Assessing multiple prior models of behaviour under ambiguity
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Assessing multiple prior models of behaviour under ambiguity Anna Conte & John D. Hey
Published online: 28 March 2013 # Springer Science+Business Media New York 2013
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. Keywords Alpha model . Ambiguity . Expected utility . Mixture models . Rank dependent expected utility . Smooth model JEL Classification D81 . C91 . C23 Ambiguity differs from risk in that, under ambiguity, events are not certain but probabilities are not known. Over the past few years, and intensively so recently, The authors would like to thank an anonymous referee for very helpful and sympathetic comments which led to significant improvements in the paper. J. D. Hey (*) Department of Economics and Related Studies, University of York, York, UK e-mail: [email protected] A. Conte Westminster Business School, University of Westminster, London, UK A. Conte Strategic Interaction Group, Max Planck Institute of Economics, Jena, Germany
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J Risk Uncertain (2013) 46:113–132
theorists have proposed many new theories of behaviour under ambiguity. The purpose of this paper is to report on the empirical adequacy of a subset of these new theories. The subset that we concentrate on here arises naturally because of a partition of the literature. All this literature is set in the context of a single-stage decision problem where the decision-maker chooses from a set of alternative decisions, Nature chooses some outcome from a set of possible outcomes, and the decision-maker’s payoff depends on the decision and on the outcome. Ambiguity arises when the probabilities of the various outcomes are not known. Part of the ambiguity literature envisages the decision-maker as realising that he or she does not know the values of the relevant probabilities, or is not prepared to make subjective judgements about the possible probabilities; while another part envisages the decision-maker as being able to list the various possibilities for the various probabilities and, moreover, as being able to attach probabilities to the various possibilities. If you like, it is second-order probabilities, or probabilities of pro
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