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The shape of the utility function under risk in the loss domain and the 'ruinous losses' hypothesis: some experimental results

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  • Nathalie Etchart-Vincent

    (CIRED - centre international de recherche sur l'environnement et le développement - Cirad - Centre de Coopération Internationale en Recherche Agronomique pour le Développement - EHESS - École des hautes études en sciences sociales - AgroParisTech - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique)

Abstract

This paper reports some preliminary experimental results as regards the shape of the utility function for losses when elicited over a wide interval of consequences. Individual utility functions are elicited using the trade-off method, which, unlike standard elicitation procedures, is robust to probability weighting (and avoids most cognitive biases). Even though most utility functions exhibit the usual convex shape, nearly 25% of them appear to be inverse-S shaped, with convexity over moderate losses changing to concavity as losses grow. Though not conclusive (due mainly to the small size of our subject pool), this result brings some new support to the old idea that ruinous or unacceptable losses may induce some abrupt change in the shape of the utility function. Most importantly, it paves the way for more systematic investigation of the "ruinous losses" hypothesis.

Suggested Citation

  • Nathalie Etchart-Vincent, 2009. "The shape of the utility function under risk in the loss domain and the 'ruinous losses' hypothesis: some experimental results," Post-Print hal-00395871, HAL.
  • Handle: RePEc:hal:journl:hal-00395871
    Note: View the original document on HAL open archive server: https://hal.science/hal-00395871
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    1. Mohammed Abdellaoui & Frank Vossmann & Martin Weber, 2005. "Choice-Based Elicitation and Decomposition of Decision Weights for Gains and Losses Under Uncertainty," Management Science, INFORMS, vol. 51(9), pages 1384-1399, September.
    2. 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.
    3. Knutson, Brian & Peterson, Richard, 2005. "Neurally reconstructing expected utility," Games and Economic Behavior, Elsevier, vol. 52(2), pages 305-315, August.
    4. 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.
    5. Schunk, Daniel & Betsch, Cornelia, 2006. "Explaining heterogeneity in utility functions by individual differences in decision modes," Journal of Economic Psychology, Elsevier, vol. 27(3), pages 386-401, June.
    6. 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.
    7. Mao, James C T, 1970. "Survey of Capital Budgeting: Theory and Practice," Journal of Finance, American Finance Association, vol. 25(2), pages 349-360, May.
    8. Harry Markowitz, 1952. "The Utility of Wealth," Journal of Political Economy, University of Chicago Press, vol. 60(2), pages 151-151.
    9. 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.
    10. Joost M. E. Pennings & Ale Smidts, 2003. "The Shape of Utility Functions and Organizational Behavior," Management Science, INFORMS, vol. 49(9), pages 1251-1263, September.
    11. Levy, Haim & Levy, Moshe, 2002. "Arrow-Pratt Risk Aversion, Risk Premium and Decision Weights," Journal of Risk and Uncertainty, Springer, vol. 25(3), pages 265-290, November.
    12. Ferdinand Vieider, 2009. "The effect of accountability on loss aversion," Post-Print halshs-00451605, HAL.
    13. Libby, R & Fishburn, Pc, 1977. "Behavioral-Models Of Risk-Taking In Business Decisions - Survey And Evaluation," Journal of Accounting Research, Wiley Blackwell, vol. 15(2), pages 272-292.
    14. 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.
    15. Paul Slovic & Melissa L. Finucane & Ellen Peters & Donald G. MacGregor, 2004. "Risk as Analysis and Risk as Feelings: Some Thoughts about Affect, Reason, Risk, and Rationality," Risk Analysis, John Wiley & Sons, vol. 24(2), pages 311-322, April.
    16. Imran S. Currim & Rakesh K. Sarin, 1989. "Prospect Versus Utility," Management Science, INFORMS, vol. 35(1), pages 22-41, January.
    17. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    18. Nathalie Etchart-Vincent, 2004. "Is Probability Weighting Sensitive to the Magnitude of Consequences? An Experimental Investigation on Losses," Journal of Risk and Uncertainty, Springer, vol. 28(3), pages 217-235, May.
    19. Lattimore, Pamela K. & Baker, Joanna R. & Witte, Ann D., 1992. "The influence of probability on risky choice: A parametric examination," Journal of Economic Behavior & Organization, Elsevier, vol. 17(3), pages 377-400, May.
    20. Nathalie Etchart-Vincent, 2009. "Probability weighting and the ‘level’ and ‘spacing’ of outcomes: An experimental study over losses," Journal of Risk and Uncertainty, Springer, vol. 39(1), pages 45-63, August.
    21. Pamela K. Lattimore & Joanna R. Baker & A. Dryden Witte, 1992. "The Influence Of Probability on Risky Choice: A parametric Examination," NBER Technical Working Papers 0081, National Bureau of Economic Research, Inc.
    22. Peter Wakker & Veronika Köbberling & Christiane Schwieren, 2007. "Prospect-theory’s Diminishing Sensitivity Versus Economics’ Intrinsic Utility of Money: How the Introduction of the Euro can be Used to Disentangle the Two Empirically," Theory and Decision, Springer, vol. 63(3), pages 205-231, November.
    23. Abdellaoui, Mohammed & Barrios, Carolina & Wakker, Peter P., 2007. "Reconciling introspective utility with revealed preference: Experimental arguments based on prospect theory," Journal of Econometrics, Elsevier, vol. 138(1), pages 356-378, May.
    24. Wakker, Peter & Tversky, Amos, 1993. "An Axiomatization of Cumulative Prospect Theory," Journal of Risk and Uncertainty, Springer, vol. 7(2), pages 147-175, October.
    25. Schmidt, Ulrich & Traub, Stefan, 2002. "An Experimental Test of Loss Aversion," Journal of Risk and Uncertainty, Springer, vol. 25(3), pages 233-249, November.
    26. Mohammed Abdellaoui, 2000. "Parameter-Free Elicitation of Utility and Probability Weighting Functions," Management Science, INFORMS, vol. 46(11), pages 1497-1512, November.
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    Cited by:

    1. Kpegli, Yao Thibaut & Corgnet, Brice & Zylbersztejn, Adam, 2023. "All at once! A comprehensive and tractable semi-parametric method to elicit prospect theory components," Journal of Mathematical Economics, Elsevier, vol. 104(C).
    2. Kontek, Krzysztof, 2011. "What is the actual shape of perception utility?," MPRA Paper 31715, University Library of Munich, Germany.
    3. Nathalie Etchart-Vincent, 2009. "Probability weighting and the ‘level’ and ‘spacing’ of outcomes: An experimental study over losses," Journal of Risk and Uncertainty, Springer, vol. 39(1), pages 45-63, August.

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    More about this item

    Keywords

    utility under risk; large losses; ruin; trade-off method; individual decision making under risk;
    All these keywords.

    JEL classification:

    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • C9 - Mathematical and Quantitative Methods - - Design of Experiments

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