=========================================================================== COMPARATIVE STUDY OF ELECTORAL SYSTEMS (CSES) - MODULE 4 (2011-2016) CODEBOOK PART 1: INTRODUCTION FULL RELEASE - MAY 29, 2018 CSES Secretariat www.cses.org =========================================================================== HOW TO CITE THE STUDY: The Comparative Study of Electoral Systems (www.cses.org). CSES MODULE 4 FULL RELEASE [dataset and documentation]. May 29, 2018 version. doi:10.7804/cses.module4.2018-05-29 These materials are based on work supported by the American National Science Foundation (www.nsf.gov) under grant numbers SES-0817701, SES-1154687, and SES-1420973, the GESIS - Leibniz Institute for the Social Sciences, the University of Michigan, in-kind support of participating election studies, the many organizations that sponsor planning meetings and conferences, and the numerous organizations that fund national election studies by CSES collaborators. Any opinions, findings and conclusions, or recommendations expressed in these materials are those of the author(s) and do not necessarily reflect the views of the funding organizations. =========================================================================== =========================================================================== TABLE OF CONTENTS =========================================================================== ))) IMPORTANT NOTE REGARDING FULL RELEASE ))) OVERVIEW OF "CODEBOOK PART 1: INTRODUCTION" ))) LIST OF TABLES IN CODEBOOK PART 1 ))) THE COMPARATIVE STUDY OF ELECTORAL SYSTEMS (CSES) PROJECT OVERVIEW >>> CSES PROJECT PROFILE >>> CSES MODULE 4 STUDY DESCRIPTION - ABSTRACT >>> CSES MODULE 4 PLANNING COMMITTEE >>> CSES MODULE 5 PLANNING COMMITTEE >>> CSES MODULE 4 COLLABORATORS >>> CSES MODULE 4 SECRETARIAT ))) CSES MODULE 4 - HOW TO ACCESS? >>> THE CSES CODEBOOK >>> THE CSES DATA FILES ))) CSES MODULE 4 STUDY >>> OVERVIEW OF CSES MODULE 4 DATA FILE PARTICULARS >>> LIST OF ELECTION STUDIES INCLUDED IN CSES MODULE 4 >>> MICRO-LEVEL (SURVEY) COMPONENT >>> CSES MODULE 4 COLLABORATOR INSTRUCTIONS FOR THE ADMINISTRATION OF THE CSES QUESTIONNAIRE >>> DISTRICT-LEVEL COMPONENT >>> MACRO-LEVEL COMPONENT ))) CSES MODULE 4 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 4 >>> CSES - ADDITIONAL DOCUMENTATION >>> HOW TO NAVIGATE THE CSES MODULE 4 CODEBOOK ))) CSES MODULE 4 STUDY DATA AND CODEBOOK: ADDITIONAL INFORMATION >>> IDENTIFICATION VARIABLES >>> MISSING DATA >>> WEIGHTS >>> FREEDOM STATUS OF ELECTIONS >>> CODING OF PARTIES/COALITIONS & LEADERS >>> PROCESSING CHECKS OF MODULE 4 DATASET BY THE CSES SECRETARIAT ))) CSES MODULE 4 BIBLIOGRAPHY =========================================================================== ))) IMPORTANT NOTE REGARDING FULL RELEASE =========================================================================== This dataset and all accompanying documentation is the "Full Release" of CSES Module 4 (2011-2016). Users of the Final Release may wish to monitor the errata for CSES Module 4 on the CSES website, to check for known errors which may impact their analyses. To view errata for CSES Module 4, go to the Data Center on the CSES website, navigate to the CSES Module 4 download page, and click on the Errata link in the gray box to the right of the page. =========================================================================== ))) OVERVIEW OF "CODEBOOK PART 1: INTRODUCTION" =========================================================================== Part 1 of the CSES Codebook provides users with information about how to use the CSES Codebook and Data including the conventions adopted in the CSES Codebook and how to load the data into various programs. Moreover, overview of the national election studies included in CSES as well as CSES conventions concerning identification variables, missing data, weights, and coding of parties/coalitions and leaders is available here. Further, Part 1 of the Codebook provides users with an overview of the CSES project, the governing council (Planning Committee), and details of the national collaborators. =========================================================================== ))) 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 MODULE 4 WITH NUMBER OF OBSERVATIONS, MODE OF DATA COLLECTION, & 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 countries 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 country 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 country by their foremost social scientists. By collaborating in this way, the CSES community hopes to forward 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 4 are available under the "HOW TO CITE THE CSES MODULE 4 STUDY". The project also receives in-kind support from participating election studies, additional organizations that sponsor planning committee meetings and conferences, and the many organizations that fund national election studies that participate in CSES. This is the fourth iteration of CSES known as CSES Module 4. The remainder of the project description relates specifically to CSES Module 4. --------------------------------------------------------------------------- >>> CSES MODULE 4 STUDY DESCRIPTION - ABSTRACT --------------------------------------------------------------------------- CSES Module 4 has two themes. The first focused on distributional politics and social protection. The goal of the module is to enhance knowledge of voter preferences for policies that affect income and wealth distribution, in a period of constrained growth, deficit reduction, and expenditure constraint and austerity. It draws upon the literature in comparative political economy and develops data that will enable scholars to understand how political institutions condition voters' reactions to the politics of budgetary restraint. The module is influenced by the economic crises of the years before its implementation. The second subtheme focused on mobilization with a battery of questions asking respondents about contacts by parties and candidates, and about personal contacts intended to influence vote choice. CSES Module 4 data was collected from 2011 through 2016. More information regarding the theme of Module 4 can be found in the CSES Module 4 Theoretical Statement available on the CSES website. --------------------------------------------------------------------------- >>> CSES MODULE 4 PLANNING COMMITTEE --------------------------------------------------------------------------- The CSES Module 4 Planning Committee was responsible for the design of CSES Module 4, 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 4 Planning Committee: ANDRE BLAIS (Module 4 Planning Committee Chair) University of Montreal, Canada BERNT AARDAL Institute for Social Research, Norway KEES AARTS University of Twente, The Netherlands JOHN ALDRICH Duke University, United States ULISES BELTRAN Centro de Investigacion y Docencia Economica (CIDE), Mexico GORAN CULAR University of Zagreb, Croatia RACHEL GIBSON University of Manchester, United Kingdom ELISABETH GIDENGIL McGill University, Canada SARA B. HOBOLT London School of Economics and Political Science, United Kingdom DAVID A. HOWELL (CSES Director of Studies, Ex-officio member) University of Michigan, United States CHI HUANG National Chengchi University, Taiwan R.O.C. KEN'ICHI IKEDA Doshisha University, Japan PEDRO MAGALHAES University of Lisbon, Portugal RADOSLAW MARKOWSKI Warsaw School of Social Sciences and Humanities, Poland RACHEL MENEGUELLO University of Campinas, Brazil DAVID SANDERS University of Essex, United Kingdom NICOLAS SAUGER Sciences Po, France MICHAL SHAMIR Tel Aviv University, Israel JACK VOWLES Victoria University of Wellington, New Zealand BERNHARD WESSELS WZB (Wissenschaftszentrum Berlin fuer Sozialforschung), Germany --------------------------------------------------------------------------- >>> CSES MODULE 5 PLANNING COMMITTEE --------------------------------------------------------------------------- The CSES Module 5 Planning Committee took responsibility not only for the design and implementation of Module 5 but also the responsibility for the remainder of CSES Module 4 until its completion. 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 (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 B. HOBOLT London School of Economics and Political Science, United Kingdom DAVID A. HOWELL (CSES Director of Studies, Ex-officio member) 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 (CSES Project Manager, Ex-officio member) GESIS - Leibniz Institute for the Social Sciences Mannheim, Germany NICOLAS SAUGER Sciences Po, France RUDIGER SCHMITT-BECK University of Mannheim, Germany CARLOS SHENGA Higher Institute of Public Administration, Mozambique ALBERTO SIMPSER Instituto Tecnologico Autonomo de Mexico (ITAM), 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 4 COLLABORATORS --------------------------------------------------------------------------- The CSES project is incredibly grateful to our Module 4 collaborators, who raised their own funds to include CSES Module 4 in a nationally representative post-election study in their country or province. Listed collaborators are those who appear in the Design Report for the respective study - they are not necessarily the parties 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. - ARGENTINA (2015) NOAM LUPU Vanderbilt University, United States of America VIRGINIA OLIVEROS Tulane University, United States LUIS SCHIUMERINI University of Oxford, United Kingdom - AUSTRALIA (2013) IAN MCALLISTER Australian National University, Australia JULIET PIETSCH Australian National University, Australia CLIVE BEAN Queensland University of Technology, Australia RACHEL GIBSON University of Manchester, United Kingdom - AUSTRIA (2013) SYLVIA KRITZINGER University of Vienna, Austria WOLFGANG C. MUELLER University of Vienna, Austria KLAUS SCHOENBACH University of Vienna, Austria - BRAZIL (2014) RACHEL MENEGUELLO Center for Studies on Public Opinion, Universidade de Campinas, Brazil - BULGARIA (2014) ALINA DOBREVA European University Institute, Bulgaria - CANADA (2011) PATRICK FOURNIER Universite de Montreal, Canada FRED CUTLER University of British Columbia, Canada STUART SOROKA, University of Michigan, United States DIETLIND STOLLE McGill University, Canada - CANADA (2015) PATRICK FOURNIER Universite de Montreal, Canada FRED CUTLER University of British Columbia, Canada STUART SOROKA, University of Michigan, United States DIETLIND STOLLE McGill University, Canada - CZECH REPUBLIC LUKAS LINEK (2013) Czech Academy of Sciences, Czech Republic - FINLAND (2015) KIMMO GROENLUND Abo Akademi University, Finland HANNA WASS University of Helsinki, Finland - FRANCE (2012) NICOLAS SAUGER Sciences Po, France - GERMANY (2013) BERNHARD WESSELS Wissenschaftszentrum Berlin fuer Sozialforschung (WZB), Germany HANS RATTINGER University of Mannheim, Germany SIGRID ROSSTEUTSCHER Goethe University, Germany RUDIGER SCHMITT-BECK University of Mannheim, Germany CHRISTOF WOLF GESIS Leibniz-Institute for the Social Sciences, Germany - GREAT BRITAIN EDWARD FIELDHOUSE (2015) University of Manchester, Great Britain JANE GREEN University of Manchester, Great Britain GEOFFREY EVANS University of Oxford, Great Britain HERMANN SCHMITT University of Manchester, Great Britain CEES VAN DER EIJK University of Nottingham, Great Britain JONATHAN MELLON University of Oxford, Great Britain CHRISTOPHER PROSSER University of Manchester, Great Britain - GREECE (2012) THEODORE CHADJIPADELIS Aristotle University of Thessaloniki, Greece IOANNIS ANDREADIS Aristotle University of Thessaloniki, Greece - GREECE (2015) IOANNIS ANDREADIS Aristotle University of Thessaloniki, Greece THEODORE CHADJIPADELIS Aristotle University of Thessaloniki, Greece EFTICHIA TEPEROGLOU Aristotle University of Thessaloniki, Greece - HONG KONG (2012) LI PANG-KWONG Lingnan University, Hong Kong - ICELAND (2013) OLAFUR P. HARDARSON University of Iceland, Iceland HULDA PORISDOTTIR University of Iceland, Iceland EVA H. ONNUDOTTIR Centre for Doctoral Social and Behavioral Sciences University of Mannheim, Germany - IRELAND (2011) MICHAEL MARSH Trinity College Dublin, Ireland - ISRAEL (2013) MICHAL SHAMIR Tel Aviv University, Israel ORIT KEDAR Hebrew University of Jerusalem, Israel - JAPAN (2013) KEN'ICHI IKEDA Doshisha University, Japan MASAHIRO YAMADA Kwansei-Gakuin University, Japan YUKIO MAEDA University of Tokyo, Japan - KENYA (2013) ROBERT MATTES University of Cape Town, South Africa WINNIE MITULLAH University of Nairobi, Kenya COLLETTE SHULZ-HERZENBERG Stellenbosch University, South Africa ABEL OYUKE University of Nairobi, Kenya - LATVIA (2011) JANIS IKSTENS University of Latvia, Latvia - LATVIA (2014) JANIS IKSTENS University of Latvia, Latvia - MEXICO (2012) ULISES BELTRAN Centro de Investigacion y Docencia Economica (CIDE), Mexico ROSARIO AGUILAR Centro de Investigacion y Docencia Economica (CIDE), Mexico - MEXICO (2015) ULISES BELTRAN Centro de Investigacion y Docencia Economica (CIDE), Mexico ROSARIO AGUILAR Centro de Investigacion y Docencia Economica (CIDE), Mexico - MONTENEGRO (2012) OLIVERA KOMAR De Facto Consultancy, Montenegro PAVLE GEGAJ De Facto Consultancy, Montenegro MILOS BESIC De Facto Consultancy, Montenegro - NEW ZEALAND (2011) JACK VOWLES Victoria University of Wellington, New Zealand - NEW ZEALAND (2014) JACK VOWLES Victoria University of Wellington, New Zealand HILDE COFFE Victoria University of Wellington, New Zealand JENNIFER CURTIN University of Auckland, New Zealand GERARD COTTERELL University of Auckland, New Zealand - NORWAY (2013) BERNT AARDAL University of Oslo, Norway JOHANNES BERGH Institute for Social Research, Oslo, Norway - PERU (2016) DAVID SULMONT Pontificia Universidad Catolica del Peru, Peru VANIA MARTINEZ Instituto de Opinion Publica, Pontificia Universidad Catolica del Peru, Peru - PHILIPPINES LINDA LUZ GUERRERO (2016) Social Weather Stations, Philippines VLADYMIR JOSEPH LICUDINE Social Weather Stations, Philippines - POLAND (2011) RADOSLAW MARKOWSKI University of Social Sciences and Humanities, Poland MIKOLAJ CZESNIK University of Social Sciences and Humanities, Poland PAWEL GRZELAK Institute of Political Studies, Polish Academy of Sciences, Poland MICHAL KOTNAROWSKI Institute of Political Studies, Polish Academy of Sciences, Poland - PORTUGAL (2015) MARINA COSTA LOBO University of Lisbon, Portugal PEDRO MAGALHAES University of Lisbon, Portugal JOAO TIAGO GASPAR University of Lisbon, Portugal - ROMANIA (2012) MIRCEA COMSA Babes-Bolyai University of Cluj-Napoca, Romania FLORIN N. FESNIC Babes-Bolyai University of Cluj-Napoca, Romania ANDREI GHEORGHITA Lucian Blaga University of Sibiu, Romania GABRIEL BADESCU Babes-Bolyai University of Cluj-Napoca, Romania CLAUDIU D. TUFIS University of Bucharest, Romania CRISTINA STANUS Lucian Blaga University of Sibiu, Romania BOGDAN VOICU Romanian Academy, Romania CAMIL POSTELNICU Babes-Bolyai University of Cluj-Napoca, Romania - ROMANIA (2014) MIRCEA COMSA Babes-Bolyai University of Cluj-Napoca, Romania ANDREI GHEORGHITA Lucian Blaga University of Sibiu, Romania CRISTINA STANUS Lucian Blaga University of Sibiu, Romania CAMIL POSTELNICU Babes-Bolyai University of Cluj-Napoca, Romania CLAUDIU D. TUFIS University of Bucharest, Romania BOGDAN VOICU Romanian Academy, Romania FLORIN N. FESNIC Babes-Bolyai University of Cluj-Napoca, Romania GABRIEL BADESCU Babes-Bolyai University of Cluj-Napoca, Romania - SERBIA (2012) BOJAN TODOSIJEVIC Center for Political Studies and Public Opinion Research, Serbia ZORAN PAVLOVIC University of Belgrade, Serbia DAVID A. HOWELL University of Michigan, United States ALTIN ILIRJANI USAID, United States - SLOVAKIA (2016) OLGA GYARFASOVA Comenius University, Slovakia MILOSLAV BAHNA Slovak Academy of Sciences (SU SAV), Slovakia - SLOVENIA (2012) JANEZ STEBE Faculty of Social Sciences, University of Ljubljana, Slovenia - SOUTH AFRICA ROBERT MATTES (2014) University of Cape Town, South Africa COLLETTE SHULZ-HERZENBERG Stellenbosch University, South Africa - SOUTH KOREA NAM YOUNG LEE (2012) Korean Social Science Data Center, South Korea WOOK KIM Paichai University, South Korea - SWEDEN (2014) HENRIK OSCARSSON University of Gothenburg, Sweden - SWITZERLAND (2011) GEORG LUTZ FORS & University of Lausanne, Switzerland - TAIWAN (2012) CHI HUANG National Chengchi University, Taiwan - THAILAND (2011) THAWILWADEE BUREEKUL King Prajadhipok's Institute, Thailand ROBERT B. ALBITTON University of Mississippi, United States RATCHAWADEE SANGMAHAMAD King Prajadhipok's Institute, Thailand - TURKEY (2015) ALI CARKOGLU Koc University, Turkey SELIM ERDEN AYTAC Koc University, Turkey - UNITED STATES DARRELL DONAKOWSKI (2012) University of Michigan, United States VINCENT HUTCHINGS University of Michigan, United States SIMON JACKMAN Stanford University, United States GARY M. SEGURA Stanford University, United States --------------------------------------------------------------------------- >>> CSES MODULE 4 SECRETARIAT --------------------------------------------------------------------------- The CSES Secretariat comprises the central staffing and operations for the CSES project, under the leadership of the chair of the CSES Planning Committee (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 Andre Blais of the University of Montreal, Chair of the CSES Module 4 Planning Committee, and Professor John Aldrich, Chair of the CSES Module 5 Planning Committee, have overseen the operations of CSES Module 4 during their respective terms as Chair. The CSES Secretariat for Module 4 was comprised of the following persons: David Howell served as the Director of Studies and Dr. Stephen Quinlan served as the Project Manager. Andrei Artimof, Lion Behrens, Dr. Kathrin Busch, Katharina Blinzler, Dr. Jessica Fortin-Rittberger, Sebastian Netscher, Christian Schimpf, Hannah Schwarz, Annika Stein, Slaven Zivkovic, and Dr. Bojan Todosijevic were responsible for research support, documentation, data preparation, data checking and cleaning, assisting with meeting and Conference organization, and providing additional administrative support. Cherolyn Brooks, Laurie Winslow, and Dr. Yioryos Nardis of the University of Michigan provided further administrative and public relations support to the project. Support was received from various sources for the activities of the CSES Secretariat during the period of CSES Module 4: (1) American National Science Foundation (NSF) grant SES-0817701, "The Dynamics of Political Choice: The Third Module of the Comparative Study of Electoral Systems" with Principal Investigators Nancy Burns (University of Michigan), Ian McAllister (Australian National University), and Andre Blais (University of Montreal), supported CSES Secretariat activities at the University of Michigan from 2008 through 2012. (2) American National Science Foundation (NSF) grant SES-1154687, "Distributional Politics and Social Protection: the Fourth Module of the Comparative Study of Electoral Systems (CSES)" with Principal Investigators Nancy Burns (University of Michigan) and Andre Blais (University of Montreal), supported CSES Secretariat activities at the University of Michigan from 2012 through 2014. (3) 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. (4) The CSES Secretariat activities at the GESIS Leibniz Institute for the Social Sciences, Germany are funded by GESIS. (5) The Center for Political Studies at the University of Michigan provides additional financial support. =========================================================================== ))) CSES MODULE 4 - HOW TO ACCESS? =========================================================================== --------------------------------------------------------------------------- >>> THE CSES CODEBOOK --------------------------------------------------------------------------- Users are advised to first download the CSES codebook file: cses4_codebook.zip Contains the six codebook files, including this one, in text format. The codebook can also be navigated online the CSES Module 4 study page at: http://www.cses.org/datacenter/module4/module4.htm --------------------------------------------------------------------------- >>> THE CSES DATA FILES --------------------------------------------------------------------------- The following ZIP files, which contain the CSES data are available to download from the CSES Module 4 study page at: http://www.cses.org/datacenter/module4/module4.htm Users can download the data in a variety of formats depending on which statistical packages) they intend to use with the data: cses4_csv.zip Contains a CSV file with variables names as column headers but no additional metadata (for instance, no code labels are included). cses4_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: cses4.sas for SAS, cses4.sps for SPSS, and cses4.do for STATA. cses4_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. cses4_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. cses4_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. cses4_stata.zip Contains a STATA 13 system file (.dta), with the dataset already prepared and ready to be loaded into STATA. Missing data statements are not applied. Please note that all of the above packages will need a File Extractor programme 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 4 release to that location: "c:/cses/module4/20180529/" The subdirectory value "20180529" represents the version (release date) of the dataset - this being 2018, and the 29 May version of CSES Module 4. This file structure is compatible with how the "cses4_syntax.zip" file (detailed above) is organized. The ,method allows users with multiple CSES datasets and/or versions to stay organized and not over-write their other files. Users of other computer types (Macs, Unix, etc.) are recommended to use a similar directory structure to organize their CSES files. =========================================================================== ))) CSES MODULE 4 STUDY =========================================================================== --------------------------------------------------------------------------- >>> OVERVIEW OF CSES MODULE 4 DATA FILE PARTICULARS --------------------------------------------------------------------------- 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, Australia & New Zealand) File Structure: RECTANGULAR Total Case Count: 75,558 Total Variable Count: 484 Total Polities: 39 Total Election Studies: 45 --------------------------------------------------------------------------- >>> LIST OF ELECTION STUDIES INCLUDED IN CSES MODULE 4 --------------------------------------------------------------------------- The Final Release of CSES Module 4 contains data from the following 45 election studies in 39 countries. They are listed below in alphabetic order with an overview of some particulars of each election study. | +++ TABLE: OVERVIEW OF ELECTION STUDIES INCLUDED IN MODULE 4 WITH | NUMBER OF OBSERVATIONS AND MODE OF DATA COLLECTION AND | FIELDWORK DATES | | POLITY (ELEC YEAR) No of Mode of Dates of Fieldwork | Observations Interview (Start-End date) | --------------------------------------------------------------------- | ARGENTINA (2015) 1,406 F2F Nov 21, 2015-Dec 30, 2015 | AUSTRALIA (2013) 3,953 MX Sep 6, 2013-Jan 6, 2014 | AUSTRIA (2013) 1,000 TP Oct 1, 2013-Oct 29, 2013 | BRAZIL (2014) 3,136 F2F Nov 1, 2014-Nov 19, 2014 | BULGARIA (2014) 999 F2F Jan 23, 2015-Jan 31, 2015 | CANADA (2011) 3,458 MX Multi-wave study*** | CANADA (2015) 4,202 MX Multi-wave study*** | CZECH REPUBLIC (2013) 1,653 F2F Oct 28, 2013-Nov 14, 2013 | FINLAND (2015) 1,587 MX Apr 24, 2015-Jul 7, 2015 | FRANCE (2012) 2,014 F2F May 9, 2012-Jun 9, 2015 | GERMANY (2013) 1,889 F2F Sep 23, 2013-Dec 23, 2013 | GREAT BRITAIN (2015) 1,567 F2F May 9, 2015-Sep 13, 2015 | GREECE (2012) 1,029 MX Oct 19, 2012-Jan 5, 2013 | GREECE (2015) 1,008 MX Jun 12, 2015-Sep 8, 2015 | HONG KONG (2012) 1,044 TP Sep 13, 2012-Sep 22, 2013 | ICELAND (2013) 1,479 TP May 4, 2013-Sep 30, 2013 | IRELAND (2011) 1,853 TP Mar 6, 2011-Apr 10, 2011 | ISRAEL (2013) 1,017 TP Feb 8, 2013-Mar 13, 2013 | JAPAN (2013) 1,937 F2F Jul 22, 2013-Aug 25, 2013 | KENYA (2013) 1,200 F2F Oct 21, 2013-Nov 28, 2013 | LATVIA (2011) 1,004 F2F Oct 16, 2011-Nov 11, 2011 | LATVIA (2014) 1,036 F2F Nov 7, 2014-Nov 20, 2014 | MEXICO (2012) 2,400 F2F Jul 13, 2012-Jul 19, 2013 | MEXICO (2015) 1,197 F2F Jun 20, 2015-Jun 28, 2015 | MONTENEGRO (2012) 967 F2F Feb 2013-Mar 2013 | NEW ZEALAND (2011) 1,374 MX Nov 30, 2011-Apr 4, 2012 | NEW ZEALAND (2014) 1,224 MX Sep 23, 2014-Feb 6, 2015 | NORWAY (2013) 1,727 MX Sep 12, 2013-Jan 6, 2014 | PERU (2016) 1,572 F2F May 7, 2016-May 17, 2016 | PHILIPPINES (2016) 1,200 F2F Jun 24, 2016-Jun 27, 2016 | POLAND (2011) 1,919 F2F Oct 20, 2011-Nov 13, 2011 | PORTUGAL (2015) 1,499 F2F Oct 7, 2015-Dec 9, 2015 | ROMANIA (2012) 2,283 F2F Dec 15, 2012-Jan 30, 2013 | ROMANIA (2014) 1,112 F2F Nov 20, 2014-Dec 8, 2014 | SERBIA (2012) 1,568 F2F Dec 6, 2012-Feb 13, 2013 | SLOVAKIA (2016) 1,150 F2F Oct 13, 2016-Nov 28, 2016 | SLOVENIA (2011) 1,031 F2F Mar 29, 2012-May 28, 2012 | SOUTH AFRICA (2014) 1,300 F2F Feb 2, 2015-Feb 26, 2015 | SOUTH KOREA (2012) 1,000 F2F Apr 12, 2012-Apr 29, 2012 | SWEDEN (2014) 832 F2F Sep 15, 2014-Nov 17, 2014 | SWITZERLAND (2011) 4,391 MX Oct 24, 2011-Dec 12, 2011 | TAIWAN (2012) 1,826 F2F Jan 15, 2012-Mar 6, 2012 | THAILAND (2011) 1,500 F2F Jul 15, 2011-Aug 11, 2011 | TURKEY (2015) 1,086 F2F Jul 18, 2015-Sep 10, 2015 | UNITED STATES (2012) 1,929 F2F Nov 7, 2012-Jan 12, 2013 | -------------------------------------------------------------------- | TOTAL 75,558 | | Key: F2F=Face to Face; TP=Telephone, MB=Mailback; MX=Mixed. | | *** = Study run across multiple waves. Please see variables | D1026-D1028 for comprehensive details for dates of fieldwork | for each wave. For election studies that are embedded in multi-wave panel studies, only those respondents who participated in the wave of the survey that included CSES Module 4 are included in the CSES Module 4 dataset. --------------------------------------------------------------------------- >>> MICRO-LEVEL (SURVEY) COMPONENT --------------------------------------------------------------------------- The core questionnaire ("Module") of CSES Module 4 was intended to be administered as a single, uninterrupted block of questions in a nationally representative post-election survey in each country. (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 the administration of 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 Part 3 of the Codebook. (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 4 COLLABORATOR INSTRUCTIONS FOR THE ADMINISTRATION OF THE CSES QUESTIONNAIRE --------------------------------------------------------------------------- The following instructions appeared in the header to the questionnaire for CSES Module 4, as instructions to collaborators regarding the implementation of the questionnaire in their respective polity. ( 1) CSES MODULE 4 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 4 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 4 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 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, it is most preferable for the CSES Module to be administered at the beginning of the survey instrument. Where this is not possible, 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) Show cards 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 show cards for select questions. It is indicated in the NOTES when a show card 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 (Q5 and Q6 question series). Wording for the Q5 and Q6 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 Q6 (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 Q5 (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 or after 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 or mail surveys will produce higher quality data. 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. 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 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. 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. 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. F) SAMPLE SIZE: We strongly recommend that no 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 e 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) 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 the returns of the lower house (first segment) election for each respondent's district. Wherever possible, these data were collected from official electoral commissions (see Bibliography for details). In other cases, CSES has been grateful for the compilations of these data provided by third-party sources. --------------------------------------------------------------------------- >>> 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 4 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 4 DOCUMENTATION - WHAT'S AVAILABLE AND HOW TO USE? =========================================================================== There are several components to the CSES documentation. We detail each in turn below: --------------------------------------------------------------------------- >>> CSES CODEBOOK OVERVIEW --------------------------------------------------------------------------- The primary component of documentation is the CSES Codebook. The codebook consists of six components, namely: 1) PART 1: INTRODUCTION (file name: cses4_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 datafile, the checks the CSES Secretariat conducts on the datafile and information on the national collaborators of the CSES project for each polity. 2) PART 2: CSES VARIABLES DESCRIPTION (file name: cses4_codebook_part2_variables.txt) Part 2 is the variable description file and includes the survey questions, code frames, general notes, election study notes, and details about sources for macro data. 3) PART 3: PARTIES AND LEADERS BY COUNTRY (file name: cses4_codebook_part3_parties_and_leaders.txt) Part 3 details the party/coalition and leader numeric and alphabetical coding for each polity included in the CSES Module 4 dataset. 4) PART 4: PRIMARY ELECTORAL DISTRICTS RESPONDENTS BY POLITY (file name: cses4_codebook_part4_primary_electoral_districts.txt) Part 4 details the primary electoral district by polity for each respondent included in the CSES Module 4 dataset. 5) PART 5: ELECTION SUMMARIES BY POLITY (file name: cses4_codebook_part5_election_summaries.txt) Part 5 contains short summaries of each election included in CSES Module 4. 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: cses4_codebook_part6.txt) Part 6 contains overviews of the design of each election study included in CSES Module 4. It also provides analysts with details regarding the polity weights provided by each election study. The CSES Module 4 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 4 download page under "Data Center" on the CSES website (www.cses.org). Analysts will also want to become familiar with the CSES Module 4 errata page. It is accessible from the CSES Module 4 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 4 dataset, all variables begin with the letter "D" (D being the fourth letter of the English alphabet and thus signifying Module 4). This convention helps reduce the possibility of overwriting data when merging with other CSES datasets. Variables are presented in five groupings: 1) D1001-D1999 Identification, weight, and election study variables 2) D2001-D2999 Demographic variables 3) D3001-D3999 Micro-level (survey) data (the CSES Module 4 questionnaire) 4) D4001-D4999 District-level data 5) D5001-D5999 Macro-level data In the Variable Descriptions portion of the codebook, 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 polity's 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 essential deviations specific to cases from CSES conventions. They are also used to provide source data information for users. Where applicable, ELECTION STUDY NOTES are listed below a particular variable and any VARIABLES NOTES in part 2 and 3 of the CSES codebook. They can be navigated in the codebook by searching for "ELECTION STUDY NOTES" in Parts 2-4 of the CSES codebook. --------------------------------------------------------------------------- >>> CSES ORIGINAL QUESTIONNAIRE FOR MODULE 4 --------------------------------------------------------------------------- The CSES Module 4 original questionnaire is available from the CSES Module 4 study page at: http://www.cses.org/datacenter/module4/module4.htm or by referencing the corresponding variable descriptions in the CSES Module 4 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 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 country level data. It aids the CSES Secretariat in collating some of the macro level data for each polity included in the country. Where available, macro reports can be found on the CSES Module 4 download page under "CSES Module 4 Election Study Archive" at: http://www.cses.org/datacenter/module4/module4.htm <<>> 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 D1001-D1034. Where available, design reports can be found on the CSES Module 4 download page under "CSES Module 4 Election Study Archive" at: http://www.cses.org/datacenter/module4/module4.htm Further, Part 6 of the 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 4 download page under "CSES Module 4 Election Study Archive" at: http://www.cses.org/datacenter/module4/module4.htm --------------------------------------------------------------------------- >>> HOW TO NAVIGATE THE CSES MODULE 4 CODEBOOK --------------------------------------------------------------------------- CSES 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 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 VARIABLES NOTES = Notes for particular variables ELECTION STUDY NOTES = Notes for a particular election study =========================================================================== ))) CSES MODULE 4 STUDY DATA AND CODEBOOK: ADDITIONAL INFORMATION =========================================================================== --------------------------------------------------------------------------- >>> IDENTIFICATION VARIABLES --------------------------------------------------------------------------- There are several identification variables in CSES Module 4 which allow users to not only identify an individual respondent, but election studies, and polities. <<>> ELECTION STUDY IDENTIFIERS Each Election Study in CSES Module 4 is uniquely identified by two variables, namely: - variable D1003 ID VARIABLE - ELECTION STUDY (NUMERIC POLITY) This variable is an eight-digit numerical code constructed from two components: the CSES polity code (variable D1006) and the year in which the election took place (D1008). 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., 03602013. AUSTRALIA (2013) - variable D1004 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 Division´s. The remaining characters correspond to the year of the election. E.g., USA_2012 <<>> POLITY IDENTIFIERS Each Polity in CSES Module 4 is uniquely identified by two variables, namely: - variable D1006_UN ID COMPONENT - POLITY UN CODE This variable consists of the numeric country codes assigned by the United Nations Statistics Division to polities E.g., 372. IRELAND (2011) - variable D1006_NAM ID COMPONENT - POLITY NAME This variable consists of polity names based on those used by the United Nations Statistics Division. E.g., New Zealand These polity identifiers allow for easy data bridging with other macro data sources such as the World Bank. <<>> RESPONDENT IDENTIFIER Respondents can be uniquely identified in the dataset by variable D1005. 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 D1008). The last ten characters are the respondent identifier from D1009, which is unique within each election study. --------------------------------------------------------------------------- >>> 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 country. These are available on the Module 4 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 a number of weight measures in the CSES data (see variables D1010-D1014 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 D1010_) namely: - SAMPLE WEIGHT (variable D1010_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 D1010_2): intended to adjust sample distributions of socio-demographic characteristics to more closely resemble the characteristics of the population - POLITICAL WEIGHT (variable D1010_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 variables, constructed from the original weights. They are: - FACTOR WEIGHTS (variable D1011) These variables report the mean weight of each type, within each polity. The resulting factors are then used to create the derivative Polity Weights (D1012 explained below) - POLITY WEIGHTS (variable D1012) These variables report standardized versions (with a mean 1 within the polity) of the original weights provided with the component election studies, described in D1010. They are the ratio of each weighting factor to the mean weight (D1011) of each type, calculated within each polity. - SAMPLE SIZE ADJUSTMENT WEIGHT (variable D1013) 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 (D1014 explained below). - DATASET WEIGHTS (variable D1014) These variables are intended for micro-level analyses involving the entire CSES sample. Using the sample size adjustment (D1013), the centered weights (D1012) 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 D1011, D1012, D1013, and D1014. Analysts are advised to read the weight documentation carefully to ensure that 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 D1010-D1014 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 country 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 4 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 D5050) 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 D5051) Polity IV assigns a numerical rating to a polity on a scale of -10 to 10 indicating whether the country is strongly democratic or strongly autocratic. Freedom House and Polity IV are not affiliated with the CSES project. --------------------------------------------------------------------------- >>> CODING OF PARTIES/COALITIONS & LEADERS --------------------------------------------------------------------------- CSES codes parties/coalitions in its dataset numerically and alphabetically. Below we provide explanations of both of these coding schemes. The details of each party/leader classification is available in Part 3 of the CSES Codebook. <<>> CSES NUMERICAL PARTY/COALITION CODING All parties/coalitions or presidential candidates, where applicable, participating in the election or the previous election receive a numerical code. These codes are used to Identify the following: - who a respondent's voted for in the current election (variable D3006). - who the respondent voted for in the previous election (variable D3008). - the respondent's party identification (variable D3018). - the extent of institutional contact the respondent received from a party/coalition during the election campaign (variable D3021). The numeric 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 D5007 and D5011). - which party/coalition held the prime ministership before and after the elections (variable D5008 and D5012). Where possible, the numeric codes assigned to parties/coalitions are consistent for the current and previous election. However, for the previous election (variable D3008) different codes might have been allocated for the same parties (for example a party in the current election might be standing as party of a coalition but previously stood alone). Users are advised to consult the election study notes for variable D3008 for each country where details of deviations are noted. <<>> CSES ALPHABETICAL PARTY/COALITION CODING Parties A through F are the six most popular parties/coalitions, ordered in descending order of their share of the popular vote in the parliamentary election (unless otherwise stated). Thus Party A is the party/coalition that received the most votes in the election, party B the second most votes etc... Parties/coalitions who achieve at least 1% of the vote nationally are eligible for an alphabetical A-F assignment. In countries with multiple electoral tiers and where one vote is cast, parties are ordered according to their vote share in tier 1 (the lowest tier), unless otherwise stated. In countries where voters have two votes (i.e.: a constituency and a list vote) simultaneously, for example Germany, parties are ordered by the national share of the party list vote (tier 2). Parties G, H, and I are supplemental parties. They may, but do not have to, accord with how parties A-F are ordered, that is ordered on the popular share of the vote in a country. More often, they are codified in no particular order. These parties are voluntarily provided by each country's election study and often reflect important or notable parties within a country. They may also include data about individual parties within a coalition, where data about the coalition and the individual parties, or some of these parties that make it up, are provided. These codes are used to identify the following in the micro component of the CSES dataset: - Respondent's likeability of the party/coalition (variable D3011). - Respondent's left-right placement of the party/coalition (variable D3013). These alphabetical codes are used to identify distinct and macro level information about these said parties/coalitions, namely: - The said party/coalition's vote share in the respondent's electoral district (variable D4003). - the said party/coalition's share of the vote in the election (variables D5001, D5002, & D5005). - the said party/coalition's share of the seats in the election (variables D5003 & D5004). - the said party/coalition's share of cabinet portfolios before and after the election (variable D5009 & D5013). - expert judgements by the national collaborators of the said party/coalition's ideological family (variable D5016). - expert judgements by the national collaborators of the said party/ coalition's left-right placement (variable D5017). <<>> CSES ALPHABETICAL LEADER CODING Leaders A through F tend to be the leaders of the six most popular parties/coalitions or the presidential candidates of these parties. They correspond to parties A-F (i.e.: Leader A will be related to Party A in some way, Leader B will be related to Party B etc...) Leaders G, H, and I are supplemental leaders. They may be related to parties G, H, I but they do not have to be. These leaders are voluntarily provided by each country's election study and often include data about additional personalities of interest. For example, in a parliamentary system, data about a President might be provided, even if the Presidency is not being contested. On many occasions, slots Leader G, H, and I will include additional data for parties/coalitions that have multiple leaders. These codes are used to identify the following in the micro and macro components of the CSES dataset: - Respondent's likeability of the leader/personality in question (variable D3012). --------------------------------------------------------------------------- >>> PROCESSING CHECKS OF MODULE 4 DATASET BY THE CSES SECRETARIAT --------------------------------------------------------------------------- Besides processing Module 4 studies from individual polities to ensure they are fit for comparative analysis, which involves detailed checking of individual studies, a key role of the CSES Secretariat is to perform several checks on the Module 4 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 - 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 4 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 4 Dataset to ensure they are appropriately assigned labels and documented in the CSES Codebook. If you identify any potential issue with the CSES Module 4 data, please contact the CSES Secretariat by e-mail at: cses@umich.edu =========================================================================== ))) CSES MODULE 4 BIBLIOGRAPHY =========================================================================== The below list constitutes a list of the primary sources that the CSES Secretariat has consulted in the development of CSES Module 4 Codebook and Data. The below list, while thorough, is not comprehensive. Instead, all sources not listed here are listed in the appropriate section of the Codebook that the information refers to. 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