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Dynamics of inductive inference in a unified framework

Author

Listed:
  • Itzhak Gilboa

    (GREGH - Groupement de Recherche et d'Etudes en Gestion à HEC - HEC Paris - Ecole des Hautes Etudes Commerciales - CNRS - Centre National de la Recherche Scientifique, TAU - Tel Aviv University)

  • Larry Samuelson

    (Department of Economics - Yale University [New Haven])

  • David Schmeidler

    (TAU - Tel Aviv University, OSU - The Ohio State University [Columbus])

Abstract

We present a model of inductive inference that includes, as special cases, Bayesian reasoning, case-based reasoning, and rule-based reasoning. This unified framework allows us to examine how the various modes of inductive inference can be combined and how their relative weights change endogenously. For example, we establish conditions under which an agent who does not know the structure of the data generating process will decrease, over the course of her reasoning, the weight of credence put on Bayesian vs. non-Bayesian reasoning. We illustrate circumstances under which probabilistic models are used until an unexpected outcome occurs, whereupon the agent resorts to more basic reasoning techniques, such as case-based and rule-based reasoning, until enough data are gathered to formulate a new probabilistic model.

Suggested Citation

  • Itzhak Gilboa & Larry Samuelson & David Schmeidler, 2013. "Dynamics of inductive inference in a unified framework," Post-Print hal-00836265, HAL.
    • Handle: RePEc:hal:journl:hal-00836265
    DOI: 10.1016/j.jet.2012.11.004
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    Cited by:

    1. Gilboa, Itzhak & Minardi, Stefania & Samuelson, Larry, 2020. "Theories and cases in decisions under uncertainty," Games and Economic Behavior, Elsevier, vol. 123(C), pages 22-40.
    2. John Rust, 2014. "The Limits of Inference with Theory: A Review of Wolpin (2013)," Journal of Economic Literature, American Economic Association, vol. 52(3), pages 820-850, September.
    3. Annie Liang, 2016. "Games of Incomplete Information Played by Statisticians," PIER Working Paper Archive 16-028, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 01 Jan 2016.
    4. Larbi Alaoui & Antonio Penta, 2018. "Cost-benefit analysis in reasoning," Economics Working Papers 1621, Department of Economics and Business, Universitat Pompeu Fabra.
    5. Chollete, Loran & Schmeidler, David, 2014. "Demand-Theoretic Approach to Choice of Priors," UiS Working Papers in Economics and Finance 2014/14, University of Stavanger.
    6. Gilboa, Itzhak & Samuelson, Larry & Schmeidler, David, 2022. "Learning (to disagree?) in large worlds," Journal of Economic Theory, Elsevier, vol. 199(C).
    7. Marsay, David, 2016. "Decision-making under radical uncertainty: An interpretation of Keynes' treatise," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 10, pages 1-31.

    More about this item

    Keywords

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    JEL classification:

    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty

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