Approximate Expected Utility Rationalization
We propose a new measure of deviations from expected utility, given data on economic choices under risk and uncertainty. In a revealed preference setup, and given a positive number e, we provide a characterization of the datasets whose deviation (in beliefs, utility, or perceived prices) is within e of expected utility theory. The number e can then be used as a distance to the theory. We apply our methodology to three recent large-scale experiments. Many subjects in those experiments are consistent with utility aximization, but not expected utility maximization. The correlation of our measure with demographics is also interesting, and provides new and intuitive findings on expected utility.
We are very grateful to Nicola Persico, who posed questions to us that led to some of the results in this paper, and to Dan Friedman and Yves Le Yaouanq for very helpful comments on an early draft. This research is supported by Grant SES1558757 from the National Science Foundation. Echenique also thanks the NSF for its support through the grant CNS-1518941.
Accepted Version - sswp1441.pdf