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Happy Times: Measuring Happiness Using Response Times

Author

Listed:
  • Shuo Liu
  • Nick Netzer

Abstract

Surveys measuring happiness or preferences generate discrete ordinal data. Ordered response models, which are used to analyze such data, suffer from an identification problem. Their conclusions depend on distributional assumptions about a latent variable. We propose using response times to solve that problem. Response times contain information about the distribution of the latent variable through a chronometric effect. Using an online survey experiment, we verify the chronometric effect. We then provide theoretical conditions for testing conventional distributional assumptions. These assumptions are rejected in some cases, but overall our evidence is consistent with the qualitative validity of the conventional models.

Suggested Citation

  • Shuo Liu & Nick Netzer, 2023. "Happy Times: Measuring Happiness Using Response Times," American Economic Review, American Economic Association, vol. 113(12), pages 3289-3322, December.
    • Handle: RePEc:aea:aecrev:v:113:y:2023:i:12:p:3289-3322
    DOI: 10.1257/aer.20211051
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    Cited by:

    1. Jean-Michel Benkert & Shuo Liu & Nick Netzer, 2024. "Time is Knowledge: What Response Times Reveal," Papers 2408.14872, arXiv.org, revised Feb 2026.
    2. Francesco Berlingieri & Matija Kovacic, 2025. "Health and relationship quality of sexual minorities in Europe," Journal of Population Economics, Springer;European Society for Population Economics, vol. 38(1), pages 1-39, March.
    3. Thomas Demuynck & León Hennen, 2026. "The Hyperplane Model of Survey Response," Working Papers ECARES 2026-04, ULB -- Universite Libre de Bruxelles.
    4. Daniel J. Benjamin & Kristen Cooper & Ori Heffetz & Miles Kimball, 2024. "From Happiness Data to Economic Conclusions," Annual Review of Economics, Annual Reviews, vol. 16(1), pages 359-391, August.
    5. Francesco Berlingieri & Matija Kovacic, 2023. "Health and relationship quality of the LGBTQIA+ population in Europe," Working Papers 2023: 29, Department of Economics, University of Venice "Ca' Foscari".
    6. Matija Kovacic & Cristina Elisa Orso, 2025. "Wounds of the past, screens of the present: how childhood adversities shape social media behaviours in adulthood," Review of Economics of the Household, Springer, vol. 23(4), pages 1323-1369, December.
    7. Garagnani, Michele & Schweinhardt, Petra & Tobler, Philippe N. & Alós-Ferrer, Carlos, 2025. "Improving numerical measures of human feelings: The case of pain," Social Science & Medicine, Elsevier, vol. 384(C).
    8. Carlos Alos Ferrer & Michele Garagnani, 2025. "Who Likes It More?," Working Papers 424225030, Lancaster University Management School, Economics Department.
    9. Penghu Zhu & Yingying Hu & Ning Zhang, 2024. "How does civilization promote happiness? Insights from the Civilized Cities Program in China," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 11(1), pages 1-18, December.

    More about this item

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • D60 - Microeconomics - - Welfare Economics - - - General
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being

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