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On comparison of non-Bayesian experts

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  • Teper, Roee

Abstract

An expert, trying to assess the true distribution over the states of nature, is associated with a preference relation over utility bundles. He prefers f to g if he believes that, according to the true distribution, the expected utility of f is greater than that of g. Expert I is said to be more knowledgeable than expert II (Lefort, 2009) if, between the two experts, it is always beneficial to follow his advice. It is shown that if experts' maxmin preferences are induced by information consistent with the true distribution, then in most cases an expert having more information is not more knowledgeable.

Suggested Citation

  • Teper, Roee, 2010. "On comparison of non-Bayesian experts," Mathematical Social Sciences, Elsevier, vol. 60(2), pages 119-122, September.
    • Handle: RePEc:eee:matsoc:v:60:y:2010:i:2:p:119-122
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    References listed on IDEAS

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    1. Lehrer, Ehud, 1998. "Comparison of experts," Journal of Mathematical Economics, Elsevier, vol. 30(2), pages 207-214, September.
    2. Ghirardato, Paolo & Marinacci, Massimo, 2002. "Ambiguity Made Precise: A Comparative Foundation," Journal of Economic Theory, Elsevier, vol. 102(2), pages 251-289, February.
    3. Lefort, Jean-Philippe, 2009. "Guessing the beliefs," Journal of Mathematical Economics, Elsevier, vol. 45(12), pages 846-853, December.
    4. Gilboa, Itzhak & Schmeidler, David, 1989. "Maxmin expected utility with non-unique prior," Journal of Mathematical Economics, Elsevier, vol. 18(2), pages 141-153, April.
    5. repec:dau:papers:123456789/7322 is not listed on IDEAS
    6. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
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    1. Aurélien Baillon & Laure Cabantous & Peter Wakker, 2012. "Aggregating imprecise or conflicting beliefs: An experimental investigation using modern ambiguity theories," Journal of Risk and Uncertainty, Springer, vol. 44(2), pages 115-147, April.

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