Mortality risk of heat wave between different groups and cities and the corresponding insurance ratemaking

doi:10.12006/j.issn.1673-1719.2018.046

Abstract

Abstract:

Under the background of global warming, heat wave events have frequently occurred around the world and increased the mortality risk greatly. Based on the daily meteorological data from 1951 to 2015 and daily mortality data from 2007 to 2013 in three cities (Nanjing, Chongqing, Guangzhou), a heat wave intensity index was firstly designed to quantify the heat waves, and then a distributed lag non-linear model (DLNM) was used to develop the vulnerability models of population under the heat wave events. Finally, Monte Carlo simulation method was run to assess the probabilistic heat wave risk and rated the premiums for heat wave life insurance. The results show that, the heat wave mortality risks and pure premium rates for the elder are both 9 to 28 times that of the young and the pure premium rates are inversely proportional to the level of socioeconomic development. The results in this study can provide guidance for developing weather index-based individual life/health insurance products and give support for the government to adopt comprehensive risk management measures to reduce public health risks.

Key words: Heat wave, Mortality risk, Distributed lag non-linear model (DLNM), Index insurance

Ling-Yan ZHANG,Zhao ZHANG,Bin HOU. Mortality risk of heat wave between different groups and cities and the corresponding insurance ratemaking[J]. Climate Change Research, 2018, 14(5): 475-484.

Figures/Tables 10

Fig. 1 Location of the study areas

Table 1 Summary mortality, weather statistics and social-economic data from 2007 to 2013 in the study areas

Fig. 2 Technical flow chart of ratemaking for heat wave life insurance

Table 2 The localized heat wave definition and the parameters of the probability distribution for heat wave in each study area

Fig. 3 Annual frequency and HWII of heat waves identified from 1951 to 2015 in each study area: (a) box plot for annul frequency of heat waves, (b) box plot for intensity index of heat waves. (The boxes present the 25- to 75-percentile, whiskers present the 10- to 90-percentile, hollow square and thick dash in boxes are mean and median values, and black dots are outliers)

Fig. 4 Annual frequency and annual average intensity index of heat waves from 1951 to 2015 in each study area

Fig. 5 Vulnerability curves for different age groups under heat wave events in each study area (the shaded areas represent 95% confidence intervals)

Fig. 6 Exceeding probability curves of stochastic 10000 years’ LCR for different age groups in each study area (The gray areas represent 95% confidence intervals)

Table 3 Pure premiums and risk premium loadings under different return periods for different age groups in each study area (The numbers in parentheses represent 95% confidence intervals)

Fig. 7 Pure premiums for different age groups and average per capita GDP from 2007 to 2013 in each study area

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