I for Czechia (2021). | ELECTION STUDY NOTES - HONG KONG (2016): E5015 | | In Hong Kong, the Executive Council (ExCo), which is established | to assist the Chief Executive (CE; equivalent to Prime Minister | or President) in policy-making, is some equivalent to the cabinet | elsewhere. However, the majority views of the ExCo, if any, are | not binding and it is up to the CE to decide whether to accept | them or not. In this sense, the ExCo members do not have voting | rights. | The ExCo consisted of the CE and 31 members (16 official members | and 15 non-official members) after the 2016 LegCo Election (as | of 31 December 2016). Only five of the ExCo members had a party | affiliation, which are reported here. | Source of data: Compiled from Hong Kong Year Book 2016, | Appendix 1. | Available at: https://www.yearbook.gov.hk/2016/en/pdf/ | Appendices.pdf (Date accessed: August 21, 2017). | ELECTION STUDY NOTES - SOUTH KOREA (2016): E5015_A | | Collaborator advises most of the Ministers are not affiliated to | political parties, but they can be considered as the members of | the Saenuri Party (SP, PARTY A) as they were chosen by the | President, a member of this party, implying ministers likely have | similar views to the President. --------------------------------------------------------------------------- E5016 >>> SIZE OF THE CABINET AFTER ELECTION --------------------------------------------------------------------------- M03d. The size of the cabinet after the election. .................................................................. 00.00-99.00 SIZE OF THE CABINET 999.00 MISSING | VARIABLE NOTES: E5016 | | E5016 details the total cabinet size after the election. For a | definition of total cabinet size as adopted by CSES, see | VARIABLE NOTES for E5012. | | Source of data: CSES Macro Report M3d. | | Data are unavailable for EL SALVADOR (2019), NEW ZEALAND (2017) | and UNITED STATES (2016 & 2020). | ELECTION STUDY NOTES - AUSTRIA (2017): E5016 | | Three additional posts were held by independents: two nominated | by the OVP (PARTY A), and one nominated by the FPO (PARTY C). | ELECTION STUDY NOTES - BELGIUM-FLANDERS (2019): E5016 | | The Reformist Movement (MR), who only contest elections in | Wallonia (PARTY B, Belgium-Wallonia) occupied the remaining five | cabinet positions, including the Prime Minister, bringing the | total number to 13. | ELECTION STUDY NOTES - BELGIUM-WALLONIA (2019): E5016 | | The remaining cabinet ministries were occupied by the | Christen-Democratisch en Vlaams (CD&V, 3) and Open Vlaamse | Liberalen den Democratsen (Open-VLD, 3), both of whom primarily | contest elections in Flanders only (CD&V, PARTY C; Open-VLD, | PARTY D), bringing the total number to 13. | ELECTION STUDY NOTES - BRAZIL (2018): E5016 | | The remaining cabinet ministries were occupied by Democratas | (DEM, 3 posts), Partido Novo (NOVO, 1 post), eight held by | Independents and six by members of the military, for a total of | 19. | ELECTION STUDY NOTES - CHILE (2017): E5016 | | Ten additional posts were held by independents, bringing the | total number to 23. | ELECTION STUDY NOTES - COSTA RICA (2018): E5016 | | Two additional posts were held by independent cabinet members, | and one post was held by a member of a regionalist party Partido | Curridabat Siglo XXI (21st Century Curridabat), bringing the | total number to 24. | ELECTION STUDY NOTES - FRANCE (2017): E5016 | | The cabinet comprised 19 members with several other parties | holding cabinet positions. They are as follows: | - Independents: 4 posts | - Democratic Movement (MoDem): 3 posts. | - Parti Radical de Gauche: 2 posts. | - Diverse left: 2 posts. | - Diverse right: 1 post. | - Ecologistes!: 1 post. | ELECTION STUDY NOTES - GREECE (2015): E5016 | | Four additional cabinet positions were held by independents, | bringing the total number to 34. | ELECTION STUDY NOTES - GREECE (2019): E5016 | | Two additional cabinet positions were held by independents, | bringing the total number to 22. | ELECTION STUDY NOTES - HONG KONG (2016): E5016 | | The Executive Council (ExCo) had 31 members (16 official members | and 15 non-official members). However, both the official and | non-official members do not have voting rights in the ExCo (SEE | ELECTION STUDY NOTES - HONG KONG (2016): E5015). | In addition to the three ExCo members with party affiliations | listed in E5011, two additional members were affiliated with | political parties. One with BPA - Business and Professionals | Alliance for HK (party coded 344011), and another one with | Liberal Party (party coded 344015). | ELECTION STUDY NOTES - INDIA (2019): E5016 | | One additional post was occupied by Rashtriya Lok Janshakti | Party (RLJP). This party was formed in October 2021 as a | splinter from the Lok Janshakti Party (LJP). | ELECTION STUDY NOTES - IRELAND (2016): E5016 | | Independents occupied the remaining three cabinet positions, | bringing the total to 15. | ELECTION STUDY NOTES - ISRAEL (2020): E5016 | | One post was occupied by the Derekh Eretz (The Way of the Land) | party, bringing the total to 34. | ELECTION STUDY NOTES - ITALY (2018): E5016 | | Six additional posts were held by independents, bringing to the | the total to 19. | ELECTION STUDY NOTES - MEXICO (2018): E5016 | | The cabinet of the Federal Government is made up of 18 | Secretaries of State plus the Legal Adviser to the Federal | Executive, the Attorney General and the Head of the Office | of the President. | In total it is 20 members, including the members of the | expanded cabinet, that is, it includes the heads of fundamental | institutions for the Mexican State who are also appointed by | the President of the Republic. These are the Mexican Institute | of Social Security (IMSS), the Institute of Security and | Social Services for State Workers (ISSSTE), Petroleos Mexicanos | (PEMEX), the Federal Electricity Commission (CFE) and the | National Water Commission (CONAGUA). | Eight additional cabinet posts were held by independent members. | ELECTION STUDY NOTES - MONTENEGRO (2016): E5016 | | Seven additional posts were held by independents, and one by | Democratic Union of Albanians (DUA), bringing the total to 21. | ELECTION STUDY NOTES - PERU (2021): E5016 | | The other members of the cabinet came from the Broad Front | (Frente Amplio, 3 ministers), and the National United Renaissance | (Renacimiento Unido Nacional (RUNA, one minister). Independents | occupied the remaining cabinet positions, bringing the total | number to 19. | ELECTION STUDY NOTES - POLAND (2019): E5016 | | Additional posts were occupied by the PiS (PARTY A) coalition | partners (two posts each for Agreement/Porozumienie & United | Poland/Solidarna Polska). Six posts were held by independents, | bringing the total to 24. | ELECTION STUDY NOTES - PORTUGAL (2019): E5016 | | Five additional posts were held by independents, bringing the | total to 16. | ELECTION STUDY NOTES - ROMANIA (2016): E5016 | | One additional post was held by an Independent, bringing the | total to 27. | ELECTION STUDY NOTES - SLOVAKIA (2020): E5016 | | The remaining cabinet ministries were occupied by two | Independents, bringing the total to 16. | ELECTION STUDY NOTES - THAILAND (2019): E5016 | | Additional portfolios were held by Action Coalition for | Thailand Party (one cabinet post) and Chart Pattana Party | (one cabinet post). | ELECTION STUDY NOTES - TUNISIA (2019): E5016 | | All the appointed cabinet members were Independents, except for | the Prime Minister Elyes Fhakfakh of the Ettakatol Party | (Democratic Forum for Labor and Liberties, NUMERICAL CODE | 788024). --------------------------------------------------------------------------- E5017_A >>> EXPERT: IDEOLOGICAL FAMILY - PARTY A E5017_B >>> EXPERT: IDEOLOGICAL FAMILY - PARTY B E5017_C >>> EXPERT: IDEOLOGICAL FAMILY - PARTY C E5017_D >>> EXPERT: IDEOLOGICAL FAMILY - PARTY D E5017_E >>> EXPERT: IDEOLOGICAL FAMILY - PARTY E E5017_F >>> EXPERT: IDEOLOGICAL FAMILY - PARTY F E5017_G >>> EXPERT: IDEOLOGICAL FAMILY - PARTY G E5017_H >>> EXPERT: IDEOLOGICAL FAMILY - PARTY H E5017_I >>> EXPERT: IDEOLOGICAL FAMILY - PARTY I --------------------------------------------------------------------------- M05a.a-i. Ideological Family Party is closest to (in the expert judgment of the CSES Collaborator). .................................................................. 01. ECOLOGY PARTIES 02. COMMUNIST PARTIES 03. SOCIALIST PARTIES 04. SOCIAL DEMOCRATIC PARTIES 05. LEFT LIBERAL PARTIES 06. LIBERAL PARTIES 07. RIGHT LIBERAL PARTIES 08. CHRISTIAN DEMOCRATIC PARTIES 09. CONSERVATIVE PARTIES 10. NATIONAL PARTIES 11. AGRARIAN PARTIES 12. ETHNIC PARTIES 13. REGIONAL PARTIES 14. INDEPENDENT PARTIES 15. OTHER 97. NOT APPLICABLE 98. NO IDEOLOGICAL FAMILY MENTIONED 99. MISSING | VARIABLE NOTES: E5017_ | | Parties/coalitions and their numerical & alphabetical | classifications for each election study are detailed in Part 3 | of the CSES Codebook. | | E5017_ details the expert judgment of the national Collaborators | as to which ideological family each party belongs to. Often | Collaborators provide two characterizations for a party. These | multiple characterizations are detailed in the ELECTION STUDY | NOTES below with details of what characterization is coded in | the dataset. | Collaborators at times provide additional information to help | refine the characterization, and when applicable, these are | detailed in the ELECTION STUDY NOTES below. | | Source of data: CSES Macro Report M5a.a-i. | ELECTION STUDY NOTES - AUSTRIA (2017): E5017_E | | PARTY E (Liste Pilz) is a personalized list of a former Green | politician. As the Party did not publish a manifesto, the | classification is challenging. Some of the Collaborators suggest | classifying it as a populist left party. | ELECTION STUDY NOTES - BELGIUM-WALLONIA (2019): E5017_G | | PARTY G (People's Party, PP) was characterized as Right-Wing | Populist party. | ELECTION STUDY NOTES - CHILE (2017): E5017_D | | PARTY D (Socialist Party of Chile, PSCH) was characterized as | both a "Socialist" and a "Social Democratic" party. Only the first | characterization is coded in the dataset. | ELECTION STUDY NOTES - CANADA (2019): E5017_D | | PARTY D (The Bloc Quebecois, BQ) was characterized as both a | "National" and a "Regional" party. Only the first | characterization is coded in the dataset. | ELECTION STUDY NOTES - COSTA RICA (2018): E5017_B | | PARTY B (Partido Restauracion Nacional, PRN) was characterized | as Evangelical party. | ELECTION STUDY NOTES - CZECHIA (2017): E5017_A | | PARTY A (Action of Dissatisfied Citizens/Yes, ANO 2011) was | characterized as a "Populist" party. | ELECTION STUDY NOTES - CZECHIA (2021): E5017_A, E5017_G, E5017_H | | The Together (SPOLU) alliance comprises three parties: | - PARTY A - Civic Democratic Party (Obcanska Demokraticka | Strana, ODS). | - PARTY G - Tradition, Responsibility, Prosperity | (Tradice Odpovednost Prosperita, TOP09). | - PARTY H - Christian and Democratic Union/People's Party | (Krestanska a Demokraticka Unie - Strana lidova, | KDU-CSL). | | Ideological family classifications are provided separately for | each party in the alliance in E5017_A, E5017_G, and E5017_H, | respectively. | ELECTION STUDY NOTES - CZECHIA (2021): E5017_B | | PARTY B (Action of Dissatisfied Citizens/Yes, ANO 2011) was | characterized as a "Populist" party. | ELECTION STUDY NOTES - CZECHIA (2021): E5017_C & E5017_I | | The Pirati - Czech Pirate Party (Ceska Piratska Strana, PARTY C) | and STAN Mayors and Independents (Starostove a nezavisli, | PARTY I) competed in the election as an alliance. Ideological | family classifications are provided separately for each party in | the alliance in E5017_C and E5017_I, respectively. | ELECTION STUDY NOTES - EL SALVADOR (2019): E5017_D | | PARTY D (VAMOS) was characterized as being Christian Humanist. | ELECTION STUDY NOTES - EL SALVADOR (2019): E5017_G | | PARTY G (New Ideas, NI) was characterized as an Emerging party. | ELECTION STUDY NOTES - FINLAND (2019): E5017_B | | PARTY B (The Finns Party; PS) was characterized as a "National" | and a "Right Wing Populist" party. Only the first | characterization is coded in the dataset. | ELECTION STUDY NOTES - FINLAND (2019): E5017_I | | PARTY I (Blue Reform, SIN) was characterized as a "National" | and a "Right Wing Populist" party. Only the first | characterization is coded in the dataset. | ELECTION STUDY NOTES - FRANCE (2017): E5017_D | | PARTY D (La France Insoumise, FI) was characterized as both a | "Other" and a "Radical Left" party. Only the first | characterization is coded in the dataset. | ELECTION STUDY NOTES - GREECE (2015): E5017_C | | PARTY C (Popular Association-Golden Dawn, XA) was characterized | as both an "Other" and an "Extreme Right" party. Only the first | characterization is coded in the dataset. | ELECTION STUDY NOTES - GREECE (2015): E5017_G | | PARTY G (Independent Greeks-National Patriotic Alliance, ANEL) | was characterized as both an "Other" and a "Right-Wing Populist" | party. Only the first characterization is coded in the dataset. | ELECTION STUDY NOTES - GREECE (2019): E5017_G | | PARTY G (Popular Association-Golden Dawn, XA) was characterized | as a far-right party. | ELECTION STUDY NOTES - GREECE (2019): E5017_H | | PARTY H (Course of Freedom) was characterized as "new left" or a | "radical left party". | ELECTION STUDY NOTES - GREECE (2019): E5017_I | | PARTY I (Union of Centrists, EK) was characterized as centrist | party. | ELECTION STUDY NOTES - HONG KONG (2016): E5017_I | | The data refer to the Youngspiration party, a leading member of | ALLinHK coalition. | ELECTION STUDY NOTES - HUNGARY (2018): E5017_A | | This classification refers to Fidesz - the dominant member of | the coalition coded here as PARTY A. The junior partner in the | coalition, the Christian Democrats (KDNP) is classified as a | "Christian Democratic" Party. | ELECTION STUDY NOTES - HUNGARY (2018): E5017_C | | This classification refers to the MSZP (Hungarian Socialist | Party) - the dominant member of the coalition represented here | as PARTY C. The junior partner in the coalition, Parbeszed, | is described as an "Ecologist Party". | ELECTION STUDY NOTES - ICELAND (2016): E5017_D | | PARTY D (Progressive Party, F) was characterized as both | "Agrarian" and "Liberal Centre" party. Only the first | characterization is coded in the dataset. | ELECTION STUDY NOTES - ICELAND (2017): E5017_E | | PARTY E (Progressive Party, F) was characterized as both | "Agrarian" and "Liberal Centre" party. Only the first | characterization is coded in the dataset. | ELECTION STUDY NOTES - INDIA (2019): E5017_F | | PARTY F (The Yuvajana Shramika Rythu Congress Party, YSRCP or | YCP) was characterized as "Regional Party" and "Social | Democratic" party. Only the second characterization is coded in | the dataset. | ELECTION STUDY NOTES - ISRAEL (2020): E5017_A | | PARTY A (Likud, National Liberal Party) was characterized as both | "National" and "Conservative" party. Only the first | characterization is coded in the dataset. | ELECTION STUDY NOTES - ISRAEL (2020): E5017_B | | PARTY B (Kahol Lavan, Blue & White) was characterized as both | "Liberal" and "Centrist" party. Only the first characterization | is coded in the dataset. | ELECTION STUDY NOTES - ISRAEL (2020): E5017_D | | PARTY D (Shas, Sephardi Keepers of the Torah) was characterized | as both "Ethnic" and "Religious" party. | ELECTION STUDY NOTES - ISRAEL (2020): E5017_E | | PARTY E (Yahadut Hatorah, United Torah Judaism) was characterized | as both "Ethnic" and "Religious" party. Only the first | characterization is coded in the dataset. | ELECTION STUDY NOTES - ISRAEL (2020): E5017_H | | PARTY H (Yamina, New Right) was characterized as both "National" | and "Religious" party. Only the first characterization is coded | in the dataset. | ELECTION STUDY NOTES - ITALY (2017): E5017_A | | PARTY A (Five Star Movement) was characterized as both "Other | (Anti-political establishment)" party and "Ecology" party. Only | the first characterization is coded in the dataset. | ELECTION STUDY NOTES - ITALY (2017): E5017_B | | PARTY B (Democratic Party) was characterized as both "Social | Democratic" and "Left Liberal" party. Only the first | characterization is coded in the dataset. | ELECTION STUDY NOTES - ITALY (2017): E5017_C | | PARTY C (Lega) was characterized as both "National" and | "Conservative". Only the first characterization is coded in the | dataset. | ELECTION STUDY NOTES - ITALY (2017): E5017_E | | PARTY E (Brothers of Italy) was characterized as both "National" | and "Conservative". Only the first characterization is coded in | the dataset. | ELECTION STUDY NOTES - ITALY (2017): E5017_F | | PARTY F (Free and Equal) was characterized as both "Socialist" | and "Left Liberal" party. Only the first characterization is | coded in the dataset. | ELECTION STUDY NOTES - JAPAN (2017): E5017_D | | PARTY D (Komeito) was characterized as Religious Parties | (Buddhist). | ELECTION STUDY NOTES - LATVIA (2018): E5017_A | | PARTY A (Social Democratic Party, Harmony) was characterized as | both "Social Democratic" and "Ethnic" party. Only the first | characterization is coded in the dataset. | ELECTION STUDY NOTES - LATVIA (2018): E5017_B | | PARTY B (Who Owns the State?, KPV LV)) was characterized as | a "Populist Party". | ELECTION STUDY NOTES - LATVIA (2018): E5017_F | | PARTY F (Union of Greens and Farmers, ZZS) was characterized as | both "Agrarian" and "Ecologist" party. Only the first | characterization is coded in the dataset. | ELECTION STUDY NOTES - LITHUANIA (2016): E5017_A | | PARTY A (Homeland Union Lithuanian Christian Democrats, TS-LKD) | was characterized as both "Conservative" and "Christian Democrat" | party. Only the first characterization is coded in the dataset. | ELECTION STUDY NOTES - LITHUANIA (2016): E5017_E | | PARTY E (Anti-Corruption Coalition of Puteikis and Krivickas, | LCP-LPP) was characterized as both "Other" and "Right Wing | Populist" party. Only the first characterization is coded in the | dataset. | ELECTION STUDY NOTES - LITHUANIA (2016): E5017_G | | PARTY G (Order and Justice, PTT) was characterized as both | "National" and "Right Liberal" party. Only the first | characterization is coded in the dataset. | ELECTION STUDY NOTES - LITHUANIA (2016): E5017_H | | PARTY H (Labor Party, DP) was characterized as both "Other" | and "Centrist" party. Only the first characterization is coded | in the dataset. | ELECTION STUDY NOTES - LITHUANIA (2020): E5017_A | | PARTY A (Homeland Union Lithuanian Christian Democrats, TS-LKD) | was characterized as both "Conservative" and "Christian Democrat" | party. Only the first characterization is coded in the dataset. | ELECTION STUDY NOTES - LITHUANIA (2020): E5017_C | | PARTY C (Labor Party, DP) was characterized as a party that had | no consistent ideology. | ELECTION STUDY NOTES - MEXICO (2018): E5017_H | | PARTY H (New Alliance Party, PNA) was previously characterized | as a Liberal party with connections to the Teachers' National | Trade Union. | ELECTION STUDY NOTES - MONTENEGRO (2016): E5017_A | | PARTY A (Democratic Party of Socialists, DPS) was characterized | as both a "Right Liberal" and an ideologically diffuse party, | nominally a Socialist Party, but a mix of rightist positions (on | economic issues) and technocrat tendancies. | ELECTION STUDY NOTES - MONTENEGRO (2016): E5017_B | | PARTY B (Democratic Front, DF) was characterized as both a | "Conservative" and "National" party. Only the first | characterization is coded in the dataset. | ELECTION STUDY NOTES - MONTENEGRO (2016): E5017_C | | These data refer to DEMOS (Democratic Alliance), a leading party | in the coalition Kljuc (Key Coalition), coded here as PARTY C. | DEMOS was characterized as both a "Social Democratic" and | "Conservative" party. Only the first characterization is coded | in the dataset. | ELECTION STUDY NOTES - MONTENEGRO (2016): E5017_D | | PARTY D (Democratic Montenegro, DCG) was characterized as both a | "Social Democratic" and "Conservative" party. Only the first | characterization is coded in the dataset. | ELECTION STUDY NOTES - MONTENEGRO (2016): E5017_F | | PARTY F (Social Democratic Party of Montenegro, SDP) is | classified to be "nominally Social Democratic". | ELECTION STUDY NOTES - MONTENEGRO (2016): E5017_H | | PARTY H (Albanians Decisively, FORCA-DUA-AA) is a coalition of | three parties: New Democratic Power FORCA, Albanian Alternative | (AA), and Democratic Union of Albanians (DUA). | ELECTION STUDY NOTES - NETHERLANDS (2021): E5017_H | | PARTY H (Forum for Democracy, FvD) was characterized as "extreme | right, anti-immigration, COVID-19 pandemic conspiracy" party. | ELECTION STUDY NOTES - NETHERLANDS (2021): E5017_I | | PARTY I (Christian Union, CU) has previously been characterized | as an Orthodox party, but Collaborators advise the party has | evolved over time and has emphasized Christian Democratic | principles in recent elections. | ELECTION STUDY NOTES - NORWAY (2017): E5017_I | | PARTY I (Red Party, R) was characterized as both "Other" and | and "Radical Socialist" party. Only the first characterization | is coded in the dataset. | ELECTION STUDY NOTES - NEW ZEALAND (2017): E5017_H | | PARTY G (MANA) is characterized as an "Ethnic" and a "Socialist" | party. Only the first characterization is coded in the dataset. | ELECTION STUDY NOTES - NEW ZEALAND (2020): E5017_B | | PARTY B (National, NP) is characterized as a Conservative and a | Liberal party. Only the first characterization is coded | in the dataset. | ELECTION STUDY NOTES - NEW ZEALAND (2020): E5017_E | | PARTY E (New Zealand First, NZF) is characterized as a National | and a Populist party. Only the first characterization is coded | in the dataset. | ELECTION STUDY NOTES - NEW ZEALAND (2020): E5017_G | | PARTY G (New Conservatives, NC) is characterized as a | Conservative party, but Collaborator notes it is a radical | Christian party. Only the first characterization is coded in | the dataset. | ELECTION STUDY NOTES - PERU (2021): E5017_E | | PARTY E (Popular Action, Accion Popular, AP) was characterized | as a "catch-all" party. | ELECTION STUDY NOTES - PERU (2021): E5017_G | | PARTY G (Alliance for Progress, Alianza Para el Progreso, APP) | was characterized as a "catch-all" party. | ELECTION STUDY NOTES - PERU (2021): E5017_H | | PARTY H (We Can for Progress of Peru, Podemos) was characterized | as a "populist" party. | ELECTION STUDY NOTES - POLAND (2019): E5017_A | | PARTY A (Law and Justice; Prawo i Sprawiedliwosc, PiS) was | characterized as both a conservative (9) and (Populist) | Radical Right party. Only the first characterization is coded | in the dataset. | ELECTION STUDY NOTES - POLAND (2019): E5017_B | | PARTY B (Civic Platform; Platforma Obywatelska, PO) was | characterized as both a Right Liberal (7) and a Conservative | (9) party. Only the first characterization is coded in the | dataset. | ELECTION STUDY NOTES - POLAND (2019): E5017_C | | PARTY C (Polish People's Party; Polskie Stronnictwo Ludowe, PSL) | was characterized as both an Agrarian (11) and a Conservative | (9) party. Only the first characterization is coded in the | dataset. | ELECTION STUDY NOTES - POLAND (2019): E5017_E | | PARTY E (Kukiz'15) was characterized as a (Populist) Radical | Right party. | ELECTION STUDY NOTES - POLAND (2019): E5017_G | | PARTY G (Spring; Wiosna) was characterized as both a Social | Democratic (4) and a Socialist (3) party. Only the first | characterization is coded in the dataset. | ELECTION STUDY NOTES - POLAND (2019): E5017_H | | PARTY H (Confederation; Konfederacja) was characterized as a | Radical Right party. | ELECTION STUDY NOTES - PORTUGAL (2019): E5017_D | | These data refer to the Unitary Democratic Coalition (CDU). CDU | is an electoral alliance of the Portuguese Communist Party (PCP) | and the Ecologist Party - The Greens (PEV). | Individually, the CSES Collaborator characterized PCP as | belonging to the "Communist Parties" family, while PEV was | described as "Green Parties". Since PCP is the principal member | of the coalition, we coded the coalition as belonging to the | family of "Communist Parties". | ELECTION STUDY NOTES - PORTUGAL (2019): E5017_G | | PARTY G (Chega!, "Enough") was characterized as | belonging to the category of "Extreme Right parties". | ELECTION STUDY NOTES - ROMANIA (2016): E5017_G | | PARTY G (United Romania Party; Partidul Romania Unita, PRU) was | characterized as a Nationalist party. | ELECTION STUDY NOTES - ROMANIA (2018): E5017_H | | PARTY H (Greater Romania Party, PRM) was characterized as a | Nationalist Left party. | ELECTION STUDY NOTES - ROMANIA (2016): E5017_I | | PARTY I (Our Romania Alliance; Alianta Noastra Romania, ANR) was | characterized as Nationalist party. | ELECTION STUDY NOTES - SLOVAKIA (2020): E5017_A | | PARTY A (Ordinary People and Independent Personalities, OL'aNO) | was characterized as both a "Conservative" and an anti- | establishment party. Only the first characterization is coded in | the dataset. | ELECTION STUDY NOTES - SLOVAKIA (2020): E5017_D | | PARTY D (Kotleba - People's Party/Our Slovakia, LsNS) is | characterized as an extreme right party. | ELECTION STUDY NOTES - SLOVAKIA (2020): E5017_G | | PARTY G (For the People, Za ludi) is characterized as a center- | right party. | ELECTION STUDY NOTES - SWEDEN (2018): E5017_D | | PARTY D (Centre Party, C) was characterized as both "agrarian" | with a liberal standpoint. Only the first characterization is | coded in the dataset. | ELECTION STUDY NOTES - SWITZERLAND (2019): E5017_F | | PARTY F (GLP/PVL - Green Liberal Party) was categorized as both | 01. ECOLOGY PARTIES, and 06. LIBERAL PARTIES. | ELECTION STUDY NOTES - TUNISIA (2019): E5017_A | | PARTY A (Ennahda party) was characterized as Islamist | conservative party. | ELECTION STUDY NOTES - TUNISIA (2019): E5017_B | | PARTY B (Heart of Tunisia/Kalb Tounes) was characterized as a | center-left party. | ELECTION STUDY NOTES - TUNISIA (2019): E5017_C | | PARTY C (Free Constitutional Party or Free Destourian Party) was | characterized as a secular nationalist party. | ELECTION STUDY NOTES - TUNISIA (2019): E5017_E | | PARTY E (Dignity Coalition) was characterized as an Islamist | conservative party. | ELECTION STUDY NOTES - TUNISIA (2019): E5017_F | | PARTY F (People's Movement) was characterized as a secular | nationalist party. | ELECTION STUDY NOTES - URUGUAY (2019): E5017_A | | PARTY A (Broad Front/Frente Amplio) was characterized as | "Social Democratic - Socialist - Communist - Revolutionary - | Left Libertarian" party. Only the first characterization | is coded in the dataset. | ELECTION STUDY NOTES - URUGUAY (2019): E5017_B | | PARTY B (National Party - White Party/Partido Nacional) was | characterized as a "Right Liberal-Christian Democratic" party. | The first characterization is coded in the dataset. | ELECTION STUDY NOTES - URUGUAY (2019): E5017_D | | PARTY D (Open Cabildo / Cabildo Abierto/People's Meeting) was | characterized as a "Nationalist - Rightist - Popularist" party. | Only the first characterization is coded in the dataset. | ELECTION STUDY NOTES - URUGUAY (2019): E5017_F | | PARTY F (People's Party/Partido de la Gente) was characterized | as a "Populist" party. | ELECTION STUDY NOTES - URUGUAY (2019): E5017_G | | PARTY G (Partido Independiente/Independent Party) was | characterized as a "Social Democratic - Christian Democratic" | party. Only the first characterization is coded in the dataset. | ELECTION STUDY NOTES - URUGUAY (2019): E5017_H | | PARTY H (Popular Unity/Unidad Popular) was characterized as a | "Revolutionary" party. | ELECTION STUDY NOTES - URUGUAY (2019): E5017_I | | PARTY I (Green Animalist Party/Partido Verde Animalista) was | characterized as an "Ecology and Animalistic Party". Only the | first characterization is coded in the dataset. --------------------------------------------------------------------------- E5018_A >>> EXPERT: IDEOLOGY LEFT-RIGHT - PARTY A E5018_B >>> EXPERT: IDEOLOGY LEFT-RIGHT - PARTY B E5018_C >>> EXPERT: IDEOLOGY LEFT-RIGHT - PARTY C E5018_D >>> EXPERT: IDEOLOGY LEFT-RIGHT - PARTY D E5018_E >>> EXPERT: IDEOLOGY LEFT-RIGHT - PARTY E E5018_F >>> EXPERT: IDEOLOGY LEFT-RIGHT - PARTY F E5018_G >>> EXPERT: IDEOLOGY LEFT-RIGHT - PARTY G E5018_H >>> EXPERT: IDEOLOGY LEFT-RIGHT - PARTY H E5018_I >>> EXPERT: IDEOLOGY LEFT-RIGHT - PARTY I --------------------------------------------------------------------------- M06a1.a-i. Parties' positions on the left-right scale (in the expert judgment of the CSES Collaborator). .................................................................. 00. LEFT 01. 02. 03. 04. 05. 06. 07. 08. 09. 10. RIGHT 97. NOT APPLICABLE 99. MISSING | VARIABLE NOTES: E5018_ | | Parties/coalitions and their numerical & alphabetical | classifications for each election study are detailed in Part 3 | of the CSES Codebook. | | E5018_ details the expert judgment of the national Collaborators | as to where parties/coalitions are located on the left-right | ideological scale. Sometimes parties'/coalitions' ideological | differences in certain polities on the left-right scale are | difficult to detect, perhaps because party competition is not | structured on a left-right dimension. These instances are | detailed in ELECTION STUDY NOTES below. Moreover, E5019_ details | an alternative expert judgment scale based on national | Collaborators' ratings of parties/coalitions on a scale of their | choice which is related to relevant national political | circumstances. | | Source of data: CSES Macro Report Q6a1.a-i. | | Data are unavailable for TAIWAN (2016 & 2020). | ELECTION STUDY NOTES - CZECHIA (2017): E5018_D | | PARTY D (Freedom and Direct Democracy, SPD) is classified as a | National far-right party on issues such as migration, Islam, | the European Union and environmental protection. However, on | economic issues, the party adopts a leftist stance focused on | low-income groups. | ELECTION STUDY NOTES - CZECHIA (2021): E5018_A, E5018_G, E5018_H | | The Together (SPOLU) alliance comprises three parties: | - PARTY A - Civic Democratic Party (Obcanska Demokraticka | Strana, ODS). | - PARTY G - Tradition, Responsibility, Prosperity | (Tradice Odpovednost Prosperita, TOP09). | - PARTY H - Christian and Democratic Union/People's Party | (Krestanska a Demokraticka Unie - Strana lidova, | KDU-CSL). | | Left-right classifications are provided separately for each party | in the alliance in E5018_A, E5018_G, and E5018_H, respectively. | ELECTION STUDY NOTES - CZECHIA (2021): E5018_C & E5018_I | | The Pirati - Czech Pirate Party (Ceska Piratska Strana, PARTY C) | and STAN Mayors and Independents (Starostove a nezavisli, | PARTY I) competed in the election as an alliance. Left-right | classifications are provided separately for each party in the | alliance in E5018_C and E5018_I, respectively. | ELECTION STUDY NOTES - GREECE (2015): E5018 | | The left-right party placements were completed by 43 polity | experts. The values reflect the median value of the experts. | ELECTION STUDY NOTES - GREECE (2019): E5018 | | The left-right party placements were completed by 12 polity | experts. The values reflect the median value of the experts. | ELECTION STUDY NOTES - HONG KONG (2016): E5018_G & E5018_I | | According to the Macro report, the three political groups that | comprise the coalition coded as PARTY G occupy different | positions on the Left-Right scale: "(1) Civic Passion does not | have a clear position in this dimension, so cannot be rated; | (2) Proletariat Political Institute's position is rated to be 2; | and (3) Hong Kong Resurgence Order's position is rated to be 5." | | E5018_I refers to the Youngspiration party, a leading member of | ALLinHK coalition. | ELECTION STUDY NOTES - HUNGARY (2018): E5018 | | Collaborators advise that in Hungary, left-right differences are | principally understood in cultural terms and not conventionally. | ELECTION STUDY NOTES - HUNGARY (2018): E5018_A | | These data refer to Fidesz - the dominant member of the | coalition represented here as PARTY A. However, the junior | partner in the coalition, KDNP, is given the same left-right | rating: 9. | ELECTION STUDY NOTES - HUNGARY (2018): E5018_C | | These data refer to the MSZP (Hungarian Socialist Party) - the | dominant member of the coalition represented here as PARTY C. | However, the junior partner in the coalition, Parbeszed, is | given the same left-right rating: 2. | ELECTION STUDY NOTES - HUNGARY (2018): E5018_G | | Collaborators describe PARTY G (Hungarian Two-tailed Dog Party; | MKKP) as a 'Joke party' and consequently did not provide a left- | right classification. | ELECTION STUDY NOTES - INDIA (2019): E5018 | | Collaborators advise that in India, left-right differences do | not structure political competition but rather ideological | differences are rooted in bringing several ethnic groups together | and the issue of property redistribution. Consequently, | classification of parties/coalitions on this dimension is | challenging. | | For more, see: | Chhibber, P. K., and R. Verma. 2018. Ideology and identity: The | changing party systems of India. Oxford University Press. | | Chhibber, P., and R. Verma. 2019. "The rise of the second | dominant party system in India: BJP's new social coalition in | 2019." Studies in Indian Politics 7 (2): 131-148. | DOI: 10.1177/2321023019874628 | ELECTION STUDY NOTES - ITALY (2018): E5018 | | From the Macro Report: | - The 5 Star Movement ostensibly classifies itself as "neither | left, nor right", while in fact its platform contains policies | that are both left and right, hence its positioning in the | center. | - The League used to be a regional party until the previous | election, it became an anti-immigration party in recent times | (at the end of 2017 it changed the name from "Northern League" | to just "League", to appeal to voters in the south as well), and | in terms of left-right it is hardly distinguishable from | Brothers of Italy. | - A general point: the left-right positions that I chose here | take into account the issues of economic redistribution (where: | the 5 Star Movement would be positioned slightly on the left, | given the emphasis on what they call a "universal minimum | income", which is in fact a more generous unemployment benefit; | the League and Forza Italia would be positioned on the right, | given their emphasis on introducing a "flat tax"; the Democratic | Party would be positioned on the center-left, Free and Equal | would be positioned on the left) and immigration (League and | Brothers of Italy on the right, Democratic Party + Free and | Equal on the left, and 5 Star slightly on the right). | - For context, on the right, a few name changes and party splits | in the last 10 years deserve some explanation: in 2007, the | parties Forza Italia (of the former Prime Minister Silvio | Berlusconi) and National Alliance (heir of the far-right Italian | Social Movement) merged into the People of Freedom (PDL). In | 2012, some former member of National Alliance left the PDL to | form Brothers of Italy. In 2013, Berlusconi re-formed Forza | Italia, so the PDL as a party was extinguished. To a great | extent, the current situation (Forza Italia and Brothers of | Italy running as separate parties albeit in the same coalition) | mirrors the pre-PDL arrangement (although, importantly, while | Berlusconi remains the leader of Forza Italia, the current | leader of Brothers of Italy is not the same old leader of | National Alliance). | ELECTION STUDY NOTES - LITHUANIA (2016): E5018 | | Collaborators advise that in Lithuania, it is challenging to | classify parties/coalitions on the left-right spectrum, as most | parties founded post-2000 do not classify themselves on this | axis. Before 2000, party competition structured on a left-right | dimension mirrored an ex-communist versus anti-communist | cleavage. | Parties such as the Lithuania Union of Farmers and Greens (LVZS, | PARTY B), the Lithuanian Poles Electoral Action - Christian | Families Alliance (LLRA-KSS, PARTY F) and Party Order and Justice | (PTT, PARTY G) take positions on the right of the political | spectrum on moral issues, but take position on the left regarding | economic issues. Further, the Labor Party (DP, PARTY H) is | liberal on the moral dimension takes a somewhat contradictory | stance on the economic dimension (combining left-wing and liberal | rhetoric). | ELECTION STUDY NOTES - LITHUANIA (2020): E5018 | | Collaborators advise that in Lithuania, it is challenging to | classify parties/coalitions on the left-right spectrum, as most | parties founded post-2000 do not classify themselves on this | axis. Before 2000, party competition structured on a left-right | dimension mirrored an ex-communist versus anti-communist | cleavage. | Parties such as the Lithuania Union of Farmers and Greens (LVZS, | PARTY B), the Lithuanian Poles Electoral Action - Christian | Families Alliance (LLRA-KSS, PARTY G) take positions on the | right of the political spectrum on moral issues, but take | positions on the left regarding economic issues. Further, the | Labor Party (DP, PARTY C) is liberal on the moral dimension | takes a somewhat contradictory stance on the economic dimension | (combining left-wing and liberal rhetoric). | The Freedom Party and the Liberal Movement are liberal both on | moral and economic dimensions, the former being more radical on | such questions as LGBT rights. Only the Homeland Union - | Lithuanian Christian Democrats (TS-LKD, PARTY A) and the | Lithuanian Social Democratic Party (LSDP, PARTY D) can be easily | placed on this dimension. | ELECTION STUDY NOTES - LITHUANIA (2020): E5018_I | | Collaborators advise that it is challenging to place this party | as it identifies as a centrist party but embraces right-wing | populism, meaning the party could be classified as score 5 | or score 9. Score 9 is characterized in the dataset. | ELECTION STUDY NOTES - MEXICO (2018): E5018_H | | PARTY H (Partido Nueva Alianza) has a right-wing ideology | regarding the economic dimension. | ELECTION STUDY NOTES - MEXICO (2018): E5018_I | | PARTY I (Partido Encuentro Social) has a right-wing ideology | regarding the social dimension with a Christian influence. | ELECTION STUDY NOTES - MONTENEGRO (2016): E5018_C | | These data refer to DEMOS (Democratic Alliance), a leading | party in the coalition Kljuc (Key Coalition, PARTY C). | The two remaining members of the coalition (Socialist | Peoples Party and United Reform Action) were both placed | on position 4. | ELECTION STUDY NOTES - NETHERLANDS (2021): E5018 | | Collaborators advise with the COVID-19 pandemic and less salience | given over to the immigration issue in the 2021 contest compared | to previous Dutch elections, the left-right position of parties | were not as consistent as in previous contests with the COVID-19 | issue acting as "a dampener on outspoken party positions". | ELECTION STUDY NOTES - PORTUGAL (2019): E5018_D | | These data refer to the Unitary Democratic Coalition (CDU). CDU | is an electoral alliance of the Portuguese Communist Party (PCP) | and the Ecologist Party - The Greens (PEV). Both parties | individually were given the left-right score of "1". --------------------------------------------------------------------------- E5019 >>> ALTERNATIVE DIMENSION --------------------------------------------------------------------------- Whether respondents were asked to rank political parties on an alternative dimension, other than left-right. .................................................................. 1. YES [SEE ELECTION STUDY NOTES FOR THE DIMENSION LABELS] 5. NO 9. MISSING | VARIABLE NOTES: E5019 | | E5019 details whether respondents (and Collaborators) ranked | PARTIES A-I on an alternative dimension other than left-right | dimension. | The decision as to what scale is invoked is the decision of the | national Collaborator and is designed to represent party | positions on a scale relevant to national political | circumstances. | The type of scales and the labels assigned to each are | detailed in the ELECTION STUDY NOTES below E5019_A - E5019_I. | | Source of data: CSES Macro Report M6b1. | | Data are unavailable for UNITED STATES (2020). --------------------------------------------------------------------------- E5019_A >>> ALTERNATIVE DIMENSION - PARTY A E5019_B >>> ALTERNATIVE DIMENSION - PARTY B E5019_C >>> ALTERNATIVE DIMENSION - PARTY C E5019_D >>> ALTERNATIVE DIMENSION - PARTY D E5019_E >>> ALTERNATIVE DIMENSION - PARTY E E5019_F >>> ALTERNATIVE DIMENSION - PARTY F E5019_G >>> ALTERNATIVE DIMENSION - PARTY G E5019_H >>> ALTERNATIVE DIMENSION - PARTY H E5019_I >>> ALTERNATIVE DIMENSION - PARTY I --------------------------------------------------------------------------- M06b1.a-i. Parties' positions on the alternative scale (in the expert judgment of the CSES Collaborator). .................................................................. 00. [SEE ELECTION STUDY NOTES FOR THE DIMENSION LABELS] 01. 02. 03. 04. 05. 06. 07. 08. 09. 10. [SEE ELECTION STUDY NOTES FOR THE DIMENSION LABELS] 97. NOT APPLICABLE 99. MISSING | VARIABLE NOTES: E5019_ | | Parties/coalitions and their numerical & alphabetical | classifications for each election study are detailed in Part 3 | of the CSES Codebook. | | E5019_ details the expert judgment of the national Collaborators | as to where parties are located on a particular scale unique to | the polity. The decision as to what scale is invoked is the | decision of the national Collaborator and is designed to | represent party positions on a scale relevant to national | political circumstances. | The type of scales invoked and labels for each polity are | detailed below in the ELECTION STUDY NOTES. | | Source of data: CSES Macro Report M6b1.a-i. | | Data are available for HONG KONG (2016), JAPAN (2017), LATVIA | (2018), MEXICO (2018), MONTENEGRO (2016), PERU (2021), SLOVAKIA | (2020), TAIWAN (2016 & 2020), THAILAND (2019), TUNISIA (2019) and | URUGUAY (2019). | ELECTION STUDY NOTES - HONG KONG (2016): E5019_ | | The alternative scale measures positions of parties in Hong | Kong's relationship with China based on expert judgments. | | Name of dimension: Center-periphery. | | Label for position 0: Pro-Hong Kong (Periphery). | Label for position 10: Pro-Beijing (Center). | ELECTION STUDY NOTES - HONG KONG (2016): E5019_I | | E5019_I refers to the Youngspiration party, a leading member of | ALLinHK coalition. | ELECTION STUDY NOTES - JAPAN (2017): E5019_ | | Name of dimension: Liberal vs. Conservative | | Label for position 0: Liberal | Label for position 10: Conservative | ELECTION STUDY NOTES - LATVIA (2018): E5019_ | | Name of dimension: Pro-Slavic vs. Pro-Latvian | | Label for position 0: Pro-Slavic | Label for position 10: Pro-Latvian | ELECTION STUDY NOTES - MEXICO (2018): E5019_ | | Name of dimension: Liberal vs. Conservative | | Label for position 0: Liberal | Label for position 10: Conservative | ELECTION STUDY NOTES - MONTENEGRO (2016): E5019_ | | Name of dimension: Pro-Montenegrin vs. Pro-Serbian | | Label for position 0: Pro-Montenegrin | Label for position 10: Pro-Serbian | ELECTION STUDY NOTES - MONTENEGRO (2016): E5019_C | | E5019_C refers to DEMOS (Democratic Alliance), a leading party | in the coalition Kljuc (Key Coalition, PARTY C). | The two remaining members of the coalition, the Socialist Peoples | Party and United Reform Action, were placed on values 8 and 4, | respectively. | ELECTION STUDY NOTES - MONTENEGRO (2016): E5019_G | | PARTY G (Bosniak Party) was not ranked on this dimension. | According to the Macro Report, "Bosniak Party is an ethnic party, | that represent attitudes of Bosniaks in Montenegro and is not | relevant for this particular cleavage. That is the reason we have | not provided their position on this scale." | ELECTION STUDY NOTES - MONTENEGRO (2016): E5019_H | | PARTY H (Albanians Decisively, a coalition of three ethnic | Albanian parties) was not ranked on this dimension. The | Pro-Montenegrin vs. Pro-Serbian cleavage was judged not | applicable to this coalition. | ELECTION STUDY NOTES - MONTENEGRO (2016): E5019_I | | PARTY I (Croatian Civic Initiative, a party of ethnic Croats) was | not ranked on this dimension. The Pro-Montenegrin vs. Pro-Serbian | cleavage was judged not applicable to this party. | ELECTION STUDY NOTES - PERU (2021): E5019_ | | Name of dimension: Liberal vs. Conservative | | Label for position 0: Economy with greater state intervention | Label for position 10: Free market economy | ELECTION STUDY NOTES - SLOVAKIA (2020): E5019_ | | Name of dimension: Liberal vs. Conservative | | Label for position 0: Liberal | Label for position 10: Conservative | ELECTION STUDY NOTES - TAIWAN (2016 & 2020): E5019_ | | Name of dimension: Independence vs. Unification | | Label for position 0: Taiwan should declare independence | immediately | Label for position 10: Taiwan and China should unify immediately | ELECTION STUDY NOTES - THAILAND (2019): E5019 | | Name of dimension: Political Movement Group | | Label for position 0: Red Shirt Group | Label for position 10: Yellow shirt group | ELECTION STUDY NOTES - TUNISIA (2019): E5019_ | | Name of dimension: Secular vs. Islamist dimension | | Label for position 0: Secular | Label for position 10: Islamist | | The Collaborator provided the following additional details: | - Ennahda party and Dignity Coalition definitely have a clear | Islamist agenda. | - Democratic Current, Free Constitutional Party, and People's | Movement support secular policies. | - Kalb Tounes did not have a clear secular agenda, however, the | party had an anti-Islamist agenda before the 2019 elections. | After the elections, Ennahda party and Kalb Tounes together | with Dignity Coalition party, formed a joint parliamentary | front. | ELECTION STUDY NOTES - URUGUAY (2019): E5019_ | | Name of dimension: Economically Statist vs. Liberal | | Label for position 0: Statist | Label for position 10: Liberal --------------------------------------------------------------------------- E5020 >>> EXPERT: POPULISM BY PARTY --------------------------------------------------------------------------- Whether Collaborators ranked the political parties in their country on the populism scale. .................................................................. 1. YES 5. NO 9. MISSING | VARIABLE NOTES: E5020 | | E5020 details whether Collaborators ranked PARTIES A-I on the | populism scale. | Sometimes parties' levels of populism are hard to determine. | These instances are detailed in ELECTION STUDY NOTES below and | below E5019_A-I. | | Data are unavailable for TAIWAN (2016 & 2020). | | Source of data: CSES Macro Report M6c. | ELECTION STUDY NOTES - BRAZIL (2018): E5020 | | Collaborators advise Some Brazilian right and left parties | adopted populist discourse during the election campaign (adopting | the definition of CSES MODULE 5), although the programmatic scope | of most of the parties is not broadly populist. | The anti-corruption conjuncture of the political elite strongly | contributed to the campaign discourses being directed to the "us | against them" equation. This equation also added strength to the | anti-petist sentiment, noting that the PT was the party that | occupied the federal government between 2003 and 2016 (President | Dilma Rousseff, elected in 2014, was impeached in 2016). | Given the definitions of populism used in MODULE 5, the two main | parties in contention for the presidency of the Republic - PT | and PSL - can be considered populist, with a significantly | populist speech in the 2018 election. The party classification | in item 6c largely responds to this assessment of campaign | discourse from leaderships. | ELECTION STUDY NOTES - GERMANY (2017): E5020 | | Collaborators advise party classifications were informed by | replication of the statistical analyses of the paper below with | current data: | Lewandowsky, Marcel & Giebler, Heiko & Wagner, Aiko. (2016). | Rechtspopulismus in Deutschland. Eine empirische Einordnung der | Parteien zur Bundestagswahl 2013 unter besonderer | Beruecksichtigung der AfD. Politische Vierteljahresschrift, 57. | 247-275. doi: 10.5771/0032-3470-2016-2-247." | ELECTION STUDY NOTES - GREECE (2015): E5020 | | Collaborators advise the classifications reflect the | median value of the responses given by 43 (after cleaning) | experts, when they were asked to position the Greek parties on | two populist attitudes dimensions (anti-elite attitudes and | people centrism). The details of the expert survey are available | at Andreadis, I. (2018). Measuring Authoritarian Populism with | Expert Surveys Extending CHES estimates on populism and | authoritarianism (Electoral Integrity Project (EIP) Seminar | Series No. 29-5-2018). Sydney." | ELECTION STUDY NOTES - GREECE (2019): E5020 | | Collaborators advise the classifications reflect the median value | of the responses given by 12 (after cleaning) experts, when they | were asked to position the Greek parties on two populist | attitudes dimensions (anti-elite attitudes and people centrism). --------------------------------------------------------------------------- E5020_A >>> EXPERT: POPULISM SCALE - PARTY A E5020_B >>> EXPERT: POPULISM SCALE - PARTY B E5020_C >>> EXPERT: POPULISM SCALE - PARTY C E5020_D >>> EXPERT: POPULISM SCALE - PARTY D E5020_E >>> EXPERT: POPULISM SCALE - PARTY E E5020_F >>> EXPERT: POPULISM SCALE - PARTY F E5020_G >>> EXPERT: POPULISM SCALE - PARTY G E5020_H >>> EXPERT: POPULISM SCALE - PARTY H E5020_I >>> EXPERT: POPULISM SCALE - PARTY I --------------------------------------------------------------------------- M06c.a-i. Parties' positions on the populism scale (in the expert judgment of the CSES Collaborator). .................................................................. 00. NOT AT ALL POPULIST 01. 02. 03. 04. 05. 06. 07. 08. 09. 10. VERY POPULIST 97. NOT APPLICABLE 98. NO POPULISM SCORE MENTIONED 99. MISSING | VARIABLE NOTES: E5020_ | | Parties/coalitions and their numerical & alphabetical | classifications for each election study are detailed in Part 3 | of the CSES Codebook. | | E5020_ details the expert judgment of the national Collaborators | as to where parties are located on a populism scale. | Definition: Populism can be defined as a thin-centered ideology | that pits a virtuous and homogeneous people against a set of | elites and dangerous 'others' who are depicted as depriving | "the people" of their rights, values, prosperity, identity, and | voice. The emphasis on anti-elite/ anti-establishment rhetoric | and the contrast between the "pure people" and the "corrupt | elite" are thus indications of the degree to which a party is | populist. Populist parties can be found across the left-right | ideological spectrum. | | Sometimes parties' levels of populism are hard to determine. | These instances are detailed in ELECTION STUDY NOTES below. | | Source of data: CSES Macro Report M6c.a-i. | | Data are unavailable for TAIWAN (2016 & 2020). | ELECTION STUDY NOTES - CZECHIA (2021): E5020_A, E5020_G, E5020_H | | The Together (SPOLU) alliance comprises three parties: | - PARTY A - Civic Democratic Party (Obcanska Demokraticka | Strana, ODS). | - PARTY G - Tradition, Responsibility, Prosperity | (Tradice Odpovednost Prosperita, TOP09). | - PARTY H - Christian and Democratic Union/People's Party | (Krestanska a Demokraticka Unie - Strana lidova, | KDU-CSL). | | Extent of populism classifications are provided separately for | each party in the alliance in E5020_A, E5020_G and E5020_H, | respectively. | ELECTION STUDY NOTES - CZECHIA (2021): E5020_C & E5020_I | | The Pirati - Czech Pirate Party (Ceska Piratska Strana, PARTY C) | and STAN Mayors and Independents (Starostove a nezavisli, | PARTY I) competed in the election as an alliance. Extent of | populism classifications are provided separately for each party | in the alliance in E5020_C and E5020_I, respectively. | ELECTION STUDY NOTES - HUNGARY (2018): E5020_A | | E5020_A refers to Fidesz - the dominant member of the | coalition represented here as PARTY A. However, the junior | partner in the coalition, KDNP, is given the same populism | rating: 9. | ELECTION STUDY NOTES - HUNGARY (2018): E5020_C | | E5020_C refers to the MSZP (Hungarian Socialist Party) - the | dominant member of the coalition represented here as PARTY C. | The junior partner in the coalition, Parbeszed, is given the | populism rating: 5. | ELECTION STUDY NOTES - ICELAND (2016): E5020_C | | According to the Macro Report, "The Pirate Party [Party C] is | clearly an anti-establishment, anti-elite party, but very | liberal on social issues, including immigration." | ELECTION STUDY NOTES - ICELAND (2017): E5020_D & E5020_G | | According to the Macro Report, Center Party (Party D) and | People's Party (Party G) "are both strongly anti-elitist, | and have been flirting with anti-immigration feelings." | ELECTION STUDY NOTES - ICELAND (2017): E5020_F | | According to the Macro Report, "The Pirate Party [Party F] is | clearly an anti-establishment, anti-elite party, but very | liberal on social issues, including immigration." | ELECTION STUDY NOTES - ITALY (2018): E5020 | | From the Macro Report: "The 5 Star Movement is a textbook | example of a populist party, given the definition above. The | League uses populist tones, but conjugated in a more national- | anthropological sense (the emphasis on the interest of the | "Italians") rather than in an anti-establishment sense (also | because they have been part of the government with Berlusconi | in the periods 1994-1995, 2001-2006, and 2008-2011. About Forza | Italia, Berlusconi used a slightly populist narrative in the mid | 1990s, however the party was more characterized as a | conservative party." | ELECTION STUDY NOTES - MONTENEGRO (2016): E5020_C | | These data refer to DEMOS (Democratic Alliance), a leading | party in the coalition Kljuc (Key Coalition), coded here as | PARTY C. | The two remaining members of the coalition, the Socialist | Peoples Party and United Reform Action, were placed on | values 6 and 3, respectively. --------------------------------------------------------------------------- E5021_1 >>> MOST SALIENT FACTORS IN ELECTION - 1ST E5021_2 >>> MOST SALIENT FACTORS IN ELECTION - 2ND E5021_3 >>> MOST SALIENT FACTORS IN ELECTION - 3RD E5021_4 >>> MOST SALIENT FACTORS IN ELECTION - 4TH E5021_5 >>> MOST SALIENT FACTORS IN ELECTION - 5TH --------------------------------------------------------------------------- The five most salient factors that affected the outcome of the election, in the judgment of national Collaborators. .................................................................. 001.-899. MOST SALIENT FACTORS CODES [SEE ELECTION STUDY NOTES] 999. MISSING | VARIABLE NOTES: E5021_ | | E5021_ detail the expert judgment of the national Collaborators | as to the five most important issues at the time of the election | (e.g., major scandals; economic events; the presence of an | independent actor; specific issues). | Issues are listed in descending order of saliency (i.e., most | important issues are listed first). | Numerical allocation by CSES is random. Collaborators are asked | to provide up to five salient issues. In some cases, | Collaborators provide fewer issues. | | Source of data: CSES Macro Report M7.1-5. | ELECTION STUDY NOTES - ALBANIA (2017): E5021 | | A description of the most salient factors in the | election is included here: | | 209. Popularity of party leaders. | 210. Vote buying and clientelism (public and private sector). | 211. Division of opposition and misinterpretation of the | electoral system. | 212. The election campaign itself. | ELECTION STUDY NOTES - AUSTRALIA (2019): E5021 | | A detailed description of the most salient factors | in the election as perceived by the Collaborators were: | 100. Economic management | 101. Health | 102. Tax | 103. Climate Change | 104. Environment | ELECTION STUDY NOTES - AUSTRIA (2017): E5021 | | A detailed description of the most salient factors | in the election as perceived by the Collaborators were: | 020. Fight unemployment | 021. Fight crime | 022. Protect Austria against terrorist attacks | 023. Control immigration | 024. Asylum rules | ELECTION STUDY NOTES - BELGIUM-FLANDERS (2019): E5021 | | A detailed description of the most salient factors | in the election as perceived by the Collaborators were: | 120. Immigration | 121. Economy | 122. Budget | 123. State Structure | ELECTION STUDY NOTES - BELGIUM-WALLONIA (2019): E5021 | | A detailed description of the most salient factors | in the election as perceived by the Collaborators were: | 124. Immigration | 125. Economy | 126. Budget | 127. State Structure | ELECTION STUDY NOTES - BRAZIL (2018): E5021 | | A detailed description of the most salient factors | in the election as perceived by the Collaborators were: | 080. In April 2018, former President Lula was arrested on | charges of corruption schemes in a process he developed | in the context of federal police operations called Car | Wash. His arrest was strongly contested due to procedural | problems. Just weeks before the election, the Worker's | Party defined as the official candidate for the | presidency of the republic the university professor | Fernando Haddad. The PT ran for the fourth term in the | federal government and Lula was the party's main | candidate name. Even in prison, Lula obtained in the | polls the average preference of 35% of the voters in the | preferences for the presidency of the republic. | 081. Within a month of the first round of the Presidential | election, right-wing Social Liberal Party candidate (Jair | Bolsonaro) suffered a knife attack in the middle of an | election campaign. This event provoked a great commotion | by political violence, and due to the period of medical | recovery in the hospital, triggered a virtual campaign | through social networks through which the candidate | communicated with the electorate. The recovery made it | possible for the candidate not to participate in the | election debates on television, greatly benefiting him. | 082. Strong left-to-right polarization (PT vs. PSL). The | campaign was marked by strong anti-petism (Workers' | Party), developed mainly through social networks. It is | important to mention that the political polarization | began in 2016, with the impeachment of President Dilma | Rousseff, elected in 2014. Polarization has provoked | violent situations in rallies and street campaigns, as | well as in social media channels. | 083. Denunciations of scandal and corruption against the | political class, affecting the most important parties of | the party system. | 084. Prominent role of social networks used by top candidates, | including the strong use of fake news. | ELECTION STUDY NOTES - CANADA (2019): E5021 | | A detailed description of the most salient factors | in the election as perceived by the Collaborators were: | 115. Carbon Tax | 116. Immigration | 117. Pharmacare | 118. Economy | 119. Political scandals and leadership | ELECTION STUDY NOTES - CHILE (2017): E5021 | | A detailed description of the most salient factors | in the election as perceived by the Collaborators were: | 025. Economic Growth | 026. Education | 027. Crime/Security | 028. Corruption | 029. Social Security | ELECTION STUDY NOTES - COSTA RICA (2018): E5021 | | The most salient factors in the election as perceived by the | Collaborators were: | 105. LGTBI marriage rights | 106. Family issues | 107. Corruption case called "Cementazo" | 108. Unemployment | 109. Religious Issues. | ELECTION STUDY NOTES - CZECHIA (2017): E5021 | | A detailed description of the most salient factors | in the election as perceived by the Collaborators were: | 238. Leaders: Populist Andre Babis, leader of the Action | of Dissatisfied Citizens/Yes (Akce Nespokojenych Obcanu, | ANO 2011, PARTY A) was charged with fraud involving | European subsidies. Most anticipated Babis would lead the | government after the 2017 elections. | 239. Migration. | 240. Corruption. | 241. Minimum wage. | 242. Lithium case involving an agreement between an Australian | mining company (European Metal Holdings) and the outgoing | Czech government, which opposition politicians criticized. | ELECTION STUDY NOTES - CZECHIA (2021): E5021 | | A detailed description of the most salient factors | in the election as perceived by the Collaborators were: | 243. Leaders: Populist Andre Babis, leader of the Action | of Dissatisfied Citizens/Yes (Akce Nespokojenych Obcanu, | ANO 2011, PARTY B) was charged with fraud involving | European subsidies. Opposition parties prompted to form | alliances in the election to oppose his candidature. | 244. Economy/Inflation. | 245. Corruption. | 246. COVID-19 pandemic. | 247. Housing. | ELECTION STUDY NOTES - DENMARK (2019): E5021 | | A detailed description of the most salient factors | in the election as perceived by the Collaborators were: | 160. Climate Change | 161. Early retirement for workers | 162. Welfare | 163. Immigration and integration | ELECTION STUDY NOTES - EL SALVADOR (2019): E5021 | | A description of the most salient factors in the election is | included here: | | 253. An 'anti-elite' and 'anti-political' discourse of the | candidate (Nayib Bukele) that won the election. | 254. Citizen discontent with traditional political parties | (ARENA and FMLN) that had dominated Presidential | elections for the past 30 years. | ELECTION STUDY NOTES - FINLAND (2019): E5021 | | A description of the most salient factors in the election is | included here: | | 136. The previous government's (PM Sipila) failed social and | health care reform and the resignation of the government | just prior to the election. | 137. Widespread media reporting of prevalent neglect and lack | of staff by large nursing home operators and the | following public discussion about elderly care (late | 2018 - early 2019). | 138. IPCC climate report (September 2019) and the following | public discussion about environmental and climate issues. | 139. Sexual violence/crime scandal - in December 2018, it was | widely covered in the media that adult migrant men were | committing sexual crimes against young girls in Oulu. | ELECTION STUDY NOTES - FRANCE (2017): E5021 | | A detailed description of the most salient factors | in the election as perceived by the Collaborators were: | 085. Elite and politicians' corruption | 086. The euro and French relation to the European Union | 087. Public service and its importance | 088. Immigration and refugee crisis | 089. Terrorism and social unrest | ELECTION STUDY NOTES - GERMANY (2017): E5021 | | A detailed description of the most salient factors | in the election as perceived by the Collaborators were: | 030. Immigration/limiting immigration/monothematic debate | about migration | 031. Increasing popularity and respective media coverage of | the AfD | 032. Decreasing popularity of SPD/unconvincing chancellor | candidate Martin Schulz | 033. Societal polarization/segmentation | 034. Fear of ever-lasting grand coalition | ELECTION STUDY NOTES - GERMANY (2021): E5021 | | A detailed description of the most salient factors | in the election as perceived by the Collaborators were: | 233. Controversy surrounding the CDU-CSU Chancellor candidate | Armin Laschet, including his public demeanor post the | 2021 German flood disaster. And the attacks on his | candidature from within his own bloc, especially from | Markus Soeder, Minister-President of Bavaria, and leader | of the CSU. | 234. Climate change. | 235. Measures to contain the COVID-19 pandemic. | 236. Uncertainty regarding government's constellation post | the 2021 election. | 237. Social justice. | ELECTION STUDY NOTES - GREAT BRITAIN (2017): E5021 | | A detailed description of the most salient factors | in the election as perceived by the Collaborators were: | 145. Brexit - United Kingdom exit from the European Union. | 146. Party leader popularity. | 147. Social care. | 148. Terrorism/Security. | 149. Scottish independence. | ELECTION STUDY NOTES - GREAT BRITAIN (2019): E5021 | | A detailed description of the most salient factors | in the election as perceived by the Collaborators were: | 218. Brexit - United Kingdom exit from the European Union. | 219. Party leader popularity. | 220. Health. | 221. Regional inequality. | 222. Scottish independence. | ELECTION STUDY NOTES - GREECE (2015): E5021 | | A detailed description of the most salient factors | in the election as perceived by the Collaborators were: | 055. Austerity policies (linked to the Memorandums between | the Greek government and its creditors); | 056. Economic recession and unemployment; | 057. Rejection of the old two-party system and old | political personnel; against corruption and vested | interests; | 058. The refugee crisis and illegal immigration; | 059. Restoration of the role of Parliament: against growing | democratic deficit in Greece under the crisis. | ELECTION STUDY NOTES - GREECE (2019): E5021 | | A description of the most salient factors in the election is | included here: | | 248. Economic recession | 249. Restructuring the state after many years of crisis - | Return to normalcy | 250. Unemployment - Job Creation | 251. National security | 252. Immigration | ELECTION STUDY NOTES - HONG KONG (2016): E5021 | | A detailed description of the most salient factors | in the election as perceived by the Collaborators were: | 060. Divisions within the opposition camp regarding campaign | strategy and attitudes towards the Central People's | Government of the People's Republic of China; | 061. Attitudes towards localism in Hong Kong / "Hong Kong | independence"; | 062. Whether to support the then Chief Executive Leung Chun | Ying seeking the second term of office; | 063. Attitudes towards Returning Officers' decisions to | deny the candidacy of some of the persons who intended | to run for the Legislative Council Election; | 064. Attitudes towards filibusters in the Legislative Council. | ELECTION STUDY NOTES - HUNGARY (2018): E5021 | | A detailed description of the most salient factors | in the election as perceived by the Collaborators were: | 006. Immigration (refugees, asylum seekers, | migrants, issue of border control). | 007. Corruption (nepotism, public procurement, | government-related oligarchs, graft, | embezzlement, etc.). | 008. Economic conjuncture (low unemployment, increasing | real wages, tax cuts, distribution of non-monetary | benefits to particular groups like food vouchers | to pensioners, etc.). | 009. Electoral cooperation of the opposition (inability | and unwillingness to do so, bilateral withdrawals, | rare instances of coordination in single-member | districts, efforts by non-partisan actors to find | 'competitive candidates', etc.). | 010. Discrediting campaigns of pro-government media outlets | directed towards leaders of the opposition (accusations | of Gabor Vona's homosexuality, Jobbik parliamentary | group leader's hinted affair, luxurious way of life | of Botka, business affairs of Hadhazy's family and the | politician's conflicts with his neighbors, etc.). | ELECTION STUDY NOTES - ICELAND (2016): E5021 | | A detailed description of the most salient factors | in the election as perceived by the Collaborators were: | 070. Health care system | 071. Social welfare system | 072. The Panama Scandal | 073. The economy | 074. Infrastructure, roads, airports etc. | ELECTION STUDY NOTES - ICELAND (2017): E5021 | | A detailed description of the most salient factors | in the election as perceived by the Collaborators were: | 075. Health care system | 076. Housing | 077. Social welfare system | 078. The 'restored honor' scandal | 079. The economy | | According to the Macro Report: "The 'restored honor' scandal | [Issue 078.] refers to the fact, that the Prime Minister did not | inform the leaders of his coalition parties on information he | had concerning 'restored honor' for child-molesters that had | served their prison sentences. Bright Future considered this as | a break of confidence among the coalition partners, and resigned | from government. The Prime Minister then decided to call for new | elections." | ELECTION STUDY NOTES - INDIA (2019): E5021 | | A description of the most salient factors in the election is | included here: | | 255. Jingoism following a terrorist incident in Kashmir which | the Indian government blamed Pakistan and then carried | out a cross-border attack in retribution. | 256. Consolidation of the Hindu vote behind the BJP. | 257. Economic aspirations and desire for economic growth. | 258. Prime Minister Modi's personal popularity. | 259. Failure of opposition parties to mount a unified front | thereby splitting opposition votes. | ELECTION STUDY NOTES - IRELAND (2016): E5021 | | A detailed description of the most salient factors | in the election as perceived by the Collaborators were: | 040. Health services | 041. Management of the economy | 042. Stable government | 043. Water charges | 044. Housing | ELECTION STUDY NOTES - ISRAEL (2020): E5021 | | A detailed description of the most salient factors | in the election as perceived by the Collaborators were: | 180. Prime Minister Netanyahu corruption allegations and | upcoming judicial trial | 181. Instability of the Israeli political system | 182. Government's management of COVID-19 pandemic | 183. Economy | 184. US President Donald Trump's Middle East Peace Plan | ELECTION STUDY NOTES - ITALY (2018): E5021 | | A detailed description of the most salient factors | in the election as perceived by the Collaborators were: | 016. Immigration (conjugated more in terms of crime/security | rather than cultural identity or economy, in particular | the murder of Pamela Mastropietro at the end of January, | the following shooting by Luca Traini, and the reactions | of the political parties, boosted the salience of the | issue right before the elections). | 017. Jobs (in particular work protection), Poverty. | 018. Taxes/Social benefits (including retirement benefits). | 019. Europe (in particular the treaties about the | distribution of migrants and asylum seekers, and the | debt constraints given by Italy being Eurozone | member) | ELECTION STUDY NOTES - JAPAN (2017): E5021 | | A description of the most salient factors in the election is | included here: | 170. Constitution | 171. Economic policy (aka Abenomics) | 172. Sales tax raised to 10% | 173. Security issues (e.g., North Korean's missiles and | nuclear bombs) | 174. Maintaining or discontinuing nuclear power plants | ELECTION STUDY NOTES - LATVIA (2018): E5021 | | A description of the most salient factors in the election is | included here: | | 260. Advent of populists | 261. Ethnic cleavage | ELECTION STUDY NOTES - LITHUANIA (2016): E5021 | | A detailed description of the most salient factors | in the election as perceived by the Collaborators were: | 011. Corruption scandal related to the Liberals Movement of | the Republic of Lithuania and the Social Democratic | Party. | 012. Popular non-partisan political actor Saulius Skvernelis | joining the Lithuanian Union of Farmers and Greens. | 013. Change of party leaders. | 014. Strategic voting in the second round in single-member | districts. | 015. Economic policy of the incumbent Lithuanian Social | Democratic Party, adoption of pro-liberal Labor Code. | ELECTION STUDY NOTES - LITHUANIA (2020): E5021 | | A description of the most salient factors in the | election is included here: | | 195. Successful electoral campaign of the newcomer Freedom | Union. | 196. COVID-19 pandemics. | 197. The comeback of Viktor Uspaskich, the founder of the | Labor Party. | 198. The popularity of Ingrida Simonyte, the candidate of the | TS-LKD to the Prime Minister position. | 199. The LRLS recovery from a crisis caused by corruption | scandals and the split in 2019. | ELECTION STUDY NOTES - MEXICO (2018): E5021 | | A detailed description of the most salient factors | in the election as perceived by the Collaborators were: | | 200. Corruption scandals of the outgoing administration (PRI). | 201. MORENA's candidate Andres Manuel Lopez Obrador was a | well-known politician that had been Presidential | candidate in the 2006 and 2012 Presidential elections. | 202. Insecurity crisis: violence and human rights violations, | specifically the disappearance of the 43 Ayotzinapa | students. | 203. The PAN and PRI candidates were bad candidates. The PAN | Presidential candidate, Ricardo Anaya, divided the party | when he got his nomination. Also, he was involved in a | corruption scandal. The PRI candidate, Jose Antonio | Meade, was seen as an outsider candidate because his | affiliation to the party was recent and, in addition, he | occupied senior positions in the secretariats of the | previous administration which, as mentioned in point one, | was corrupt. | ELECTION STUDY NOTES - MONTENEGRO (2016): E5021 | | A detailed description of the most salient factors | in the election as perceived by the Collaborators were: | 001. Montenegrins vs. Serbs cleavage and related | statehood issues. | 002. Electoral integrity. | 003. Unemployment. | 004. NATO integration. | 005. Crime. | ELECTION STUDY NOTES - NETHERLANDS (2017): E5021 | | A description of the most salient factors in the election is | included here: | 140. Austerity | 141. Migration / integration | 142. Health care | 143. Pensions / retirement age | 144. The environment / global warming | ELECTION STUDY NOTES - NETHERLANDS (2021): E5021 | | A description of the most salient factors in the election is | included here: | | 228. COVID-19 pandemic: government's management of crisis | 229. COVID-19 pandemic: Consequences for economy and healthcare | 230. Leadership images | 231. Migration | 232. Economy | ELECTION STUDY NOTES - NEW ZEALAND (2017): E5021 | | A more detailed description of the most salient factors | in the election is included here: | 095. Economy. | 096. Housing. | 097. Health. | 098. Poverty. | 099. Tax. | ELECTION STUDY NOTES - NEW ZEALAND (2020): E5021 | | A more detailed description of the most salient factors | in the election is included here: | 164. COVID-19 pandemic. | 165. Economic stimulus. | 166. Leadership. | ELECTION STUDY NOTES - NORWAY (2017): E5021 | | A detailed description of the most salient factors | in the election as perceived by the Collaborators were: | 090. Immigration | 091. Environment | 092. Education | 093. Taxes | 094. Economy, industry and employment | ELECTION STUDY NOTES - PERU (2021): E5021 | | A detailed description of the most salient factors | in the election as perceived by the Collaborators were: | 223. Health measures against COVID-19 pandemic. | 224. Economy. | 225. Citizen security. | 226. Corruption. | 227. Education. | ELECTION STUDY NOTES - POLAND (2019): E5021 | | A description of the most salient factors in the | election is included here: | | 213. "Plebiscitary nature of the 2019 electoral contest - for | or against PiS - and more broadly for or against a | liberal version of democracy, as well as for or against | the EU" (Markowski 2020: 1521). | 214. Redistributive policies. | 215. LGBT+ rights, Women's rights. | 216. Democratic backsliding, Rule of Law. | 217. EU. | ELECTION STUDY NOTES - PORTUGAL (2019): E5021 | | The most salient factors in the election as perceived by the | Collaborators were: | 128. Healthcare | 129. Corruption | 130. Economic Issues | ELECTION STUDY NOTES - ROMANIA (2016): E5021 | | The most salient factors in the election as perceived by the | Collaborators were: | 204. The Colectiv nightclub fire on October 30, 2015, that led | to the death of 64 people and raised a series of anti- | corruption protests in Romania. As a result, Prime | Minister Victor Ponta resigned on November 4, 2015. His | Cabinet (formed by three parties - Social Democratic | Party, Alliance of Liberals and Democrats, and National | Union for Romania's Progress) was replaced by a | technocratic Cabinet led by the former European | Commissioner Dacian Ciolo?. | 205. The Dacian Ciolo? technocratic Cabinet, in office for one | year prior to the 2016 General Election (November 17, | 2015 - January 4, 2017). | 206. The reluctance of Prime Minister Dacian Ciolo? to | formally associate with the National Liberal Party in the | electoral campaign. | 207. The rise of the Save Romania Union, with roots in the | civil society, as an anti-system and loudly anti- | corruption political contender. | 208. The return to the PR electoral system for the 2016 | Parliamentary Elections as a consequence of Law no. | 208/2015, passed by the Parliament with a large majority. | ELECTION STUDY NOTES - SLOVAKIA (2020): E5021 | | A detailed description of the most salient factors | in the election as perceived by the Collaborators were: | 185. Corruption scandals. | 186. Quest for change. | 187. Justice and judicial system. | 188. Socio-economic issues: standard of living, employment, | social benefits. | 189. Socio-cultural issues: reproductive rights, sexual | minority rights. | ELECTION STUDY NOTES - SOUTH KOREA (2016): E5021 | | A detailed description of the most salient factors | in the election as perceived by the Collaborators were: | 050. The gap between rich and poor | 051. Political Corruption | 052. South-North Korea relations | 053. Balanced regional development | 054. Human rights | ELECTION STUDY NOTES - SWEDEN (2018): E5021 | | A detailed description of the most salient factors | in the election as perceived by the Collaborators were: | 150. Healthcare. | 151. Immigration and integration. | 152. Schools/Education. | 153. Environment. | 154. Elderly care/pensions. | ELECTION STUDY NOTES - SWITZERLAND (2019): E5021 | | The most salient factors in the election as perceived by the | Collaborators were: | 110. Climate change: Public debate on global climate change | and large mobilizations for numerous events (such as | school strikes and demonstrations for stricter climate | protection measures) across the country during the | election year. | 111. Women's strike: National women's strike on 14 June 2019, | which mobilized hundreds of thousands of women to | demonstrate against their persisting unequal treatment in | the Swiss society. During the election campaign, several | trade unions and women's associations called upon parties | to put more women on their lists and upon citizens to | deliberately vote for women in the federal elections. | 112. Old-age pensions: Voters mentioned problems regarding the | welfare state and social insurances as the second most | important political problem (after climate change). Due | to the aging of the population health costs are | increasing and a reform of the old-age pension system | becomes more and more urgent in order to secure pensions | in the future. | 113. Relations with EU: Even though the bilateral relationship | between Switzerland and the EU was not the most salient | topic during the election campaign, it still made it into | the top 3 of the most important political problems | according to voters. Especially the debate on the | institutional framework agreement played an important | role in the election year. | 114. Negative campaigning: There was some media attention when | the SVP unveiled a poster that showed a red apple with a | Swiss flag being eaten by worms wearing the colors of the | four other main political parties as well as the EU. | Another event of negative campaigning was the CVP's | Internet campaign, which criticized the positions of | candidates from other parties and promoted its own | candidates. | ELECTION STUDY NOTES - TAIWAN (2016): E5021 | | A detailed description of the most salient factors | in the election as perceived by the Collaborators were: | 035. Party identification | 036. Personal traits and capability of the candidates | 037. Cross-Strait issues: 92 Consensus | 038. Economic issues | 039. President Ma's whole term in office | ELECTION STUDY NOTES - TAIWAN (2020): E5021 | | A description of the most salient factors in the election is | included here: | 131. Party identification | 132. Personal traits and capability of the candidates | 133. Cross-Strait issues | 134. Economic issues | 135. President Tsai's whole term in office | ELECTION STUDY NOTES - THAILAND (2019): E5021 | | A description of the most salient factors in the election is | included here: | 175. Electoral system. | 176. Populism policies before the election (the period of | Military junta) such as State Welfare Card Scheme | 177. Name of Prime Ministerial candidate. | 178. Moving party of the former member of the House of | Representatives. | 179. Using the Article 44 of the 2014 Constitution by the | Military junta. | ELECTION STUDY NOTES - TUNISIA (2019): E5021 | | A description of the most salient factors in the election is | included here: | 167. One of the candidates, Nabil Karoui, from the | Presidential elections was held in jail for suspicion of | financial crimes. He was not allowed to take part in the | Presidential debates with other candidates. He was | released when he won the first round. The move was | considered by media and analysts as a strategy to | undermine his popularity in the elections (both | Presidential and legislative). Nabil Karoui was running | as a candidate in the Presidential but also with his | party, Kalb Tounes, in the legislative elections. | 168. Scandal: Nabil Karoui was found dealing with Canadian | lobbyist, who is also a former Israeli intelligence | agent. The deal consisted of a contract of US$ 1million | to support Karoui's presidency and in return he would | play the role of a regional peace-maker in the Libyan | conflict. | 169. Death of the President of the country, Beji Caid Essebsi | in July 2019, which led to a change in the elections' | dates. | ELECTION STUDY NOTES - TURKEY (2018): E5021 | | A detailed description of the most salient factors | in the election as perceived by the Collaborators were: | 065. The Economy | 066. The Welfare | 067. Terror | 068. Syrians, Security | 069. Regime debate | ELECTION STUDY NOTES - UNITED STATES (2016): E5021 | | A detailed description of the most salient factors | in the election as perceived by the Collaborators were: | 045. Candidate evaluations and scandals (For Donald Trump | his attitudes on several issues such as race and | immigration as well as his comments towards women | in a 2006 tape release; For Hillary Clinton the e-mail | scandal). | 046. Immigration and anti-elitism. | 047. Economy | 048. Healthcare. | 049. Race. | ELECTION STUDY NOTES - UNITED STATES (2020): E5021 | | A detailed description of the most salient factors | in the election as perceived by the Collaborators were: | 190. COVID-19 pandemic. | 191. Election integrity (mail-in voting; acceptance of the | result by the incumbent President; foreign interference | and misinformation). | 192. Racial injustice and inequality. | 193. Economy. | 194. Candidate evaluations and fitness for office. | ELECTION STUDY NOTES - URUGUAY (2019): E5021 | | A description of the most salient factors in the election is | included here: | 155. Public safety - crime | 156. Economy - fiscal deficit | 157. Public Administration - mismanagement of public | money | 158. Education | 159. International policy - Mercosur - Venezuela --------------------------------------------------------------------------- E5022 >>> FAIRNESS OF THE ELECTION --------------------------------------------------------------------------- M08a. How impartial was the body that administered the election law? .................................................................. 1. VERY IMPARTIAL 2. MOSTLY IMPARTIAL 3. NOT VERY IMPARTIAL 4. NOT IMPARTIAL AT ALL 9. MISSING | VARIABLE NOTES: E5022 | | Source of data: CSES Macro Report M8a. | ELECTION STUDY NOTES - HONG KONG (2016): E5022 | | As before, the body administering the election law in Hong Kong | (the Electoral Affairs Commission) largely considered the 2016 | LegCo Election as impartial. However, in this election, | there was one incident that led to queries over the body's | impartiality: returning officers under the Electoral Affairs | Commission decided that six persons were not qualified for | running for LegCo on the ground that judging from their past | remarks and social media posts, the disqualified persons | advocated Hong Kong independence, so could not genuinely support | the Basic Law (according to which Hong Kong is an inalienable | part of China). Since in previous elections, returning officers | had never made this kind of political judgments, some perceived | their decisions as political censorship over who could run for | LegCo Election and rejection of the candidacy of some persons on | political grounds. (From the Macro Report.) --------------------------------------------------------------------------- E5023 >>> FORMAL COMPLAINTS AGAINST NATIONAL LEVEL RESULTS --------------------------------------------------------------------------- M08b. Was there a formal complaint against the national level results? .................................................................. 1. YES 5. NO 6. OTHER - SEE ELECTION STUDY NOTES 9. MISSING | VARIABLE NOTES: E5023 | | Source of data: CSES Macro Report M8b. | ELECTION STUDY NOTES - AUSTRIA (2017): E5023 | | A formal complaint was filed by the list "Fuer Osterreich, | Zuwanderungsstopp, Grenzschutz, Neutralitaet, EU-Austritt | (EUAUS)". EUAUS received 693 votes (< 0.1% of the total vote). | They contested the election on a variety of reasons (e.g., the | ballot order). The constitutional court rejected the formal | complaint. | ELECTION STUDY NOTES - CZECHIA (2017): E5023 | | The complaint referred to the design of ballot papers and how | preference votes were counted in the election. Ballot papers | contained list of candidates on both sides of the ballot (front | and back). However, in several electoral districts, the Electoral | Commission did not count the preferential votes on the back page | of the ballots. The Supreme Administrative Court ordered a | recount of preferential votes, which resulted in a different | individual being elected in the Central Bohemia district for the | Civic Democratic Party (ODS, PARTY B). | ELECTION STUDY NOTES - GERMANY (2021): E5023 | | Formal complaints against the election results are a common | occurrence in Germany, including disputes over ballot layout and | and errors in vote tabulation. But two complaints generated | notable coverage in the media. The first was a complaint from | the Alternative for Germany (AfD, PARTY E), which objected to | the Green Party (Buendnis 90/Die Gruenen, PARTY C) gender | balanced slate of candidates for the 2021 election | ("Frauenstatut"), calling them undemocratic. | The second notable complaint was problems with voting in Berlin | state with voting plagued with problems including missing or | incorrect ballot papers, polling stations temporarily closed | during voting hours, and other organizational challenges, some | associated with the Berlin Marathon, which was taking place | on the same day, and made voting challenging for some people. | The Federal Election Commissioner submitted an objection due | to these challenges. | ELECTION STUDY NOTES - PERU (2021): E5023 | | Defeated Presidential candidate Keiko Fujimori (PARTY B, Fuerza | Popular, FP) alleged on June 7, 2021, that there was "fraud" at | several rural polling stations, arguing that this made a material | difference to the result of the Presidential election and the | victory of Pedro Castillo. Fuerza Popular presented 945 | complaints regarding the electoral process to the National | Electoral Jury (Jurado Nacional del Eleccionnes, JNE) but most | of the objections were dismissed, and the JNE reaffirmed the | result of the Presidential election. | Some allies of Fuerza Popular continued to cast doubt on the | result and petitioned the Organization of American States (OAS) | for an audit of the election results but the request to the OAS | was not granted. | ELECTION STUDY NOTES - POLAND (2019): E5023 | | Immediately after the Senate election results were announced, PiS | started challenging several results (though without any objective | justification) because allegedly there were too many invalid | ballots. All of those challenges were rejected by the courts. | ELECTION STUDY NOTES - UNITED STATES (2020): E5023 | | While there was no formal complaint against the national-level | results per se, there were many challenges by Republican Party | officials and President Trump's supporters at the state level. | Sixty-three lawsuits were filed, including in states like | Georgia, Michigan, Nevada, Pennsylvania, and Wisconsin, all | states won by Democratic challenger Joe Biden (PARTY A), | challenging the election. Most legal challenges, some of which | the US Supreme Court considered, were dismissed or dropped due | to lack of evidence. | | Sources of data: | | Bloomberg Law: "Trump's election lawsuits: Where the Fights are | Playing Out" | https://news.bloomberglaw.com/us-law-week/trumps-election- | lawsuits-where-the-fights-are-playing-out | (Date accessed: February 03, 2022). | | New York Times: "Supreme Court Rejects Republican Challenge to | Pennsylvania Vote" | https://www.nytimes.com/2020/12/08/us/supreme-court-republican- | challenge-pennsylvania-vote.html | (Date accessed: February 03, 2022). | | New York Times: "Supreme Court Rejects Texas Suit Seeking to | Subvert Election" | https://www.nytimes.com/2020/12/11/us/politics/supreme-court- | election-texas.html | (Date accessed: February 03, 2022). --------------------------------------------------------------------------- E5024 >>> ELECTION IRREGULARITIES REPORTED --------------------------------------------------------------------------- M08c. Were there irregularities reported by international election observers? .................................................................. 1. YES 5. NO 6. NO INTERNATIONAL ELECTION OBSERVERS 9. MISSING | VARIABLE NOTES: E5024 | | Source of data: CSES Macro Report M8c. | ELECTION STUDY NOTES - POLAND (2019): E5024 | | The Statement of Preliminary Findings and Conclusions issued on | 14 October concluded that the parliamentary elections were | prepared well, 'but media bias and intolerant rhetoric in the | campaign were of significant concern. While all candidates were | able to campaign freely, senior state officials used publicly | funded events for campaign messaging. The dominance of the | ruling party in public media further amplified its advantage. | Election day was orderly, although secrecy of the vote was not | always enforced. Timely publication of preliminary results | ensured transparency'. --------------------------------------------------------------------------- E5025_1 >>> DATE ELECTION SCHEDULED - MONTH E5025_2 >>> DATE ELECTION SCHEDULED - DAY E5025_3 >>> DATE ELECTION SCHEDULED - YEAR E5026_1 >>> DATE ELECTION HELD - MONTH E5026_2 >>> DATE ELECTION HELD - DAY E5026_3 >>> DATE ELECTION HELD - YEAR E5026_W >>> DATE ELECTION HELD - TIMING E5026_S >>> DATE ELECTION HELD - SEASON --------------------------------------------------------------------------- M08d. On what date was the election originally legally scheduled to be held? M08e. On what date was the election actually held? .................................................................. MONTH 01. JANUARY 02. FEBRUARY 03. MARCH 04. APRIL 05. MAY 06. JUNE 07. JULY 08. AUGUST 09. SEPTEMBER 10. OCTOBER 11. NOVEMBER 12. DECEMBER 99. MISSING DAY 01-31. DAY OF MONTH 96. [SEE ELECTION STUDY NOTES] 99. MISSING YEAR 2016-2021. YEAR 9999. MISSING TIMING 0. ELECTION HELD ON WEEKEND 1. ELECTION HELD ON WEEKDAY 2. ELECTION HELD ON WEEKEND & WEEKDAY 96. NOT ASCERTAINABLE 99. MISSING SEASON 0. ELECTION HELD IN SPRING 1. ELECTION HELD IN SUMMER 2. ELECTION HELD IN FALL 3. ELECTION HELD IN WINTER 99. MISSING | VARIABLE NOTES: E5025_ & E5026_ | | Source of data: CSES Macro Report M8d-e. | | If the election involved multiple rounds, dates reported in | E5025_ and E5026_ refer to the first round, unless stated | otherwise in the ELECTION STUDY NOTES below. | | Elections held Monday-Friday inclusive are classified as weekday | elections. Elections held Saturday-Sunday are classified as | weekend elections. However, researchers are advised that while | this conceptualization of workweek and weekend applies to most | of the world, there are some notable exceptions with Sunday- | Thursday workweeks (e.g., Israel due to the Shabbat and some | Muslim-majority countries due to Friday prayers). | | Seasonal designations for elections in the Northern Hemisphere | are classified as follows: | - Spring: March, April, May | - Summer: June, July, August | - Fall: September, October, November | - Winter: December, January, February | | Seasonal designations for elections in the Southern Hemisphere | are classified as follows: | - Fall: March, April, May | - Winter: June, July, August | - Spring: September, October, November | - Summer: December, January, February | | Furthermore, data refer to the main election, unless otherwise | stated. | CSES classifies the main election based on the regime | (executive) type and the election in which the CSES survey has | been administered. For polities rated as parliamentary systems, | CSES classifies the main election as elections to the lower house | for most studies. It deviates for a few cases when elections to | the upper house constitutes the main election, usually due to the | respective CSES study focusing on the upper house contest. | For polities rated as Presidential systems, CSES conventionally | classifies the main election as the Presidential election. It | sometimes deviates when data for the Presidential election is | unavailable (e.g., when the CSES survey was administered in a | midterm election). For polities rated as mixed systems, CSES | has tended to classify the main election as elections to the | lower house. However, it sometimes deviates depending on data | availability. Users are advised to consult the table listed in | VARIABLE NOTES for E3013_OUTGOV specifying the main election for | each study in CSES for specific details. | ELECTION STUDY NOTES - BRAZIL (2018): E5025 & E5026 | | The second round of the election was held on October 28, 2018, | three weeks after the first round. As the majority of the country | is located in the Southern Hemisphere, Brazil is classified as | such for the seasonal calculation. | ELECTION STUDY NOTES - CZECHIA (2017): E5026_2 | | Elections were held on two days, October 20 and 21, 2017. Only | the first date (October 20) is characterized in the dataset. | ELECTION STUDY NOTES - CZECHIA (2021): E5026_2 | | Elections were held on two days, October 8 and 9, 2021. Only | the first date (October 8) is characterized in the dataset. | ELECTION STUDY NOTES - FRANCE (2017): E5025 & E5026 | | The second round of the French Presidential election was held | on May 7, 2017. | ELECTION STUDY NOTES - GREECE (2015): E5025 | | The election was originally legally scheduled to be held in | January 2019. | ELECTION STUDY NOTES - GREECE (2019): E5025_2 | | The election was originally legally scheduled to be held in | September 2019. | ELECTION STUDY NOTES - ICELAND (2016): E5025 & E5026 | | The elections were due to be held on or before April 27, 2017, | that is, four years after the 2013 elections. | ELECTION STUDY NOTES - ICELAND (2017): E5025 & E5026 | | The elections were due to be held in or before October 2020, | because the previous elections were held on October 29, 2016. | ELECTION STUDY NOTES - INDIA (2019): E5025 & E5026 | | The elections were scheduled and held on multiple dates and were | conducted between April 11, 2019, and May 19, 2019, in seven | phases. Only the first date (April 11) is characterized in the | dataset as the date scheduled. For the timing variable, India is | classified as "96. NOT ASCERTAINABLE". | ELECTION STUDY NOTES - ISRAEL (2019): E5026_W | | The Israeli 2020 election was held on Monday, March 2, 2020. | Hence, irrespective of the diverging Sunday-Thursday working week | convention in Israel, elections were held on a weekday. | ELECTION STUDY NOTES - JAPAN (2017): E5025 & E5026 | | The elections were due to be held in December 2018, that is, | four years after the 2014 elections. | ELECTION STUDY NOTES - NETHERLANDS (2021): E5026_2 | | Elections were held across three days, March 15-17, 2021, to | facilitate early voting and prevent crowding at polling stations | due to the ongoing COVID-19 pandemic. The election was originally | scheduled for March 17, 2021. The dataset characterizes this date | as the date the election was initially intended to occur. | ELECTION STUDY NOTES - PERU (2021): E5023 | | Round 2 of the Presidential election was held on June 6, 2021. | ELECTION STUDY NOTES - THAILAND (2019): E5025 & E5026 | | These were the first elections since the 2014 Thai coup d'etat | that installed coup leader General Prayut Chan-o-cha as prime | minister (leader of Palang Pracharath Party, PARTY A), and the | first held in accordance with the 2017 constitution, which was | drafted under the ruling military junta. | The final election date was selected in early 2019 after several | delays. Hence, the "date election scheduled" has a specific | meaning here. | ELECTION STUDY NOTES - TUNISIA (2019): E5025 & E5026 | | The data refer to the parliamentary election. The Presidential | election was originally scheduled to be held on November 17 and | November 24, 2019. However, due to the death of President Beji | Caid Essebsi on July 25, 2019, the elections were brought forward | to September 15, 2019 (Round 1), and October 14, 2019 (Round 2). | ELECTION STUDY NOTES - TURKEY (2018): E5025 | | The election was originally legally scheduled to be held on | November 3, 2019. | ELECTION STUDY NOTES - URUGUAY (2019): E5025 & E5026 | | The entered date refers to the first round of elections. The | second round was held on November 24th, 2019. --------------------------------------------------------------------------- E5027 >>> ELECTION DATE IRREGULARITIES --------------------------------------------------------------------------- M08e. If the election was held on a different date than scheduled, please explain why? .................................................................. 0. ELECTION WAS HELD ON THE SAME DAY AS SCHEDULED 1. ELECTION WAS NOT HELD ON THE SAME DAY AS SCHEDULED [SEE ELECTION STUDY NOTES] 9. MISSING | VARIABLE NOTES: E5027 | | E5027 details whether or not the election was held on a different | date than scheduled, i.e., whether any election date | irregularities occurred. | | In instances where elections were held on a different day than | scheduled, ELECTION STUDY NOTES below provide further details. | | Source of data: CSES Macro Report M8e. | ELECTION STUDY NOTES - ALBANIA (2017): E5027 | | This was an early election. The 2017 elections were initially | scheduled for 18 June but were postponed by one week, following | an agreement between the PS and PD on 18 May to allow senior | opposition officials to monitor the election process. The PD had | boycotted Parliament since February 2017 in support of their | call for the creation of a technocratic government to oversee | the organization of free and fair elections. (Source of data: | Inter-Parliamentary Union, http://archive.ipu.org/parline- | e/reports/2001_E.htm; Date accessed: July 20, 2023). | ELECTION STUDY NOTES - GREAT BRITAIN (2017): E5027 | | Under the Fixed Term Parliament Act, British parliamentary terms | are conventionally five years, with elections scheduled for the | first Thursday in May, five years from the previous election. As | the previous election had been held on May 7, 2015, the next | election was scheduled for May 2020. | However, Conservative incumbent Prime Minister Theresa May sought | an early election to strengthen her mandate for Brexit | negotiations with the EU. Under the Fixed Term Parliament Act, | Parliament can be dissolved for an early election if 2/3 of the | Parliament vote in favor. A House of Commons motion was passed on | 19 April 2017 facilitating the early election - supported by | the Conservatives, Labor, the Liberal Democrats, and the Greens, | on a vote of 522-13 (the SNP abstained). | ELECTION STUDY NOTES - GREAT BRITAIN (2019): E5027 | | Under the Fixed Term Parliament Act, British parliamentary terms | are conventionally five years. Under the Fixed Term Parliament | Act, Parliament can be dissolved for an early election if 2/3 of | the parliament vote in favor. An election was not anticipated | until May 2022. However, Conservative Prime Minister Theresa | May's failure to get House of Commons support for her Brexit | deal agreed with the European Union in November 2018 saw Britain | fail to leave the Union by March 31, 2019. A disastrous | performance by the Conservative Party in the 2019 European | elections saw the Conservatives slump to fifth place in the | national vote and the Brexit party win the most votes. It forced | Theresa May to resign as Conservative leader and Prime Minister | to be replaced by Boris Johnson, an original Brexit supporter. | Upon assuming office, Mr. Johnson decided to re-open | negotiations with the European Union, but also made three | attempts in the House of Commons for parliament to be dissolved. | All failed to meet the two-thirds threshold required for an | early dissolution, with opposition parties (and some backbench | Conservative MPs) insisting that Mr. Johnson rule out a "no-deal" | UK withdrawal from the EU. Prime Minister Johnson conceded to | keep negotiations with the EU open. Eventually, the government | agreed to a revised withdrawal deal with the European Union in | November 2019. A House of Commons motion was passed on October | 28, 2019, facilitating the early election - 438-20 votes. | ELECTION STUDY NOTES - GREECE (2015): E5027 | | This was an early election, following Prime Minister Alexis | Tsipras' announcement of his resignation on August 20, 2015. | Almost one-third of Syriza's MPs were against the third bailout | agreement signed by Tsipras - consequently, after signing the | agreement, Tsipras lost the parliamentary majority. Previous | parliamentary elections were held on 25 January 2015. | ELECTION STUDY NOTES - GREECE (2019): E5027 | | This was an early election, following the defeat of SYRIZA | at European and local elections held on May 26, 2019. The | new election date was July 7, 2019. | ELECTION STUDY NOTES - ICELAND (2016): E5027 | | The current elections were held ahead of time, on October 29, | 2016. The elections were due to be held on or before April 27, | 2017, that is, four years after the 2013 elections. | However, following the publication of the Panama Papers and the | 2016 Icelandic anti-government protests, the ruling coalition | announced that early elections would be held before the end | of 2016. | ELECTION STUDY NOTES - ICELAND (2017): E5027 | | The current elections were held ahead of time, on October 28, | 2017. The 2017 snap elections were triggered by the collapse of | the coalition government, when Bright Future left the coalition | citing a breach of confidence, following a scandal involving the | Prime Minister's father. | According to the Macro Report: "The 'restored honor' scandal | [Issue 078.] refers to the fact, that the Prime Minister did not | inform the leaders of his coalition parties on information he | had concerning 'restored honor' for child-molesters that had | served their prison sentences. Bright Future considered this as | a break of confidence among the coalition partners, and resigned | from government. The Prime Minister then decided to call for new | elections." | ELECTION STUDY NOTES - INDIA (2019): E5027 | | The elections were conducted between April 11 and May 19, 2019, | in 7 phases, as scheduled. | ELECTION STUDY NOTES - ISRAEL (2020): E5027 | | Conventionally, the Israeli Basic Law provides for elections to | be held every four years, usually in the Jewish month of Cheshvan | (in the Roman calendar October-November). The 2020 elections | were held after two inconclusive elections in March 2019 and | September 2019 respectively, where no new majority coalition | government could be formed. The date scheduled for the election | by the dissolution of the 22nd Israeli Parliament (the Knesset, | (elected in September 2019) was March 2, 2020, the day the | election was held. This contest represented the first time | in Israeli history that three general elections had been held in | the space of 13 months. The date classified in the dataset as | the scheduled election date for 2020 does not capture this | tumult or that the term of the 22nd Israeli Parliament was cut | significantly short from its anticipated 4-year term, due to | the failure to form a majority coalition government. | ELECTION STUDY NOTES - NEW ZEALAND (2020): E5027 | | On January 28, 2020, Prime Minister Jacinda Ardern announced that | the 2020 election would be held on September 19, 2020. However, | after a community transmission outbreak in Auckland in New | Zealand's North Island, on August 17, 2020, Prime Minister Ardern | announced the election would be delayed until October 17, 2020 | after consultations with the Electoral Commission and support of | the main opposition National Party. Any election held after | November 28, 2020, would have required a super-majority | legislative change in the House of Representatives. | ELECTION STUDY NOTES - JAPAN (2017): E5027 | | The current elections were held ahead of time, on October 22, | 2017. The elections were due to be held in December 2018, that | is four years after the 2014 elections held on December 14, 2014. | However, due to the then-ongoing North Korea missile crisis, | Prime Minister Shinzo Abe called for an early general election. | The snap election was held on October 22, 2017. | ELECTION STUDY NOTES - THAILAND (2019): E5027 | | SEE ELECTION STUDY NOTES - THAILAND (2019): E5025 & E5026. | ELECTION STUDY NOTES - TUNISIA (2019): E5027 | | The parliamentary elections were held as scheduled. However, the | Presidential elections were originally scheduled to be held on | 17th and 24th of November 2019. However, due to the death of | President Beji Caid Essebsi on 25th July 2019, early | Presidential elections were scheduled for September 15th and | October 14th, 2019. | ELECTION STUDY NOTES - TURKEY (2018): E5027 | | This was an early election. The current parliamentary elections | were originally scheduled for November 3, 2019, as previous | parliamentary elections were held on November 1, 2015. However, | President Recep Tayyip Erdogan called a snap election in April | 2018, because of the passage of a series of constitutional | amendments confirmed in the 2017 referendum. | ELECTION STUDY NOTES - UNITED STATES (2020): E5027 | | In a series of Twitter contributions on July 30, 2020, President | Donald Trump (PARTY B) suggested that the election be delayed | due to controversial integrity concerns over states' adoption of | universal mail/absentee voting or mechanisms allowing citizens | to vote early in light of the COVID-19 pandemic. The suggestions | by President Trump were criticized by Democratic Party (PARTY A) | politicians. Leading members of the Republican Party (PARTY B) | rejected the idea, and the election was held as originally | scheduled on November 3, 2020 (although early voting/mail-in | voting started before this date). | | While states have the authority to determine the date of primary, | the Federal election date in the United States of America is | statutorily set by the Federal Government as "the Tuesday next | after the first Monday in the month of November", a law in place | since 1845. Article 2 of the United States Constitution empowers | the US Congress to choose the timing of the Federal election, | meaning the US President does not have the power to change | the election date without Congressional approval. | A change in the Federal Election date can only occur if the US | Congress (both House and Senate) enacts legislation to this | effect. Even if that were to occur, the US Constitution mandates | that a new Congress takes office on January 3 in the year after | the election, and that a new President's term must begin on | January 20 in the year following the election in accordance with | the 20th Amendment to the US Constitution. In sum, a change in | the Federal election date is possible, but only with | Congressional agreement, and even with that, US constitutional | provisions limit the scope for how long any delay could occur. | | Sources of data: | | BBC News "Donald Trump suggests delay to 2020 US Presidential | election" | https://www.bbc.com/news/world-us-canada-53597975 | (Date accessed: December 10, 2021). | | National Constitution Centre: | https://constitutioncenter.org/blog/does-the-constitution | -allow-for-a-delayed-presidential-election | (Date accessed: December 10, 2021). | | National Geographic: History and Culture | https://www.nationalgeographic.com/history/article/ | united-states-never-delayed-presidential-election-why-tricky | (Date accessed: December 10, 2021). --------------------------------------------------------------------------- E5028 >>> ELECTION VIOLENCE --------------------------------------------------------------------------- M09a. To what extent was there violence and voter or candidate intimidation during the election campaign and the election day? .................................................................. 1. NO VIOLENCE AT ALL 2. SPORADIC VIOLENCE ON THE PART OF THE GOVERNMENT 3. SPORADIC VIOLENCE ON THE PART OF OPPOSITION GROUPS 4. SPORADIC VIOLENCE ON ALL SIDES 5. SIGNIFICANT VIOLENCE ON THE PART OF THE GOVERNMENT 6. SIGNIFICANT VIOLENCE ON THE PART OF OPPOSITION GROUPS 7. SIGNIFICANT VIOLENCE OF ALL SIDES 9. MISSING | VARIABLE NOTES: E5028 | | Source of data: CSES Macro Report M9a. --------------------------------------------------------------------------- E5029 >>> GEOGRAPHIC CONCENTRATION OF VIOLENCE --------------------------------------------------------------------------- M09b. If there was violence, was it geographically concentrated or national? .................................................................. 1. NO ELECTION VIOLENCE 2. GEOGRAPHICALLY CONCENTRATED 3. NATIONAL 9. MISSING | VARIABLE NOTES: E5029 | | Source of data: CSES Macro Report M9b. | ELECTION STUDY NOTES - PERU (2021): E5029 | | The day after the second round of the Presidential election, | Fuerza Popular (PARTY B) alleged electoral "fraud" in rural | districts and that this had a material impact on the outcome of | the Presidential election. Defeated Presidential candidate Keiko | Fujimori called on their supporters to mobilize against the | result, seeing some protests, particularly in Lima, with crowds | protesting the election outcome. In response, supporters | of the winning candidate, Pedro Castillo, held counter | demonstrations asking for the result to be respected. | Protestors from both camps clashed with one another and had to | be separated by police. | The National Electoral Jury (Jurado Nacional del Eleccionnes, | JNE), the body overseeing the election, dismissed most of the | claims of electoral malfeasance. --------------------------------------------------------------------------- E5030 >>> POST-ELECTION VIOLENCE --------------------------------------------------------------------------- M09c. To what extent was there violence following the election? .................................................................. 1. NO VIOLENCE AT ALL 2. SPORADIC VIOLENCE ON THE PART OF THE GOVERNMENT 3. SPORADIC VIOLENCE ON THE PART OF OPPOSITION GROUPS 4. SPORADIC VIOLENCE ON ALL SIDES 5. SIGNIFICANT VIOLENCE ON THE PART OF THE GOVERNMENT 6. SIGNIFICANT VIOLENCE ON THE PART OF OPPOSITION GROUPS 7. SIGNIFICANT VIOLENCE OF ALL SIDES 9. MISSING | VARIABLE NOTES: E5030 | | Source of data: CSES Macro Report M9c. | ELECTION STUDY NOTES - UNITED STATES (2020): E5030 | | The sporadic violence did not take the form of the government | using state apparatus such as the army and the police. Instead, | the sporadic violence came principally from supporters of | President Trump, including from groups such as the Proud Boys, | a far-right organization. In November and December 2020, after | repeated allegations of electoral fraud and malpractice by | President Trump (PARTY B), there were clashes in the capital | city, Washington D.C., between Trump supporters and counter | -protesters. While charges of such electoral malpractice | have not been sustained either through investigations or court | challenges, violence culminated on January 6, 2021, in a rally | held and addressed by President Trump in Washington, D.C., to | coincide with the U.S. Congress' certification of the election | results. After President Trump's speech, some attendees at the | President's rally marched on the U.S. Capitol building, breaking | through law enforcement, occupying the building. The sittings of | both chambers were suspended as politicians and staff were | evacuated from the building. After several hours of a standoff, | where those occupying the building vandalized property and | attacked law enforcement, law enforcement regained control and | ejected protestors from the Capitol. Five people died either | shortly before, during, or following the event. Many protestors | and 138 police were injured. Incumbent President Donald Trump | was impeached by the US House of Representatives for a second | time over his role in the events of January 6, 2021, on January | 13, 2021, eight days before leaving office. He was acquitted | in a vote of the US Senate in February 2021, having left office | although a majority of lawmakers (57-43), including seven | Republicans (PARTY B), voted to convict the former President. For | a President to be impeached, two-thirds of the Senate must vote | to convict. | | Sources of data: | | Reuters: Four officers who responded to U.S. Capitol Attack have | died by suicide | https://www.reuters.com/world/us/officer-who-responded-us- | capitol-attack-is-third-die-by-suicide-2021-08-02/ | (Date accessed: February 03, 2022). | | National Public Radio (NPR): Read Trump's January 6 Speech, a Key | Part of the Impeachment Trial | https://www.npr.org/2021/02/10/966396848/read-trumps-jan-6- | speech-a-key-part-of-impeachment-trial?t=1643892201680 | (Date accessed: February 03, 2022). | | Washington Post: 41 minutes of fear: A video timeline from inside | the Capitol Siege | https://www.washingtonpost.com/investigations/2021/01/16/ | video-timeline-capitol-siege/ | (Date accessed: February 03, 2022). | | Time: Incited by the President, Pro-Trump Rioters Violently Storm | the Capitol | https://time.com/5926883/trump-supporters-storm-capitol/ | (Date accessed: February 03, 2022). --------------------------------------------------------------------------- E5031 >>> POST-ELECTION PROTEST --------------------------------------------------------------------------- M09d. To what extent was there protest following the election? .................................................................. 1. NO PROTEST AT ALL 2. SPORADIC PROTEST 3. SIGNIFICANT PROTEST 9. MISSING | VARIABLE NOTES: E5031 | | Source of data: CSES Macro Report M9d. | ELECTION STUDY NOTES - AUSTRIA (2017): E5031 | | On election day, a small protest (a few hundred participants) | took place in Vienna after the first predictions had been | published. It was directed against the Freedom Party's possible | participation in government and the rightward shift in general. | Further protests followed during and after the inauguration of | the new OVP-FPO government (in December 2017 and in January | 2018). | ELECTION STUDY NOTES - GERMANY (2021): E5031 | | While protests were not specifically directed at the election | outcome, protests related to the new government and its agenda | where held in the immediate months after the election. The first | set of protests was by climate activists, who demanded a stronger | commitment from the new government to fighting climate change, | with significant protests in October and November 2021. The | second set of protests focused on opposition to the ongoing | COVID-19 measures introduced by the government to control | spreading of the disease, with ire concentrated on suggestions | by protesters that mandatory vaccination could be introduced | by the government. | ELECTION STUDY NOTES - MONTENEGRO (2016): E5031 | | The opposition did not officially recognize the election results | and was not participating in the work of the National Parliament | at the time of writing the Macro Report. | ELECTION STUDY NOTES - PERU (2021): E5031 | | The day after the second round of the Presidential election, | Fuerza Popular (PARTY B) alleged electoral "fraud" in rural | districts and that this had a material impact on the outcome of | the Presidential election. Defeated Presidential candidate Keiko | Fujimori called on their supporters to mobilize against the | result, seeing some protests, particularly in Lima, with crowds | protesting the election outcome. In response, supporters | of the winning candidate, Pedro Castillo, held counter | demonstrations asking for the result to be respected. | Protestors from both camps clashed with one another and had to | be separated by police. | The National Electoral Jury (Jurado Nacional del Eleccionnes, | JNE), the body overseeing the election, dismissed most of the | claims of electoral malfeasance. | ELECTION STUDY NOTES - TURKEY (2018): E5031 | | Yet, before the official election results' declaration, in | certain public places, there were armed individuals who were | celebrating AKP's (Justice and Development Party, PARTY A) | unofficial election victory. | ELECTION STUDY NOTES - UNITED STATES (2016): E5031 | | Following Donald Trump's surprise victory, large protests broke | out across the United States and globally, which continued | sporadically until Trump became President in January 2017. | ELECTION STUDY NOTES - UNITED STATES (2020): E5031 | | SEE ELECTION STUDY NOTES - UNITED STATES (2020): E5030. --------------------------------------------------------------------------- E5032 >>> ELECTORAL ALLIANCES PERMITTED IN ELECTION --------------------------------------------------------------------------- Whether or not electoral alliances/coalitions are legally allowable. .................................................................. 1. YES 5. NO 9. MISSING | VARIABLE NOTES: E5032 | | E5032 details whether or not electoral alliances/coalitions | (involving joint lists/candidates) are legally allowable. | Definitions: A joint list refers to one on which candidates | of different parties run together. Apparentement refers to | a legal agreement between two or more lists to pool their | votes for the purposes of an initial seat allocation, with | seats initially allocated to the alliance then reallocated | to the lists in the alliance. | | Source of data: CSES Macro Report M10a. | ELECTION STUDY NOTES - AUSTRALIA (2019): E5032 | | While electoral alliances are not allowed to form for the | House of Representatives election (Lower House), they are | permitted for Senate (Upper House) election. The coding in | the data reflects the Lower House situation. | ELECTION STUDY NOTES - FRANCE (2017): E5032 | | Such alliances are not forbidden, but neither are they | explicitly allowed. | ELECTION STUDY NOTES - HONG KONG (2016): E5032 | | According to the Macro Report, there is no "law or regulation | that explicitly allows joint lists/election coalitions, but | Register maintained under section 20 of the Particulars | Relating to Candidates on Ballot Papers (Legislative Council | and District Councils) Regulation specifies that when a | candidate is endorsed by more than one party, the candidate's | name appears together with the names of all endorsing parties on | the ballot. Such a regulation implicitly recognizes that joint | list election coalitions are allowable." | ELECTION STUDY NOTES - NETHERLANDS (2017): E5032 | | Electoral alliances with joint lists are not forbidden, but | they are not used in practice. However, parties can (and do) | form a list combination ("lijstverbinding", or Appartement, | see ELECTION STUDY NOTES - NETHERLANDS (2017): E5036) before the | election. In the distribution of seats, these alliances are seen | as one party; only after the distribution of seats over parties | and alliances, the seats within the alliances are distributed. | It may give the alliance an extra remainder seat, but it does not | play a role in the electoral campaign. | ELECTION STUDY NOTES - NETHERLANDS (2021): E5032 | | Electoral alliances with joint lists are permissible but | they are not used in practice. | ELECTION STUDY NOTES - TURKEY (2018): E5032 | | According to an election alliance law approved in early 2018, | parties are given the ability to contest the election under | formal alliances as a means of jointly surpassing the | election threshold. --------------------------------------------------------------------------- E5033 >>> ELECTORAL ALLIANCES IN PRACTICE --------------------------------------------------------------------------- M10b. Is this type of electoral coalition used in practice, even if not legally allowable? .................................................................. 1. YES 5. NO 9. MISSING | VARIABLE NOTES: E5033 | | Source of data: CSES Macro Report M10b. | ELECTION STUDY NOTES - AUSTRIA (2017): E5033 | | Historically, this type of electoral coalition is not uncommon | in Austria, but it was not used this time. | ELECTION STUDY NOTES - FRANCE (2017): E5033 | | Such alliances are not forbidden, but neither are they explicitly | allowed. | ELECTION STUDY NOTES - GREAT BRITAIN (2017 & 2019): E5033 | | Collaborator advises while these alliances occur in practice, | they are relatively low salience - for example, Labor candidates | often running as Labor and Co-Operative Party candidates, but | this is not something which gets a lot of attention among voters. | ELECTION STUDY NOTES - NETHERLANDS (2017): E5033 | | SEE ELECTION STUDY NOTES - NETHERLANDS (2017): E5032. | ELECTION STUDY NOTES - NETHERLANDS (2021): E5033 | | SEE ELECTION STUDY NOTES - NETHERLANDS (2021): E5032. | ELECTION STUDY NOTES - TAIWAN (2020): E5033 | | Historically, this type of electoral coalition is not uncommon | in Taiwan, but it was not used this time. --------------------------------------------------------------------------- E5034 >>> DID ANY ELECTORAL ALLIANCES FORM? --------------------------------------------------------------------------- M10c. (If yes to M10a or M10b) Did any electoral alliances form? .................................................................. 1. YES [SEE CODEBOOK PART 3 FOR DETAILS OF ALLIANCES] 5. NO 7. NOT APPLICABLE [NO ALLIANCES PERMITTED] 9. MISSING | VARIABLE NOTES: E5034 | | Source of data: CSES Macro Report M10c. | | Details of alliances and parties/coalitions, and their numerical | and alphabetical classifications for each election study are | detailed in Part 3 of the CSES Codebook. --------------------------------------------------------------------------- E5035 >>> REQUIREMENTS FOR JOINT PARTY LISTS --------------------------------------------------------------------------- Whether or not joint lists are subject to different regulations than single-party lists. .................................................................. 1. YES, JOINT PARTY LISTS MUST SATISFY HIGHER THRESHOLDS 2. YES, JOINT PARTY LISTS MAY PRESENT DIFFERENT NUMBERS OF CANDIDATES 3. YES, JOINT PARTY LISTS ARE SUBJECT TO OTHER REGULATIONS THAT ARE DIFFERENT FROM THE REGULATIONS GOVERNING INDEPENDENT PARTIES 5. NO, JOINT PARTIES ARE GOVERNED BY THE SAME RULES AS OTHER PARTIES 7. NOT APPLICABLE; NO JOINT PARTY LISTS ARE ALLOWED 9. MISSING | VARIABLE NOTES: E5035 | | E5035 details whether joint lists - if permissible - are subject | to different regulations than single-party lists (e.g. in terms | of higher thresholds, different numbers of candidates that may | appear on the list, etc.). | | Source of data: CSES Macro Report M11. | | Please also refer to VARIABLE NOTES for variables E5031-E5033. | ELECTION STUDY NOTES - BRAZIL (2018): E5035 | | This applies to lower house elections. Joint party lists may | present a different number of candidates in the following | circumstances: | - When district magnitude >=20: a political party can present | up to 1.5 candidates for each seat. When there is a joint | list a political party can present up to 2 candidates for | each seat. | - When district magnitude <20: a political party can present | up to 2 candidates for each seat. When there is a joint | list a political party can present up to 2.5 candidates for | each seat. | ELECTION STUDY NOTES - GREECE (2015 & 2019): E5035 | | "2.a. The independent Party that came first in valid votes in | the electoral District of Greece, besides the seats that are | allocated to it according to paragraph 1, gains fifty (50) more | seats, which are derived from the electoral peripheries that | have seats not allocated after the conclusion of the procedure | in accordance with the provisions of article 6. | These extra fifty (50) seats could be also gained by a party | coalition, under the condition that the average of the | percentages that the Parties of the coalition gained is higher | than the percentage of the independent Party that came first in | valid votes. This average is obtained by the division of the | percentage that the fore mentioned party coalition gained | divided by the number of Parties that it consists of." [Excerpt | from Law 3636/2008: Article 1, Paragraph 2a (Amendment of Law | 3231/2004 "Election of the Members of the Parliament").] | | This means that if a party coalition gets the relative | majority but its average power is less than the power of the | independent party that gets the higher percentage among the | independent parties, the extra fifty seats are gained by this | independent party. | ELECTION STUDY NOTES - ITALY (2018): E5035 | | In the proportional component of both Houses of the Parliament | (second segments), thresholds for obtaining seats are 3% for | parties running alone, 10% for coalitions, and 1% for parties | within coalitions. | ELECTION STUDY NOTES - NETHERLANDS (2017): E5035 | | Number of candidates may be higher than the number on the | list of separate parties (depends on previous election results). | ELECTION STUDY NOTES - ROMANIA (2016): E5035 | | This applies to both the Chamber of Deputies and the | Senate elections. The threshold for political parties if | 5% of the valid votes. An electoral alliance of two parties | however, is subject to a threshold of 8% of the valid votes. | A three-party alliance is subject to a 9% threshold of valid | votes while alliances comprising four parties or more are | required to reach 10% of the valid votes. --------------------------------------------------------------------------- E5036 >>> THE POSSIBILITY OF APPARENTEMENT --------------------------------------------------------------------------- M12a. Is there apparentement or linking of lists? .................................................................. 1. YES 5. NO 9. MISSING | VARIABLE NOTES: E5036 | | Source of data: CSES Macro Report M12a. | ELECTION STUDY NOTES - NETHERLANDS (2017): E5036 | | Dutch political parties can (and do) form a list combination | ("lijstverbinding", or Appartement before the election. In the | distribution of seats, these alliances are seen as one party; | only after the distribution of seats over parties and | alliances, the seats within the alliances are distributed. It | may give the alliance an extra remainder seat, but it does not | play a role in the electoral campaign. | ELECTION STUDY NOTES - NETHERLANDS (2021): E5036 | | Previously, Dutch political parties could form a list combination | ("lijstverbinding", or Appartement before the election), where | in the distribution of seats, these alliances would be considered | as one party. However, this procedure was abolished in December | 2017. | ELECTION STUDY NOTES - URUGUAY (2019): E5036 | | Apparentement exists approximately. Namely, the Multiple | Simultaneous Vote (MVS) can be seen as the inverse of | apparentement, in which votes are cast by lists, which are | added by the effect of apparentement. --------------------------------------------------------------------------- E5037 >>> TYPES OF APPARENTEMENT AGREEMENTS --------------------------------------------------------------------------- M12b. If apparentement is possible, what lists can participate in such agreements? .................................................................. 1. LISTS OF THE SAME PARTY IN THE SAME CONSTITUENCY 2. LISTS OF THE SAME PARTY FROM DIFFERENT CONSTITUENCIES 3. LISTS OF DIFFERENT PARTIES IN THE SAME CONSTITUENCY 7. NOT APPLICABLE; NO APPARENTEMENT 9. MISSING | VARIABLE NOTES: E5037 | | Source of data: CSES Macro Report M12b. | | Please also refer to VARIABLE NOTES for variable E5035. | ELECTION STUDY NOTES - CHILE (2017): E5037 | | According to the Macro Report, "Apparentments are nationwide. | So, the parties that form an apparentement are part of the | same list in all districts." | ELECTION STUDY NOTES - NETHERLANDS (2017): E5037 | | SEE ELECTION STUDY NOTES - NETHERLANDS (2017): E5036. | ELECTION STUDY NOTES - SWEDEN (2018): E5037 | | In Sweden, it is also possible that lists of different parties | (code 3) can participate in an apparentement. | ELECTION STUDY NOTES - URUGUAY (2019): E5037 | | SEE ELECTION STUDY NOTES - URUGUAY (2019): E5036. --------------------------------------------------------------------------- E5038 >>> MULTI-PARTY ENDORSEMENTS --------------------------------------------------------------------------- M13a. Can candidates run with the endorsement of more than one party? .................................................................. 1. YES 5. NO 7. NOT APPLICABLE 9. MISSING | VARIABLE NOTES: E5038 | | Source of data: CSES Macro Report M13a. | ELECTION STUDY NOTES - EL SALVADOR (2019): E5038 | | In Presidential elections, candidates can be supported by | multi-party coalitions as well as individual parties. In | parliamentary elections, electoral lists can be submitted by | individual parties as well as by coalitions. | ELECTION STUDY NOTES - LITHUANIA (2016 & 2020): E5038 | | Voters vote for party lists, not directly for candidates. | Names of the official lists may but do not have to mention | any party names. | ELECTION STUDY NOTES - MONTENEGRO (2016): E5038 | | In Montenegrin parliamentary elections, voters vote for (closed) | party lists, not directly for candidates. Names of the official | lists may but do not have to mention any party names. --------------------------------------------------------------------------- E5039 >>> MULTI-PARTY ENDORSEMENTS ON BALLOT --------------------------------------------------------------------------- M13b. If candidates can run with the endorsement of more than one party, is this reflected on the ballot? .................................................................. 1. NO 2. NO PARTY ENDORSEMENTS ARE INDICATED ON THE BALLOT PAPER 3. YES, CANDIDATE'S NAME APPEARS ONCE, TOGETHER WITH THE NAMES OF ALL SUPPORTING PARTIES 4. YES, CANDIDATE'S NAME APPEARS AS MANY TIMES AS THERE ARE DIFFERENT PARTIES ENDORSING HIM/HER, EACH TIME WITH THE NAME OF THE ENDORSING PARTY 5. YES, OTHER [SEE ELECTION STUDY NOTES] 7. NOT APPLICABLE 9. MISSING | VARIABLE NOTES: E5039 | | Source of data: CSES Macro Report M13b. | | Please also refer to VARIABLE NOTES for variable E5037. | ELECTION STUDY NOTES - EL SALVADOR (2019): E5039 | | In parliamentary elections, open electoral lists can be | submitted by individual parties as well as by coalitions. | Coalitions are usually represented by party logos of all | parties constituting a coalition. | ELECTION STUDY NOTES - LITHUANIA (2016 & 2020): E5039 | | Voters vote for party lists, not directly for candidates. | Names of the official lists may but do not have to mention | any party names. | ELECTION STUDY NOTES - MONTENEGRO (2016): E5039 | | In Montenegrin parliamentary elections, voters vote for (closed) | party lists, not directly for candidates. Names of the official | lists may but do not have to mention any party names. Hence, | this variable is coded: 7. NOT APPLICABLE. | ELECTION STUDY NOTES - NEW ZEALAND (2017 & 2020): E5039 | | A candidate standing in tier 1 ("constituency vote") may have | an endorsement from another party, but it is usually tacit | rather than direct and usually the main party of the candidate | is the one that appears on the ballot paper. | ELECTION STUDY NOTES - UNITED STATES (2016 & 2020): E5039 | | Nearly all of these options are possible in the United States | with the rules varying by state. --------------------------------------------------------------------------- E5040_1 >>> VOTES CAST - LOWER - 1ST SEGMENT (TIER) E5040_2 >>> VOTES CAST - LOWER - 2ND SEGMENT (TIER) E5040_3 >>> VOTES CAST - UPPER - 1ST SEGMENT (TIER) E5040_4 >>> VOTES CAST - UPPER - 2ND SEGMENT (TIER) --------------------------------------------------------------------------- M15a. How many votes do voters cast or can cast? .................................................................. 01-90. NUMBER OF VOTES 91. OTHER [SEE ELECTION STUDY NOTES] 97. NOT APPLICABLE 99. MISSING | VARIABLE NOTES: E5040_ | | Source of data: CSES Macro Report M15a. | ELECTION STUDY NOTES - AUSTRALIA (2019): E5040_1 | | For lower house elections, Australia employs the Alternative Vote | (AV) system. In this system, voters are required to list their | preferences for as many candidates as there are on the ballot. | Thus, the total number of votes varies across electoral | districts. | ELECTION STUDY NOTES - AUSTRALIA (2019): E5040_3 | | For upper house elections, Australia employs a single- | transferable-vote (STV) form of proportional representation. In | this system, each voter indicates the order of preference among | all the candidates competing in her district, or alternatively, | she can indicate support for a party ticket (which determines | the order of preference of candidates within the party). | ELECTION STUDY NOTES - AUSTRIA (2017): E5040_1 | | The Austrian electoral system is a proportional representation | system with three segments or tiers. These correspond to the | regional districts tier, the Land level tier (or state level) | and the federal (or national) level tier. Counting and | allocation of seats passes through each of these levels. | However, voters cast a single vote. In this vote, they can | express preferences for specific candidates. | However, since voters cast a single vote only, this system is | different from systems with multiple tiers where voters vote | separately in different tiers. Hence, the system is coded as | consisting of a single tier in variables E5040-E5049. | ELECTION STUDY NOTES - BRAZIL (2018): E5040_3 | | Members of the Brazilian Senate (Senado Federal) are elected for | an 8-years term, and the chamber is composed of 81 members, with | each state in Brazil having three Senators each. | Members are elected in alternative electoral cycles: two thirds | of the Senate seats (n=54) are contested in one election cycle | while the remaining one-third are contested in the other. The | 2018 elections saw two-thirds of the Senate seats contested | (n=54). Accordingly, voters had two votes in this election, as | two Senators per State were being selected. | ELECTION STUDY NOTES - COSTA RICA (2018): E5040_1 | | For parliamentary elections, Costa Rica uses proportional, | closed party-list system. The 57 members of the Legislative | Assembly are elected by the largest remainder method from | seven multi-member constituencies, each of which contains between | four and 19 seats. | Parties that reach a quotient are entitled to receive seats. | Seats remaining unfilled by the quotient system are distributed | among parties in descending order of their residual votes; | parties that did not attain the sub-quotient are also taken into | account, their votes being treated as residual votes. | The quotient is the number obtained by dividing the total of | valid votes cast in a particular province by the number of seats | to be filled in the same province; the sub-quotient is the total | of valid votes cast for a party which, while not attaining the | quotient, obtains or exceeds 50% of it. | Voting is compulsory. Party lists were required to alternate | between male and female candidates, with parties also required | to have three or four of their seven regional lists headed by | a female candidate. | ELECTION STUDY NOTES - CZECHIA (2017 & 2021): E5040_3 | | Senate (the upper chamber of the Parliament of the Czechia) | consists of 81 directly elected members. Senators are | elected for a term of 6 years, while one-third of the Chamber is | renewed every two years. Elections are based on 81 single-member | constituencies, using a two-round majoritarian system. | ELECTION STUDY NOTES - DENMARK (2019): E5040_1 & E5040_2 | | The Danish Folketing has 179 members, 175 of which are elected | in mainland Denmark and the remaining four from the territories | of Greenland and the Faroe Islands. In mainland Denmark, 135 | members are elected from 10 multi-member constituencies across | three geographical regions, namely: Copenhagen, Northern Jutland, | and Seeland-Southern Denmark. Additionally, 40 supplementary | seats are distributed across these three geographical regions in | order to achieve full proportionality. While voters do not cast | a ballot directly for this tier, it is widely acknowledged to | constitute a separate tier of the electoral system. | ELECTION STUDY NOTES - EL SALVADOR (2019): E5040_1 | | For parliamentary elections, El Salvador uses proportional, open | party-list system. The 84 members of the Legislative Assembly are | elected by the largest remainder method from fourteen multi- | member constituencies. | Parties that reach a quotient are entitled to receive seats. | Seats remaining unfilled by the quotient system are distributed | among parties in descending order of their residual votes. The | quotient is the number obtained by dividing the total of valid | votes cast in a particular province by the number of seats to be | filled in the same province. | ELECTION STUDY NOTES - GERMANY (2017 & 2021): E5040_1 & E5040_2 | | In elections in Germany, each voter has two votes, one in each | segment: One vote ("first vote") for an individual candidate in | one of the electoral constituencies (tier 1), and another vote | ("second vote") for a regional party-list, based on the 16 states | (Laender), drawn up by each political party (tier 2). | ELECTION STUDY NOTES - GREECE (2015 & 2019): E5040_1 | | In the Greek electoral system, representatives are elected | according to three methods of counting votes. First, 250 | representatives are elected proportionally in 56 (59 in 2019 | election) constituencies. | Next, up to 1/20 of the Parliament (currently 12) may be | elected not in a specified constituency but throughout the | country at large. These are the State Deputies, whose exact | number depends on the total electoral strength of each party. | Finally, there are 50 'bonus' seats awarded to the party | receiving the largest share of the vote. | However, since voters cast a single vote only, this system is | different from systems with multiple tiers where voters vote | separately in different tiers. Hence, the system is coded as | consisting of a single tier in variables E5040-E5049. | ELECTION STUDY NOTES - HONG KONG (2016): E5040_1 & E5040_2 | | Hong Kong has a unicameral legislature. The Legislative Council | of the HKSAR has 70 members. Half of the legislative council is | returned by geographic constituency (popular) elections; the | other half is returned by functional constituency elections. | Election data on Hong Kong electoral institutions refer to the | geographical constituency elections only. | In the Geographical Constituency (GC) part of the Election, Hong | Kong is divided into five constituencies, and voters elect | candidates by universal suffrage. The number of LegCo seats in | each constituency is decided according to the constituency | population. The voting system adopted is the closed list | proportional representation system. Geographical Constituency is | treated here as the first segment of the LegCo. | There are two parts of the Functional Constituencies (FCs): the | traditional FCs and the District Council (Second) FC. | The traditional FCs return 30 LegCo members. Registration as a | voter in some traditional FCs requires certain qualifications, | for example, registered medical practitioners or dentists for | the Medical FC. Note that in some FCs, voters are individuals, | while in others, 'voters' are not individuals but companies or | organizations. | The District Council (Second) FC is treated here as the second | segment of the LegCo. This segment returns 5 LegCo members. In | this part of the election, the whole of Hong Kong has one | constituency only, and the voting system adopted is the closed | list proportional representation system. Candidates must be | elected District Council members who are nominated by no less | than 15 other elected District Council members; whereas voters | are registered GC electors who are not registered in other FCs. | ELECTION STUDY NOTES - HUNGARY (2018): E5040_1 & E5040_2 | | In elections in Hungary, each voter has two votes, one in each | segment: One vote for an individual candidate in one of the | electoral constituencies (tier 1, 106 single-member | constituencies), and another vote (party list vote) for a | national party-list (tier 2). | ELECTION STUDY NOTES - ICELAND (2016 & 2017): E5040_2 | | There is a second tier where 9 (out of 63) so-called | "supplementary" seats are allocated to party lists receiving | at least 5% of the valid vote. However, voters cast only a | single vote, and voters do not directly cast a vote for | this tier. Hence, this variable is coded "97. NOT APPLICABLE". | ELECTION STUDY NOTES - IRELAND (2011): E5040_1 | | Voters have one ballot but can cast as many votes (first | preference and subsequent lower preferences) as there are | candidates running for election. However, a voter is only | required to express a first preference vote for the vote to be | valid with lower preferences optional. | ELECTION STUDY NOTES - ITALY (2018): E5040 | | Voters could make a sign (1) on the district candidate's name, | (2) on a party list supporting a district candidate, (3) on both | the candidate's name and the party list supporting the | candidate. Thus, voters have a vote for both electoral segments | (district candidates and party lists). | However, it is important to note that split ballots are not | allowed, which makes the voting system nearly identical as if | voters had a single vote. | Voters residing abroad (3rd segment) vote only for the lists. | The same rules apply to both Chambers of the Italian Parliament. | ELECTION STUDY NOTES - JAPAN (2017): E5040 | | Kokkai (National Diet) is a Japanese bicameral parliament. Lower | house is Sangiin (House of Councilors), while the Upper house | is Shugiin (House of Representatives). | The Lower house (465 directly elected members) consists of two | segments - majoritarian and proportional. The first segment | consists of 289 single-member constituencies, elected via simple | majority voting system. The second segment (proportional) is | based on 11 multi-member (6 to 28 seats) constituencies, in total | giving 176 seats (party list system, using the d'Hondt method | for the allocation of the seats. | The Upper House has 242 members. The first segment is | represented by 45 multi-member constituencies (between two and | 12 seats each) for a total of 146 seats (43 formed on a | metropolitan or prefectural basis; and two other constituencies | covering two prefectures each). Successful candidates are | decided in the order of the number of valid votes obtained on | the basis of the comparative plurality. | The second segment is represented by one national constituency | for the remaining 96 seats, elected on the basis of party list | proportional system. At each election, half of the Upper house | is renewed. | ELECTION STUDY NOTES - LITHUANIA (2016 & 2020): E5040_1 & E5040_2 | | In elections in Lithuania, each voter votes in two segments. | In the first segment, voters vote for an individual candidate | in one of 71 single-member constituencies. In the second | segment, voters vote for a national party list in a nationwide | multi-member constituency (70 seats). | In the proportional representation tier, voters can cast one | vote for a party list, and they have five preferential votes for | the candidates of the party they have voted for. Hence, for the | second segment, this variable was coded 5. | ELECTION STUDY NOTES - MEXICO (2018): E5040_1 & E5040_2 | | Mexican voters cast a single vote in a single-member district | plurality election. However, this also counts for the allocation | of the proportional representation seats disputed in the larger | regional multi-member districts (five circumscriptions). Thus, | voters are not allowed to split their vote; in fact, the same | vote is subject to a double counting that produces two-seat | relevant vote totals. The first vote total determines who wins | the plurality in the single-member district (300 seats). The | second serves to allocate seats in the multi-member districts | (200 seats). The PR seats are allocated according to the | aggregate distribution of votes of multi-member districts. | For a party to be entitled to have members of proportional | representation in the Lower Chamber, it must attain at least | 3 percent of the total valid votes cast for these elections. | ELECTION STUDY NOTES - MEXICO (2018): E5040_3 & E5040_4 | | For senatorial (Upper House) elections, voters cast a single | vote in 3-seat multi-member districts (which correspond to the | country's 31 states plus the Federal District). The first two | seats are awarded to the plurality winner, and the third seat is | given to the first runner-up. This vote also counts for the | allocation of proportional representation seats disputed in one | national district. Thus, each vote is subject to a double | counting that produces two-seat relevant vote totals. The first | vote total determines who wins the in the multi-member districts | (96 seats), the second serves to allocate through proportional | representation the remaining 32 seats. For the allocation of the | PR seats the national distribution of votes excludes nonvalid | votes, votes for parties that obtained less than 3% and votes | for non-registered candidates. | ELECTION STUDY NOTES - NEW ZEALAND (2017): E5040_1 & E5040_2 | | In elections in New Zealand, each voter has two votes, | one in each segment: One vote ("first vote") for an individual | candidate in one of the electoral constituencies (tier 1), | and another vote ("second vote") for a national party-list | drawn up by each political party (tier 2). | ELECTION STUDY NOTES - NEW ZEALAND (2020): E5040_1 & E5040_2 | | In elections in New Zealand, each voter has two votes, | one in each segment: One vote ("first vote") for an individual | candidate in one of the electoral constituencies (tier 1), | and another vote ("second vote") for a national party-list | drawn up by each political party (tier 2). | ELECTION STUDY NOTES - NORWAY (2017): E5040_2 | | The Norwegian Parliament comprises 169 seats in two tiers: | 150 members are elected in 19 multi-member districts using | proportional representation. The remaining 19 seats are | compensatory and are allocated to parties that receive 4%+ of | the national vote. These seats are known as "members at large" | and are seen as a means of evening out discrepancies between | the number of votes received and the number of seats in the | Storting. The distribution is based on a comparison of the | actual distribution of seats with what would have been occurred | had the country been treated as on big constituency, thus | allowing a determination to be made as to which parties are | under-represented. These parties are then awarded "seats at | large" in the constituencies where they were closest to winning | an ordinary seat. While voters do not cast a ballot directly for | this tier and the seats are awarded at the national level | (albeit dispersed at the constituency level), it is widely | acknowledged to constitute a separate tier of the electoral | system. | For more, see: | https://www.stortinget.no/en/In-English/About-the-Storting/ | Elections/ | (Date accessed: March 23, 2020). | ELECTION STUDY NOTES - ROMANIA (2016): E5040 | | According to the new electoral law (passed in 2015), both | chambers use a proportional representation system, with mostly | similar regulations. | ELECTION STUDY NOTES - SOUTH KOREA (2016): E5040_1 & E5040_2 | | Korea employs a mixed-member majoritarian system that combines | 253 single-member districts (SMD) with 47 proportional | representation (PR) seats, elected from a single nationwide | district. Each voter casts two votes, one for an individual | candidate in the SMD segment, and one for a closed party list | in the PR segment. | ELECTION STUDY NOTES - SWEDEN (2018): E5040_1 & E5040_2 | | The Swedish Riksdag has 349 members, where 310 members are | elected from 29 multi-member constituencies. Additionally, | 39 supplementary seats are distributed in order to achieve full | proportionality which are equivalent to a second tier. While | voters do not cast a ballot directly for this tier, it is widely | acknowledged to constitute a separate tier of the electoral | system. | ELECTION STUDY NOTES - SWITZERLAND (2019): E5040_1 | | In Switzerland, voters have as many votes as the number of seats | in their district (between 1 and 35, depending on the cantons). | Voters can choose one of the parties on the party lists, or they | can create their own list by filling an empty list on the ballot | with the candidates they prefer. Moreover, they can modify the | party (e.g., add candidates from other parties instead of a | candidates of the list [panachage]), delete candidates or vote | twice for the same candidate (cumulation). | If a voter casts fewer votes than seats in the district, the | remaining votes go to the party indicated on the list. If | no party is indicated, the remaining votes are lost. Since all | candidates belong to a party, if a voter casts a single vote for | a candidate, that vote automatically counts for that candidate's | party list. | ELECTION STUDY NOTES - SWITZERLAND (2019): E5040_3 | | In 20 cantons of Switzerland, voters have two votes, while in the | six so-called half-cantons (BL, BS, OW, NW, AI, AR) voters have | one vote. The number of votes is equal to the number of seats | elected in a particular canton (or half canton). | ELECTION STUDY NOTES - TAIWAN (2016): E5040_1 & E5040_2 | | Taiwan uses a mixed-member majoritarian (MMM) system, and the | total number of seats is 113. The seats are distributed via two | segments (tiers). The first segment is represented by 73 seats, | elected in single-member districts (SMD). The second segment is | a nationwide district employing a proportional representation | system. In addition, six seats are reserved for aboriginal | groups. These seats are elected using the same system as the | first segment (SMD). | ELECTION STUDY NOTES - TAIWAN (2020): E5040_1 & E5040_2 | | Taiwan uses a mixed-member majoritarian (MMM) system, and the | total number of seats is 113. The seats are distributed via two | segments (tiers). The first segment is represented by 73 seats, | elected in single-member districts (SMD). The second segment is | a nationwide district employing a proportional representation | system. In addition, six seats reserved for aboriginal groups. | These seats are elected using the same system as the first | segment (SMD). | ELECTION STUDY NOTES - THAILAND (2019): E5040_1 & E5040_2 | | Thailand has a bicameral National Assembly (Rathasapha) | consisting of the Senate (Wuthisapha) with 250 seats and the | House of Representatives (Sapha Phuthael Ratsadon) with 500 | seats. In the House of Representatives (Sapha Phuthaen | Ratsadon), 350 members are elected by plurality vote in single- | member constituencies (1st segment) and 150 members are elected | through a closed-list proportional representation system (2nd | segment) to serve 4-year terms. | According to the 2017 Constitution, the Lower House uses a new | mixed member apportionment electoral system. Despite there being | two separate types of seats to fill in this new system, voters | make only one "fused" choice on the ballot. A voter's mark on | the ballot will now indicate their choice of a constituency | representative and their choice of a political party as the | basis for the distribution of the 150 party list seats. These | decisions were separate under Thailand's previous mixed system. | Distributions of the party list seats are now determined by each | party's share of the popular fused vote. The number of single- | member seats won are subtracted from the share of all 500 seats | a party would receive based on the popular vote. The remainder | is roughly the number of PR seats awarded to that party. | ELECTION STUDY NOTES - THAILAND (2019): E5040_3 & E5040_4 | | In 2019, Thailand had a Senate (Upper House) not elected | directly by the people. According to the 2017 post-coup d'etat | law, for its first five years, the Senate is composed of 250 | appointees, instead of 200 appointees for the period beyond. | While six seats are reserved for commanders of the armed forces, | the police, and the Defense secretary, the remaining 244 are | selected by the National Council for Peace and Order (NCPO) | through two different processes. Fifty Senators represent 10 | economic and social groups, and are selected by the NCPO after | an initial screening by the Election Commission of Thailand | (ECT), while the remaining 194 are nominated by the NCPO itself, | through an ad hoc screening committee. Senate nominees are | ultimately endorsed by the King. | Since the Senate is not directly elected, but at the time of | this election, appointed by the military, variables E5040-E5049 | referring to the Upper House are all coded Not Applicable. --------------------------------------------------------------------------- E5041_1 >>> VOTING PROCEDURE - LOWER - 1ST SEGMENT (TIER) E5041_2 >>> VOTING PROCEDURE - LOWER - 2ND SEGMENT (TIER) E5041_3 >>> VOTING PROCEDURE - UPPER - 1ST SEGMENT (TIER) E5041_4 >>> VOTING PROCEDURE - UPPER - 2ND SEGMENT (TIER) --------------------------------------------------------------------------- M15b. Do they vote for candidates (not party lists) or party lists? .................................................................. 1. CANDIDATES 2. PARTY LISTS 3. PARTY BLOC VOTING 4. OTHER [SEE ELECTION STUDY NOTES] 7. NOT APPLICABLE 9. MISSING | VARIABLE NOTES: E5041_ | | Definition: Party bloc voting is used in multi-member districts | where voters cast a single party-centered vote for their party | of choice; the party with the most votes wins all of the | district seats. | | Source of data: CSES Macro Report M15b. | ELECTION STUDY NOTES - AUSTRALIA (2019): E5041_1 | | Voting is by the full preferential system (also known as | instant-runoff system), where voters rank the candidates | in order of preference rather than vote for a single candidate. | ELECTION STUDY NOTES - AUSTRALIA (2019): E5041_3 | | Senators are popularly elected under a single transferable | vote system, where voters have as many votes as there are | candidates in a district. voters can also vote for an | individual party ('group voting ticket'). | ELECTION STUDY NOTES - AUSTRIA (2017): E5041_1 | | The Austrian electoral system is a proportional representation | system with three segments or tiers. These correspond to the | regional districts tier, the Land level tier (or state level) | and the federal (or national) level tier. Counting and | allocation of seats passes through each of these levels. | Voters can cast a (single) party vote on an open list and | indicate their preferred candidate on the respective party list. | Also SEE ELECTION STUDY NOTES - AUSTRIA (2017): E5040. | ELECTION STUDY NOTES - BRAZIL (2018): E5041_1 | | For the Federal deputy election, each political party presents | a list of candidates. Voters can vote for a candidate or | they can vote for a party. | ELECTION STUDY NOTES - DENMARK (2019): E5041_1 | | Voters can choose to endorse a party, a candidate on a party | list, or an independent candidate. Parties can choose to have | either an open or a party-ranked list of candidates. If the | list is open, votes that are cast for the party (the voter has | not given a personal vote) are distributed between the candidates | based on the number of personal votes. If the list is party- | ranked, a vote cast for the party will be given to the candidate | listed first on the list until he or she has received enough | votes to be elected, and so on. | ELECTION STUDY NOTES - FINLAND (2019): E5041_1 | | Electoral system in Finland is based on open lists, where the | votes for candidates per party list in each constituency form | the basis for seat allocation. Each voter must choose a | candidate; it is not possible to vote for a party as such. | The method for seat allocation is PR/d'Hondt within each | constituency. | ELECTION STUDY NOTES - HONG KONG (2016): E5041_1 & E5041_2 | | Both in the Geographical Constituency (GC) and in the | District Council (Second) Functional Constituency, voters vote | for closed party lists. | ELECTION STUDY NOTES - HUNGARY (2018): E5041_1 & E5041_2 | | In the first segment (candidate vote), voters vote for | candidates. In the second segment (party list vote), | voters vote for closed party lists. | ELECTION STUDY NOTES - ICELAND (2016 & 2017): E5041_2 | | There is a second tier where 9 (out of 63) so-called | "supplementary" seats are allocated to party lists receiving | at least 5% of the valid vote. However, voters cast only a | single vote, and voters do not directly cast a vote for | this tier. Hence, this variable is coded "7. NOT APPLICABLE". | ELECTION STUDY NOTES - INDIA (2019): E5041 | | The "None of the Above (NOTA)" option is available on | all ballots. This means that voters can explicitly express their | lack of support for any of the listed candidates. | ELECTION STUDY NOTES - JAPAN (2017): E5041_1 | | First segments of each house are based on votes for candidates. | The second segment of each house is based on party list votes. | Also SEE ELECTION STUDY NOTES - JAPAN (2017): E5040. | ELECTION STUDY NOTES - LATVIA (2018): E5041_1 | | The 100 members of the Saeima (Latvian single chamber | Parliament) are elected by open list proportional representation | from five multi-member constituencies (Kurzeme, Latgale, Riga | (in which overseas votes are counted), Vidzeme and Zemgale) | between 13 and 32 seats in size. Seats are allocated using the | Sainte-Lague method with a national electoral threshold of 5%. | Electors vote for lists of candidates but can also indicate | specific support or rejection. | ELECTION STUDY NOTES - LITHUANIA (2016 & 2020): E5041_1 & E5041_2 | | In the first segment (candidate vote), voters vote for | candidates. In the second segment (party list vote), voters vote | for open party lists. | ELECTION STUDY NOTES - MEXICO (2018): E5041_1 & E5041_2 | | In Mexico, each voter's vote is counted twice; once for the | single member district contest, and a second time for the | regional PR contest (SEE ELECTION STUDY NOTES - MEXICO (2018): | E5040_1 & E5040_2 for details). | Accordingly, the voting procedure is coded as voting for | candidates and for a party list for each respective contest. | ELECTION STUDY NOTES - MEXICO (2018): E5041_3 & E5041_4 | | In Mexico, each voter's vote for choosing senators is counted | twice; once for the 3-seat multi-member districts contest, and a | second time for the national PR contest (SEE ELECTION STUDY | NOTES - MEXICO (2018): E5040_3 & E5040_4 for details). | Accordingly, the voting procedure is coded as voting for | candidates and for a party list for each respective contest. | ELECTION STUDY NOTES - NETHERLANDS (2017 & 2021): E5041_1 | | The Netherlands uses a multi-member candidate PR-list system with | voters presented with a list of candidates on the ballot, with | the name of the party/list placed above the list of candidates. | Consequently, the one vote cast by citizens is one for a | list and candidate simultaneously (sometimes referred to as a | matrix vote). Conventionally, most people vote for the list's | leading candidate, implicitly suggesting they have no particular | preference for a candidate on the list, or indicating they favor | the party's top list candidate. That said, some voters cast a | preference vote (voorkeurstem) in support of a particular | candidate. Candidates receiving 25 percent of the quota can take | priority on a party list. | ELECTION STUDY NOTES - NORWAY (2017): E5041_2 | | Voters in Norway cast only one single ballot in the election on | the basis of party lists. This vote directly impacts the | selection of the 150 members elected in the 19 multi-member | districts using proportional representation. However, the ballot | also influences the dispersion of the 19 "member at large seats" | (for more SEE ELECTION STUDY NOTES - NORWAY (2017): E5040_2). | As such, when voters are casting their ballot for party lists, | they are also casting a ballot, albeit indirectly for the | allocation of the "member at large seats". Accordingly, we code | this as "2. PARTY LISTS". | ELECTION STUDY NOTES - SLOVAKIA (2020): E5041_1 | | Slovak voters can vote for party lists of political parties and | every voter has got four preferential votes; they are counted if | they reach 3% of all votes for the party. | ELECTION STUDY NOTES - SOUTH KOREA (2016): E5041_1 & E5041_2 | | Korean voters have two votes - one vote in the 253 single member | constituencies and one on a single nationwide proportional | district. | ELECTION STUDY NOTES - SWITZERLAND (2019): E5041_1 | | An empty ballot paper has a line for the party/list name on top | and then as many lines as there are seats in a canton which can | be filled with candidates' names. Instead of an empty ballot | paper, voters can also use one of the pre-printed ballot papers | that already contains the list name and all the candidates of | this list/party. There are, however, differences across the | cantons. | ELECTION STUDY NOTES - SWITZERLAND (2019): E5041_3 | | Cantonal laws govern elections to the Council of States. | However, candidates are generally chosen by absolute majority | vote. One exception is the canton of Jura that uses a PR | system to elect its two seats. | ELECTION STUDY NOTES - THAILAND (2019): E5041_1 & E5041_2 | | SEE ELECTION STUDY NOTES - THAILAND (2019): E5040 for more | details. --------------------------------------------------------------------------- E5042_1 >>> VOTING ROUNDS - LOWER - 1ST SEGMENT (TIER) E5042_2 >>> VOTING ROUNDS - LOWER - 2ND SEGMENT (TIER) E5042_3 >>> VOTING ROUNDS - UPPER - 1ST SEGMENT (TIER) E5042_4 >>> VOTING ROUNDS - UPPER - 2ND SEGMENT (TIER) --------------------------------------------------------------------------- M15c. How many rounds of voting are there? .................................................................. 01-90. NUMBER OF ROUNDS 97. NOT APPLICABLE 99. MISSING | VARIABLE NOTES: E5042_ | | Source of data: CSES Macro Report M15c. | ELECTION STUDY NOTES - CZECHIA (2017 & 2021): E5042_3 | | Senate (the upper chamber of the Parliament of the Czechia) | consists of 81 directly elected members. Senators are elected for | a term of 6 years, while one-third of the Chamber is renewed | every two years. Elections are based on 81 single-member | constituencies, using a two-round majoritarian system. | ELECTION STUDY NOTES - ICELAND (2016 & 2017): E5042_2 | | There is a second tier where 9 (out of 63) so-called | "supplementary" seats are allocated to party lists receiving | at least 5% of the valid vote. However, voters cast only a | single vote, and voters do not directly cast a vote for | this tier. Hence, this variable is coded "97. NOT APPLICABLE". | ELECTION STUDY NOTES - MEXICO (2018): E5042_1 & E5042_2 | | In Mexico, each voter's vote is counted twice; once for the | single member district contest, and a second time for the | regional PR contest (SEE ELECTION STUDY NOTES - MEXICO (2018): | E5040_1 & E5040_2 for details). | ELECTION STUDY NOTES - MEXICO (2018): E5042_3 & E5042_4 | | In Mexico, each voter's vote for choosing senators is counted | twice; once for the 3-seat multi-member districts contest, and a | second time for the national PR contest (SEE ELECTION STUDY | NOTES - MEXICO (2018): E5040_3 & E5040_4 for details). | ELECTION STUDY NOTES - NORWAY (2017): E5042_2 | | SEE ELECTION STUDY NOTES - NORWAY (2017): E5040_2 and ELECTION | STUDY NOTES - NORWAY (2017): E5041_2. | ELECTION STUDY NOTES - PERU (2016): E5042_1 | | The President is elected using the two-round system. If a | candidate wins a majority of the vote in Round 1, they are deemed | elected. But if no candidate obtains a majority of the vote in | Round 1, the top two candidates who receive a plurality of the | vote in Round 1 advance to the Round 2 run-off. | For Congressional elections, there is one round of voting only. | ELECTION STUDY NOTES - SWITZERLAND (2019): E5042_3 | | The electoral rules (except the number of seats to be filled) | are subject to cantonal regulations. Therefore, the electoral | system varies. Most cantons have two-round majoritarian | elections, where an absolute majority is required in the first | round. However, one canton uses a PR system for its two seats | (canton of Jura). | ELECTION STUDY NOTES - THAILAND (2019): E5042_1 & E5042_2 | | SEE ELECTION STUDY NOTES - THAILAND (2019): E5040 for more | details. | ELECTION STUDY NOTES - UNITED STATES (2020): E5042_1 | | For the Presidential elections, there is only one round of | voting. In most states, for Congressional elections (to the House | of Representatives and the Senate), there is also one round of | voting. The exceptions are for House and Senate elections in | Georgia and Louisiana. | | In the state of Georgia, winning candidates for all congressional | offices must win 50% of the popular vote. Failure to | do so results in a run-off election with the two most popular | candidates in vote share from the original election advancing | to the run-off contest. This occurred in the 2020 regular (as | opposed to special election) Senate election in Georgia when | incumbent Republican (PARTY B) David Purdue lost to Democratic | (PARTY A) challenger Jon Ossoff in the run-off election held in | January 2021. In the original Senate contest in November 2020, | Purdue won more votes than Ossoff, but failed to achieve a | majority support, hence the need for a run-off contest. | For Senate special elections in the state of Georgia, a | non-partisan "jungle primary" operates, where all candidates for | the office, regardless of party affiliation, contest the | election. | A candidate must achieve 50% of the vote to win. If no candidate | does, the two most popular candidates in vote share advance | to a run-off election. This occurred in 2020 when incumbent | Republican (PARTY B) Kelly Loeffler, appointed to the seat by | the Republican Governor of Georgia Brian Kemp after the | resignation of long-time Senator Johnny Isakson in late 2019, | came second in vote share to Democratic (PARTY A) challenger | Raphael Warnock. Warnock failed to achieve a majority of votes | in the original contest and advanced with Loeffler to a run-off | contest in January 2021, in which Warnock defeated Loeffler. | | In the state of Louisiana, a "jungle primary" has been used since | 1977. If one candidate obtains a majority of the vote, they | win the office they are seeking outright, the only "primary" | where a candidate can actually achieve this without a run-off. | When a candidate does not win a majority of the vote, the top | two candidates in vote share, irrespective of party, | go forward to a run-off election, usually held one month later. | In 2020, incumbent Republican (PARTY B) Bill Cassidy was re- | elected, achieving a majority of the vote share in the jungle | primary, negating the need for a run-off contest. --------------------------------------------------------------------------- E5043_1 >>> PARTY LISTS - LOWER - 1ST SEGMENT (TIER) E5043_2 >>> PARTY LISTS - LOWER - 2ND SEGMENT (TIER) E5043_3 >>> PARTY LISTS - UPPER - 1ST SEGMENT (TIER) E5043_4 >>> PARTY LISTS - UPPER - 2ND SEGMENT (TIER) --------------------------------------------------------------------------- M15d. If there are lists, are they closed, open, flexible, or is there party bloc voting? .................................................................. 1. CLOSED (Order of candidates elected is determined by the party and voters are unable to express preference for a particular candidate) 2. OPEN (Voters can indicate their preferred party and their favored candidate within that party) 3. FLEXIBLE (Voters can allocate votes to candidates either within a single party list or across different party lists as they see fit) 7. NOT APPLICABLE 9. MISSING | VARIABLE NOTES: E5043_ | | Source of data: CSES Macro Report M15d. | ELECTION STUDY NOTES - CZECHIA (2017 & 2021): E5043_1 | | Voters cast votes for party lists. Voters may select four | candidates within a party list. A candidate who receives over 5% | of the preferential votes at the regional level will be | placed at the top of the party list. In cases where several | candidates receive over 5% of preferential votes, they | will be placed on the list in descending order based on the | total number of preferential votes they receive. | ELECTION STUDY NOTES - GREECE (2015): E5043_1 | | In the Greek electoral system, the election of the | parliamentarians is based on a party list system using an open | list. However, if general elections are held within 18 months of | the previous elections, the provisions of the Presidential | Decree 152/1985 regarding the allocation of seats by closed | list are reinstated and applied. (Based on article 72, paragraph | 11 of the Presidential Decree 26/2012). Hence the Greek 2015 | study is coded as using a closed-list system, unlike the Greek | 2019 study also included in this CSES release. | ELECTION STUDY NOTES - ICELAND (2016 & 2017): E5043_2 | | There is a second tier where 9 (out of 63) so-called | "supplementary" seats are allocated to party lists receiving | at least 5% of the valid vote. However, voters cast only a | single vote, and voters do not directly cast a vote for | this tier. Hence, this variable is coded "7. NOT APPLICABLE". | ELECTION STUDY NOTES - JAPAN (2017): E5043_2 & E5043_4 | | In the Lower House elections, party lists (2nd segment) are | closed. The second segment of the Upper House uses open lists. | Also SEE ELECTION STUDY NOTES - JAPAN (2017): E5040. | ELECTION STUDY NOTES - LITHUANIA (2016 & 2020): E5043_2 | | In the proportional representation tier, voters can cast one | vote for an open party list, and they have five preferential | votes for the candidates of the party they voted for. | ELECTION STUDY NOTES - NORWAY (2017): E5043_2 | | SEE ELECTION STUDY NOTES - NORWAY (2017): E5040_2 and ELECTION | STUDY NOTES - NORWAY (2017): E5041_2. | ELECTION STUDY NOTES - SWITZERLAND (2019): E5043_1 | | SEE ELECTION STUDY NOTES - SWITZERLAND (2019): E5040_1 and | ELECTION STUDY NOTES - SWITZERLAND (2019): E5041_1. | ELECTION STUDY NOTES - THAILAND (2019): E5043_1 & E5043_2 | | SEE ELECTION STUDY NOTES - THAILAND (2019): E5040 for more | details. --------------------------------------------------------------------------- E5044_1 >>> TRANSFERABLE VOTES - LOWER - 1ST SEGMENT (TIER) E5044_2 >>> TRANSFERABLE VOTES - LOWER - 2ND SEGMENT (TIER) E5044_3 >>> TRANSFERABLE VOTES - UPPER - 1ST SEGMENT (TIER) E5044_4 >>> TRANSFERABLE VOTES - UPPER - 2ND SEGMENT (TIER) --------------------------------------------------------------------------- M16. Are the votes transferable? .................................................................. 1. YES 5. NO 7. NOT APPLICABLE 9. MISSING | VARIABLE NOTES: E5044_ | | Definition: In systems with preferential voting, a voter can | express a list of preferences. For example, votes can be cast | by putting a '1' in the column next to the voter's preferred | candidate, a '2' beside their second favorite candidate and | so on. Votes are counted according to the first preferences and | any candidates who have achieved the predetermined quota are | elected. To decide which of the remaining candidates are elected | the votes are transferred from candidates who have more than the | necessary number to achieve the quota and from the candidate with | the least number of votes. An example of this is the election in | Ireland in 2002. | | Source of data: CSES Macro Report M16. --------------------------------------------------------------------------- E5045_1 >>> CUMULATED VOTES - LOWER - 1ST SEGMENT (TIER) E5045_2 >>> CUMULATED VOTES - LOWER - 2ND SEGMENT (TIER) E5045_3 >>> CUMULATED VOTES - UPPER - 1ST SEGMENT (TIER) E5045_4 >>> CUMULATED VOTES - UPPER - 2ND SEGMENT (TIER) --------------------------------------------------------------------------- M17. If more than one vote can be cast, can they be cumulated? .................................................................. 1. YES 5. NO 7. NOT APPLICABLE 9. MISSING | VARIABLE NOTES: E5045_ | | Definition: Cumulative voting refers to systems in which voters | are allowed to cast more than one vote for a single candidate. | | Source of data: CSES Macro Report M17 | ELECTION STUDY NOTES - SWITZERLAND (2019): E5045_1 | | SEE ELECTION STUDY NOTES - SWITZERLAND (2019): E5040_1. --------------------------------------------------------------------------- E5046_1 >>> COMPULSORY VOTING - LOWER - 1ST SEGMENT (TIER) E5046_2 >>> COMPULSORY VOTING - LOWER - 2ND SEGMENT (TIER) E5046_3 >>> COMPULSORY VOTING - UPPER - 1ST SEGMENT (TIER) E5046_4 >>> COMPULSORY VOTING - UPPER - 2ND SEGMENT (TIER) --------------------------------------------------------------------------- M18. Is voting compulsory? .................................................................. 1. YES; STRICTLY ENFORCED SANCTIONS 2. YES; WEAKLY ENFORCED SANCTIONS 3. YES; WITHOUT SANCTION FOR VIOLATION 5. NO 7. NOT APPLICABLE 9. MISSING | VARIABLE NOTES: E5046_ | | Definition: Voting is compulsory if the law states that all those | who have the right to vote are obliged to exercise that right. | | Source of data: CSES Macro Report M18. | ELECTION STUDY NOTES - BRAZIL (2018): E5046 | | Voting is compulsory for those aged 18-70 unless they are | illiterate. Voting is optional for the illiterate, those over | 70, and those aged 16-18. Those who do fail to vote must provide | a justification to the Brazilian Election Commission. | (Source of data: Bustani 2001, p. 306,n. 2). | ELECTION STUDY NOTES - MEXICO (2018): E5046_1 & E5046_3 | | Voting in Mexico is formally compulsory, but without sanction | for violation. | ELECTION STUDY NOTES - SWITZERLAND (2019): E5046_1 & E5046_3 | | Voting is compulsory in one constituency/canton only | (Schaffhausen). --------------------------------------------------------------------------- E5047_1 >>> IS THERE PARTY THRESHOLD - LOWER - 1ST SEGMENT (TIER) E5047_2 >>> IS THERE PARTY THRESHOLD - LOWER - 2ND SEGMENT (TIER) E5047_3 >>> IS THERE PARTY THRESHOLD - UPPER - 1ST SEGMENT (TIER) E5047_4 >>> IS THERE PARTY THRESHOLD - UPPER - 2ND SEGMENT (TIER) --------------------------------------------------------------------------- M20a. Are there legally mandated thresholds that a party must exceed before it is eligible to receive seats? .................................................................. 1. YES 5. NO 7. NOT APPLICABLE 9. MISSING | VARIABLE NOTES: E5047_ | | Source of data: CSES Macro Report M20a. | | Further details on the size of the threshold(s), if applicable, | are provided in ELECTION STUDY NOTES for variables E5048_ (Party | Threshold). | ELECTION STUDY NOTES - DENMARK (2017): E5047_2 | | The electoral threshold in Denmark only applies to the | compensatory seats (n=40 at second tier). Only parties receiving | at least 2% of the total vote are entitled to receive one of the | 40 seats to be allocated. Alternatively, parties winning a seat | directly in any of the ten multi-member constituencies or who | obtain a number of votes corresponding - at least - to the | provincial votes/seat ratio in two of the three geographical | regions (i.e., Copenhagen, Northern Jutland, and Seeland-Southern | Denmark) are also entitled to compensatory seats. | ELECTION STUDY NOTES - NORWAY (2017): E5047_2 | | The electoral threshold in Norway only applies to the "member | at large" seats (n=19) at second tier). Only parties receiving | at least 4% of the total vote are entitled to receive one of the | 19 seats to be allocated. --------------------------------------------------------------------------- E5048_1 >>> PARTY THRESHOLD - LOWER - 1ST SEGMENT (TIER) E5048_2 >>> PARTY THRESHOLD - LOWER - 2ND SEGMENT (TIER) E5048_3 >>> PARTY THRESHOLD - UPPER - 1ST SEGMENT (TIER) E5048_4 >>> PARTY THRESHOLD - UPPER - 2ND SEGMENT (TIER) --------------------------------------------------------------------------- M20b. If YES in M20a, what is the threshold? .................................................................. 00.00 THERE IS NO THRESHOLD 0.10-95.00 A PARTY MUST RECEIVE THIS PERCENT (0.1% TO 95%) OF THE POPULAR VOTE IN ORDER TO BE ELIGIBLE FOR SEATS 96.00 OTHER THRESHOLD [SEE ELECTION STUDY NOTES] 97.00 NOT APPLICABLE 99.00 MISSING | VARIABLE NOTES: E5048_ | | Source of data: CSES Macro Report M20b. | | See also VARIABLE NOTES for E5047_. | ELECTION STUDY NOTES - ALBANIA (2017): E5048_1 | | "For elections to the Assembly, parties that run on their own | and that have obtained less than 3 percent, and coalitions | that have obtained less than 5 percent of the valid votes in | the respective electoral zone are excluded from the allocation | of seats." (Article 162, The Electoral Code of the Republic of | Albania.) | ELECTION STUDY NOTES - AUSTRIA (2017): E5048_1 | | Parties that already won a seat in one of the 39 regional | districts ("Regionalwahlkreis") or received at least 4% of | the nationwide valid votes can enter the parliament. | Also SEE ELECTION STUDY NOTES - AUSTRIA (2017): E5040. | ELECTION STUDY NOTES - BRAZIL (2018): E5048_1 | | The threshold is based on the Hare Quota. To win seats, a party | must exceed the quota (total valid votes divided by the number | of seats) in each electoral district. Each party is entitled to | as many seats as the number of times its vote reaches the quota. | Unallocated seats apportioned according to the d'Hondt formula. | (Source of data: ACE Electoral Knowledge Network and Nicolau | 2008, p.170). | ELECTION STUDY NOTES - BRAZIL (2018): E5048_3 | | The Senate is chosen by a simple majority. | ELECTION STUDY NOTES - COSTA RICA (2018): E5048_1 | | There is no formal threshold. For the allocation of the seats | in the National Assembly, the Electoral Court uses a modified | version of the Hare quota (half quota). | Also SEE ELECTION STUDY NOTES - COSTA RICA (2018): E5041_1. | ELECTION STUDY NOTES - CZECHIA (2017): E5048_1 | | The threshold is 5% for a single party. It is higher for | coalitions: | 10% for a coalition of 2 parties, | 15% for a coalition of 3 parties, | 20% for a coalition of 4 parties, etc. | ELECTION STUDY NOTES - CZECHIA (2021): E5048_1 | | In February 2021, the Czechia Constitutional Court, on foot of | a legal complaint from several parties, ruled that the electoral | thresholds in place for the 2017 legislative elections had | unfairly favored larger parties. The threshold of 5% for a single | party remained. However, for coalitions, new thresholds were set: | - 8% for a coalition of 2 parties, | - 11% for a coalition of 3 parties or more. | ELECTION STUDY NOTES - EL SALVADOR (2019): E5048_1 | | There is no formal threshold. For the allocation of the seats | in the National Assembly, the Electoral Court uses the Hare | quota. | Also SEE ELECTION STUDY NOTES - EL SALVADOR (2019): E5040_1. | ELECTION STUDY NOTES - GERMANY (2017 & 2021): E5048_1 | | Constituency candidates with a relative majority (first vote) | in one of the 299 constituencies win a seat. | ELECTION STUDY NOTES - GERMANY (2017 & 2021): E5048_2 | | Germany has a double threshold in tier 2 (party list, "second | vote") segment. Parties with more than 5% of the valid votes | nationally based on their tier 2 votes (party list, "second | vote"), or those who have won three of the 299 constituency seats | (tier 1), are eligible for a proportional share of list seats | based on their national vote share. | ELECTION STUDY NOTES - GREECE (2015 & 2019): E5048_1 | | Parties that receive at least 3% of all valid votes cast are | entitled to participate in the so-called first round of | proportional allocation of 250 seats at the national level. The | remaining 50 seats are awarded to the party that obtained the | nationwide plurality of votes, regardless of its obtained | percentage or the difference with the second party. | ELECTION STUDY NOTES - HUNGARY (2018): E5048_2 | | The threshold for political parties to obtain seats in the second | tier (party-list, national-level constituency) is 5% of the | valid votes. However, it is higher for electoral alliances | comprising more than one party: | - A threshold of 10% of valid votes for coalitions | of 2 parties. | - A threshold of 15% of valid votes for coalitions | of 3 parties or more. | ELECTION STUDY NOTES - ICELAND (2016 & 2017): E5048_1 & E5048_2 | | While there is no formal threshold at the first tier, in | the second tier (national district - SEE ELECTION STUDY NOTES - | ICELAND (2016 & 2017): E5040_2 for details) only party lists | receiving at least 5% of the national vote are entitled to | receive one of the 9 so-called compensatory seats to be | allocated. | ELECTION STUDY NOTES - ISRAEL (2020): E5048_1 | | The legal threshold in Israel is 3.25%, having been changed in | 2014 from 2%. | ELECTION STUDY NOTES - ITALY (2018): E5048_2 | | In the proportional components (2nd segments) of both Houses of | the Italian Parliament, thresholds for obtaining seats are 3% | for parties running alone, 10% for coalitions (with the | condition that at least one of the coalition members obtains at | least 3% of the votes), and 1% for parties within coalitions. | ELECTION STUDY NOTES - ITALY (2018): E5048_4 | | In the proportional components (2nd segments) of both Houses of | the Italian parliament, thresholds for obtaining seats are 3% | for parties running alone, 10% for coalitions, and 1% for | parties within coalitions. | ELECTION STUDY NOTES - JAPAN (2017): E5048_1 | | Electoral threshold in the first (majoritarian) segment of | the Lower House is one-sixth of the number of valid votes | in each single-member district (16.67% of the valid vote). | ELECTION STUDY NOTES - JAPAN (2017): E5048_3 | | In the majoritarian segment of the Upper House (Prefectural | Districts), successful candidates are decided in the order of | the number of valid votes obtained on the basis of the | comparative plurality. To have a seat, a candidate should | receive the number of votes which is equal to or more than | one-sixth of the quotient, dividing the total of valid ballots | cast by the number of seats to be filled from the constituency | concerned. | ELECTION STUDY NOTES - LATVIA (2018): E5048_1 | | The 100 members of the Saeima (Parliament, single chamber) are | elected by open list proportional representation from five | multi-member constituencies. Seats are allocated using the | Sainte-Lague method with a national electoral threshold of | five percent of valid votes nationally. | ELECTION STUDY NOTES - LITHUANIA (2016 & 2020): E5048_2 | | In the second tier (party-list, national-level constituency), | the electoral threshold is 5% of the total vote for individual | parties, and 7% for electoral coalitions. | ELECTION STUDY NOTES - MEXICO (2018): E5048_2 & E5048_4 | | Since the 2014 electoral reform, in order for a political | party to have the right to participate in the allocation of | proportional representation deputies or senators, it must obtain | at least 3% of the total votes cast in the respective election. | ELECTION STUDY NOTES - NETHERLANDS (2017): E5048_1 | | The threshold is 0.67 percent of the electoral quota - or | one seat. | ELECTION STUDY NOTES - NEW ZEALAND (2017 & 2020): E5048_2 | | New Zealand has a double threshold: Parties with more than 5% of | the valid votes nationally on the basis of the party list votes | ("second vote", tier 2) or those who have won one of the 70 | constituency seats (tier 1) are entitled to sit in parliament and | may be eligible to receive a proportional share of the 50 list | seats on the basis of their national vote share. | ELECTION STUDY NOTES - NORWAY (2017): E5048_2 | | SEE ELECTION STUDY NOTES - NORWAY (2017): E5047_2. | ELECTION STUDY NOTES - PERU (2021): E5048_1 | | Peru has a double threshold. Parties with 5% or more of the valid | votes nationally or those who win six seats in two electoral | districts are eligible for list seats. | ELECTION STUDY NOTES - POLAND (2019): E5048_1 | | The threshold is 5% (8% for electoral alliances) of the valid | votes cast nationwide. | ELECTION STUDY NOTES - ROMANIA (2016): E5048_1 & E5048_3 | | According to the new electoral law (passed in 2015), both | chambers use a proportional representation system. The rules | concerning thresholds apply to elections for both houses. | The threshold for single-party lists is 5% of the total number | of votes validly cast at the national level. There is also the | alternative route of receiving 20% of the total number of | validly cast votes in at least four electoral constituencies. | For alliances, 3% is added to the normal threshold for the | second party and 1% for each other additional party in the | alliance. However, the requested threshold for alliances | cannot exceed 10%. | ELECTION STUDY NOTES - SLOVAKIA (2020): E5048_1 | | The threshold for political parties to obtain seats is 5% of the | valid votes. However, it is higher for electoral alliances | comprising of more parties: | - A threshold of 7% of valid votes for coalitions | of 2 or 3 parties. | - A threshold of 10% of valid votes for coalitions | of 4 parties or more. | ELECTION STUDY NOTES - SOUTH KOREA (2016): E5048_1 | | Constituency candidates with a relative majority in one of the | 253 constituencies win a seat. | ELECTION STUDY NOTES - SOUTH KOREA (2016): E5048_2 | | South Korea has a double threshold in the second (proportional) | segment: Parties with more than 3% of the valid votes nationally | on the basis of the party list votes ("party votes") or those | who have won at least 5 of the 253 constituency seats receive a | proportional share of the 47 list seats on the basis of their | national vote share. | ELECTION STUDY NOTES - THAILAND (2019): E5048_1 & E5048_2 | | SEE ELECTION STUDY NOTES - THAILAND (2019): E5040 for more | details. | ELECTION STUDY NOTES - TURKEY (2018): E5048_1 | | The threshold is 10% of the valid votes cast nationwide. In | addition, a political party can only be elected if the party | (a) is officially organized in at least half of the provinces | and one-third of the districts within these provinces; | (b) has nominated two candidates for each parliamentary seat | in at least half of the provinces. --------------------------------------------------------------------------- E5049_1 >>> UNIT FOR THE THRESHOLD - LOWER - 1ST SEGMENT (TIER) E5049_2 >>> UNIT FOR THE THRESHOLD - LOWER - 2ND SEGMENT (TIER) E5049_3 >>> UNIT FOR THE THRESHOLD - UPPER - 1ST SEGMENT (TIER) E5049_4 >>> UNIT FOR THE THRESHOLD - UPPER - 2ND SEGMENT (TIER) --------------------------------------------------------------------------- M20c. If YES in M21a, what is the unit for the threshold mentioned in M21b? .................................................................. 1. PERCENT OF TOTAL VOTES 2. PERCENT OF VALID VOTES 3. PERCENT OF THE TOTAL ELECTORATE 4. OTHER [SEE ELECTION STUDY NOTES] 7. NOT APPLICABLE 9. MISSING | VARIABLE NOTES: E5049_ | | Source of data: CSES Macro Report M20c. | ELECTION STUDY NOTES - GERMANY (2017 & 2021): E5049_2 | | Germany has a double threshold in tier 2 (party list, "second | vote") segment. Parties with more than 5% of the valid votes | nationally based on their tier 2 votes (party list, "second | vote"), or those who have won three of the 299 constituency seats | (tier 1), are eligible for a proportional share of list seats | based on their national vote share. | ELECTION STUDY NOTES - MEXICO (2018): E5049_2 & E5049_4 | | Since the 2014 electoral reform, in order for a political | party to have the right to participate in the allocation of | proportional representation deputies or senators, it must obtain | at least 3% of the total votes cast in the respective election. | ELECTION STUDY NOTES - NEW ZEALAND (2017 & 2020): E5049_2 | | New Zealand has an alternative threshold: Parties with more than | 5% of the total votes nationally on the basis of the party list | votes ('party vote', tier 2) or those who have won one of the 70 | constituency seats (tier 1) are entitled to sit in parliament | and may be eligible to receive a proportional share of the 50 | list seats on the basis of their national vote share. | ELECTION STUDY NOTES - NORWAY (2017): E5049_2 | | SEE ELECTION STUDY NOTES - NORWAY (2017): E5047_2. | ELECTION STUDY NOTES - THAILAND (2019): E5049_1 & E5049_2 | | SEE ELECTION STUDY NOTES - THAILAND (2019): E5040 for more | details. --------------------------------------------------------------------------- E5050 >>> AGE OF THE CURRENT REGIME --------------------------------------------------------------------------- The number of years since the most recent regime change. .................................................................. 001-500. AGE OF THE REGIME (YEARS) 999. MISSING | VARIABLE NOTES: E5050 | | E5050 details the number of years since the most recent regime | change. It is taken from the POLITY IV project and is based on | the "DURABLE" variable. Change in regime is defined by POLITY IV | as a three-point change in the POLITY score over a period of | three years or less or the end of transition periods defined | by the lack of stable political institutions, as denoted by a | standardized AUTHORITY score. | | Source of data: POLITY IV Project: | Political Regime Characteristics and Transitions, 1800-2017, | Monty G. Marshall and Keith Jaggers, George Mason University and | Colorado State University | (http://www.systemicpeace.org/polity/polity4.htm) | (Date accessed: July 14, 2021). | | The Polity IV Dataset Users' Manual: | (http://www.systemicpeace.org/inscr/p4manualv2017.pdf). | (Date accessed: April 05, 2019). | | The Polity IV annual time-series dataset | (www.systemicpeace.org/inscr/p4v2017.xls) | (Date accessed: July 14, 2021). | | Data are unavailable for HONG KONG (2016) and ICELAND (2016 & | 2017). --------------------------------------------------------------------------- E5051 >>> REGIME: TYPE OF EXECUTIVE --------------------------------------------------------------------------- Classification of political regimes. .................................................................. 1. PARLIAMENTARY REGIME 2. MIXED REGIME 3. PRESIDENTIAL REGIME 9. MISSING | VARIABLE NOTES: E5051 | | In CSES MODULE 5, classifications of political regimes mainly | rely on the following decision rule as presented by Cheibub, | 2007: | | A. The system is parliamentary either (i) if there is no | independently (indirectly or directly) elected President or (ii) | if there is an independently (indirectly or directly) elected | President but the government is not responsible to the President. | B. The system is mixed either if there is an independently | (indirectly or directly) elected President and government is | responsible to the President. | C. The system is Presidential if the government is not | responsible to the elected legislature. | | NOTE: Responsibility refers to whether the survival of the | executive depends directly on legislature (i.e., vote of | confidence). | | However, researchers are advised that in a small number of | cases, coding employed in CSES MODULE 5 may diverge from regime | classifications as suggested by Cheibub. | Further, all polities included in CSES MODULE 5 are classified | according to the above coding scheme, irrespective of their | democratic status. Researchers interested in democracy ratings | may refer to E5090_ (Freedom House) or E5091_ (Polity IV). | | Source of data: Publicly Available Sources and Cheibub, Jose | Antonio. 2007. "Presidentialism, Parliamentarism, and Democracy". | New York. Cambridge University Press. | ELECTION STUDY NOTES - AUSTRIA (2017): E5051 | | Austrian executive power is coded as mixed or semi-Presidential, | given that the President can dissolve the National Council. | Article 29 of the Constitution states: | "(1) The Federal President can dissolve the National Council, | but he may avail himself of this prerogative only once for the | same reason." However, in practice, the system works mostly | like a parliamentary system. | ELECTION STUDY NOTES - FINLAND (2019): E5051 | | Classifying the Finish executive power is subject to some | controversy. Here it is coded as a mixed or semi-Presidential | system. Some key features of the Finnish system that distinguish | it from a traditional parliamentary system are that by | constitution a) the President is popularly elected by direct | vote for a fixed term of six years and for no more than two | consecutive terms of office; b) the President can, on | recommendation of the Prime Minister, dissolve the legislature; | c) the President can veto legislature, though parliament can | override the Presidential veto with a simple majority; and | d) the President may issue decrees that have the force of law. | More details can be found in Fish & Kroenig, 2009. Nonetheless, | it has been argued that Finland, after constitutional reforms in | the 1990s, works in practice as a parliamentary system. | ELECTION STUDY NOTES - HONG KONG (2016): E5051 | | Hong Kong is not a sovereign state, but a Special Administrative | Region (SAR) in China. The Central Government authorizes the | HKSAR to exercise a high degree of autonomy and enjoy executive, | legislative and independent judicial power. Therefore, the HKSAR | Government comparable to a local government. | The Chief Executive (CE) is the President of the Executive | Council of Hong Kong and head of the Government of the Hong | Kong Special Administrative Region. The Chief Executive is | elected by an 800-member Election Committee. The elected CE | must then be appointed by the Central People's Government. | Regarding the relationship between the CE and Legislative | Council, the type of executive may be regarded as some form of a | Presidential system, because the CE and the LegCo members are | returned by different elections. | According to Article 52, the CE must resign in case of refusal | to sign a bill passed by a two-thirds majority of the Legislative | Council. | ELECTION STUDY NOTES - PORTUGAL (2019): E5051 | | Following Cheibub (2007), Portugal is regarded as 2. MIXED | REGIME in CSES MODULE 5, as Portugal's President is directly | elected and the government is accountable both to parliament | and the President (Article 190 of the constitution). | Users are advised that classifying the Portuguese regime type is | subject to some controversy, as the country is sometimes also | regarded as a parliamentary regime. | ELECTION STUDY NOTES - TAIWAN (2016 & 2020): E5051 | | Since 1992, the constitution provides for the direct election | of a President. Yet, the Executive Yuan (cabinet) is responsible | to the Legislative Yuan (parliament) provided that the | Legislative Yuan is in session, its members have the right to | interpolate the President of the Executive Yuan, and Ministers | and chairmen of the Commissions of the said Yuan (Article 57 of | the Constitution). However, the legislature cannot vote no | confidence in the government and can be dissolved by the | President. | ELECTION STUDY NOTES - TURKEY (2018): E5051 | | The constitutional amendments approved in the 2017 Turkish | constitutional referendum turned the Presidency into executive | post, effective with the 2018 general election. Hence, the | Republic of Turkey is a Presidential republic. --------------------------------------------------------------------------- E5052 >>> NUMBER OF MONTHS SINCE LAST LOWER HOUSE ELECTION --------------------------------------------------------------------------- The number of months between the current and previous lower house election. .................................................................. 1-200. NUMBER OF MONTHS SINCE LAST LOWER HOUSE ELECTION 999. MISSING | VARIABLE NOTES: E5052 | | E5052 details the number of months since the current and previous | lower house election. | If the previous national lower chamber election was held in more | than one round (i.e., run-off election), the data refer to the | number of months since the first round. | | Further details on election date irregularities (i.e., elections | held on a different date than scheduled) are provided in ELECTION | STUDY NOTES for variable E5027. | | Source of data: Publicly Available Sources. | ELECTION STUDY NOTES - INDIA (2019): E5052 | | Since Indian parliamentary elections are held on multiple dates, | these data refer to the first days of the previous and current | elections (April 2014 and April 2019, respectively). | ELECTION STUDY NOTES - THAILAND (2019): E5052 | | This refers to the election of February 2, 2014. | On May 22, 2014, the Royal Thai Armed Forces, led by General | Prayut Chan-o-cha, Commander of the Royal Thai Army (RTA), | launched a coup d'etat. The current 2019 elections were the | first since the coup. --------------------------------------------------------------------------- E5053 >>> NUMBER OF MONTHS SINCE LAST PRESIDENTIAL ELECTION --------------------------------------------------------------------------- The number of months between the current and previous Presidential election. .................................................................. 1-200. NUMBER OF MONTHS SINCE LAST PRESIDENTIAL ELECTION 997. NOT APPLICABLE 999. MISSING | VARIABLE NOTES: E5053 | | E5053 details the number of months since the current and previous | Presidential contest. E5053 does not signify that the election | chose either the nominal or effective head of government. | If the previous Presidential election was held in more than one | round (i.e., run-off election), the data refer to the number | of months since the first round. | | Source of data: Publicly Available Sources. | ELECTION STUDY NOTES - HONG KONG (2016): E5053 | | The Chief Executive (CE) is the President of the Executive | Council of Hong Kong and head of the Government of the Hong | Kong Special Administrative Region. As such, the CE can be | seen as an equivalent of the President elsewhere. It is the | highest government official of the HKSAR Government. | The Chief Executive is not elected by a popular vote. Instead, | CE is elected by an 800-member Election Committee. The elected | CE must then be appointed by the Central People's Government. | ELECTION STUDY NOTES - TURKEY (2018): E5053 | | Previous Presidential elections were held on August 10, 2014. | The current Presidential election was originally scheduled for | November 2019. However, President Recep Tayyip Erdogan called a | snap election, due to the passage of a series of constitutional | amendments in the 2017 referendum. --------------------------------------------------------------------------- E5054 >>> PRESIDENTIAL ELECTIONS ELECTORAL FORMULA --------------------------------------------------------------------------- The electoral formula used to elect the President that is elected by popular vote. .................................................................. 1. PLURALITY 2. ABSOLUTE MAJORITY RULE 3. QUALIFIED MAJORITY RULE 4. ELECTORAL COLLEGE 5. SINGLE TRANSFERABLE VOTE 7. NOT APPLICABLE 9. MISSING | VARIABLE NOTES: E5054 | | E5054 details the electoral formula used to elect the President | when the President is elected by popular vote. Presidents | indirectly elected (for example, those elected by Parliament) are | classified as "7. NOT APPLICABLE". | | Below, the classifications of each electoral formula are | summarized: | - PLURALITY: The candidate that obtains the most votes wins. | - ABSOLUTE MAJORITY RULE: A candidate must win over 50% of the | vote to win. If no candidate wins this many votes in | Round 1, then there is a runoff election (Round 2), | conventionally between the top two candidates. | - QUALIFIED MAJORITY RULE: Each qualified majority system | specifies a particular percentage of the vote a candidate | must win in order to be elected in Round 1. If two or more | candidates overcome these thresholds, then the one with the | highest number of votes wins. The qualified majority systems | vary regarding the electoral procedure that applies when | these thresholds are not met. | - ELECTORAL COLLEGE: The candidate that wins a plurality | of the electoral college votes wins. | - SINGLE TRANSFERABLE VOTE: Requires voters to rank single | candidates in order of the most to least preferred. Votes | are transferred until candidates obtain the Droop quota. The | candidate that obtains this quota first is elected. In | essence, this is the Alternative Vote as only one candidate | is elected. | | The definition of this variable is taken from Matt Golder's | database about Democratic Electoral Systems Around the World, | 1946-2011. | Source of data: | http://mattgolder.com/elections. (Date accessed: November 21, | 2016). | ELECTION STUDY NOTES - AUSTRIA (2017): E5054 | | The President of Austria is elected by absolute majority for a | six-year term. | ELECTION STUDY NOTES - BRAZIL (2018): E5054 | | The President of Brazil is elected by absolute majority for a | four-year term. | ELECTION STUDY NOTES - CHILE (2017): E5054 | | The President of Chile is elected by absolute majority for a | four-year term. | ELECTION STUDY NOTES - COSTA RICA (2018): E5054 | | The President of Costa Rica is elected by qualified majority for | a four-year term. A candidate must win 40% of the vote in Round 1 | to secure victory. If no candidate wins in Round 1, a run-off | election is held between the two candidates with the most votes | in Round 1, with the candidate winning the most votes in Round 2 | elected. | ELECTION STUDY NOTES - FRANCE (2017): E5054 | | The President of France is elected by absolute majority for a | five-year term. | ELECTION STUDY NOTES - ROMANIA (2016): E5054 | | The President of Romania is elected by absolute majority. An | individual may serve two terms. While in office, the President | may not be a formal member of a political party. | ELECTION STUDY NOTES - TURKEY (2018): E5054 | | The President of Turkey is elected by absolute majority for a | five-year term. | ELECTION STUDY NOTES - UNITED STATES (2016 & 2020): E5054 | | The President and Vice President are not directly elected by | the voters. Voters cast their vote for President and Vice- | President by selecting a pair of candidates listed on a single | Presidential/Vice Presidential ticket. This vote selects slates | of electors to serve in the Electoral College. In forty-eight | of the fifty states and the District of Columbia, the list of | electors that obtains a majority of votes wins the state and | with it the electoral college votes for that state. Maine and | Nebraska allow the possibility for state electoral votes to be | split on the basis of which slate of electors obtains the most | votes in electoral districts. If no candidate obtains a | majority in the electoral college, the election is decided by | the incoming House of Representatives. --------------------------------------------------------------------------- E5055 >>> ELECTORAL FORMULA IN ALL ELECTORAL SEGMENTS (TIERS) --------------------------------------------------------------------------- Whether the country uses a majoritarian formula, a proportional formula, or a mixed formula in all of its electoral segments/tiers. .................................................................. 1. MAJORITARIAN 2. PROPORTIONAL 3. MIXED 9. MISSING | VARIABLE NOTES: E5055 | | The definition of E5055 is taken from Matt Golder's database | about Democratic Electoral Systems Around the World, 1946-2011 | (http://mattgolder.com/elections, Date accessed: | November 21, 2016). | | MAJORITARIAN systems require successful candidates to win either | a plurality or majority of the vote. As a result, they are | considered majoritarian. | | PROPORTIONAL systems can be divided into two types: those that | use party lists and those like the single transferable vote that | do not. Those systems employing lists can themselves be divided | into two further categories: quota systems (with allocation of | remainders) and highest average systems. | | MIXED systems use a mixture of majoritarian and proportional | electoral rules. A country can be classified as having a mixed | system whether it uses one or more electoral segments (tiers); in | practice, most mixed systems have more than one segment (tier). | Mixed electoral systems can be divided into those in which the | two electoral formulas are dependent and those in which they are | independent. | | Source of data: CSES Macro Report and Publicly Available Sources | ELECTION STUDY NOTES - BRAZIL (2018): E5055 | | This concerns the Lower House (Federal deputies) electoral | system. | ELECTION STUDY NOTES - COSTA RICA (2018): E5055 | | For parliamentary elections, Costa Rica uses proportional, | closed party list system. The 57 members of the Legislative | Assembly are elected through the largest remainder method from | seven multi-member constituencies with between four and 19 | seats, which are based on the seven provinces. For the | allocation of the seats in the National Assembly, the Electoral | Court uses a modified version of the Hare quota (half quota). | ELECTION STUDY NOTES - GERMANY (2017): E5055 | | Mixed: 299 members are elected at the district level under the | majority (first-past-the-post) system. The remaining seats | are allocated through a party list using proportional | representation and the Sainte-Lague Formula. | ELECTION STUDY NOTES - GREECE (2015): E5055 | | Greece uses the Hagenbach-Bischoff system of "reinforced" | proportional representation, with voting for party lists and, | within each list, preferential vote. However, if general | elections are held within 18 months of the previous elections, | the provisions of Presidential Decree 152/1985 regarding the | allocation of seats by closed list is reinstated and applied. | (Based on article 72, paragraph 11 of the Presidential Decree | 26/2012). Hence the Greek 2015 study is coded as using a closed | list system in variable E5043, unlike the Greek 2019 study also | included in this CSES release. | ELECTION STUDY NOTES - GREECE (2019): E5055 | | Greece uses the Hagenbach-Bischoff system of "reinforced" | proportional representation, with voting for party lists and, | within each list, preferential vote. | ELECTION STUDY NOTES - HONG KONG (2016): E5055 | | E5055 concerns the election of 35 representatives in | geographical constituencies, and 5 representatives in the | District Council (Second) Functional Constituency. | ELECTION STUDY NOTES - HUNGARY (2018): E5055 | | Hungary uses a mixed system. Out of 199 Members of Parliament, | 106 Members are elected in individual constituencies under a | majority (first-past-the-post) system. The remaining 93 Members | are elected using proportional representation and a single | national constituency. | ELECTION STUDY NOTES - ICELAND (2016): E5055 | | The Icelandic Althingi (Parliament) has 63 members, where 54 | members are elected from 6 multi-member (9 seats apiece) | constituencies (first tier). In addition, there is a second | tier, comprising of 9 "supplementary" seats that are | allocated to parties (using the D'Hondt method) to ensure the | number of seats they receive is in proportion to its national | vote. However, only party lists that obtain at least 5% of | the national vote are entitled to receive these seats. | | Source of data: | Landskjorstjorn Elections to the Althingi: | http://www.landskjor.is/media/frettir/AnalysisIceland | Election2013.pdf | (Date accessed: February 12, 2020). | ELECTION STUDY NOTES - IRELAND (2011): E5055 | | The electoral system in Ireland is a proportional | representation single transferable vote system (PRSTV). Voters | put a '1' beside their most preferred candidate, a '2' beside | their second most preferred candidate, and so on. Voters can | express as many preferences as there are candidates running in | their constituency. On the first count, candidates are declared | elected if they attract enough first preference votes to pass a | specified threshold, which is defined separately for each | constituency according to the formula: [total valid votes/ | (total number of seats +1) +1]. If a candidate is declared | elected on the first count, the second preferences of the | candidate's surplus votes (i.e., votes over and above the | threshold) are then distributed among the other candidates. If | this redistribution does not push any of the remaining | candidates over the threshold, the candidate with the lowest | number of votes is eliminated, then the second preferences of | the eliminated candidate's votes are redistributed. This process | of redistribution of surpluses and elimination of candidates | continues until all the seats in a given constituency are | filled. | | Owing to the quota formula: [total valid votes/(total number | of seats "+1") +1], the STV system in Ireland works similarly | as the party-list proportional representation, which uses | the largest-reminder method with droop quota. | ELECTION STUDY NOTES - ITALY (2018): E5055 | | Currently, Italy has a mixed-member majoritarian system | consisting of three components. In the majoritarian component, | accounting for about 1/3 of the seats, candidates supported by | electoral coalitions (or single parties) compete in single | member districts under plurality rule. Approximately 2/3 of | the seats are distributed proportionally among parties according | to the results at the national level. | Finally, 12 members elected from multi-member constituencies | abroad, using the proportional representation system. | ELECTION STUDY NOTES - LITHUANIA (2016 & 2020): E5055 | | Lithuania uses a mixed system. Out of the 141 Members of | Parliament, 71 Members are elected in individual constituencies | under the majority (first-past-the-post) system. The remaining | 70 Members are elected using proportional representation and a | single nationwide constituency. | ELECTION STUDY NOTES - NEW ZEALAND (2017 & 2020): E5055 | | Mixed: 70 members are elected at the district level (tier 1) | under the majority (first-past-the post) system. The remaining | 50 seats (tier 2) are allocated through a national party list | using proportional representation based on the Sainte-Lague | Formula. | ELECTION STUDY NOTES - SOUTH KOREA (2016): E5055 | | Korea employs a mixed-member majoritarian system that combines | 253 single-member districts (SMD) with 47 proportional | representation (PR) seats, elected from a single nationwide | district. Each voter casts two votes, one for an individual | candidate in the SMD segment, and one for a closed party list | in the PR segment. | ELECTION STUDY NOTES - THAILAND (2019): E5055 | | SEE ELECTION STUDY NOTES - THAILAND (2019): E5040 for more | details. | ELECTION STUDY NOTES - TURKEY (2018): E5055 | | The 600 members of the Grand National Assembly of Turkey | are elected by party-list proportional representation in | 87 electoral districts, using the D'Hondt method. | ELECTION STUDY NOTES - URUGUAY (2019): E5055 | | The Lower Chamber (Camara de Representantes; House of | Representatives) of the Uruguayan General Assembly consists | of 99 members. Seats are assigned between parties in a single | nationwide district based on a proportional (d'Hondt) system. | The system uses closed lists and Double Simultaneous Vote (DSV) | in regional districts. | DSV is the system by which the voter votes synchronously in a | logical order: first by a party ("lema" or label or motto) and | then a list of candidates ("lista" or list). --------------------------------------------------------------------------- E5056 >>> NUMBER OF ELECTORAL SEGMENTS (TIERS) --------------------------------------------------------------------------- The number of electoral segments (tiers) in each country. .................................................................. 1-3. NUMBER OF ELECTORAL SEGMENTS (TIERS) 9. MISSING | VARIABLE NOTES: E5056 | | E5056 primarily concerns the Lower House election. However, if | a particular study is focused on the Upper House or Presidential | election, it may report results for these elections, | respectively. | | Source of data: CSES Macro Report and Publicly Available Sources | ELECTION STUDY NOTES - AUSTRIA (2017): E5056 | | The Austrian electoral system is a proportional representation | system with three segments or tiers. These correspond to the | regional districts tier, the Land level tier (or state level) | and the federal (or national) level tier. Counting and | allocation of seats passes through each of these levels. | However, voters cast a single vote. In this vote, they can | express preferences for specific candidates, particularly, a | Laender level candidate and/or for a regional level candidate. | ELECTION STUDY NOTES - DENMARK (2019): E5056 | | The Danish Folketing has 179 members, 175 of which are elected | in mainland Denmark and the remaining four from the territories | of Greenland and the Faroe Islands (two seats in each territory). | In mainland Denmark, 135 members are elected from 10 multi-member | constituencies across three geographical regions, namely: | Copenhagen, Northern Jutland, and Seeland-Southern Denmark (Tier | 1). Additionally, 40 supplementary seats are distributed across | these three geographical regions in order to achieve full | proportionality (Tier 2). | ELECTION STUDY NOTES - GERMANY (2017 & 2021): E5056 | | Tier 1 is represented by the district level under the majority | (first-past-the-post) system, where candidates compete in 299 | constituencies. Tier 2 is based on a party list system using | proportional representation. | ELECTION STUDY NOTES - GREECE (2015 & 2019): E5056 | | Of the 300 members of parliament, 250 are elected proportionally | in 56 (59 in 2019) constituencies. | According to the Greek Constitution (Article 54.3), part of the | Parliament (no more than 1/20) may be elected not in a specified | constituency but rather throughout the country at large. These | are the State Deputies, whose exact number depends on the total | electoral strength of each party. | The remaining 50 seats are awarded to the party receiving the | largest share of the vote as a 'premium'. | However, since voters cast a single vote only, this system is | different from systems with multiple tiers where voters vote | separately in different tiers. Hence, the system is coded as | consisting of three tiers in variable E5056, and of a single | tier in variables E5040-E5049. | ELECTION STUDY NOTES - HONG KONG (2016): E5056 | | Hong Kong has a unicameral legislature. The Legislative Council | of the HKSAR has 70 members. Half of the legislative council is | returned by geographic constituency (popular) elections; the | other half is returned by functional constituency elections. | Geographical Constituency is treated here as the first segment | of the LegCo. | There are two parts of the Functional Constituencies (FCs): the | traditional FCs and the District Council (Second) FC. | Only the District Council (Second) FC is based on direct | popular elections. Therefore, it is treated here as the | second segment of the LegCo. This segment returns 5 LegCo | members and was introduced by an electoral reform in 2010. | | SEE ELECTION STUDY NOTES - HONG KONG (2016): E5040 for more | details. | ELECTION STUDY NOTES - ITALY (2018): E5056 | | Italy uses a mixed-member majoritarian system consisting of | three components. In the majoritarian component which accounts | for about 1/3 of the seats, candidates supported by electoral | coalitions (or single parties) compete in single-member | districts under plurality rule. Approximately 2/3 of the seats | are distributed proportionally among parties according to the | results at the national level. | Finally, 12 members are elected from multi-member constituencies | abroad, using the proportional representation system. | ELECTION STUDY NOTES - NORWAY (2017): E5056 | | The Norwegian Parliament comprises 169 seats in two tiers: | 150 members are elected in 19 multi-member districts using | proportional representation. The remaining 19 seats are | compensatory and are allocated to parties that receive 4%+ of | the national vote. These seats are known as "members at large" | and are seen as a means of evening out discrepancies between | the number of votes received and the number of seats in the | Storting. The distribution is based on a comparison of the | actual distribution of seats with what would have been occurred | had the country been treated as on big constituency, thus | allowing a determination to be made as to which parties are | under-represented. While voters do not cast a ballot directly | for this second tier and the seats are awarded at the national | level (albeit dispersed at the constituency level), the tiers | are considered linked because a voter casts only one ballot for | both tiers and the fact that allocation of the 19 additional | seats in part depends on how many seats are won by a party list | in the first tier. | For more, see: | https://www.stortinget.no/en/In-English/About-the-Storting/ | Elections/ | (Date accessed: March 23, 2020). | ELECTION STUDY NOTES - SOUTH KOREA (2016): E5056 | | Korea employs a mixed-member majoritarian system that combines | 253 single-member districts (first tier) with 47 proportional | representation (second tier) seats, elected from a single | nationwide district. Each voter casts two votes, one for | an individual candidate in the SMD segment, and one for a | closed party list in the PR segment. | ELECTION STUDY NOTES - TAIWAN (2016 & 2020): E5056 | | Taiwan uses a mixed-member majoritarian (MMM) system, and the | total number of seats is 113. The seats are distributed via two | segments (tiers). The first segment is represented by 73 seats, | elected in single-member districts (SMD). The second segment is | a nationwide district employing a proportional representation | system. In addition, six seats are reserved for aboriginal | groups. These seats are elected using the same system as the | first segment (SMD). | ELECTION STUDY NOTES - URUGUAY (2019): E5056 | | SEE ELECTION STUDY NOTES - URUGUAY (2019): E5055. --------------------------------------------------------------------------- E5057 >>> LINKED ELECTORAL SEGMENTS (TIERS) --------------------------------------------------------------------------- Whether countries with multiple segments (tiers) have linked (connected) or unlinked (unconnected) segments (tiers). .................................................................. 1. YES 5. NO 6. [SEE ELECTION STUDY NOTES] 7. NOT APPLICABLE 9. MISSING | VARIABLE NOTES: E5057 | | Definition: Linkage occurs whenever (i) unused votes from one | electoral segment (tier) are used at another level or (ii) the | allocation of seats in one segment (tier) is conditional on the | seats received in another segment (tier). | The definition of E5057 is taken from Matt Golder's database | about Democratic Electoral Systems Around the World, 1946-2011 | (http://mattgolder.com/elections; Date accessed: April 05, 2019). | | E5057 primarily concerns the Lower House election. However, if a | particular study is focused on the Upper House or Presidential | election, it may report results for these elections, | respectively. | | Source of data: CSES Macro Report and Publicly Available Sources | ELECTION STUDY NOTES - AUSTRIA (2017): E5057 | | The Austrian electoral system is a (non-mixed) proportional | representation system with three segments or tiers. These | correspond to the federal level tier, the Land level tier (or | state level) and the regional districts tier. Counting and | allocation of seats passes through each of these levels, and | as a consequence is a three-step process. In first place in each | Laender a Hare quota is calculated and used to distribute seats | across the regional districts. That is, parties are allocated | seats from each regional district depending on how often they | exceeded the Land level specified quota. Followed by these seats | are allocated at the Land level tier, also following the Land | level quota. Finally, at the national level seats are | distributed following the D'Hondt system. Seats that have been | already allocated in the first and second tiers are deducted | from the number of seats each party obtains at the national | level. Only those parties that obtain more than 4% of the | national valid votes or one seat from the regional | constituencies qualify to receive seats from the Laender and | National seat distribution. Given this last element the | electoral system is coded as linked. | ELECTION STUDY NOTES - DENMARK (2019): E5057 | | SEE ELECTION STUDY NOTES - DENMARK (2019): E5040 and ELECTION | STUDY NOTES - DENMARK (2019): E5056. | ELECTION STUDY NOTES - ITALY (2018): E5057 | | Voters could make a sign (1) on the district candidate's name | (1st segment), (2) on a party list supporting a district | candidate (2nd segment), (3) on both the candidate's name and | the party list supporting the candidate. However, it is | important to note that split ballots are not allowed, which | makes the voting system nearly identical as if votes had a | single vote. So it can be said that the segments are linked, | although the seat distribution in different segments is not | strictly conditional on the seats received in another segment | (tier). Also SEE ELECTION STUDY NOTES - ITALY (2018): E5055. | ELECTION STUDY NOTES - MEXICO (2018): E5057 | | In Mexico, each voter's vote is counted twice; once for the | single member district contest, and a second time for the | regional PR contest (SEE ELECTION STUDY NOTES - MEXICO (2018): | E5040_1 & E5040_2 for details). | This means that split ballots are not possible. So it could | be argued that the segments are linked, although the seat | distribution in different segments is not strictly conditional | on the seats received in another segment (tier). | ELECTION STUDY NOTES - NEW ZEALAND (2017 & 2020): E5057 | | The two tiers are linked with the "second vote" for the national | party list (tier 2) acting as a compensatory mechanism to tier 1 | ("constituency vote"), ensuring that the total number of seats | each party wins is nearly proportional to its total vote. Tier 2 | seats are allocated through a national party list using | proportional representation based on the Sainte-Lague Formula. | ELECTION STUDY NOTES - SOUTH KOREA (2016): E5057 | | In Korea's mixed electoral system, seats of both tiers are | allocated separately; each party is allocated its proportionate | share of the PR seats plus the SMD seats won by its candidates. | Thus, its segments are classified as not being linked. | ELECTION STUDY NOTES - SWEDEN (2018): E5057 | | There are 39 supplementary seats which are distributed to ensure | proportionality. Having aggregated the seats for each party in | each constituency (310 seats in total), a new distribution of | seats is conducted, based on the total votes for each party at | the national level. As such, the 39 supplementary seats are | allocated to ensure the result is as close as possible to | the proportional result nationally. | | Source of data: Valmyndigheten, | https://www.val.se/servicelankar/other-languages/ | english-engelska/electoral-system/distribution-of-seats.html | (Date accessed: June 05, 2021). | ELECTION STUDY NOTES - THAILAND (2019): E5057 | | SEE ELECTION STUDY NOTES - THAILAND (2019): E5040 for more | details. --------------------------------------------------------------------------- E5058 >>> DEPENDENT FORMULAE IN MIXED SYSTEMS --------------------------------------------------------------------------- Whether the two electoral formulas used in a mixed system are dependent or independent. .................................................................. 1. INDEPENDENT 2. INDEPENDENT/DEPENDENT 3. DEPENDENT 7. NOT APPLICABLE 9. MISSING | VARIABLE NOTES: E5058 | | Definition: A dependent mixed system is one in which the | application of one formula is dependent on the outcome produced | by the other formula. An independent mixed system is one in which | the two electoral formulas are implemented independently of each | other. | The definition of E5058 is taken from Matt Golder's database | about Democratic Electoral Systems Around the World, 1946-2011 | (http://mattgolder.com/elections; Date accessed: April 05, 2019). | | E5058 primarily concerns the Lower House election. However, if a | particular study is focused on the Upper House or Presidential | election, it may report results for these elections, | respectively. | | Source of data: CSES Macro Report and Publicly Available Sources | ELECTION STUDY NOTES - FRANCE (2017): E5058 | | French 2017 study is focused on Presidential elections. | ELECTION STUDY NOTES - ITALY (2018): E5058 | | The application of the formulae in the two electoral tiers is | mutually independent. However, the voting system does not | allow split-ticket voting, so the election outcome in the two | segments are closely connected. | Also SEE ELECTION STUDY NOTES - ITALY (2018): E5055 and ELECTION | STUDY NOTES - ITALY (2018): E5057. | ELECTION STUDY NOTES - MEXICO (2018): E5058 | | In Mexico, each voter's vote is counted twice; once for the | single member district contest, and a second time for the | regional PR contest (SEE ELECTION STUDY NOTES - MEXICO (2018): | E5040_1 & E5040_2 for details). | Hence, Mexico's mixed electoral system is classified as | independent because the formulas are applied independently | although they are based on the single vote. | ELECTION STUDY NOTES - THAILAND (2019): E5058 | | SEE ELECTION STUDY NOTES - THAILAND (2019): E5040 for more | details. --------------------------------------------------------------------------- E5059 >>> SUBTYPES OF MIXED ELECTORAL SYSTEMS --------------------------------------------------------------------------- Sub-types of mixed electoral systems. .................................................................. 1. COEXISTENCE 2. SUPERPOSITION 3. FUSION 4. CORRECTION 5. CONDITIONAL 6. [SEE ELECTION STUDY NOTES] 7. NOT APPLICABLE 9. MISSING | VARIABLE NOTES: E5059 | | The definition of E5059 is taken from Matt Golder's database | about Democratic Electoral Systems Around the World, 1946-2011 | (http://mattgolder.com/elections; Date accessed: April 05, 2019). | | COEXISTENCE: This is a system in which some districts use a | majoritarian formula, while others employ a proportional formula | in a single electoral segment (tier). Coexistence systems are | independent mixed systems. | | SUPERPOSITION: This is a system in which a majoritarian and | proportional formula are applied in independent electoral | districts. | | FUSION: This is a system in which majoritarian and proportional | formulas are used in an independent manner within a single | district. | | CORRECTION: This is a system in which seats distributed by | proportional representation in one set of districts are used to | correct the distortions created by the majoritarian formula in | another. Correction systems are a dependent form of mixed system. | | CONDITIONAL: This is a system in which the actual use or not of | one electoral formula depends on the outcome produced by the | other. Conditional systems are a dependent form of mixed system. | | E5059 primarily concerns the Lower House election. However, if a | particular study is focused on the Upper House or Presidential | election, it may report results for these elections, | respectively. | | Source of data: Publicly Available Sources | ELECTION STUDY NOTES - FRANCE (2017): E5059 | | French 2017 study is focused on Presidential elections. | ELECTION STUDY NOTES - THAILAND (2019): E5059 | | SEE ELECTION STUDY NOTES - THAILAND (2019): E5040 for more | details. --------------------------------------------------------------------------- E5060 >>> NUMBER OF ELECTORAL DISTRICTS - LOWEST SEGMENT (TIER) - LOWER HOUSE --------------------------------------------------------------------------- Number of electoral districts/constituencies in the first or lowest electoral segment (tier) for the lower house of the legislature. .................................................................. 001. [SEE ELECTION STUDY NOTES] 002-900. NUMBER OF ELECTORAL DISTRICTS 999. MISSING | VARIABLE NOTES: E5060 | | Source of data: CSES Macro Report and Publicly Available Sources | ELECTION STUDY NOTES - AUSTRALIA (2019): E5060 | | The number of seats in the lower house increased by 1 | from the 2013 and 2016 elections, where 150 seats were | contested due to redistribution of federal divisions in | Victoria, South Australia and the ACT due to updated | population data with increases in Victoria and ACT | necessitating a seat gain for each and a seat reduction in SA. | ELECTION STUDY NOTES - AUSTRIA (2017): E5060 | | The Austrian electoral system consists of three overlapping | tiers. The first tier is made up of 39 regional electoral | districts, the second tier of 9 Land or state-level electoral | districts and the third tier of one nationwide electoral | district. Also SEE ELECTION STUDY NOTES - AUSTRIA (2017): E5057. | ELECTION STUDY NOTES - BELGIUM-FLANDERS (2019): E5060 | | These data represent the number of electoral districts in | Flanders only. In Belgium, there are 11 electoral districts: 5 | in Flanders, 5 in Wallonia, and the Brussels Capital Region. | ELECTION STUDY NOTES - BELGIUM-WALLONIA (2019): E5060 | | These data represent the number of electoral districts in | Wallonia only. In Belgium, there are 11 electoral districts: 5 | in Flanders, 5 in Wallonia, and the Brussels Capital Region. | ELECTION STUDY NOTES - BRAZIL (2018): E5060 | | All 513 members of the Chamber of Deputies (federal deputies) | are elected from 27 multi-member constituencies corresponding | to the states and Federal District, varying in size from eight | to 70 seats. The Chamber elections are held using open list | proportional representation. | ELECTION STUDY NOTES - CHILE (2017): E5060 | | The 2017 elections were the first ones to be held after the | implementation of a new electoral law in 2015. | The Lower House elections in 2017 were conducted in 28 multi- | member electoral districts (between 3 and 8 seats per district), | following the open-list proportional system. The size of the | House of Deputies increased from 120 to 155 representatives. | ELECTION STUDY NOTES - DENMARK (2019): E5060 | | Mainland Denmark is divided into three electoral provinces: | Copenhagen, Sealand-Southern Denmark, and Northern Jutland. The | three provinces are subdivided into a nationwide total of ten | multi-member constituencies for mainland Denmark. There is an | additional layer below these ten multi-member constituencies - | classified as nomination districts which number 92, but which | have no importance regarding seat allocation. Rather they | influence candidate nomination and electoral administration. | | Source of data: The Parliamentary Electoral System in Denmark, | p. 4-5, available at: https://www.thedanishparliament.dk/ | -/media/pdf/publikationer/english/the-parliamentary-system-of | -denmark_2011.ashx (Date accessed: October 14, 2021). | ELECTION STUDY NOTES - FINLAND (2019): E5060 | | The number of constituencies in the Parliamentary election of | 2019 was 13. There are 200 MPs in total. The number of MPs per | constituency is decided before each election based on the number | of inhabitants in each constituency. In the Parliamentary | election of 2019, the number of MPs on the mainland | constituencies varied between 7 (in the constituency of Lapland) | and 36 (Uusimaa). Of the 200 MPs, 199 are elected in mainland | Finland. Moreover, the constituency of the autonomous Aland | Islands elects 1 MP according to the Election Act. | ELECTION STUDY NOTES - GREAT BRITAIN (2017 & 2019): E5060 | | These data represent the number of electoral districts in the | United Kingdom - England, Scotland, Wales, and Northern Ireland. | However, the British Election Studies do not include | respondents from Northern Ireland. Excluding Northern Ireland's | 18 parliamentary seats means the number of electoral districts | in Great Britain is 632. | ELECTION STUDY NOTES - GREECE (2015 & 2019): E5060 | | Of the 300 members of parliament, 250 are elected proportionally | in 56 (59 in 2019) constituencies. | According to Greek Constitution (Article 54.3), part of the | Parliament (no more than 1/20) may be elected not in a | specified constituency but rather throughout the country at | large. These are the State Deputies, whose exact number depends | on the total electoral strength of each party. | The remaining 50 seats are awarded to the party receiving the | largest share of the vote, as a 'premium'. | ELECTION STUDY NOTES - HONG KONG (2016): E5060 | | Thirty-five members of the Legislative Council of the HKSAR are | elected directly, on the basis of five geographic electoral | constituencies. | ELECTION STUDY NOTES - INDIA (2019): E5060 | | MPs are elected from 543 single-member constituencies using | first-past-the-post voting. The President of India can appoint | an additional two members from the Anglo-Indian community (this | feature of the electoral system was abolished in January 2020). | ELECTION STUDY NOTES - ISRAEL (2020): E5060 | | Israel has a single electoral constituency with the country | operating as a nationwide district. | ELECTION STUDY NOTES - JAPAN (2017): E5060 | | The Lower house (465 directly elected members) consists of two | segments - majoritarian and proportional. The first or lowest | segment consists of 289 single-member constituencies, elected | via a simple majority voting system. | ELECTION STUDY NOTES - LATVIA (2018): E5060 | | The 100 members of the Saeima (Latvian single chamber Parliament) | are elected by open list proportional representation from five | multi-member constituencies (Kurzeme, Latgale, Riga (in which | overseas votes are counted), Vidzeme and Zemgale) between 13 and | 32 seats in size. | ELECTION STUDY NOTES - MONTENEGRO (2016): E5060 | | Montenegro has a single electoral constituency with the country | operating as a nationwide district. | ELECTION STUDY NOTES - NETHERLANDS (2017 & 2021): E5060 | | The Netherlands has a single electoral constituency with | the country operating as a nationwide district. | ELECTION STUDY NOTES - NEW ZEALAND (2017): E5060 | | Officially, there are 71 electoral constituencies at tier 1 | (although this can alter if there are overhang seats - SEE | ELECTION STUDY NOTES - NEW ZEALAND (2017): E5072 for more), made | up of 64 constituencies representing the general population and | 7 Maori constituencies. | The latter provides special representation to New Zealand's Maori | community. Maori electorates were introduced in 1867 and operate | in the same way as general constituencies but include Maori | electors who have decided to place their name on the Maori | electoral roll rather than the general electoral roll. | ELECTION STUDY NOTES - NEW ZEALAND (2020): E5060 | | Officially, there are 72 electoral constituencies at tier 1 | (although this can alter if there are overhang seats - SEE | ELECTION STUDY NOTES - NEW ZEALAND (2020): E5072 for more), made | up of 65 constituencies representing the general population and | 7 Maori constituencies. | The latter provides special representation to New Zealand's Maori | community. Maori electorates were introduced in 1867 and operate | in the same way as general constituencies but include Maori | electors who have decided to place their name on the Maori | electoral roll rather than the general electoral roll. | ELECTION STUDY NOTES - NORWAY (2017): E5060 | | In the first tier, there are 19 multi-member districts, | electing 150 representatives in total. | ELECTION STUDY NOTES - PERU (2021): E5060 | | The 130 members of Congress are elected in 27 multi-member | districts using closed list proportional representation. | The districts represent Peru's 25 regions, with a special | district for metropolitan Lima and Peruvians living overseas. | The representatives are elected for a 5-year term. Previously, | overseas voters' votes were counted in the metropolitan Lima | district, hence the increase of one district from 26 to 27 | for the 2021 elections. | ELECTION STUDY NOTES - PORTUGAL (2019): E5060 | | Portugal has 22 electoral districts in total: 18 in mainland | Portugal plus four other constituencies covering the overseas | (split into two, depending on whether they reside in Europe or | outside Europe) and two remaining districts for the overseas | territories of Madeira and the Azores. | ELECTION STUDY NOTES - ROMANIA (2016): E5060 | | According to the new electoral law (passed in 2015), elections | for the Lower House are based on 43 multi-member constituencies: | 41 represent counties, the remaining two represent the Bucharest | municipality, and the Romanian citizens domiciled or residing | abroad (Article 3, Law No. 208 of 20 July 2015). | ELECTION STUDY NOTES - SLOVAKIA (2020): E5060 | | Slovakia has a single electoral constituency with the country | operating as a nationwide district. | ELECTION STUDY NOTES - SWEDEN (2018): E5060 | | In the first tier, there are 29 multi-member districts, | electing 310 representatives in total. | ELECTION STUDY NOTES - TUNISIA (2019): E5060 | | The 217 members of the Assembly of the Representatives of the | People are elected by closed-list proportional representation in | 33 multi-member constituencies (27 in Tunisia and 6 representing | Tunisians residing abroad). The 27 multi-member constituencies | in Tunisia provide 199 seats, between four and 10 seats each). | The remaining 18 seats are allocated to expatriate constituencies | in France (two constituencies, five seats each), one in Italy | (three seats) and one in Germany (one seat), one for the rest of | Europe and the Americas (two seats), and one for the Arab States | and the rest of the world (two seats). Seats were allocated using | the largest remainder method. | ELECTION STUDY NOTES - TURKEY (2018): E5060 | | The 600 members of the Grand National Assembly of Turkey | are elected by party-list proportional representation in | 87 multi-member electoral districts. | The electoral districts correspond to 77 of Turkey's 81 | provinces. Due to their large populations, the provinces of | Bursa and Izmir are divided into two districts, while the | provinces of Ankara and Istanbul are each divided into three. | ELECTION STUDY NOTES - URUGUAY (2019): E5060 | | In Parliamentary elections (Upper and Lower House), the | Uruguayan electoral system is called Multiple Simultaneous Vote. | Each voter votes simultaneously for a party and a closed and | blocked list of candidates. On a single sheet of paper, the | voter votes for the same party for the President of the | Republic, Upper House, and Lower House. Each party must have | only one Presidential candidate and may have multiple lists | for each chamber. | For the distribution of seats between the parties, for both | chambers, the relevant constituency is the national one. For | the distribution of seats for the Lower House within each | party, the constituency is by the department. --------------------------------------------------------------------------- E5061 >>> AVERAGE DISTRICT MAGNITUDE - LOWEST SEGMENT (TIER) - LOWER HOUSE --------------------------------------------------------------------------- Average district magnitude in the first or lowest electoral segment (tier). .................................................................. 001.00-900.00 NUMBER OF SEATS ELECTED PER DISTRICT 999. MISSING | VARIABLE NOTES: E5061 | | E5061 details the average district magnitude in the first | tier, calculated as the total number of seats allocated in the | lowest segment (tier) divided by the total number of districts in | that segment (tier).s | Source of data: CSES Macro Report and Publicly Available Sources | ELECTION STUDY NOTES - AUSTRIA (2017): E5061 | | The data represents the empirical average district magnitude | calculated from the total number of seats allocated in the 39 | first tier districts in the 2017 election. Average district | magnitude varies over time based on electoral results. | SEE ELECTION STUDY NOTES - AUSTRIA (2017): E5057 for more | details. | ELECTION STUDY NOTES - BELGIUM-FLANDERS (2019): E5061 | | These data represent the average district magnitude of districts | in Flanders only (87 seats across 5 electoral districts). | In Belgium, 150 seats are contested across 11 electoral districts | yielding an average district magnitude of 13.64. | ELECTION STUDY NOTES - BELGIUM-WALLONIA (2019): E5061 | | These data represent the average district magnitude of districts | in Wallonia only (48 seats across 5 electoral districts). Data | from the Brussels Capital Region is not included in the | calculation. In Belgium, 150 seats are contested across 11 | electoral districts yielding an average district magnitude of | 13.64. | ELECTION STUDY NOTES - CHILE (2017): E5061 | | The 2017 elections were the first ones to be held after the | implementation of a new electoral law in 2015. | The Lower House elections in 2017 were conducted in 28 multi- | member electoral districts (between 3 and 8 seats per district), | following the open-list proportional system. The size of the | House of Deputies increased from 120 to 155 representatives. | ELECTION STUDY NOTES - DENMARK (2019): E5061 | | These data represent the average district magnitude of districts | in mainland Denmark only (175 seats in total; of which 135 | are contested at the lowest tier) across 10 multi-member | constituencies. | ELECTION STUDY NOTES - FINLAND (2019): E5061 | | These data refer to the mainland multi-member constituencies | which give 199 out of 200 MPs. The constituency of the autonomous | Aland Islands always elects 1 MP. | ELECTION STUDY NOTES - GREECE (2015): E5061 | | The average district magnitude refers to the 250 seats | elected proportionally in 56 constituencies comprised of 48 | multi- and 8 single-seat constituencies. | ELECTION STUDY NOTES - GREECE (2019): E5061 | | The average district magnitude refers here to the 250 seats | elected proportionally in 59 constituencies. | ELECTION STUDY NOTES - HONG KONG (2016): E5061 | | Thirty-five members of the Legislative Council of the HKSAR are | directly elected on the basis of five geographic electoral | constituencies. The exact number of LegCo seats in each | constituency is decided according to the constituency population. --------------------------------------------------------------------------- E5062 >>> ELECTORAL FORMULA - LOWEST SEGMENT (TIER) - LOWER HOUSE --------------------------------------------------------------------------- The precise electoral formula used in the first or lowest electoral segment (tier) of the lower house. .................................................................. 10. PLURALITY 11. PLURALITY - SINGLE MEMBER DISTRICTS 12. PLURALITY - MULTI MEMBER DISTRICTS 20. MAJORITY 21. MAJORITY - RUN-OFF 22. MAJORITY - ALTERNATIVE 30. PROPORTIONAL REPRESENTATION 31. PR - D'HONDT 32. PR - LARGEST REMAINDER - DROOP 33. PR - LARGEST REMAINDER - HARE 34. PR - MODIFIED STE-LAGUE 98. OTHER [SEE ELECTION STUDY NOTES] 99. MISSING | VARIABLE NOTES: E5062 | | Source of data: CSES Macro Report and Publicly Available Sources | ELECTION STUDY NOTES - AUSTRALIA (2019): E5062 | | According to Parline: "Voters are required to express a | preference among all the candidates contesting the same seat. | A candidate is elected if he/she gains an absolute majority or | 50% + 1 vote. If none of the candidates in a division obtains | an absolute majority of the first preference votes, a second | round of counting is held. At this point, the candidate with the | least number of votes is eliminated, and the votes which he/she | obtained in the first round are redistributed among the | remaining candidates on the basis of the electors' second | choices. This procedure is repeated until such time as one of | the candidates obtains an absolute majority." | For details: http://www.ipu.org/parline-e/reports/2015_B.htm | (Date accessed: April 30, 2020). | ELECTION STUDY NOTES - COSTA RICA (2018): E5062 | | For parliamentary elections, Costa Rica uses proportional, | closed party list system. The 57 members of the Legislative | Assembly are elected through the largest remainder method from | seven multi-member constituencies with between four and 19 | seats, which are based on the seven provinces. For the | allocation of the seats in the National Assembly, the Electoral | Court uses a modified version of the Hare quota (half quota). | ELECTION STUDY NOTES - GREECE (2015 & 2019): E5062 | | The 250 seats are allocated proportionally using the Hagenbach- | Bischoff method. However, the data is coded with response 31 PR - | D'Hondt. The reason is that the Hagenbach-Bischoff method is | considered a variant of the D'Hondt method. Further, both systems | return identical results. | ELECTION STUDY NOTES - SLOVAKIA (2020): E5062 | | Slovakia uses the Hagenbach-Bischoff method to distribute seats, | a variant of the D'Hondt system. An electoral quota is | calculated by dividing the total number of valid votes won | by lists eligible for seats by the number of seats on offer plus | one (i.e., 150+1=151). The number of votes polled by each party | that surpasses the threshold is divided by the quota | (with any fractional remainder disregarded), and this gives | the number of seats each party is entitled to. Any seats that | remain unallocated after the application of this procedure | are distributed according to the largest remainder method. | | Source of data: http://www.electionresources.org/sk/ | (Date accessed: February 09, 2017) | ELECTION STUDY NOTES - SWEDEN (2018): E5062 | | Modified St-Lague method. "The permanent constituency seats | are distributed on the basis of the total number of votes gained | by the political parties in each constituency. Comparative | numbers are calculated for the parties that will take part in | the distribution of seats. The first comparative number is | obtained by dividing the parties' respective total number of | votes by 1.4. The party which receives the highest comparative | number is awarded the first seat in the constituency. That party | is then allocated a new comparative number, obtained by dividing | the party's votes by 3. The other parties keep their comparative | numbers until they are awarded a seat. When a party obtains its | second seat, its votes are divided by 5 to calculate the next | comparative number. For the third seat by 7 etc. This method of | calculation is referred to as the 'adjusted odd-number method'." | | Source of data: Valmyndigheten, | https://www.val.se/val-och-folkomrostningar/det-svenska- | valsystemet/rostrakning-och-valresultat/mandatfordelning.html | (Date accessed: June 05, 2021). | ELECTION STUDY NOTES - UNITED STATES (2016 & 2020): E5062 | | While a plurality of votes is sufficient in 48 states and the | District of Columbia, in the states of Georgia and Louisiana, | candidates need a majority of the vote to win. | In special elections in Georgia and all elections in Louisiana | a "jungle primary" operates (it operated in Louisiana since 1977) | The system employed is akin to the first round of a majority | run-off election system, whereby all candidates for an office | regardless of party affiliation, run against one another in one | election. If one candidate obtains a majority of the vote, they | win the office they are seeking outright, the only "primary" | where a candidate can actually achieve this without a run-off. | When a candidate does not win a majority of the vote, the top | two candidates, irrespective of party, go forward to a run-off | election, usually held one month later. | ELECTION STUDY NOTES - URUGUAY (2019): E5062 | | The Lower Chamber (Camara de Representantes; House of | Representatives) of the Uruguayan General Assembly consists | of 99 members. Seats are assigned among parties in a single | nationwide district, based on a proportional (d'Hondt) system. | The system uses closed lists and Double Simultaneous Vote (DSV) | in regional districts. | DVS is the system by which the voter votes synchronously in a | logical order: first by a party ("lema" or label or motto) and | then a list of candidates ("lista" or list). For more details | SEE ELECTION STUDY NOTES - URUGUAY (2019): E5001 and ELECTION | STUDY NOTES - URUGUAY (2019): E5003. --------------------------------------------------------------------------- E5063 >>> NUMBER OF ELECTORAL DISTRICTS - SECOND SEGMENT (TIER) - LOWER HOUSE --------------------------------------------------------------------------- Number of electoral districts or constituencies in the second electoral segment (tier) for the lower house of the legislature. .................................................................. 001-900. NUMBER OF ELECTORAL DISTRICTS 997. NOT APPLICABLE 999. MISSING | VARIABLE NOTES: E5063 | | Source of data: CSES Macro Report and Publicly Available Sources | ELECTION STUDY NOTES - AUSTRIA (2017): E5063 | | The Austrian electoral system has three segments or tiers. These | correspond to the federal level tier, the Land or state level | tier (9 districts) and the regional districts tier | (39 districts). | SEE ELECTION STUDY NOTES - AUSTRIA (2017): E5057 for more | details. | ELECTION STUDY NOTES - DENMARK (2019): E5063 | | There are 40 supplementary seats. Seats are allocated to | qualifying parties in strict proportionality to the number of | votes obtained by these parties. The basis of the calculation | is the pure Hare quota. Seats that remain unallocated by the | full quota are allocated based on the largest remainders. The | aggregate number of seats obtained by the party in all ten | multi-member constituencies is deducted from the number of | compensatory seats to which the party is entitled to - i.e., the | difference represents the party's share of the 40 compensatory | seats. | | Source of data: The Parliamentary Electoral System in Denmark, | p. 7-8, available at: https://www.thedanishparliament.dk/ | -/media/pdf/publikationer/english/the-parliamentary-system-of | -denmark_2011.ashx (Date accessed: October 14, 2021). | ELECTION STUDY NOTES - HONG KONG (2016): E5063 | | The District Council (Second) FC is treated here as the second | segment of the LegCo. This segment returns 5 LegCo members. In | this part of the election, the whole of Hong Kong functions as a | single constituency. | ELECTION STUDY NOTES - ITALY (2018): E5063 | | The national territory is divided into 27 regional or sub- | regional electoral districts. However, these units are | considered to be "pseudo-multi-member districts", because | districts do not actually account for the seat distribution, | which is based on national-level results. Hence, this variable | is coded "1". | ELECTION STUDY NOTES - JAPAN (2017): E5063 | | The second segment of the Lower House (proportional) is based | on 11 multi-member (6 to 28 seats) constituencies, in total | giving 176 seats (party list system, using the d'Hondt method | for the allocation of the seats. | ELECTION STUDY NOTES - NORWAY (2017): E5063 | | In addition to the 150 seats in 19 electoral districts, the | second tier comprises 19 "members at large" seats (for more | SEE ELECTION STUDY NOTES - NORWAY (2017): E5040_2). These seats | are allotted by the modified Saint-Lague method. | ELECTION STUDY NOTES - SWEDEN (2018): E5063 | | There are 39 supplementary seats which are distributed to ensure | proportionality. These seats are allocated by a system of | proportional representation based on the votes obtained | nationwide following the "adjusted odd-number method", SEE | ELECTION STUDY NOTES - SWEDEN (2018): E5062. | | Source of data: Valmyndigheten, | https://www.val.se/servicelankar/other-languages/ | english-engelska/electoral-system/distribution-of-seats.html | (Date accessed: June 05, 2021). | ELECTION STUDY NOTES - TAIWAN (2016 & 2020): E5063 | | Taiwan's Parliament (The Legislative Yuan) has 113 members. The | seats are distributed via two segments (tiers). The first | segment is represented by 73 seats, elected in single-member | districts (SMD). The second segment is a nationwide district | employing a proportional representation system. In addition, six | seats reserved for aboriginal groups. --------------------------------------------------------------------------- E5064 >>> AVERAGE DISTRICT MAGNITUDE - SECOND SEGMENT (TIER) - LOWER HOUSE --------------------------------------------------------------------------- Average district magnitude in the second electoral segment (tier). .................................................................. 001.00-900.00 NUMBER OF SEATS ELECTED PER DISTRICT 997. NOT APPLICABLE 999. MISSING | VARIABLE NOTES: E5064 | | E5064 details the average district magnitude in the second tier, | calculated as the total number of seats allocated in the second | segment (tier) divided by the total number of districts in that | segment (tier). | | Source of data: CSES Macro Report and Publicly Available Sources | ELECTION STUDY NOTES - AUSTRIA (2017): E5064 | | The number is the average district magnitude calculated on the | basis of the seats allocated in the nine second-tier districts | in the 2017 election. The average district magnitude varies over | time, depending on the electoral results. | ELECTION STUDY NOTES - GERMANY (2017 & 2021): E5064 | | The average district magnitude in Germany is liable to change | depending on whether overhang and leveling seats are | allotted or not. Without overhang seats, the value is 18.69 | which is the value the CSES data reflects (299 seats and 16 | electoral districts based on the states (laender)). | | In the 2017 election, there were 111 overhang and leveling | seats. The nominal size of the Bundestag is 598, but after the | 2017 elections, there were 709 MPs. Including these overhang | mandates in the district magnitude calculation yields a score of | 26.63. | In the 2021 election, there were 138 overhang and leveling | seats, meaning the size of the Bundestag was 736. Including these | 138 compensatory seats in this district magnitude calculation | yields a score of 27.31. | ELECTION STUDY NOTES - NEW ZEALAND (2017): E5064 | | The average district magnitude in New Zealand is liable to | change depending on whether compensatory seats are allotted or | not. Without compensatory seats the value is 49, which is | the value the CSES data reflects. | In the 2017 election, there were zero compensatory seats (the | total membership of the 2017 House of Representatives was 120). | ELECTION STUDY NOTES - NEW ZEALAND (2020): E5064 | | The average district magnitude in New Zealand is liable to | change depending on whether compensatory seats are allotted or | not. Without compensatory seats the value is 48, which is | the value the CSES data reflects. | In the 2020 election, there were zero compensatory seats (the | total membership of the 2020 House of Representatives was 120). --------------------------------------------------------------------------- E5065 >>> ELECTORAL FORMULA - SECOND SEGMENT (TIER) - LOWER HOUSE --------------------------------------------------------------------------- The precise electoral formula used in the second electoral segment (tier) of the lower house. .................................................................. 10. PLURALITY 11. PLURALITY - SINGLE MEMBER DISTRICTS 12. PLURALITY - MULTI MEMBER DISTRICTS 20. MAJORITY 21. MAJORITY - RUN-OFF 22. MAJORITY - ALTERNATIVE 30. PROPORTIONAL REPRESENTATION 31. PR - D'HONDT 32. PR - LARGEST REMAINDER - DROOP 33. PR - LARGEST REMAINDER - HARE 34. PR - MODIFIED STE-LAGUE 97. NOT APPLICABLE 98. OTHER [SEE ELECTION STUDY NOTES] 99. MISSING | VARIABLE NOTES: E5065 | | Source of data: CSES Macro Report and Publicly Available Sources --------------------------------------------------------------------------- E5066 >>> NUMBER OF ELECTORAL DISTRICTS - THIRD SEGMENT (TIER) - LOWER HOUSE --------------------------------------------------------------------------- Number of electoral districts or constituencies in the third electoral segment (tier) for the lower house of the legislature. .................................................................. 001-900. NUMBER OF ELECTORAL DISTRICTS 997. NOT APPLICABLE 999. MISSING | VARIABLE NOTES: E5066 | | E5066 is taken from Matt Golder's database about Democratic | Electoral Systems Around the World, 1946-2011 | (http://mattgolder.com/elections; Date accessed: November 21, | 2016). Original variable name: DISTRICTS3. | | Source of data: CSES Macro Report and Publicly Available Sources | ELECTION STUDY NOTES - AUSTRIA (2017): E5066 | | The Austrian electoral system has three segments or tiers. The | single federal electoral district represents the third tier, | while the remaining two are the Land or state level and the | regional tier. | SEE ELECTION STUDY NOTES - AUSTRIA (2017): E5057 for more | details. | ELECTION STUDY NOTES - ITALY (2018): E5066 | | Twelve seats in the Chamber of Deputies (and 6 the in Senate) are | reserved for Italians residing abroad. The election is based on | purely proportional system. --------------------------------------------------------------------------- E5067 >>> AVERAGE DISTRICT MAGNITUDE - THIRD SEGMENT (TIER) - LOWER HOUSE --------------------------------------------------------------------------- Average district magnitude in the third electoral segment (tier). .................................................................. 001.00-900.00 NUMBER OF SEATS ELECTED PER DISTRICT 997. NOT APPLICABLE 999. MISSING | VARIABLE NOTES: E5067 | | E5067 details the average district magnitude in the third tier, | calculated as the total number of seats allocated in the third | segment (tier) divided by the total number of districts in that | segment (tier). | E5067 is taken from Matt Golder's database about Democratic | Electoral Systems Around the World, 1946-2011 | (http://mattgolder.com/elections; Date accessed: November 21, | 2016). Original variable name: AVEMAG3. | | Source of data: CSES Macro Report and Publicly Available Sources | ELECTION STUDY NOTES - AUSTRIA (2017): E5067 | | The data refers to the district magnitude calculated based on | the number of seats allocated in the single third-tier district | in the 2017 election. | District magnitude varies over time based on electoral results. | SEE ELECTION STUDY NOTES - AUSTRIA (2017): E5057 for more | details. | ELECTION STUDY NOTES - ITALY (2018): E5067 | | SEE ELECTION STUDY NOTES - ITALY (2018): E5066. --------------------------------------------------------------------------- E5068 >>> ELECTORAL FORMULA - THIRD SEGMENT (TIER) - LOWER HOUSE --------------------------------------------------------------------------- The precise electoral formula used in the third electoral segment (tier) of the lower house. .................................................................. 10. PLURALITY 11. PLURALITY - SINGLE MEMBER DISTRICTS 12. PLURALITY - MULTI MEMBER DISTRICTS 20. MAJORITY 21. MAJORITY - RUN-OFF 22. MAJORITY - ALTERNATIVE 30. PROPORTIONAL REPRESENTATION 31. PR - D'HONDT 32. PR - LARGEST REMAINDER - DROOP 33. PR - LARGEST REMAINDER - HARE 34. PR - MODIFIED STE-LAGUE 97. NOT APPLICABLE 98. OTHER [SEE ELECTION STUDY NOTES] 99. MISSING | VARIABLE NOTES: E5068 | | Source of data: CSES Macro Report and Publicly Available Sources --------------------------------------------------------------------------- E5069 >>> NUMBER OF SEATS ABOVE THE FIRST SEGMENT (TIER) - LOWER HOUSE --------------------------------------------------------------------------- The number of seats allocated in electoral districts/constituencies above the first or lowest segment (tier). .................................................................. 000-900. NUMBER OF SEATS 999. MISSING | VARIABLE NOTES: E5069 | | E5069 may include seats allocated in several different upper | segments (tiers). | Source of data: CSES Macro Report and Publicly Available Sources | ELECTION STUDY NOTES - AUSTRIA (2017): E5069 | | The number is based on the seat allocation after the 2017 | election. The number of distributed seats within each tier varies | from election to election, depending on the electoral result. | SEE ELECTION STUDY NOTES - AUSTRIA (2017): E5057 for more | details. | ELECTION STUDY NOTES - GERMANY (2017 & 2021): E5069 | | This number of seats allocated in the second (list) tier can | change depending on whether overhang and leveling seats are | allotted or not. Without compensatory seats, the value is always | 299, which is the value the CSES data reflects. | In the 2021 election, there were 138 overhang and leveling seats, | and including these in this metric yields a score of 437. | ELECTION STUDY NOTES - GREECE (2015 & 2019): E5069 | | The data refers to the 50 seats awarded to the party receiving | the largest share of the vote, as a 'premium'. | SEE ELECTION STUDY NOTES - GREECE (2015 & 2019): E5060 for more | details. | ELECTION STUDY NOTES - HONG KONG (2016): E5069 | | The District Council (Second) FC is treated here as the second | segment of the LegCo. This segment returns 5 LegCo members. In | this part of the election, the whole of Hong Kong functions as a | single constituency. | ELECTION STUDY NOTES - TAIWAN (2016 & 2020): E5069 | | Taiwan's Parliament (The Legislative Yuan) has 113 members. The | seats are distributed via two segments (tiers). The first | segment is represented by 73 seats, elected in single-member | districts (SMD). The second segment is a nationwide district | employing a proportional representation system. In addition, six | seats are reserved for aboriginal groups. --------------------------------------------------------------------------- E5070 >>> PERCENTAGE OF SEATS ABOVE THE FIRST SEGMENT (TIER) - LOWER HOUSE --------------------------------------------------------------------------- Percentage of seats allocated in electoral districts above the lowest segment (tier). .................................................................. 000.00-100.00 PERCENTAGE OF SEATS 999. MISSING | VARIABLE NOTES: E5070 | | Source of data: CSES Macro Report and Publicly Available Sources | ELECTION STUDY NOTES - AUSTRIA (2017): E5070 | | The number (91/183=49.73) is based on the seat allocation after | the 2017 election. The number of seats distributed within each | tier varies from election to election, depending on electoral | result. | SEE ELECTION STUDY NOTES - AUSTRIA (2017): E5057 for more | details. | ELECTION STUDY NOTES - GERMANY (2017 & 2021): E5070 | | This percentage of seats changes depending on whether overhang | and leveling seats are allotted or not. Without the overhang | seats, the value is always 50% which is the value the CSES | data reflects. | ELECTION STUDY NOTES - GREECE (2015 & 2019): E5070 | | The data refers to the 50 seats awarded to the party receiving | the largest share of the vote, as a 'premium'. | SEE ELECTION STUDY NOTES - GREECE (2015 & 2019): E5060 for more | details. | ELECTION STUDY NOTES - HONG KONG (2016): E5070 | | The District Council (Second) FC is treated here as the second | segment of the LegCo. This segment returns 5 LegCo members. | These data are calculated taking into account only directly | elected seats (Geographic constituency of 35 seats, and the | Second FC with five seats (40 seats in total). | SEE ELECTION STUDY NOTES - HONG KONG (2016): E5038 for more | details about the electoral system. | ELECTION STUDY NOTES - NEW ZEALAND (2017): E5070 | | The number of seats allocated in the second tier can change | depending on whether compensatory seats are allotted or | not. Without compensatory seats, the value is always 40.8% which | is the value the CSES data reflects. No compensatory seats were | allocated in tier 2 in the 2017 elections. | ELECTION STUDY NOTES - NEW ZEALAND (2020): E5070 | | The number of seats allocated in the second tier can change | depending on whether compensatory seats are allotted or | not. Without compensatory seats, the value is always 40.0% which | is the value the CSES data reflects. No compensatory seats were | allocated in tier 2 in the 2020 elections. --------------------------------------------------------------------------- E5071 >>> FUSED VOTE --------------------------------------------------------------------------- Whether or not a fused vote was used for Presidential and legislative elections. .................................................................. 1. YES 5. NO 7. NOT APPLICABLE 9. MISSING | VARIABLE NOTES: E5071 | | Definition: A fused vote is when a citizen casts a single ballot | for the elections of more than one political office. | E5071 captures when the single ballot is for the Presidency and | the legislature. Citizens are unable to divide their votes among | the candidates or lists of different parties. Split-ticket voting | is expressly prohibited. | Source of data: CSES Macro Report and Publicly Available Sources | ELECTION STUDY NOTES - ITALY (2018): E5071 | | In Italy, votes for Presidential and legislative elections | cannot be fused. However, the votes for the two Houses of the | Parliament are fused. | ELECTION STUDY NOTES - URUGUAY (2019): E5071 | | Voters have a single vote. However, each Ballot contains a | Presidential ticket, a closed list for Senate, and a closed | list for the Lower Chamber. Each Ballot must necessarily | contain lists of a single party. Electors cast votes necessarily | (for President and two chambers) for the same party. Hence, the | election results are basically identical for all three | institutions - both houses of the Parliament, and for the | President (first round). --------------------------------------------------------------------------- E5072 >>> SIZE OF THE LOWER HOUSE --------------------------------------------------------------------------- Total number of seats in the lower house of the legislature during the election year. .................................................................. 001-900. SEATS IN THE LOWER HOUSE 999. MISSING. | VARIABLE NOTES: E5072 | | Source of data: CSES Macro Report and Publicly Available Sources | ELECTION STUDY NOTES - BELGIUM-FLANDERS (2019): E5072 | | The Belgian Parliament has 150 members in total. Eighty-seven | are elected in Belgium-Flanders, 48 in Belgium-Wallonia, and | the remaining 15 are elected from the Brussels Capital Region. | ELECTION STUDY NOTES - BELGIUM-WALLONIA (2019): E5072 | | The Belgian Parliament has 150 members in total. Eighty-seven | are elected in Belgium-Flanders, 48 in Belgium-Wallonia, and | the remaining 15 are elected from the Brussels Capital Region. | ELECTION STUDY NOTES - DENMARK (2019): E5072 | | The Danish Folketing has 179 members, 175 of which are elected | in mainland Denmark and the remaining four from the territories | of Greenland and the Faroe Islands (two seats each). | ELECTION STUDY NOTES - GERMANY (2017): E5072 | | The Bundestag nominally has 598 members: 299 members elected at | the lower tier and 299 members elected in the upper tier. The | German system, however, allows for overhang and leveling | seats. In the 2017 elections, there were 111 of these which | resulted in a total number of 709 members of the Bundestag. | ELECTION STUDY NOTES - GERMANY (2021): E5072 | | Theoretically, the Bundestag comprises of 598 seats. Half | of the members (299) members are elected in single-member | districts using the first past the post electoral system | (the "first vote"). The remaining 299 seats are filled by | proportional representation using the party list (the "second | vote"). These seats are distributed according to the Saint | Lague method. | Seat allocation between tier 1 and tier 2 is linked. When | parties/blocs win sufficient seats in tier 1 (single member | districts, "first vote") to qualify for allocation of seats in | tier 2 (list vote, "second vote"), despite failing to meet the | tier 2 threshold (in Germany's case, 5% of the list vote), the | allocation of these seats to a party/bloc creates what are | colloquially known as "overhang seats". Accordingly, and to | ensure a proportional allocation between the share of votes and | share of seats nationwide, compensatory seats (sometimes | referred to as leveling seats) are also allocated. | In the 2021 Bundestag elections, there were 138 compensatory | seats, resulting in the size of the Bundestag being 736, the | largest in its history. | ELECTION STUDY NOTES - GREAT BRITAIN (2017 & 2019): E5072 | | These data represent the number of electoral districts in the | United Kingdom - England, Scotland, Wales, and Northern Ireland. | However, the British Election Studies do not include | respondents from Northern Ireland. Excluding Northern Ireland's | 18 parliamentary seats means the number of electoral districts | in Great Britain is 632. | ELECTION STUDY NOTES - HONG KONG (2016): E5072 | | The Legislative Council (LegCo) in Hong Kong is composed of 70 | members, 35 of which are returned by Geographical Constituency | elections and another 35 by Functional Constituency elections. | SEE ELECTION STUDY NOTES - HONG KONG (2016): E5040 for more | details about the electoral system. | ELECTION STUDY NOTES - INDIA (2019): E5072 | | MPs are elected from 543 single-member constituencies using | first-past-the-post voting. The President of India can appoint | additional two members from the Anglo-Indian community (this | feature of the electoral system was abolished in January 2020). | ELECTION STUDY NOTES - NEW ZEALAND (2017 & 2020): E5072 | | Conventionally, The New Zealand Parliament has 120 members. | However, this can sometimes increase due to 'overhang' seats, | which arise when a party gains more constituency seats (tier 1) | than its party list vote (tier 2) would entitle it to on a | proportional basis. In 2017 and 2020, there were 0 compensatory | seats, so the size of parliament was 120 in both instances. | ELECTION STUDY NOTES - ROMANIA (2016): E5072 | | The size of the Lower house is defined according to the rule | "The representation rate for the election of the Chamber of | Deputies is one Deputy for 73,000 inhabitants" (Article 2, Law | No. 208 of 20 July 2015). In 2016, parties and candidates | competed for 329 seats in the Lower House. | ELECTION STUDY NOTES - TURKEY (2018): E5072 | | The Grand National Assembly of Turkey is the unicameral | Turkish legislature. After the 2017 constitutional referendums, | the Assembly increased the number of MPs from 550 to 600. | ELECTION STUDY NOTES - URUGUAY (2019): E5072 | | The Lower Chamber (Camara de Representantes; House of | Representatives) of the Uruguayan General Assembly consists | of 99 members. Seats are assigned among parties in a single | nationwide district, based on a proportional (d'Hondt) system. --------------------------------------------------------------------------- E5073 >>> CONSTITUTIONAL FEDERAL STRUCTURE --------------------------------------------------------------------------- Is the country federal? .................................................................. 1. YES 5. NO 9. MISSING | VARIABLE NOTES: E5073 | | Federations are "compound polities, combining strong constituent | units and strong general government, each possessing powers | delegated to it by the people through a constitution and each | empowered to deal directly with the citizens in the exercise of | the legislative, administrative and taxing powers, and each | directly elected by the citizens." (Watts 2008, page 12). | | Source of data: Ronald L. Watts, (2008). "Comparing Federal | Systems". Institute of Intergovernmental Relations, Queen's | University, Kingston, Ontario, Canada. --------------------------------------------------------------------------- E5074 >>> NUMBER OF LEGISLATIVE CHAMBERS --------------------------------------------------------------------------- The number of legislative chambers. .................................................................. 1. ONE LEGISLATIVE CHAMBER; UNICAMERAL LEGISLATURE 2. TWO LEGISLATIVE CHAMBERS; BICAMERAL LEGISLATURE 9. MISSING | VARIABLE NOTES: E5074 | | Some of the countries have indirectly elected Upper Chambers. | | Source of data: CSES Macro Report and Publicly Available Sources --------------------------------------------------------------------------- E5075 >>> PERCENTAGE OF WOMEN IN PARLIAMENT --------------------------------------------------------------------------- Percentage of women in parliament. .................................................................. 00.00-100.00 PERCENTAGE OF WOMEN IN PARLIAMENT 999. MISSING | VARIABLE NOTES: E5075 | | Source of data: | - CSES Macro Report | - World Bank (n.d.). Proportion of seats held by women in | national parliaments (%). Available at: https://data. | worldbank.org/indicator/SG.GEN.PARL.ZS | (Date accessed: October 18, 2018). | | Users are advised that there is normally a two or three-year time | lag between these estimates becoming available. Consequently, for | Advance Releases of the CSES (and possibly Full Releases), data | may not be available at the time of coding. In circumstances | where this occurs, the polity will be listed as DATA UNAVAILABLE | in the VARIABLE NOTES below. Should data become available | between an Advance Release of CSES and a Full Release of CSES, | data for these polities will be included in a subsequent release | of the CSES. | ELECTION STUDY NOTES - HONG KONG (2016): E5075 | | Data was taken from the Election Guide, International | Foundation for Electoral Systems (IFES), | http://www.electionguide.org/elections/id/2597/. | (Date accessed: April 30, 2020) | ELECTION STUDY NOTES - TAIWAN (2016): E5075 | | Data was taken from the Election Guide, International | Foundation for Electoral Systems (IFES), | http://www.electionguide.org/ elections/id/2736/. | (Date accessed: May 08, 2019). | ELECTION STUDY NOTES - TAIWAN (2020): E5075 | | This information comes from the Central Electoral Commission | of Taiwan (https://web.cec.gov.tw/english/cms/le/32472) | (Date accessed: July 14, 2021). --------------------------------------------------------------------------- E5076_1 >>> PARTY FUNDING: DIRECT PUBLIC FUNDING --------------------------------------------------------------------------- Do parties receive direct public funding? .................................................................. 1. YES 5. NO 9. MISSING | VARIABLE NOTES: E5076_1 | | Source of data: ACE Electoral Knowledge Network (n.d). Party | Funding. Available at: | http://aceproject.org/epicen/CDTable?view=country&question=PC012 | (Date accessed: October 30, 2018) | | Data are unavailable for HONG KONG (2016). | ELECTION STUDY NOTES - UNITED STATES (2016): E5076_1 | | The Presidential Election Campaign Fund Act permits all | eligible national committees of major and minor parties to | receive public funds to pay the official costs of their | Presidential nominating conventions should they get 5 percent | of the vote in the previous election. Each major party | convention committee is entitled to receive $4 million, plus an | adjustment for inflation (since 1974). The U.S. Treasury makes | initial payments on or after July 1 of the year preceding the | Presidential election. --------------------------------------------------------------------------- E5076_2 >>> PARTY FUNDING: INDIRECT PUBLIC FUNDING --------------------------------------------------------------------------- Do parties receive indirect public funding? .................................................................. 1. YES 5. NO 9. MISSING | VARIABLE NOTES: E5076_2 | | Source of data: ACE Electoral Knowledge Network (n.d). Party | Funding. Available at: | http://aceproject.org/epicen/CDTable?view=country&question=PC012 | (Date accessed: October 30, 2018) | | Data are unavailable for HONG KONG (2016). --------------------------------------------------------------------------- E5077 >>> NUMBER OF PARTIES PARTICIPATING IN ELECTION --------------------------------------------------------------------------- How many political parties received votes in the election? .................................................................. 001-900. NUMBER OF PARTIES 999. MISSING | VARIABLE NOTES: E5077 | | E5077 details the number of participating political parties in | the election as available by official sources. Data is for the | Lower House elections unless otherwise stated in ELECTION STUDY | NOTES below. Independent candidates are not counted. Where | coalitions are present, constituent parties are counted | separately if possible. | | Source of data: Publicly available sources such as National | Election Commissions. | ELECTION STUDY NOTES - AUSTRALIA (2019): E5077 | | This calculation counts the Liberal and Liberal National Party | as separate parties. Additionally, the National Party and the | Country Liberals that run in the Northern Territory are also | considered separate parties. Only seven parties received votes | in excess of 1% nationally. | ELECTION STUDY NOTES - BELGIUM-FLANDERS (2019): E5077 | | These data represent the number of parties who received votes | in Flanders only. 31 parties received votes in Belgium in total. | ELECTION STUDY NOTES - BELGIUM-WALLONIA (2019): E5077 | | These data represent the number of parties who received votes | in Wallonia only. Data from the Brussels Capital Region is not | included in the calculation. 31 parties received votes in | Belgium in total. | ELECTION STUDY NOTES - CZECHIA (2021): E5077 | | Many parties competed in alliances in 2021 and these data | represent when the parties are counted separately. Counting | alliances as one entity means 22 entities participated in the | election. | ELECTION STUDY NOTES - DENMARK (2019): E5077 | | These data represent the number of parties who received votes | in mainland Denmark only. Including parties contesting in | Greenland (7) and the Faroe Islands (6), 26 parties contested. | ELECTION STUDY NOTES - EL SALVADOR (2019): E5077 | | These data represent the number of parties contesting the | Presidential election. Four of the seven listed parties | contested as part of an electoral alliance. Counting alliances as | one entity means 4 entities contested the election. | ELECTION STUDY NOTES - GERMANY (2017): E5077 | | These data represent the number of parties who received list | votes (tier 2) and count the CDU (PARTY A) and CSU (PARTY G), | who compete in an alliance, separately. | ELECTION STUDY NOTES - GERMANY (2021): E5077 | | These data represent the number of parties who received list | votes (tier 2) and count the CDU (PARTY B) and CSU (PARTY F), | who compete in an alliance, separately. Counting this alliance | as one entity (Unionsparteien) results in 39 parties receiving | list (tier 2) votes. Counting the CDU (PARTY B) and CSU (PARTY F) | as separate entities, 44 parties received votes at the | constituency level (tier 1, 43 if the CDU and CSU are classified | as one entity). | ELECTION STUDY NOTES - GREAT BRITAIN (2019): E5077 | | These data represent the number of parties contesting in | England, Scotland, and Wales. Parties contesting in Northern | Ireland are not included as the British Election Study does not | include respondents from Northern Ireland. | ELECTION STUDY NOTES - HONG KONG (2016): E5077 | | These data represent the number of parties contesting in | tier 1 only (i.e., the 35 representatives elected in the | geographical constituencies. | ELECTION STUDY NOTES - HUNGARY (2018): E5077 | | These data represent the number of parties contesting in | both tier 1 and tier 2. Taken separately, 66 parties contested | in tier 1 (first-past-the-post plurality constituencies), and 36 | parties competed in tier 2 (proportional list segment). This | includes 13 lists that represent national self-governments of | minorities. | ELECTION STUDY NOTES - IRELAND (2016): E5077 | | The Socialist Party and the People Before Profit Alliance, both | of which make up the Anti-Austerity Alliance, are treated as | separate entities in this count. Furthermore, only nine parties | received votes in excess of 1% nationally. | ELECTION STUDY NOTES - ITALY (2018): E5077 | | Counting alliances as one entity means 21 entities participated | in the election. | ELECTION STUDY NOTES - JAPAN (2017): E5077 | | These data represent the number of parties contesting in | both tier 1 and tier 2. Taken separately, 17 parties contested | in tier 1 (first-past-the-post plurality constituencies), and 11 | parties competed in tier 2 (proportional list segment). | ELECTION STUDY NOTES - LATVIA (2018): E5077 | | These data represent the number of entities rather than | indiviudal parties. In most cases, only the leading coalition | members have contested national elections on their own. | ELECTION STUDY NOTES - LITHUANIA (2016): E5077 | | These data represent the number of parties who received list | votes (tier 2). There were 14 electoral lists, two of which were | two-party coalitions. | ELECTION STUDY NOTES - LITHUANIA (2020): E5077 | | These data represent the number of parties who received list | votes (tier 2). There were 17 electoral lists, two of which were | two-party coalitions. | ELECTION STUDY NOTES - MONTENEGRO (2016): E5077 | | Counting alliances as one entity means 17 entities participated | in the election. | ELECTION STUDY NOTES - NEW ZEALAND (2017): E5077 | | These data represent the number of parties who received list | votes (tier 2). 26 parties received votes at the constituency | level (tier 1). | ELECTION STUDY NOTES - NEW ZEALAND (2020): E5077 | | These data represent the number of parties who received list | votes (tier 2). 32 parties received votes at the constituency | level (tier 1). | ELECTION STUDY NOTES - PERU (2021): E5077 | | These data represent the number of parties contesting Round 1 of | the Presidential election. The number of parties contesting the | Congressional election was 20. | ELECTION STUDY NOTES - PORTUGAL (2019): E5077 | | Counting alliances as one entity means 21 entities participated | in the election. | ELECTION STUDY NOTES - SOUTH KOREA (2016): E5077 | | These data represent the number of parties who received list | votes (tier 2). | ELECTION STUDY NOTES - TUNISIA (2019): E5077 | | These data represent the number of parties winning seats in the | parliamentary elections. No specific data on the specific number | of parties contesting the elections with over 200 parties | officially registered. | ELECTION STUDY NOTES - UNITED STATES (2016): E5077 | | These data represent parties that fielded candidates in the | Presidential election. Candidates may not have competed in every | state. | Forty-one parties contested the House of Representative | elections while 18 different parties contested the 34 Senate | races. However, precisely estimating the number of parties | contesting the election is difficult as parties do not always use | the same names in different states, and sometimes vote records do | not acknowledge smaller parties, but instead, collate the | results under an umbrella "other" category. | ELECTION STUDY NOTES - UNITED STATES (2020): E5077 | | These data represent to parties that fielded candidates in the | Presidential election. Candidates may not have competed in every | state. | Thirty-five parties contested the House of Representative | elections while 16 different parties contested the 35 Senate | races. However, estimating precisely the number of parties | contesting the election is difficult as parties do not always use | the same names in different states, and sometimes vote records do | not acknowledge smaller parties, but instead collate the | results under an umbrella "other" category. --------------------------------------------------------------------------- E5078 >>> EFFECTIVE NUMBER OF ELECTORAL PARTIES --------------------------------------------------------------------------- The effective number of electoral parties (ENEP). .................................................................. 00.00-150.00 EFFECTIVE NUMBER OF ELECTORAL PARTIES 997. PRESIDENTIAL ELECTION ONLY - NOT CALCULATED 999. MISSING | VARIABLE NOTES: E5078 | | Formula: ENPP = 1/(SUM[V_i^2]) | where V_i represents the vote share of party i, and all | parties (i=1,2...n) receiving votes are included in the | calculation. | | Definition based on Laakso, M. and R. Taagepera (1979). | '"Effective" Number of Parties: A Measure with Application to | West Europe', Comparative Political Studies 12: 3-27. | | The electoral data employed to calculate E5078 comes from lower | house elections, unless the study is focused on upper house | elections exclusively. | For countries with mixed electoral systems (see E5055) the | electoral returns come from the segment containing the most | seats. If there are an equal amount of seats in each segment | the results come from the proportional representation segment, | unless otherwise stated. | | The CSES Secretariat calculates these data for each polity's | election and cross-checks it against the standard source of data, | namely: | Gallagher, Michael, 2017. "Election indices dataset" - see: | http://www.tcd.ie/Political_Science/staff/michael_gallagher | /ElSystems/index.php, | (Date accessed: April 09, 2019). | ELECTION STUDY NOTES - AUSTRALIA (2019): E5078 | | These data are calculated by treating the Liberals (Liberal | Party and Liberal National Party) and the Nationals (the National | Party and the Country Liberals) as single entities. | ELECTION STUDY NOTES - BELGIUM-FLANDERS (2019): E5078 | | These data are calculated by taking only parties that competed | in Flanders. The effective number of electoral parties (ENEP) | for Belgium is 10.94. | ELECTION STUDY NOTES - BELGIUM-WALLONIA (2019): E5078 | | These data are calculated by taking only parties that competed | in Wallonia. The effective number of electoral parties (ENEP) | for Belgium is 10.94. Data from the Brussels Capital Region is | not included in the calculation. | ELECTION STUDY NOTES - DENMARK (2019): E5078 | | These data are calculated by taking parties that competed in | mainland Denmark only. | ELECTION STUDY NOTES - GERMANY (2021): E5078 | | These data are calculated by classifying the CDU and CSU as | separate entities. With the CDU and CSU classified as one entity | (Unionsparteien), the ENEP is 6.14. | ELECTION STUDY NOTES - GREAT BRITAIN (2017 & 2019): E5078 | | These data are calculated on the national share of the vote | and share of seats attained by parties who fielded candidates | in England, Scotland, and Wales. Northern Ireland data is not | included in the calculation of Effective Number of Electoral | or Parliamentary Parties as the 2017 and 2019 British Election | Studies did not include respondents from Northern Ireland. | Including parties contesting in Northern Ireland, the ENEP for | 2017 is 2.89 and 3.23 for 2019, respectively. | ELECTION STUDY NOTES - IRELAND (2016): E5078 | | These data are calculated by treating the Anti-Austerity Alliance | (AAA, Party E) made up of the Socialist Party and the United Left | Alliance as a single entity. | ELECTION STUDY NOTES - MEXICO (2018): E5078 | | These data are calculated based on parties and not coalitions. | ELECTION STUDY NOTES - POLAND (2019): E5078 | | These data are calculated based on parties and not coalitions. | ELECTION STUDY NOTES - THAILAND (2019): E5078 | | These data refer to the fused votes that count for both tiers of | the Lower House. | ELECTION STUDY NOTES - UNITED STATES (2016 & 2020): E5078 | | As US states are responsible for election counts, results for | different blocs are often reported differently by each state. | Consequently, the ENEP estimates include results data for | Independent candidates, blank votes, undervotes, and overvotes. | Excluding these categories, the ENEP for the 2020 contest is | 2.063. The ENEP estimate for the 2020 Electoral College, | which determines the US Presidency, is 2.09. --------------------------------------------------------------------------- E5079 >>> CORRECTED EFFECTIVE NUMBER OF ELECTORAL PARTIES --------------------------------------------------------------------------- The corrected effective number of electoral parties (CENEP). .................................................................. 00.00-150.00 CORRECTED EFFECTIVE NUMBER OF ELECTORAL PARTIES 997. PRESIDENTIAL ELECTION ONLY - NOT CALCULATED 999. MISSING | VARIABLE NOTES: E5079 | | Corrected Effective Number of Electoral Parties corrects for the | "other" category using the least component method of bounds | suggested by Taagepera. The method requires calculating the | ENEP (E5078) two times. One is treating the "other" category as | a single party and the second is calculating the ENEP as if every | vote in the "other" category belonged to a different party. | The CENEP is the mean of both measures. | | Definition based on: Taagepera, R. (1997). 'Effective Number of | Parties for incomplete Data', Electoral Studies 16: 145-151. | | The electoral data employed to calculate E5079 comes from lower | house elections, unless the study is focused on upper house | elections exclusively. | For countries with mixed electoral systems (see E5055) the | electoral returns come from the segment containing the most | seats. If there are an equal amount of seats in each segment | the results come from the proportional representation segment, | unless otherwise stated. | | The CSES Secretariat calculates these data for each polity's | election and cross-checks it against the standard source of data, | namely: | Gallagher, Michael, 2017. "Election indices dataset" - see: | http://www.tcd.ie/Political_Science/staff/michael_gallagher | /ElSystems/index.php, | (Date accessed: April 09, 2019). | ELECTION STUDY NOTES - AUSTRALIA (2019): E5079 | | These data are calculated by treating the Liberals | (Liberal party and Liberal National Party) and the | Nationals (the National Party and the Country Liberals) | as single entities. | ELECTION STUDY NOTES - BELGIUM-FLANDERS (2019): E5079 | | These data are calculated by taking only parties that competed | in Flanders. | ELECTION STUDY NOTES - BELGIUM-WALLONIA (2019): E5079 | | These data are calculated by taking only parties that competed | in Wallonia. Data from the Brussels Capital Region is not | included in the calculation. | ELECTION STUDY NOTES - DENMARK (2019): E5079 | | These data are calculated by taking parties that competed in | mainland Denmark only. | ELECTION STUDY NOTES - GERMANY (2021): E5079 | | These data are calculated by classifying the CDU and CSU as | separate entities. With the CDU and CSU classified as one entity | (Unionsparteien), the CENEP is 5.75. | ELECTION STUDY NOTES - GREAT BRITAIN (2017 & 2019): E5079 | | These data are calculated on the national share of the vote | and share of seats attained by parties who fielded candidates | in England, Scotland, and Wales. Northern Ireland data is not | included in the calculation as the 2017 and 2019 British Election | Studies did not include respondents from Northern Ireland. | ELECTION STUDY NOTES - IRELAND (2016): E5079 | | These data are calculated by treating the Anti-Austerity Alliance | (AAA, Party E) made up of the Socialist Party and the United | Left Alliance as a single entity. | ELECTION STUDY NOTES - MEXICO (2018): E5079 | | These data are calculated based on parties and not coalitions. | ELECTION STUDY NOTES - POLAND (2019): E5079 | | These data are calculated based on parties and not coalitions. | ELECTION STUDY NOTES - THAILAND (2019): E5079 | | These data refer to the fused votes that count for both tiers of | the Lower House. | ELECTION STUDY NOTES - UNITED STATES (2016 & 2020): E5079 | | These data are calculated based on elections to the US House of | Representatives. As US states are responsible for election | counts, results for different blocs are often reported | differently by each state. Consequently, the CENEP estimates | include results data for Independent candidates, blank votes, | undervotes, and overvotes. Excluding these categories, the CENEP | for the 2020 contest is 2.064. --------------------------------------------------------------------------- E5080 >>> EFFECTIVE NUMBER OF PARLIAMENTARY PARTIES --------------------------------------------------------------------------- The effective number of parliamentary parties (ENPP). .................................................................. 00.00-150.00 EFFECTIVE NUMBER OF PARLIAMENTARY PARTIES 997. PRESIDENTIAL ELECTION ONLY - NOT CALCULATED 999. MISSING | VARIABLE NOTES: E5080 | | Formula: ENPP = 1/(SUM[S_i^2]) | where S_i represents the seat share of party i, and all | parties (i=1,2...n) receiving votes are included in the | calculation. | | Definition based on Laakso, M. and R. Taagepera (1979). | '"Effective" Number of Parties: A Measure with Application to | West Europe', Comparative Political Studies 12: 3-27. | | The electoral data employed to calculate E5080 comes from lower | house elections, unless the study is focused on upper house | elections exclusively, and is based on all seats in the | parliament, unless otherwise stated. | | The CSES Secretariat calculates these data for each polity's | election and cross-checks it against the standard source of data, | namely: | Gallagher, Michael, 2017. "Election indices dataset" - see: | http://www.tcd.ie/Political_Science/staff/michael_gallagher | /ElSystems/index.php, | (Date accessed: April 09, 2019). | ELECTION STUDY NOTES - AUSTRALIA (2019): E5080 | | These data are calculated by treating the Liberals | (Liberal Party and Liberal National Party) and the | Nationals (the National Party and the Country Liberals) | as single entities. | ELECTION STUDY NOTES - BELGIUM-FLANDERS (2019): E5080 | | These data are calculated by taking only parties that competed | in Flanders. The effective number of parliamentary parties (ENPP) | for Belgium is 9.70. | ELECTION STUDY NOTES - BELGIUM-WALLONIA (2019): E5080 | | These data are calculated by taking only parties that competed | in Wallonia. The effective number of parliamentary parties (ENPP) | for Belgium is 9.70. Data from the Brussels Capital Region is not | included in the calculation. | ELECTION STUDY NOTES - DENMARK (2019): E5080 | | These data are calculated by taking parties that competed in | mainland Denmark only. | ELECTION STUDY NOTES - GERMANY (2021): E5080 | | These data are calculated by classifying the CDU and CSU as | separate entities. With the CDU and CSU classified as one entity | (Unionsparteien), the ENPP is 4.84. | ELECTION STUDY NOTES - GREAT BRITAIN (2017 & 2019): E5080 | | These data are calculated on the national share of the vote | and share of seats attained by parties who fielded candidates | in England, Scotland, and Wales. Northern Ireland data is not | included in the calculation of Effective Number of Electoral | or Parliamentary Parties as the 2017 and 2019 British Election | Studies did not include respondents from Northern Ireland. | Including parties contesting in Northern Ireland, the ENPP is | 2.48 for 2017 and 2.39 for 2019, respectively. | ELECTION STUDY NOTES - HONG KONG (2016): E5080 | | These data are calculated based on the first tier only (i.e., the | 35 representatives elected in the geographical constituencies). | ELECTION STUDY NOTES - MEXICO (2018): E5080 | | These data are calculated based on parties and not coalitions. | ELECTION STUDY NOTES - POLAND (2019): E5080 | | These data are calculated based on parties and not coalitions. | ELECTION STUDY NOTES - UNITED STATES (2016 & 2020): E5080 | | These data are calculated based on elections to the US House of | Representatives. As US states are responsible for election | counts, results for different blocs are often reported | differently by each state. Consequently, the ENPP estimates | include results data for Independent candidates, blank votes, | undervotes, and overvotes. Excluding these categories, the ENEP | estimate is 1.999. The 2020 election ENEP estimate for the | Electoral College, which determines the US Presidency, is 1.96. --------------------------------------------------------------------------- E5081 >>> CORRECTED EFFECTIVE NUMBER OF PARLIAMENTARY PARTIES --------------------------------------------------------------------------- The corrected Effective number of parliamentary parties (CENPP). .................................................................. 00.00-150.00 CORRECTED EFFECTIVE NUMBER OF PARLIAMENTARY PARTIES 997. PRESIDENTIAL ELECTION ONLY - NOT CALCULATED 999. MISSING | VARIABLE NOTES: E5081 | | Corrected Effective Number of Parliamentary Parties corrects for | the "other" category using the least component method of bounds | suggested by Taagepera (1997). The method requires calculating | the ENPP two times. One is treating the "other" category as a | single party and the second is calculating the ENPP as if every | seat in the "other" category belonged to a different party. | The CENPP is the mean of both measures. | | Definition based on: Taagepera, R. (1997). 'Effective Number of | Parties for incomplete Data', Electoral Studies 16: 145-151. | | The electoral data employed to calculate E5081 comes from lower | house elections, unless the study is focused on upper house | elections exclusively, and is based on all seats in the | parliament, unless otherwise stated. | | The CSES Secretariat calculates these data for each polity's | election and cross-checks it against the standard source of data, | namely: | Gallagher, Michael, 2017. "Election indices dataset" - see: | http://www.tcd.ie/Political_Science/staff/michael_gallagher | /ElSystems/index.php, | (Date accessed: April 09, 2017). | ELECTION STUDY NOTES - AUSTRALIA (2019): E5081 | | These data are calculated by treating the Liberals | (Liberal Party and Liberal National Party) and the | Nationals (the National Party and the Country Liberals) | as single entities. | ELECTION STUDY NOTES - BELGIUM-FLANDERS (2019): E5081 | | These data are calculated by taking only parties that competed | in Flanders. | ELECTION STUDY NOTES - BELGIUM-WALLONIA (2019): E5081 | | These data are calculated by taking only parties that competed | in Wallonia. Data from the Brussels Capital Region is not | included in the calculation. | ELECTION STUDY NOTES - DENMARK (2019): E5081 | | These data are calculated by taking parties that competed in | mainland Denmark only. | ELECTION STUDY NOTES - GERMANY (2021): E5081 | | These data are calculated by classifying the CDU and CSU as | separate entities. With the CDU and CSU classified as one entity | (Unionsparteien), the CENPP is also 4.84. | ELECTION STUDY NOTES - GREAT BRITAIN (2017 & 2019): E5081 | | These data are calculated on the national share of the vote | and share of seats attained by parties who fielded candidates | in England, Scotland, and Wales. Northern Ireland data is not | included in the calculation as the 2017 and 2019 British Election | Studies did not include respondents from Northern Ireland. | ELECTION STUDY NOTES - HONG KONG (2016): E5081 | | These data are calculated based on the first tier only (i.e., the | 35 representatives elected in the geographical constituencies). | ELECTION STUDY NOTES - MEXICO (2018): E5081 | | These data are calculated based on parties and not coalitions. | ELECTION STUDY NOTES - POLAND (2019): E5081 | | These data are calculated based on parties and not coalitions. | ELECTION STUDY NOTES - THAILAND (2019): E5081 | | These data refer to the total number of seats obtained in | both tiers of the Lower House. | ELECTION STUDY NOTES - UNITED STATES (2020): E5081 | | These data are calculated based on elections to the US House of | Representatives. As US states are responsible for election | counts, results for different blocs are often reported | differently by each state. Consequently, the CENPP estimates | include results data for Independent candidates, blank votes, | undervotes, and overvotes. Excluding these categories, the ENEP | estimate is 1.999. --------------------------------------------------------------------------- E5082_1 >>> DIRECT DEMOCRACY: REFERENDUM MANDATORY --------------------------------------------------------------------------- Direct democracy: Are there any Legal Provisions for Mandatory Referendums at the national level? .................................................................. 1. YES 2. NO 5. NO INFORMATION AVAILABLE 9. MISSING | VARIABLE NOTES: E5082_1 | | Source of data: ACE Electoral Knowledge Network | http://aceproject.org/epic-en/CDTable?view=country&question=DD003 | (Date accessed: October 29, 2018). | ELECTION STUDY NOTES - UNITED STATES (2016 & 2020): E5082_1 | | Provision for mandatory referendums, known in the USA | colloquially as initiatives or ballot propositions do exist at | the state level but not the national level. --------------------------------------------------------------------------- E5082_2 >>> DIRECT DEMOCRACY: REFERENDUM OPTIONAL --------------------------------------------------------------------------- Direct democracy: Are there any Legal Provisions for Option Referendums at the National Level? .................................................................. 1. YES 2. NO 5. NO INFORMATION AVAILABLE 9. MISSING | VARIABLE NOTES: E5082_2 | | Source of data: ACE Electoral Knowledge Network | http://aceproject.org/epic-en/CDTable?view=country&question=DD004 | (Date accessed: October 29, 2018). --------------------------------------------------------------------------- E5082_3 >>> DIRECT DEMOCRACY: REFERENDUMS BY CITIZEN INITIATIVE --------------------------------------------------------------------------- Direct democracy: Are there any Legal Provisions for Citizen's Initiatives at the National Level? .................................................................. 1. YES 2. NO 5. NO INFORMATION AVAILABLE 9. MISSING | VARIABLE NOTES: E5082_3 | | Source of data: ACE Electoral Knowledge Network | http://aceproject.org/epic-en/CDTable?view=country&question=DD005 | (Date accessed: October 29, 2018). | ELECTION STUDY NOTES - UNITED STATES (2016 & 2020): E5082_3 | | Provision for referendums by citizen initiative do exist | at the state level but not the national level. --------------------------------------------------------------------------- E5082_4 >>> DIRECT DEMOCRACY: REFERENDUM RESULT BINDING OR CONSULTATIVE --------------------------------------------------------------------------- Direct democracy: Are the results of referenda always binding, never binding or sometimes binding? .................................................................. 1. ALWAYS BINDING 2. SOMETIMES BINDING 3. NEVER BINDING 5. NO INFORMATION AVAILABLE 7. NOT APPLICABLE 9. MISSING | VARIABLE NOTES: E5082_4 | | Source of data: ACE Electoral Knowledge Network | http://aceproject.org/epic-en/CDTable?view=country&question=DD129 | (Date accessed: October 29, 2018). --------------------------------------------------------------------------- E5083_1 >>> COVID-19 PANDEMIC - CUMULATIVE N INFECTIONS - TIME T-4 DAYS E5083_2 >>> COVID-19 PANDEMIC - CUMULATIVE N INFECTIONS - TIME T-7 DAYS E5083_3 >>> COVID-19 PANDEMIC - CUMULATIVE N INFECTIONS - TIME T-14 DAYS E5083_4 >>> COVID-19 PANDEMIC - CUMULATIVE N INFECTIONS - TIME T-28 DAYS E5083_5 >>> COVID-19 PANDEMIC - CUMULATIVE N INFECTIONS - TIME T-91 DAYS --------------------------------------------------------------------------- The cumulative number of COVID-19 infections at five time periods from the date of the election. .................................................................. 0 to 9088385. COVID-19 PANDEMIC: CUMULATIVE N INFECTIONS 999999997. NOT APPLICABLE: ELECTION PRE COVID-19 PANDEMIC 999999999. MISSING | VARIABLE NOTES: E5083_ | | E5083_ detail the cumulative number of COVID-19 infections at | five time periods from the date of the election: four days before | the election (T-4 days); seven days before the election | (T-7 days); fourteen days before the election (T-14 days); | twenty-eight days before the election (T-28 days); and three | months before the election (T-91 days). | | Definition: A pandemic is an epidemic of infectious disease that | has spread across a large region or multiple or worldwide and | affecting a substantial number of individuals. | At the time of writing, COVID-19 was first discovered in November | 2019. However, it is possible human-to-human transmission of the | disease was occurring before this discovery. On January 11, 2020 | the World Health Organization (WHO) was notified by Chinese | authorities of a virus outbreak in Wuhan, China. On January 30, | 2020, the World Health Organization classified COVID-19 as a | Public Health Emergency of Concern before eventually declaring | the Health situation as a pandemic on March 11, 2020. | | E5083_ details the number of cumulative confirmed COVID-19 | infections in a polity as reported by national health authorities | on a particular day relative to the date of the election. Data | represents the number of cases as reported by that date, not | necessarily the actual number of cases in the polity on that date | due to different lags in the reporting of data. | Consequently, time series can show sudden shifts as polities | may correct data because a particular day under or overreported | cases. These data can include probable cases. | | E5083_ are collated by the COVID-19 Data Repository by the | Centre for Systems Science and Engineering (CSSE) at John Hopkins | University (JHU). The CSES sources this data from the | Coronavirus Pandemic (COVID-19) database - see: | https://github.com/owid/covid-19-data/tree/master/public/data | (Date accessed: January 09, 2023). | | CSES only reports data for E5083 for polities which held | elections on or after January 30, 2020. | | Data for E5083_ are unavailable for SLOVAKIA (2020). | | Data for E5083_3 are unavailable for ISRAEL (2020). | Data for E5083_4 are unavailable for ISRAEL (2020). | Data for E5083_5 are unavailable for ISRAEL (2020). | ELECTION STUDY NOTES - CZECHIA (2021): E5083_ | | The 2021 Czech election was held on October 8-9, 2021. The data | for each of the time periods represents the cumulative N of | infections reported as of the following dates: | T-4 days: Monday, October 4, 2021. | T-7 days: Friday, October 1, 2021. | T-14 days: Friday, September 24, 2021. | T-28 days: Friday, September 10, 2021. | T-91 days: Friday, July 9, 2021. | ELECTION STUDY NOTES - GERMANY (2021): E5083_ | | The 2021 German election was held on September 26, 2021. The data | for each of the time periods represents the cumulative N of | infections reported as of the following dates: | T-4 days: Wednesday, September 22, 2021. | T-7 days: Sunday, September 19, 2021. | T-14 days: Sunday, September 12, 2021. | T-28 days: Sunday, August 29, 2021. | T-91 days: Sunday, June 27, 2021. | ELECTION STUDY NOTES - ISRAEL (2020): E5083_ | | The 2020 Israeli election was held on March 2, 2020. The data | for each of the time periods represents the cumulative N of | infections reported as of the following dates: | T-4 days: Thursday, February 27, 2020. | T-7 days: Monday, February 24, 2020. | T-14 days: Monday, February 17, 2020. | T-28 days: Monday, February 3, 2020. | ELECTION STUDY NOTES - LITHUANIA (2020): E5083_ | | The 2020 Lithuanian elections were held on October 11, 2020 | (First Round) and October 25, 2020 (Second Round). The data for | each of the time periods represents the cumulative N of | infections reported as of the following dates: | T-4 days: Wednesday, October 7, 2020. | T-7 days: Sunday, October 4, 2020. | T-14 days: Sunday, September 27, 2020. | T-28 days: Sunday, September 13, 2020. | T-91 days: Sunday, July 12, 2020. | ELECTION STUDY NOTES - NETHERLANDS (2021): E5083_ | | The 2021 Dutch election was held on March 17, 2021. The data | for each of the time periods represents the cumulative N of | infections reported as of the following dates: | T-4 days: Saturday, March 13, 2021. | T-7 days: Wednesday, March 10, 2021. | T-14 days: Wednesday, March 3, 2021. | T-28 days: Wednesday, February 17, 2021. | T-91 days: Wednesday, December 16, 2020. | ELECTION STUDY NOTES - NEW ZEALAND (2020): E5083_ | | The 2020 New Zealand election was held on October 17, 2020. The | data for each of the time periods represents the cumulative N of | infections reported as of the following dates: | T-4 days: Tuesday, October 13, 2020. | T-7 days: Saturday, October 10, 2020. | T-14 days: Saturday, October 3, 2020. | T-28 days: Saturday, September 19, 2020. | T-91 days: Saturday, July 18, 2020. | ELECTION STUDY NOTES - PERU (2021): E5083_ | | The 2021 Peruvian elections were held on April 11, 2021 | (First Round) and June 6, 2021 (Second Round). The data for | each of the time periods represents the cumulative N of | infections reported as of the following dates: | T-4 days: Wednesday, April 7, 2021. | T-7 days: Sunday, April 4, 2021. | T-14 days: Sunday, March 28, 2021. | T-28 days: Sunday, March 14, 2021. | T-91 days: Saturday, January 10, 2021. | ELECTION STUDY NOTES - SLOVAKIA (2020): E5083_ | | The 2020 Slovakia election was held on February 29, 2020. | However, COVID-19 data for Slovakia is only available from | March 6, 2020. | ELECTION STUDY NOTES - UNITED STATES (2020): E5083_ | | The 2020 US election was held on November 3, 2020. The data | for each of the time periods represents the cumulative N of | infections reported as of the following dates: | T-4 days: Friday, October 30, 2020. | T-7 days: Tuesday, October 27, 2020. | T-14 days: Tuesday, October 20, 2020. | T-28 days: Tuesday, October 6, 2020. | T-91 days: Tuesday, August 4, 2020. --------------------------------------------------------------------------- E5084_1 >>> COVID-19 PANDEMIC - CUMULATIVE N DEATHS - TIME T-4 DAYS E5084_2 >>> COVID-19 PANDEMIC - CUMULATIVE N DEATHS - TIME T-7 DAYS E5084_3 >>> COVID-19 PANDEMIC - CUMULATIVE N DEATHS - TIME T-14 DAYS E5084_4 >>> COVID-19 PANDEMIC - CUMULATIVE N DEATHS - TIME T-28 DAYS E5084_5 >>> COVID-19 PANDEMIC - CUMULATIVE N DEATHS - TIME T-91 DAYS --------------------------------------------------------------------------- The cumulative number of deaths ascribed to COVID-19 at five time periods from the date of the election. .................................................................. 0 to 229555. COVID-19 PANDEMIC: CUMULATIVE N DEATHS 9999999997. NOT APPLICABLE: ELECTION PRE COVID-19 PANDEMIC 9999999999. MISSING | VARIABLE NOTES: E5084_ | | E5084_ detail the cumulative number of deaths ascribed to | COVID-19 at five time periods from the date of the election: four | days before the election (T-4 days); seven days before the | election (T-7 days); fourteen days before the election | (T-14 days); twenty-eight days before the election (T-28 days); | and three months before the election (T-91 days). | | Definition: A pandemic is an epidemic of infectious disease that | has spread across a large region or multiple or worldwide and | affecting a substantial number of individuals. | At the time of writing, COVID-19 was first discovered in November | 2019. However, it is possible human-to-human transmission of the | disease was occurring before this discovery. On January 11, 2020 | the World Health Organization (WHO) was notified by Chinese | authorities of a virus outbreak in Wuhan, China. On January 30, | 2020, the World Health Organization classified COVID-19 as a | Public Health Emergency of Concern before eventually declaring | the Health situation as a pandemic on March 11, 2020. | | E5084_ details the number of cumulative deaths ascribed to | COVID-19 infections in a polity as reported by national health | authorities on a particular day relative to the date of the | election. Data represents the number of cases as reported by that | date, not necessarily the actual number of cases in the polity | on that date due to different lags in the reporting of data. | Consequently, time series can show sudden shifts as polities | may correct data because a particular day under or overreported | cases. These data can include probable deaths. | Furthermore, polities ascribed deaths according to COVID-19 | differently and users are advised to consult national health | service data for precise classifications by polity. | | E5084_ are collated by the COVID-19 Data Repository by the | Centre for Systems Science and Engineering (CSSE) at John Hopkins | University (JHU). The CSES sources this data from the | Coronavirus Pandemic (COVID-19) database - see: | https://github.com/owid/covid-19-data/tree/master/public/data | (Date accessed: January 09, 2023). | | CSES only reports data for E5084_ for polities which held | elections on or after January 30, 2020. | | Data for E5084_ are unavailable for SLOVAKIA (2020). | | Data for E5084_3 are unavailable for ISRAEL (2020). | Data for E5084_4 are unavailable for ISRAEL (2020). | Data for E5084_5 are unavailable for ISRAEL (2020). | ELECTION STUDY NOTES - CZECHIA (2021): E5084_ | | The 2021 Czech election was held on October 8-9, 2021. The data | for each of the time periods represents the cumulative N of | deaths ascribed to COVID-19 reported as of the following dates: | T-4 days: Monday, October 4, 2021. | T-7 days: Friday, October 1, 2021. | T-14 days: Friday, September 24, 2021. | T-28 days: Friday, September 10, 2021. | T-91 days: Friday, July 9, 2021. | ELECTION STUDY NOTES - GERMANY (2021): E5084_ | | The 2021 German election was held on September 26, 2021. The data | for each of the time periods represents the cumulative N of | deaths ascribed to COVID-19 reported as of the following dates: | T-4 days: Wednesday, September 22, 2021. | T-7 days: Sunday, September 19, 2021. | T-14 days: Sunday, September 12, 2021. | T-28 days: Sunday, August 29, 2021. | T-91 days: Sunday, June 27, 2021. | ELECTION STUDY NOTES - ISRAEL (2020): E5084_ | | The 2020 Israeli election was held on March 2, 2020. The data | for each of the time periods represents the cumulative N of | deaths ascribed to COVID-19 reported as of the following dates: | T-4 days: Thursday, February 27, 2020. | T-7 days: Monday, February 24, 2020. | T-14 days: Monday, February 17, 2020. | T-28 days: Monday, February 3, 2020. | ELECTION STUDY NOTES - LITHUANIA (2020): E5084_ | | The 2020 Lithuanian elections were held on October 11, 2020 | (First Round) and October 25, 2020 (Second Round). The data | for each of the time periods represents the cumulative N of | deaths ascribed to COVID-19 reported as of the following dates: | T-4 days: Wednesday, October 7, 2020. | T-7 days: Sunday, October 4, 2020. | T-14 days: Sunday, September 27, 2020. | T-28 days: Sunday, September 13, 2020. | T-91 days: Sunday, July 12, 2020. | ELECTION STUDY NOTES - NETHERLANDS (2021): E5084_ | | The 2021 Dutch election was held on March 17, 2021. he data | for each of the time periods represents the cumulative N of | deaths ascribed to COVID-19 reported as of the following dates: | T-4 days: Saturday, March 13, 2021. | T-7 days: Wednesday, March 10, 2021. | T-14 days: Wednesday, March 3, 2021. | T-28 days: Wednesday, February 17, 2021. | T-91 days: Wednesday, December 16, 2020. | ELECTION STUDY NOTES - NEW ZEALAND (2020): E5084_ | | The 2020 New Zealand election was held on October 17, 2020. The | data for each of the time periods represents the cumulative N of | deaths ascribed to COVID-19 reported as of the following dates: | T-4 days: Tuesday, October 13, 2020. | T-7 days: Saturday, October 10, 2020. | T-14 days: Saturday, October 3, 2020. | T-28 days: Saturday, September 19, 2020. | T-91 days: Saturday, July 18, 2020. | ELECTION STUDY NOTES - PERU (2021): E5084_ | | The 2021 Peruvian elections were held on April 11, 2021 | (First Round) and June 6, 2021 (Second Round). The data | for each of the time periods represents the cumulative N of | deaths ascribed to COVID-19 reported as of the following dates: | T-4 days: Wednesday, April 7, 2021. | T-7 days: Sunday, April 4, 2021. | T-14 days: Sunday, March 28, 2021. | T-28 days: Sunday, March 14, 2021. | T-91 days: Saturday, January 10, 2021. | ELECTION STUDY NOTES - SLOVAKIA (2020): E5084_ | | The 2020 Slovakia election was held on February 29, 2020. | However, COVID-19 data for Slovakia is only available from | March 6, 2020. | ELECTION STUDY NOTES - UNITED STATES (2020): E5084_ | | The 2020 US election was held on November 3, 2020. The data | for each of the time periods represents the cumulative N of | deaths ascribed to COVID-19 reported as of the following dates: | T-4 days: Friday, October 30, 2020. | T-7 days: Tuesday, October 27, 2020. | T-14 days: Tuesday, October 20, 2020. | T-28 days: Tuesday, October 6, 2020. | T-91 days: Tuesday, August 4, 2020. --------------------------------------------------------------------------- E5085_1 >>> COVID-19 PANDEMIC - REPRODUCTION RATE - TIME T-4 DAYS E5085_2 >>> COVID-19 PANDEMIC - REPRODUCTION RATE - TIME T-7 DAYS E5085_3 >>> COVID-19 PANDEMIC - REPRODUCTION RATE - TIME T-14 DAYS E5085_4 >>> COVID-19 PANDEMIC - REPRODUCTION RATE - TIME T-28 DAYS E5085_5 >>> COVID-19 PANDEMIC - REPRODUCTION RATE - TIME T-91 DAYS --------------------------------------------------------------------------- The reproduction rate (R value) for COVID-19 at five time periods from the date of the election. .................................................................. 0 to 2. COVID-19 PANDEMIC: REPRODUCTIVE RATE 997. NOT APPLICABLE: ELECTION PRE COVID-19 PANDEMIC 999. MISSING | VARIABLE NOTES: E5085_ | | E5085_ detail the reproduction rate (R value) for COVID-19 at | five time periods from the date of the election: four days before | the election (T-4 days); seven days before the election | (T-7 days); fourteen days before the election (T-14 days); | twenty-eight days before the election (T-28 days); and three | months before the election (T-91 days). | | Definition: A pandemic is an epidemic of infectious disease that | has spread across a large region or multiple or worldwide and | affecting a substantial number of individuals. | At the time of writing, COVID-19 was first discovered in November | 2019. However, it is possible human-to-human transmission of the | disease was occurring before this discovery. On January 11, 2020 | the World Health Organization (WHO) was notified by Chinese | authorities of a virus outbreak in Wuhan, China. On January 30, | 2020, the World Health Organization classified COVID-19 as a | Public Health Emergency of Concern before eventually declaring | the Health situation as a pandemic on March 11, 2020. | | E5085_ details the reproduction rate (R value) of COVID-19 | infections in a polity as reported by national health authorities | on a particular day relative to the date of the election. The | reproduction rate (R) indicates how fast COVID-19 is spreading | among a population. The number indicates how many people are | infected on average by a person who carries the virus. | If the R value is greater than 1.0, then it is anticipated the | number of infections will keep increasing. If the R value is | lower than 1.0, the disease will eventually stop spreading, | as fewer new infections will develop. | | E5085_ are collated by the COVID-19 Data Repository by the | Centre for Systems Science and Engineering (CSSE) at John Hopkins | University (JHU). The CSES sources this data from the | Coronavirus Pandemic (COVID-19) database - see: | https://github.com/owid/covid-19-data/tree/master/public/data | (Date accessed: January 09, 2023). | | CSES only reports data for E5085_ for polities which held | elections on or after January 30, 2020. | ELECTION STUDY NOTES - CZECHIA (2021): E5085_ | | The 2021 Czech election was held on October 8-9, 2021. The data | for each of the time periods represents the estimated COVID-19 | reproduction rate reported as of the following dates: | T-4 days: Monday, October 4, 2021. | T-7 days: Friday, October 1, 2021. | T-14 days: Friday, September 24, 2021. | T-28 days: Friday, September 10, 2021. | T-91 days: Friday, July 9, 2021. | ELECTION STUDY NOTES - GERMANY (2021): E5085_ | | The 2021 German election was held on September 26, 2021. The data | for each of the time periods represents the estimated COVID-19 | reproduction rate reported as of the following dates: | T-4 days: Wednesday, September 22, 2021. | T-7 days: Sunday, September 19, 2021. | T-14 days: Sunday, September 12, 2021. | T-28 days: Sunday, August 29, 2021. | T-91 days: Sunday, June 27, 2021. | ELECTION STUDY NOTES - ISRAEL (2020): E5085_ | | The 2020 Israeli election was held on March 2, 2020. The data | for each of the time periods represents the estimated COVID-19 | reproduction rate reported as of the following dates: | T-4 days: Thursday, February 27, 2020. | T-7 days: Monday, February 24, 2020. | T-14 days: Monday, February 17, 2020. | T-28 days: Monday, February 3, 2020. | ELECTION STUDY NOTES - LITHUANIA (2020): E5085_ | | The 2020 Lithuanian elections were held on October 11, 2020 | (First Round) and October 25, 2020 (Second Round). The data | for each of the time periods represents the estimated COVID-19 | reproduction rate reported as of the following dates: | T-4 days: Wednesday, October 7, 2020. | T-7 days: Sunday, October 4, 2020. | T-14 days: Sunday, September 27, 2020. | T-28 days: Sunday, September 13, 2020. | T-91 days: Sunday, July 12, 2020. | ELECTION STUDY NOTES - NETHERLANDS (2021): E5085_ | | The 2021 Dutch election was held on March 17, 2021. The data | for each of the time periods represents the estimated COVID-19 | reproduction rate reported as of the following dates: | T-4 days: Saturday, March 13, 2021. | T-7 days: Wednesday, March 10, 2021. | T-14 days: Wednesday, March 3, 2021. | T-28 days: Wednesday, February 17, 2021. | T-91 days: Wednesday, December 16, 2020. | ELECTION STUDY NOTES - NEW ZEALAND (2020): E5085_ | | The 2020 New Zealand election was held on October 17, 2020. The | data for each of the time periods represents the estimated | COVID-19 reproduction rate reported as of the following dates: | T-4 days: Tuesday, October 13, 2020. | T-7 days: Saturday, October 10, 2020. | T-14 days: Saturday, October 3, 2020. | T-28 days: Saturday, September 19, 2020. | T-91 days: Saturday, July 18, 2020. | ELECTION STUDY NOTES - PERU (2021): E5085_ | | The 2021 Peruvian elections were held on April 11, 2021 | (First Round) and June 6, 2021 (Second Round). The data | for each of the time periods represents the estimated COVID-19 | reproduction rate reported as of the following dates: | T-4 days: Wednesday, April 7, 2021. | T-7 days: Sunday, April 4, 2021. | T-14 days: Sunday, March 28, 2021. | T-28 days: Sunday, March 14, 2021. | T-91 days: Saturday, January 10, 2021. | ELECTION STUDY NOTES - SLOVAKIA (2020): E5085_ | | The 2020 Slovakia election was held on February 29, 2020. | However, COVID-19 data for Slovakia is only available from | March 6, 2020. | ELECTION STUDY NOTES - UNITED STATES (2020): E5085_ | | The 2020 US election was held on November 3, 2020. The data | for each of the time periods represents the estimated COVID-19 | reproduction rate reported as of the following dates: | T-4 days: Friday, October 30, 2020. | T-7 days: Tuesday, October 27, 2020. | T-14 days: Tuesday, October 20, 2020. | T-28 days: Tuesday, October 6, 2020. | T-91 days: Tuesday, August 4, 2020. III. OTHER MACRO-LEVEL DATA --------------------------------------------------------------------------- E5090_1 >>> FREEDOM HOUSE RATING - TIME T E5090_2 >>> FREEDOM HOUSE RATING - TIME T-1 E5090_3 >>> FREEDOM HOUSE RATING - TIME T-2 --------------------------------------------------------------------------- Freedom House's rating at three time periods (average of the "Political Rights" and "Civil Liberties" scores). .................................................................. 1.00-7.00 FREEDOM SCORE 9.00 MISSING | VARIABLE NOTES: E5090_ | | E5090_ detail Freedom House's rating of freedom in a country at | three time periods: the election year (time T), one year before | election (T-1), and two years before election (T-2). | Each country and territory is assigned a numerical rating, on a | scale of 1 to 7. A rating of 1 indicates the highest degree of | freedom and 7 the least amount of freedom. CSES reports average | of the "Political Rights" and "Civil Liberties" scores. | | Source of data: Freedom House's annual publications "Freedom in | the World" (https://freedomhouse.org/report-types/freedom-world; | Date accessed: October 29, 2018). | | Until 2003, countries whose combined average ratings for | Political Rights and for Civil Liberties fell between 1.0 and | 2.5 were designated "Free"; between 3.0 and 5.5 "Partly Free", | and between 5.5 and 7.0 "Not Free". Beginning with the ratings | for 2003, countries whose combined average ratings fall between | 3.0 and 5.0 are "Partly Free", and those between 5.5 and 7.0 are | "Not Free". | | More information about Freedom House's methodology is available | at: http://freedomhouse.org/ (Date accessed: April 30, 2020). | | CSES collects the most up-to-date data for each polity available | at the time the data is being processed by the CSES Secretariat. | However, aggregate-level macro data from Freedom House can be | updated retroactively as revised estimates become available. | The CSES policy is to provide users with estimates of data | at the time the data is processed. CSES does not retroactively | update these estimates as to do so might impede replication. --------------------------------------------------------------------------- E5091_1 >>> DEMOCRACY-AUTOCRACY - POLITY IV RATING - TIME T E5091_2 >>> DEMOCRACY-AUTOCRACY - POLITY IV RATING - TIME T-1 E5091_3 >>> DEMOCRACY-AUTOCRACY - POLITY IV RATING - TIME T-2 --------------------------------------------------------------------------- The POLITY IV ratings of institutionalized democracy versus autocracy in a country at three time periods. .................................................................. 10. DEMOCRATIC 09. 08. 07. 06. 05. 04. 03. 02. 01. 00. -01. -02. -03. -04. -05. -06. -07. -08. -09. -10. AUTOCRATIC -66. INTERRUPTION PERIODS -77. INTERREGUM PERIODS -88. TRANSITION PERIODS 99. MISSING | VARIABLE NOTES: E5091_ | | E5091_ detail POLITY IV ratings of institutionalized democracy | versus autocracy in a country, at three time periods: the | election year (time T), one year before election (T-1), and | two years before election (T-2). | | E5091_ reports the original variable POLITY - Combined Polity | Score. The variable is constructed by subtracting the autocracy | score from the democracy score; the resulting scale ranges from | +10 (strongly democratic) to -10 (strongly autocratic). | | Source of data: POLITY IV Project: | Political Regime Characteristics and Transitions, 1800-2017, | Monty G. Marshall and Keith Jaggers, George Mason University and | Colorado State University | (http://www.systemicpeace.org/polity/polity4.htm; Date accessed: | April 30, 2020). | | The Polity IV Dataset Users' Manual: | (http://www.systemicpeace.org/inscr/p4manualv2017.pdf). | (Date accessed: April 05, 2019). | | The Polity IV annual time-series dataset: | (www.systemicpeace.org/inscr/p4v2017.xls; Date accessed: April | 30, 2020). | | CSES collects the most up-to-date data for each polity available | at the time the data is being processed by the CSES Secretariat. | However, aggregate-level macro data from Polity project can be | updated retroactively as revised estimates become available. | The CSES policy is to provide users with estimates of data | at the time the data is processed. CSES does not retroactively | update these estimates as to do so might impede replication. | | Data for E5091_ are unavailable for CZECHIA (2021), GERMANY | (2021), HONG KONG (2016), ICELAND (2016 & 2017), NETHERLANDS | (2021), PERU (2021) and TUNISIA (2019). | | Data for E5091_1 are unavailable for BELGIUM-FLANDERS (2019), | BELGIUM-WALLONIA (2019), EL SALVADOR (2019), GREAT BRITAIN | (2019), GREECE (2019), HUNGARY (2018), INDIA (2019), ISRAEL | (2020), LITHUANIA (2020), NETHERLANDS (2021), POLAND (2019), | SLOVAKIA (2020), THAILAND (2019) and UNITED STATES (2020). | | Data for E5091_2 are unavailable for LITHUANIA (2020), SLOVAKIA | (2020) and UNITED STATES (2020). --------------------------------------------------------------------------- E5092 >>> GINI COEFFICIENT OF EQUALIZED DISPOSABLE INCOME - (YEAR CLOSEST TO ELECTION YEAR AVAILABLE) --------------------------------------------------------------------------- The Gini coefficient of equalized disposable income in the year of election or the year closest to election at time of processing. .................................................................. 0.00-100.00 GINI COEFFICIENT 999. MISSING | VARIABLE NOTES: E5092 | | Definition: E5092 details the World Bank estimate of the | distribution of income among individuals or households within an | economy and the extent to which it deviates from a perfectly | equal distribution. A Lorenz curve plots the cumulative | percentages of total income received against the cumulative | number of recipients, starting with the poorest individual or | household. The Gini index measures the area between the Lorenz | curve and a hypothetical line of absolute equality. Thus a Gini | index of 0 represents perfect equality, while an index of 100 | implies perfect inequality. | | Source of data: World Bank World Development Indicators Open | Database: https://data.worldbank.org/indicator/SI.POV.GINI/ | (Date accessed: October 29, 2018). | | Users are advised that there is normally a two or three-year | time lag between these estimates becoming available. | Consequently, data may not be available at the time of coding. | In circumstances where this occurs, the polity will be listed | as DATA UNAVAILABLE in the VARIABLE NOTES below. | | CSES collects the most up-to-date data for each polity available | at the time the data is being processed by the CSES Secretariat. | However, aggregate-level macro data from the World Bank is often | updated retroactively as revised estimates become available. | These revised estimates are usually because of improved data | collection, or more evidence becoming available to allow for a | more robust estimates to be made, or changes in methodology. | For more see the advice of the World Bank at: | https://datahelpdesk.worldbank.org/knowledgebase/articles/114939 | -how-are-revisions-managed | (Date accessed: April 09, 2019). | | The time lag for this variable becoming available is often | many years. CSES where possible has a policy of providing users | with the data in the year of election - the default approach. | However, at the time of processing, GINI coefficient data is | often unavailable and this can remain the case for several years. | To avoid excessive missing values for multiple studies, CSES | provides the GINI coefficient estimate for the year closest to | the election available at the time of data processing. The | specific years the GINI data refers for all studies are listed | in the below table. | | The CSES policy is to provide users with estimates of data | at the time the data is processed. CSES does not retroactively | update these estimates as to do so might impede replication. | | Data are unavailable for NEW ZEALAND (2017 & 2020). | | The following table gives an overview of the year in which | GINI coefficient reported in the data refers to. | | +++ TABLE: GINI COEFFICIENT YEAR OF CALCULATION | BY ELECTION STUDY | | POLITY (ELEC YEAR) Year of GINI coefficient reported in data | ------------------------------------------------------------- | ALBANIA (2017) 2017 | AUSTRALIA (2019) 2014 | AUSTRIA (2017) 2015 | BELGIUM-FLANDERS (2019) 2018 | BELGIUM-WALLONIA (2019) 2018 | BRAZIL (2018) 2017 | CANADA (2019) 2017 | CHILE (2017) 2015 | COSTA RICA (2018) 2017 | CZECHIA (2017) 2017 | CZECHIA (2021) 2017 | DENMARK (2019) 2018 | EL SALVADOR (2019) 2019 | FINLAND (2019) 2018 | FRANCE (2017) 2015 | GERMANY (2017) 2015 | GERMANY (2021) 2018 | GREAT BRITAIN (2017) 2017 | GREAT BRITAIN (2019) 2017 | GREECE (2015) 2015 | GREECE (2019) 2019 | HONG KONG (2016) 2016 | HUNGARY (2018) 2015 | ICELAND (2016) 2014 | ICELAND (2017) 2014 | INDIA (2019) 2019 | IRELAND (2016) 2016 | ISRAEL (2020) 2018 | ITALY (2018) 2015 | JAPAN (2017) 2013 | LATVIA (2018) 2018 | LITHUANIA (2016) 2015 | LITHUANIA (2020) 2018 | MEXICO (2018) 2018 | MONTENEGRO (2016) 2014 | NETHERLANDS (2017) 2017 | NETHERLANDS (2021) 2019 | NEW ZEALAND (2017) UNAVAILABLE | NEW ZEALAND (2020) UNAVAILABLE | NORWAY (2017) 2015 | PERU (2021) 2020 | POLAND (2019) 2018 | PORTUGAL (2019) 2018 | ROMANIA (2016) 2018 | SLOVAKIA (2020) 2018 | SOUTH KOREA (2016) 2012 | SWEDEN (2018) 2018 | SWITZERLAND (2019) 2015 | TAIWAN (2016) 2014 - SEE ELECTION STUDY NOTES | TAIWAN (2020) 2019 - SEE ELECTION STUDY NOTES | THAILAND (2019) 2019 | TUNISIA (2019) 2015 | TURKEY (2018) 2016 | UNITED STATES (2016) 2016 | UNITED STATES (2020) 2019 | URUGUAY (2019) 2019 | ------------------------------------------------------------- | ELECTION STUDY NOTES - TAIWAN (2016): E5092 | | Source of data: CIA World Fact Book. | ELECTION STUDY NOTES - TAIWAN (2020): E5092 | | Source of data: Statista database | (https://www.statista.com/statistics/922574/taiwan-gini-index/) | (Date accessed: July 14, 2021). --------------------------------------------------------------------------- E5093_1 >>> GDP GROWTH - ANNUAL % (WORLD BANK) - TIME T E5093_2 >>> GDP GROWTH - ANNUAL % (WORLD BANK) - TIME T-1 E5093_3 >>> GDP GROWTH - ANNUAL % (WORLD BANK) - TIME T-2 --------------------------------------------------------------------------- World Bank estimate of the annual GDP growth at three time periods. .................................................................. -20.00 to +25.00. PERCENT ANNUAL GROWTH 99. MISSING | VARIABLE NOTES: E5093_ | | E5093_ report World Bank estimates of the annual GDP growth, at | three time periods: the election year (time T), one year before | election (T-1), and two years before election (T-2). | | Definition: E5093_ details the World Bank estimate of the annual | percentage growth rate of GDP at market prices based on constant | local currency. Aggregates are based on constant 2000 U.S. | dollars. GDP is the sum of gross value added by all resident | producers in the economy plus any product taxes and minus any | subsidies not included in the value of the products. It is | calculated without making deductions for depreciation of | fabricated assets or for depletion and degradation of natural | resources. | | Source of data: World Bank World Development Indicators Open | Database: https://data.worldbank.org/indicator/NY.GDP.MKTP.KD.ZG | (Date accessed: October 29, 2018). | | Users are advised that there is normally a two or three-year | time lag between these estimates becoming available. | Consequently, data may not be available at the time of coding. | In circumstances where this occurs, the polity will be listed | as DATA UNAVAILABLE in the VARIABLE NOTES below. | | CSES collects the most up-to-date data for each polity available | at the time the data is being processed by the CSES Secretariat. | However, aggregate-level macro data from the World Bank is often | updated retroactively as revised estimates become available. | These revised estimates are usually because of improved data | collection, or more evidence becoming available to allow for a | more robust estimates to be made, or changes in methodology. | For more see the advice of the World Bank at: | https://datahelpdesk.worldbank.org/knowledgebase/articles/114939 | -how-are-revisions-managed | (Date accessed: April 09, 2019). | | The CSES policy is to provide users with estimates of data | at the time the data is processed. CSES does not retroactively | update these estimates as to do so might impede replication. | | Data for E5093_1 are unavailable for LITHUANIA (2020) and TAIWAN | (2020). | Data for E5093_3 are unavailable for TAIWAN (2016). | ELECTION STUDY NOTES - TAIWAN (2016 & 2020): E5093 | | Source of data: CIA World Fact Book. --------------------------------------------------------------------------- E5094_1 >>> GDP PER CAPITA, PPP (WORLD BANK) - TIME T E5094_2 >>> GDP PER CAPITA, PPP (WORLD BANK) - TIME T-1 E5094_3 >>> GDP PER CAPITA, PPP (WORLD BANK) - TIME T-2 --------------------------------------------------------------------------- World Bank estimate of the GDP per capita at three time periods. .................................................................. 00000.00-899999.00 GDP PER CAPITA 999999. MISSING | VARIABLE NOTES: E5094_ | | E5094_ detail World Bank estimates of the GDP per capita at three | time periods: the election year (time T), one year before | election (T-1), and two years before election (T-2). | | Definition: E5094_ detail the World Bank estimate of GDP per | capita, i.e., the gross domestic product at purchaser prices | divided by midyear population. GDP is the sum of the gross value | added by all resident producers in the economy plus any product | taxes and minus any subsidies not included in the value of the | products. It is calculated without deductions for depreciation | of fabricated assets or for depletion and degradation of natural | resources. PPP GDP is gross domestic product converted to | international dollars using purchasing power parity rates. An | international dollar has the same purchasing power over GDP as a | U.S. dollar has in the United States. Data are in constant 2005 | international dollars. | | Source of data: World Bank World Development Indicators Open | Database: https://data.worldbank.org/indicator/NY.GDP.PCAP.PP.CD | (Date accessed: October 29, 2018). | | Users are advised that there is normally a two or three-year | time lag between these estimates becoming available. | Consequently, data may not be available at the time of coding. | In circumstances where this occurs, the polity will be listed | as DATA UNAVAILABLE in the VARIABLE NOTES below. | | CSES collects the most up-to-date data for each polity available | at the time the data is being processed by the CSES Secretariat. | However, aggregate-level macro data from the World Bank is often | updated retroactively as revised estimates become available. | These revised estimates are usually because of improved data | collection, or more evidence becoming available to allow for a | more robust estimates to be made, or changes in methodology. | For more see the advice of the World Bank at: | https://datahelpdesk.worldbank.org/knowledgebase/articles/114939 | -how-are-revisions-managed | (Date accessed: April 09, 2019). | | The CSES policy is to provide users with estimates of data | at the time the data is processed. CSES does not retroactively | update these estimates as to do so might impede replication. | | Data for E5094_1 are unavailable for TAIWAN (2020) & LITHUANIA | (2020). | Data for E5094_3 are unavailable for TAIWAN (2016 & 2020). | ELECTION STUDY NOTES - TAIWAN (2016): E5094_1 | | Source of data: CIA World Fact Book. | ELECTION STUDY NOTES - TAIWAN (2020): E5094_2 | | Source of data: Statista data platform | (https://www.statista.com/statistics/725742/countries-with-the- | largest-gross-domestic-product-gdp-at-purchasing-power-parity- | per-capita/) (Date accessed: July 14, 2021). --------------------------------------------------------------------------- E5095_1 >>> INFLATION, GDP DEFLATOR (ANNUAL %) (WORLD BANK) - TIME T E5095_2 >>> INFLATION, GDP DEFLATOR (ANNUAL %) (WORLD BANK) - TIME T-1 E5095_3 >>> INFLATION, GDP DEFLATOR (ANNUAL %) (WORLD BANK) - TIME T-2 --------------------------------------------------------------------------- World Bank estimate of Inflation at three time periods. .................................................................. -100.00-10000.00 INFLATION (ANNUAL %) 99999. MISSING | VARIABLE NOTES: E5095_ | | E5095_ detail World Bank estimates of inflation at three time | periods: the election year (time T), one year before election | (T-1), and two years before election (T-2). | | Definition: E5095_ detail the World Bank estimate of inflation. | Inflation as measured by the annual growth rate of the GDP | implicit deflator shows the rate of price change in the economy | as a whole. The GDP implicit deflator is the ratio of GDP in | current local currency to GDP in constant local currency. | | Source of data: World Bank World Development Indicators Open | Database: https://data.worldbank.org/indicator/NY.GDP.DEFL.KD.ZG | (Date accessed: October 29, 2018). | | Users are advised that there is normally a two or three-year | time lag between these estimates becoming available. | Consequently, data may not be available at the time of coding. | In circumstances where this occurs, the polity will be listed | as DATA UNAVAILABLE in the VARIABLE NOTES below. | | CSES collects the most up-to-date data for each polity available | at the time the data is being processed by the CSES Secretariat. | However, aggregate-level macro data from the World Bank is often | updated retroactively as revised estimates become available. | These revised estimates are usually because of improved data | collection, or more evidence becoming available to allow for a | more robust estimates to be made, or changes in methodology. | For more see the advice of the World Bank at: | https://datahelpdesk.worldbank.org/knowledgebase/articles/114939 | -how-are-revisions-managed | (Date accessed: April 09, 2019). | | The CSES policy is to provide users with estimates of data | at the time the data is processed. CSES does not retroactively | update these estimates as to do so might impede replication. | | Data for E5095_1 are unavailable for LITHUANIA (2020). | Data for E5095_2 are unavailable for TAIWAN (2016). | Data for E5095_3 are unavailable for TAIWAN (2016). | ELECTION STUDY NOTES - TAIWAN (2016): E5095_1 | | Source of data: CIA World Fact Book. | ELECTION STUDY NOTES - TAIWAN (2020): E5095 | | Source of data: Statista data platform | (https://www.statista.com/statistics/727598/inflation- | rate-in-taiwan/) (Date accessed: July 14, 2021). --------------------------------------------------------------------------- E5096_1 >>> CENTRAL GOVERNMENT DEBT, TOTAL (% GDP) - TIME T E5096_2 >>> CENTRAL GOVERNMENT DEBT, TOTAL (% GDP) - TIME T-1 E5096_3 >>> CENTRAL GOVERNMENT DEBT, TOTAL (% GDP) - TIME T-2 --------------------------------------------------------------------------- World Bank estimates of the Central government debt, total (% of GDP), at three time periods. .................................................................. 00.00-220.00 CENTRAL GOVERNMENT DEBT, TOTAL (% GDP) 999. MISSING | VARIABLE NOTES: E5096_ | | E5096_ detail World Bank estimates of the Central government | debt, total (% of GDP) at three time periods: the election year | (time T), one year before election (T-1), and two years before | election (T-2). | | Definition: E5096_ detail the World Bank estimate of Central | government debt. Debt is the entire stock of direct government | fixed-term contractual obligations to others outstanding on a | particular date. It includes domestic and foreign liabilities | such as currency and money deposits, securities other than | shares, and loans. It is the gross amount of government | liabilities reduced by the amount of equity and financial | derivatives held by the government. Because debt is a stock | rather than a flow, it is measured as of a given date, usually | the last day of the fiscal year. | | Source of data: World Bank World Development Indicators Open | Database: https://data.worldbank.org/indicator/GC.DOD.TOTL.GD.ZS | (Date accessed: October 29, 2018). | | Users are advised that there is normally a two or three-year | time lag between these estimates becoming available. | Consequently, data may not be available at the time of coding. | In circumstances where this occurs, the polity will be listed | as DATA UNAVAILABLE in the VARIABLE NOTES below. | | CSES collects the most up-to-date data for each polity available | at the time the data is being processed by the CSES Secretariat. | However, aggregate-level macro data from the World Bank is often | updated retroactively as revised estimates become available. | These revised estimates are usually because of improved data | collection, or more evidence becoming available to allow for a | more robust estimates to be made, or changes in methodology. | For more see the advice of the World Bank at: | https://datahelpdesk.worldbank.org/knowledgebase/articles/114939 | -how-are-revisions-managed | (Date accessed: April 09, 2019). | | The CSES policy is to provide users with estimates of data | at the time the data is processed. CSES does not retroactively | update these estimates as to do so might impede replication. | | Data for E5096_ are unavailable for CHILE (2017), COSTA RICA | (2018), CZECHIA (2017 & 2021), DENMARK (2019), FINLAND (2019), | GERMANY (2017 & 2021), HONG KONG (2016), ISRAEL (2020), | ITALY (2018), LATVIA (2018), LITHUANIA (2020), MEXICO (2018), | MONTENEGRO (2016), NETHERLANDS (2017 & 2021), NORWAY (2017), | POLAND (2019), PORTUGAL (2019), ROMANIA (2016), TAIWAN (2016 | & 2020), & TUNISIA (2019). | | Data for E5096_1 are unavailable for ALBANIA (2017), BRAZIL | (2018), INDIA (2019) and PERU (2021). | | Data for E5096_2 are unavailable for BRAZIL (2018). | | Data for E5096_3 are unavailable for ICELAND (2017), & THAILAND | (2019). --------------------------------------------------------------------------- E5097_1 >>> HUMAN DEVELOPMENT INDEX (UNPD) - TIME T E5097_2 >>> HUMAN DEVELOPMENT INDEX (UNPD) - TIME T-1 E5097_3 >>> HUMAN DEVELOPMENT INDEX (UNPD) - TIME T-2 --------------------------------------------------------------------------- UNDP Human Development Index (HDI) at three time periods. .................................................................. 00.00-1.00 HUMAN DEVELOPMENT INDEX 999. MISSING | VARIABLE NOTES: E5097_ | | E5097_ detail the UNDP Human Development Index (HDI) at three | time periods: the election year (time T), one year before | election (T-1), and two years before election (T-2). | | Definition: E5097_ details the UNDP Human Development Index | (HDI), which is a composite index measuring the average | achievements in a country in three basic dimensions of human | development: a long and healthy life; access to knowledge; and a | decent standard of living. These basic dimensions are measured by | life expectancy at birth, adult literacy and combined gross | enrolment in primary, secondary and tertiary level education, and | gross domestic product (GDP) per capita in Purchasing Power | Parity US dollars (PPP US$), respectively. | | Source of data: United Nations Human Development Database: | http://hdr.undp.org/en/data | (Date accessed: October 29, 2018). | | Users are advised that there is normally a two or three-year | time lag between these estimates becoming available. | Consequently, data may not be available at the time of coding. | In circumstances where this occurs, the polity will be listed | as DATA UNAVAILABLE in the VARIABLE NOTES below. | | Data for E5097_ are unavailable for TAIWAN (2016). | | Data for E5097_1 are unavailable for ROMANIA (2016), LITHUANIA | (2020), & TAIWAN (2020). | ELECTION STUDY NOTES - TAIWAN (2020): E5097 | | Source of data: Directorate General of Budget, Accounting, and | Statistics of Taiwan | https://www.dgbas.gov.tw/public/Data/112116036FDX2D8F3.pdf | (Date accessed: July 14, 2021). --------------------------------------------------------------------------- E5098_1 >>> POPULATION, TOTAL (WORLD BANK) - TIME T E5098_2 >>> POPULATION, TOTAL (WORLD BANK) - TIME T-1 E5098_3 >>> POPULATION, TOTAL (WORLD BANK) - TIME T-2 --------------------------------------------------------------------------- World Bank estimates of the total population size, at three time periods. .................................................................. 320,000-1,400,000,000. POPULATION SIZE 9,999,999,999. MISSING | VARIABLE NOTES: E5098_ | | E5098_ detail World Bank estimates of the total population size, | at three time periods: the election year (time T), one year | before election (T-1), and two years before election (T-2). | | Definition: E5098_ details the World Bank estimate of total | population size. Total population is based on the de facto | definition of population, which counts all residents regardless | of legal status or citizenship - except for refugees not | permanently settled in the country of asylum, who are generally | considered part of the population of their country of origin. | | Source of data: World Bank World Development Indicators Open | Database: http://data.worldbank.org/indicator/SP.POP.TOTL | (Date accessed: October 29, 2018). | | Users are advised that there is normally a two or three-year | time lag between these estimates becoming available. | Consequently, data may not be available at the time of coding. | In circumstances where this occurs, the polity will be listed | as DATA UNAVAILABLE in the VARIABLE NOTES below. | | CSES collects the most up-to-date data for each polity available | at the time the data is being processed by the CSES Secretariat. | However, aggregate-level macro data from the World Bank is often | updated retroactively as revised estimates become available. | These revised estimates are usually because of improved data | collection, or more evidence becoming available to allow for a | more robust estimates to be made, or changes in methodology. | For more see the advice of the World Bank at: | https://datahelpdesk.worldbank.org/knowledgebase/articles/114939 | -how-are-revisions-managed | (Date accessed: April 09, 2019). | | The CSES policy is to provide users with estimates of data | at the time the data is processed. CSES does not retroactively | update these estimates as to do so might impede replication. | | Data for E5098_1 are unavailable for LITHUANIA (2020). | Data for E5098_3 are unavailable for TAIWAN (2016). | ELECTION STUDY NOTES - TAIWAN (2016): E5098_1 & E5098_2 | | The population estimates come from Worldometers.info. Author: | Worldometers.info, Publishing Date: 24 March, 2019. Place of | publication: Dover, Delaware, U.S.A. (http://www.worldometers. | info/world-population/taiwan-population/; Date accessed: May | 08, 2019). | ELECTION STUDY NOTES - TAIWAN (2020): E5098_1 & E5098_2 | | The population estimates come from Worldometers.info. Author: | Worldometers.info, Place of publication: Dover, Delaware, U.S.A. | (http://www.worldometers.info/world-population/taiwan-population | (Date accessed: July 14, 2021). --------------------------------------------------------------------------- E5099_1 >>> UNEMPLOYMENT, TOTAL (WORLD BANK) - TIME T E5099_2 >>> UNEMPLOYMENT, TOTAL (WORLD BANK) - TIME T-1 E5099_3 >>> UNEMPLOYMENT, TOTAL (WORLD BANK) - TIME T-2 --------------------------------------------------------------------------- World Bank estimates of the unemployment rate (% of total labor force) at three time periods. ................................................................. 00.00-100.00 UNEMPLOYMENT RATE (% OF TOTAL LABOR FORCE) 999. MISSING | VARIABLE NOTES: E5099_ | | E5099_ details the World Bank estimate of the total unemployment | rate (% of total labor force) at three time periods: the election | year (time T), one year before election (T-1), and two years | before election (T-2). | | Definition: Unemployment is the share of the labor force without | work but available for and seeking employment. Definitions of | labor force and unemployment may differ by country. | | Source of data: World Bank World Development Indicators Open | Database: http://data.worldbank.org/indicator/SL.UEM.TOTL.ZS | (Date accessed: April 09, 2017). | | Users are advised that there is normally a two or three-year | time lag between these estimates becoming available. | Consequently, data may not be available at the time of coding. | In circumstances where this occurs, the polity will be listed | as DATA UNAVAILABLE in the VARIABLE NOTES below. | | CSES collects the most up-to-date data for each polity available | at the time the data is being processed by the CSES Secretariat. | However, aggregate-level macro data from the World Bank is often | updated retroactively as revised estimates become available. | These revised estimates are usually because of improved data | collection, or more evidence becoming available to allow for a | more robust estimates to be made, or changes in methodology. | For more see the advice of the World Bank at: | https://datahelpdesk.worldbank.org/knowledgebase/articles/114939 | -how-are-revisions-managed | (Date accessed: April 09, 2019). | | The CSES policy is to provide users with estimates of data | at the time the data is processed. CSES does not retroactively | update these estimates as to do so might impede replication. | | Data for E5099_1 are unavailable for TAIWAN (2020). | Data for E5099_2 and E5099_3 are unavailable for TAIWAN (2016). | ELECTION STUDY NOTES - TAIWAN (2020): E5099_ | | Source of data: CIA World Factbook. --------------------------------------------------------------------------- E5100_1 >>> UNEMPLOYMENT, TOTAL FOR PEOPLE AGED 15-24 YEARS (WORLD BANK) - TIME T E5100_2 >>> UNEMPLOYMENT, TOTAL FOR PEOPLE AGED 15-24 YEARS (WORLD BANK) - TIME T-1 E5100_3 >>> UNEMPLOYMENT, TOTAL FOR PEOPLE AGED 15-24 YEARS (WORLD BANK) - TIME T-2 -------------------------------------------------------------------------- World Bank estimates of the unemployment rate (% of total labor force), at three time periods. .................................................................. 00.00-100.00 UNEMPLOYMENT RATE OF PEOPLE AGED 15-24 YEARS (% OF TOTAL LABOR FORCE) 999. MISSING | VARIABLE NOTES: E5100_ | | E5100_ details the World Bank estimate of the unemployment | rate (% of total labor force) for people aged 15-24 years at | three time periods: the election year (time T), one year before | election (T-1), and two years before election (T-2). | | Definition: Unemployment is the share of the labor force without | work but available for and seeking employment. Definitions of | labor force and unemployment may differ by country. | | Source of data: World Bank World Development Indicators Open | Database: https://data.worldbank.org/indicator/SL.UEM.1524.ZS | (Date accessed: October 30, 2018). | | Users are advised that there is normally a two or three-year | time lag between these estimates becoming available. | Consequently, data may not be available at the time of coding. | In circumstances where this occurs, the polity will be listed | as DATA UNAVAILABLE in the VARIABLE NOTES below. | | CSES collects the most up-to-date data for each polity available | at the time the data is being processed by the CSES Secretariat. | However, aggregate-level macro data from the World Bank is often | updated retroactively as revised estimates become available. | These revised estimates are usually because of improved data | collection, or more evidence becoming available to allow for a | more robust estimates to be made, or changes in methodology. | For more see the advice of the World Bank at: | https://datahelpdesk.worldbank.org/knowledgebase/articles/114939 | -how-are-revisions-managed | (Date accessed: April 09, 2019). | | The CSES policy is to provide users with estimates of data | at the time the data is processed. CSES does not retroactively | update these estimates as to do so might impede replication. | | Data for E5100_ are unavailable for TAIWAN (2020). | Data for E5100_1 are unavailable for LITHUANIA (2020). | Data for E5100_3 are unavailable for TAIWAN (2016). | ELECTION STUDY NOTES - TAIWAN (2016): E5100_1 | | Source of data: CIA World Fact Book. --------------------------------------------------------------------------- E5101 >>> COUNTRY SUBJECT TO IMF CONDITIONALITY AT ELECTION --------------------------------------------------------------------------- Is the Polity subject to IMF conditionality at election? .................................................................. 1. YES 5. NO 9. MISSING | VARIABLE NOTES: E5101 | | Source of data: International Monetary Fund - Available at: | https://www.imf.org/external/np/pdr/mona/index.aspx | (Date accessed: October 30, 2018). | | Data are unavailable for HONG KONG (2016). --------------------------------------------------------------------------- E5102 >>> TI CORRUPTION PERCEPTION INDEX --------------------------------------------------------------------------- The Transparency International Corruption Perceptions Index (CPI). .................................................................. 00.-100. TI CORRUPTION PERCEPTION INDEX 999. MISSING | VARIABLE NOTES: E5102 | | Definition: E5102 details the Transparency International | Corruption Perceptions Index (CPI), that aggregates data from | several sources providing perceptions of business people and | country experts of the level of corruption in the public sector. | The Index measures the perceived levels of public sector | corruption in countries worldwide, scoring them from 0 (highly | corrupt) to 100 (very clean). | | Source of data: Transparency International - available at: | http://www.transparency.org/research/cpi/overview | (Date accessed: April 09, 2019). | | Users are advised that there is normally a two or three-year | time lag between these estimates becoming available. | Consequently, data may not be available at the time of coding. | In circumstances where this occurs, the polity will be listed | as DATA UNAVAILABLE in the VARIABLE NOTES below. --------------------------------------------------------------------------- E5103_1 >>> CONTROL OF CORRUPTION INDEX ESTIMATE - TIME T E5103_1se >>> CONTROL OF CORRUPTION INDEX ESTIMATE - TIME T ST. ERROR E5103_2 >>> CONTROL OF CORRUPTION INDEX ESTIMATE - TIME T-1 E5103_2se >>> CONTROL OF CORRUPTION INDEX ESTIMATE - TIME T-1 ST. ERROR E5103_3 >>> CONTROL OF CORRUPTION INDEX ESTIMATE - TIME T-2 E5103_3se >>> CONTROL OF CORRUPTION INDEX ESTIMATE - TIME T-2 ST. ERROR --------------------------------------------------------------------------- World Bank Control of Corruption Index in the given year (E5103_) and the standard errors (E5103_se) associated with these estimates. .................................................................. -001.-100. CONTROL OF CORRUPTION INDEX 999. MISSING | VARIABLE NOTES: E5103_ | | E5103_ detail the World Bank Control of Corruption Index at three | time periods: the election year (time T), one year before | election (T-1), and two years before election (T-2). | These data are available in two forms. The first is the estimate | in the given year (E5103_1, E5103_2, and E5103_3) and the | standard errors (E5103_1se, E5103_2se, and E5103_3se) associated | with these estimates. | | Definition: Control of Corruption captures perceptions of the | extent to which public power is exercised for private gain, | including both petty and grand forms of corruption, as well as | "capture" of the state by elites and private interests. | | Standard error indicates the precision of the estimate of | governance. Larger values of the standard error indicate less | precise estimates. A 90 percent confidence interval for the | governance estimate is given by the estimate +/- 1.64 times the | standard error. | | Source of data and definitions: World Bank World Development | Indicators Open Database: | http://databank.worldbank.org/data/source/worldwide-governance- | indicators# | (Date accessed: October 30, 2018). | | Data for E5103_1 and E5103_1se are unavailable for LITHUANIA | (2020) & TAIWAN (2020). --------------------------------------------------------------------------- E5104_1 >>> QOG EXPERT JUDGEMENT OF PUBLIC SECTOR: FIRMS PROVIDE KICKBACKS TO PUBLIC SERVANTS --------------------------------------------------------------------------- QOG expert judgment of public sector: Firms that provide the most favorable kickbacks to senior officials are awarded public procurement contracts in favor of forms making the lowest bid. .................................................................. 01. HARDLY EVER 02. 03. 04. 05. 06. 07. ALMOST ALWAYS 09. MISSING | VARIABLE NOTES: E5104_1 | | Source of data: Dahlstrom, C., J. Teorell, S. Dahlberg, F. | Hartmann, A. Lindberg, & M. Nistotskaya (2015). The QoG Expert | Survey Dataset II. University of Gothenburg: The Quality of | Government Institute. | | Data are unavailable for MONTENEGRO (2016) and TUNISIA (2019). --------------------------------------------------------------------------- E5104_2 >>> QOG EXPERT JUDGEMENT OF PUBLIC SECTOR: PUBLIC SECTOR EMPLOYEES AND HOW THEY TREAT SOCIETY --------------------------------------------------------------------------- QOG expert judgment of public sector: When deciding to implement policies in individual cases, public sector employees treat some groups in society unfairly. .................................................................. 01. HARDLY EVER 02. 03. 04. 05. 06. 07. ALMOST ALWAYS 09. MISSING | VARIABLE NOTES: E5104_2 | | Source of data: Dahlstrom, C., J. Teorell, S. Dahlberg, F. | Hartmann, A. Lindberg, & M. Nistotskaya (2015). The QoG Expert | Survey Dataset II. University of Gothenburg: The Quality of | Government Institute. | | Data are unavailable for SLOVAKIA (2020) and TUNISIA (2019). --------------------------------------------------------------------------- E5104_3 >>> QOG EXPERT JUDGEMENT OF PUBLIC SECTOR: TREAT CASES IMPARTIALLY --------------------------------------------------------------------------- QOG expert judgment of public sector: Generally speaking, how often would you say that public sector employees today, in our chose country, act impartially when deciding how to implement a policy in an individual case? .................................................................. 01. HARDLY EVER 02. 03. 04. 05. 06. 07. ALMOST ALWAYS 09. MISSING | VARIABLE NOTES: E5104_3 | | Source of data: Dahlstrom, C., J. Teorell, S. Dahlberg, F. | Hartmann, A. Lindberg, & M. Nistotskaya (2015). The QoG Expert | Survey Dataset II. University of Gothenburg: The Quality of | Government Institute. | | Data are unavailable for TUNISIA (2019). --------------------------------------------------------------------------- E5104_4 >>> QOG EXPERT JUDGEMENT OF PUBLIC SECTOR: STRIVE TO FOLLOW RULES --------------------------------------------------------------------------- QOG expert judgment of public sector: Public sector employees strive to follow rules. .................................................................. 01. HARDLY EVER 02. 03. 04. 05. 06. 07. ALMOST ALWAYS 09. MISSING | VARIABLE NOTES: E5104_4 | | Source of data: Dahlstrom, C., J. Teorell, S. Dahlberg, F. | Hartmann, A. Lindberg, & M. Nistotskaya (2015). The QoG Expert | Survey Dataset II. University of Gothenburg: The Quality of | Government Institute. | | Data are unavailable for TUNISIA (2019). --------------------------------------------------------------------------- E5105_1 >>> NET MIGRATION RATE 2000-2005 --------------------------------------------------------------------------- The net difference in the number of migrants during the period 2000-2005. .................................................................. -100.00 to +100.00. NET MIGRATION RATE 2000-2005 999.00. MISSING | VARIABLE NOTES: E5105_1 | | E5105_1 details the net difference in the number of migrants as | an average estimate of the net number of migrants per 1,000 of | the population during the period 2000-2005. | | E5105_1 is calculated by taking the number of immigrants minus | the number of emigrants and dividing by the person/years lived | by the population of the receiving country over that period. | A positive value represents more people entering the country than | leaving it. A negative value represents more people leaving than | entering the country. | | Source of data: the United Nations World Population Prospects | 2015 revisions - available at: | see: https://esa.un.org/unpd/wpp/Download/Standard/Migration/ | (Date accessed: October 30, 2018). | | Users are advised that there is normally a two or three-year | time lag between these estimates becoming available. | Consequently, data may not be available at the time of coding. | In circumstances where this occurs, the polity will be listed | as DATA UNAVAILABLE in the VARIABLE NOTES below. | | CSES collects the most up-to-date data for each polity available | at the time the data is being processed by the CSES Secretariat. | However, aggregate-level macro data from the United Nations is | often updated retroactively as revised estimates become | available. These revised estimates are usually because of | improved data collection, or more evidence becoming available to | allow for more robust estimates to be made, or changes in | methodology. | | The CSES policy is to provide users with estimates of data | at the time the data is processed. CSES does not retroactively | update these estimates as to do so might impede replication. --------------------------------------------------------------------------- E5105_2 >>> NET MIGRATION RATE 2005-2010 --------------------------------------------------------------------------- The net difference in the number of migrants during the period 2005-2010. .................................................................. -100.00 to +100.00. NET MIGRATION RATE 2005-2010 999.00. MISSING | VARIABLE NOTES: E5105_2 | | E5105_2 details the net difference in the number of migrants as | an average estimate of the net number of migrants per 1,000 of | the population during the period 2005-2010. | | E5105_2 is calculated by taking the number of immigrants minus | the number of emigrants and dividing by the person/years lived | by the population of the receiving country over that period. | A positive value represents more people entering the country than | leaving it. A negative value represents more people leaving than | entering the country. | | Source of data: UN World Population Prospects, the 2015 Revision | Net Migration Rate by Major Area, Region, and Country - | Available at: http://esa.un.org/unpd/wpp/Excel-Data/migration.htm | (Date accessed: May 08, 2019). | | Users are advised that there is normally a two or three-year | time lag between these estimates becoming available. | Consequently, data may not be available at the time of coding. | In circumstances where this occurs, the polity will be listed | as DATA UNAVAILABLE in the VARIABLE NOTES below. | | CSES collects the most up-to-date data for each polity available | at the time the data is being processed by the CSES Secretariat. | However, aggregate-level macro data from the United Nations is | often updated retroactively as revised estimates become | available. These revised estimates are usually because of | improved data collection, or more evidence becoming available to | allow for more robust estimates to be made, or changes in | methodology. | | The CSES policy is to provide users with estimates of data | at the time the data is processed. CSES does not retroactively | update these estimates as to do so might impede replication. --------------------------------------------------------------------------- E5105_3 >>> NET MIGRATION RATE 2010-2015 --------------------------------------------------------------------------- The net difference in the number of migrants during the period 2010-2015. .................................................................. -100.00 to +100.00. NET MIGRATION RATE 2010-2015 999.00. MISSING | VARIABLE NOTES: E5105_3 | | E5105_3 details the net difference in the number of migrants as | an average estimate of the net number of migrants per 1,000 of | the population during the period 2010-2015. | | E5105_3 is calculated by taking the number of immigrants minus | the number of emigrants and dividing by the person/years lived | by the population of the receiving country over that period. | A positive value represents more people entering the country than | leaving it. A negative value represents more people leaving than | entering the country. | | Source of data: UN World Population Prospects, the 2015 Revision | Net Migration Rate by Major Area, Region, and Country - | Available at: http://esa.un.org/unpd/wpp/Excel-Data/migration.htm | (Date accessed: May 08, 2019). | | Users are advised that there is normally a two or three-year | time lag between these estimates becoming available. | Consequently, data may not be available at the time of coding. | In circumstances where this occurs, the polity will be listed | as DATA UNAVAILABLE in the VARIABLE NOTES below. | | CSES collects the most up-to-date data for each polity available | at the time the data is being processed by the CSES Secretariat. | However, aggregate-level macro data from the United Nations is | often updated retroactively as revised estimates become | available. These revised estimates are usually because of | improved data collection, or more evidence becoming available to | allow for more robust estimates to be made, or changes in | methodology. | | The CSES policy is to provide users with estimates of data | at the time the data is processed. CSES does not retroactively | update these estimates as to do so might impede replication. --------------------------------------------------------------------------- E5105_4 >>> NET MIGRATION RATE 2015-2020 --------------------------------------------------------------------------- The net difference in the number of migrants during the period 2015-2020. .................................................................. -100.00 to +100.00. NET MIGRATION RATE 2015-2020 999.00. MISSING | VARIABLE NOTES: E5105_4 | | E5105_4 details the net difference in the number of migrants as | an average estimate of the net number of migrants per 1,000 of | the population during the period 2015-2020. | | E5105_4 is calculated by taking the number of immigrants minus | the number of emigrants and dividing by the person/years lived | by the population of the receiving country over that period. | A positive value represents more people entering the country than | leaving it. A negative value represents more people leaving than | entering the country. | | Source of data: UN World Population Prospects, the 2015 Revision | Net Migration Rate by Major Area, Region, and Country - | Available at: http://esa.un.org/unpd/wpp/Excel-Data/migration.htm | (Date accessed: May 08, 2019). | | Users are advised that there is normally a two or three-year | time lag between these estimates becoming available. | Consequently, data may not be available at the time of coding. | In circumstances where this occurs, the polity will be listed | as DATA UNAVAILABLE in the VARIABLE NOTES below. | | CSES collects the most up-to-date data for each polity available | at the time the data is being processed by the CSES Secretariat. | However, aggregate-level macro data from the United Nations is | often updated retroactively as revised estimates become | available. These revised estimates are usually because of | improved data collection, or more evidence becoming available to | allow for more robust estimates to be made, or changes in | methodology. | | The CSES policy is to provide users with estimates of data | at the time the data is processed. CSES does not retroactively | update these estimates as to do so might impede replication. | | Data unavailable for IRELAND (2016). --------------------------------------------------------------------------- E5106_1 >>> POPULATION BY CITIZENSHIP: PERCENTAGE OF POPULATION WHO ARE CITIZENS --------------------------------------------------------------------------- Population by citizenship (citizens). .................................................................. 000.00-100.00 PERCENT OF POPULATION (CITIZENS) 999.00. MISSING | VARIABLE NOTES: E5106_1 | | Source of data: United Nations Demographic Statistics Database - | Available at: https://unstats.un.org/unsd/demographic-social/ | (Date accessed: October 29, 2018) | | The time lag for this variable becoming available is often | many years. CSES where possible has a policy of providing users | with the data in the year of election. However, at the time of | processing, population data by citizenship status is often | unavailable and this can remain the case for several years. | To avoid excessive missing values for multiple studies, | CSES provides population-by-citizenship data for the year | closest to the election available at the time of data processing. | The specific years for which the population-by-citizenship data | refers to are listed in the below table. | | The CSES policy is to provide users with estimates of data | at the time the data is processed. CSES does not retroactively | update these estimates as to do so might impede replication. | | Data are unavailable for CHILE (2017), EL SALVADOR (2019), | ICELAND (2016 & 2017), INDIA (2019), ISRAEL (2020), MEXICO | (2018), NETHERLANDS (2017 & 2021), NEW ZEALAND (2017 & 2020), | TAIWAN (2016 & 2020), TUNISIA (2019) & URUGUAY (2019). | | +++ TABLE: POPULATION CLASSIFICATIONS SOURCE DATA YEAR BY | ELECTION STUDY | | POLITY (ELEC YEAR) Year of Population Classification | ------------------------------------------------------------- | ALBANIA (2017) 2011 | AUSTRALIA (2019) 2017 | AUSTRIA (2017) 2012 | BELGIUM-FLANDERS (2019) 2011 | BELGIUM-WALLONIA (2019) 2011 | BRAZIL (2018) 2010 | CANADA (2019) 2016 | COSTA RICA (2018) 2007 | CZECHIA (2017) 2012 | CZECHIA (2021) 2012 | DENMARK (2019) 2019 - SEE ELECTION STUDY NOTES | FINLAND (2019) 2011 | FRANCE (2017) 2015 | GERMANY (2017) 2014 | GERMANY (2021) 2014 | GREAT BRITAIN (2017) 2014 | GREAT BRITAIN (2019) 2014 | GREECE (2015) 2011 | GREECE (2019) 2014 | HONG KONG (2016) 2016 | HUNGARY (2018) 2011 | IRELAND (2016) 2011 | ITALY (2018) 2012 | JAPAN (2017) 2015 | LATVIA (2018) 2013 | LITHUANIA (2016) 2014 | LITHUANIA (2020) 2014 | MONTENEGRO (2016) 2013 | NORWAY (2017) 2011 | PERU (2021) 2009 | POLAND (2019) 2013 | PORTUGAL (2019) 2013 | ROMANIA (2016) 2002 | SLOVAKIA (2020) 2013 | SOUTH KOREA (2016) 2015 | SWEDEN (2018) 2014 | SWITZERLAND (2019) 2012 | THAILAND (2019) 2010 | TURKEY (2018) 2009 | UNITED STATES (2016) 2000 | UNITED STATES (2020) 2000 | ------------------------------------------------------------- | ELECTION STUDY NOTES - DENMARK (2019): E5106_1 | | Source of data: Statistics Denmark | https://www.statistikbanken.dk/statbank5a/default.asp?w=1280 | Source Year: 2019 | (Date accessed: December 07, 2021). --------------------------------------------------------------------------- E5106_2 >>> POPULATION BY CITIZENSHIP: PERCENTAGE OF POPULATION FOREIGN BORN/NOT CITIZEN --------------------------------------------------------------------------- Population by citizenship (foreigners). .................................................................. 000.00-100.00 PERCENT OF POPULATION (FOREIGNERS) 999.00. MISSING | VARIABLE NOTES: E5106_2 | | Source of data: United Nations Demographic Statistics Database - | Available at: https://unstats.un.org/unsd/demographic-social/ | (Date accessed: October 29, 2018). | | The time lag for this variable becoming available is often | many years. CSES where possible has a policy of providing users | with the data in the year of election. However, at the time of | processing, population data by citizenship status is often | unavailable and this can remain the case for several years. | To avoid excessive missing values for multiple studies, | CSES provides population-by-citizenship data for the year | closest to the election available at the time of data processing. | The specific years for which the population-by-citizenship data | refers to are listed in the table provided in the VARIABLE NOTES | for E5106_1. | | The CSES policy is to provide users with estimates of data | at the time the data is processed. CSES does not retroactively | update these estimates as to do so might impede replication. | | Data are unavailable for CHILE (2017), EL SALVADOR (2019), | ICELAND (2016 & 2017), INDIA (2019), ISRAEL (2020), MEXICO | (2018), NETHERLANDS (2017 & 2021), NEW ZEALAND (2017 & 2020), | TAIWAN (2016 & 2020), TUNISIA (2019) and URUGUAY (2019). | | The years for which source data are available by election study | are listed in the variable notes for variable E5106_1. | ELECTION STUDY NOTES - DENMARK (2019): E5106_2 | | Source of data: Statistics Denmark | https://www.statistikbanken.dk/statbank5a/default.asp?w=1280 | Source Year: 2019 | (Date accessed: December 07, 2021). --------------------------------------------------------------------------- E5106_3 >>> POPULATION BY CITIZENSHIP: PERCENTAGE OF POPULATION UNKNOWN CITIZENSHIP STATUS --------------------------------------------------------------------------- Population by citizenship (unknown). .................................................................. 000.00-100.00 PERCENT OF POPULATION (UNKNOWN) 999.00. MISSING | VARIABLE NOTES: E5106_3 | | Source of data: United Nations Demographic Statistics Database - | Available at: https://unstats.un.org/unsd/demographic-social/ | (Date accessed: October 29, 2018). | | The time lag for this variable becoming available is often | many years. CSES where possible has a policy of providing users | with the data in the year of election. However, at the time of | processing, population data by citizenship status is often | unavailable and this can remain the case for several years. | To avoid excessive missing values for multiple studies, | CSES provides population-by-citizenship data for the year | closest to the election available at the time of data processing. | The specific years for which the population-by-citizenship data | refers to are listed in the table provided in the VARIABLE NOTES | for E5106_1. | | The CSES policy is to provide users with estimates of data | at the time the data is processed. CSES does not retroactively | update these estimates as to do so might impede replication. | | Data are unavailable for CHILE (2017), EL SALVADOR (2019), | ICELAND (2016 & 2017), INDIA (2019), ISRAEL (2020), MEXICO | (2018), NETHERLANDS (2017 & 2021), NEW ZEALAND (2017 & 2020), | TAIWAN (2016 & 2020), TUNISIA (2019), UNITED STATES (2016) and | URUGUAY (2019). | | The years for which source data are available by election study | are listed in the variable notes for variable E5106_1. | ELECTION STUDY NOTES - DENMARK (2019): E5106_3 | | Source of data: Statistics Denmark | https://www.statistikbanken.dk/statbank5a/default.asp?w=1280 | Source Year: 2019 | (Date accessed: December 07, 2021). --------------------------------------------------------------------------- E5107 >>> LINGUISTIC FRACTIONALIZATION INDEX: ALESINA ET AL. 2003 --------------------------------------------------------------------------- Linguistic Fractionalization Index (Alesina et al., 2003). .................................................................. 0.00-1.00 LINGUISTIC FRACTIONALIZATION INDEX 9.00 MISSING | VARIABLE NOTES: E5107 | | Source of data: Alesina, A., Devleeschauwer, A., Easterly, W., | Kurlat, S., Wacziarg, R. (2003). Fractionalization. Journal of | Economic Growth. Vol.8, 155-194. Data available at: | http://www.anderson.ucla.edu/faculty_pages/romain.wacziarg/ | papersum.html | (Date accessed: October 29, 2018). | | Data are unavailable for MONTENEGRO (2016). | | The following table gives an overview of the Alesina et al. 2003 | data and the year for which E5107 was calculated for. | | +++ TABLE: LINGUISTIC FRACTIONALIZATION SOURCE DATA YEAR | BY ELECTION STUDY | | POLITY (ELEC YEAR) Year of Fractionalization Estimate | ------------------------------------------------------------- | ALBANIA (2017) 2001 | AUSTRALIA (2019) 2001 | AUSTRIA (2017) 2001 | BRAZIL (2018) 2001 | BELGIUM-FLANDERS (2019) 2001 | BELGIUM-WALLONIA (2019) 2001 | CANADA (2019) 2001 | CHILE (2017) 2001 | COSTA RICA (2018) 2001 | CZECHIA (2017) 1991 | CZECHIA (2021) 1991 | DENMARK (2019) 2001 | EL SALVADOR (2019) 2001 | FINLAND (2019) 2001 | FRANCE (2017) 2001 | GERMANY (2017) 1997 | GERMANY (2021) 1997 | GREAT BRITAIN (2017) 2001 | GREAT BRITAIN (2019) 2001 | GREECE (2015) 2001 | GREECE (2019) 2001 | HONG KONG (2016) 2001 | HUNGARY (2018) 2001 | ICELAND (2016) 2001 | ICELAND (2017) 2001 | INDIA (2019) 2001 | IRELAND (2016) 2001 | ISRAEL (2020) 2001 | ITALY (2018) 2001 | JAPAN (2017) 2001 | LATVIA (2018) 2001 | LITHUANIA (2016) 2001 | LITHUANIA (2020) 2001 | MEXICO (2018) 2001 | MONTENEGRO (2016) UNAVAILABLE | NETHERLANDS (2017) 2001 | NETHERLANDS (2021) 2001 | NEW ZEALAND (2017) 2001 | NEW ZEALAND (2020) 2001 | NORWAY (2017) 2001 | PERU (2021) 1981 | POLAND (2019) 2001 | PORTUGAL (2019) 2001 | ROMANIA (2016) 2001 | SLOVAKIA (2020) 2001 | SOUTH KOREA (2016) 2001 | SWEDEN (2018) 2001 | SWITZERLAND (2019) 2001 | TAIWAN (2016) 2001 | TAIWAN (2020) 2001 | THAILAND (2019) 2001 | TUNISIA (2019) 2001 | TURKEY (2018) 2001 | UNITED STATES (2016) 2001 | UNITED STATES (2020) 2001 | URUGUAY (2019) 2001 | ------------------------------------------------------------- --------------------------------------------------------------------------- E5108 >>> RELIGIOUS FRACTIONALIZATION INDEX: ALESINA ET AL. 2003 --------------------------------------------------------------------------- Religious Fractionalization Index (Alesina et al., 2003). .................................................................. 0.00-1.00 RELIGIOUS FRACTIONALIZATION INDEX 9.00 MISSING | VARIABLE NOTES: E5108 | | Source of data: Alesina, A., Devleeschauwer, A., Easterly, W., | Kurlat, S., Wacziarg, R. (2003). Fractionalization. Journal of | Economic Growth. Vol.8, 155-194. Data available at: | http://www.anderson.ucla.edu/faculty_pages/romain.wacziarg/ | papersum.html | (Date accessed: October 29, 2018). | | Data are unavailable for MONTENEGRO (2016). | | The following table gives an overview of the Alesina et al. 2003 | data and the year for which E5108 was calculated for. | | +++ TABLE: RELIGIOUS FRACTIONALIZATION SOURCE DATA YEAR | BY ELECTION STUDY | | POLITY (ELEC YEAR) Year of Fractionalization Estimate | ------------------------------------------------------------- | ALBANIA (2017) 2001 | AUSTRALIA (2019) 2001 | AUSTRIA (2017) 2001 | BELGIUM-FLANDERS (2019) 2001 | BELGIUM-WALLONIA (2019) 2001 | BRAZIL (2018) 2001 | CANADA (2019) 2001 | CHILE (2017) 2001 | COSTA RICA (2018) 2001 | CZECHIA (2017) 1991 | CZECHIA (2021) 1991 | DENMARK (2019) 2001 | EL SALVADOR (2019) 2001 | FINLAND (2019) 2001 | FRANCE (2017) 2001 | GERMANY (2017) 1997 | GERMANY (2021) 1997 | GREAT BRITAIN (2017) 2001 | GREAT BRITAIN (2019) 2001 | GREECE (2015) 2001 | GREECE (2019) 2001 | HONG KONG (2016) 2001 | HUNGARY (2018) 2001 | ICELAND (2016) 2001 | ICELAND (2017) 2001 | INDIA (2019) 2001 | IRELAND (2016) 2001 | ISRAEL (2020) 2001 | ITALY (2018) 2001 | JAPAN (2017) 2001 | LATVIA (2018) 2001 | LITHUANIA (2016) 2001 | LITHUANIA (2020) 2001 | MEXICO (2018) 2001 | MONTENEGRO (2016) UNAVAILABLE | NETHERLANDS (2017) 2001 | NETHERLANDS (2021) 2001 | NEW ZEALAND (2017) 2001 | NEW ZEALAND (2020) 2001 | NORWAY (2017) 2001 | PERU (2021) 1981 | POLAND (2019) 2001 | PORTUGAL (2019) 2001 | ROMANIA (2016) 2001 | SLOVAKIA (2020) 2001 | SOUTH KOREA (2016) 2001 | SWEDEN (2018) 2001 | SWITZERLAND (2019) 2011 | TAIWAN (2016) 2001 | TAIWAN (2020) 2001 | THAILAND (2019) 2001 | TUNISIA (2019) 2001 | TURKEY (2018) 2001 | UNITED STATES (2016) 2001 | UNITED STATES (2020) 2001 | URUGUAY (2019) 2001 | ------------------------------------------------------------- --------------------------------------------------------------------------- E5109 >>> ETHNIC FRACTIONALIZATION INDEX: ALESINA ET AL. 2003 --------------------------------------------------------------------------- Ethnic Fractionalization Index (Alesina et al., 2003). .................................................................. 0.00-1.00 ETHNIC FRACTIONALIZATION INDEX 9.00 MISSING | VARIABLE NOTES: E5109 | | Source of data: Alesina, A., Devleeschauwer, A., Easterly, W., | Kurlat, S., Wacziarg, R. (2003). Fractionalization. Journal of | Economic Growth. Vol.8, 155-194. Data available at: | http://www.anderson.ucla.edu/faculty_pages/romain.wacziarg/ | papersum.html | (Date accessed: October 29, 2018). | | Data are unavailable for MONTENEGRO (2016). | | The following table gives an overview of the Alesina et al. 2003 | data and the year for which E5109 was calculated for. | | +++ TABLE: ETHNIC FRACTIONALIZATION METRIC SOURCE DATA YEAR | BY ELECTION STUDY | | POLITY (ELEC YEAR) Year of Fractionalization Estimate | ------------------------------------------------------------- | ALBANIA (2017) 1989 | AUSTRALIA (2019) 1986 | AUSTRIA (2017) 1998 | BELGIUM-FLANDERS (2019) 2001 | BELGIUM-WALLONIA (2019) 2001 | BRAZIL (2018) 1995 | CANADA (2019) 1991 | CHILE (2017) 1992 | COSTA RICA (2018) 1993 | CZECHIA (2017) 1991 | CZECHIA (2021) 1991 | DENMARK (2019) 1996 | EL SALVADOR (2019) 1993 | FINLAND (2019) 2001 | FRANCE (2017) 1999 | GERMANY (2017) 1997 | GERMANY (2021) 1997 | GREAT BRITAIN (2017) 1994 | GREAT BRITAIN (2019) 1994 | GREECE (2015) 1998 | GREECE (2019) 1998 | HONG KONG (2016) 1994 | HUNGARY (2018) 1993 | ICELAND (2016) 1995 | ICELAND (2017) 1995 | INDIA (2019) 2000 | IRELAND (2016) 1997 | ISRAEL (2020) 1995 | ITALY (2018) 1983 | JAPAN (2017) 1999 | LATVIA (2018) 1996 | LITHUANIA (2016) 1996 | LITHUANIA (2020) 1996 | MEXICO (2018) 1996 | MONTENEGRO (2016) UNAVAILABLE | NETHERLANDS (2017) 1995 | NETHERLANDS (2021) 1995 | NEW ZEALAND (2017) 1996 | NEW ZEALAND (2020) 1996 | NORWAY (2017) 1998 | PERU (2021) 1981 | POLAND (2019) 1998 | PORTUGAL (2019) 1998 | ROMANIA (2016) 1998 | SLOVAKIA (2020) 2001 | SOUTH KOREA (2016) 1990 | SWEDEN (2018) 1998 | SWITZERLAND (2019) 2001 | TAIWAN (2016) 2001 | TAIWAN (2020) 2001 | THAILAND (2019) 1983 | TUNISIA (2019) 2001 | TURKEY (2018) 2001 | UNITED STATES (2016) 2000 | UNITED STATES (2020) 2000 | URUGUAY (2019) 1990 | ------------------------------------------------------------- --------------------------------------------------------------------------- E5110 >>> POLITY FRAGMENTATION INDEX --------------------------------------------------------------------------- Polity Fragmentation Index (POLITY IV Project). .................................................................. 0. NO OVERT FRAGMENTATION 1. SLIGHT FRAGMENTATION 2. MODERATE FRAGMENTATION 3. SERIOUS FRAGMENTATION 9. MISSING | VARIABLE NOTES: E5110 | | E5110 details the POLITY IV Projects' Polity Fragmentation Index, | which provides information about "the operational existence of a | separate polity, or polities, comprising substantially territory | and population within the recognized borders of the state and | over which the coded polity exercises no effective authority | (effective authority may be participatory or coercive)." | | Source of data: POLITY IV Project: | Political Regime Characteristics and Transitions, 1800-2017, | Monty G. Marshall and Keith Jaggers, George Mason University and | Colorado State University | (http://www.systemicpeace.org/polity/polity4.htm). | (Date accessed: May 08, 2019). | | The Polity IV Dataset Users' Manual: | http://www.systemicpeace.org/inscr/p4manualv2017.pdf | (Date accessed: April 05, 2019). | | The Polity IV annual time-series dataset | (www.systemicpeace.org/inscr/p4v2017.xls; Date accessed: April | 30, 2020). | | Users are advised that there is normally a two or three-year | time lag between these estimates becoming available. | Consequently, for Advance Releases of the CSES (and possibly | Full Releases), data may not be available at the time of coding. | In circumstances where this occurs, the polity will be listed | as DATA UNAVAILABLE in the VARIABLE NOTES below. Should data | become available between an Advance Release of CSES and a Full | Release of CSES, data for these polities may be included in a | subsequent release of the CSES. | | CSES collects the most up-to-date data for each polity available | at the time the data is being processed by the CSES Secretariat. | However, aggregate-level macro data from the United Nations is | often updated retroactively as revised estimates become | available. These revised estimates are usually because of | improved data collection, or more evidence becoming available to | allow for more robust estimates to be made, or changes in | methodology. | | The CSES policy is to provide users with estimates of data | at the time the data is processed. CSES does not retroactively | update these estimates as to do so might impede replication. | | Data are unavailable for AUSTRALIA (2019), BELGIUM-FLANDERS | (2019), BELGIUM-WALLONIA (2019), HONG KONG (2016), ICELAND | (2016, 2017), ISRAEL (2020), ITALY (2018) and SLOVAKIA (2020). --------------------------------------------------------------------------- E5111 >>> PERCENTAGE OF INDIVIDUALS USING THE INTERNET --------------------------------------------------------------------------- Percentage of individuals using the Internet. .................................................................. 00.00-100.00 PERCENTAGE OF INDIVIDUALS USING THE INTERNET 999.00 MISSING | VARIABLE NOTES: E5111 | | Source of data: The International Telecommunication Union ICT | eye statistics. (http://www.itu.int/ITU-D/icteye/Indicators/ | Indicators.aspx) | (Date accessed: October 29, 2018). | | Users are advised that there is normally a two or three-year | time lag between these estimates becoming available. | Consequently, data may not be available at the time of coding. | In circumstances where this occurs, the polity will be listed | as DATA UNAVAILABLE in the VARIABLE NOTES below. | | CSES collects the most up-to-date data for each polity available | at the time the data is being processed by the CSES Secretariat. | However, aggregate-level macro data from the United Nations is | often updated retroactively as revised estimates become | available. These revised estimates are usually because of | improved data collection, or more evidence becoming available to | allow for more robust estimates to be made, or changes in | methodology. | | The CSES policy is to provide users with estimates of data | at the time the data is processed. CSES does not retroactively | update these estimates as to do so might impede replication. | | Data are unavailable for TAIWAN (2020). --------------------------------------------------------------------------- E5112 >>> MOBILE PHONE SUBSCRIPTIONS PER 100 INHABITANTS --------------------------------------------------------------------------- Number of mobile-cellular subscriptions per 100 inhabitants. .................................................................. 00.00-800.00 MOBILE PHONE SUBSCRIPTIONS PER 100 INHABITANTS 999. MISSING | VARIABLE NOTES: E5112 | | Source of data: The International Telecommunication Union ICT | eye statistics (http://www.itu.int/ITU-D/icteye/Indicators/ | Indicators.aspx) | (Date accessed: October 29, 2018). | | Users are advised that there is normally a two or three-year | time lag between these estimates becoming available. | Consequently, data may not be available at the time of coding. | In circumstances where this occurs, the polity will be listed | as DATA UNAVAILABLE in the VARIABLE NOTES below. | | CSES collects the most up-to-date data for each polity available | at the time the data is being processed by the CSES Secretariat. | However, aggregate-level macro data from the United Nations is | often updated retroactively as revised estimates become | available. | These revised estimates are usually because of improved data | collection, or more evidence becoming available to allow for | more robust estimates to be made, or changes in methodology. | | The CSES policy is to provide users with estimates of data | at the time the data is processed. CSES does not retroactively | update these estimates as to do so might impede replication. | | Data are unavailable for LITHUANIA (2020) & TAIWAN (2020). --------------------------------------------------------------------------- E5113 >>> FIXED TELEPHONE LINES PER 100 INHABITANTS --------------------------------------------------------------------------- Number of Fixed-telephone subscriptions per 100 inhabitants. .................................................................. 00.00-100.00 FIXED TELEPHONE LINES PER 100 INHABITANTS 999. MISSING | VARIABLE NOTES: E5113 | | Source of data: The International Telecommunication Union ICT | eye statistics (http://www.itu.int/ITU-D/icteye/Indicators/ | Indicators.aspx) | (Date accessed: October 29, 2018). | | Users are advised that there is normally a two or three-year | time lag between these estimates becoming available. | Consequently, data may not be available at the time of coding. | In circumstances where this occurs, the polity will be listed | as DATA UNAVAILABLE in the VARIABLE NOTES below. | | CSES collects the most up-to-date data for each polity available | at the time the data is being processed by the CSES Secretariat. | However, aggregate-level macro data from the United Nations is | often updated retroactively as revised estimates become | available. | These revised estimates are usually because of improved data | collection, or more evidence becoming available to allow for | more robust estimates to be made, or changes in methodology. | | The CSES policy is to provide users with estimates of data | at the time the data is processed. CSES does not retroactively | update these estimates as to do so might impede replication. | | Data are unavailable for LITHUANIA (2020) & TAIWAN (2020). IV. MACRO DATA: ADDITIONAL DATA BRIDGING VARIABLES --------------------------------------------------------------------------- E5200_A >>> MANIFESTO RESEARCH ON POLITICAL REPRESENTATION (MARPOR/CMP) IDENTIFIER - PARTY A E5200_B >>> MANIFESTO RESEARCH ON POLITICAL REPRESENTATION (MARPOR/CMP) IDENTIFIER - PARTY B E5200_C >>> MANIFESTO RESEARCH ON POLITICAL REPRESENTATION (MARPOR/CMP) IDENTIFIER - PARTY C E5200_D >>> MANIFESTO RESEARCH ON POLITICAL REPRESENTATION (MARPOR/CMP) IDENTIFIER - PARTY D E5200_E >>> MANIFESTO RESEARCH ON POLITICAL REPRESENTATION (MARPOR/CMP) IDENTIFIER - PARTY E E5200_F >>> MANIFESTO RESEARCH ON POLITICAL REPRESENTATION (MARPOR/CMP) IDENTIFIER - PARTY F E5200_G >>> MANIFESTO RESEARCH ON POLITICAL REPRESENTATION (MARPOR/CMP) IDENTIFIER - PARTY G E5200_H >>> MANIFESTO RESEARCH ON POLITICAL REPRESENTATION (MARPOR/CMP) IDENTIFIER - PARTY H E5200_I >>> MANIFESTO RESEARCH ON POLITICAL REPRESENTATION (MARPOR/CMP) IDENTIFIER - PARTY I --------------------------------------------------------------------------- MARPOR/CMP numeric party identifier for PARTY [A/B/C/D/E/F/G/H/I]. .................................................................. 11110-171611. MARPOR/CMP PARTY IDENTIFIER 999999. NOT AVAILABLE IN MANIFESTO RESEARCH ON POLITICAL REPRESENTATION (MARPOR/CMP) DATASET | VARIABLE NOTES: E5200_ | | POTENTIAL PARTY/COALITION LEVEL BRIDGING IDENTIFIER | | E5200_ detail the party identification codes from the Manifesto | Research on Political Representation (MARPOR/CMP) project. Codes | are provided for parties that are assigned an alphabetical code | (A-I) by the CSES and for polities for which MARPOR/CMP | identifiers are available. | The complete list of PARTIES A-I and their MARPOR/CMP codes are | detailed in Part 3 of the Codebook. | | The MARPOR/CMP party codes were retrieved from the Manifesto | Project Dataset (version 2017b): | Volkens, A., Lehmann, P., Matthiess, T., Merz, N., Regel, S., | and Wessels, B. (2017): The Manifesto Data Collection. Manifesto | Project (MRG/CMP/MARPOR). Version 2017b. Berlin: | Wissenschaftszentrum Berlin fuer Sozialforschung (WZB). | doi: 10.25522/manifesto.mpds.2017b | | Available at: https://manifestoproject.wzb.eu/datasets | (Date accessed: May 22, 2018). | | Users are advised that CSES only provides data in E5200_ for the | main MARPOR/CMP product listed above. Other supplementary | datasets, such as the Manifesto Project Dataset: South America, | have not been considered. | | Data are unavailable for BRAZIL (2018), CHILE (2017), COSTA | RICA (2018), EL SALVADOR (2019), HONG KONG (2016), INDIA (2019), | PERU (2021), TAIWAN (2016 & 2020), THAILAND (2019) and TUNISIA | (2019). --------------------------------------------------------------------------- E5201_A >>> PARLIAMENTS AND GOVERNMENT DATABASE (PARLGOV) IDENTIFIER - PARTY A E5201_B >>> PARLIAMENTS AND GOVERNMENT DATABASE (PARLGOV) IDENTIFIER - PARTY B E5201_C >>> PARLIAMENTS AND GOVERNMENT DATABASE (PARLGOV) IDENTIFIER - PARTY C E5201_D >>> PARLIAMENTS AND GOVERNMENT DATABASE (PARLGOV) IDENTIFIER - PARTY D E5201_E >>> PARLIAMENTS AND GOVERNMENT DATABASE (PARLGOV) IDENTIFIER - PARTY E E5201_F >>> PARLIAMENTS AND GOVERNMENT DATABASE (PARLGOV) IDENTIFIER - PARTY F E5201_G >>> PARLIAMENTS AND GOVERNMENT DATABASE (PARLGOV) IDENTIFIER - PARTY G E5201_H >>> PARLIAMENTS AND GOVERNMENT DATABASE (PARLGOV) IDENTIFIER - PARTY H E5201_I >>> PARLIAMENTS AND GOVERNMENT DATABASE (PARLGOV) IDENTIFIER - PARTY I --------------------------------------------------------------------------- ParlGov numeric party identifier for PARTY [A/B/C/D/E/F/G/H/I]. .................................................................. 0002-2808. PARLGOV PARTY IDENTIFIER 9999. NOT AVAILABLE IN PARLIAMENTS AND GOVERNMENT DATABASE (PARLGOV) | VARIABLE NOTES: E5201_ | | POTENTIAL PARTY/COALITION LEVEL BRIDGING IDENTIFIER | | E5201_ detail the party identification codes from the Parliaments | and Government Database (ParlGov) project. Codes are provided for | parties that are assigned an alphabetical code (A-I) by the CSES | and for polities, for which ParlGov identifiers are available. | The complete list of PARTIES A-I and their ParlGov codes are | detailed in Part 3 of the Codebook. | | The ParlGov party codes were retrieved from the projects' | website, available at: http://www.parlgov.org/#data | (Date accessed: April 04, 2018). | | Data are unavailable for ALBANIA (2017), BRAZIL (2018), CHILE | (2017), COSTA RICA (2018), EL SALVADOR (2019), HONG KONG (2016), | INDIA (2019), MEXICO (2018), MONTENEGRO (2016), PERU (2021), | SOUTH KOREA (2016), TAIWAN (2016 & 2020), THAILAND (2019), | TUNISIA (2019), UNITED STATES (2016 & 2020) and URUGUAY (2019). --------------------------------------------------------------------------- E5202_A >>> CHAPEL HILL EXPERT SURVEY (CHES) IDENTIFIER - PARTY A E5202_B >>> CHAPEL HILL EXPERT SURVEY (CHES) IDENTIFIER - PARTY B E5202_C >>> CHAPEL HILL EXPERT SURVEY (CHES) IDENTIFIER - PARTY C E5202_D >>> CHAPEL HILL EXPERT SURVEY (CHES) IDENTIFIER - PARTY D E5202_E >>> CHAPEL HILL EXPERT SURVEY (CHES) IDENTIFIER - PARTY E E5202_F >>> CHAPEL HILL EXPERT SURVEY (CHES) IDENTIFIER - PARTY F E5202_G >>> CHAPEL HILL EXPERT SURVEY (CHES) IDENTIFIER - PARTY G E5202_H >>> CHAPEL HILL EXPERT SURVEY (CHES) IDENTIFIER - PARTY H E5202_I >>> CHAPEL HILL EXPERT SURVEY (CHES) IDENTIFIER - PARTY I --------------------------------------------------------------------------- CHES numeric party identifier for PARTY [A/B/C/D/E/F/G/H/I]. .................................................................. 102-6007. CHES PARTY/COALITION IDENTIFIER 9999. NOT AVAILABLE IN CHAPEL HILL EXPERT SURVEY (CHES) DATABASE | VARIABLE NOTES: E5202_A-I | | POTENTIAL PARTY/COALITION LEVEL BRIDGING IDENTIFIER | | E5202_ detail the party identification codes from the Chapel Hill | Expert Survey Database (CHES) project. Codes are provided for | parties that are assigned an alphabetical code (A-I) by the CSES | and for polities, for which CHES identifiers are available. | | The complete list of PARTIES A-I and their CHES codes are | detailed in Part 3 of the CSES MODULE 5 Codebook. | | The Chapel Hill expert surveys estimate party positioning on | European integration, ideology and policy issues for national | parties in a variety of European countries. The first survey was | conducted in 1999, with subsequent waves in 2002, 2006, 2010, | 2014, and 2019. Questions on parties' general position on | European integration, several EU policies, general left/right, | economic left/right, and social left/right are common to all | surveys. | | The CHES party codes were retrieved from the project website, | available at: https://www.chesdata.eu/our-surveys | (Date accessed: February 05, 2020). | | Data are unavailable for ALBANIA (2017), AUSTRALIA (2019), BRAZIL | (2018), CANADA (2019), CHILE (2017), COSTA RICA (2018), EL | SALVADOR (2019), HONG KONG (2016), INDIA (2019), ISRAEL (2020), | JAPAN (2017), MEXICO (2018), NEW ZEALAND (2017 & 2020), PERU | (2021), SOUTH KOREA (2016), TAIWAN (2016 & 2020), THAILAND | (2019), TUNISIA (2019), UNITED STATES (2016 & 2020) and URUGUAY | (2019). --------------------------------------------------------------------------- E5203_A >>> PARTY FACTS IDENTIFIER - PARTY A E5203_B >>> PARTY FACTS IDENTIFIER - PARTY B E5203_C >>> PARTY FACTS IDENTIFIER - PARTY C E5203_D >>> PARTY FACTS IDENTIFIER - PARTY D E5203_E >>> PARTY FACTS IDENTIFIER - PARTY E E5203_F >>> PARTY FACTS IDENTIFIER - PARTY F E5203_G >>> PARTY FACTS IDENTIFIER - PARTY G E5203_H >>> PARTY FACTS IDENTIFIER - PARTY H E5203_I >>> PARTY FACTS IDENTIFIER - PARTY I --------------------------------------------------------------------------- Party Facts numeric party identifier for PARTY [A/B/C/D/E/F/G/H/I]. .................................................................. 0003-9089. PARTY FACTS PARTY/COALITION IDENTIFIER 9999. NOT AVAILABLE IN PARTY FACTS PROJECT | VARIABLE NOTES: E5203_A-I | | POTENTIAL PARTY/COALITION LEVEL BRIDGING IDENTIFIER | | E5203_ detail the party identification codes from the Party Facts | project. Codes are provided for parties that are assigned an | alphabetical code (A-I) by the CSES and for polities for which | Party Facts identifiers are available. | | The complete list of PARTIES A-I and their Party Facts codes | are detailed in Part 3 of the CSES MODULE 5 Codebook. | | Party Facts links datasets on political parties and provides an | online platform about parties and their history as recorded in | social science datasets. | Political scientists have accumulated a large amount of data on | political parties. With this information, we can trace the | dynamics of party competition across countries and time. However, | the many existing datasets with crucial information about | political parties are difficult to link. Party Facts establishes | an infrastructure that supports political scientists in linking | parties across datasets. | | The Party Facts codes were retrieved from the project website, | available at: | https://partyfacts.herokuapp.com/download/ | (Date accessed: July 15, 2020). =========================================================================== ))) CSES MODULE 5 VARIABLES: DATA BRIDGING WITH CSES PRODUCTS =========================================================================== --------------------------------------------------------------------------- E6000_PR_1 >>> IMD BRIDGING VARIABLE: CURRENT PRESIDENTIAL ELECTION: VOTE CHOICE - 1ST ROUND E6000_PR_2 >>> IMD BRIDGING VARIABLE: CURRENT PRESIDENTIAL ELECTION: VOTE CHOICE - 2ND ROUND --------------------------------------------------------------------------- Respondent's vote choice for President in the first/second round of election, based on numeric party codes from the CSES Integrated Module Dataset (CSES IMD). .................................................................. 0000001-9000000. [SEE CSES IMD CODEBOOK PART 3 FOR HARMONIZED PARTY /COALITION NUMERICAL CODES] 9999980. CSES IMD NUMERIC PARTY CODE NOT ASSIGNED YET 9999988. NONE OF THE CANDIDATES 9999989. INDEPENDENT CANDIDATE 9999990. OTHER LEFT WING CANDIDATE (NOT FURTHER SPECIFIED) 9999991. OTHER RIGHT WING CANDIDATE (NOT FURTHER SPECIFIED) 9999992. OTHER CANDIDATE (NOT FURTHER SPECIFIED) 9999993. INVALID/ BLANK BALLOT 9999995. NOT APPLICABLE: NO ROLE OF PRESIDENT 9999996. NOT APPLICABLE: NO PRESIDENTIAL ELECTION/ NO SECOND ROUND 9999997. VOLUNTEERED: REFUSED 9999998. VOLUNTEERED: DON'T KNOW 9999999. MISSING/ABSTAINED (DID NOT VOTE) | VARIABLE NOTES: E6000_PR_ | | POTENTIAL CSES PRODUCT BRIDGING IDENTIFIER | | E6000_ detail respondents' vote choice in the current election - | if applicable and respondents cast a ballot - based on | harmonized numeric identification codes applied in the CSES | Integrated Module Dataset (IMD), a CSES data product including | data from all four completed CSES Modules. | | By coding vote choice according to IMD standards, E6000_ | variables thus ease appending the current version of CSES | MODULE 5 to the CSES IMD and thereby facilitate longitudinal | comparative research. | | In CSES IMD, each party/coalition receives a unique numerical | identifier that is consistent across modules. This seven-digit | numerical identifier, on which coding for E6000_ is based, | contains information on the polity and a unique numerical value | to distinguish the party/coalition. Hence, numerical party/ | coalition codes are harmonized across Modules within CSES IMD. | For more detailed information on how CSES codes | parties/coalitions, please see Part 3 of the CSES IMD Codebook. | | The harmonized and consistent codes for parties/coalitions are | detailed in Part 3 of the CSES IMD Codebook. Users can search for | the following term: "CSES IMD HARMONIZED PARTY/COALITION | NUMERICAL CODES". | | The corresponding variables to E6000_ in the CSES IMD are: | E6000_PR_1: IMD3002_PR_1 | E6000_PR_2: IMD3002_PR_2 | E6000_LH_PL: IMD3002_LH_PL | E6000_LH_DC: IMD3002_LH_DC | | Codes are provided in E6000_PR_ for parties that are assigned a | harmonized IMD numeric party code by the CSES and for polities | which are at least represented once in the CSES IMD. | Parties that are not represented in the IMD and have thus not | been assigned an IMD numeric party code yet are coded "999980. | IMD NUMERIC PARTY CODE NOT ASSIGNED YET" in E6000_PR_ and are | listed in the table below. | | +++ TABLE: PARTIES INCLUDED IN E3013_PR_ FOR WHICH IMD NUMERIC | PARTY CODES HAVE NOT BEEN ASSIGNED YET | | CSES MODULE 5 NUMERICAL CODE CSES MODULE 5 ALPHABETICAL | AND PARTY/COALITION NAME PARTY CODE (IF APPLICABLE) |----------------------------------------------------------------- | BRAZIL (2018): | 076013. New Party (NOVO) | 076026. Sustainability Network (REDE) | | CHILE (2017): | 152006. Democratic Revolution (RD) PARTY F | 152011. Progressive Party (PRO) | 152017. Patriotic Union (UPA) | 152020. Pais | 152089. Jose Antonio Kast (Independent) | | FRANCE (2017): | 250001. The Republic Onwards! (LaREM) PARTY A | 250004. Indomitable France (FI) PARTY D | 250007. Resist! | 250009. Popular Republican Union (UPR) | | MEXICO (2018): | 484089. Jaime Heliodoro Rodriguez Calderon | (Independent) | | PERU (2021): | 604001. Free Peru (PL) PARTY A | 604003. Popular Renewal (RP) PARTY C | 604004. Go on Country-Social Integration Party (AvP) PARTY D | 604006. Together for Peru (JP) PARTY F | 604008. National Victory (VN) | 604009. We Can Peru (PL) PARTY H | 604010. Purple Party (PM) PARTY I | 604011. Christian People's Party (PPC) | 604013. Peruvian Nationalist Party (PNP) | 604014. Union for Peru (UPP) | 604015. National United Renaissance (RUNA) | | TURKEY (2018): | 792005. Good Party (IYI) PARTY E | | URUGUAY (2019): | 858004. Open Cabildo PARTY D | 858005. Intransigent Radical Ecology Party (PERI) PARTY E | 858006. People's Party PARTY F | 858009. Green Animalist Party (PVA) PARTY I | 858010. Digital Party |----------------------------------------------------------------- | | Users are advised that appending the CSES MODULE 5 dataset to | CSES IMD requires renaming E6000_ variables in accordance with | IMD naming conventions first. | In what follows, we provide example syntax on how appending | can be achieved in STATA: | | ** // RENAMING E1005 ID VARIABLE AND E6000_ VARIABLES ACCORDING | ** TO IMD STANDARDS | | rename E1005 IMD1005 | rename E6000_PR_1 IMD3002_PR_1 | rename E6000_PR_2 IMD3002_PR_2 | rename E6000_LH_PL IMD3002_LH_PL | rename E6000_LH_DC IMD3002_LH_DC | | ** // SAVING MODULE 5 DATASET | save "cses5.dta", replace | | ** // APPENDING CSES MODULE 5 DATASET TO CSES IMD | use "cses_imd.dta", clear | append using "cses5.dta" | | ** // END OF EXAMPLE CODE | | Further, users should note that upon appending the CSES MODULE 5 | dataset to IMD, code "9999980. CSES IMD NUMERIC PARTY CODE NOT | ASSIGNED YET" will not be labeled yet, as this code was newly | introduced in E6000_ and has hence not been envisaged for IMD. --------------------------------------------------------------------------- E6000_LH_PL >>> IMD BRIDGING VARIABLE: CURRENT LOWER HOUSE ELECTION: VOTE CHOICE: PARTY LIST --------------------------------------------------------------------------- Respondent's vote choice for party list in the current Lower House elections, based on numeric party codes from the CSES Integrated Module Dataset (CSES IMD). .................................................................. 0000001-9000000. [SEE CSES IMD CODEBOOK PART 3 FOR HARMONIZED PARTY /COALITION NUMERICAL CODES] 9999980. CSES IMD NUMERIC PARTY CODE NOT ASSIGNED YET 9999988. NONE OF THE CANDIDATES/PARTIES 9999989. INDEPENDENT CANDIDATE 9999990. OTHER LEFT WING CANDIDATE/PARTY (NOT FURTHER SPECIFIED) 9999991. OTHER RIGHT WING CANDIDATE/PARTY (NOT FURTHER SPECIFIED) 9999992. OTHER CANDIDATE/PARTY (NOT FURTHER SPECIFIED) 9999993. INVALID/ BLANK BALLOT 9999995. NOT APPLICABLE: NOT A LIST SYSTEM 9999996. NOT APPLICABLE: NO LOWER HOUSE ELECTION 9999997. VOLUNTEERED: REFUSED 9999998. VOLUNTEERED: DON'T KNOW 9999999. MISSING/ABSTAINED (DID NOT VOTE) | VARIABLE NOTES: E6000_LH_PL | | POTENTIAL CSES PRODUCT BRIDGING IDENTIFIER | | E6000_ detail respondents' vote choice in the current election - | if applicable and respondents cast a ballot - based on | harmonized numeric identification codes applied in the | CSES Integrated Module Dataset (IMD), a CSES data product | including data from all four completed CSES Modules. | | By coding vote choice according to IMD standards, E6000_ | variables thus ease appending the current version of CSES | MODULE 5 to the CSES IMD and thereby facilitate longitudinal | comparative research. | | In CSES IMD, each party/coalition receives a unique numerical | identifier that is consistent across modules. This seven-digit | numerical identifier, on which coding for E6000_ is based, | contains information on the polity and a unique numerical value | to distinguish the party/coalition. Hence, numerical party/ | coalition codes are harmonized across Modules within CSES IMD. | For more detailed information on how CSES codes | parties/coalitions, please see Part 3 of the CSES IMD Codebook. | | The harmonized and consistent codes for parties/coalitions are | detailed in Part 3 of the CSES IMD Codebook. Users can search for | the following term: "CSES IMD HARMONIZED PARTY/COALITION | NUMERICAL CODES". | | The corresponding variables to E6000_ in the CSES IMD are: | E6000_PR_1: IMD3002_PR_1 | E6000_PR_2: IMD3002_PR_2 | E6000_LH_PL: IMD3002_LH_PL | E6000_LH_DC: IMD3002_LH_DC | | Codes are provided in E6000_LH_PL for parties that are assigned | a harmonized IMD numeric party code by the CSES and for polities | which are at least represented once in the CSES IMD. | Parties that are not represented in the IMD and have thus not | been assigned an IMD numeric party code yet are coded "999980. | IMD NUMERIC PARTY CODE NOT ASSIGNED YET" in E6000_LH_PL and are | listed in the table below. | | +++ TABLE: PARTIES INCLUDED IN E3013_LH_PL FOR WHICH IMD NUMERIC | PARTY CODES HAVE NOT BEEN ASSIGNED YET | | CSES MODULE 5 NUMERICAL CODE CSES MODULE 5 ALPHABETICAL | AND PARTY/COALITION NAME PARTY CODE (IF APPLICABLE) |----------------------------------------------------------------- | ALBANIA (2017): | 008004. Party for Justice, Integration and Unity (PDIU) PARTY D | 008005. Libra Party (LIBRA) PARTY E | 008007. New Democratic Spirit | 008009. Party for the Future of the Greek Minority | (MEGA) | | AUSTRIA (2017): | 040005. Peter Pilz List PARTY E | 040007. Roland Dueringer List - My Vote Counts (GILT) | 040008. Communist Party of Austria and | Platform PLUS - Open List (KPOE+) | 040009. Free Austria List and FPS | Dr. Karl Schnell List (FLOE) | | BELGIUM-WALLONIA (2019): | 056907. People's Party (PP) | | BRAZIL (2018): | 076013. New Party (NOVO) | 076026. Sustainability Network (REDE) | 076032. Party of Brazilian Women (PMB) | | CHILE (2017): | 152006. Democratic Revolution (RD) PARTY F | 152008. Political Evolution (Evopoli) PARTY H | 152011. Progressive Party (PRO) | 152014. Social Green Regionalist Federation (FREVS) | 152015. Citizen Power | 152016. Amplitude | 152017. Patriotic Union (UPA) | 152018. Liberal Party of Chile (PL) | 152024. MAS Region (MAS) | 152027. Otro | 152030. Let's Go Chile | 152031. The Force of the Majority / New Majority | 152032. Broad Front | 152033. Democratic Convergence | 152034. All Over Chile | 152035. Green Regionalist Coalition | 152036. Let's Add | | CZECHIA (2017): | 203004. Freedom and Direct Democracy (SPD) PARTY D | 203009. Mayors and Independents (STAN) PARTY I | 203013. Realists | 203017. Bloc against Islamization - Defense of the Homeland | 203018. Good Choice 2016 | | CZECHIA (2021): | 203101. Together (SPOLU) | 203103. Pirates and Mayors (PirStan) | 203104. Freedom and Direct Democracy (SPD) PARTY D | 203105. Oath (PSH) | 203108. Trikolora-Svobodni-Soukromnici | 203109. Free Block | 203111. Swiss Democracy (SD) | 203114. Sources Movement | 203115. Don't Vote Urza.cz. | 203116. Alliance of National Forces (ANS) | 203117. Pensioners 21 | 203118. The Left | | DENMARK (2019): | 208008. The Alternative PARTY H | 208009. The New Right PARTY I | 208011. Hard Line | 208013. Klaus Riskaer Pedersen List | | FINLAND (2019): | 246009. Blue Reform PARTY I | | GERMANY (2017): | 276015. Basic Income Alliance (BGE) | 276016. V-Party 3 - Party for Change, Vegetarians | and Vegans (V-Partei3) | 276017. Democracy in Motion (DiB) | 276019. Alliance of German Democrats (AD-Demokraten) | | GERMANY (2021): | 276110. Grassroots Democratic Party of Germany | (dieBasis) | 276112. Team Todenhoefer - The Justice Party | 276114. Volt Germany (Volt) | 276118. Party of Humanists (Die Humanisten) | 276119. Alliance C - Christians for Germany | (Buendnis C) | 276122. The Greys - For all Generations (Die Grauen) | 276126. Party of Progress (PdF) | 276129. Courage | | GREECE (2015): | 300004. Democratic Coalition - PASOK-DIMAR PARTY D | 300009. Popular Unity (LAE) | 300010. Front of the Greek Anticapitalist Left | (ANTARSYA) - Workers Revolutionary Party (EEK) | 300011. United Popular Front (EPAM) | 300012. Society | 300014. Democrats-Society of Values - | Pirate Party of Greece (D-KA-KPE) | | GREECE (2019): | 300103. Movement for Change (KINAL) PARTY C | 300105. Greek Solution PARTY E | 300106. European Realistic Disobedience Front (MeRA25) PARTY F | 300108. Course of Freedom PARTY H | 300111. United Popular Front (EPAM) | 300113. Popular Unity (LAE) | | HONG KONG (2016): | 344006. People Power - League of Social Democrats PARTY F | (PP - LSD) | 344010. Civic Passion - Hong Kong Resurgence Order | 344011. Civic Passion (CP) | 344012. Proletariat Political Institute (PPI) | 344016. Youngspiration | 344017. Kowloon East Community | 344018. Demosisto | 344019. Business and Professionals Alliance | for Hong Kong | 344020. Democracy Groundwork | 344025. Path of Democracy | 344026. Third Side | 344027. Justice Alliance | 344029. Voice of Loving Hong Kong | 344031. Pioneer of Victoria Park | | HUNGARY (2018): | 348001. Fidesz-KDNP PARTY A | 348003. Hungarian Socialist Party - PARTY C | Dialogue for Hungary (MSZP) | 348004. Politics Can Be Different (LMP) PARTY D | 348005. Democratic Coalition (DK) PARTY E | 348006. Momentum Movement PARTY F | 348007. Hungarian Two-tailed Dog Party PARTY G | 348008. Together PARTY H | | ICELAND (2016): | 352005. Reform Party PARTY E | 352008. People's Party (FIF) PARTY H | 352010. People's Front of Iceland (PFI) | | ICELAND (2017): | 352104. Centre Party (M) PARTY D | 352107. People's Party (FIF) PARTY G | 352108. Reform Party PARTY H | | ISRAEL (2020): | 376002. Blue and White (KL) PARTY B | 376003. Joint List PARTY C | 376006. Labor-Gesher-Meretz (Emet) PARTY F | 376008. Yamina PARTY H | | ITALY (2018): | 380008. Us with Italy - Christian Democratic Union | (NcI-UdC) | 380009. Power to the People (PaP) | 380011. Together List | 380012. Communist Party (PC) | 380013. For a Revolutionary Left (PuSR) | 380014. CasaPound Italy (CPI) | 380015. The People of Family (PdF) | | JAPAN (2017): | 392002. Constitutional Democratic Party of Japan (CDP) PARTY B | 392003. Party of Hope PARTY C | 392006. Japan Innovation Party PARTY F | 392008. Party for Japanese Kokoro | | LATVIA (2018): | 428002. Who Owns the State? (KPV LV) PARTY B | 428004. Development/For! (AP!) PARTY D | 428005. National Alliance (NA) PARTY E | 428010. The Progressives PARTY I | 428012. Latvian Nationalists | 428013. For an Alternative | 428014. SKG Alliance | 428015. Action Party | | LITHUANIA (2016): | 440001. Homeland Union - Lithuanian Christian PARTY A | Democrats (TS-LKD) | 440002. Lithuania Union of Farmers and Greens (LVZS) PARTY B | 440003. Lithuanian Social Democratic Party (LSDP) PARTY C | 440004. Liberal Movement of the Republic of Lithuania PARTY D | (LRLS) | 440005. Anti-Corruption Coalition (LCP-LPP) PARTY E | 440007. Party 'Order and Justice' (PTT) PARTY G | 440008. Labor Party (DP) PARTY H | 440009. Lithuanian Freedom Union (Liberals) (LLS) | 440010. Lithuanian Green Party (LZP) | 440011. Political Pary 'List of Lithuania' | 440012. Lithuanian People's Party (LLP) | 440013. Coalition of Anti-Corruption and Poverty | (JL-LTS) | | LITHUANIA (2020): | 440102. Lithuanian Farmers and Greens Union (LVZS) PARTY B | 440103. Labor Party (DP) PARTY C | 440105. Freedom Party (LP) PARTY E | 440106. Liberal Movement of the Republic of PARTY F | Lithuania (LRLS) | 440108. Lithuanian Social Democratic Labor Party PARTY H | (LSDDP) | 440109. Lithuanian Center Party - Nationalists (CPT) PARTY I | 440110. National Alliance (NS) | 440111. Freedom and Justice (LT) | 440112. Lithuanian Green Party (LZP) | 440113. The Way of Courage (DK) | 440114. Party 'Lithuania - For Everyone' (PLV) | 440115. Christian Union (KS) | 440116. The Union of Generations' Solidarity - | Unity for Lithuania (KSSSL) | 440117. Lithuanian People's Party (LLP) | | MONTENEGRO (2016): | 499003. Key Coalition (DEMOS, SNP, URA) PARTY C | 499006. Social Democrats of Montenegro (SD) PARTY F | 499008. Albanians Decisively (FORCA-DUA-AA) PARTY H | 499011. Albanian Coalition "With one Goal" | 499012. Democratic Alliance of Albanians | 499013. Serb Party (SS) | 499014. Bosniak Democratic Union in Montenegro (BDZ) | | NETHERLANDS (2017): | 528010. 50Plus (50+) | 528012. Political Movement Think (DENK) | 528013. Forum for Democracy (FvD) | 528014. For Netherlands (VNL) | 528015. Pirate Party (PPNL) | 528016. Article 1 | 528017. New Ways | 528018. Entrepreneurs Party | | NETHERLANDS (2021): | 528108. Forum for Democracy (FvD) PARTY H | 528111. Volt Netherlands (Volt) | 528112. Correct Answer 2021 (JA21) | 528114. Political Movement Think (DENK) | 528115. 50Plus (50+) | 528116. Farmer-Citizen Movement (BBB) | 528117. Together (BIJ1) | 528118. Code Orange (CO) | 528119. NIDA | 528120. Splinter | 528121. Pirate Party (PPNL) | 528122. Young | 528124. Henk Krol List (LHK) | 528125. NLBetter | 528127. Libertarian Party (LP) | 528128. OpRecht | 528129. Free and Social Netherlands (VSN) | | NEW ZEALAND (2017): | 554005. The Opportunities Party (TOP) PARTY E | | PERU (2021): | 604001. Free Peru (PL) PARTY A | 604003. Popular Renewal (RP) PARTY C | 604004. Go on Country-Social Integration Party (AvP) PARTY D | 604006. Together for Peru (JP) PARTY F | 604008. National Victory (VN) | 604009. We Can Peru (PL) PARTY H | 604010. Purple Party (PM) PARTY I | 604011. Christian People's Party (PPC) | 604013. Peruvian Nationalist Party (PNP) | 604014. Union for Peru (UPP) | 604015. National United Renaissance (RUNA) | 604017. Peru Secure Homeland (PPS) | 604019. Agricultural People's Front of Peru (FREPAP) | 604020. With You (C) | | POLAND (2019): | 616010. Confederation Liberty and Independence PARTY I | | PORTUGAL (2019): | 620007. Enough (CH) PARTY G | 620008. Liberal Initiative (IL) PARTY H | 620009. Free (L) PARTY I | 620010. Alliance (A) | | ROMANIA (2016): | 642003. Save Romania Union (USR) PARTY C | 642005. Alliance of Liberals and Democrats (ALDE) PARTY E | 642006. People's Movement Party (PMP) PARTY F | 642007. United Romania Party (PRU) PARTY G | 642010. Our Romania Alliance (ANR) PARTY I | | SLOVAKIA (2020): | 703005. Progressive Slovakia - TOGETHER-Civic Democracy PARTY E | 703007. For the People PARTY G | 703009. Hungarian Community Togetherness (MKO) PARTY I | 703011. Good Choice | 703012. Homeland | 703014. Socialist.sk | 703015. Hlinka's Slovak People's Party | 703017. Mayors and Independents | 703018. Labor of the Slovak Nation | | SOUTH KOREA (2016): | 410002. Democratic Party of Korea (DP) PARTY B | 410003. The People's Party (PP) PARTY C | 410004. Justice Party (JP) PARTY D | | TAIWAN (2016): | 158003. New Power Party (NPP) PARTY C | 158004. Green-Social Democratic Coalition (GP - SDP) PARTY D | 158005. Minkuotang (MKT) PARTY E | 158009. Faith and Hope League | 158010. Trees Party (TP) | 158012. Chinese Unionist Party (CUP) | 158013. Free Taiwan Party (FTP) | 158014. MCFAP | 158017. Peace Dove Alliance Party | | TAIWAN (2020): | 158103. Taiwan People's Party (TPP) PARTY C | 158104. New Power Party (NPP) PARTY D | 158106. Taiwan Statebuilding Party (TSP) PARTY F | 158107. Congress Party Alliance | 158110. Stabilizing Force Party | 158111. Taiwan Action Party Alliance | 158114. Formosa Alliance | 158116. Interfaith Union | | THAILAND (2019): | 764001. State Power Party PARTY A | 764003. Future Forward Party PARTY C | 764006. New Economics Party PARTY F | 764008. Thai Liberal Party PARTY H | 764009. People's Nation Party PARTY I | 764010. Puea Chat Party | 764011. Action Coalition for Thailand | 764013. Thai Local Power Party | 764014. Thai Forest Conversation Party | | TURKEY (2018): | 792005. Good Party (IYI) PARTY E | | URUGUAY (2019): | 858004. Open Cabildo PARTY D | 858005. Intransigent Radical Ecology Party (PERI) PARTY E | 858006. People's Party PARTY F | 858009. Green Animalist Party (PVA) PARTY I | 858010. Digital Party |----------------------------------------------------------------- | | Users are advised that appending the CSES MODULE 5 dataset to | CSES IMD requires renaming E6000_ variables in accordance with | IMD naming conventions first. | In what follows, we provide example syntax on how appending | can be achieved in STATA: | | ** // RENAMING E1005 ID VARIABLE AND E6000_ VARIABLES ACCORDING | ** TO IMD STANDARDS | | rename E1005 IMD1005 | rename E6000_PR_1 IMD3002_PR_1 | rename E6000_PR_2 IMD3002_PR_2 | rename E6000_LH_PL IMD3002_LH_PL | rename E6000_LH_DC IMD3002_LH_DC | | ** // SAVING MODULE 5 DATASET | save "cses5.dta", replace | | ** // APPENDING CSES MODULE 5 DATASET TO CSES IMD | use "cses_imd.dta", clear | append using "cses5.dta" | | ** // END OF EXAMPLE CODE | | Further, users should note that upon appending the CSES MODULE 5 | dataset to IMD, code "9999980. CSES IMD NUMERIC PARTY CODE NOT | ASSIGNED YET" will not be labeled yet, as this code was newly | introduced in E6000_ and has hence not been envisaged for IMD. --------------------------------------------------------------------------- E6000_LH_DC >>> IMD BRIDGING VARIABLE: CURRENT LOWER HOUSE ELECTION: VOTE CHOICE: DISTRICT CANDIDATE --------------------------------------------------------------------------- Respondent's vote choice for district candidate in the current Lower House elections, based on numeric party codes from the CSES Integrated Module Dataset (CSES IMD). .................................................................. 0000001-9000000. [SEE CSES IMD CODEBOOK PART 3 FOR HARMONIZED PARTY /COALITION NUMERICAL CODES] 9999980. CSES IMD NUMERIC PARTY CODE NOT ASSIGNED YET 9999988. NONE OF THE CANDIDATES/PARTIES 9999989. INDEPENDENT CANDIDATE 9999990. OTHER LEFT WING CANDIDATE/PARTY (NOT FURTHER SPECIFIED) 9999991. OTHER RIGHT WING CANDIDATE/PARTY (NOT FURTHER SPECIFIED) 9999992. OTHER CANDIDATE/PARTY (NOT FURTHER SPECIFIED) 9999993. INVALID/ BLANK BALLOT 9999995. NOT APPLICABLE: NO DISTRICT CANDIDATE VOTE 9999996. NOT APPLICABLE: NO LOWER HOUSE ELECTION 9999997. VOLUNTEERED: REFUSED 9999998. VOLUNTEERED: DON'T KNOW 9999999. MISSING/ABSTAINED (DID NOT VOTE) | VARIABLE NOTES: E6000_LH_DC | | POTENTIAL CSES PRODUCT BRIDGING IDENTIFIER | | E6000_ detail respondents' vote choice in the current election - | if applicable and respondents cast a ballot - based on | harmonized numeric identification codes applied in the CSES | Integrated Module Dataset (IMD), a CSES data product including | data from all four completed CSES Modules. | | By coding vote choice according to IMD standards, E6000_ | variables thus ease appending the current version of CSES | MODULE 5 to the CSES IMD and thereby facilitate longitudinal | comparative research. | | In CSES IMD, each party/coalition receives a unique numerical | identifier that is consistent across modules. This seven-digit | numerical identifier, on which coding for E6000_ is based, | contains information on the polity and a unique numerical value | to distinguish the party/coalition. Hence, numerical party/ | coalition codes are harmonized across Modules within CSES IMD. | For more detailed information on how CSES codes | parties/coalitions, please see Part 3 of the CSES IMD Codebook. | | The harmonized and consistent codes for parties/coalitions are | detailed in Part 3 of the CSES IMD Codebook. Users can search for | the following term: "CSES IMD HARMONIZED PARTY/COALITION | NUMERICAL CODES". | | The corresponding variables to E6000_ in the CSES IMD are: | E6000_PR_1: IMD3002_PR_1 | E6000_PR_2: IMD3002_PR_2 | E6000_LH_PL: IMD3002_LH_PL | E6000_LH_DC: IMD3002_LH_DC | | Codes are provided in E6000_LH_DC for parties that are assigned | a harmonized IMD numeric party code by the CSES and for polities | which are at least represented once in the CSES IMD. | Parties that are not represented in the IMD and have thus not | been assigned an IMD numeric party code yet are coded "999980. | IMD NUMERIC PARTY CODE NOT ASSIGNED YET" in E6000_LH_DC and are | listed in the table below. | | +++ TABLE: PARTIES INCLUDED IN E3013_LH_DC FOR WHICH IMD NUMERIC | PARTY CODES HAVE NOT BEEN ASSIGNED YET | | CSES MODULE 5 NUMERICAL CODE CSES MODULE 5 ALPHABETICAL | AND PARTY/COALITION NAME PARTY CODE (IF APPLICABLE) |----------------------------------------------------------------- | AUSTRALIA (2019): | 036007. Animal Justice Party | 036009. Fraser Anning's Conservative National Party | 036011. Centre Alliance | 036013. Sustainable Australia | 036015. Derryn Hinch's Justice Party | 036016. Western Australia Party | 036019. Rise Up Australia Party | 036021. Victorian Socialists | 036022. Reason Australia | 036023. Australia First Party (NSW) Incorporated | 036024. The Great Australian Party | 036029. Non-Custodial Parents Party | 036030. Involuntary Medication Objectors | (Vaccination/Fluoride) Party | 036031. VOTEFLUX.ORG | Upgrade Democracy! | 036032. Yellow Vest Australia | (Australian Liberty Alliance) | 036035. Australian Conservatives | 036036. Help End Marijuana Prohibition (HEMP) Party | 036037. Jacqui Lambie Network | | CANADA (2019): | 124006. People's Party (PP) PARTY F | | GERMANY (2017): | 276016. V-Party 3 - Party for Change, Vegetarians | and Vegans (V-Partei3) | 276028. Democratic Citizens Germany (DBD) | | GERMANY (2021): | 276110. Grassroots Democratic Party of Germany | (dieBasis) | 276114. Volt Germany (Volt) | 276127. Climate List Baden-Wuerttemberg | | GREAT BRITAIN (2019): | 826106. Brexit Party (BP) PARTY F | | HUNGARY (2018): | 348001. Fidesz-KDNP PARTY A | 348003. Hungarian Socialist Party - PARTY C | Dialogue for Hungary (MSZP) | 348004. Politics Can Be Different (LMP) PARTY D | 348005. Democratic Coalition (DK) PARTY E | 348006. Momentum Movement PARTY F | 348007. Hungarian Two-tailed Dog Party PARTY G | 348008. Together PARTY H | | IRELAND (2016): | 372005. Anti-Austerity Alliance - PARTY E | People Before Profit (AAA-PBP) | 372006. Social Democrats (SD) PARTY F | 372008. Renua Ireland (RI) PARTY H | 372010. Direct Democracy Ireland (DDI) | | ITALY (2018): | 380008. Us with Italy - Christian Democratic Union | (NcI-UdC) | 380009. Power to the People (PaP) | 380012. Communist Party (PC) | 380014. CasaPound Italy (CPI) | 380015. The People of Family (PdF) | 380016. Great North (GN) | | JAPAN (2017): | 392002. Constitutional Democratic Party of Japan (CDP) PARTY B | 392003. Party of Hope PARTY C | 392006. Japan Innovation Party PARTY F | | LITHUANIA (2016): | 440001. Homeland Union - Lithuanian Christian PARTY A | Democrats (TS-LKD) | 440002. Lithuania Union of Farmers and Greens (LVZS) PARTY B | 440003. Lithuanian Social Democratic Party (LSDP) PARTY C | 440004. Liberal Movement of the Republic of Lithuania PARTY D | (LRLS) | 440005. Anti-Corruption Coalition (LCP-LPP) PARTY E | 440007. Party 'Order and Justice' (PTT) PARTY G | 440008. Labor Party (DP) PARTY H | 440009. Lithuanian Freedom Union (Liberals) (LLS) | 440010. Lithuanian Green Party (LZP) | 440011. Political Pary 'List of Lithuania' | 440014. Political Party 'Road of Courage' (DK) | | LITHUANIA (2020): | 440102. Lithuanian Farmers and Greens Union (LVZS) PARTY B | 440103. Labor Party (DP) PARTY C | 440105. Freedom Party (LP) PARTY E | 440106. Liberal Movement of the Republic of PARTY F | Lithuania (LRLS) | 440108. Lithuanian Social Democratic Labor Party PARTY H | (LSDDP) | 440109. Lithuanian Center Party - Nationalists (CPT) PARTY I | 440110. National Alliance (NS) | 440111. Freedom and Justice (LT) | 440112. Lithuanian Green Party (LZP) | 440113. The Way of Courage (DK) | 440114. Party 'Lithuania - For Everyone' (PLV) | 440115. Christian Union (KS) | 440116. The Union of Generations' Solidarity - | Unity for Lithuania (KSSSL) | 440117. Lithuanian People's Party (LLP) | 440118. Political Party 'List of Lithuania' | | NEW ZEALAND (2017): | 554005. The Opportunities Party (TOP) PARTY E | 554012. Ban 1080 Party | 554014. Climate First Party | 554015. Forest and Bird Party | | SOUTH KOREA (2016): | 410002. Democratic Party of Korea (DP) PARTY B | 410003. The People's Party (PP) PARTY C | 410004. Justice Party (JP) PARTY D | | TAIWAN (2016): | 158003. New Power Party (NPP) PARTY C | 158004. Green-Social Democratic Coalition (GP - SDP) PARTY D | 158005. Minkuotang (MKT) PARTY E | 158009. Faith and Hope League | 158010. Trees Party (TP) | 158012. Chinese Unionist Party (CUP) | 158013. Free Taiwan Party (FTP) | 158014. MCFAP | 158022. The Motorist Party of the ROC | | TAIWAN (2020): | 158103. Taiwan People's Party (TPP) PARTY C | 158104. New Power Party (NPP) PARTY D | 158106. Taiwan Statebuilding Party (TSP) PARTY F | 158107. Congress Party Alliance | 158109. Taiwan Renewal Party | 158110. Stabilizing Force Party | 158111. Taiwan Action Party Alliance | 158113. United Action Alliance | 158114. Formosa Alliance | 158116. Interfaith Union | 158117. Taiwan Animal Protection Party | 158131. Judicial Justice Party | | THAILAND (2019): | 764001. State Power Party PARTY A | 764003. Future Forward Party PARTY C | 764006. New Economics Party PARTY F | 764008. Thai Liberal Party PARTY H | 764009. People's Nation Party PARTY I | 764010. Puea Chat Party | 764011. Action Coalition for Thailand | 764013. Thai Local Power Party | 764014. Thai Forest Conversation Party | | URUGUAY (2019): | 858004. Open Cabildo PARTY D | 858005. Intransigent Radical Ecology Party (PERI) PARTY E | 858006. People's Party PARTY F | 858009. Green Animalist Party (PVA) PARTY I | 858010. Digital Party |----------------------------------------------------------------- | | Users are advised that appending the CSES MODULE 5 dataset to | CSES IMD requires renaming E6000_ variables in accordance with | IMD naming conventions first. | In what follows, we provide example syntax on how appending | can be achieved in STATA: | | ** // RENAMING E1005 ID VARIABLE AND E6000_ VARIABLES ACCORDING | ** TO IMD STANDARDS | | rename E1005 IMD1005 | rename E6000_PR_1 IMD3002_PR_1 | rename E6000_PR_2 IMD3002_PR_2 | rename E6000_LH_PL IMD3002_LH_PL | rename E6000_LH_DC IMD3002_LH_DC | | ** // SAVING MODULE 5 DATASET | save "cses5.dta", replace | | ** // APPENDING CSES MODULE 5 DATASET TO CSES IMD | use "cses_imd.dta", clear | append using "cses5.dta" | | ** // END OF EXAMPLE CODE | | Further, users should note that upon appending the CSES MODULE 5 | dataset to IMD, code "9999980. CSES IMD NUMERIC PARTY CODE NOT | ASSIGNED YET" will not be labeled yet, as this code was newly | introduced in E6000_ and has hence not been envisaged for IMD. //END OF FILE