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Ambiguity in Individual Choice and Market Environments: On the Importance of Comparative Ignorance

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  • Jonathan E. Alevy

    (Department of Economics, University of Alaska Anchorage)

Abstract

After Ellsberg’s thought experiments brought focus to the relevance of missing information for choice, extensive efforts have been made to understand ambiguity theoretically and empirically (Ellsberg 1961). Fox and Tversky (1995) make an important contribution to understanding behavioral responses to ambiguity. In an individual choice setting they demonstrate that an aversion to ambiguous lotteries arises only when a comparison to unambiguous lotteries is available. The current study advances this literature by exploring the importance of Fox and Tversky’s finding for market outcomes and finds support for their Comparative Ignorance Hypothesis in the market setting.

Suggested Citation

  • Jonathan E. Alevy, 2011. "Ambiguity in Individual Choice and Market Environments: On the Importance of Comparative Ignorance," Working Papers 2011-04, University of Alaska Anchorage, Department of Economics.
    • Handle: RePEc:ala:wpaper:2011-04
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    File URL: http://www.econpapers.uaa.alaska.edu/RePEC/ala/wpaper/ALA201104.pdf
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    References listed on IDEAS

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    Cited by:

    1. Qiu, Jianying & Weitzel, Utz, 2011. "Reference dependent ambiguity aversion: theory and experiment," MPRA Paper 35289, University Library of Munich, Germany, revised 08 Dec 2011.
    2. John Griffin, 2015. "Risk Premia and Knightian Uncertainty in an Experimental Market Featuring a Long-Lived Asset," Fordham Economics Discussion Paper Series dp2015-01er:dp2015-01, Fordham University, Department of Economics.
    3. John Griffin, 2015. "Risk Premia and Knightian Uncertainty in an Experimental Market Featuring a Long-Lived Asset," Fordham Economics Discussion Paper Series dp2015-01, Fordham University, Department of Economics.

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    More about this item

    Keywords

    ambiguity; asset market experiment; comparitive ignorance;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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