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Least convex capacities

Author

Listed:
  • Larry G. Epstein

    () (Department of Economics, University of Rochester, Harkness Hall, Rochester, NY 14627-0156, USA)

  • Jiankang Zhang

    () (Department of Economics, University of Rochester, Harkness Hall, Rochester, NY 14627-0156, USA)

Abstract

Debreu proposed the notion of `least concave utility' as a way to disentangle risk attitudes from the certainty preferences embedded in a von-Neumann Morgenstern index. This paper studies preferences under uncertainty, as opposed to risk, and examines a corresponding decomposition of preference. The analysis is carried out within the Choquet expected utility model of preference and is centered on the notion of a least convex capacity.

Suggested Citation

  • Larry G. Epstein & Jiankang Zhang, 1999. "Least convex capacities," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 13(2), pages 263-286.
  • Handle: RePEc:spr:joecth:v:13:y:1999:i:2:p:263-286
    Note: Received: May 7, 1997; revised version: November 5, 1997
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    Citations

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    Cited by:

    1. Kin Chung Lo, 1998. "Epistemic Conditions for Agreement and Stochastic Independence of epsilon-Contaminated Beliefs," Working Papers 1998_02, York University, Department of Economics.
    2. Takao Asano, 2004. "Portfolio Inertia under Ambiguity," ISER Discussion Paper 0609, Institute of Social and Economic Research, Osaka University.
    3. Nishimura, Kiyohiko G. & Ozaki, Hiroyuki, 2004. "Search and Knightian uncertainty," Journal of Economic Theory, Elsevier, vol. 119(2), pages 299-333, December.

    More about this item

    Keywords

    Uncertainty · Uncertainty aversion · Choquet expected utility · Capacity · Convex capacity · Risk aversion · Ambiguity · Non-additive probability.;

    JEL classification:

    • C69 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Other
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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