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Eliciting ambiguity aversion in unknown and in compound lotteries: A KMM experimental approach

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  • Attanasi, Giuseppe Marco
  • Gollier, Christian
  • Montesano, Aldo
  • Pace, Noémie
Abstract
We define coherent-ambiguity aversion within the Klibanoff, Marinacci and Mukerji (2005) smooth ambiguity model (henceforth KMM) as the combination of choice-ambiguity aversion and value-ambiguity aversion. We analyze theoretically five ambiguous decision tasks, where a subject faces two-stage lotteries with binomial, uniform or unknown second-order probabilities. We check our theoretical predictions through a 10-task laboratory experiment. In (unambiguous) tasks 1-5, we elicit risk aversion both through a portfolio choice method and through a BDM mechanism. In (ambiguous) tasks 6-10, we elicit choice-ambiguity aversion through the portfolio choice method and value-ambiguity aversion through the BDM mechanism. We find that more than 75% of classified subjects behave according to the KMM model in all tasks 6-10, independent of their degree of risk aversion. Further, the percentage of coherently-ambiguity-averse subjects is lower in the binomial than in the uniform and in the unknown treatment, with only the latter difference being significant. Finally, highly-risk-averse subjects are more prone to coherent-ambiguity.
(This abstract was borrowed from another version of this item.)

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  • Attanasi, Giuseppe Marco & Gollier, Christian & Montesano, Aldo & Pace, Noémie, 2012. "Eliciting ambiguity aversion in unknown and in compound lotteries: A KMM experimental approach," IDEI Working Papers 744, Institut d'Économie Industrielle (IDEI), Toulouse.
    • Handle: RePEc:ide:wpaper:26341
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    More about this item

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

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