Empirical Analysis Of The Influence Factors Of Urbanization In Our Country

Urbanization has become a world-scale trends in the Western developed countries as early as the Industrial Revolution, The Industrial Revolution stimulates the process of urbanization. China, due to historical issues, missed the opportunity for the Industrial Revolution, after the founding of New China, the efforts of China’s industrial development help to increase the level of urbanization improvement, but compared with the same level of developing countries such as Malaysia, the Philippines and other countries, the level of urbanization is still low.With the international financial crisis in 2008, the bonuses in population and resources in China tend to be exhausted and the support of the exported-economy experiences an unprecedented blow and tends to be the end, the Chinese government began to look for a new opportunity to promote the steady growth of China’s economy, at the same time, vigorously promoting the urbanization is recognized as the engine of future economic growth, Thus, the researches on urbanization become hotter.Nowadays, urbanization research including theoretical research and empirical research has made certain progress, but there is little study of the factors that influence the urbanization.In this paper,we use the panel data in 31 provinces of municipalities and autonomous regions from 2001 to 2011 to continue the study so that we can find the factors influencing the urbanization.So this paper is conducive to the study on urbanization and provides the government with theoretical guidance when she makes some policy.There are two ways in innovation,one is about the variables that choosen.The study is engaged from the level of economic development, population quality and industrial structure by choosing real GDP per capital,level of education and the ratio of the number of practioners in the secondary industry and tertiary-industry as indexes,so that factors affecting urbanization are analyzed. The other one is the model we use. we establish the panel vector autoregression (PVAR) model which has the advantages of both panal data and the model of VAR and is suitable for handling the relationship of between-endogenous variables and further analysis of the dynamic relationship among the choosen various variables.