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Risk and Rationality: Uncovering Heterogeneity in Probability Distortion

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  • Adrian Bruhin
  • Helga Fehr-Duda
  • Thomas Epper

Abstract

It has long been recognized that there is considerable heterogeneity in individual risk taking behavior, but little is known about the distribution of risk taking types. We present a parsimonious characterization of risk taking behavior by estimating a finite mixture model for three different experimental data sets, two Swiss and one Chinese, over a large number of real gains and losses. We find two major types of individuals: In all three data sets, the choices of roughly 80% of the subjects exhibit significant deviations from linear probability weighting of varying strength, consistent with prospect theory. Twenty percent of the subjects weight probabilities near linearly and behave essentially as expected value maximizers. Moreover, individuals are cleanly assigned to one type with probabilities close to unity. The reliability and robustness of our classification suggest using a mix of preference theories in applied economic modeling. Copyright 2010 The Econometric Society.

Suggested Citation

  • Adrian Bruhin & Helga Fehr-Duda & Thomas Epper, 2010. "Risk and Rationality: Uncovering Heterogeneity in Probability Distortion," Econometrica, Econometric Society, vol. 78(4), pages 1375-1412, July.
    • Handle: RePEc:ecm:emetrp:v:78:y:2010:i:4:p:1375-1412
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    References listed on IDEAS

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    1. Helga Fehr-Duda & Manuele Gennaro & Renate Schubert, 2006. "Gender, Financial Risk, and Probability Weights," Theory and Decision, Springer, vol. 60(2), pages 283-313, May.
    2. Urs Fischbacher, 2007. "z-Tree: Zurich toolbox for ready-made economic experiments," Experimental Economics, Springer;Economic Science Association, vol. 10(2), pages 171-178, June.
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    More about this item

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • C49 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Other

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