On the relation between robust and Bayesian decision making
AbstractThis paper compares Bayesian decision theory with robust decision theory where the decision maker optimizes with respect to the worst state realization. For a class of robust decision problems there exists a sequence of Bayesian decision problems whose solution converges towards the robust solution. It is shown that the limiting Bayesian problem displays infinite risk aversion and that its solution is insensitive (robust) to the precise assignment of prior probabilities. Moreover, the limiting Bayesian objective turns out not to be time separable even if the objective function of the robust decision makers displays time separability.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Economic Dynamics and Control.
Volume (Year): 28 (2004)
Issue (Month): 10 (September)
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Web page: http://www.elsevier.com/locate/jedc
Other versions of this item:
- Adam, Klaus, 2003. "On the Relation between Robust and Bayesian Decision Making," CFS Working Paper Series 2003/02, Center for Financial Studies (CFS).
- Klaus Adam, 2001. "On the Relation between Robust and Bayesian Decision Making," CSEF Working Papers 68, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
- D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
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