The Research On The Relationship Between Urbanization And The Tertiary Industry In Jiangsu Province

Generally speaking, the level of urbanization of a country or a region is an important symbol of the comprehensive development level of its economy. Under the background of economic globalization, the world economy is changing from the industrial economy to the service economy, and the tertiary industry is becoming more and more important. General experience in the world shows that the direct reason of urbanization development is the industrialization, and when the industrialization development reaches a certain stage, the tertiary industry will replace the industrialization as the dominant driving force to urbanization. And the development of urbanization will also affect the development of the third industry.Recently the economy in China gets into the "new normal", an important feature of the "new normal" is the tertiary industry will exceed the second industry as the subject of economic development. The 2012 annual data in Jiangsu Province shows the level of urbanization in the city is 63%, and the average national level is 52.57%, the level of urbanization in Jiangsu province has exceeded the national average of ten percentage points in the year; and also in the 2012 year, the development level of third industry in Jiangsu province is 43.5%, lower than the national average of 44.6% year. This reflects the development of the third industry in Jiangsu province is too slow and the third industry and urbanization development is not coordinate. So that there is some practical significance to research on the relationship between urbanization and the third industry in Jiangsu province under the background of "new normal".In the paper, at first we expound the connotation of urbanization and the third industry, and analyze the relationship between them in theory. Then we analyze the present situation of them, and test the relationship between them by empirical research method. In the empirical study, this paper uses regression analysis, cointegration test, Grainger causality test, error correction model, the method of panel data regression and the grey correlation analysis. In the end, the paper puts forward some conclusions and policy suggestions.