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Happy times: measuring happiness using response times

Author

Listed:
  • Shuo Liu
  • Nick Netzer
Abstract
Surveys that measure subjective states like happiness or preferences often generate discrete ordinal data. Ordered response models, which are commonly used to analyze such data, suffer from a fundamental identification problem. Their conclusions depend on unjustified assumptions about the distribution of a latent variable. In this paper, we propose using survey response times to solve that problem. Response times contain information about the distribution of the latent variable even among subjects who give the same survey response, through a chronometric effect. Using an online survey, we test and verify the existence of the chronometric effect. We then provide theoretical conditions under which group differences in happiness or other variables are detectable based on response time data without making distributional assumptions. In our survey, we find evidence supporting the assumptions of traditional ordered response models for some common survey questions but not for others.

Suggested Citation

  • Shuo Liu & Nick Netzer, 2020. "Happy times: measuring happiness using response times," ECON - Working Papers 371, Department of Economics - University of Zurich, revised Mar 2023.
    • Handle: RePEc:zur:econwp:371
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    References listed on IDEAS

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    1. Oswald, Andrew J., 2008. "On the curvature of the reporting function from objective reality to subjective feelings," Economics Letters, Elsevier, vol. 100(3), pages 369-372, September.
    2. Kaiser, Caspar & Vendrik, Maarten C.M., 2020. "How threatening are transformations of happiness scales to subjective wellbeing research?," Research Memorandum 032, Maastricht University, Graduate School of Business and Economics (GSBE).
    3. Carlos Alós-Ferrer & Ernst Fehr & Nick Netzer, 2021. "Time Will Tell: Recovering Preferences When Choices Are Noisy," Journal of Political Economy, University of Chicago Press, vol. 129(6), pages 1828-1877.
    4. Stefan Boes & Rainer Winkelmann, 2006. "Ordered Response Models," Springer Books, in: Olaf Hübler & Jachim Frohn (ed.), Modern Econometric Analysis, chapter 12, pages 167-181, Springer.
    5. Betsey Stevenson & Justin Wolfers, 2008. "Economic Growth and Subjective Well-Being: Reassessing the Easterlin Paradox," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 39(1 (Spring), pages 1-102.
    6. Peter Moffatt, 2005. "Stochastic Choice and the Allocation of Cognitive Effort," Experimental Economics, Springer;Economic Science Association, vol. 8(4), pages 369-388, December.
    7. repec:cup:judgdm:v:14:y:2019:i:4:p:381-394 is not listed on IDEAS
    8. David M Kaplan & Wei Zhao, 2023. "Comparing latent inequality with ordinal data," The Econometrics Journal, Royal Economic Society, vol. 26(2), pages 189-214.
    9. Schröder, Carsten & Yitzhaki, Shlomo, 2017. "Revisiting the evidence for cardinal treatment of ordinal variables," European Economic Review, Elsevier, vol. 92(C), pages 337-358.
    10. Ilyana Kuziemko & Michael I. Norton & Emmanuel Saez & Stefanie Stantcheva, 2015. "How Elastic Are Preferences for Redistribution? Evidence from Randomized Survey Experiments," American Economic Review, American Economic Association, vol. 105(4), pages 1478-1508, April.
    11. Anja Achtziger & Carlos Alós-Ferrer, 2014. "Fast or Rational? A Response-Times Study of Bayesian Updating," Management Science, INFORMS, vol. 60(4), pages 923-938, April.
    12. Timothy N. Bond & Kevin Lang, 2013. "The Evolution of the Black-White Test Score Gap in Grades K–3: The Fragility of Results," The Review of Economics and Statistics, MIT Press, vol. 95(5), pages 1468-1479, December.
    13. Joseph K. Goodman & Gabriele Paolacci, 2017. "Crowdsourcing Consumer Research," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 44(1), pages 196-210.
    14. repec:cup:judgdm:v:5:y:2010:i:5:p:411-419 is not listed on IDEAS
    15. Christopher F. Chabris & David Laibson & Carrie L. Morris & Jonathon P. Schuldt & Dmitry Taubinsky, 2009. "The Allocation of Time in Decision-Making," Journal of the European Economic Association, MIT Press, vol. 7(2-3), pages 628-637, 04-05.
    16. Chen, Le-Yu & Oparina, Ekaterina & Powdthavee, Nattavudh & Srisuma, Sorawoot, 2022. "Robust Ranking of Happiness Outcomes: A Median Regression Perspective," Journal of Economic Behavior & Organization, Elsevier, vol. 200(C), pages 672-686.
    17. Raphael Studer & Rainer Winkelmann, 2014. "Reported Happiness, Fast and Slow," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 117(3), pages 1055-1067, July.
    18. James Andreoni & Charles Sprenger, 2012. "Risk Preferences Are Not Time Preferences," American Economic Review, American Economic Association, vol. 102(7), pages 3357-3376, December.
    19. Avoyan, Ala & Schotter, Andrew, 2020. "Attention in games: An experimental study," European Economic Review, Elsevier, vol. 124(C).
    20. Stefano DellaVigna & Devin Pope, 2018. "What Motivates Effort? Evidence and Expert Forecasts," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 85(2), pages 1029-1069.
    21. Ariel Rubinstein, 2007. "Instinctive and Cognitive Reasoning: A Study of Response Times," Economic Journal, Royal Economic Society, vol. 117(523), pages 1243-1259, October.
    22. Armin Falk & Anke Becker & Thomas Dohmen & Benjamin Enke & David B. Huffman & Uwe Sunde, 2017. "Global Evidence on Economic Preferences," NBER Working Papers 23943, National Bureau of Economic Research, Inc.
    23. Armin Falk & Anke Becker & Thomas Dohmen & Benjamin Enke & David Huffman & Uwe Sunde, 2018. "Global Evidence on Economic Preferences," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 133(4), pages 1645-1692.
    24. Sendhil Mullainathan & Marianne Bertrand, 2001. "Do People Mean What They Say? Implications for Subjective Survey Data," American Economic Review, American Economic Association, vol. 91(2), pages 67-72, May.
    25. Bryan Boulier & Robert Goldfarb, 1998. "On the use and nonuse of surveys in economics," Journal of Economic Methodology, Taylor & Francis Journals, vol. 5(1), pages 1-21.
    26. Garry F. Barrett & Stephen G. Donald, 2003. "Consistent Tests for Stochastic Dominance," Econometrica, Econometric Society, vol. 71(1), pages 71-104, January.
    27. Hess, Stephane & Stathopoulos, Amanda, 2013. "Linking response quality to survey engagement: A combined random scale and latent variable approach," Journal of choice modelling, Elsevier, vol. 7(C), pages 1-12.
    28. G. Hanoch & H. Levy, 1969. "The Efficiency Analysis of Choices Involving Risk," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 36(3), pages 335-346.
    29. Kaiser, Caspar, 2022. "Using memories to assess the intrapersonal comparability of wellbeing reports," Journal of Economic Behavior & Organization, Elsevier, vol. 193(C), pages 410-442.
    30. Easterlin, Richard A., 1974. "Does Economic Growth Improve the Human Lot? Some Empirical Evidence," MPRA Paper 111773, University Library of Munich, Germany.
    31. Ariel Rubinstein, 2016. "A Typology of Players: Between Instinctive and Contemplative," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(2), pages 859-890.
    32. Timothy N. Bond & Kevin Lang, 2019. "The Sad Truth about Happiness Scales," Journal of Political Economy, University of Chicago Press, vol. 127(4), pages 1629-1640.
    33. Clithero, John A., 2018. "Improving out-of-sample predictions using response times and a model of the decision process," Journal of Economic Behavior & Organization, Elsevier, vol. 148(C), pages 344-375.
    34. Chen, Le-Yu & Oparina, Ekaterina & Powdthavee, Nattavudh & Srisuma, Sorawoot, 2019. "Have Econometric Analyses of Happiness Data Been Futile? A Simple Truth about Happiness Scales," IZA Discussion Papers 12152, Institute of Labor Economics (IZA).
    35. Rafael Di Tella & Robert MacCulloch, 2006. "Some Uses of Happiness Data in Economics," Journal of Economic Perspectives, American Economic Association, vol. 20(1), pages 25-46, Winter.
    36. Ariel Rubinstein, 2007. "Instinctive and Cognitive Reasoning: Response Times Study," Levine's Bibliography 321307000000001011, UCLA Department of Economics.
    37. Clithero, John A., 2018. "Response times in economics: Looking through the lens of sequential sampling models," Journal of Economic Psychology, Elsevier, vol. 69(C), pages 61-86.
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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.
    2. Daniel J. Benjamin & Kristen Cooper & Ori Heffetz & Miles S. Kimball, 2023. "From Happiness Data to Economic Conclusions," NBER Working Papers 31727, National Bureau of Economic Research, Inc.
    3. 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".
    4. Penghu Zhu & Yingying Hu & Ning Zhang, 2024. "How does civilization promote happiness? Insights from the Civilized Cities Program in China," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-18, December.

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    More about this item

    Keywords

    Surveys; ordinal data; response times; non-parametric identification;
    All these keywords.

    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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