Random Expected Utility
We develop and analyze a model of random choice and random expected utility. A decision problem is a finite set of lotteries that describe the feasible choices. A random choice rule associates with each decision problem a probability measure over choices. A random utility function is a probability measure over von Neumann-Morgenstern utility functions. We show that a random choice rule maximizes some random utility function if and only if it is mixture continuous, monotone (the probability that a lottery is chosen does not increase when other lotteries are added to the decision problem), extreme (lotteries that are not extreme points of the decision problem are chosen with probability 0), and linear (satisfies the independence axiom). Copyright The Econometric Society 2006.
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|Date of creation:||02 May 2002|
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- Gil Kalai & Ariel Rubinstein & Ran Spiegler, 2002.
"Rationalizing Choice Functions By Multiple Rationales,"
Econometric Society, vol. 70(6), pages 2481-2488, November.
- Gil Kalai & Ariel Rubenstein & Ran Spiegler, 2001. "Rationalizing Choice Functions by Multiple Rationales," Economics Working Papers 0010, Institute for Advanced Study, School of Social Science.
- Gil Kalai & Ariel Rubinstein & Ran Spiegler, 2001. "Rationalizing Choice Functions by Multiple Rationales," Discussion Paper Series dp278, The Federmann Center for the Study of Rationality, the Hebrew University, Jerusalem.
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- Faruk Gul & Wolfgang Pesendorfer, 2006.
"Random Expected Utility,"
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- Fishburn, Peter C., 1992. "Induced binary probabilities and the linear ordering polytope: a status report," Mathematical Social Sciences, Elsevier, vol. 23(1), pages 67-80, February.
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