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The representative heuristic and catastrophe-related risk behaviors

Author

Listed:
  • Randy E. Dumm

    (Temple University)

  • David L. Eckles

    (University of Georgia)

  • Charles Nyce

    (Florida State University)

  • Jacqueline Volkman-Wise

    (Temple University)

Abstract

Building on the work by Volkman-Wise Journal of Risk and Uncertainty, 51, 267–290 (2015) and Dumm et al. (The Geneva Risk and Insurance Review, 42, 117–139 (2017), we examine behavioral aspects of risk through the representative heuristic’s impact on catastrophe-related probability assessment and insurance demand of Florida homeowners. The representative heuristic models individuals as underweighting prior probabilities and overweighting posterior probabilities, thereby overweighting the probability of a loss from a disaster after a disaster occurs. Using data for homeowners’ insurance purchases through Florida’s residual market over a time period (2003-2008) that includes a sub-period of many losses (2004-2005) and sub-period of few catastrophic losses (2003, 2006-2008), we find increases in demand at the individual policyholder level for coverage following losses. Also consistent with the representative heuristic, we find that the effect attenuates as the losses fade from memory. That is, the effect of losses on demand is much higher for more recent losses. We also are able to parameterize the representative heuristic model showing that individual policy holders overweight the probability of another catastrophic event occurring by nearly 50%, after one has occurred.

Suggested Citation

  • Randy E. Dumm & David L. Eckles & Charles Nyce & Jacqueline Volkman-Wise, 2020. "The representative heuristic and catastrophe-related risk behaviors," Journal of Risk and Uncertainty, Springer, vol. 60(2), pages 157-185, April.
  • Handle: RePEc:kap:jrisku:v:60:y:2020:i:2:d:10.1007_s11166-020-09324-7
    DOI: 10.1007/s11166-020-09324-7
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    References listed on IDEAS

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    Cited by:

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    2. Xiao Lin, 2020. "Risk awareness and adverse selection in catastrophe insurance: Evidence from California’s residential earthquake insurance market," Journal of Risk and Uncertainty, Springer, vol. 61(1), pages 43-65, August.
    3. Yingmei Tang & Huifang Cai & Rongmao Liu, 2022. "Will marketing strategies affect farmers’ preferences and willingness to pay for catastrophe insurance? Evidence from a choice experiment in China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(1), pages 1376-1389, January.
    4. Lu Fang & Lingxiao Li & Abdullah Yavas, 2023. "The Impact of Distant Hurricane on Local Housing Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 66(2), pages 327-372, February.
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    6. Shereen J. Chaudhry & Michael Hand & Howard Kunreuther, 2020. "Broad bracketing for low probability events," Journal of Risk and Uncertainty, Springer, vol. 61(3), pages 211-244, December.
    7. Menna Hassan & Nourhan Sakr & Arthur Charpentier, 2022. "Government Intervention in Catastrophe Insurance Markets: A Reinforcement Learning Approach," Papers 2207.01010, arXiv.org.

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    More about this item

    Keywords

    Natural disasters; Insurance demand; Catastrophic Risk; Risk beliefs; Heuristics;
    All these keywords.

    JEL classification:

    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • 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
    • G02 - Financial Economics - - General - - - Behavioral Finance: Underlying Principles
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies

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