Cointegration Analysis And GM(1,1) Grey Prediction Of Life Insurance Premium Income

With the gradual recovery of insurance business in China from 1978,the insurance industry has witnessed a rapid development.The domestic premium income of life insurance is also rapidly increasing year by year.Premium income is the most important source of income for the insurance industry.The amount of premium income plays a crucial role in the insurance company's business decision-making.At the same time,it can also reflect the level of development of life insurance and the demand for life insurance in a country or region to a certain extent.Based on this,this paper is devoted to studying the influence factors and trends of the life insurance premium income in China.The main contents of this paper are as follows.Firstly,it introduces the research background and significance,domestic and foreign literature review,logical thinking and structure arrangement.Secondly,taking the life insurance premium income in China as the research object,this paper chooses the annual related data from 1997 to 2016.Then combining the existing research,the main macroscopic factors affecting the life insurance premium income in our country is analyzed qualitatively.Thirdly,using the cointegration theory's methods to quantitatively analyze the impact of various variables on life insurance premium income.The Granger test is used to determine the causality between variables.Fourthly,the most common GM(1,1)model in the grey forecasting model is applied to the prediction of life insurance premium income in China,and the data from 1997 to 2016 in China are fitted.And make predictions on life insurance premium income in the next five years.The results show that:1.There are long-term equilibrium relationships between GDP,per capita disposable income of urban households,year-end balance of urban and rural residents'RMB savings deposits,population and mortality,and life insurance premium income in China.And all of them have a positive effect to the premium income.2.According to the Granger causality test,the above-mentioned factors other than the mortality rate of the population all have a strong single causal relationship with the life insurance premium income.3.The fitting effect of the GM(1,1)model passes the post-inspection difference test and the grey relational degree test,and the conclusion that the accuracy is one level is obtained.Through the forecast of the next five years,China's life insurance premium income still shows an upward trend,which means that the development of China's life insurance industry will continue to progress in the future.