Dynamic modeling of public and private decision-making for hurricane risk management including insurance, acquisition, and mitigation policy

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      <subfield code="a">Dynamic modeling of public and private decision-making for hurricane risk management including insurance, acquisition, and mitigation policy</subfield>
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      <subfield code="a">We develop a computational framework for the stochastic and dynamic modeling of regional natural catastrophe losses with an insurance industry to support government decision-making for hurricane risk management. The analysis captures the temporal changes in the building inventory due to the acquisition (buyouts) of high-risk properties and the vulnerability of the building stock due to retrofit mitigation decisions. The system is comprised of a set of interacting models to (1) simulate hazard events; (2) estimate regional hurricane-induced losses from each hazard event based on an evolving building inventory; (3) capture acquisition offer acceptance, retrofit implementation, and insurance purchase behaviors of homeowners; and (4) represent an insurance market sensitive to demand with strategically interrelated primary insurers. This framework is linked to a simulation-optimization model to optimize decision-making by a government entity whose objective is to minimize region-wide hurricane losses. We examine the effect of different policies on homeowner mitigation, insurance take-up rate, insurer profit, and solvency in a case study using data for eastern North Carolina. Our findings indicate that an approach that coordinates insurance, retrofits, and acquisition of high-risk properties effectively reduces total (uninsured and insured) losses.

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      <subfield code="a">Toma de decisiones</subfield>
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      <subfield code="g">06/06/2022 Tomo 25 Número 2 - 2022 , p. 173-199</subfield>
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      <subfield code="t">Risk management & insurance review</subfield>
      <subfield code="d">Malden, MA : The American Risk and Insurance Association by Blackwell Publishing, 1999-</subfield>
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