IDEAS home Printed from https://ideas.repec.org/p/hal/journl/halshs-01242616.html
   My bibliography  Save this paper

Measuring Loss Aversion under Ambiguity: A Method to Make Prospect Theory Completely Observable

Author

Listed:
  • Mohammed Abdellaoui

    (HEC Paris - Ecole des Hautes Etudes Commerciales, 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)

  • Han Bleichrodt

    (Erasmus School of Economics - Erasmus University Rotterdam, Department of Applied Economics - Erasmus University Rotterdam)

  • 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, CREM - Centre de recherche en économie et management - UNICAEN - Université de Caen Normandie - NU - Normandie Université - UR - Université de Rennes - CNRS - Centre National de la Recherche Scientifique)

  • Dennie van Dolder

    (UON - University of Nottingham, UK)

Abstract

We propose a simple, parameter‐free method that, for the first time, makes it possible to completely observe Tversky and Kahneman's (1992) prospect theory. While methods existed to measure event weighting and the utility for gains and losses separately, there was no method to measure loss aversion under ambiguity. Our method allows this and thereby it can measure prospect theory's entire utility function. Consequently, we can properly identify properties of utility and perform new tests of prospect theory. We implemented our method in an experiment and obtained support for prospect theory. Utility was concave for gains and convex for losses and there was substantial loss aversion. Both utility and loss aversion were the same for risk and ambiguity, as assumed by prospect theory, and sign‐comonotonic trade‐off consistency, the central condition of prospect theory, held.

Suggested Citation

  • Mohammed Abdellaoui & Han Bleichrodt & Olivier L’haridon & Dennie van Dolder, 2016. "Measuring Loss Aversion under Ambiguity: A Method to Make Prospect Theory Completely Observable," Post-Print halshs-01242616, HAL.
  • Handle: RePEc:hal:journl:halshs-01242616
    DOI: 10.1007/s11166-016-9234-y
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hal:journl:halshs-01242616. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.