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A language for the construction of preferences under uncertainty

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Author Info

  • Marco LiCalzi

    (University of Venice, Italy)

Abstract

This paper studies a target-based procedure to rank lotteries that is normatively and observationally equivalent to the expected utility model. In view of this equivalence, the traditional utility-based language for decision making may be substituted with an alternative target-based language. Switching language may have significant modelling consequences. To exemplify, we contrast the utility-based viewpoint of prospect theory against the target-based viewpoint and provide an explanation of Allais’ paradox based on context dependence instead of distorted probabilities.

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File URL: http://128.118.178.162/eps/game/papers/0509/0509002.pdf
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Bibliographic Info

Paper provided by EconWPA in its series Game Theory and Information with number 0509002.

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Length: 21 pages
Date of creation: 05 Sep 2005
Date of revision:
Handle: RePEc:wpa:wuwpga:0509002

Note: Type of Document - pdf; pages: 21. 25 pages, pdf
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Web page: http://128.118.178.162

Related research

Keywords: expected utility; prospect theory; target-based decisions; choice anomalies; benchmarking;

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References

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  1. Manski, C.F., 1988. "Ordinal Utility Models Of Decision Making Under Uncertainty," Working papers 363, Wisconsin Madison - Social Systems.
  2. Machina, Mark J, 1982. ""Expected Utility" Analysis without the Independence Axiom," Econometrica, Econometric Society, vol. 50(2), pages 277-323, March.
  3. Yaari, Menahem E, 1987. "The Dual Theory of Choice under Risk," Econometrica, Econometric Society, vol. 55(1), pages 95-115, January.
  4. Gul, Faruk, 1991. "A Theory of Disappointment Aversion," Econometrica, Econometric Society, vol. 59(3), pages 667-86, May.
  5. Amos Tversky & Daniel Kahneman, 1979. "Prospect Theory: An Analysis of Decision under Risk," Levine's Working Paper Archive 7656, David K. Levine.
  6. Robert Bordley & Marco LiCalzi, 2000. "Decision analysis using targets instead of utility functions," Decisions in Economics and Finance, Springer, vol. 23(1), pages 53-74.
  7. Drazen Prelec, 1998. "The Probability Weighting Function," Econometrica, Econometric Society, vol. 66(3), pages 497-528, May.
  8. Tversky, Amos & Kahneman, Daniel, 1992. " Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
  9. Marvin H. Berhold, 1973. "The Use of Distribution Functions to Represent Utility Functions," Management Science, INFORMS, vol. 19(7), pages 825-829, March.
  10. Shafir, Eldar & Diamond, Peter & Tversky, Amos, 1997. "Money Illusion," The Quarterly Journal of Economics, MIT Press, vol. 112(2), pages 341-74, May.
  11. Marco LiCalzi, 2000. "Upper and lower bounds for expected utility," Economic Theory, Springer, vol. 16(2), pages 489-502, 09.
  12. DellaVigna, Stefano & LiCalzi, Marco, 2001. "Learning to make risk neutral choices in a symmetric world," Mathematical Social Sciences, Elsevier, vol. 41(1), pages 19-37, January.
  13. Erio Castagnoli & Marco LiCalzi, 2005. "Expected utility without utility," Game Theory and Information 0508004, EconWPA.
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Cited by:
  1. Sergiy Gerasymchuk, 2007. "Mean-Variance Portfolio Selection with Reference Dependent Preferences," Working Papers 150, Department of Applied Mathematics, Università Ca' Foscari Venezia.

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