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A repeated-choice foundation for stochastic choice

Author

Listed:
  • Lu, Jay

    (Department of Economics, University of California, Los Angeles)

  • Saito, Kota

    (Division of the Humanities and Social Sciences, California Institute of Technology)

Abstract

We characterize when an agent’s observed stochastic choice can be represented as a limit frequency of optimal choices over time. In our model, an agent repeatedly chooses among risky prospects aware that future preferences will evolve according to a subjective ergodic utility process. We show that the parameters of the model can be uniquely identified and provide a complete characterization. As part of our axiomatization, we extend the representation theorems of Gul and Pesendorfer (2006) and Dekel et al. (2001, 2007) to an infinite-dimensional space with countably-additive probability measures. This is accomplished through a unified methodology based on Lipschitz continuous utilities.

Suggested Citation

  • Lu, Jay & Saito, Kota, 0. "A repeated-choice foundation for stochastic choice," Theoretical Economics, Econometric Society.
    • Handle: RePEc:the:publsh:6597
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    References listed on IDEAS

    as
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    4. Larry G. Epstein & Stanley E. Zin, 2013. "Substitution, risk aversion and the temporal behavior of consumption and asset returns: A theoretical framework," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 12, pages 207-239, World Scientific Publishing Co. Pte. Ltd..
    5. Dillenberger, David & Lleras, Juan Sebastián & Sadowski, Philipp & Takeoka, Norio, 2014. "A theory of subjective learning," Journal of Economic Theory, Elsevier, vol. 153(C), pages 287-312.
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    Cited by:

    1. G. Charles-Cadogan, 2026. "Local Expected Utility in Infinite-Dimensional Spaces: Theory and Elicitation," Papers 2609.25026, arXiv.org, revised Oct 2026.

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    Keywords

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    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General

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