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An experimental methodology testing for prudence and third-order preferences

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  • Sebastian Ebert

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  • Daniel Wiesen

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    Abstract

    We propose an experimental method to test individuals for prudence (i.e. downside risk aversion) outside the expected utility framework. Our method relies on a novel representation of compound lotteries which allows for a systematic parameterization that captures the full generality of prudence. Therefore, we develop a general technique for lottery calibration in experiments. Since we investigate a very subtle third-order property we test our method in the laboratory employing a factorial design. We find that it yields robust results and that prudence is observed on the aggregate as well as on the individual level. Further we show that preferences based on statistical moments, in particular skewness seeking, can at most approximately explain individuals' behavior in the experiment.

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    File URL: http://www.wiwi.uni-bonn.de/bgsepapers/bonedp/bgse21_2009.pdf
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    Bibliographic Info

    Paper provided by University of Bonn, Germany in its series Bonn Econ Discussion Papers with number bgse21_2009.

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    Length: 45
    Date of creation: Sep 2009
    Date of revision:
    Handle: RePEc:bon:bonedp:bgse21_2009

    Contact details of provider:
    Postal: Bonn Graduate School of Economics, University of Bonn, Adenauerallee 24 - 26, 53113 Bonn, Germany
    Fax: +49 228 73 6884
    Web page: http://www.bgse.uni-bonn.de

    Related research

    Keywords: Decision making under uncertainty; risk preferences; prudence; downside risk; statistical moments; laboratory experiment;

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    1. Gomes, Francisco J & Michaelides, Alexander, 2005. "Optimal Life-Cycle Asset Allocation: Understanding the Empirical Evidence," CEPR Discussion Papers 4853, C.E.P.R. Discussion Papers.
    2. Ekern, Steinar, 1980. "Increasing Nth degree risk," Economics Letters, Elsevier, vol. 6(4), pages 329-333.
    3. Louis Eeckhoudt & Harris Schlesinger, 2006. "Putting Risk in Its Proper Place," American Economic Review, American Economic Association, vol. 96(1), pages 280-289, March.
    4. Amos Tversky & Daniel Kahneman, 1979. "Prospect Theory: An Analysis of Decision under Risk," Levine's Working Paper Archive 7656, David K. Levine.
    5. David Crainich & Louis Eeckhoudt, 2008. "On the intensity of downside risk aversion," Journal of Risk and Uncertainty, Springer, vol. 36(3), pages 267-276, June.
    6. Patrick Roger, 2008. "Mixed Risk Aversion and Preference for Risk Disaggregation," Working Papers of LaRGE Research Center 2008-17, Laboratoire de Recherche en Gestion et Economie (LaRGE), Université de Strasbourg (France).
    7. 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.
    8. Christophe Courbage & Béatrice Rey, 2006. "Prudence and optimal prevention for health risks," Health Economics, John Wiley & Sons, Ltd., vol. 15(12), pages 1323-1327.
    9. Louis Eeckhoudt & Christian Gollier, 2005. "The impact of prudence on optimal prevention," Economic Theory, Springer, vol. 26(4), pages 989-994, November.
    10. Walter Briec & Kristiaan Kerstens & Octave Jokung, 2007. "Mean-Variance-Skewness Portfolio Performance Gauging: A General Shortage Function and Dual Approach," Management Science, INFORMS, vol. 53(1), pages 135-149, January.
    11. Menezes, C & Geiss, C & Tressler, J, 1980. "Increasing Downside Risk," American Economic Review, American Economic Association, vol. 70(5), pages 921-32, December.
    12. Cary Deck & Harris Schlesinger, 2008. "Exploring Higher-Order Risk Effects," CESifo Working Paper Series 2487, CESifo Group Munich.
    13. Camerer, Colin F, 1989. " An Experimental Test of Several Generalized Utility Theories," Journal of Risk and Uncertainty, Springer, vol. 2(1), pages 61-104, April.
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