IDEAS home Printed from https://ideas.repec.org/a/wly/iecrev/v59y2018i4p2107-2131.html
   My bibliography  Save this article

Zooming In On Ambiguity Attitudes

Author

Listed:
  • Aurélien Baillon
  • Aysil Emirmahmutoglu

Abstract

Empirical studies of ambiguity attitudes to date have focused on events of moderate likelihood. Extrapolation to rare events requires caution. In an Ellsberg‐like experiment with very unlikely events, we measured ambiguity attitudes with neither assumptions on subjects' beliefs nor restrictions to specific ambiguity models. Very unlikely events were overweighted, being weighted more strongly in isolation than when part of larger events. Using latent profile analysis, we classified the subjects in terms of deviations from ambiguity neutrality. One third behaved close to ambiguity neutrality. The others exhibited overweighting of rare events. Such behavior can lead to money‐pump situations.

Suggested Citation

  • Aurélien Baillon & Aysil Emirmahmutoglu, 2018. "Zooming In On Ambiguity Attitudes," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 59(4), pages 2107-2131, November.
  • Handle: RePEc:wly:iecrev:v:59:y:2018:i:4:p:2107-2131
    DOI: 10.1111/iere.12331
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/iere.12331
    Download Restriction: no

    File URL: https://libkey.io/10.1111/iere.12331?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lu Li & Richard Peter, 2021. "Should we do more when we know less? The effect of technology risk on optimal effort," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 88(3), pages 695-725, September.
    2. Masaki Aoyagi & Takehito Masuda & Naoko Nishimura, 2021. "Strategic Uncertainty and Probabilistic Sophistication," ISER Discussion Paper 1117, Institute of Social and Economic Research, Osaka University.
    3. Cathleen Johnson & Aurélien Baillon & Han Bleichrodt & Zhihua Li & Dennie Dolder & Peter P. Wakker, 2021. "Prince: An improved method for measuring incentivized preferences," Journal of Risk and Uncertainty, Springer, vol. 62(1), pages 1-28, February.
    4. Peter, Richard & Ying, Jie, 2020. "Do you trust your insurer? Ambiguity about contract nonperformance and optimal insurance demand," Journal of Economic Behavior & Organization, Elsevier, vol. 180(C), pages 938-954.

    More about this item

    Statistics

    Access and download statistics

    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:wly:iecrev:v:59:y:2018:i:4:p:2107-2131. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/deupaus.html .

    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.