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Can Online Surveys Represent the Entire Population?

Author

Listed:
  • Grewenig, Elisabeth

    (ifo Institute)

  • Lergetporer, Philipp

    (ifo Institute)

  • Simon, Lisa

    (ifo Institute)

  • Werner, Katharina

    (ifo Institute)

  • Woessmann, Ludger

    (ifo Institute and LMU Munich)

Abstract

A general concern with the representativeness of online surveys is that they exclude the \"offline\" population that does not use the internet. We run a large-scale opinion survey with (1) onliners in web mode, (2) offliners in face-to-face mode, and (3) onliners in face-to-face mode. We find marked response differences between onliners and offliners in the mixed-mode setting (1 vs. 2). Response differences between onliners and offliners in the same face-to-face mode (2 vs. 3) disappear when controlling for background characteristics, indicating mode effects rather than unobserved population differences. Differences in background characteristics of onliners in the two modes (1 vs. 3) indicate that mode effects partly reflect sampling differences. In our setting, re-weighting online-survey observations appears a pragmatic solution when aiming at representativeness for the entire population.

Suggested Citation

  • Grewenig, Elisabeth & Lergetporer, Philipp & Simon, Lisa & Werner, Katharina & Woessmann, Ludger, 2018. "Can Online Surveys Represent the Entire Population?," Rationality and Competition Discussion Paper Series 117, CRC TRR 190 Rationality and Competition.
  • Handle: RePEc:rco:dpaper:117
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    References listed on IDEAS

    as
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    Cited by:

    1. Riccardo Bruni & Alessandro Gioffré & Maria Marino, 2022. ""In-group bias in preferences for redistribution: a survey experiment in Italy"," IREA Working Papers 202223, University of Barcelona, Research Institute of Applied Economics, revised Nov 2023.
    2. Lergetporer, Philipp & Woessmann, Ludger, 2019. "The Political Economy of Higher Education Finance: How Information and Design Affect Public Preferences for Tuition," Rationality and Competition Discussion Paper Series 145, CRC TRR 190 Rationality and Competition.
    3. Ingar Haaland & Christopher Roth & Johannes Wohlfart, 2023. "Designing Information Provision Experiments," Journal of Economic Literature, American Economic Association, vol. 61(1), pages 3-40, March.
    4. Ludger Wößmann & Philipp Lergetporer & Elisabeth Grewenig & Sarah Kersten & Katharina Werner, 2018. "Was denken die Deutschen zu Geschlechterthemen und Gleichstellung in der Bildung? – Ergebnisse des ifo Bildungsbarometers 2018," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 71(17), pages 15-30, September.
    5. Gangadharan, Lata & Harrison, Glenn W. & Leroux, Anke D., 2019. "Are risks over multiple attributes traded off? A case study of aid," Journal of Economic Behavior & Organization, Elsevier, vol. 164(C), pages 166-198.
    6. Ludger Wößmann & Vera Freundl & Elisabeth Grewenig & Philipp Lergetporer & Katharina Werner, 2020. "Deutsche sind für mehr Einheitlichkeit und Vergleichbarkeit im Bildungssystem – Ergebnisse des ifo Bildungsbarometers 2020," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 73(09), pages 40-48, September.
    7. Grewenig, Elisabeth & Lergetporer, Philipp & Werner, Katharina & Woessmann, Ludger, 2022. "Incentives, search engines, and the elicitation of subjective beliefs: Evidence from representative online survey experiments," Journal of Econometrics, Elsevier, vol. 231(1), pages 304-326.
    8. Cattaneo, Maria & Lergetporer, Philipp & Schwerdt, Guido & Werner, Katharina & Woessmann, Ludger & Wolter, Stefan C., 2020. "Information provision and preferences for education spending: Evidence from representative survey experiments in three countries," European Journal of Political Economy, Elsevier, vol. 63(C).
    9. Starkov, Egor, 2023. "Only time will tell: Credible dynamic signaling," Journal of Mathematical Economics, Elsevier, vol. 109(C).
    10. Roth, Christopher & Settele, Sonja & Wohlfart, Johannes, 2022. "Beliefs about public debt and the demand for government spending," Journal of Econometrics, Elsevier, vol. 231(1), pages 165-187.
    11. Cattaneo, Cristina & Grieco, Daniela, 2021. "Turning opposition into support to immigration: The role of narratives," Journal of Economic Behavior & Organization, Elsevier, vol. 190(C), pages 785-801.
    12. Sonja Settele, 2019. "How Do Beliefs about the Gender Wage Gap Affect the Demand for Public Policy?," CEBI working paper series 19-13, University of Copenhagen. Department of Economics. The Center for Economic Behavior and Inequality (CEBI).
    13. Angerer, Silvia & Glätzle-Rützler, Daniela & Lergetporer, Philipp & Rittmannsberger, Thomas, 2023. "How does the vaccine approval procedure affect COVID-19 vaccination intentions?," European Economic Review, Elsevier, vol. 158(C).
    14. Prabatha, Tharindu & Karunathilake, Hirushie & Mohammadpour Shotorbani, Amin & Sadiq, Rehan & Hewage, Kasun, 2021. "Community-level decentralized energy system planning under uncertainty: A comparison of mathematical models for strategy development," Applied Energy, Elsevier, vol. 283(C).
    15. Lergetporer, P & Woessmann, L, 2022. "Income Contingency and the Electorates Support for Tuition," CAGE Online Working Paper Series 606, Competitive Advantage in the Global Economy (CAGE).
    16. Simon Hetland & Rasmus Søndergaard Pedersen & Anders Rahbek, 2019. "Dynamic Conditional Eigenvalue GARCH," Discussion Papers 19-13, University of Copenhagen. Department of Economics.
    17. Tiziana Carpi & Airo Hino & Stefano Maria Iacus & Giuseppe Porro, 2021. "Twitter Subjective Well-Being Indicator During COVID-19 Pandemic: A Cross-Country Comparative Study," Papers 2101.07695, arXiv.org.
    18. Elisabeth Grewenig & Philipp Lergetporer & Katharina Werner, 2020. "Gender Norms and Labor-Supply Expectations: Experimental Evidence from Adolescents," CESifo Working Paper Series 8611, CESifo.
    19. Sonja Settele, 2022. "How Do Beliefs About the Gender Wage Gap Affect the Demand for Public Policy?," ECONtribute Discussion Papers Series 179, University of Bonn and University of Cologne, Germany.
    20. Ferdi Botha & John P. New & Sonja C. New & David C. Ribar & Nicolás Salamanca, 2021. "Implications of COVID-19 labour market shocks for inequality in financial wellbeing," Journal of Population Economics, Springer;European Society for Population Economics, vol. 34(2), pages 655-689, April.
    21. Knox, Melissa A. & Oddo, Vanessa M. & Walkinshaw, Lina Pinero & Jones-Smith, Jessica, 2020. "Is the public sweet on sugary beverages? Social desirability bias and sweetened beverage taxes," Economics & Human Biology, Elsevier, vol. 38(C).
    22. Elisabeth Grewenig & Sarah Kersten & Franziska Kugler & Philipp Lergetporer & Franziska Werner & Ludger Wößmann & Katharina Werner, 2019. "Was die Deutschen über Bildungsungleichheit denken," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 72(17), August.
    23. Lergetporer, Philipp & Woessmann, Ludger, 2023. "Earnings information and public preferences for university tuition: Evidence from representative experiments," Journal of Public Economics, Elsevier, vol. 226(C).
    24. Ludger Wößmann & Vera Freundl & Elisabeth Grewenig & Philipp Lergetporer & Katharina Werner & Larissa Zierow, 2020. "Bildung in der Coronakrise: Wie haben die Schulkinder die Zeit der Schulschließungen verbracht, und welche Bildungsmaßnahmen befürworten die Deutschen?," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 73(09), pages 25-39, September.
    25. Sonja Settele & Cortnie Shupe, 2020. "Lives or Livelihoods? Perceived Tradeoffs and Public Demand for Non-Pharmaceutical Interventions," CEBI working paper series 20-17, University of Copenhagen. Department of Economics. The Center for Economic Behavior and Inequality (CEBI).

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    More about this item

    Keywords

    online survey; representativeness; mode effects; offliner; public opinion;
    All these keywords.

    JEL classification:

    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • I20 - Health, Education, and Welfare - - Education - - - General

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