The Factors Analysis of Regional Differences on China’s Insurance Density
|Keywords||Insurance density Regional differences Causality test Panel Data model|
Since the reform and opening up, the insurance industry which has maintained a rapid growth has become a part of our national system,and whose impact to the national economy has growing. However, regional insurance industry is great different from the absolute level of development and the relative level of development. After China joined the WTO in 2001,China insurance has been from the very beginning of the limited opening to today’s fully opened and more and more foreign insurance companies enter the Chinese market. That makes domestic insurance industry to face fierce market competition. Therefore, studying the difference of factors of affecting regional insurance industry and the using the differences to develop regional insurance industry has a certain practical significance for the development of China’s insurance industry.This article attempts to divide the national into eastern, central, and western by geography, and use Panel Data Model to analysis different factors of area insurance density. The major content of this research includes:(1)Expounding insurance density of sources and related indicators of the theory, observing their differences in insurance density, and analysis the factors of affecting the development of China’s insurance industry in theory to provide theoretical basis for quantitative analysis.(2)Choosing representative indicators from the economic, population and social security to carry out causality test with insurance density, then using the results of causality test and Panel Data model to study the factors of affected national and area insurance density and analysis their distraction.(3) Providing some recommendations to increase area insurance density according to the results of the above analysis.The difference of factors of affecting area insurance density are from three aspects: the economic aspects’difference are per-capita GDP and per capita consumption level difference from high to low; the population aspects’difference are educated, urban population and age structure from high to low; Social security difference is per-capita level of social security.