Extreme analysis of typhoons disaster in mainland China with insurance management

Hu, Kaihao, Wang, Ruojin, Xu, Jingyi, Constantinescu, Corina ORCID: 0000-0002-5219-3022, Chen, Ying and Ling, Chengxiu (2024) Extreme analysis of typhoons disaster in mainland China with insurance management. International Journal of Disaster Risk Reduction, 106. p. 104411.

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Official URL: http://dx.doi.org/10.1016/j.ijdrr.2024.104411

Abstract

Due to climate change, typhoons, especially extreme typhoons, are becoming more intense and causing ascending financial losses. A majority of previous studies on typhoon economic losses over a period of time considered all types of typhoon rather than the extreme typhoons. This study focuses on the risk management of extreme typhoons by establishing the compensation mechanism and a typhoon-specific insurance product. The annual maximum losses of typhoons is first modelled by generalized extreme value distribution (GEV) under the Extreme Value Theory (EVT). The prediction of unexpected economic losses is then obtained via VaR and CVaR for the compensation mechanism among individual, insurance company and government. To analyse the typhoon vulnerability of 11 Chinese coastal provinces (or municipalities), the Multiple-Criteria Decision Making (MCDM) method, combining Analytic Hierarchy Process (AHP) based Grey Rational Analysis (GRA) and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), is applied for evaluating the typhoon vulnerability of these regions for 2022. The nationwide best estimates for typhoon reserves on the basis of insurance compensation mechanism is therefore calculated and will be allocated to these 11 provinces according to the vulnerability ranking obtained via MCDM method. The findings indicate that the top three provinces (Guangdong, Fujian and Zhejiang) in typhoon vulnerability rankings are also with the highest losses and frequency in practice, while Hebei has the highest insurance premium.

Item Type:	Article
Divisions:	Faculty of Science and Engineering > School of Physical Sciences
Depositing User:	Symplectic Admin
Date Deposited:	11 Apr 2024 07:33
Last Modified:	12 Apr 2024 11:47
DOI:	10.1016/j.ijdrr.2024.104411
Open Access URL:	https://www.sciencedirect.com/science/article/pii/...
Related URLs:	Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3180271