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The Descriptive and Predictive Adequacy of Theories of Decision Making Under Uncertainty/Ambiguity

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Author Info
John D Hey
Gianna Lotito
Anna Maffioletti

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Abstract

In this paper we examine the performance of theories of decision making under uncertainty/ambiguity from the perspective of their descriptive and predictive power, taking into account the relative parsimony of the various theories. To this end, we employ an innovative experimental design which enables us to reproduce ambiguity in the laboratory in a transparent and non-probabilistic way. We find that judging theories on the basis of their theoretical appeal, or on their ability to do well in testing contexts, is not the same as judging them on the basis of their explanatory and predictive power. We also find that the more elegant theoretical models do not perform as well as simple rules of thumb.

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Publisher Info
Paper provided by Department of Economics, University of York in its series Discussion Papers with number 08/04.

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Date of creation: Apr 2008
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Handle: RePEc:yor:yorken:08/04

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Related research
Keywords: Ambiguity; Bingo Blower; Choquet Expected Utility; Decision Field Theory; Decision Making; Expected Utility; Hurwicz Criterion; (Gilboa and Schmeidler) MaxMin EU; (Gilboa and Schmeidler) MaxMax EU; (Ghirardato) Alpha-Model; MaxMin; MaxMax; Minimum Regret; Prospect Theory; Uncertainty.;

Find related papers by JEL classification:
D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

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References listed on IDEAS
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  1. Peter Moffatt & Simon Peters, 2001. "Testing for the Presence of a Tremble in Economic Experiments," Experimental Economics, Springer, vol. 4(3), pages 221-228, December. [Downloadable!] (restricted)
  2. Segal, Uzi, 1987. "The Ellsberg Paradox and Risk Aversion: An Anticipated Utility Approach," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 28(1), pages 175-202, February. [Downloadable!] (restricted)
    Other versions:
  3. John Hey & Jinkwon Lee, 2005. "Do Subjects Separate (or Are They Sophisticated)?," Experimental Economics, Springer, vol. 8(3), pages 233-265, September. [Downloadable!] (restricted)
  4. Ben Greiner, 2004. "The Online Recruitment System ORSEE 2.0 - A Guide for the Organization of Experiments in Economics," Working Paper Series in Economics 10, University of Cologne, Department of Economics. [Downloadable!]
  5. Ghirardato, Paolo & Maccheroni, Fabio & Marinacci, Massimo, 2004. "Differentiating ambiguity and ambiguity attitude," Journal of Economic Theory, Elsevier, vol. 118(2), pages 133-173, October. [Downloadable!] (restricted)
  6. Gilboa, Itzhak & Schmeidler, David, 1989. "Maxmin expected utility with non-unique prior," Journal of Mathematical Economics, Elsevier, vol. 18(2), pages 141-153, April. [Downloadable!] (restricted)
  7. Schmeidler, David, 1989. "Subjective Probability and Expected Utility without Additivity," Econometrica, Econometric Society, vol. 57(3), pages 571-87, May. [Downloadable!] (restricted)
  8. Kahneman, Daniel & Tversky, Amos, 1979. "Prospect Theory: An Analysis of Decision under Risk," Econometrica, Econometric Society, vol. 47(2), pages 263-91, March. [Downloadable!] (restricted)
  9. Peter Klibanoff & Massimo Marinacci & Sujoy Mukerji, 2005. "A Smooth Model of Decision Making under Ambiguity," Econometrica, Econometric Society, vol. 73(6), pages 1849-1892, November. [Downloadable!] (restricted)
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  10. Fox, Craig R & Tversky, Amos, 1995. "Ambiguity Aversion and Comparative Ignorance," The Quarterly Journal of Economics, MIT Press, vol. 110(3), pages 585-603, August. [Downloadable!] (restricted)
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