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Approximate Expected Utility Rationalization

Author

Listed:
  • Federico Echenique
  • Taisuke Imai
  • Kota Saito

Abstract

We propose a new measure of deviations from expected utility theory. For any positive number e, we give a characterization of the datasets with a rationalization that is within e (in beliefs, utility, or perceived prices) of expected utility (EU) theory, under the assumption of risk aversion. The number e can then be used as a measure of how far the data is to EU theory. We apply our methodology to data from three large-scale experiments. Many subjects in these experiments are consistent with utility maximization, but not with EU maximization. Our measure of distance to expected utility is correlated with the subjects’ demographic characteristics.

Suggested Citation

  • Federico Echenique & Taisuke Imai & Kota Saito, 2023. "Approximate Expected Utility Rationalization," Journal of the European Economic Association, European Economic Association, vol. 21(5), pages 1821-1864.
    • Handle: RePEc:oup:jeurec:v:21:y:2023:i:5:p:1821-1864.
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    File URL: http://hdl.handle.net/10.1093/jeea/jvad028
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    Cited by:

    1. Yujian Chen & Joshua Lanier & John K. -H. Quah, 2024. "Goodness-of-fit and utility estimation: what's possible and what's not," Papers 2405.08464, arXiv.org, revised Feb 2026.
    2. Thomas Demuynck & John Rehbeck, 2023. "Computing revealed preference goodness-of-fit measures with integer programming," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 76(4), pages 1175-1195, November.
    3. Roy Allen & John Rehbeck, 2021. "Measuring rationality: percentages vs expenditures," Theory and Decision, Springer, vol. 91(2), pages 265-277, September.
    4. Choi, Syngjoo & Cipriani, Marco & Guarino, Antonio & Kariv, Shachar, 2025. "Douglas Gale’s contribution to social learning, decision under risk and uncertainty, monotone games and networks," Journal of Financial Intermediation, Elsevier, vol. 62(C).
    5. Dziewulski, Paweł, 2025. "A revealed preference approach to approximate utility maximisation," Journal of Economic Theory, Elsevier, vol. 228(C).
    6. Mingshi Chen & Tracy Xiao Liu & You Shan & Shu Wang & Songfa Zhong & Yanju Zhou, 2025. "How General Are Measures of Choice Consistency? Evidence from Experimental and Scanner Data," Papers 2505.05275, arXiv.org, revised Sep 2025.
    7. Pawel Dziewulski, 2021. "A comprehensive revealed preference approach to approximate utility maximisation," Working Paper Series 0621, Department of Economics, University of Sussex Business School.
    8. Thomas Demuynck & Tom Potoms, 2022. "Testing revealed preference models with unobserved randomness: a column generation approach," Working Papers ECARES 2022-42, ULB -- Universite Libre de Bruxelles.
    9. Thomas Dohmen & Georgios Gerasimou, 2025. "Learning to Maximize Ordinal and Expected Utility, and the Indifference Hypothesis," CRC TR 224 Discussion Paper Series crctr224_2025_687, University of Bonn and University of Mannheim, Germany.
    10. Echenique, Federico & Imai, Taisuke & Saito, Kota, 2019. "Decision Making under Uncertainty: An Experimental Study in Market Settings," Rationality and Competition Discussion Paper Series 197, CRC TRR 190 Rationality and Competition.
    11. Ashesh Rambachan, 2022. "Identifying Prediction Mistakes in Observational Data," NBER Chapters, in: Economics of Artificial Intelligence, National Bureau of Economic Research, Inc.
    12. Pawe{l} Dziewulski & Joshua Lanier & John K. -H. Quah, 2024. "Revealed preference and revealed preference cycles: a survey," Papers 2405.08459, arXiv.org.
    13. Yiting Chen & Tracy Xiao Liu & You Shan & Songfa Zhong, 2023. "The emergence of economic rationality of GPT," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 120(51), pages 2316205120-, December.
    14. Federico Echenique, 2020. "New Developments in Revealed Preference Theory: Decisions Under Risk, Uncertainty, and Intertemporal Choice," Annual Review of Economics, Annual Reviews, vol. 12(1), pages 299-316, August.
    15. Jeongbin Kim & Matthew Kovach & Kyu-Min Lee & Euncheol Shin & Hector Tzavellas, 2024. "Learning to be Homo Economicus: Can an LLM Learn Preferences from Choice," Papers 2401.07345, arXiv.org.
    16. Dziewulski, Paweł & Lanier, Joshua & Quah, John K.-H., 2024. "Revealed preference and revealed preference cycles: A survey," Journal of Mathematical Economics, Elsevier, vol. 113(C).
    17. Mia Lu & Nick Netzer, 2022. "The swaps index for consumer choice," ECON - Working Papers 418, Department of Economics - University of Zurich, revised May 2023.

    More about this item

    JEL classification:

    • D01 - Microeconomics - - General - - - Microeconomic Behavior: Underlying Principles
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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