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A Behavioral Characterization of Plausible Priors

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  • Marciano Siniscalchi

Abstract

Recent theories of choice under uncertainty represent ambiguity via multiple priors, informally interpreted as alternative probabilistic models of the uncertainty that the decision-maker considers equally plausible. This paper provides a robust behavioral foundation for this interpretation. A prior P is deemed “plausible” if (i) preferences over a subset C of acts are consistent with subjective expected utility (SEU), and (ii) jointly with an appropriate utility function, P provides the unique SEU representation of preferences over C. Under appropriate axioms, plausible priors can be elicited from preferences; moreover, if these axioms hold, (i) preferences are probabilistically sophisticated if and only if they are SEU, and (ii) under suitable consequentialism and dynamic consistency axioms, “plausible posteriors” can be derived from plausible priors via Bayes’ rule. Several well-known decision models are consistent with the axioms proposed here.

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Bibliographic Info

Paper provided by UCLA Department of Economics in its series Levine's Bibliography with number 234936000000000064.

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Date of creation: 07 Apr 2003
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Handle: RePEc:cla:levrem:234936000000000064

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  17. Ghirardato, Paolo & Marinacci, Massimo, 2002. "Ambiguity Made Precise: A Comparative Foundation," Journal of Economic Theory, Elsevier, vol. 102(2), pages 251-289, February.
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Citations

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Cited by:
  1. Ehud Lehrer & Roee Teper, 2014. "Extension Rules or What Would the Sage Do?," American Economic Journal: Microeconomics, American Economic Association, vol. 6(1), pages 5-22, February.
  2. Tigran Melkonyan & Mark Pingle, 2010. "Ambiguity, pessimism, and rational religious choice," Theory and Decision, Springer, vol. 69(3), pages 417-438, September.
  3. Marciano Siniscalchi, 2007. "Vector Expected Utility and Attitudes toward Variation," Discussion Papers 1455, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
  4. Rigotti, Luca & Shannon, Chris, 2012. "Sharing risk and ambiguity," Journal of Economic Theory, Elsevier, vol. 147(5), pages 2028-2039.
  5. Martin Dumav & Maxwell B. Stinchcombe, 2013. "The von Neumann/Morgenstern approach to ambiguity," Working Papers 480, Bielefeld University, Center for Mathematical Economics.
  6. Ludwig, Alexander & Zimper, Alexander, 2004. "Investment Behavior under Ambiguity: The Case of Pessimistic Decision Makers," Sonderforschungsbereich 504 Publications 04-31, Sonderforschungsbereich 504, Universität Mannheim & Sonderforschungsbereich 504, University of Mannheim.
  7. Amit Kothiyal & Vitalie Spinu & Peter Wakker, 2014. "An experimental test of prospect theory for predicting choice under ambiguity," Journal of Risk and Uncertainty, Springer, vol. 48(1), pages 1-17, February.
  8. Klaus Nehring, 2006. "Bernoulli Without Bayes: A Theory of Utility-Sophisticated Preferences under Ambiguity," Economics Working Papers 0072, Institute for Advanced Study, School of Social Science.
  9. Siniscalchi, Marciano, 2011. "Dynamic choice under ambiguity," Theoretical Economics, Econometric Society, vol. 6(3), September.
  10. Tigran Melkonyan & Mark Pingle, 2008. "Ambiguity, Pessimism, and Religious Choice," Working Papers 08-002, University of Nevada, Reno, Department of Economics & University of Nevada, Reno , Department of Resource Economics.
  11. Melkonyan, Tigran A., 2011. "The Effect of Communicating Ambiguous Risk Information on Choice," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 36(2), August.
  12. Hansen, Lars Peter & Maenhout, Pascal & Rustichini, Aldo & Sargent, Thomas J. & Siniscalchi, Marciano M., 2006. "Introduction to model uncertainty and robustness," Journal of Economic Theory, Elsevier, vol. 128(1), pages 1-3, May.
  13. Scott Condie & Jayant Ganguli, 2011. "Informational efficiency with ambiguous information," Economic Theory, Springer, vol. 48(2), pages 229-242, October.

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