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Objective and subjective foundations for multiple priors

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  • Stinchcombe, Maxwell B.

Abstract

Foundations for priors can be grouped in two broad categories: objective, deriving probabilities from observations of similar instances; and subjective, deriving probabilities from the internal consistency of choices. Partial observations of similar instances and the Savage–de Finetti extensions of subjective priors yield objective and subjective sets of priors suitable for modeling choice under ambiguity. These sets are best suited to such modeling when the distribution of the observables, or the prior to be extended, is non-atomic. In this case, the sets can be used to model choices between elements of the closed convex hull of the faces in the set of distributions over outcomes, equivalently, all sets bracketed by the upper and lower probabilities induced by correspondences.

Suggested Citation

  • Stinchcombe, Maxwell B., 2016. "Objective and subjective foundations for multiple priors," Journal of Economic Theory, Elsevier, vol. 165(C), pages 263-291.
  • Handle: RePEc:eee:jetheo:v:165:y:2016:i:c:p:263-291
    DOI: 10.1016/j.jet.2016.04.011
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    References listed on IDEAS

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    1. Maxwell B. Stinchcombe & Halbert White, 1992. "Some Measurability Results for Extrema of Random Functions Over Random Sets," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 59(3), pages 495-514.
    2. Nabil I. Al-Najjar, 2009. "Decision Makers as Statisticians: Diversity, Ambiguity, and Learning," Econometrica, Econometric Society, vol. 77(5), pages 1371-1401, September.
    3. Gilboa, Itzhak & Schmeidler, David, 1989. "Maxmin expected utility with non-unique prior," Journal of Mathematical Economics, Elsevier, vol. 18(2), pages 141-153, April.
    4. Stinchcombe, Maxwell B., 1990. "Bayesian information topologies," Journal of Mathematical Economics, Elsevier, vol. 19(3), pages 233-253.
    5. Ghirardato, Paolo & Maccheroni, Fabio & Marinacci, Massimo, 2004. "Differentiating ambiguity and ambiguity attitude," Journal of Economic Theory, Elsevier, vol. 118(2), pages 133-173, October.
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    Cited by:

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    2. David McCarthy & Kalle Mikkola & Teruji Thomas, 2019. "Aggregation for potentially infinite populations without continuity or completeness," Papers 1911.00872, arXiv.org.

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    More about this item

    Keywords

    Multiple prior models and ambiguous choice; Partial observability and partially identified models; Finitely additive learning models; Savage–de Finetti indeterminacy; Dempster compatible sets of probabilities; Difficulty of learning problems;
    All these keywords.

    JEL classification:

    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics

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