German Internet Panel, Wave 41 (May 2019)

Version
1.0.0
Resource Type
Dataset : Survey and aggregate data
Creator
  • Blom, Annelies G. (Universität Mannheim)
  • Fikel, Marina (Universität Mannheim)
  • Friedel, Sabine (Universität Mannheim)
  • Höhne, Jan Karem (Universität Mannheim)
  • Krieger, Ulrich (Universität Mannheim)
  • Rettig, Tobias (Universität Mannheim)
  • Wenz, Alexander (Universität Mannheim)
  • SFB 884 ´Political Economy of Reforms´, Universität Mannheim
Publication Date
2020-03-16
Contributor
  • forsa Marktforschung, Frankfurt am Main (Data Collector)
Language
German
Classification
  • ZA:
    • Public expenditures
    • Natural Environment, Nature
  • CESSDA Topic Classification:
    • Social welfare systems/structures
    • Environmental degradation/pollution and protection
Description
  • 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. The questionnaire contains numerous experimental variations in the survey instruments. For further information, please refer to the study documentation. Topics: Opinion on a reform of the health care system; advocated measures to finance the health care system (e.g. increase of contributions to health insurance); preference for family doctor model or free choice of doctor; opinion on a reform of security of unemployed; conditions for receiving unemployment benefit II - Hartz IV (e.g. indigence); federal government should set more or less rules for the German labour market than at present; opinion on a reform of the pension system; most or least supported proposals on pension financing; opinion on a reform of the education system; federal government should spend more or less money on the education system than at present; most important area of education; less important area of education; eligible area of education; opinion on a reform of the tax system; government should take measures to reduce income disparities; acceptance of tax evasion; opinion on reforms of the labour market and social systems in the member states of the Euro zone; EU should decide more or less on reforms in the member states than at present; policy areas in which the EU should have more resp. less decision-making power; policy areas in which the state is most likely to expand or reduce benefits; importance of various topics for the federal government and the respondent personally (labour market, foreign policy, European unification, internal security, pension system, tax system, environment and climate protection, defence, economy, immigration, health system, education and research, family, transport, civil liberties); support of Fridays for future demonstrations against climate change; participation in a Fridays for future demonstration; intention to participate in such a climate protection demonstration; threat of climate change; support of carbon tax; environmental behaviour (changing personal lifestyles for climate protection). Demography: sex; age (year of birth, categorized); highest educational degree; highest professional qualification; marital status; household size; employment status; German citizenship; frequency of private Internet usage; federal state. Additionally coded: respondent ID; household ID, GIP; person ID (within the household); year of recruitment (2012, 2014, and 2018); interview date; current online status; assignment to experimental groups.
Temporal Coverage
  • 2019-05-01 / 2019-05-31
Geographic Coverage
  • Germany (DE)
Sampled Universe
Persons between the ages of 16 and 75 who were living in private households at the time of recruitment
Time Dimension
  • Longitudinal: Panel
Collection Mode
  • Self-administered questionnaire: Web-based
Data and File Information
  • Number of Variables: 134
Availability
Delivery
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.
Rights
All metadata from GESIS DBK are available free of restriction under the Creative Commons CC0 1.0 Universal Public Domain Dedication. However, GESIS requests that you actively acknowledge and give attribution to all metadata sources, such as the data providers and any data aggregators, including GESIS. For further information see https://dbk.gesis.org/dbksearch/guidelines.asp
Alternative Identifiers
  • ZA7590 (Type: ZA-No.)
Publications
  • Steinacker, G.; Schmidt, S.; Schneekloth, U. (2012): German Internet Panel (GIP): Stichprobenziehung und Rekrutierung der Teilnehmer. München: TNS Infratest Sozialforschung, Feldbericht zur Erhebung 2012
  • Steinacker, G.; Schmidt, S. (2014): German Internet Panel (GIP): Stichprobenziehung und Rekrutierung der Teilnehmer. München: TNS Infratest Sozialforschung, Feldbericht zur Erhebung 2014
  • Blom, A. G., Gathmann, C., & Krieger, U. (2015). Setting Up an Online Panel Representative of the General Population: The German Internet Panel. Field Methods, 27(4), 391–408. https://doi.org/10.1177/1525822X15574494
  • 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. https://doi.org/10.1177/0894439316651584
  • 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. doi.org/10.1177/0894439318774758
  • Felderer, B., & Blom, A. G. (2019). Acceptance of the automated online collection of geographical information. Sociological Methods & Research, 1-21. https://doi.org/10.1177/0049124119882480

Update Metadata: 2021-04-07 | Issue Number: 16 | Registration Date: 2020-03-16