Disaster probability, optimal government expenditure for disaster prevention and mitigation, and expected economic growth

Sci Total Environ. 2020 Mar 20:709:135888. doi: 10.1016/j.scitotenv.2019.135888. Epub 2019 Dec 16.

Abstract

As global climate warms, the occurrence frequency and loss of natural disaster are both increasing, posing a great threat to the sustainable development of human society. One of the most important approaches of disaster management is to prevent disaster and reduce disaster loss through fiscal expenditure of government; however, the optimal proportion of expenditure for disaster prevention and mitigation has always been a difficult issue that people concern about. First, this paper, after considering the impact of disaster on human capital, established a resident-manufacturer-government decision making model which contains the probability of disaster, and then solved the optimal proportion of government expenditure for disaster prevention and reduction as well as the expected economic growth rates under different conditions. Second, through numerical simulation method, this paper studied the impacts of such factors as coefficient of risk aversion and elasticity coefficient of substitution on the optimal proportion of disaster prevention and reduction expenditure. Third, through constant elasticity of substitution (CES) production function and ridge regression method, this paper verified the applicability of the proposed model with the data of the expenditures for disaster prevention and mitigation of Hunan Province in 2014. Finally, this paper summarized the research results and put forward corresponding suggestions on policy. The theoretical model proposed in this paper enriches the related researches of disaster economics, and the conclusions of empirical analysis can provide government departments with useful reference for the practice of disaster prevention and mitigation.

Keywords: Expected economic growth rate; Government expenditure for disaster prevention and mitigation; Probability of disaster; Residents-manufacturer-government decision model.