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An axiomatic approach to $\boldsymbol{\varepsilon}$ -contamination

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  • Kiyohiko Nishimura
  • Hiroyuki Ozaki

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Abstract

Suppose that an economic agent is $(1-\varepsilon) \times$ 100% certain that uncertainty she faces is characterized by a particular probability measure, but that she has a fear that, with $\varepsilon \times$ 100% chance, her conviction is completely wrong and she is left perfectly ignorant about the true measure in the present as well as in the future. This situation is often called “ $\varepsilon$ -contamination of confidence.” The purpose of this paper is to provide a simple set of behavioral axioms under which the decision-maker’s preference is represented by the Choquet expected utility with the $\varepsilon$ -contamination of confidence. Copyright Springer-Verlag Berlin/Heidelberg 2006

Suggested Citation

  • Kiyohiko Nishimura & Hiroyuki Ozaki, 2006. "An axiomatic approach to $\boldsymbol{\varepsilon}$ -contamination," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 27(2), pages 333-340, January.
  • Handle: RePEc:spr:joecth:v:27:y:2006:i:2:p:333-340
    DOI: 10.1007/s00199-004-0584-3
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    Citations

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    Cited by:

    1. Igor Kopylov, 2016. "Subjective probability, confidence, and Bayesian updating," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 62(4), pages 635-658, October.
    2. Soren Christensen & Luis H. R. Alvarez E, 2019. "A Solvable Two-dimensional Optimal Stopping Problem in the Presence of Ambiguity," Papers 1905.05429, arXiv.org.
    3. repec:spr:joecth:v:65:y:2018:i:3:d:10.1007_s00199-016-1025-9 is not listed on IDEAS
    4. Marcello Basili & Carlo Zappia, 2018. "Ellsberg’s Decision Rules and Keynes’s Long-Term Expectations," Department of Economics University of Siena 777, Department of Economics, University of Siena.
    5. Luis H. R. Alvarez E. & Soren Christensen, 2019. "A Class of Solvable Multidimensional Stopping Problems in the Presence of Knightian Uncertainty," Papers 1907.04046, arXiv.org.

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