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Using Preferred Outcome Distributions to estimate Value and Probability Weighting Functions in Decisions under Risk

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  • Bas Donkers

    (Erasmus University Rotterdam)

  • Carlos J.S. Lourenco

    (Erasmus University Rotterdam)

  • Benedict G.C. Dellaert

    (Erasmus University Rotterdam)

  • Daniel G. Goldstein

    (Microsoft Research)

Abstract

In this paper we propose the use of preferred outcome distributions as a new method to elicit individuals' value and probability weighting functions in decisions under risk. Extant approaches for the elicitation of these two key ingredients of individuals' risk attitude typically rely on a long, chained sequence of lottery choices. In contrast, preferred outcome distributions can be elicited through an intuitive graphical interface, and, as we show, the information contained in two preferred outcome distributions is sufficient to identify non-parametrically both the value function and the probability weighting function in rank-dependent utility models. To illustrate our method and its advantages, we run an incentive-compatible lab study in which participants use a simple graphical interface - the Distribution Builder (Goldstein et al. 2008) - to construct their preferred outcome distributions, subject to a budget constraint. Results show that estimates of the value function are in line with previous research but that probability weighting biases are diminished, thus favoring our proposed approach based on preferred outcome distributions.

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Bibliographic Info

Paper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 13-065/VII.

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Date of creation: 08 May 2013
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Handle: RePEc:dgr:uvatin:20130065

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Web page: http://www.tinbergen.nl

Related research

Keywords: Decision making; risk preference; distribution builder; rank dependent utility; preference elicitation; micro economics;

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  1. Mohammed Abdellaoui & Han Bleichrodt & Olivier L’Haridon, 2008. "A tractable method to measure utility and loss aversion under prospect theory," Journal of Risk and Uncertainty, Springer, vol. 36(3), pages 245-266, June.
  2. Peter Wakker & Daniel Deneffe, 1996. "Eliciting von Neumann-Morgenstern Utilities When Probabilities Are Distorted or Unknown," Management Science, INFORMS, vol. 42(8), pages 1131-1150, August.
  3. Casper van Ewijk & C. Santing, 2010. "A meta-analysis of the equity premium," CPB Discussion Paper 156, CPB Netherlands Bureau for Economic Policy Analysis.
  4. Han Bleichrodt & Jose Luis Pinto, 2000. "A Parameter-Free Elicitation of the Probability Weighting Function in Medical Decision Analysis," Management Science, INFORMS, vol. 46(11), pages 1485-1496, November.
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  8. Daniel G. Goldstein & Eric J. Johnson & William F. Sharpe, 2008. "Choosing Outcomes versus Choosing Products: Consumer-Focused Retirement Investment Advice," Journal of Consumer Research, University of Chicago Press, vol. 35(3), pages 440-456, 08.
  9. Drazen Prelec, 1998. "The Probability Weighting Function," Econometrica, Econometric Society, vol. 66(3), pages 497-528, May.
  10. Syngjoo Choi & Raymond Fisman & Douglas Gale & Shachar Kariv, 2007. "Consistency and Heterogeneity of Individual Behavior under Uncertainty," American Economic Review, American Economic Association, vol. 97(5), pages 1921-1938, December.
  11. Mohammed Abdellaoui, 2000. "Parameter-Free Elicitation of Utility and Probability Weighting Functions," Management Science, INFORMS, vol. 46(11), pages 1497-1512, November.
  12. John C. Hershey & Paul J. H. Schoemaker, 1985. "Probability Versus Certainty Equivalence Methods in Utility Measurement: Are they Equivalent?," Management Science, INFORMS, vol. 31(10), pages 1213-1231, October.
  13. Charles A. Holt & Susan K. Laury, 2002. "Risk Aversion and Incentive Effects," American Economic Review, American Economic Association, vol. 92(5), pages 1644-1655, December.
  14. 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.
  15. Mark McCord & Richard de Neufville, 1986. ""Lottery Equivalents": Reduction of the Certainty Effect Problem in Utility Assessment," Management Science, INFORMS, vol. 32(1), pages 56-60, January.
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