| China’s life insurance business has achieved rapid growth since 1982’s recovery operation. The premium income reached 942.6 billion Yuan in 2013, which has increased by 782 times more than it in 1989.And the market share that life insurance premium accounted for the insurance industry has risen from 38.2 percent in 1989 to 50.8 percent in 2013. Life insurance industry propped up half of the insurance industry. Life insurance industry made its own progress, at the same time, it also played an important role in promoting sustainable economic development and maintaining the stability of our society. We all knew that life insurance industry could not develop without the macro-environment of population, while population aging is one of China’s present and future trends in population growth. Due to the decline in fertility, mortality and the prolonged average life expectancy, China has entered the aging society in 2001.According to the relevant documents released by the National Aging Committee, the aging process in China is in a period of rapid aging. It is predicted that by 2050, the number of elderly population in China will be more than 400 million by 2050, accounting for more than 30% of the total population. The grim situation of population aging will have a profound impact on the economy and society. Therefore, this paper take population aging and life insurance demand closely together to explore the impact of population aging on the life insurance form two aspects which include total demand and demand structure.Firstly,this paper introduces the related concepts about life insurance demand, population aging, and the development of both, which can make a basis for further research. Secondly, this paper makes an qualitative analysis of aging population’s influence on the total life insurance demand and demand structure. In this chapter,the content is divided into two parts. The first part describes the theory of life insurance needs, then analyzes the impact of population aging on the total demand for life insurance from three perspectives. The second part describes the consumption theory related to the life insurance demand structure changes, and then analyzes the impact of population aging on the structure of life insurance demand from two aspects which include life insurance demand’s motive of elderly population in the background of aging and life insurance’s specific functions. Thirdly, the paper carries out corresponding empirical research. Correspondingly, this content divides into two parts. The first part sets up static panel and dynamic panel data model to explore the influence of population aging on the total demand of life insurance. The dynamic panel model take regional differences and the demand ineitia of life insurance into account. The second part constructs panel gray correlation model and panel data regression model to analyze the impact of population aging on the structure of the life insurance needs. Finally, the article gives conclusions and policy recommendations.Study reach the following two conclusions:(1) both static and dynamic panel model estimation results indicate that the combined effects of population aging on the life insurance demand is significantly positive. Dynamic panel model’s estimation results also indicate that life insurance density lag is significant, which means that the demand for life insurance has inertia. After taking regional dummy variables to the dynamic model, the results show that population aging’s effect on the total life insurance needs has regional difference among the eastern, central, western. The aging population’s influence in eastern, central is greater than it in the western, whereas the eastern and the western was not significantly different, the central and western is significantly different. (2) Panel gray correlation results indicate that besides Shanghai, in the other areas the correlation between the ratio over the age of 65 and the ratio of investment-type insurance premiums is larger than the correlation between the ratio over the age of 65 and the ratio of guarantee-type insurance premiums. Panel data regression model results show that the increasing number of elderly people will promote demand of both type insurance, but the increase in demand for investment-type life insurance is larger than guarantee-type life insurance. Overall, the two methods basically have similar results. In summary, the conclusion of the study is of great significance for our country’s life insurance business. |
