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Measuring and Comparing Two Kinds of Rationalizable Opportunity Cost in Mixture Models

Department of Economics, Mail Stop 922, The University of Toledo, University Hall, Toledo, OH 43606, USA
Games 2020, 11(1), 1; https://doi.org/10.3390/g11010001
Received: 23 September 2019 / Revised: 30 October 2019 / Accepted: 4 November 2019 / Published: 19 December 2019
(This article belongs to the Special Issue The Empirics of Behaviour under Risk and Ambiguity)
In experiments of decision-making under risk, structural mixture models allow us to take a menu of theories about decision-making to the data, estimating the fraction of people who behave according to each model. While studies using mixture models typically focus only on how prevalent each of these theories is in people’s decisions, they can also be used to assess how much better this menu of theories organizes people’s utility than does just one theory on its own. I develop a framework for calculating and comparing two kinds of rationalizable opportunity cost from these mixture models. The first is associated with model mis-classification: How much worse off is a decision-maker if they are forced to behave according to model A, when they are in fact a model B type? The second relates to the mixture model’s probabilistic choice rule: How much worse off are subjects because they make probabilistic, rather than deterministic, choices? If the first quantity dominates, then one can conclude that model a constitutes an economically significant departure from model B in the utility domain. On the other hand, if the second cost dominates, then models a and B have similar utility implications. I demonstrate this framework on data from an existing experiment on decision-making under risk. View Full-Text
Keywords: mixture model; expected utility; rank dependent expected utility; rationalizable opportunity cost; absolute welfare cost mixture model; expected utility; rank dependent expected utility; rationalizable opportunity cost; absolute welfare cost
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Bland, J.R. Measuring and Comparing Two Kinds of Rationalizable Opportunity Cost in Mixture Models. Games 2020, 11, 1.

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