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Assessing Multiple Prior Models of Behaviour under Ambiguity

Author

Listed:
  • Anna Conte
  • John D. Hey
Abstract
The recent spate of theoretical models of behaviour under ambiguity can be partitioned into two sets: those involving multiple priors (in which the probabilities of the various events are not known but probabilities can be attached to the various possible values for the probabilities) and those not involving multiple priors. This paper concentrates on the first set and provides an experimental investigation into recently proposed theories. Using an appropriate experimental interface, in which the probabilities on the various possibilities are explicitly stated, we examine the fitted and predictive power of the various theories. We first estimate subject-by-subject, and then we estimateand predict using a mixture model over the contending theories. The individual estimates suggest that 25% of our 149 subjects have behaviour consistent with Expected Utility, 54% with the Smooth Model (of Klibanoff et al, 2005), 12% with Rank Dependent Expected Utility and 9% with the Alpha Model (of Ghirardato et al 2004); these figures are very close to the mixing proportions obtained from the mixture estimates. However, if we classify our subjects through the posterior probabilities (given all the evidence) of each of them being of the various types: using the estimates we get 38%, 19%, 28% and 16% (for EU, Smooth, Rank Dependent and Alpha); while using the predictions 36%, 19%, 33% and 11%. Interestingly the older models (EU and RD) seem to fare relatively better, suggesting that representing ambiguity through multiple priors is perceived by subjects as risk, rather than ambiguity

Suggested Citation

  • Anna Conte & John D. Hey, 2012. "Assessing Multiple Prior Models of Behaviour under Ambiguity," Discussion Papers 12/01, Department of Economics, University of York.
    • Handle: RePEc:yor:yorken:12/01
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    More about this item

    Keywords

    Alpha Model; Ambiguity; Expected Utility; Mixture Models; Rank Dependent Expected Utility; Smooth Model.;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables

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