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Eliciting People's First-Order Concerns: Text Analysis of Open-Ended Survey Questions

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  • Beatrice Ferrario
  • Stefanie Stantcheva

Abstract

This paper illustrates the design and use of open-ended survey questions as a way of eliciting people's first-order concerns on policies. Multiple choice questions are the backbone of most surveys, but they may prime respondents to select answer options that they would not naturally have thought about, and they may omit relevant options. Open-ended questions that do not constrain respondents with specific answer choices are a valuable tool for eliciting first-order thinking. We discuss three text analysis methods to analyze open-ended questions' answers. To illustrate how to apply these methods, we provide evidence from large-scale surveys on income and estate taxation. We show the that key concerns relate mostly to distribution issues, fairness, and government, rather than to efficiency concerns. There are large partisan gaps in the first-order concerns on policies.

Suggested Citation

  • Beatrice Ferrario & Stefanie Stantcheva, 2022. "Eliciting People's First-Order Concerns: Text Analysis of Open-Ended Survey Questions," NBER Working Papers 29686, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:29686
    Note: EFG LS PE POL
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    References listed on IDEAS

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    1. Stefanie Stantcheva, 2021. "Understanding Tax Policy: How do People Reason?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 136(4), pages 2309-2369.
    2. Matthew Gentzkow & Jesse M. Shapiro, 2010. "What Drives Media Slant? Evidence From U.S. Daily Newspapers," Econometrica, Econometric Society, vol. 78(1), pages 35-71, January.
    3. Margaret E. Roberts & Brandon M. Stewart & Dustin Tingley & Christopher Lucas & Jetson Leder‐Luis & Shana Kushner Gadarian & Bethany Albertson & David G. Rand, 2014. "Structural Topic Models for Open‐Ended Survey Responses," American Journal of Political Science, John Wiley & Sons, vol. 58(4), pages 1064-1082, October.
    4. Scott Deerwester & Susan T. Dumais & George W. Furnas & Thomas K. Landauer & Richard Harshman, 1990. "Indexing by latent semantic analysis," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 41(6), pages 391-407, September.
    5. Margaret Roberts & Brandon Stewart & Tingley, Dustin & Edoardo Airoldi, 2013. "The structural topic model and applied social science," Working Paper 132666, Harvard University OpenScholar.
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    Citations

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    Cited by:

    1. Demgensky, Lisa & Fritsche, Ulrich, 2023. "Narratives on the causes of inflation in Germany: First results of a pilot study," WiSo-HH Working Paper Series 77, University of Hamburg, Faculty of Business, Economics and Social Sciences, WISO Research Laboratory.
    2. Filippini, Massimo & Leippold, Markus & Wekhof, Tobias, 2024. "Sustainable finance literacy and the determinants of sustainable investing," Journal of Banking & Finance, Elsevier, vol. 163(C).
    3. Sebastian Link & Andreas Peichl & Christopher Roth & Johannes Wohlfart, 2023. "Attention to the Macroeconomy," ECONtribute Discussion Papers Series 256, University of Bonn and University of Cologne, Germany.
    4. Jiang, Lingqing & Zhu, Zhen, 2022. "Information exchange and multiple peer groups: A natural experiment in an online community," Journal of Economic Behavior & Organization, Elsevier, vol. 203(C), pages 543-562.
    5. Burgstaller, Lilith & Pfeil, Katharina, 2024. "You don’t need an invoice, do you? An online experiment on collaborative tax evasion," Journal of Economic Psychology, Elsevier, vol. 101(C).
    6. An, Zidong & Binder, Carola & Sheng, Xuguang Simon, 2023. "Gas price expectations of Chinese households," Energy Economics, Elsevier, vol. 120(C).
    7. Jordi Brandts & Francesc Trillas, 2024. "Opposing Views on Public Ownership and Their Influence on Citizens’ Attitudes," Working Papers 1453, Barcelona School of Economics.
    8. Conti, Gabriella & Giannola, Michele & Toppeta, Alessandro, 2022. "Parental Beliefs, Perceived Health Risks, and Time Investment in Children: Evidence from COVID-19," IZA Discussion Papers 15765, Institute of Labor Economics (IZA).
    9. Tobias Wekhof & Sébastien Houde, 2023. "Using narratives to infer preferences in understanding the energy efficiency gap," Nature Energy, Nature, vol. 8(9), pages 965-977, September.
    10. Fabienne Cantner & Geske Rolvering, 2022. "Does information help to overcome public resistance to carbon prices? Evidence from an information provision experiment," Working Papers 219, Bavarian Graduate Program in Economics (BGPE).
    11. Quentin Lippmann & Khushboo Surana, 2022. "The Hierarchy of Partner Preferences," Discussion Papers 22/08, Department of Economics, University of York.
    12. Tobias König & Renke Schmacker, 2022. "Preferences for Sin Taxes," CESifo Working Paper Series 10046, CESifo.

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    More about this item

    JEL classification:

    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • H1 - Public Economics - - Structure and Scope of Government
    • H2 - Public Economics - - Taxation, Subsidies, and Revenue

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