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Approximate Expected Utility Rationalization

Author

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  • Federico Echenique
  • Taisuke Imai
  • Kota Saito

Abstract

We propose a new measure of deviations from expected utility, given data on economic choices under risk and uncertainty. In a revealed preference setup, and given a positive number e, we provide a characterization of the datasets whose deviation (in beliefs, utility, or perceived prices) is within e of expected utility theory. The number e can then be used as a distance to the theory. We apply our methodology to three recent large-scale experiments. Many subjects in those experiments are consistent with utility maximization, but not expected utility maximization. The correlation of our measure with demographics is also interesting, and provides new and intuitive findings on expected utility.

Suggested Citation

  • Federico Echenique & Taisuke Imai & Kota Saito, 2018. "Approximate Expected Utility Rationalization," CESifo Working Paper Series 7348, CESifo.
  • Handle: RePEc:ces:ceswps:_7348
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    References listed on IDEAS

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    1. Syngjoo Choi & Shachar Kariv & Wieland M?ller & Dan Silverman, 2014. "Who Is (More) Rational?," American Economic Review, American Economic Association, vol. 104(6), pages 1518-1550, June.
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    11. , P. & ,, 2014. "On the consistency of data with bargaining theories," Theoretical Economics, Econometric Society, vol. 9(1), January.
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    Cited by:

    1. 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.
    2. Roy Allen & John Rehbeck, 2021. "Measuring rationality: percentages vs expenditures," Theory and Decision, Springer, vol. 91(2), pages 265-277, September.
    3. Pawel Dziewulski, 2021. "A comprehensive revealed preference approach to approximate utility maximisation," Working Paper Series 0621, Department of Economics, University of Sussex Business School.
    4. 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.
    5. 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.
    6. Federico Echenique & Taisuke Imai & Kota Saito, 2019. "Decision Making under Uncertainty: An Experimental Study in Market Settings," Papers 1911.00946, arXiv.org, revised May 2021.
    7. Mia Lu & Nick Netzer, 2022. "The swaps index for consumer choice," ECON - Working Papers 418, Department of Economics - University of Zurich, revised May 2023.
    8. Ashesh Rambachan, 2022. "Identifying Prediction Mistakes in Observational Data," NBER Chapters, in: Economics of Artificial Intelligence, National Bureau of Economic Research, Inc.

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    More about this item

    Keywords

    expected utility; revealed preferences;

    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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