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The Rich Domain of Uncertainty: Source Functions and Their Experimental Implementation

Author

Listed:
  • 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)

  • Laetitia Placido

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, 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)

  • Aurélien Baillon

    (GRID - Groupe de Recherche sur le risque, l'Information et la Décision - ENS Cachan - École normale supérieure - Cachan - CNRS - Centre National de la Recherche Scientifique)

  • P.P. Wakker

Abstract

We often deal with uncertain events for which no probabilities are known. Several normative models have been proposed. Descriptive studies have usually been qualitative, or they estimated ambiguity aversion through one single number. This paper introduces the source method, a tractable method for quantitatively analyzing uncertainty empirically. The theoretical key is the distinction between different sources of uncertainty, within which subjective (choice-based) probabilities can still be defined. Source functions convert those subjective probabilities into willingness to bet. We apply our method in an experiment, where we do not commit to particular ambiguity attitudes but let the data speak.

Suggested Citation

  • Mohammed Abdellaoui & Laetitia Placido & Aurélien Baillon & P.P. Wakker, 2011. "The Rich Domain of Uncertainty: Source Functions and Their Experimental Implementation," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00609214, HAL.
    • Handle: RePEc:hal:cesptp:hal-00609214
    DOI: 10.1257/aer.101.2.695
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    JEL classification:

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

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