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Assessing Multiple Prior Models of Behaviour under Ambiguity

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  • Anna Conte
  • John D. Hey

Abstract

The recent spate of theoretical models of behaviour under ambiguity can be partitioned into two sets: those involving multiple priors (in which the probabilities of the various events are not known but probabilities can be attached to the various possible values for the probabilities) and those not involving multiple priors. This paper concentrates on the first set and provides an experimental investigation into recently proposed theories. Using an appropriate experimental interface, in which the probabilities on the various possibilities are explicitly stated, we examine the fitted and predictive power of the various theories. We first estimate subject-by-subject, and then we estimateand predict using a mixture model over the contending theories. The individual estimates suggest that 25% of our 149 subjects have behaviour consistent with Expected Utility, 54% with the Smooth Model (of Klibanoff et al, 2005), 12% with Rank Dependent Expected Utility and 9% with the Alpha Model (of Ghirardato et al 2004); these figures are very close to the mixing proportions obtained from the mixture estimates. However, if we classify our subjects through the posterior probabilities (given all the evidence) of each of them being of the various types: using the estimates we get 38%, 19%, 28% and 16% (for EU, Smooth, Rank Dependent and Alpha); while using the predictions 36%, 19%, 33% and 11%. Interestingly the older models (EU and RD) seem to fare relatively better, suggesting that representing ambiguity through multiple priors is perceived by subjects as risk, rather than ambiguity

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Bibliographic Info

Paper provided by Department of Economics, University of York in its series Discussion Papers with number 12/01.

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Date of creation: Jan 2012
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Handle: RePEc:yor:yorken:12/01

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Postal: Department of Economics and Related Studies, University of York, York, YO10 5DD, United Kingdom
Phone: (0)1904 323776
Fax: (0)1904 323759
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Web page: http://www.york.ac.uk/economics/
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Keywords: Alpha Model; Ambiguity; Expected Utility; Mixture Models; Rank Dependent Expected Utility; Smooth Model.;

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References

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  1. Sujoy Mukerji & Peter Klibanoff, 2002. "A Smooth Model of Decision,Making Under Ambiguity," Economics Series Working Papers 113, University of Oxford, Department of Economics.
  2. Amos Tversky & Daniel Kahneman, 1979. "Prospect Theory: An Analysis of Decision under Risk," Levine's Working Paper Archive 7656, David K. Levine.
  3. Quiggin, John, 1982. "A theory of anticipated utility," Journal of Economic Behavior & Organization, Elsevier, vol. 3(4), pages 323-343, December.
  4. Conte, Anna & Hey, John D. & Moffatt, Peter G., 2011. "Mixture models of choice under risk," Journal of Econometrics, Elsevier, vol. 162(1), pages 79-88, May.
  5. 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.
  6. John D Hey & Gianna Lotito & Anna Maffioletti, 2008. "The Descriptive and Predictive Adequacy of Theories of Decision Making Under Uncertainty/Ambiguity," Discussion Papers 08/04, Department of Economics, University of York.
  7. Ghirardato, Paolo & Maccheroni, Fabio & Marinacci, Massimo, 2004. "Differentiating ambiguity and ambiguity attitude," Journal of Economic Theory, Elsevier, vol. 118(2), pages 133-173, October.
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  9. Thibault Gajdos & Takashi Hayashi & Jean-Marc Tallon & Jean-Christophe Vergnaud, 2006. "Attitude toward imprecise information," Cahiers de la Maison des Sciences Economiques v06081, Université Panthéon-Sorbonne (Paris 1).
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  14. 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.
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  16. 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.
  17. John D Hey & Noemi Pace, . "The Explanatory and Predictive Power of Non Two-Stage-Probability Theories of Decision Making Under Ambiguity," Discussion Papers 11/22, Department of Economics, University of York.
  18. 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.
  19. Gilboa, Itzhak & Schmeidler, David, 1989. "Maxmin expected utility with non-unique prior," Journal of Mathematical Economics, Elsevier, vol. 18(2), pages 141-153, April.
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Citations

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Cited by:
  1. Anna Conte & M. Vittoria Levati, 2011. "Use of data on planned contributions and stated beliefs in the measurement of social preferences," Jena Economic Research Papers 2011-039, Friedrich-Schiller-University Jena, Max-Planck-Institute of Economics.
  2. Attanasi, Giuseppe & Gollier, Christian & Montesano, Aldo & Pace, Noémie, 2012. "Eliciting ambiguity aversion in unknown and in compound lotteries: A KMM experimental approach," LERNA Working Papers 12.21.378, LERNA, University of Toulouse.
  3. Sujoy Mukerji & Robin Cubitt & Gijs van de Kuilen, 2014. "Discriminating between Models of Ambiguity Attitude: A Qualitative Test," Economics Series Working Papers 692, University of Oxford, Department of Economics.
  4. Anna Conte & John D. Hey & Ivan Soraperra, 2014. "The Determinants of Decision Time," Jena Economic Research Papers 2014-004, Friedrich-Schiller-University Jena, Max-Planck-Institute of Economics.

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