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The Midweight Method to Measure Attitudes Toward Risk and Ambiguity

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Author Info

  • Gijs van de Kuilen

    ()
    (Department of Economics, Tilburg University, 5000 LE Tilburg, The Netherlands)

  • Peter P. Wakker

    ()
    (Econometric Institute, Erasmus University, 3000 DR Rotterdam, The Netherlands)

Abstract

This paper introduces a parameter-free method for measuring the weighting functions of prospect theory and rank-dependent utility. These weighting functions capture risk attitudes, subjective beliefs, and ambiguity attitudes. Our method, called the midweight method, is based on a convenient way to obtain midpoints in the weighting function scale. It can be used both for risk (known probabilities) and for uncertainty (unknown probabilities). The resulting integrated treatment of risk and uncertainty is particularly useful for measuring ambiguity, i.e., the difference between uncertainty and risk. Compared to existing methods to measure weighting functions and attitudes toward uncertainty and ambiguity, our method is more efficient and can accommodate violations of expected utility under risk. An experiment demonstrates the tractability of our method, yielding plausible results such as ambiguity aversion for moderate and high likelihoods but ambiguity seeking for low likelihoods, as predicted by Ellsberg. This paper was accepted by George Wu, decision analysis.

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File URL: http://dx.doi.org/10.1287/mnsc.1100.1282
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Bibliographic Info

Article provided by INFORMS in its journal Management Science.

Volume (Year): 57 (2011)
Issue (Month): 3 (March)
Pages: 582-598

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Handle: RePEc:inm:ormnsc:v:57:y:2011:i:3:p:582-598

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Keywords: prospect theory; ambiguity; probability weighting; pessimism;

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References

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Citations

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Cited by:
  1. Helga Fehr-Duda & Thomas Epper, 2012. "Probability and Risk: Foundations and Economic Implications of Probability-Dependent Risk Preferences," Annual Review of Economics, Annual Reviews, vol. 4(1), pages 567-593, 07.
  2. Michał Krawczyk, 2014. "Probability weighting in different domains: the role of stakes, fungibility, and affect," Working Papers 2014-15, Faculty of Economic Sciences, University of Warsaw.
  3. Arthur E. Attema & Werner B.F. Brouwer & Olivier L'Haridon, 2013. "Prospect theory in the health domain: A quantitative assessment," Post-Print halshs-00866788, HAL.
  4. Bas Donkers & Carlos J.S. Lourenco & Benedict G.C. Dellaert & Daniel G. Goldstein, 2013. "Using Preferred Outcome Distributions to estimate Value and Probability Weighting Functions in Decisions under Risk," Tinbergen Institute Discussion Papers 13-065/VII, Tinbergen Institute.
  5. Jianying Qiu & Eva-Maria Steiger, 2010. "Understanding the Two Components of Risk Attitudes: An Experimental Analysis," Jena Economic Research Papers 2010-053, Friedrich-Schiller-University Jena, Max-Planck-Institute of Economics.
  6. Erner, Carsten & Klos, Alexander & Langer, Thomas, 2013. "Can prospect theory be used to predict an investor’s willingness to pay?," Journal of Banking & Finance, Elsevier, vol. 37(6), pages 1960-1973.
  7. Stefan Zeisberger & Dennis Vrecko & Thomas Langer, 2012. "Measuring the time stability of Prospect Theory preferences," Theory and Decision, Springer, vol. 72(3), pages 359-386, March.
  8. repec:dgr:uvatin:2013065 is not listed on IDEAS
  9. Thomas Epper & Helga Fehr-Duda, 2012. "The missing link: Unifying risk taking and time discounting," ECON - Working Papers 096, Department of Economics - University of Zurich.
  10. Katarzyna Werner & Horst Zank, 2012. "Foundations for Prospect Theory Through Probability Midpoint Consistency," The School of Economics Discussion Paper Series 1210, Economics, The University of Manchester.
  11. David Dillenberger & Uzi Segal, 2013. "Skewed Noise," PIER Working Paper Archive 13-066, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  12. David Dillenberger & Uzi Segal, 2013. "Skewed Noise," Boston College Working Papers in Economics 843, Boston College Department of Economics.

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