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A Bayesian Method for Characterizing Population Heterogeneity

Department of Economics, University of Texas at Austin, Austin, TX 78712, USA
Games 2019, 10(4), 40; https://doi.org/10.3390/g10040040
Received: 31 August 2019 / Revised: 20 September 2019 / Accepted: 25 September 2019 / Published: 9 October 2019
(This article belongs to the Special Issue The Empirics of Behaviour under Risk and Ambiguity)
A stylized fact from laboratory experiments is that there is much heterogeneity in human behavior. We present and demonstrate a computationally practical non-parametric Bayesian method for characterizing this heterogeneity. In addition, we define the concept of behaviorally distinguishable parameter vectors, and use the Bayesian posterior to say what proportion of the population lies in meaningful regions. These methods are then demonstrated using laboratory data on lottery choices and the rank-dependent expected utility model. In contrast to other analyses, we find that 79% of the subject population is not behaviorally distinguishable from the ordinary expected utility model. View Full-Text
Keywords: Bayesian methods; population heterogeneity; identifying types; behavioral distinguishability; rank-dependent expected utility Bayesian methods; population heterogeneity; identifying types; behavioral distinguishability; rank-dependent expected utility
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Stahl, D.O. A Bayesian Method for Characterizing Population Heterogeneity. Games 2019, 10, 40.

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