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Coping With Ignorance: Unforeseen Contingencies and Non-Additive Uncertainty

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  • Ghirardato, Paolo

Abstract

In real-life decision problems, decision makers are never provided with the necessary background structure: the set of states of the world, the outcome space, the set of actions. They have to devise all these by themselves. I model the (static) choice problem of a decision maker (DM) who is aware that her perception of the decision problem is too coarse, as for instance when there might be unforeseen contingencies. I make a "bounded rationality'' assumption on the way the DM deals with this difficulty, and then I show that imposing standard subjective expected utility axioms on her preferences only implies that they can be represented by a (generalized) expectation with respect to a non-additive measure, called a belief function. However, the axioms do have strong implications for how the DM copes with the type of ignorance described above. Finally, I show that some decision rules that have been studied in the literature can be obtained as a special case of the model presented here (though they have to be interpreted differently).
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Ghirardato, Paolo, 1996. "Coping With Ignorance: Unforeseen Contingencies and Non-Additive Uncertainty," Working Papers 945, California Institute of Technology, Division of the Humanities and Social Sciences.
    • Handle: RePEc:clt:sswopa:945
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    File URL: http://www.hss.caltech.edu/SSPapers/sswp945.pdf
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    Cited by:

    1. Youichiro Higashi & Kazuya Hyogo, 2012. "Lexicographic expected utility with a subjective state space," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 49(1), pages 175-192, January.
    2. Galanis, Spyros, 2007. "Unawareness of theorems," Discussion Paper Series In Economics And Econometrics 51816, Economics Division, School of Social Sciences, University of Southampton.
    3. Peter Wakker, 2011. "Jaffray’s ideas on ambiguity," Theory and Decision, Springer, vol. 71(1), pages 11-22, July.
    4. Hiroyuki Nakata, 2011. "Equivalent comparisons of information channels," Theory and Decision, Springer, vol. 71(4), pages 559-574, October.
    5. Luca Rigotti & Matthew Ryan & Rhema Vaithianathan, 2011. "Optimism and firm formation," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 46(1), pages 1-38, January.
    6. Vassili Vergopoulos, 2011. "Dynamic consistency for non-expected utility preferences," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 48(2), pages 493-518, October.
    7. Jean-Yves Jaffray & Meglena Jeleva, 2011. "How to deal with partially analyzable acts?," Theory and Decision, Springer, vol. 71(1), pages 129-149, July.
    8. Nabil I. Al-Najjar & Luciano De Castro, 2010. "Uncertainty, Efficiency and Incentive Compatibility," Discussion Papers 1532, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
    9. Jürgen Eichberger & David Kelsey, 1999. "E-Capacities and the Ellsberg Paradox," Theory and Decision, Springer, vol. 46(2), pages 107-138, April.

    More about this item

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • L22 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Organization and Market Structure

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