=========================================================================== COMPARATIVE STUDY OF ELECTORAL SYSTEMS (CSES) - MODULE 6 (2021-2026) CODEBOOK PART 1: INTRODUCTION SECOND ADVANCE RELEASE - DECEMBER 16, 2025 CSES Secretariat www.cses.org =========================================================================== HOW TO CITE THE STUDY: The Comparative Study of Electoral Systems (www.cses.org). CSES MODULE 6 SECOND ADVANCE RELEASE [dataset and documentation]. December 16, 2025 version. doi:10.7804/cses.module6.2025-12-16. These materials are based on work supported by the American National Science Foundation (www.nsf.gov) under grant numbers SES-1760058 and SES-2214278, 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. =========================================================================== =========================================================================== TABLE OF CONTENTS =========================================================================== ))) CSES ADVANCE RELEASE - WHAT USERS NEED TO KNOW ))) CSES DESIGN, DOCUMENTATION, & WEIGHTS - ADVICE TO USERS ))) OVERVIEW OF "CODEBOOK PART 1: INTRODUCTION" ))) HOW TO NAVIGATE THE CSES MODULE 6 CODEBOOK ))) LIST OF TABLES IN CODEBOOK PART 1 ))) THE COMPARATIVE STUDY OF ELECTORAL SYSTEMS (CSES) PROJECT OVERVIEW >>> CSES PROJECT PROFILE >>> CSES MODULE 6 STUDY DESCRIPTION - ABSTRACT >>> CSES MODULE 6 PLANNING COMMITTEE >>> CSES MODULE 7 PLANNING COMMITTEE >>> CSES MODULE 6 COLLABORATORS >>> CSES SECRETARIAT ))) CSES MODULE 6 - HOW TO ACCESS? >>> THE CSES CODEBOOK >>> THE CSES DATA FILES ))) CSES MODULE 6 STUDY >>> OVERVIEW OF CSES MODULE 6 DATA FILE PARTICULARS >>> LIST OF ELECTION STUDIES INCLUDED IN CSES MODULE 6 >>> MICRO-LEVEL (SURVEY) COMPONENT >>> CSES MODULE 6 COLLABORATOR INSTRUCTIONS FOR THE ADMINISTRATION OF THE CSES QUESTIONNAIRE >>> DISTRICT-LEVEL COMPONENT >>> MACRO-LEVEL COMPONENT ))) CSES MODULE 6 DOCUMENTATION - WHAT'S AVAILABLE AND HOW TO USE? >>> CSES CODEBOOK OVERVIEW >>> CSES CODEBOOK CONVENTIONS >>> CSES CODEBOOK - VARIABLE NOTES AND ELECTION STUDY NOTES >>> CSES ORIGINAL QUESTIONNAIRE FOR MODULE 6 >>> CSES - ADDITIONAL DOCUMENTATION ))) CSES MODULE 6 STUDY DATA AND CODEBOOK: ADDITIONAL INFORMATION >>> CODING OF PARTIES/COALITIONS & LEADERS >>> CSES DATA BRIDGING: NEW FRONTIERS IN DATA LINKAGE >>> DERIVATIVE VARIABLES >>> IDENTIFICATION VARIABLES >>> MISSING DATA >>> WEIGHTS >>> FREEDOM STATUS OF ELECTIONS >>> PROCESSING CHECKS OF MODULE 6 DATASET BY THE CSES SECRETARIAT ))) CSES MODULE 6 BIBLIOGRAPHY =========================================================================== ))) CSES ADVANCE RELEASE - WHAT USERS NEED TO KNOW =========================================================================== This dataset and all accompanying documentation is the "Second Advance Release" of CSES Module 6 (2021-2026). An Advance Release is a preliminary version of this CSES product. It thus lacks some of the checking, cleaning, processing, documentation, data, and variables that we anticipate in the Full Release of this product. The product is still in development, and data will be added gradually. Many election studies and variables that will eventually be present in the CSES Module 6 Full Release are unavailable in this file. Advance Releases are provided as a service to the CSES user community for those analysts who find it valuable to work with preliminary versions of the dataset. Users should anticipate future changes and improvements to the naming, data, and documentation of variables and election studies that appear in an advanced release file. If users wish to re-use their programming syntax/code on a future release of this product, we recommend that the code be written to accommodate these potential changes. Users of the Advance Release may also wish to monitor the errata for CSES Module 6 on the CSES website to check for known errors that may impact their analyses. To view errata for CSES Module 6, go to Data Download on the CSES website, navigate to the CSES Module 6 download page, and click on the Errata link in the white box to the right of the page. We hope that until the Full Release of CSES Module 6 is available, users will find this and future CSES Module 6 Advance Releases helpful in their work. =========================================================================== ))) CSES DESIGN, DOCUMENTATION, & WEIGHTS - ADVICE 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 over samples of specific sub-populations 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. =========================================================================== ))) OVERVIEW OF "CODEBOOK PART 1: INTRODUCTION" =========================================================================== Part 1 of the Codebook provides an extensive overview of the CSES MODULE 6 study. It includes general details about the project, the project's governing board (the Planning Committee), information on the national Collaborators who administered CSES MODULE 6 in their national election study, and on the activities of the CSES Secretariat - the operational hub of the project. Further, extensive information about the CSES MODULE 6 datafile particulars, how to access CSES data, CSES documentation conventions, and CSES coding conventions are also provided. In addition, Codebook Part 1 offers guidance on the different components of a CSES dataset (micro, district, and macro- level data), and derivative variables and data bridging variables available to users. Part 1 of the Codebook closes with the project bibliography, a non-exhaustive list of references consulted by the CSES Secretariat for processing CSES MODULE 6. =========================================================================== ))) HOW TO NAVIGATE THE CSES MODULE 6 CODEBOOK =========================================================================== In the CSES MODULE 6 dataset, all variables begin with the letter "F" (F being the sixth letter of the English alphabet and thus signifying MODULE 6). 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. 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. =========================================================================== ))) LIST OF TABLES IN CODEBOOK PART 1 =========================================================================== Below, we list the Tables located in Codebook Part 1. Tables can be accessed in the electronic version of the CSES Codebook by searching for "+++". - OVERVIEW OF ELECTION STUDIES INCLUDED IN CSES MODULE 6 WITH NUMBER OF OBSERVATIONS, MODE OF DATA COLLECTION, AND FIELDWORK DATES =========================================================================== ))) THE COMPARATIVE STUDY OF ELECTORAL SYSTEMS (CSES) PROJECT OVERVIEW =========================================================================== --------------------------------------------------------------------------- >>> CSES PROJECT PROFILE --------------------------------------------------------------------------- The Comparative Study of Electoral Systems (CSES) is a collaborative program of research among election study teams from around the world. Participating polities include a common module of survey questions in their post-election studies. The resulting data are deposited along with voting, demographic, district, and macro variables. The studies are then merged into a single, free, public dataset for use in comparative study and cross-level analysis. The CSES project focuses on respondents' behavior and attitudes during the time of a national election, with a particular emphasis on voting and turnout. Each CSES Module consists of a nationally-representative post-election survey and additional variables about the context of the overall polity and electoral system within which the respondents find themselves. Every five years a new CSES Module is designed with a different substantive theme selected to address essential questions in electoral studies and social science. An international committee of leading scholars of electoral politics and political science develop the research agenda, questionnaires, and study design. The design is implemented in each polity by their foremost social scientists. By collaborating in this way, the CSES community hopes to advance scientific inquiry into the relationship between electoral institutions and political behavior. The work of the CSES Secretariat is funded by the American National Science Foundation, the GESIS - Leibniz Institute for the Social Sciences, and the University of Michigan's Center for Political Studies. Details of particular grants that provided funding for MODULE 6 are available under the "HOW TO CITE THE CSES MODULE 6 STUDY". The project also receives in-kind support from participating election studies, additional organizations that sponsor Planning Committee (PC) meetings and conferences, and the many organizations that fund national election studies that participate in CSES. This is the sixth iteration of CSES known as CSES MODULE 6. The remainder of the project description relates specifically to CSES MODULE 6. --------------------------------------------------------------------------- >>> CSES MODULE 6 STUDY DESCRIPTION - ABSTRACT --------------------------------------------------------------------------- CSES MODULE 6 is scheduled to officially be in data collection from 2021 to 2026. CSES MODULE 6 focuses on the theme "Representative Democracy Under Pressure" with questions tapping citizens' views on the functioning of the democratic system and perceptions of system outputs, gender representation, preferences for government and the impact of the COVID-19 pandemic. More information regarding the theme of MODULE 6 can be found in the CSES MODULE 6 Stimulus Paper available on the CSES website in the "About" section ("Planning Committee"). --------------------------------------------------------------------------- >>> CSES MODULE 6 PLANNING COMMITTEE --------------------------------------------------------------------------- The CSES MODULE 6 Planning Committee (PC) was responsible for the design of CSES MODULE 6 and took initial responsibility for its implementation. Besides the Chair, Planning Committee Members are listed alphabetically by surname. The following persons were members of the CSES MODULE 6 Planning Committee: ELIZABETH ZECHMEISTER (MODULE 6 Planning Committee Chair) Vanderbilt University, United States EVA ANDUIZA Universitat Autonoma de Barcelona, Spain ALI CARKOGLU Koc University, Turkey MARINA COSTA LOBO University of Lisbon, Portugal DAVID HOWELL, ex officio University of Michigan, United States ORIT KEDAR The Hebrew University of Jerusalem, Israel GEORG LUTZ University of Lausanne, Switzerland IRFAN NOORUDDIN Georgetown University, United States HENRIK OSCARSSON University of Gothenburg, Sweden STEPHEN QUINLAN, ex officio GESIS - Leibniz Institute for the Social Sciences, Germany RUDIGER SCHMITT-BECK University of Mannheim, Germany CARLOS SHENGA Higher Institute of Public Administration, Mozambique JILL SHEPPARD Australian National University, Australia ALBERTO SIMPSER ITAM (Instituto Tecnologico Autonomo de Mexico), Mexico LAURA STEPHENSON Western University, Canada DAVID SULMONT Pontifical Catholic University of Peru, Peru JOSHUA TUCKER New York University, United States WOUTER VAN DER BRUG University of Amsterdam, The Netherlands MARKUS WAGNER University of Vienna, Austria MASAHIRO YAMADA Kwansei Gakuin University, Japan ERIC YU National Chengchi University, Taiwan R.O.C. Past members of the CSES MODULE 6 Planning Committee include: CATHERINE E. DE VRIES Free University Amsterdam, Netherlands AIDA JUST Bilkent University, Turkey --------------------------------------------------------------------------- >>> CSES MODULE 7 PLANNING COMMITTEE --------------------------------------------------------------------------- The CSES MODULE 7 Planning Committee (PC) takes responsibility not only for the design and implementation of MODULE 7 but also the responsibility for the remainder of CSES MODULE 6 until its completion. The following persons are members of the CSES MODULE 7 Planning Committee: RUTH DASSONNEVILLE (MODULE 7 Planning Committee Chair) KU Leuven, Belgium SELIM ERDEM AYTAC Koc University, Turkey THORSTEN FAAS Free University Berlin, Germany LIRAN HARSGOR University of Haifa, Israel AIRO HIRO Waseda University, Japan DAVID HOWELL, ex officio University of Michigan, United States LUKAS LINEK Czech Academy of Sciences, Czechia NOAM LUPU Vanderbilt University, United States AMENI MEHREZ Central European University, Hungary IRFAN NOORUDDIN Georgetown University, United States EVA H. ONNUDOTTIR University of Iceland, Iceland ROSARIO QUEIROLO Universidad Catolica del Uruguay, Uruguay MARIANA RODRIGUEZ, ex officio Vanderbilt University, United States COLLETTE SCHULZ-HERZENBERG Stellenbosch University, South Africa LAURA STEPHENSON Western University, Canada DAVID SULMONT Pontifical Catholic University of Peru, Peru JOSHUA TUCKER New York University, United States ASA VON SCHOULTZ University of Helsinki, Finland ERIC YU National Chengchi University, Taiwan R.O.C. Past members of the CSES MODULE 7 Planning Committee include: STEPHEN QUINLAN GESIS - Leibniz Institute for the Social Sciences, Germany MARINA COSTA LOBO (Former Chair of the PC) University of Lisbon, Portugal JILL SHEPPARD Australian National University, Australia --------------------------------------------------------------------------- >>> CSES MODULE 6 COLLABORATORS --------------------------------------------------------------------------- The CSES project is extremely grateful to our MODULE 6 Collaborators, who raised their own funds to include CSES MODULE 6 in a nationally representative post-election study in their polity or province. Listed Collaborators are those who appear in the Design Report for the respective study - they are not necessarily the actors who collected the data, and they are not necessarily the only investigators on each study. Most election studies benefited from the scientific input and data preparation skills of additional persons not listed here. Within each election study, Collaborators are presented in the order in which they are listed in the Design Report deposited by each Collaborator team. The affiliations listed are current as of the date when each election study's Design Report was deposited with CSES. The polities are listed in alphabetical order. - AUSTRALIA (2022) IAN MCALLISTER Australian National University, Australia SARAH CAMERON Griffith University, Australia SIMON JACKMAN Sydney University, Australia JILL SHEPPARD Australian National University, Australia - AUSTRIA (2024) SYLVIA KRITZINGER University of Vienna, Austria KATHARINA PFAFF University of Vienna, Austria JULIA PARTHEYMULLER University of Vienna, Austria - BRAZIL (2022) RACHEL MENEGUELLO State University of Campinas (UNICAMP), Brazil - DENMARK (2022) KASPER M. HANSEN Department of Political Science, University of Copenhagen, Denmark RUNE STUBAGER Department of Political Science, Aarhus University, Denmark - FRANCE (2022) NICOLAS SAUGER Centre de donnees socio-politiques Sciences Po, Paris, France - MONTENEGRO (2023) OLIVERA KOMAR De Facto Consultancy & Faculty of Political Science, University of Montenegro, Montenegro SLAVEN ZIVKOVIC De Facto Consultancy, Montenegro NEMANJA BATRICEVIC Faculty of Political Science, University of Montenegro, Montenegro NEMANJA STANKOV Faculty of Political Science, University of Montenegro, Montenegro - NEW ZEALAND (2023) JACK VOWLES Victoria University of Wellington, New Zealand - NORTH MACEDONIA (2024) JOVAN BLIZNAKOVSKI Ss. Cyril and Methodius University in Skopje, Institute for Sociological, Political and Juridical Research, North Macedonia ANETA CEKIKJ Ss. Cyril and Methodius University in Skopje, Institute for Sociological, Political and Juridical Research, North Macedonia - POLAND (2023) MIKOLAJ CZESNIK SWPS University, Poland RADOSLAW MARKOWSKI SWPS University, Poland MACIEJ SYCHOWIEC SWPS University, Poland OLIWIA SZCZUPSKA SWPS University, Poland - PORTUGAL (2022) MARINA COSTA LOBO Institute of Social Sciences, University of Lisbon, Portugal PEDRO MAGALHAES Institute of Social Sciences, University of Lisbon, Portugal - PORTUGAL (2024) MARINA COSTA LOBO Institute of Social Sciences, University of Lisbon, Portugal PEDRO MAGALHAES Institute of Social Sciences, University of Lisbon, Portugal - SLOVAKIA (2023) OLGA GYARFASOVA Comenius University, in Bratislava, Slovakia MILOSLAV BAHNA Sociological Institute, Slovak Academy of Sciences, Slovakia - SLOVENIA (2022) META NOVAK University of Ljubljana, Faculty of Social Sciences Slovenia ZIVA BRODER University of Ljubljana, Faculty of Social Sciences Slovenia - SWEDEN (2022) HENRIK OSCARSSON Department of Political Science, University of Gothenburg, Sweden - SWITZERLAND (2023) ANKE TRESCH FORS/ University of Lausanne, Switzerland LINE RENNWALD FORS, Switzerland LUKAS LAUENER FORS, Switzerland - TAIWAN (2024) CHEN LU-HUEI Election Study Center, National Chengchi University (NCCU), Taiwan, R.O.C. - TURKIYE (2023) SELIM ERDEM AYTAC Koc University, Istanbul, Turkiye ALI CARKOGLU Koc University, Istanbul, Turkiye ERSIN KALAYCIOGLU Sabanci University, Istanbul, Turkiye MERT MORAL Sabanci University, Istanbul, Turkiye SUSAN BANDUCCI University of Exeter, United Kingdom - UNITED STATES (2024) NICHOLAS A. VALENTINO University of Michigan, United States SHANTO IYENGAR Stanford University, United States D. SUNSHINE HILLYGUS Duke University, United States DARON SHAW University of Texas Austin, United States --------------------------------------------------------------------------- >>> CSES SECRETARIAT --------------------------------------------------------------------------- The CSES Secretariat comprises the central staffing and operational hub for the CSES project, under the leadership of the Chair of the CSES Planning Committee, PC - listed above). Since June 2011, the Secretariat has been a collaboration between the GESIS - Leibniz Institute for the Social Sciences, Germany, and the University of Michigan's Center for Political Studies in the United States. Professor Elizabeth Zechmeister of the Vanderbilt University, and Chair of the CSES MODULE 6 Planning Committee, and Professor Marina Costa Lobo of the University of Lisbon, Chair of the CSES MODULE 7 Planning Committee, have overseen the operations of CSES MODULE 6 during their respective terms as Chair. Various persons have staffed the CSES Secretariat throughout the MODULE 6 period. David Howell served as the Director of Studies for the first two advance releases of MODULE 6. Dr. Stephen Quinlan served as the Project Manager for the first two advance releases of MODULE 6. Katharina Blinzler, Dr. Klara Dentler, Dr. Mariana Rodriguez, Dr. Bojan Todosijevic, Dr. Rob Vidigal, & Dr. Slaven Zivkovic were responsible for research support, documentation, preparation, communications, and other services. Additional support to the Secretariat was provided by several research assistants from the GESIS - Leibniz Institute for the Social Sciences. Support was received from various sources for the activities of the CSES Secretariat during the period of CSES MODULE 6: 1. American National Science Foundation (NSF) grant SES-1760058, "The Sixth Module of the Comparative Study of Electoral Systems (CSES)" with Principal Investigators Ken Kollman (University of Michigan), John Aldrich (Duke University), and Elizabeth Zechmeister (Vanderbilt University) supported CSES Secretariat activities at the University of Michigan beginning in 2018. 2. American National Science Foundation (NSF) grant SES-2214278, "The Seventh Module of the Comparative Study of Electoral Systems (CSES)" with Principal Investigators Ken Kollman (University of Michigan) and Elizabeth Zechmeister (Vanderbilt University) supported CSES Secretariat activities at the University of Michigan beginning in 2023. 3. The CSES Secretariat activities at the GESIS - Leibniz Institute for the Social Sciences, Germany are funded by the GESIS - Leibniz Institute. 4. The Center for Political Studies (CPS) at the University of Michigan provides additional financial support. =========================================================================== ))) CSES MODULE 6 - HOW TO ACCESS? =========================================================================== --------------------------------------------------------------------------- >>> THE CSES CODEBOOK --------------------------------------------------------------------------- Users are advised to first download the CSES Codebook file: cses6_codebook.zip Contains the five Codebook files, including this one, in text format. The Codebook can also be navigated online the CSES MODULE 6 study page at: https://cses.org/data-download/cses-module-6-2021-2026/ --------------------------------------------------------------------------- >>> THE CSES DATA FILES --------------------------------------------------------------------------- The following ZIP files, which contain the CSES data are available to download from the CSES MODULE 6 study page at: https://cses.org/data-download/cses-module-6-2021-2026/ Users can download the data in a variety of formats depending on which statistical packages they intend to use with the data: cses6_csv.zip Contains a .CSV file with variables names as column headers but no additional metadata (for instance, no code labels are included). cses6_r.zip Contains a R Workplace system file (.rdata), with the dataset already prepared and ready to be loaded into R. Missing data statements are not applied. cses6_sas.zip Contains a SAS 7-8 system file (.sas7bdat), with the dataset already prepared and ready to be loaded into SAS. Missing data statements are not applied. cses6_spss.zip Contains a SPSS system file (.sav), with the dataset already prepared and ready to be loaded into SPSS. Missing data statements are not applied. cses6_stata.zip Contains a STATA 18 system file (.dta), with the dataset already prepared and ready to be loaded into STATA. Missing data statements are not applied. Users of STATA 13 or earlier versions of this program are advised to use the "cses_syntax.zip" files to load the dataset into their package. Please note that all above packages will need a File Extractor program downloaded to their computer to be able to Unzip and open the above files. We recommend that PC users create the following directory on their hard drive, and to download their files from this MODULE 6 release to that location: "c:/cses/module6/20251216/" The sub-directory value "20251216" represents the version (release date) of the dataset - this being 2025, and the December 16 version of CSES MODULE 6. This file structure is compatible with how the "cses6_syntax.zip" file (detailed above) is organized. The method allows users with multiple CSES datasets and/or versions to stay organized and not over-write their other files. Users of other computer types (Macs, Unix, etc.) are recommended to use a similar directory structure to organize their CSES files. =========================================================================== ))) CSES MODULE 6 STUDY =========================================================================== --------------------------------------------------------------------------- >>> OVERVIEW OF CSES MODULE 6 DATA FILE PARTICULARS --------------------------------------------------------------------------- The particulars of the Second Advance Release of CSES MODULE 6 are: Type of study: CROSS-SECTIONAL Kind of data: SURVEY DATA FUSED WITH CONTEXTUAL MACRO DATA Primary Unit of Analysis: INDIVIDUALS Universe: ALL PERSONS OF ELIGIBLE VOTING AGE AND ELIGIBLE TO VOTE IN THE NATIONAL ELECTION Geographic Coverage: GLOBAL (Europe, parts of Asia and South America, Australia) Total Geographic Regions: 6 (as defined by the UN Geographic regions) File Structure: RECTANGULAR Total Case Count: 33,871 Total Variable Count: 676 Total Polities: 17 Total Election Studies: 18 Users are advised that the above information relates to this Advance Release. The product is still in development, and data will be added gradually. Many election studies and variables that will eventually be present in the CSES Module 6 Full Release are unavailable in this version of the file. --------------------------------------------------------------------------- >>> LIST OF ELECTION STUDIES INCLUDED IN CSES MODULE 6 --------------------------------------------------------------------------- The Second Advance Release of CSES MODULE 6 contains data from the following 18 election studies in 17 polities. They are listed below in alphabetic order with an overview of some particulars of each election study. | +++ TABLE: OVERVIEW OF ELECTION STUDIES INCLUDED IN CSES MODULE 6 WITH | NUMBER OF OBSERVATIONS, MODE OF DATA COLLECTION, AND | FIELDWORK DATES | | POLITY (ELEC YEAR) N of Mode of Dates of Fieldwork | Observations Interview (Start-End date) | --------------------------------------------------------------------- | AUSTRALIA (2022) 3,269 MX May 23, 2022-Jun 05, 2022 | AUSTRIA (2024) 1,569 INT Sep 30, 2024-Oct 21, 2024 | BRAZIL (2022) 2,001 F2F Nov 19, 2022-Dec 04, 2022 | DENMARK (2022) 1,549 MX Nov 02, 2022-Feb 01, 2023 | FRANCE (2022) 1,575 INT Apr 28, 2022-May 26, 2022 | MONTENEGRO (2023) 1,200 F2F Oct 14, 2023-Oct 30, 2023 | NEW ZEALAND (2023) 910 MX Oct 18, 2023-Mar 09, 2024 | NORTH MACEDONIA (2024) 1,055 F2F Oct 25, 2024-Dec 04, 2024 | POLAND (2023) 1,500 F2F Nov 07, 2023-Dec 16, 2023 | PORTUGAL (2022) 1,010 F2F Feb 11, 2022-Mar 07, 2022 | PORTUGAL (2024) 1,001 F2F Apr 27, 2024-May 07, 2024 | SLOVAKIA (2023) 1,021 F2F Jan 31, 2024-Feb 26, 2024 | SLOVENIA (2022) 855 MX Sep 26, 2022-Dec 03, 2022 | SWEDEN (2022) 2,845 MX Sep 13, 2022-Jan 04, 2023 | SWITZERLAND (2023) 5,033 MX Oct 23, 2023-Jan 11, 2024 | TAIWAN (2024) 1,206 F2F Jan 15, 2024-May 31, 2024 | TURKIYE (2023) 1,508 F2F Aug 25, 2023-Oct 04, 2023 | UNITED STATES (2024) 4,764 MX Nov 07, 2024-Feb 19, 2025 | --------------------------------------------------------------------- | TOTAL 33,871 | | Key: F2F=Face-to-face. | TP=Telephone. | INT=Internet/Online. | MX=Mixed. | | Users are advised to consult the VARIABLE NOTES for Variables F1019_ | in Codebook Part 2 concerning fieldwork date classifications. Users are advised that the above information relates to this Advance Release. The product is still in development, and data will be added gradually. Many election studies and variables that will eventually be present in the CSES Module 6 Full Release are unavailable in this version of the file. --------------------------------------------------------------------------- >>> MICRO-LEVEL (SURVEY) COMPONENT --------------------------------------------------------------------------- The core questionnaire ("Module") of CSES MODULE 6 was intended to be administered as a single, uninterrupted block of questions in a nationally representative post-election survey in each polity. A) The question text is included in the variable documentation of this Codebook. The questions are reported in the order in which they appear in the CSES questionnaire. For some questions, Collaborator instructions for administering the CSES Questionnaire were important. These are reported in the next section. B) Where there are known differences in the way a particular question was administered in an election study, this is noted in the "Election Study Notes" following the documentation of the corresponding variable. C) There are several sets of party and leader evaluation items included in the module. These correspond to parties labeled A-F, in descending order of vote share, of the six most popular parties in the main election (unless stated otherwise). Where respondents were asked to evaluate other parties, these evaluations have been included where possible and are labeled parties G-I, regardless of their vote shares. The parties and leaders to which these evaluations apply are identified in Codebook Part 3. D) There are several questions (including the vote choice and party identification items) that ask the respondents to specify a political party. The codes for these items are also reported in Codebook Part 3. --------------------------------------------------------------------------- >>> CSES MODULE 6 COLLABORATOR INSTRUCTIONS FOR THE ADMINISTRATION OF THE CSES QUESTIONNAIRE --------------------------------------------------------------------------- The following instructions appeared in the header to the questionnaire for CSES MODULE 6, as instructions to Collaborators regarding the implementation of the questionnaire: ( 1) Following these collaborator instructions, this document is comprised of three sections: ))) CSES MODULE 6 QUESTIONNAIRE: ADMINISTRATIVE VARIABLES The "Administrative Variables" section is a list of common administrative variables that, if possible, should be provided at the time data are deposited with the CSES Secretariat. ))) CSES MODULE 6 QUESTIONNAIRE: CSES MODULE This is the CSES Module itself, a common module of survey questions for researchers to include in their national post-election survey. The CSES Module is intended to be administered exactly as it is specified in this document. ))) CSES MODULE 6 QUESTIONNAIRE: DEMOGRAPHIC VARIABLES Collaborators are asked to provide data on background (demographic) characteristics of respondents, coded to an agreed upon set of standards as indicated in this section. There is great international variation in the ways that collaborators will go about soliciting information on the background characteristics of their respondents. The objective here is not standardization of the way collaborators ask these background questions, but instead, standardization to a common, cross-national scheme for coding each variable. ( 2) The CSES Module (consisting of the questions which are named beginning with the letter "Q") is intended to be administered in its entirety as a single, uninterrupted block of questions, unless noted otherwise for particular questions. In most cases, the CSES Module is included as part of a larger study. For reliable comparisons to be made, it is important that any additional items investigators may wish to include do not interrupt the CSES Module. ( 3) The CSES module should be administered as a post-election interview. ( 4) Where the CSES module is included in a larger study, to ensure that question-ordering effects are minimized, collaborators should be sensitive to the effects questions asked immediately prior to the module may have. ( 5) NOTES often precede the question TEXT, and provide instructions for the administration of the item. Where no question TEXT is provided, collaborators should provide documentation of the question used. ( 6) Showcards may be helpful for the administration of some questions. For this reason, a Respondent Booklet is available for download from the CSES website. The Respondent Booklet contains showcards for select questions. It is indicated in the NOTES when a showcard is available for a question. ( 7) The response options that should be read to the respondent are contained in the body of the question TEXT. ( 8) Where lower-case words appear in brackets [ ] collaborators should select the words that are most appropriate. For example: [party/presidential candidate] ...indicates that either the word "party" or the phrase "presidential candidate" should be read, but not both. ( 9) Where upper-case words appear in brackets [ ] collaborators should substitute the words that are most appropriate. For example: [COUNTRY] ...should be replaced with the name of the country where the election was held (perhaps "Canada" or "the Philippines"). Another example: [NUMBER OF YEARS BETWEEN THE PREVIOUS AND THE PRESENT ELECTION OR CHANGE IN GOVERNMENT] ...should be replaced with a number that indicates the amount of years that have passed between the previous election and either the current election or recent change in government. (10) Phrases that appear in parentheses ( ) contain words that are optional - that collaborators (or their interviewers) can decide to read or not read to respondents as needed. (11) Words in question text that are in upper-case but NOT within brackets [ ] should be emphasized by the interviewer when reading the question text. For example, the word "COUNTRY" would be emphasized in the following question when the interviewer reads the question to the respondent: What COUNTRY do you live in? But in this next example, the interviewer does not emphasize the word "[COUNTRY]". Instead, this is an instruction for the collaborator to substitute the name of the respondent's country into the question text (for more information, see the eighth Collaborator Instruction above): How long have you lived in [COUNTRY]? (12) Interviewer instructions are available for some questions. These interviewer instructions, labeled as HELP, are intended to provide advice to the interviewers to assist in administering the question. It is also useful to discuss the interviewer instructions as part of interviewer training. The interviewer instructions, where available, appear after the question TEXT. In interviewer-administered surveys, interviewer instructions should be available to the interviewer, but not to the respondent. For example, in a computer-assisted interview, the interviewer instructions might appear on the screen in a special color, and interviewers trained to make use of those instructions as necessary, but the interviewer should NOT read the interviewer instructions to the respondent. (13) Some response options are followed by an arrow (->) and a skip pattern instruction. If the respondent selects that response option, the skip pattern instruction after the arrow is to be executed. (14) Respondents who volunteer the response "DON'T KNOW" (or who have REFUSED to answer a question) should be coded as such. Interviewers should accept these responses and should NOT probe for additional information or force a respondent to use one of the response options provided in the text of the question. (15) Special care should be taken in the administration of the Vote Choice items (Q10 and Q14 question series). Wording for the Q10 and Q14 question series, which is to record vote choice in the elections, should follow national standards. Collaborators are invited to compare their own national instrument with other instruments of countries that are part of the CSES and look for convergence where this is possible. For Q14 (previous election), ask about the previous national election of the same type (whether legislative or presidential). For countries where more than one institution is being currently elected on the same day (e.g., president and legislature), please consider asking about the previous lower house election if votes have been recorded for the current lower house election. For Q10 (current election), for countries where more than one institution is elected on the same day (e.g., president and legislature) using different votes, please ensure that all votes are supplied. Consider including all national elections having been held within three months before the study's data collection period. Please ensure all vote choices are supplied as separate variables in the dataset that you deposit. For countries where voters have two votes for the same institution (e.g. parallel and mixed member proportional systems; double ballot systems), please ensure that both/all votes are supplied. For countries using preferential systems (e.g., STV, AV) please provide first and second preference vote. (16) For questions asking about parties, collaborators should be advised that they may add one or several party blocs to a list of individual parties if they feel that it will be difficult for respondents to recognize individual parties. --------------------------------------------------------------------------- >>> DISTRICT-LEVEL COMPONENT --------------------------------------------------------------------------- The district-level variables report relevant election result data (mostly pertaining to the lower house elections) for each respondent's district. Wherever possible, these data were collected from official sources (see CSES MODULE 6 Codebook Part 2 and Bibliography in Part 1 for details). In other cases, CSES has been grateful for the compilation of these data provided by third-party sources. Parts 2 and 4 of the CSES MODULE 6 Codebook provide more information on the district data, including details of any polities where we deviate from the CSES conventions as well as the sources of the data for each polity. --------------------------------------------------------------------------- >>> MACRO-LEVEL COMPONENT --------------------------------------------------------------------------- To supplement the micro (individual survey level) data, CSES augments this data with macro and contextual data. CSES has been a pioneer in this field having included a macro data component in its products since its inception in 1996. There are two types of macro data included in CSES: - System/polity macro data - Aggregated macro data System/polity level data refers to data about the polity or contextual characteristics. These are often sourced from official documents like constitutions, electoral laws, government information pages, or expert judgments. Aggregated macro data summarizes data about lower-level units into a higher-level unit. Economic indicators such as gross domestic product (GDP) or unemployment data for a country fall into this classification. The CSES Planning Committee, the project governing board, specifies the specific macro data to collect for each CSES Module after consultation with the CSES Secretariat. The rationale for collecting specific macro variables is usually specified in CSES Planning Committee reports on the particular module. CSES macro data is principally collated from two sources, namely: - The CSES Macro Report - The CSES Secretariat The CSES Macro Report is a detailed questionnaire completed by national Collaborators who field the CSES study. This Report allows CSES to collect certain macro information consistently from national-level experts. Moreover, as polities participating in CSES are only sometimes available from other comparative datasets, it ensures macro data is available for all elections and polities. The CSES Secretariat reviews Macro Reports as provided by Collaborators before publication. These reports can be accessed on the CSES website in the "CSES Module 6 Election Study Archive" at the bottom of the CSES Module 6 Download page. The CSES Secretariat is comprised of macro experts - individuals who have substantial expertise (usually at the post-doctoral level) in the political dynamics and electoral systems of many of the polities in CSES. They are tasked with collating macro data from other sources, including comparative databases such as the World Bank and Freedom House, and bringing their expertise to classifying election results. They are also tasked with harmonizing these data and providing additional user guidance where necessary. Sources consulted for these macro level data are listed as appropriate in the Bibliography section at the end of this part of the CSES Codebook. =========================================================================== ))) CSES MODULE 6 DOCUMENTATION - WHAT'S AVAILABLE AND HOW TO USE? =========================================================================== There are several components to the CSES documentation. We detail each form below: --------------------------------------------------------------------------- >>> CSES CODEBOOK OVERVIEW --------------------------------------------------------------------------- The primary documentation component is the CSES MODULE 6 Codebook. The Codebook consists of five components, namely: 1) PART 1: INTRODUCTION (file name: cses6_codebook_part1_introduction.txt) Part 1 (This file) overview of the CSES study and data, information about how to use the files, information on the CSES data file, the checks the CSES Secretariat conducts on the data file and information on the national Collaborators of the CSES project for each polity. 2) PART 2: CSES VARIABLES DESCRIPTION (file name: cses6_codebook_part2_variables.txt) Part 2 is the Variable Description file and includes the survey questions, code frames, general variable notes, election study notes, and details about sources for macro data. 3) PART 3: PARTIES AND LEADERS BY POLITY (file name: cses6_codebook_part3_parties_and_leaders.txt) Part 3 details the party/coalition and leader numerical and alphabetical classifications for each polity included in the CSES MODULE 6 dataset. 4) PART 4: PRIMARY ELECTORAL DISTRICTS RESPONDENTS BY POLITY (file name: cses6_codebook_part4_primary_electoral_districts.txt) Part 4 details the primary electoral district by polity for each respondent included in the CSES MODULE 6 dataset. 5) PART 5: STUDY DESIGN AND WEIGHTS OVERVIEW BY POLITY (file name: cses6_codebook_part5_designs_and_weights.txt) Part 5 contains overviews of the design of each election study included in CSES MODULE 6. It also provides analysts with details regarding the polity weights provided by each election study. The CSES MODULE 6 questionnaire is also available from the website or by referencing the corresponding variables in this Codebook. For all election studies included in CSES, Collaborators have provided documentation to accompany their election studies. These documents, where available, can be found on the CSES MODULE 6 download page. Analysts will also want to become familiar with the CSES MODULE 6 errata page. It is accessible from the CSES MODULE 6 download page on the CSES website in the white box to the right of the page. Information, updates, and error notifications and corrections are posted there, in real time, as they become available. Please regularly check for errata notifications to keep up to date. --------------------------------------------------------------------------- >>> CSES CODEBOOK CONVENTIONS --------------------------------------------------------------------------- The CSES project uses American English language and date standards (MM-DD-YYYY). In the CSES MODULE 6 dataset, all variables begin with the letter "F" (F being the sixth letter of the English alphabet and thus signifying MODULE 6). This convention helps reduce the possibility of overwriting data when merging with other CSES datasets. Variables are presented in six groupings: 1) F1001-F1999 Identification, weight, and election study variables 2) F2001-F2999 Demographic data 3) F3001-F3999 Micro-level (survey) data (the CSES MODULE 6 questionnaire) 4) F4001-F4999 District-level data 5) F5000-F5999 Macro-level data 6) F6000-F6999 IMD bridging Variables In the Variable Descriptions portion of the CSES MODULE 6 Codebook (Part 2), the headers for individual variables are surrounded by two lines of dashes. Variable names do not exceed eight characters in length. --------------------------------------------------------------------------- >>> 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 important 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 Parts 2 and 3 of the CSES Codebook. They can be navigated in the Codebook by searching for "ELECTION STUDY NOTES" in Parts 2 and 3 of the CSES MODULE 6 Codebook. --------------------------------------------------------------------------- >>> CSES ORIGINAL QUESTIONNAIRE FOR MODULE 6 --------------------------------------------------------------------------- The CSES MODULE 6 original questionnaire is available from the CSES Module 6 study page at: https://cses.org/data-download/cses-module-6-2021-2026/ or by referencing the corresponding Variable Descriptions in this Codebook (see Part 2). --------------------------------------------------------------------------- >>> CSES - ADDITIONAL DOCUMENTATION --------------------------------------------------------------------------- All election studies included in CSES provide numerous source material. These documents include the following: - Macro Reports. - Design Reports. - Original questionnaires including in the language of origin. We describe each in turn below. <<>> MACRO REPORT Collaborators submit a Macro Report to the CSES Secretariat when depositing their national data. Its purpose is to provide a coherent link between national level specialists and data specific to the election and polity in question. It provides information on the election, the composition of cabinet before and after election, expert assessments of the parties, information on electoral rules operating in the polity, as well as original sources for the polity level data. It aids the CSES Secretariat in collating some of the macro level data for each polity included in the study. Where available, Macro Reports can be found on the CSES MODULE 6 download page under "CSES MODULE 6 Election Study Archive" at: https://cses.org/data-download/cses-module-6-2021-2026/ <<>> DESIGN REPORT Collaborators also submit a Design Report to the CSES Secretariat when depositing their national data. It provides all information on the implementation of each individual election study including details regarding fieldwork dates, mode of interview, sampling procedures, sampling frame, response and refusal rates, information on translation procedures, and weights. Some of this data is included directly in the CSES data in variables F1001-F1106. Where available, Design Reports can be found on the CSES MODULE 6 download page under "CSES MODULE 6 Election Study Archive" at: https://cses.org/data-download/cses-module-6-2021-2026/ Further, Part 5 of the CSES MODULE 6 Codebook provides overviews of each polity's study design and polity level weights. It draws heavily on information from each polity's Design Report. <<>> ORIGINAL QUESTIONNAIRES Where available, CSES provides the original language questionnaires from each polity's national election study. Further, CSES requests that all studies included provide the English language questionnaire used as the basis for translation of the CSES questionnaire into a polity's native tongue(s). Where available, the questionnaires can be found on the CSES MODULE 6 download page under "CSES MODULE 6 Election Study Archive" at: https://cses.org/data-download/cses-module-6-2021-2026/ =========================================================================== ))) CSES MODULE 6 STUDY DATA AND CODEBOOK: ADDITIONAL INFORMATION =========================================================================== --------------------------------------------------------------------------- >>> CODING OF PARTIES/COALITIONS & LEADERS --------------------------------------------------------------------------- CSES classifies 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 CSES MODULE 6 Codebook. <<>> CSES NUMERICAL PARTY/COALITION CODING Each party/coalition 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 a respondent voted for in the current election (variables F3011_). - who the respondent voted for in the previous election (variables F3016_). - the respondent's party identification (variable F3023_3). The numerical coding is also used to identify macro level information about the parties/coalitions, namely: - numeric party code identifiers for relational data (variables F5000_) - numeric party code identifiers for leaders' party affiliations (variables F5000_L_) - which party/coalition held the Presidency before and after the elections (variable F5019_1 and F5019_2). - which party/coalition held the Prime Ministership before and after the elections (variable F5020_1 and F5020_2). - which party/coalition held the ministry of finance before and after the elections (variable F5023_1 and F5023_2). - which party/coalition held the foreign ministry before and after the elections (variable F5023_3 and F5023_4). - which party/coalition held the health ministry before and after the elections (variable F5023_5 and F5023_6). Numerical codes assigned to parties/coalitions are consistent for the current and previous election. <<>> CSES ALPHABETICAL PARTY/COALITION CODING Parties/coalitions A through F are the six most popular parties/coalitions, ordered in descending order of their share of the popular vote in the main 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) unless stated otherwise. 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 polity. More often, they are codified in no particular order. These parties are voluntarily provided by each polity's election study and often reflect important or notable parties within a polity. 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 F3018). - Respondent's left-right placement of the party/coalition (variable F3020). - Respondent's placement of the party/coalition on an alternative scale, if applicable (variable F3021). 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 F4004). - the said party/coalition's share of the seats in the election in the respondent's electoral district (variable F4005). - the said party/coalition's share of the vote in the election (variables F5001, F5003, F5005, and F5006). - the said party/coalition's share of the seats in the election (variables F5002 and F5004). - the said party/coalition's share of cabinet portfolios before and after the election (variables F5021 and F5022). - expert judgments by the national Collaborators of the said party/ coalition's ideological family (variable F5028). - expert judgments by the national Collaborators of the said party/ coalition's left-right placement (variable F5029). - expert judgments by the national Collaborators of the said party/ coalition's placement on an alternative scale, if applicable (variable F5030). - expert judgments by the national Collaborators of the said party/ coalition's level of populism (variable F5031). - The said party/coalition's Manifesto Research on Political Representation (MARPOR/CMP) Identifier (variable F5200). - The said party/coalition's Parliaments and Government Database (ParlGov) Identifier (variable F5201). - The said party/coalition's Chapel Hill Expert Survey (CHES) Identifier (variable F5202). - The said party/coalition's Party Facts Identifier (variable F5203). <<>> 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. In most instances, they correspond to parties/coalitions 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 polity'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 F3019). - the said leader/personality's biological sex (F5000_L_ABS-IBS). --------------------------------------------------------------------------- >>> CSES DATA BRIDGING: NEW FRONTIERS IN DATA LINKAGE --------------------------------------------------------------------------- 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 6. 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 6 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 6 facilitates data bridging with other datasets at the polity level with the following variables: - F1006_UN ID COMPONENT - POLITY UN ISO_3166-1 NUMERIC CODE - F1006_UNALPHA2 ID COMPONENT - POLITY UN ISO_3166-1 ALPHABETIC TWO LETTER CODE - F1006_UNALPHA3 ID COMPONENT - POLITY UN ISO_3166-1 ALPHABETIC THREE LETTER CODE - F1006_NAM ID COMPONENT - POLITY NAME - F1007_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., "F1006_UN") or using the search term "POTENTIAL POLITY LEVEL BRIDGING IDENTIFIER". CSES MODULE 6 facilitates data bridging with other datasets at the regional level through the following variables: - F1007_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., "F1007_REG") or using the search term "POTENTIAL REGIONAL LEVEL BRIDGING IDENTIFIER". CSES MODULE 6 facilitates data bridging with other datasets by date through the following variables: - F1009 ID COMPONENT - ELECTION YEAR - F1010_M DATE 1ST ROUND ELECTION BEGAN - MONTH - F1010_D DATE 1ST ROUND ELECTION BEGAN - DAY - F1010_Y DATE 1ST ROUND ELECTION BEGAN - YEAR - F1010_1 DATE 1ST ROUND ELECTION BEGAN - YYYY-MM-DD - F1010_2 DATE 1ST ROUND ELECTION BEGAN - YYYYMM - F1011_M DATE 2ND ROUND ELECTION BEGAN - MONTH - F1011_D DATE 2ND ROUND ELECTION BEGAN - DAY - F1011_Y DATE 2ND ROUND ELECTION BEGAN - YEAR - F1011_1 DATE 2ND ROUND ELECTION BEGAN - YYYY-MM-DD - F1011_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., "F1009") or using the search term "POTENTIAL TIME BRIDGING IDENTIFIER". CSES MODULE 6 facilitates data bridging with other datasets at the party/coalition level with the following variables: - F5200_A-I MANIFESTO RESEARCH ON POLITICAL REPRESENTATION (MARPOR/CMP) IDENTIFIER - PARTY A-I - F5201_A-I PARLIAMENTS AND GOVERNMENT DATABASE (PARLGOV) IDENTIFIER - PARTY A-I - F5202_A-I CHAPEL HILL EXPERT SURVEY (CHES) IDENTIFIER - PARTY A-I - F5203_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., "F5200_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 6 Codebook. CSES MODULE 6 facilitates data bridging with other CSES products at the party/coalition level with the following variables: - F6000_PR_1 IMD BRIDGING VARIABLE: CURRENT PRESIDENTIAL ELECTION: VOTE CHOICE - 1ST ROUND - F6000_PR_2 IMD BRIDGING VARIABLE: CURRENT PRESIDENTIAL ELECTION: VOTE CHOICE - 2ND ROUND - F6000_LH_PL IMD BRIDGING VARIABLE: CURRENT LOWER HOUSE ELECTION: VOTE CHOICE: PARTY LIST - F6000_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". --------------------------------------------------------------------------- >>> DERIVATIVE VARIABLES --------------------------------------------------------------------------- CSES MODULE 6 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 6 Codebook. - F2001_A AGE OF RESPONDENT (IN YEARS) - F2001_GG BIRTH GENERATION: GREATEST GENERATION (BORN 1927 OR BEFORE) - F2001_GS BIRTH GENERATION: SILENT GENERATION (BORN FROM 1928 TO 1945) - F2001_GBB BIRTH GENERATION: BABY BOOMERS (BORN FROM 1946 TO 1964) - F2001_GX BIRTH GENERATION: GENERATION X (BORN FROM 1965 TO 1980) - F2001_GY BIRTH GENERATION: GENERATION Y (BORN FROM 1981 TO 1996) - F2001_GZ BIRTH GENERATION: GENERATION Z (BORN FROM 1997 ONWARDS) - F3010_TS TURNOUT SWITCHER BETWEEN CURRENT ELECTION AND PREVIOUS ELECTION - F3010_FTV FIRST-TIME VOTER IN CURRENT MAIN ELECTION - F3011_OUTGOV CURRENT MAIN ELECTION: VOTE CHOICE - OUTGOING GOVERNMENT (INCUMBENT) - F3011_VS_1 VOTE SWITCHER BETWEEN CURRENT ELECTION AND PREVIOUS ELECTION - F3011_LR_CSES CURRENT MAIN ELECTION - VOTE FOR LEFTIST/CENTER/RIGHTIST - CSES - F3011_LR_MARPOR CURRENT MAIN ELECTION - VOTE FOR LEFTIST/RIGHTIST (RILE) - MARPOR/CMP - F3011_IF_CSES CURRENT MAIN ELECTION - VOTE CHOICE BY IDEOLOGICAL FAMILY CLASSIFICATION - CSES - F3100_LR_CSES CURRENT MAIN ELECTION - VOTE CHOICE LINKED WITH CSES COLLABORATOR EXPERT JUDGMENT L-R - F3100_LR_MARPOR CURRENT MAIN ELECTION - VOTE CHOICE LINKED WITH MARPOR/CMP RILE - F3100_POP_CSES CURRENT MAIN ELECTION - VOTE CHOICE LINKED WITH CSES COLLABORATOR EXPERT JUDGMENT ON POPULISM - F3100_IF_CSES CURRENT MAIN ELECTION - VOTE CHOICE LINKED WITH CSES COLLABORATOR EXPERT JUDGMENT IDEOLOGICAL FAMILY - F5019_C PARTY OF THE PRESIDENT CHANGED - F5020_C PARTY OF THE PRIME MINISTER CHANGED --------------------------------------------------------------------------- >>> IDENTIFICATION VARIABLES --------------------------------------------------------------------------- There are several Identification Variables in CSES MODULE 6 which allow users to not only identify an individual respondent, but election studies, and polities. <<>> ELECTION STUDY IDENTIFIERS Each Election Study in CSES MODULE 6 is uniquely identified by two variables, namely: - variable F1004 ID VARIABLE - ELECTION STUDY (ALPHABETIC POLITY) This variable is an alphanumerical code constructed from two components: the alpha-3 country codes assigned by the United Nations Statistics Divisions. The remaining characters correspond to the year of the election. E.g., TUR_2023 - variable F1005 ID VARIABLE - ELECTION STUDY (NUMERIC POLITY) This variable is an eight-digit numerical code constructed from two components: the CSES polity code (variable F1006) and the year in which the election took place (F1009). The first three digits represent the country codes assigned by the United Nations Statistics Division. The fourth digit distinguishes between multiple election studies within a single country for the same election. The final four digits represent the year of the election. E.g., 03602022. AUSTRALIA (2022) <<>> POLITY IDENTIFIERS Each Polity in CSES MODULE 6 is uniquely identified by four variables, namely: - variable F1006_UN ID COMPONENT - POLITY UN ISO_3166-1 NUMERIC CODE This variable consists of the three-digit numerical country codes assigned by the United Nations Statistics Division to polities in line with the International Organization for Standardization (ISO). The numerical codes are maintained by the United Nations Statistics Division and are based on the M49 UN framework. E.g., 036. AUSTRALIA - variable F1006_UNALPHA2 ID COMPONENT - POLITY UN ISO_3166-1 ALPHABETIC TWO LETTER CODE This variable consists of the two-letter country codes assigned by the United Nations Statistics Division to polities based on the International Organization for Standardization (ISO). The lettered codes are maintained by the ISO as part of their ISO3166-1 standard. E.g., DK. Denmark (DK=Denmark) - variable F1006_UNALPHA3 ID COMPONENT - POLITY UN ISO_3166-1 ALPHABETIC THREE LETTER CODE This variable consists of the three-letter country codes assigned by the United Nations Statistics Division to polities based on the International Organization for Standardization (ISO). The lettered codes are maintained by the ISO as part of their ISO3166-1 standard. E.g., PRT. Portugal (PRT=Portugal) - variable F1006_NAM ID COMPONENT - POLITY NAME This variable consists of polity names based on those used by the United Nations Statistics Division. E.g., France These polity identifiers allow for easy data bridging with other macro data sources such as the World Bank. <<>> POLITY GEOGRAPHIC IDENTIFIERS - variable F1007_REG ID COMPONENT - POLITY UN GEOGRAPHIC REGIONS NUMERIC CODES This variable consists of a two-digit numerical code assigned by the United Nations Statistics Division to polities based on their geographic (continental) region. Each polity is shown in one region only. <<>> POLITY MEMBERSHIP IDENTIFIERS CSES MODULE 6 classifies whether each polity was a member of two international organizations at the time of the election, namely the Organization for Economic Cooperation and Development (OECD) and the European Union (EU). - variable F1007_OECD ID COMPONENT - POLITY MEMBER OF OECD This variable classifies whether polity was a member of the Organization for Economic Cooperation and Development (OECD) at the time of the election. - variable F1007_EU ID COMPONENT - POLITY MEMBER OF EU This variable classifies whether polity was a member of the European Union at the time of the election. <<>> RESPONDENT IDENTIFIER Respondents can be uniquely identified in the dataset by variable F1003_1. It is an 18-character identifier. The first three characters are the numeric version of the country codes assigned by the United Nations Statistics Division. If applicable, 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 digit is 0. The fifth through eighth characters correspond to the election year (see variable F1009). The last ten characters are the respondent identifier from F1003_2, which is unique within each election study. <<>> COVID-19 PANDEMIC IDENTIFIER Some studies were conducted either partially or completely during the COVID-19 pandemic. 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. Prior to the onset of CSES MODULE 6, the World Health Organization classified COVID-19 as a pandemic on March 11, 2020. On May 5, 2023, the WHO assessed that given the disease was by now well established and ongoing, it no longer fit the definition of a Public Health Emergency of International Concern (PHEIC) and hence the state of a global emergency. An election (or election study) in CSES MODULE 6 is classified as taking place during the COVID-19 pandemic if the election itself took place and/or the entire study fieldwork was administered before May 5, 2023, the end date of the WHO PHEIC classification. CSES classifies whether the election took place after, partially, or fully during the pandemic - this is identified in the dataset by variable F1012_2. --------------------------------------------------------------------------- >>> MISSING DATA --------------------------------------------------------------------------- Multiple response categories can relate to missing data relating from not applicable to a respondent refusing to answer or failing to answer a question. Users should consult individual variables for the specific missing designations assigned to each variable. For some election studies in which we could not distinguish among various answers, the code "missing" may include cases where respondents refused to answer the question, "don't know" responses, and cases where there a particular question went unanswered for other reasons. Moreover, while CSES guidelines request that the response categories "Refused" and "Don't Know" be volunteered responses, this was not always consistently applied. For instance, sometimes the options were offered explicitly to respondents in mail-back surveys, which do not have the benefit of an interviewer being present. To identify whether the response options were volunteered (or not) in a particular election study, users should refer to the original questionnaires of each polity. These are available on the MODULE 6 page. While there is no consistent CSES convention regarding the application of missing values, some commonalities exist, namely: - Not applicable values are commonly designated as 7, 97, 997, 9997 etc... - Don't know values are commonly designated as 8, 98, 998, 9998 etc... - Missing values are commonly designated as 9, 99, 999, 9999 etc... However, users are advised that the commonalities do not always hold and they are advised to consult individual variables for the specific missing designations assigned to the variable in question. --------------------------------------------------------------------------- >>> WEIGHTS --------------------------------------------------------------------------- CSES provides several weight measures in the CSES data (see variables F1101-F1105 inclusive). There is a strong degree of variance in the sample designs used in the national election studies included in CSES. Hence, the weights provided by Collaborators vary significantly. Users are advised to read carefully about the different weights in CSES to ascertain whether their analyses should be subjected to weighting and if so which kind. CSES provides users with up to three original weights from each national election study (see variable F1101_) namely: - SAMPLE WEIGHT (variable F1101_1): intended to correct for unequal selection probabilities resulting from booster samples procedures for selection within the household, non-response, or other sample design features - DEMOGRAPHIC WEIGHT (variable F1101_2): intended to adjust sample distributions of socio-demographic characteristics to more closely resemble the characteristics of the population - POLITICAL WEIGHT (variable F1101_3): intended to reconcile discrepancies in the reported electoral behavior of respondents' vis-a-vis official electoral counts. For more information on polity weights, users are advised to consult Part 5 of the CSES Codebook or the individual design reports of each study. The remainder of the weight variables in the dataset are derivative weights, constructed from the original weights. They are: - FACTOR WEIGHTS (variable F1102) These variables report the mean weight of each type, within each polity. The resulting factors are then used to create the derivative Polity Weights (variable F1103 explained below). - POLITY WEIGHTS (variable F1103) These variables report standardized versions (with a mean 1 within the polity) of the original weights provided with the component election studies, described in F1101. They are the ratio of each weighting factor to the mean weight (F1102) of each type, calculated within each polity. - SAMPLE SIZE ADJUSTMENT WEIGHT (variable F1104) This variable reports the ratio of the average sample size to each election study sample. The resulting factor is then used to create the derivative Dataset Weights, see variable F1105. - DATASET WEIGHTS (variable F1105) These variables are intended for micro-level analyses involving the entire CSES sample. Using the sample size adjustment (F1104), the centered weights (F1103) are corrected such that each election study component contributes equally to the analysis, regardless of the original sample size. Details of the calculation of the above derivative weights, including the precise STATA code used to create the weights, can be found in the variable notes for variables F1102, F1103, F1104, and F1105. Analysts are advised to read the weight documentation carefully to ensure their analyses are weighted appropriately (if applicable). The CSES project does not provide advice as to which weights are appropriate to use in particular circumstances. This is best left to analysts to decide based on their detailed knowledge of the research question under investigation. We advise analysts to consult variable notes F1101-F1105 for more specific information on each polities weight and the derivative weights calculated for the Cross-National Dataset. --------------------------------------------------------------------------- >>> FREEDOM STATUS OF ELECTIONS --------------------------------------------------------------------------- The majority of studies that comprise CSES are collected in countries that have free or partly free elections. However, sometimes a Collaborator will include the CSES module in a study of a polity that is a developing democracy or that is considered not free. If the data collection is judged to be of sufficiently high quality, the study is included in CSES datasets even if the polity is considered to be not free. The decision regarding inclusion of particular polities in an analysis is thus left to users. To assist users in making appropriate decisions concerning their analysis, CSES MODULE 6 includes two measures about the freedom and liberty of a polity in the year the election was held (and indeed the two preceding years), namely: - FREEDOM HOUSE RATING (variables F5070_) Freedom House assigns a numerical rating of a polity on a scale of 1 to 7 providing an indication of freedom. - POLITY IV DEMOCRACY-AUTOCRACY RATING (variables F5071_) Polity IV assigns a numerical rating to a polity on a scale of -10 to 10 indicating whether the polity is strongly democratic or strongly autocratic. These data are last available for the years 2016-2018. Freedom House and Polity IV are not affiliated with the CSES project. --------------------------------------------------------------------------- >>> PROCESSING CHECKS OF MODULE 6 DATASET BY THE CSES SECRETARIAT --------------------------------------------------------------------------- Besides processing MODULE 6 studies from individual polities to ensure they are fit for comparative analysis, which involves detailed checking of the individual studies' data, a key role of the CSES Secretariat is to perform several checks on the MODULE 6 Dataset before it is released. These checks include (but are not confined to): - CHECK OF DUPLICATE IDs Identification of respondents with corresponding answers to all questions or respondent identification data that are similar. - DERIVATIVE VARIABLES CHECKS To identify all derivative variables created by the CSES Secretariat are coded in line with original variables and documented in the CSES Codebook comprehensively. - INCONSISTENCY CHECKS To identify sets of variables which are inconsistent, or could be perceived as inconsistent (e.g., strange skip pattern, incompatible answers to related questions). The CSES convention is not to change data that we receive from national Collaborators. Instead, inconsistencies are noted in the CSES Codebook under the appropriate variable and the data are left unchanged. This allows users to make the final determination on whether inconsistencies may affect their analyses. - IRREGULAR AND EXTRAORDINARY CODE CHECKS To identify irregular and extraordinary codes in the CSES MODULE 6 Dataset. Sometimes these irregular or extraordinary codes are legitimate in the sense that they may be accounted for by a polity deviation on a particular variable. - THEORETICAL CHECKS These checks explore expected relationships between variables that we might expect to occur (e.g., correlation between Political Efficacy and Satisfaction with Democracy). We do this by exploring distributions, correlation analysis, and regression analysis. - VARIABLE AND VALUE LABEL CHECKS Checking all variables in the CSES MODULE 6 Dataset to ensure they are appropriately assigned labels and documented in the CSES Codebook. - INTERVIEW(ER) VALIDATION CHECKS Review performed at the respondent and interviewer levels using various statistical techniques to identify anomalous response patterns in the data (e.g., identification of highly similar interviews, straightlining, unusually high proportion of interviews conducted by an individual interviewer on a single day). If you identify any potential issue with the CSES MODULE 6 data, please contact the CSES Secretariat by e-mail at: cses@umich.edu =========================================================================== ))) CSES MODULE 6 BIBLIOGRAPHY =========================================================================== The below list constitutes a list of the primary sources that the CSES Secretariat has consulted in the development of CSES MODULE 6 Codebook and Data. The list is not exhaustive. Please note: Period symbol at end of URL addresses may be considered a full stop or could be part of the URL address. Aylott, N. and N. Bolin. 2023. "A new right: the Swedish parliamentary election of September 2022". West European Politics 46(5): 1049-1062. DOI: 10.1080/01402382.2022.2156199 Bendjaballah, S. and N. Sauger. 2023. France: Political developments and data for 2022: Back to normal?. European Journal of Political Research Political Data Yearbook (62) 1:, 167-189. DOI: 10.1111/2047-8852.12403 Delivorias, A. and E. Lazarou. 2023. "Brazilian democracy in the aftermath of 8 January". European Parliament Briefing PE 739.354 - February 2023. Available at: https://www.europarl.europa.eu/RegData/etudes/BRIE/2023/739354/EPRS_BRI (2023)739354_EN.pdf (Date accessed: August 9, 2024). Doctor, M. 2022. "What Happens in Brazil Won't Stay in Brazil: The 2022 Brazilian Elections." Political Insight 13(3): 8-11. DOI: 10.1177/20419058221127464 Enns, Peter K. et al. (2025). "Understanding Biden’s Exit and the 2024 Election: The State Presidential Approval/State Economy Model." PS: Political Science & Politics. April 2025, pp. 298 - 305. DOI: https://doi.org/10.1017/S1049096524000994 Hansen, K. M. and R. Stubager. 2023. "The Danish National Election Study 2022". CVAP Working Paper Series 5, Copenhagen: Department of Political Science, University of Copenhagen. Available at: https://digidata.rigsarkivet.dk/aflevering/51035 (Date accessed: May 14, 2024). Jacobson, Gary C. (2025). "The 2024 Presidential and Congressional Elections: Small Wave, Seismic Effects." Political Science Quarterly, Volume 140, Issue 3, Fall 2025, Pages 439–473. DOI: 10.1093/psquar/qqaf050 Krasovec, A. 2023. "Slovenia: Political Developments and Data in 2022 A Year of Elections and Political Changes." European Journal of Political Research. Political Data Yearbook. 62 (1): 448-471. DOI: 10.1111/2047-8852.12409. Lajh, D. Novak, M. 2024. "Politicization of the European Union in Slovenia in the Twenty Years of its Membership." Politics in Central Europe. 20 (3) 331.353. DOI: 10.2478/pce-2024-0015. Lavrelashvili, T. 2020. "Party Passport: North Macedonia". European Party Monitor, Brussels/Leuven, available at: https://soc.kuleuven.be/io/english/ european-party-monitor/north-macedonia/north-macedonia (Date accessed: June 27, 2025). Lindskog, H., S. Dahlberg, R. Ohrvall and H. Oscarsson. 2024. "The Voter Next Door: Stigma Effects on Advance Voting for Radical Right Parties". Political Studies 72(4): 1591-1608. DOI: 10.1177/00323217231216305 Lopes, H. F. 2023. "An unexpected Socialist majority: the 2022 Portuguese general elections." West European Politics 46 (2): 437-450. DOI: 10.1080/01402382.2022.2070983. Lopes, H. F. 2025. "Radical right advance and party system change: the 2024 Portuguese snap elections." West European Politics 48 (1): 228-245. DOI: 10.1080/01402382.2024.2372752. Magone, J. M. 2022. "Portugal: Political Developments and Data in 2021 An Election Year and the Dismissal of the Costa II Government." European Journal of Political Research 61 (1): 374-384. DOI: 10.1111/2047-8852.12383. Markowski, R. 2006. "The polish elections of 2005: Pure chaos or a restructuring of the party system?". West European Politics 29(4): 814-832. DOI: 10.1080/01402380600842452. OSCE. Office for Democratic Institutions and Human Rights (ODIHR). 2024. "Republic of North Macedonia. Presidential and Parliamentary Elections 24 April and 8 May 2024. ODIHR Election Observation Mission Final Report." https://www.osce.org/files/f/documents/5/e/576648.pdf (Date accessed: June 27, 2025). Santana-Pereira, J. & Rogerio Nina, S. "The relevance and resilience of the cordon sanitaire in Portugal: the March 2024 legislative elections." TFO Collections (The Radical Right in Southern Europe): 243-268. DOI: 10.1080/13608746.2024.2413857. Superior Electoral Court Brazil (TSE), International Affairs Unit. 2022. Practical Guide: 2022 Brazilian Elections. Brasilia: Tribunal Superior Eleitoral. https://international.tse.jus.br/en/assuntos-internacionais/ guia-pratico-para-pessoas-estrangeiras_ingles_digital-1.pdf (Date accessed: October 14, 2024). Tarouco, G. 2023. Brazilian 2022 general elections: process, results, and implications. Revista Uruguaya de Ciencia Politica 32(1): 153-168. DOI:10.26851/rucp.32.1.7 Treneska, J., T. Smilevski, G. Hadzi Janev and A. Sofeska. 2024. "Handbook on 2024 Parliamentary Elections in the Republic of North Macedonia". Handbook by Konrad Adenauer Foundation, Office in Skopje (KAS) and the Institute for Democracy "Societas Civilis" (IDSCS). Available at: https://www.kas.de/en/web/nordmazedonien/single-title/-/content/ handbook-on-2024-parliamentary-elections-in-the-republic-of-north-macedonia (Date accessed: June 27, 2025). Tworzecki, H. 2019. "Poland: A Case of Top-Down Polarization". The ANNALS of the American Academy of Political and Social Science 681(1): 97-119. DOI: 10.1177/0002716218809322. Vujovic, Z. and A. Nenezic. 2023. "Montenegro in Crises: Navigating Political Turmoil and the Path to European Integration". Suedosteuropa Mitteilungen 63 (2): 25-44. Available at: https://www.sogde.org/site/assets/files/27497/vujovic_23046_sog_mitteilungen _02-2023_internet-4.pdf (Date accessed: June 26, 2024). Walker, N. 2022. "Brazil: 2022 presidential election." Research Briefing, House of Commons Library. Available at: https://researchbriefings.files.parliament.uk/documents/CBP-9653/ CBP-9653.pdf (Date accessed: August 9, 2024). Wojnicki, J. 2023. "The 2023 Elections in Montenegro - A Real Political Breakthrough?" In Poland's Experience in Combating Disinformation: Inspirations for the Western Balkans, edited by A. Adamczyk, G. Ilik, M. Tahirovic, and K. Zajaczkowski, 199-209. Oficyna Wydawnicza ASPRA-JR. DOI: 10.33067/978-83-8209-282-0 Zajc, D. 2023. "2022: A Super Election Year in Slovenia." European Perspectives. 14 (1). 21-38. DOI: 10.60073/euper.2023.4.03 //END OF FILE