Assessing multiple prior models of behaviour under ambiguity

Anna Conte and John Hey

Journal of Risk and Uncertainty, 2013, vol. 46, issue 2, 113-132

Abstract: The recent spate of theoretical models of behaviour under ambiguity can be partitioned into two sets: those involving multiple priors and those not involving multiple priors. This paper provides an experimental investigation into the first set. Using an appropriate experimental interface we examine the fitted and predictive power of the various theories. We first estimate subject-by-subject, and then estimate and predict using a mixture model over the contending theories. The individual estimates suggest that 24% of our 149 subjects have behaviour consistent with Expected Utility, 56% with the Smooth Model, 11% with Rank Dependent Expected Utility and 9% with the Alpha Model; these figures are close to the mixing proportions obtained from the mixture estimates where the respective posterior probabilities of each of them being of the various types are 25%, 50%, 20% and 5%; and using the predictions 22%, 53%, 22% and 3%. The Smooth model appears the best. Copyright Springer Science+Business Media New York 2013

Keywords: Alpha model; Ambiguity; Expected utility; Mixture models; Rank dependent expected utility; Smooth model; D81; C91; C23 (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (32)

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Related works:
Chapter: Assessing multiple prior models of behaviour under ambiguity (2018)
Working Paper: Assessing Multiple Prior Models of Behaviour under Ambiguity (2012)
Working Paper: Assessing Multiple Prior Models of Behaviour under Ambiguity (2012)
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DOI: 10.1007/s11166-013-9164-x

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