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Upper and lower bounds for expected utility

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  • Marco LiCalzi

Abstract

The decision-theoretic literature has developed very few techniques to bound the expected utility of a random variable when only simple statistics like its median or mode or mean are known. One reason for this lack of results is that we are missing a convenient way to link probability theory and expected utility. This paper is written to demonstrate a general (and genuinely probabilistic) technique to obtain upper and lower bounds for the expected utility of a lottery. Copyright Springer-Verlag Berlin Heidelberg 2000

Suggested Citation

  • Marco LiCalzi, 2000. "Upper and lower bounds for expected utility," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 16(2), pages 489-502, September.
    • Handle: RePEc:spr:joecth:v:16:y:2000:i:2:p:489-502
    DOI: 10.1007/s00199-000-0001-5
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    Cited by:

    1. James Cox & Vjollca Sadiraj & Bodo Vogt & Utteeyo Dasgupta, 2013. "Is there a plausible theory for decision under risk? A dual calibration critique," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 54(2), pages 305-333, October.
    2. Marco LiCalzi, 2005. "A language for the construction of preferences under uncertainty," Game Theory and Information 0509002, University Library of Munich, Germany.
    3. Eduardo Zambrano, 2008. "Expected utility inequalities: theory and applications," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 36(1), pages 147-158, July.
    4. Ioana Popescu, 2005. "A Semidefinite Programming Approach to Optimal-Moment Bounds for Convex Classes of Distributions," Mathematics of Operations Research, INFORMS, vol. 30(3), pages 632-657, August.

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