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Is Imprecise Knowledge Better than Conflicting Expertise? Evidence from Insurers’ Decisions in the United States

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Abstract

Testing whether risk professionals (here insurers) behave differently under risk and ambiguity when they cover catastrophic risks (floods and earthquakes) and non-catastrophic risks (fires), this paper reports the results of the first field experiment in the United States designed to distinguish two sources of ambiguity: imprecise ambiguity (outside experts agree on a range of probability, but not on any point estimate) versus conflict ambiguity (each expert group provides precise probability estimates which differ from one group to another). Insurers charge higher premiums when faced with ambiguity than when the probability of a loss is well specified. Furthermore they charge more for conflict ambiguity than imprecise ambiguity for flood and hurricane hazards, but less so in the case of fire. The source of ambiguity also impacts causal inferences insurers make to reduce their uncertainty.

Suggested Citation

  • Laure Cabantous & Denis Hilton & Howard Kunreuther & Erwann Michel-Kerjan, 2010. "Is Imprecise Knowledge Better than Conflicting Expertise? Evidence from Insurers’ Decisions in the United States," ICBBR Working Papers 7, International Centre for Behavioural Business Research.
  • Handle: RePEc:bbr:workpa:7
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    Citations

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    Cited by:

    1. Jim Engle-Warnick & Sonia Laszlo, 2017. "Learning-by-doing in an ambiguous environment," Journal of Risk and Uncertainty, Springer, vol. 55(1), pages 71-94, August.
    2. Marielle Brunette & Laure Cabantous & Stéphane Couture & Anne Stenger, 2013. "The impact of governmental assistance on insurance demand under ambiguity: a theoretical model and an experimental test," Theory and Decision, Springer, vol. 75(2), pages 153-174, August.
    3. 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.
    4. Keck, Steffen & Diecidue, Enrico & Budescu, David V., 2014. "Group decisions under ambiguity: Convergence to neutrality," Journal of Economic Behavior & Organization, Elsevier, vol. 103(C), pages 60-71.
    5. repec:pal:gpprii:v:42:y:2017:i:2:d:10.1057_s41288-016-0004-5 is not listed on IDEAS
    6. 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.
    7. Théodora Dupont-Courtade, 2012. "Insurance demand under ambiguity and conflict for extreme risks : Evidence from a large representative survey," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00718642, HAL.
    8. Huang, Rachel J. & Huang, Yi-Chieh & Tzeng, Larry Y., 2013. "Insurance bargaining under ambiguity," Insurance: Mathematics and Economics, Elsevier, vol. 53(3), pages 812-820.
    9. repec:eee:ejores:v:266:y:2018:i:3:p:1175-1188 is not listed on IDEAS
    10. repec:eee:insuma:v:77:y:2017:i:c:p:14-23 is not listed on IDEAS
    11. Théodora Dupont-Courtade, 2012. "Insurance demand under ambiguity and conflict for extreme risks : Evidence from a large representative survey," Post-Print halshs-00718642, HAL.
    12. Michel-Kerjan, Erwann & Raschky, Paul A., 2011. "The effects of government intervention on the market for corporate terrorism insurance," European Journal of Political Economy, Elsevier, vol. 27(S1), pages 122-132.
    13. Howard Kunreuther & Geoffrey Heal & Myles Allen & Ottmar Edenhofer & Christopher B. Field & Gary Yohe, 2012. "Risk Management and Climate Change," NBER Working Papers 18607, National Bureau of Economic Research, Inc.
    14. Jean Desrochers & J. Francois Outreville, 2013. "Uncertainty, Ambiguity and Risk Taking: an experimental investigation of consumer behavior and demand for insurance," ICER Working Papers 10-2013, ICER - International Centre for Economic Research.
    15. Huang, Yi-Chieh & Tzeng, Larry Y. & Zhao, Lin, 2015. "Comparative ambiguity aversion and downside ambiguity aversion," Insurance: Mathematics and Economics, Elsevier, vol. 62(C), pages 257-269.
    16. Aurélien Baillon & Laure Cabantous & Peter Wakker, 2012. "Aggregating imprecise or conflicting beliefs: An experimental investigation using modern ambiguity theories," Journal of Risk and Uncertainty, Springer, vol. 44(2), pages 115-147, April.

    More about this item

    Keywords

    Ambiguity; Source of Uncertainty; Insurance Pricing; Decision-Making;

    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

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