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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
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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. 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).
  2. Schmeidler, David, 1989. "Subjective Probability and Expected Utility without Additivity," Econometrica, Econometric Society, vol. 57(3), pages 571-87, May.
  3. Peter Klibanoff & Massimo Marinacci & Sujoy Mukerji, 2002. "A smooth model of decision making under ambiguity," ICER Working Papers - Applied Mathematics Series 11-2003, ICER - International Centre for Economic Research, revised Apr 2003.
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  5. Yoram Halevy, 2007. "Ellsberg Revisited: An Experimental Study," Econometrica, Econometric Society, vol. 75(2), pages 503-536, 03.
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  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.
  8. Steffen Andersen & Glenn Harrison & Morten Lau & E. Rutström, 2009. "Elicitation using multiple price list formats," Experimental Economics, Springer, vol. 12(3), pages 365-366, September.
  9. 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.
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  12. John Hey & Gianna Lotito & Anna Maffioletti, 2010. "The descriptive and predictive adequacy of theories of decision making under uncertainty/ambiguity," Journal of Risk and Uncertainty, Springer, vol. 41(2), pages 81-111, October.
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  14. Anna Conte & John D Hey & Peter G Moffatt, 2007. "Mixture Models of Choice Under Risk," Discussion Papers 07/06, Department of Economics, University of York.
  15. 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.
  16. Uzi Segal, 1985. "The Ellsberg Paradox and Risk Aversion: An Anticipated Utility Approach," UCLA Economics Working Papers 362, UCLA Department of Economics.
  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. 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.
  19. Andersen, Steffen & Fountain, John & Harrison, Glenn W. & Rutström, Elisabet E., 2009. "Estmating Aversion to Uncertainty," Working Papers 07-2009, Copenhagen Business School, Department of Economics.
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  21. Quiggin, John, 1982. "A theory of anticipated utility," Journal of Economic Behavior & Organization, Elsevier, vol. 3(4), pages 323-343, December.
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Cited by:
  1. Attanasi, Giuseppe & Gollier, Christian & Montesano, Aldo & Pace, Noémie, 2012. "Eliciting ambiguity aversion in unknown and in compound lotteries: A KMM experimental approach," IDEI Working Papers 744, Institut d'Économie Industrielle (IDEI), Toulouse.
  2. 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.
  3. 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.
  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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