German Internet Panel, Wave 12 (July 2014)

Resource Type
Dataset : Survey and aggregate data
  • Blom, Annelies G. (Universität Mannheim)
  • Bossert, Dayana (Universität Mannheim)
  • Gebhard, Franziska (Universität Mannheim)
  • Holthausen, Annette (Universität Mannheim)
  • Krieger, Ulrich (Universität Mannheim)
  • SFB 884 ´Political Economy of Reforms´
Publication Date
  • TNS Infratest Sozialforschung, München (F2F-Rekrutierung) (Data Collector)
  • LINK, Frankfurt (Onlineerhebung) (Data Collector)
  • ZA:
    • Political Attitudes and Behavior
    • Economic Policy, National Economic Situation
    • Natural Environment, Nature
  • CESSDA Topic Classification:
    • Social conditions and indicators
    • Mass political behaviour, attitudes/opinion
    • Government, political systems and organisation
    • Elections
    • Environmental degradation/pollution and protection
    • Economic conditions and indicators
  • Abstract

    The German Internet Panel (GIP) is an infrastructure project. The GIP serves to collect data about individual attitudes and preferences which are relevant for political and economic decision-making processes. Experimental variations in the instruments were used. The questionnaire contains numerous randomizations (order of questions or answer categories) as well as a cross-questionnaire experiment. Topics: Political responsibility of selected institutions for the economic situation in the country (Federal Government, banks, International Monetary Fund (IMF, IMF) and European Union); assessment of the probability to vote for the parties CDU, CSU, SPD, Die Linke, Bündnis 90/Die Grünen, FDP and Alternative für Deutschland (AfD); opinion on European unification as well as presumed position of the aforementioned parties on European unification; approval of the Federal Government´s achievements; approval of last year´s EU policy; participation in the European elections and voting behaviour; assessment of Germany´s membership in the EU; party affiliation and identification; degree of party affiliation; dealing with the issue of personal influence on the environment; correspondence of lifestyle with personal commitment to the environment; assessment of personal lifestyle as environmentally friendly; most important environmental problems in Germany (air pollution, chemicals and pesticides, water scarcity, water pollution, nuclear waste, household waste disposal, climate change, genetically modified food, depletion of raw materials and natural resources); extent of concern about climate change; opinion on global warming (proven fact caused by emissions, proven fact caused by natural processes or hitherto unproven theory); reasons for the global rise in temperature; demand for the German government to limit climate-damaging greenhouse gases; government and industry should start climate protection, not the ordinary citizen; demand for financial support from the state for solar systems in private homes; global warming can be slowed down without fundamental changes versus only with fundamental changes in lifestyle; personal environmental behavior: switching off lights in unused rooms, refusing to buy because of packaging, buying products made of recycled paper, own shopping bag when shopping, using public transport; number of occupational flights and holiday flights in the last year; number of kilometres driven by car in the last month or respondent does not drive a car; purchase of green electricity; acceptance of higher prices, higher taxes and cuts in living standards to halt climate change; opinion on shifting decision-making power from Germany to the European Union; estimated proportion (classified) of foreign-born (divorced) per 100 people in Germany; knowledge of exact proportion of foreign-born per 100 people in Germany; demand for government measures to reduce income disparities; migration preference: government should allow more well-qualified versus low-qualified immigrants from other countries to live in Germany. Demography: sex; citizenship; year of birth (categorised); highest school leaving certificate; highest professional qualification; marital status; household size; employment status; private internet use; federal state. Additionally coded was: interview date; questionnaire evaluation; assessment of the survey as a whole; unique ID, household ID and person ID within the household.
Temporal Coverage
  • 2014-07-01 / 2014-07-31
Geographic Coverage
  • Germany (DE)
Sampled Universe
Resident population in private households between 16 and 75 years of age
Collection Mode
  • Self-administered questionnaire: CAWI (Computer Assisted Web Interview)
Data and File Information
  • Number of Variables: 102
C - Data and documents are only released for academic research and teaching after the data depositor’s written authorization. For this purpose the Data Archive obtains a written permission with specification of the user and the analysis intention.
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Alternative Identifiers
  • ZA5923 (Type: ZA-No.)
  • Is new version of
    DOI: 10.4232/1.12123
  • Steinacker, G.; Schmidt, S. (2014): German Internet Panel (GIP): Stichprobenziehung und Rekrutierung der Teilnehmer. München: TNS Infratest Sozialforschung, Feldbericht zur Erhebung 2014
  • Steinacker, G.; Schmidt, S.; Schneekloth, U. (2012): German Internet Panel (GIP): Stichprobenziehung und Rekrutierung der Teilnehmer. München: TNS Infratest Sozialforschung, Feldbericht zur Erhebung 2012
  • Blom, A. G., Bosnjak, M., Cornilleau, A., Cousteaux, A. S., Das, M., Douhou, S. & Krieger, U. (2016). A Comparison of Four Probability-Based Online and Mixed-Mode Panels in Europe. Social Science Computer Review, 34(1), 8-25. doi: 10.1177/0894439315574825
  • Blom, A. G., Herzing, J. M. E., Cornesse, C., Sakshaug, J. W., Krieger, U., & Bossert, D. (2017). Does the Recruitment of Offline Households Increase the Sample Representativeness of Probability-Based Online Panels? Evidence From the German Internet Panel. Social Science Computer Review, 35(4), 498–520.
  • Herzing, J. M. E., & Blom, A. G. (2019). The Influence of a Person’s Digital Affinity on Unit Nonresponse and Attrition in an Online Panel. Social Science Computer Review, 37(3), 404–424.
  • Felderer, B., & Blom, A. G. (2019). Acceptance of the automated online collection of geographical information. Sociological Methods & Research, 1-21.

Update Metadata: 2021-04-07 | Issue Number: 22 | Registration Date: 2016-08-23