A Bayesian Approach to Uncertainty Aversion
AbstractThe Ellsberg paradox demonstrates that people's belief over uncertain events might not be representable by subjective probability. We argue that Uncertainty Aversion may be viewed as a case of "Rule Rationality''. This paradigm claims that people's decision making has evolved to simple rules that perform well in most regular environments. Such an environment consists of replicas of some basic singular circumstance. When the rule is applied to a singular environment, the behavior may seem paradoxical. We claim that the regular environment in which decisions under uncertainty take place, is described by one decision that spans multiple ambiguous risks, which are positively correlated. We show that when a risk averse individual has a Bayesian prior and uses a rule, which is optimal for the regular ambiguous environment, to evaluate a singular vague circumstance - his behavior will exhibit uncertainty aversion. Thus, the behavior predicted by Ellsberg may be explained within the Bayesian expected utility paradigm.
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Bibliographic InfoPaper provided by Econometric Society in its series Econometric Society World Congress 2000 Contributed Papers with number 1125.
Date of creation: 01 Aug 2000
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- Feltkamp, Vincent & Halevy, Yoram, 2004. "A Bayesian Approach to Uncertainty Aversion," Microeconomics.ca working papers halevy-04-02-13-07-48-37, Vancouver School of Economics, revised 25 Feb 2014.
- Yoram Halevy & Vincent Feltkamp, . "A Bayesian Approach to Uncentainty Aversion," CARESS Working Papres 99-03, University of Pennsylvania Center for Analytic Research and Economics in the Social Sciences.
- Vincent Feltkamp & Yoram Halevy, 1999. "- A Bayesian Approach To Uncertainty Aversion," Working Papers. Serie AD 1999-14, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
- Yoram Halevy & Vincent Feltkamp, . "A Bayesian Approach to Uncentainty Aversion," Penn CARESS Working Papers f17f3e2c6ad93e4b53fd58fc9, Penn Economics Department.
- D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
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