=========================================================================== COMPARATIVE STUDY OF ELECTORAL SYSTEMS (CSES) - MODULE 5 (2016-2021) CODEBOOK PART 1: INTRODUCTION 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 1: INTRODUCTION" ))) HOW TO NAVIGATE THE CSES MODULE 5 CODEBOOK ))) LIST OF TABLES IN CODEBOOK PART 1 ))) THE COMPARATIVE STUDY OF ELECTORAL SYSTEMS (CSES) PROJECT OVERVIEW >>> CSES PROJECT PROFILE >>> CSES MODULE 5 STUDY DESCRIPTION - ABSTRACT >>> CSES MODULE 5 PLANNING COMMITTEE >>> CSES MODULE 6 PLANNING COMMITTEE >>> CSES MODULE 5 COLLABORATORS >>> CSES SECRETARIAT ))) CSES MODULE 5 - HOW TO ACCESS? >>> THE CSES CODEBOOK >>> THE CSES DATA FILES ))) CSES MODULE 5 STUDY >>> OVERVIEW OF CSES MODULE 5 DATA FILE PARTICULARS >>> LIST OF ELECTION STUDIES INCLUDED IN CSES MODULE 5 >>> MICRO-LEVEL (SURVEY) COMPONENT >>> CSES MODULE 5 COLLABORATOR INSTRUCTIONS FOR THE ADMINISTRATION OF THE CSES QUESTIONNAIRE >>> DISTRICT-LEVEL COMPONENT >>> MACRO-LEVEL COMPONENT ))) CSES MODULE 5 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 5 >>> CSES - ADDITIONAL DOCUMENTATION >>> HOW TO NAVIGATE THE CSES MODULE 5 CODEBOOK ))) CSES MODULE 5 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 5 DATASET BY THE CSES SECRETARIAT ))) CSES MODULE 5 BIBLIOGRAPHY =========================================================================== ))) OVERVIEW OF "CODEBOOK PART 1: INTRODUCTION" =========================================================================== Part 1 of the Codebook provides an extensive overview of the CSES MODULE 5 study. It includes general details about the project, the project's governing board (the Planning Committee), and information on the national Collaborators who administered CSES MODULE 5 in their national election study. Further, extensive information about how to access CSES data, CSES documentation, and CSES coding conventions are also provided. In addition, an overview of the sampling procedures and weights of each polity's study as well as a project bibliography are also detailed in this section. =========================================================================== ))) 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. 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 5 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 5 are available under the "HOW TO CITE THE CSES MODULE 5 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 fifth iteration of CSES known as CSES MODULE 5. The remainder of the project description relates specifically to CSES MODULE 5. --------------------------------------------------------------------------- >>> CSES MODULE 5 STUDY DESCRIPTION - ABSTRACT --------------------------------------------------------------------------- CSES MODULE 5 is scheduled to officially be in data collection from 2016 to 2021. Data collection in 2015 is possible for pre-test studies. CSES MODULE 5 focuses on the examination of so-called "populist attitudes" in the population and how they shape electoral behavior. It focuses on the measurement of three core themes: attitudes towards political elites, attitudes towards representative democracy and majority rule, and attitudes towards out-groups. More information regarding the theme of MODULE 5 can be found in the CSES MODULE 5 Theoretical Statement available on the CSES website. --------------------------------------------------------------------------- >>> CSES MODULE 5 PLANNING COMMITTEE --------------------------------------------------------------------------- The CSES MODULE 5 Planning Committee (PC) was responsible for the design of CSES MODULE 5 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 5 Planning Committee: JOHN ALDRICH, Chair (MODULE 5 Planning Committee Chair) Duke University, United States EVA ANDUIZA Universitat Autonoma de Barcelona, Spain ALI CARKOGLU Koc University, Turkey GORAN CULAR University of Zagreb, Croatia RACHEL GIBSON University of Manchester, United Kingdom ELISABETH GIDENGIL McGill University, Canada SARA HOBOLT London School of Economics and Political Science, United Kingdom DAVID HOWELL, ex officio University of Michigan, United States CHI HUANG National Chengchi University, Taiwan AIDA JUST Bilkent University, Turkey ORIT KEDAR The Hebrew University of Jerusalem, Israel GEORG LUTZ University of Lausanne, Switzerland PEDRO MAGALHAES University of Lisbon, Portugal RACHEL MENEGUELLO Universidade Estadual de Campinas, Brazil HENRIK OSCARSSON University of Gothenburg, Sweden STEPHEN QUINLAN, ex officio GESIS - Leibniz Institute for the Social Sciences, Germany NICOLAS SAUGER Sciences Po, France RUDIGER SCHMITT-BECK University of Mannheim, Germany CARLOS SHENGA Higher Institute of Public Administration, Mozambique ALBERTO SIMPSER ITAM (Instituto Tecnologico Autonomo de Mexico), Mexico WOUTER VAN DER BRUG University of Amsterdam, The Netherlands MARKUS WAGNER University of Vienna, Austria MASAHIRO YAMADA Kwansei Gakuin University, Japan ELIZABETH ZECHMEISTER Vanderbilt University, United States --------------------------------------------------------------------------- >>> CSES MODULE 6 PLANNING COMMITTEE --------------------------------------------------------------------------- The CSES MODULE 6 Planning Committee (PC) takes responsibility not only for the design and implementation of MODULE 6 but also the responsibility for the remainder of CSES MODULE 5 until its completion. Besides the Chair, Planning Committee Members are listed alphabetically by surname. The following persons are 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 CATHERINE E. DE VRIES Free University Amsterdam, Netherlands 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: AIDA JUST Bilkent University, Turkey --------------------------------------------------------------------------- >>> CSES MODULE 5 COLLABORATORS --------------------------------------------------------------------------- The CSES project is extremely grateful to our MODULE 5 Collaborators, who raised their own funds to include CSES MODULE 5 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. - ALBANIA (2017) Blendi Ceka University of Tirana, Albania - AUSTRALIA (2019) IAN MCALLISTER Australian National University, Australia JILL SHEPPARD Australian National University, Australia - AUSTRIA (2017) WOLFGANG C. MUELLER University of Vienna, Austria SYLVIA KRITZINGER University of Vienna, Austria HAJO BOOMGAARDEN University of Vienna, Austria - BELGIUM-FLANDERS MARC HOOGHE (2019) KU Leuven, Centre for Political Research RUTH DASSONNEVILLE University of Montreal, Department of Political Science MARTIN OKOLIKJ KU Leuven, Centre for Political Research DIETER STIERS KU Leuven, Centre for Political Research - BELGIUM-WALLONIA MARC HOOGHE (2019) KU Leuven, Centre for Political Research RUTH DASSONNEVILLE University of Montreal, Department of Political Science MARTIN OKOLIKJ KU Leuven, Centre for Political Research DIETER STIERS KU Leuven, Centre for Political Research - BRAZIL (2018) RACHEL MENEGUELLO Centre for Studies on Public Opinion, Universidade de Campinas, Brazil - CANADA (2019) LAURA STEPHENSON University of Western Ontario, Canada ALLISON HARELL Universite du Quebec a Montreal, Canada DANIEL RUBENSON Ryerson University, Canada PETER JOHN LOEWEN University of Toronto, Canada - CHILE (2017) CAROLINE SEGOVIA Universidad Diego Portales, Chile RICARDO GAMBOA Universidad de Chile, Chile - COSTA RICA (2018) RONALD ALFARO-REDONDO Public Opinion Unit, Political Studies and Research Center, University of Costa Rica FELIPE ALPIZAR Political Studies and Research Center, University of Costa Rica JESUS GUZMAN-CASTILLO Public Opinion Unit, Political Studies and Research Center, University of Costa Rica - CZECHIA (2017) LUKAS LINEK Institute of Sociology, Czech Academy of Sciences Czech Republic - CZECHIA (2021) LUKAS LINEK Institute of Sociology, Czech Academy of Sciences Czech Republic - DENMARK (2019) KASPER M. HANSEN Department of Political Science, University of Copenhagen, Denmark RUNE STUBAGER Department of Political Science, Aarhus University, Denmark - EL SALVADOR (2019) RICARDO CORDOVA Fundacion Dr. Guillermo Manuel Ungo (FUNDAUNGO), El Salvador CARLOS ARGUETA Fundacion Dr. Guillermo Manuel Ungo (FUNDAUNGO), El Salvador - FINLAND (2019) KIMMO GRONLUND Social Science Research Institute, Abo Akademi University - FRANCE (2017) NICOLAS SAUGER Centre de donnees socio-politiques Sciences Po, Paris, France BRUNEL VALENTIN Centre de donnees socio-politiques Sciences Po, Paris, France - GERMANY (2017) BERNHARD WESSELS WZB (Berlin Social Science Center), Germany HARALD SCHOEN University of Mannheim, Germany SIGRID ROSSTEUTSCHER Goethe University, Frankfurt am Main, Germany RUEDIGER SCHMITT-BECK University of Mannheim, Germany CHRISTOF WOLF GESIS - Leibniz Institute for the Social Sciences, Germany - GERMANY (2021) SIGRID ROSSTEUTSCHER Goethe University, Frankfurt am Main, Germany HARALD SCHOEN University of Mannheim, Germany THORSTEN FAAS Freie Universitaet Berlin, Germany MARC DEBUS University of Mannheim, Germany REINHARD POLLAK GESIS - Leibniz Institute for the Social Sciences, Germany - GREAT BRITAIN EDWARD FIELDHOUSE (2017) University of Manchester, UK JANE GREEN Oxford University, UK GEOFFREY EVANS Oxford University, UK JONATHAN MELLON University of Manchester, UK CHRIS PROSSER University of London, UK - GREAT BRITAIN EDWARD FIELDHOUSE (2019) University of Manchester, UK JANE GREEN Oxford University, UK GEOFFREY EVANS Oxford University, UK JONATHAN MELLON University of Manchester, UK CHRIS PROSSER University of London, UK JACK BAILEY University of Manchester, UK - GREECE (2015) IOANNIS ANDREADIS Aristotle University Thessaloniki, Greece THEODORE CHADJIPADELIS Aristotle University Thessaloniki, Greece EFTICHIA TEPEROGLOU Aristotle University Thessaloniki, Greece - GREECE (2019) IOANNIS ANDREADIS Aristotle University Thessaloniki, Greece THEODORE CHADJIPADELIS Aristotle University Thessaloniki, Greece EFTICHIA TEPEROGLOU Aristotle University Thessaloniki, Greece - HONG KONG (2016) LI PANG-KWONG Lingnan University, Hong Kong - HUNGARY (2018) ZSOLT ENYEDI Central European University, Hungary BOJAN TODOSIJEVIC Institute of social sciences, Serbia LEVENTE LITTVAY Central European University, Hungary - ICELAND (2016) EVA H. ONNUDOTTIR University of Iceland, Iceland OLAFUR O. HARDARSON University of Iceland, Iceland HULDA PORISDOTTIR University of Iceland, Iceland AGNAR FREYR HELGASON University of Iceland, Iceland TINNA LAUFEY ASGEIRSDOTTIR University of Iceland, Iceland SHAUN BOWLER University of California Riverside, United States GUNNAR HELGI KRISTINSSON University of Iceland, Iceland GRETAR POR EYBORSSON University of Iceland, Iceland INDRIDI H. INDRIDOASON University of California Riverside, United States JON GUNNAR BERNBURG University of Iceland, Iceland SIGRUN OLAFSDOTTIR University of Iceland, Iceland - ICELAND (2017) EVA H. ONNUDOTTIR University of Iceland, Iceland OLAFUR O. HARDARSON University of Iceland, Iceland HULDA PORISDOTTIR University of Iceland, Iceland AGNAR FREYR HELGASON University of Iceland, Iceland - INDIA (2019) IRFAN NOORUDDIN Georgetown University, United States DHANANJAI JOSHI Cicero Associates & Consultants Pvt Ltd, India - IRELAND (2016) MICHAEL MARSH Trinity College Dublin (TCD), Ireland - ISRAEL (2020) MICHAL SHAMIR Tel Aviv University, Israel YAEL SHOMER Tel Aviv University, Israel LIOR SHEFFER Tel Aviv University, Israel ALON YAKTER Tel Aviv University, Israel - ITALY (2018) PAOLO SEGATTI University of Milan, Italy FEDERICO VEGETTI University of Milan, Italy - JAPAN (2017) MASAHIRO YAMADA Kwansei Gakuin University, Japan YUKIO MAEDA University of Tokyo, Japan AIRO HINO Waseda University, Japan TETSUYA MATSUBAYASHI Osaka University, Japan - LATVIA (2018) JANIS IKSTENS Univesity of Latvia, Latvia - LITHUANIA (2016) AINE RAMONAITE Vilnius University, Lithuania - LITHUANIA (2020) AINE RAMONAITE Vilnius University, Lithuania - MEXICO (2018) ULISES BELTRAN Political Studies Division, CIDE, Mexico RODRIGO CASTRO CORNEJO Political Studies Division, CIDE, Mexico - MONTENEGRO (2016) OLIVERA KOMAR De Facto Consultancy & University of Montenegro, Montenegro SLAVEN ZIVKOVIC De Facto Consultancy & University of Montenegro, Montenegro IVA MALESEVIC De Facto Consultancy, Montenegro STEVAN KANDIC De Facto Consultancy, Montenegro NEMANJA BATRICEVIC Central European University Budapest, Hungary NEMANJA STANKOV Central European University Budapest, Hungary - NETHERLANDS (2017) RODERIK REKKER University of Amsterdam, Netherlands WOUTER VAN DER BRUG University of Amsterdam, Netherlands TOM VAN DER MEER University of Amsterdam, Netherlands HENK VAN DER KOLK University of Twente, Netherlands - NETHERLANDS (2021) TOM VAN DER MEER University of Amsterdam, Netherlands MARCEL LUBBERS University of Utrecht, Netherlands NIELS SPIERINGS Radboud University, Netherlands KRISTOF JACOBS Radboud University, Netherlands TAKE SIPMA Tilburg University, Netherlands WOUTER VAN DER BRUG University of Amsterdam, Netherlands - NEW ZEALAND (2017) JACK VOWLES Victoria University of Wellington, New Zealand - NEW ZEALAND (2020) JACK VOWLES Victoria University of Wellington, New Zealand LARA GREAVES University of Auckland, New Zealand - NORWAY (2017) JOHANNES BERGH Institute for Social Research, Norway BERNT AARDAL University of Oslo, Norway - PERU (2021) ARTURO MALDONADO Pontificia Universidad Catolica del Peru, Peru DAVID SULMONT Pontificia Universidad Catolica del Peru, Peru JORGE ARAGON Pontificia Universidad Catolica del Peru, Peru - POLAND (2019) RADOSLAW MARKOWSKI Centre for the Study of Democracy, SWPS University of Social Sciences and Humanities, Poland MIKOLAJ CZESNIK Centre for the Study of Democracy, SWPS University of Social Sciences and Humanities, Poland - PORTUGAL (2019) MARINA COSTA LOBO Institute of Social Sciences, University of Lisbon, Portugal PEDRO MAGALHAES Institute of Social Sciences, University of Lisbon, Portugal - ROMANIA (2016) MIRCEA COMSA Department of Sociology, Babes-Bolyai University of Cluj-Napoca, Romania ANDREI GHEORGHITA Centre for Social Research, Lucian Blaga University of Sibiu, Romania CRISTINA STANUS Department of Political Science, International Relations, and Security Studies, Lucian Blaga University of Sibiu, Romania CAMIL POSTELNICU Department of Sociology, Babes-Bolyai University of Cluj-Napoca, Romania CLAUDIU D. TUFIS Department of Political Science, University of Bucharest, Romania BOGDAN VOICU Research Institute for the Quality of Life, Romanian Academy, Romania FLORIN N. FESNIC Department of Political Science, Babes-Bolyai University of Cluj-Napoca, Romania GABRIEL BADESCU Center for the Study of Democracy, Babes-Bolyai University of Cluj-Napoca, Romania - SLOVAKIA (2020) OLGA GYARFASOVA Comenius University, Slovakia MILOSLAV BAHNA Sociological Institute, Slovak Academy of Sciences, Slovakia - SOUTH KOREA (2016) NAM YOUNG LEE Korean Social Science Data Center, South Korea WOOK KIM Paichai University, South Korea - SWEDEN (2018) HENRIK OSCARSSON University of Gothenburg, Sweden - SWITZERLAND (2019) ANKE TRESCH FORS LAURENT BERNHARD FORS LUKAS LAUENER FORS - TAIWAN (2016) CHI HUANG National Chengchi University, Taiwan - TAIWAN (2020) CHI HUANG National Chengchi University, Taiwan - THAILAND (2019) THAWILWADEE BUREEKUL King Prajadhipok's Institute, Thailand RATCHAWADEE SANGMAHAMAD King Prajadhipok's Institute, Thailand - TUNISIA (2019) AMENI MEHREZ Central European University, Hungary BOJAN TODOSIJEVIC Institute of social sciences, Serbia CARSTEN Q. SCHNEIDER Central European University, Hungary LEVENTE LITTVAY Central European University, Hungary - TURKEY (2018) ALI CARKOGLU Koc University, Istanbul, Turkey SELIM ERDEM AYTAC Koc University, Istanbul, Turkey - UNITED STATES VINCENT HUTCHINGS (2016) University of Michigan, United States TED BRADER University of Michigan, United States MATTHEW DEBELL Stanford University, United States DARRELL DONAKOWSKI University of Michigan, United States SHANTO IYENGAR Stanford University, United States - UNITED STATES DAVID HOWELL (2020) University of Michigan, United States TED BRADER University of Michigan, United States SHANTO IYENGAR Stanford University, United States SUNSHINE HILLYGUS Duke University, United States DARON SHAW University of Texas at Austin, United States NICHOLAS VALENTINO University of Michigan, United States MATTHEW DEBELL Stanford University, United States - URUGUAY (2019) OSCAR ALBERTO BOTTINELLI Instituto Factum, Universidad de la Republica, Uruguay EDUARDO BOTTINELLI Instituto Factum, Universidad de la Republica, Uruguay LUCIA SELIOS Universidad de la Republica, Uruguay --------------------------------------------------------------------------- >>> 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 Centre for Political Studies in the United States. Professor John Aldrich of Duke University, and Chair of the CSES MODULE 5 Planning Committee, and Professor Elizabeth Zechmeister of the Vanderbilt University, Chair of the CSES MODULE 6 Planning Committee, have overseen the operations of CSES MODULE 5 during their respective terms as Chair. Various persons have staffed the CSES Secretariat throughout the MODULE 5 period. David Howell served as the Director of Studies and Stephen Quinlan served as the Project Manager. Katharina Blinzler, Kathrin Busch, Klara Dentler, Yioryos Nardis, Christian Schimpf, Hannah Schwarz, Bojan Todosijevic, and 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 5: 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-1420973, "The Fifth Module of the Comparative Study of Electoral Systems (CSES)" with Principal Investigators Nancy Burns (University of Michigan), Andre Blais (University of Montreal), and John Aldrich (Duke University) supported CSES Secretariat activities at the University of Michigan beginning in 2014. 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 5 - HOW TO ACCESS? =========================================================================== --------------------------------------------------------------------------- >>> THE CSES CODEBOOK --------------------------------------------------------------------------- Users are advised to first download the CSES Codebook file: cses5_codebook.zip Contains the six Codebook files, including this one, in text format. The Codebook can also be navigated online the CSES MODULE 5 study page at: https://cses.org/data-download/cses-module-5-2016-2021/ (Date accessed: July 15, 2023). --------------------------------------------------------------------------- >>> THE CSES DATA FILES --------------------------------------------------------------------------- The following ZIP files, which contain the CSES data are available to download from the CSES MODULE 5 study page at: https://cses.org/data-download/cses-module-5-2016-2021/ (Date accessed: July 15, 2023). Users can download the data in a variety of formats depending on which statistical packages) they intend to use with the data: cses5_csv.zip Contains a .CSV file with variables names as column headers but no additional metadata (for instance, no code labels are included). cses5_syntax.zip Contains a raw data file and syntax statements to read the dataset into SAS, SPSS, and STATA. The instructions for doing so are found in the headers of the syntax files for each statistical package: cses5.sas for SAS, cses5.sps for SPSS, and cses5.do for STATA. Users of STATA 13 or earlier versions are advised to use these files to load the dataset into their package. cses5_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. cses5_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. cses5_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. cses5_stata.zip Contains a STATA 16 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 programme 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 5 release to that location: "c:/cses/module5/20230725/" The sub-directory value "20230725" represents the version (release date) of the dataset - this being 2023, and the July 25 version of CSES MODULE 5. This file structure is compatible with how the "cses5_syntax.zip" file (detailed above) is organized. The method allows users with multiple CSES dataset's 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 5 STUDY =========================================================================== --------------------------------------------------------------------------- >>> OVERVIEW OF CSES MODULE 5 DATA FILE PARTICULARS --------------------------------------------------------------------------- The particulars of the Full Release of CSES MODULE 5 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, North America, parts of Asia, and South America, North Africa, Australia, and New Zealand) Total Geographic Regions: 13 (as defined by the UN Geographic regions) File Structure: RECTANGULAR Total Case Count: 114,714 Total Variable Count: 605 Total Polities: 45 Total Election Studies: 56 --------------------------------------------------------------------------- >>> LIST OF ELECTION STUDIES INCLUDED IN CSES MODULE 5 --------------------------------------------------------------------------- The Full Release of CSES MODULE 5 contains data from the following 56 election studies in 45 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 5 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) | --------------------------------------------------------------------- | ALBANIA (2017) 1,255 F2F Feb 15, 2018-Apr 11, 2018 | AUSTRALIA (2019) 2,000 MX Jun 03, 2019-Jun 17, 2019 | AUSTRIA (2017) 1,203 TP Oct 19, 2017-Nov 30, 2017 | BEL-FLANDERS (2019) 1,084 MX May 29, 2019-Sep 24, 2019 | BEL-WALLONIA (2019) 730 MX May 29, 2019-Sep 03, 2019 | BRAZIL (2018) 2,506 F2F Nov 10, 2018-Nov 24, 2018 | CANADA (2019) 2,889 MX Oct 22, 2019-Nov 21, 2019 | CHILE (2017) 2,000 F2F1 Dec 18, 2017-Jan 31, 2018 | COSTA RICA (2018) 1,456 TP Feb 27, 2019-Mar 06, 2019 | CZECHIA (2017) 1,559 F2F2 Oct 23, 2017-Nov 12, 2017 | CZECHIA (2021) 1,490 F2F2 Oct 11, 2021-Nov 24, 2021 | DENMARK (2019) 1,418 INT Jun 06, 2019-Sep 28, 2019 | EL SALVADOR (2019) 1,488 F2F Jul 04, 2019-Jul 24, 2019 | FINLAND (2019) 1,598 MX Apr 17, 2019-Oct 05, 2019 | FRANCE (2017) 1,830 F2F May 09, 2017-May 23, 2017 | GERMANY (2017) 2,032 F2F Sep 25, 2017-Nov 30, 2017 | GERMANY (2021) 3,152 MX Sep 27, 2021-Nov 21, 2021 | GREAT BRITAIN (2017) 984 MX Jun 28, 2017-Oct 02, 2017 | GREAT BRITAIN (2019) 2,537 MX Dec 28, 2019-Jul 13, 2020 | GREECE (2015) 1,078 MX Oct 29, 2015-Feb 29, 2016 | GREECE (2019) 1,324 INT Dec 12, 2019-Mar 07, 2020 | HONG KONG (2016) 1,020 TP Sep 06, 2016-Sep 18, 2016 | HUNGARY (2018) 1,208 F2F Apr 23, 2018-May 14, 2018 | ICELAND (2016) 1,295 TP Oct 30, 2016-Jan 25, 2017 | ICELAND (2017) 2,073 TP Oct 30, 2017-Feb 02, 2018 | INDIA (2019) 13,963 F2F May 15, 2019-May 26, 2019 | IRELAND (2016) 1,000 TP Mar 01, 2016-Mar 06, 2016 | ISRAEL (2020) 1,209 TP Jun 07, 2020-Aug 06, 2020 | ITALY (2018) 2,001 MX Mar 08, 2018-May 02, 2018 | JAPAN (2017) 1,688 MX Jan 12, 2018-Feb 01, 2018 | LATVIA (2018) 1,011 F2F Nov 14, 2018-Dec 01, 2018 | LITHUANIA (2016) 1,500 F2F1 Nov 11, 2016-Dec 10, 2016 | LITHUANIA (2020) 1,781 INT Jan 21, 2021-Feb 21, 2021 | MEXICO (2018) 1,239 F2F Jul 12, 2018-Jul 18, 2018 | MONTENEGRO (2016) 1,213 F2F Dec 08, 2016-Jan 16, 2017 | NETHERLANDS (2017) 1,903 MX Mar 16, 2017-Jul 03, 2017 | NETHERLANDS (2021) 3,485 MX Mar 18, 2021-May 16, 2021 | NEW ZEALAND (2017) 1,808 MX Sep 27, 2017-Mar 02, 2018 | NEW ZEALAND (2020) 1,725 MX Oct 21, 2020-May 01, 2021 | NORWAY (2017) 1,792 INT Sep 20, 2017-Oct 26, 2017 | PERU (2021) 1,199 F2F Dec 22, 2021-Jan 07, 2022 | POLAND (2019) 2,003 F2F Oct 24, 2019-Nov 17, 2019 | PORTUGAL (2019) 1,500 F2F Oct 12, 2019-Dec 15, 2019 | ROMANIA (2016) 1,105 F2F Dec 13, 2016-Feb 20, 2017 | SLOVAKIA (2020) 1,003 F2F Jun 10, 2020-Aug 31, 2020 | SOUTH KOREA (2016) 1,199 F2F1 Apr 14, 2016-Apr 23, 2016 | SWEDEN (2018) 3,784 MX Sep 11, 2018-Nov 06, 2018 | SWITZERLAND (2019) 4,645 MX Oct 21, 2019-Jan 05, 2020 | TAIWAN (2016) 1,690 F2F Jan 17, 2016-Apr 21, 2016 | TAIWAN (2020) 1,680 F2F Jan 14, 2020-May 30, 2020 | THAILAND (2019) 1,536 F2F1 Apr 25, 2019-Jun 05, 2019 | TUNISIA (2019) 1,477 F2F Jul 18, 2020-Jul 30, 2020 | TURKEY (2018) 1,069 F2F1 Jul 23, 2018-Sep 09, 2018 | UNITED STATES (2016) 3,648 MX Nov 09, 2016-Jan 09, 2017 | UNITED STATES (2020) 7,449 MX Nov 06, 2020-Jan 03, 2021 | URUGUAY (2019) 1,200 TP Jan 28, 2020-Feb 27, 2020 | -------------------------------------------------------------------- | TOTAL 114,714 | | Key: F2F=Face-to-face (using electronic/computerized questionnaire). | F2F1=Face-to-face (using a paper questionnaire). | F2F2=Face-to-face (using both electronic & paper questionnaire). | TP=Telephone. | INT=Internet/Online. | MX=Mixed. | | Users are advised to consult the VARIABLE NOTES for Variables E1032- | E1034 in Codebook Part 2 concerning fieldwork date classifications. --------------------------------------------------------------------------- >>> MICRO-LEVEL (SURVEY) COMPONENT --------------------------------------------------------------------------- The core questionnaire ("Module") of CSES MODULE 5 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 lower house elections (or Presidential elections if legislative elections were not held). 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 5 COLLABORATOR INSTRUCTIONS FOR THE ADMINISTRATION OF THE CSES QUESTIONNAIRE --------------------------------------------------------------------------- The following instructions appeared in the header to the questionnaire for CSES MODULE 5, as instructions to Collaborators regarding the implementation of the questionnaire; ( 1) Following these Collaborator instructions, this document is comprised of three sections: ))) CSES MODULE 5 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 5 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 5 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 (Q12 and Q13 question series). Wording for the Q12 and Q13 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 Q13 (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 Q12 (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. (17) Collaborators in the Comparative Study of Electoral Systems shall adhere to the following standards of data quality: a. Mode of interviewing: Interviews should be conducted face-to-face, unless local circumstances dictate that telephone, Internet, or mail surveys will produce higher-quality data. Mixed-mode surveys are acceptable to increase response rates and/or compensate for under coverage associated with particular survey modes. In cases of mode variation as well as in cases of within-mode variation (e.g., adaption of Internet surveys to multiple devices) presentation of questionnaires to respondents should be as similar as possible. All variation within surveys shall be documented in detail, and technical information on survey mode and, where appropriate, device used shall be identified in the data set for each respondent. National studies should seek to keep mode changes to a minimum to maximize comparability of their data sets across modules. b. Timing of interviewing: We strongly recommend that Collaborators in the Comparative Study of Electoral Systems conduct their interviews in the weeks following their national election. Interviewing should not start later than six months after the election. Out of concern for data quality, data collection should be completed in as timely a fashion as possible. In the event of a runoff election, interviewing shall be conducted after the first round election. The date of interview shall be provided for each respondent. c. Placement of module in post-election questionnaire: The questionnaire module should be asked as a single, uninterrupted block of questions. We leave it to each Collaborator to select an appropriate location for the module in their national survey instrument. Collaborators should take steps to ensure that questions asked immediately prior to the questionnaire module do not contaminate the initial questions in the module. Collaborators are also free to select an appropriate place in their survey instrument to ask the turnout, vote choice, and demographic questions. d. Population to be sampled: National samples should be drawn from all age-eligible citizens. No sampling frames with systematic under coverage of significant population groups (such as citizens without access to the Internet) are acceptable. When non-citizens (or other non-eligible respondents) are included in the sample, a variable should be provided to permit the identification of those non-eligible respondents. When a Collaborator samples from those persons who appear on voter registration lists, the Collaborator should quantify the estimated degree of discrepancy between this population and the population of all age-eligible citizens. Studies based on panels or access panels are acceptable if dictated by local circumstances. In such cases the Collaborator should seek to minimize the time lag between initial sampling and the CSES survey and quantify the estimated degree of discrepancy to the population of all age-eligible citizens and provide weights. Details about initial sampling must be documented. e. Sampling procedures: We strongly encourage the use of random samples, with random sampling procedures used at all stages of the sampling process. Collaborators should provide detailed documentation of their sampling practices for all stages. f. Sample Size: We strongly recommend that no fewer than 1,500 age-eligible respondents be interviewed, and under no circumstances should fewer than 1,000 age-eligible respondents be interviewed. g. Interviewer training: Collaborators should pre-test their survey instrument and should train interviewers in the administration of the questionnaire. The Planning Committee will provide each Collaborator with documentation that clarifies the purposes and objectives of each item and with rules with respect to probing "don't know" responses. h. Field practices: Collaborators should make every effort to ensure a high response rate. Investigators should be diligent in their effort to reach respondents not interviewed on the initial contact with the household and should be diligent in their effort to convert respondents who initially refuse to participate in the study. Data on the number of contact attempts, the number of contacts with sample persons, and special persuasion or conversion efforts undertaken should be coded for each respondent. i. Strategies for translation (and back-translation): Each Collaborator should translate the questionnaire module into their native language(s). To ensure the equivalence of the translation, Collaborators shall perform an independent re-translation of the questionnaire back into English. Collaborators engaged in translation of the questionnaire module into the same language (e.g., Spanish, French, English, German, and Portuguese) should collaborate on the translation. --------------------------------------------------------------------------- >>> 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 5 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 5 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 (survey) data, the teams of researchers responsible for the collection of the public opinion data, also compiled and deposited the following types of data: electoral legislation, political party platforms, and official electoral returns. To facilitate this process, a detailed questionnaire was constructed to serve as a framework for the macro component of the project. The Macro Data Reports, completed by the CSES Collaborators, can be found on the CSES website in the MODULE 5 section under the "Data Center". Additional measures thought pertinent to the micro-district-macro design are also compiled and available in the CSES data files. Sources consulted for the macro level component are listed as appropriate in the Bibliography at the end of this part of the CSES Codebook. =========================================================================== ))) CSES MODULE 5 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 5 Codebook. The Codebook consists of six components, namely: 1) PART 1: INTRODUCTION (file name: cses5_codebook_part1_introduction.txt) Part 1 (This file) overview of the CSES study and data, information about how to use the files, election study descriptions, 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: cses5_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: cses5_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 5 dataset. 4) PART 4: PRIMARY ELECTORAL DISTRICTS RESPONDENTS BY POLITY (file name: cses5_codebook_part4_primary_electoral_districts.txt) Part 4 details the primary electoral district by polity for each respondent included in the CSES MODULE 5 dataset. 5) PART 5: ELECTION SUMMARIES BY POLITY (file name: cses5_codebook_part5_election_summaries.txt) Part 5 contains short summaries of each election included in CSES MODULE 5. It also provides analysts with details of additional sources they may wish to consult to understand the elections included in CSES in greater detail. 6) PART 6: STUDY DESIGN AND WEIGHTS OVERVIEW BY POLITY (file name: cses5_codebook_part6_designs_and_weights.txt) Part 6 contains overviews of the design of each election study included in CSES MODULE 5. It also provides analysts with details regarding the polity weights provided by each election study. The CSES MODULE 5 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 5 download page. Analysts will also want to become familiar with the CSES MODULE 5 errata page. It is accessible from the CSES MODULE 5 download page under "Data Center" on the CSES website. 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 5 dataset, all variables begin with the letter "E" (E being the fifth letter of the English alphabet and thus signifying MODULE 5). This convention helps reduce the possibility of overwriting data when merging with other CSES datasets. Variables are presented in five groupings: 1) E1001-E1999 Identification, weight, and election study variables 2) E2001-E2999 Demographic data 3) E3001-E3999 Micro-level (survey) data (the CSES MODULE 5 questionnaire) 4) E4001-E4999 District-level data 5) E5000-E5999 Macro-level data 6) E6000-E6999 IMD bridging Variables In the Variable Descriptions portion of the CSES MODULE 5 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 --------------------------------------------------------------------------- <<>> VARIABLES 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. VARIABLES NOTES are listed below the descriptive information for the said variable and can be navigated in the Codebook by searching for "VARIABLES 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 VARIABLES 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 5 Codebook. --------------------------------------------------------------------------- >>> CSES ORIGINAL QUESTIONNAIRE FOR MODULE 5 --------------------------------------------------------------------------- The CSES MODULE 5 original questionnaire is available from the CSES Module 5 study page at: https://cses.org/data-download/cses-module-5-2016-2021/ (Date accessed: July 15, 2023). 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 5 download page under "CSES MODULE 5 Election Study Archive" at: https://cses.org/data-download/cses-module-5-2016-2021/ <<>> 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 E1001-E1039. Where available, Design Reports can be found on the CSES MODULE 5 download page under "CSES MODULE 5 Election Study Archive" at: https://cses.org/data-download/cses-module-5-2016-2021/ Further, Part 6 of the CSES MODULE 5 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 5 download page under "CSES MODULE 5 Election Study Archive" at: https://cses.org/data-download/cses-module-5-2016-2021/ --------------------------------------------------------------------------- >>> HOW TO NAVIGATE THE CSES MODULE 5 CODEBOOK --------------------------------------------------------------------------- The CSES MODULE 5 Codebook is produced in .txt format to allow for easy accessibility and as such the Codebook can be read into a variety of programs. The Codebook is also partially machine readable. The CSES MODULE 5 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. VARIABLES 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. =========================================================================== ))) CSES MODULE 5 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 5 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 respondent's 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 numerical coding is also used to identify macro level information about the parties/coalitions, namely: - 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/coalitions 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) 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 E3017). - Respondent's left-right placement of the party/coalition (variable E3019). 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 judgements by the national Collaborators of the said party/ coalition's ideological family (variable E5017). - expert judgements by the national Collaborators of the said party/ coalition's left-right placement (variable E5018). - expert judgements 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. 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 E3018). --------------------------------------------------------------------------- >>> 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 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_UNALPHA3 ID COMPONENT - POLITY UN ISO_3166-1 ALPHABETIC THREE 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". --------------------------------------------------------------------------- >>> 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 --------------------------------------------------------------------------- >>> IDENTIFICATION VARIABLES --------------------------------------------------------------------------- There are several Identification Variables in CSES MODULE 5 which allow users to not only identify an individual respondent, but election studies, and polities. <<>> ELECTION STUDY IDENTIFIERS Each Election Study in CSES MODULE 5 is uniquely identified by two variables, namely: - variable E1003 ID VARIABLE - ELECTION STUDY (NUMERIC POLITY) This variable is an eight-digit numerical code constructed from two components: the CSES polity code (variable E1006) and the year in which the election took place (E1008). 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., 04002017. AUSTRIA (2017) - variable E1004 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., USA_2016 <<>> POLITY IDENTIFIERS Each Polity in CSES MODULE 5 is uniquely identified by two variables, namely: - variable E1006_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., 040. AUSTRIA (2017) - variable E1006_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., DE. Germany (DE=Deutschland) - variable E1006_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 E1006_NAM ID COMPONENT - POLITY NAME This variable consists of polity names based on those used by the United Nations Statistics Division. E.g., Greece These polity identifiers allow for easy data bridging with other macro data sources such as the World Bank. <<>> POLITY GEOGRAPHIC IDENTIFIERS - variable E1006_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 5 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 E1006_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 E1006_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 E1005. 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 E1008). The last ten characters are the respondent identifier from E1009, 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. 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 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 in which the World Health Organization (WHO) officially classified the COVID-19 Health Crisis as a pandemic. CSES classifies whether the election took place before, partially, or fully during the pandemic - this is identified in the dataset by variable E1038. --------------------------------------------------------------------------- >>> 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 5 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 E1010-E1014 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 E1010_) namely: - SAMPLE WEIGHT (variable E1010_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 E1010_2): intended to adjust sample distributions of socio-demographic characteristics to more closely resemble the characteristics of the population - POLITICAL WEIGHT (variable E1010_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 6 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 E1011) 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 E1012 explained below). - POLITY WEIGHTS (variable E1012) These variables report 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. - SAMPLE SIZE ADJUSTMENT WEIGHT (variable E1013) 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 varaible E1014. - DATASET WEIGHTS (variable E1014) These variables 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 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 E1011, E1012, E1013, and E1014. 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 E1010-E1014 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 5 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 E5090_) 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 E5091_) 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. Freedom House and Polity IV are not affiliated with the CSES project. --------------------------------------------------------------------------- >>> PROCESSING CHECKS OF MODULE 5 DATASET BY THE CSES SECRETARIAT --------------------------------------------------------------------------- Besides processing MODULE 5 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 5 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 5 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 5 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 5 data, please contact the CSES Secretariat by e-mail at: cses@umich.edu =========================================================================== ))) CSES MODULE 5 BIBLIOGRAPHY =========================================================================== The below list constitutes a list of the primary sources that the CSES Secretariat has consulted in the development of CSES MODULE 5 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. LIST OF REFERENCES Aardal, B., and J. Bergh. 2018. "The 2017 Norwegian election." West European Politics 41 (5): 1208-1216. DOI: 10.1080/01402382.2017.1415778 ACE Electoral Knowledge Network. n.d. "Direct Democracy." http://aceproject.org/epic-en/CDTable?view=country&question=DD129. (Date accessed: October 29, 2018). ACE Electoral Knowledge Network. n.d. "Direct Democracy. 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American Federal Election Commission https://transition.fec.gov/general/FederalElections2016.shtml (Date accessed: May 08, 2019). American Federal Election Commission (2017). Federal Election 2016. Available at: https://transition.fec.gov/pubrec/fe2016/federalelections 2016.pdf (Date accessed: March 23, 2019). Andreadis, I. 2018. "Measuring Authoritarian Populism with Expert Surveys. Extending CHES estimates on populism and authoritarianism." In Electoral Integrity Project (EIP) 2018 Seminar Series. Sydney, AU. https://static1.squarespace.com/static/58533f31bebafbe99c85dc9b/t/5b0c81cb 575d1fdde9b34089/1527546335460/Measuring+Authoritarian+Populism+Expert+ Surveys+28-5-2018.pdf. (Date accessed: February 9, 2022). Aparicio, F. J., and R. Castro Cornejo. 2020. "2018 Elections. A Historical Political Juncture in Mexico." Politica y gobierno 27(2): 3-21. Arter, D. 2020. "When a pariah party exploits its demonised status: the 2019 Finnish general election." West European Politics 43 (1): 260-273. DOI: 10.1080/01402382.2019.1635799 Australian Electoral Commission (AEC). n.d. "2019 Federal Election House of Representatives Turnout By Division." https://results.aec.gov.au/24310/Website/Downloads/HouseTurnoutByDivision Download-24310.csv. (Date accessed: February 08, 2021). Australian Electoral Commission (AEC). n.d. "Divisional results" https://results.aec.gov.au/24310/Website/HouseDivisionalResults-24310.htm. (Date accessed: February 08, 2021). Austrian Minister of Interior. n.d. https://wahl17.bmi.gv.at/ (Date accessed: March 19, 2019). Austrian Ministry of Interior. n.d. "Elections in Austria." https://www.bmi.gv.at/412_english/. (Date accessed: March 19, 2019). Aylott, N., and N. Bolin. 2019. "A party system in flux: the Swedish parliamentary election of September 2018." West European Politics 42 (7): 1504-1515. DOI: 10.1080/01402382.2019.1583885 Bacelar da Silva, A. J., and E. R. Larkins. 2019. "The Bolsonaro Election, Antiblackness, and Changing Race Relations in Brazil." The Journal of Latin American and Caribbean Anthropology 24 (4): 893-913. DOI: 10.1111/jlca.12438 Baldini, G., and M. F. N. Giglioli. 2019. "Italy 2018: The Perfect Populist Storm?" Parliamentary Affairs 73 (2): 363-384. DOI: 10.1093/pa/gsy052 Barrett, D. 2016. "Irish general election 2016 report: whither the party system?" Irish Political Studies 31 (3): 418-431. DOI: 10.1080/07907184.2016.1195814 BBC News. 2020. "Donald Trump suggests delay to 2020 US presidential election." July 30, 2020. https://www.bbc.com/news/world-us-canada-53597975. (Date accessed: December 10, 2021). Bennett, D., E. Brown, A. Mirza, S. Cahlan, J. S. Lee, M. Kelly, E. Samuels, and J. Swaine. 2021. "41 minutes of fear: A video timeline from inside the Capitol siege." The Washington Post, January 16, 2021. https://www.washingtonpost.com/investigations/2021/01/16/video-timeline- capitol-siege/. (Date accessed: February 03, 2022). 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