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Efficient elicitation of utility and probability weighting functions

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  • Pavlo Blavatskyy

Abstract

Elicitation methods in decision making under risk allow a researcher to infer the subjective utilities of outcomes as well as the subjective weights of probabilities from the observed preferences of an individual. An optimally efficient elicitation method is proposed, which takes into account the inevitable distortion of preferences by random errors and minimizes the effect of such errors on the inferred utility and probability weighting functions. Under mild assumptions, the optimally efficient method for eliciting utilities (weights) of many outcomes (probabilities) is the following three-stage procedure. First, a probability is elicited whose subjective weight is one half. Second, an individual�s utility function is elicited through the midpoint chaining certainty equivalent method employing the probability elicited at the first stage as an input. Finally, an individual�s probability weighting function is elicited through the probability equivalent method.

Suggested Citation

  • Pavlo Blavatskyy, "undated". "Efficient elicitation of utility and probability weighting functions," IEW - Working Papers 211, Institute for Empirical Research in Economics - University of Zurich.
  • Handle: RePEc:zur:iewwpx:211
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    File URL: https://www.zora.uzh.ch/id/eprint/52106/1/iewwp211.pdf
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    References listed on IDEAS

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    2. repec:bla:econom:v:65:y:1998:i:260:p:581-98 is not listed on IDEAS
    3. 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.
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    6. John D. Hey & Chris Orme, 2018. "Investigating Generalizations Of Expected Utility Theory Using Experimental Data," World Scientific Book Chapters, in: Experiments in Economics Decision Making and Markets, chapter 3, pages 63-98, World Scientific Publishing Co. Pte. Ltd..
    7. Loomes, Graham & Sugden, Robert, 1995. "Incorporating a stochastic element into decision theories," European Economic Review, Elsevier, vol. 39(3-4), pages 641-648, April.
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    Cited by:

    1. Fehr, Ernst & Fischbacher, Urs & Kosfeld, Michael, 2005. "Neuroeconomic Foundations of Trust and Social Preferences," IZA Discussion Papers 1641, Institute of Labor Economics (IZA).
    2. Tania Singer & Ernst Fehr, 2005. "The Neuroeconomics of Mind Reading and Empathy," American Economic Review, American Economic Association, vol. 95(2), pages 340-345, May.
    3. Armin Falk & Ernst Fehr & Christian Zehnder, "undated". "The Behavioral Effects of Minimum Wages," IEW - Working Papers 247, Institute for Empirical Research in Economics - University of Zurich.

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    More about this item

    Keywords

    decision theory; rank-dependent expected utility; cumulative prospect theory; von Neumann-Morgenstern utility; probability weighting; elicitation;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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