Abstract:Using a generalized linear model to determine the claim frequency of auto insurance is a key ingredient in non-life insurance research. Among auto insurance rate-making models, there are very few considering auto types. Therefore, in this paper we are proposing a model that takes auto types into account by making an innovative use of the auto burden index. Based on this model and data from a Chinese insurance company, we built a clustering model that classifies auto insurance rates into three risk levels. The claim frequency and the claim costs are fitted to select a better loss distribution. Then the Logistic Regression model is employed to fit the claim frequency, with the auto burden index considered. Three key findings can be concluded from our study. First, more than 80% of the autos with an auto burden index of 20 or higher belong to the highest risk level. Secondly, the claim frequency is better fitted using the Poisson distribution, however the claim cost is better fitted using the Gamma distribution. Lastly, based on the AIC criterion, the claim frequency is more adequately represented by models that consider the auto burden index than those do not. It is believed that insurance policy recommendations that are based on Generalized linear models (GLM) can benefit from our findings.

This is the supplemental file of the paper. The supplement is written for the authors, the reviewers, and the readers to check the correctness of the derivations and to replicate the results.

The impact of environmental regulations (ER) on haze pollution control has been continuously debated in the field of sustainable development. This paper explores the direct and indirect threshold effects of ER on haze pollution, and five underlying mechanisms—technological innovation (TI), industrial structure (IS), foreign direct investment (FDI), urbanization (UR), and electricity consumption (EC)—are adopted to investigate the indirect threshold effects. Panel data, over the period 2008–2018, of 284 Chinese cities were used and the threshold effects were predicted endogenously based on the panel smooth transition regression (PSTR) model. The results showed the following: (1) For the direct threshold effect, there exists a U-shaped relationship between ER and haze pollution. ER significantly reduced haze pollution when ER < 38.86 due to “cost effects”. However, ER increased haze pollution after the threshold owing to the “green paradox”, which was not significant. (2) For the indirect threshold effect, when TI = 0.37, IS = 39.61, FDI = 7.25, and UR = 42.86, the relationships between ER and haze pollution changed. The changes and corresponding reasons for the indirect threshold effects are discussed in detail. (3) After a comprehensive analysis, the threshold effects have obvious regional distribution characteristics and internal connections. Finally, based on the results, it is essential for governments to enact appropriate environmental regulatory policies and enhance inter-regional synergies in environmental governance.

No abstract

The relationship between haze pollution and insurance development is investigated based on the concentration of PM2.5 of 268 Chinese cities during 2009~2018. Subsequently, the effect of haze pollution on the development of insurance and the underlying mechanisms are also explored. The regional governance of haze pollution and its impact on insurance development is estimated by using a unified framework of two-stage least squares. The machine learning method-elastic network is adopted to filter the control variables and avoid multi-collinearity. The results show that haze pollution has an adverse effect on the insurance development through two important underlying mechanisms, residents’ emotions and economic development. Haze pollution affects residents’ emotions, and the impact coefficient is approximately equal to -0.18, which further inhibits residents’ participation in insurance. Moreover, pollution restricts residents’ budgets by hindering economic development, the impact coefficient is about -0.07, thus, the development of insurance is suppressed. These two negative effects exhibit regional variations, which gradually attenuate from eastern, western to the Chinese central region. The regional governance has a positive effect on haze pollution with the coefficient of -0.07, while impact coefficient of haze pollution on insurance development decreases to -0.02. The policy implication is that government supervision can formulate reasonable environmental and insurance policies based on the heterogeneity of regional development to alleviate haze pollution and promote insurance development.