IDEAS home Printed from https://ideas.repec.org/p/mse/cesdoc/12020.html
   My bibliography  Save this paper

Insurance demand under ambiguity and conflict for extreme risks: Evidence from a large representative survey

Author

Abstract

This paper investigates how the general public behaves when confronted with low probability events and ambiguity in an insurance context. It reports the results of a questionnaire completed by a large representative sample of the French population that aims at separating attitudes toward risk, imprecision and conflict and at determining if there is a demand for ambiguous and extreme event risks. The data show a strong distinction between two aspects of the problem: the decision of purchasing insurance and the willingness to pay. In the decision to insure, more than 25% of the respondents refuse to buy insurance and people are more willing to insure in a risky situation than in an ambiguous one. This certain taste for risk can be explained by the respondents' observable characteristics. In addition, it highlights a lack of confidence in the insurance markets. When it comes to willingness to pay, people exhibit ambiguity seeking behaviors. They are willing to pay more under risk than under ambiguity (embracing here imprecision and conflict), revealing that people consider ambiguous situations as inferior. Furthermore, respondents behave differently under imprecision and conflict. They exhibit a preference for consensual information and dislike conflicts. However, the willingness to pay is poorly correlated with observable characteristics

Suggested Citation

  • Théodora Dupont-Courtade, 2012. "Insurance demand under ambiguity and conflict for extreme risks: Evidence from a large representative survey," Documents de travail du Centre d'Economie de la Sorbonne 12020, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
  • Handle: RePEc:mse:cesdoc:12020
    as

    Download full text from publisher

    File URL: ftp://mse.univ-paris1.fr/pub/mse/CES2012/12020.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Johanna Etner & Meglena Jeleva & Jean-Marc Tallon, 2009. "Decision theory under uncertainty," Documents de travail du Centre d'Economie de la Sorbonne 09064, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Nov 2009.
    2. Sujoy Chakravarty & Jaideep Roy, 2009. "Recursive expected utility and the separation of attitudes towards risk and ambiguity: an experimental study," Theory and Decision, Springer, vol. 66(3), pages 199-228, March.
    3. Kunreuther, Howard & Novemsky, Nathan & Kahneman, Daniel, 2001. "Making Low Probabilities Useful," Journal of Risk and Uncertainty, Springer, vol. 23(2), pages 103-120, September.
    4. Laure Cabantous & Denis Hilton & Howard Kunreuther & Erwann Michel-Kerjan, 2011. "Is imprecise knowledge better than conflicting expertise? Evidence from insurers’ decisions in the United States," Journal of Risk and Uncertainty, Springer, vol. 42(3), pages 211-232, June.
    5. McClelland, Gary H & Schulze, William D & Coursey, Don L, 1993. "Insurance for Low-Probability Hazards: A Bimodal Response to Unlikely Events," Journal of Risk and Uncertainty, Springer, vol. 7(1), pages 95-116, August.
    6. Cohen, Michele & Jaffray, Jean-Yves & Said, Tanios, 1987. "Experimental comparison of individual behavior under risk and under uncertainty for gains and for losses," Organizational Behavior and Human Decision Processes, Elsevier, vol. 39(1), pages 1-22, February.
    7. Gajdos, T. & Hayashi, T. & Tallon, J.-M. & Vergnaud, J.-C., 2008. "Attitude toward imprecise information," Journal of Economic Theory, Elsevier, vol. 140(1), pages 27-65, May.
    8. Carmela Di Mauro & Anna Maffioletti, 2001. "The Valuation of Insurance under Uncertainty: Does Information about Probability Matter?," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 26(3), pages 195-224, December.
    9. Gilboa, Itzhak & Schmeidler, David, 1989. "Maxmin expected utility with non-unique prior," Journal of Mathematical Economics, Elsevier, vol. 18(2), pages 141-153, April.
    10. Luigi Guiso & Tullio Jappelli, 1998. "Background Uncertainty and the Demand for Insurance Against Insurable Risks," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 23(1), pages 7-27, June.
    11. Thibault Gajdos & Jean-Christophe Vergnaud, 2013. "Decisions with conflicting and imprecise information," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 41(2), pages 427-452, July.
    12. Peter Klibanoff & Massimo Marinacci & Sujoy Mukerji, 2005. "A Smooth Model of Decision Making under Ambiguity," Econometrica, Econometric Society, vol. 73(6), pages 1849-1892, November.
    13. repec:hal:wpaper:hal-00443075 is not listed on IDEAS
    14. Wakker,Peter P., 2010. "Prospect Theory," Cambridge Books, Cambridge University Press, number 9780521765015, December.
    15. Einhorn, Hillel J & Hogarth, Robin M, 1986. "Decision Making under Ambiguity," The Journal of Business, University of Chicago Press, vol. 59(4), pages 225-250, October.
    16. Dobbs, Ian M, 1991. "A Bayesian Approach to Decision-Making under Ambiguity," Economica, London School of Economics and Political Science, vol. 58(232), pages 417-440, November.
    17. Clare Chua Chow & Rakesh Sarin, 2002. "Known, Unknown, and Unknowable Uncertainties," Theory and Decision, Springer, vol. 52(2), pages 127-138, March.
    18. Kahn, Barbara E & Sarin, Rakesh K, 1988. " Modeling Ambiguity in Decisions under Uncertainty," Journal of Consumer Research, Oxford University Press, vol. 15(2), pages 265-272, September.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Ambiguity; imprecision; conflict; decision making; extreme risk; insurance demand; willingness to pay;

    JEL classification:

    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:mse:cesdoc:12020. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Lucie Label). General contact details of provider: http://edirc.repec.org/data/cenp1fr.html .

    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.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.