GESIS - DBK - ZA5700

ZA5700: Pre-election Cross Section (GLES 2013)

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List of Files

List of Files


  • (Dataset) 2 KBytes
  • ZA5700_de_v2-0-2.dta (Dataset Stata) 5 MBytes
  • ZA5700_de_v2-0-2.sav (Dataset SPSS) 3 MBytes
  • (Dataset) 2 KBytes
  • ZA5700_en_v2-0-2.dta (Dataset Stata) 5 MBytes
  • ZA5700_en_v2-0-2.sav (Dataset SPSS) 3 MBytes


  • ZA5700_fb.pdf (Questionnaire) 422 KBytes
  • ZA5700_Listenheft.pdf (Questionnaire) 2 MBytes
  • ZA5700_Listenheft_Bayern.pdf (Questionnaire) 2 MBytes
  • ZA5700_Listenheft_Hessen.pdf (Questionnaire) 2 MBytes
  • ZA5700_q.pdf (Questionnaire) 873 KBytes

Other Documents

  • (Codeplan) 138 KBytes
  • ZA5700_sb.pdf (Study Description) 166 KBytes
Availability Availability A - Data and documents are released for academic research and teaching.
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Bibliographic Citation

Citation Citation GLES (2019): Pre-election Cross Section (GLES 2013). GESIS Data Archive, Cologne. ZA5700 Data file Version 2.0.2,
Study No.ZA5700
TitlePre-election Cross Section (GLES 2013)
Current Version2.0.2, 2019-2-26,
Date of Collection29.07.2013 - 21.09.2013
Principal Investigator/ Authoring Entity, Institution
  • Rattinger, Hans - Universität Mannheim
  • Roßteutscher, Sigrid - Universität Frankfurt
  • Schmitt-Beck, Rüdiger - Universität Mannheim
  • Weßels, Bernhard - Wissenschaftszentrum Berlin für Sozialforschung
  • Wolf, Christof - GESIS – Leibniz-Institut für Sozialwissenschaften
Contributor, Institution, Role
  • Roßteutscher, Sigrid - Universität Frankfurt - ProjectLeader
  • Bieber, Ina - Universität Frankfurt - ProjectManager
  • Scherer, Philipp - Universität Frankfurt - ProjectMember
  • Förster, André - GESIS - Leibniz-Institut für Sozialwissenschaften - DataCurator
  • Kratz, Sophia - GESIS - Leibniz-Institut für Sozialwissenschaften - DataCurator


Topics Topics
  • 9.1 Information society
  • 9.2 Mass media
  • 11.5 Mass political behaviour, attitudes/opinion
  • 11.6 Government, political systems and organisation
  • 11.7 Elections
  • 17.5 Economic policy
  • 17.6 Economic systems and development


Geographic Coverage
  • Germany (DE)
UniverseThe population comprises all persons with German citizenship resident in the Federal Republic of Germany, who had a minimum age of 16 years and lived in private households at the time the survey was being conducted.
Analysis Unit Analysis Unit
  • Individual
Sampling Procedure Sampling Procedure
  • Probability: Stratified: Disproportional
Disproportional stratified multistage random sampling based on the ADM-design. All in all, 210 sampling points were drawn in West Germany with the aim to realize 1,400 interviews. 96 sampling points were drawn in East Germany to realize 700 interviews. That means that the East German population is overrepresented in the sample. The target person in the household was determined by Sweden key.
Mode of Collection Mode of Collection
  • Face-to-face interview: Computer-assisted (CAPI/CAMI)
Time Method Time Method
  • Cross-section
Kind of Data Kind of Data
  • Numeric
  • Text
Data CollectorMARPLAN Media- und Sozialforschungsgesellschaft mbH, Frankfurt am Main
Date of Collection
  • 29.07.2013 - 21.09.2013

Errata & Versions

VersionDate, Name, DOI
2.0.2 (current version)2019-2-26 Release2-0-2
2.0.12017-6-7 Release2-0-1
2.0.02014-7-17 Release2-0-0
1.0.02014-1-15 Release1-0-0
Errata in current version
2014-1-17Wrong Filter: q134aa-bb (Recall Federal State Election Bavaria)One participant (vw_lfdn = 1756) who answered to had taken part in the Bavarian federal state election, was not shown questions about his election decision (q134aa-bb) and got -97 ´not applicable´ instead.
2014-1-17Wrong scale in questionnaire: q66a-f (position of coalitions socioeconomic dimension)In the documentation of the questionnaire, there is a wrong answering scale concerning the variables q66a-f. The correct version is: (1) lower taxes, even if this means a reduction in the benefits offered by the social state (2) 2 (3) 3 (4) 4 (5) 5 (6) 6 (7) 7 (8) 8 (9) 9 (10) 10 (11) more benefits offered by the social state, even if this means an increase in taxation; the participants of the study were asked via the correct answering categories.
Version changes
Changes between version 2.0.2 and it's previous version
DateSubjectDescriptionCorrection Description
2019-2-26Extensive revision of the variable labels and value labels in the English data set2019-2-26

Further Remarks

Number of Units: 2003
Number of Variables: 650
Analysis System(s): SPSS, Stata


Relevant full texts
from SSOAR (automatically assigned)


Research Data Centre
  •  German Longitudinal Election Study (GLES)
    The German Longitudinal Election Study (GLES) is a DFG-funded project which made its debut just prior to the 2009 federal election. GLES is the largest and most ambitious election study held so far in Germany. Although the initial mandate is to examine and analyse the electorate for three consecutive elections, the aspired goal is to integrate the project within GESIS as an institutionalized election study after the federal election of 2017, and hence to make it a permanent study.