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Demand for Windstorm Insurance Coverage and the Representative Heuristic

Author

Listed:
  • Randy E. Dumm

    (Fox School of Business, Temple University)

  • David L. Eckles

    (University of Georgia)

  • Charles Nyce

    (Florida State University)

  • Jacqueline Volkman-Wise

    (Fox School of Business, Temple University)

Abstract

With recent research suggesting a behavioral explanation for changes in demand for insurance (e.g., Volkman-Wise (2015)), we study homeowners’ demand for windstorm insurance in the wake of losses. In particular, we examine the representative heuristic’s impact on the demand for homeowners’ insurance, which provides coverage for windstorm losses, in Florida (U.S.). Under this paradigm, individuals underweight prior probabilities and overweight posterior probabilities. This results in an over (under)-weighting of the probability of a loss from a disaster in the event (absence) of a disaster. Using data for new homeowners’ insurance, purchases in Florida’s residual market between 2005 and 2007 (a period of high hurricane activity), we find, subsequent to losses, the demand for coverage limits and the number of policies sold both increase. Further, we find that this effect attenuates as the losses become further away in time. That is, more recent losses have a stronger effect on demand. This attenuation of the demand is also consistent with the representative heuristic.

Suggested Citation

  • Randy E. Dumm & David L. Eckles & Charles Nyce & Jacqueline Volkman-Wise, 2017. "Demand for Windstorm Insurance Coverage and the Representative Heuristic," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 42(2), pages 117-139, September.
    • Handle: RePEc:pal:genrir:v:42:y:2017:i:2:d:10.1057_s10713-017-0021-8
    DOI: 10.1057/s10713-017-0021-8
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    References listed on IDEAS

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    Cited by:

    1. 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.
    2. Xiao Lin, 2020. "Feeling Is Believing? Evidence From Earthquake Shaking Experience and Insurance Demand," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 87(2), pages 351-380, June.
    3. Chloe H. Lucas & Kate I. Booth & Carolina Garcia, 2021. "Insuring homes against extreme weather events: a systematic review of the research," Climatic Change, Springer, vol. 165(3), pages 1-21, April.
    4. Shinichi Kamiya & Noriyoshi Yanase, 2019. "Learning from extreme catastrophes," Journal of Risk and Uncertainty, Springer, vol. 59(1), pages 85-124, August.
    5. Benjamin L. Collier & Marc A. Ragin, 2020. "The Influence of Sellers on Contract Choice: Evidence from Flood Insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 87(2), pages 523-557, June.
    6. 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.

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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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