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Separating curvature and elevation: A parametric probability weighting function

Author

Listed:
  • Olivier L'Haridon

    (GREGH - Groupement de Recherche et d'Etudes en Gestion à HEC - HEC Paris - Ecole des Hautes Etudes Commerciales - CNRS - Centre National de la Recherche Scientifique)

  • Mohammed Abdellaoui

    (GREGH - Groupement de Recherche et d'Etudes en Gestion à HEC - HEC Paris - Ecole des Hautes Etudes Commerciales - CNRS - Centre National de la Recherche Scientifique)

  • Horst Zank

    (Department of Applied Economics - Erasmus University Rotterdam)

Abstract

This paper presents a preference foundation for a two-parameter family of probability weighting functions. We provide a theoretical link between the well-established notions of probabilistic risk attitudes (i.e., optimism and pessimism) used in economics and the important independent measures for individual behavior used in the psychology literature (i.e., curvature and elevation). One of the parameters in our model measures curvature and represents the diminishing effect of optimism and pessimism when moving away from extreme probabilities 0 and 1. The other parameter measures elevation and represents the relative strength of optimism vs. pessimism. Our empirical analysis indicates that the new weighting function fits elicited probability weights well, and that it can explain differences in the treatment of probabilities for gains compared to that for probabilities of losses.

Suggested Citation

  • Olivier L'Haridon & Mohammed Abdellaoui & Horst Zank, 2010. "Separating curvature and elevation: A parametric probability weighting function," Post-Print hal-00528381, HAL.
    • Handle: RePEc:hal:journl:hal-00528381
    DOI: 10.1007/s11166-010-9097-6
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    References listed on IDEAS

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    More about this item

    Keywords

    Curvature; Elevation; Optimism; Pessimism; Preference foundation; Prospect theory;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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