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Experiments on Decisions under Uncertainty: A Theoretical Framework

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  • Eran Shmaya
  • Leeat Yariv

Abstract

The analysis of lab data entails a joint test of the underlying theory and of subjects' conjectures regarding the experimental design itself, how subjects frame the experiment. We provide a theoretical framework for analyzing such conjectures. We use experiments of decision making under uncertainty as a case study. Absent restrictions on subjects' framing of the experiment, we show that any behavior is consistent with standard updating ("anything goes"), including those suggestive of anomalies such as overconfidence, excess belief stickiness, etc. When the experimental protocol restricts subjects' conjectures (plausibly, by generating information during the experiment), standard updating has nontrivial testable implications.

Suggested Citation

  • Eran Shmaya & Leeat Yariv, 2016. "Experiments on Decisions under Uncertainty: A Theoretical Framework," American Economic Review, American Economic Association, vol. 106(7), pages 1775-1801, July.
    • Handle: RePEc:aea:aecrev:v:106:y:2016:i:7:p:1775-1801
    Note: DOI: 10.1257/aer.20120978
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    References listed on IDEAS

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    1. Brocas, Isabelle & Carrillo, Juan D. (ed.), 2003. "The Psychology of Economic Decisions: Volume One: Rationality and Well-Being," OUP Catalogue, Oxford University Press, number 9780199251087, Decembrie.
    2. Bikhchandani, Sushil & Hirshleifer, David & Welch, Ivo, 1992. "A Theory of Fads, Fashion, Custom, and Cultural Change in Informational Cascades," Journal of Political Economy, University of Chicago Press, vol. 100(5), pages 992-1026, October.
    3. Green, Edward J. & Park, In-Uck, 1996. "Bayes contingent plans," Journal of Economic Behavior & Organization, Elsevier, vol. 31(2), pages 225-236, November.
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    Cited by:

    1. J. Aislinn Bohren & Daniel N. Hauser, 2023. "Behavioral Foundations of Model Misspecification," PIER Working Paper Archive 23-007, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    2. Jonathan de Quidt & Johannes Haushofer & Christopher Roth, 2018. "Measuring and Bounding Experimenter Demand," American Economic Review, American Economic Association, vol. 108(11), pages 3266-3302, November.
    3. Hoeft, Leonard & Kurschilgen, Michael & Mill, Wladislaw, 2025. "Norms as obligations," International Review of Law and Economics, Elsevier, vol. 81(C).
    4. Daniele Vignoli & Raffaele Guetto & Giacomo Bazzani & Elena Pirani & Alessandra Minello, 2020. "Economic Uncertainty and Fertility in Europe: Narratives of the Future," Econometrics Working Papers Archive 2020_01, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    5. Gilboa, Itzhak & Wang, Fan, 2019. "Rational status quo," Journal of Economic Theory, Elsevier, vol. 181(C), pages 289-308.
    6. Arieli, Itai & Babichenko, Yakov, 2024. "A population's feasible posterior beliefs," Journal of Economic Theory, Elsevier, vol. 215(C).
    7. Kuzmics, Christoph, 2017. "Abraham Wald's complete class theorem and Knightian uncertainty," Games and Economic Behavior, Elsevier, vol. 104(C), pages 666-673.
    8. Piermont, Evan, 2017. "Context dependent beliefs," Journal of Mathematical Economics, Elsevier, vol. 71(C), pages 63-73.

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    More about this item

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D11 - Microeconomics - - Household Behavior - - - Consumer Economics: Theory
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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