Evaluation of Expected Insurance Returns in Extreme Weather Based on CRITIC and Generalized Extreme Value Distribution Methods
DOI:
https://doi.org/10.62051/z1pwrm83Keywords:
Extreme weather; insurance; CRITIC method; Generalized Extreme Value (GEV) distribution method.Abstract
The frequency of extreme weather events has become a powerful catalyst for huge economic losses. Payouts for natural disasters have increased significantly, leading to a rapid rise in premium rates, and the phenomenon poses a serious challenge to the profitability of insurance companies. In order to specifically study the impact of extreme weather on the calculation of the expected profit that an insurance company can make from underwriting a policy for a specific landmass, and thus to assess the applicability of insurance in a certain region, this paper, based on the data of economic losses due to extreme weather events in five continents from the EM-DAT database. Using the CRiteria Importance Through Intercriteria Correlation (CRITIC) method and the Generalized Extreme Value (GEV) distribution method, we build a model for assessing the expected profit from insurance and verify the applicability of the model through sensitivity analysis. Finally, we provide a reference for insurance companies' underwriting strategies, a probabilistic assessment for property owners to insure their properties, and a reference suggestion for communities to enhance their extreme weather risk tolerance.
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[1] GUO Xingxu. Research on the impact of extreme weather events on agricultural production in Hubei[J]. Rural Economy and Science and Technology,2018,29(13):197-198
[2] Wagner, K.R.H. Designing insurance for climate change. Nat. Clim. Chang. 12, 1070–1072 (2022).
[3] Gourevitch, J.D., Kousky, C., Liao, Y.(. et al. Unpriced climate risk and the potential consequences of overvaluation in US housing markets. Nat. Clim. Chang. 13, 250–257 (2023).
[4] WEI Hualin,WU Lianqiang. Weather index insurance and sustainable development of agricultural insurance[J]. Finance and Trade Economics,2010,(03):5-12+136.
[5] TIAN Zhenhua,WU Xuemin,QIU Jian. Difficulties and countermeasures of agricultural insurance operation under extreme weather[J]. Banker,2022,(02):110-112+7.
[6] Kati K ,Daniel O ,Christian H , et al. Insurance Against Extreme Weather Events: An Overview[J].Review of Economics,2021,72(2):71-95.
[7] Arsu, Talip. Assessment of Macroeconomic Performances and Human Development Levels of BRICS and MINT Countries Using CRITIC and COPRAS Methods[J]. A Refereed Monthly International Journal of Management, 2022, 14(04): 1-19.
[8] Fiedler, T., Pitman, A.J., Mackenzie, K. et al. Business risk and the emergence of climate analytics. Nat. Clim. Chang. 11, 87–94 (2021).
[9] Gonga, Mathews Adera. Determinants of Financial Performance of Insurance Firms: a Survey of Selected Insurance Firms in Nairobi County[J]. Strategic Journal of Business & Change Management, 2017.
[10] Yan Su. Research on risk differential rates of deposit insurance system in China[J]. Journal of Shanghai University of International Business and Economics,2019,26(01):97-107.
[11] Kunreuther H ,Lyster R .The role of public and private insurance in reducing losses from extreme weather events and disasters[J].Asia Pacific Journal of Environmental Law,2016,19(1):29-54.
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