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New Perspectives on Statistical Decisions Under Ambiguity

Author

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  • Jörg Stoye

    () (Department of Economics, Cornell University, Ithaca, New York 14853)

Abstract

This review summarizes and connects recent work on the foundations and applications of statistical decision theory. Minimax models of decisions making under ambiguity are identified as a thread running through several literatures. In axiomatic decision theory, these models motivated a large literature on modeling ambiguity aversion. Some findings of this literature are reported in a way that should be directly accessible to statisticians and econometricians. In statistical decision theory, the models inform a rich theory of estimation and treatment choice, which was recently extended to account for partial identification and thereby ambiguity that does not vanish with sample size. This literature is illustrated by discussing global, finite-sample admissible, and minimax decision rules for a number of stylized decision problems with point and partial identification.

Suggested Citation

  • Jörg Stoye, 2012. "New Perspectives on Statistical Decisions Under Ambiguity," Annual Review of Economics, Annual Reviews, vol. 4(1), pages 257-282, July.
  • Handle: RePEc:anr:reveco:v:4:y:2012:p:257-282
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    File URL: http://www.annualreviews.org/doi/abs/10.1146/annurev-economics-080511-110959
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    Citations

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    Cited by:

    1. Stoye, Jörg, 2015. "Choice theory when agents can randomize," Journal of Economic Theory, Elsevier, vol. 155(C), pages 131-151.
    2. repec:kap:enreec:v:68:y:2017:i:4:d:10.1007_s10640-016-0062-y is not listed on IDEAS
    3. Gabriel Carroll, 2015. "Robustness and Linear Contracts," American Economic Review, American Economic Association, vol. 105(2), pages 536-563, February.
    4. Tamini, Lota Dabio, 2012. "Optimal quality choice under uncertainty on market development," Working Papers 148589, Structure and Performance of Agriculture and Agri-products Industry (SPAA).
    5. Tamini, Lota D., 2012. "Optimal quality choice under uncertainty on market development," MPRA Paper 40845, University Library of Munich, Germany.
    6. Liao, Yuan & Simoni, Anna, 2012. "Semi-parametric Bayesian Partially Identified Models based on Support Function," MPRA Paper 43262, University Library of Munich, Germany.
    7. repec:bos:wpaper:wp2013-001 is not listed on IDEAS

    More about this item

    Keywords

    statistical decision theory; minimax; minimax regret; treatment choice; partial identification;

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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