Study Of Urbanization Progress Of Gansu Province On The Increase In Farmers’ Income

Urbanization is a great project of the21st century implemented by our nation. As a national policy, the process of urbanization is well responded and actively promoted by all regions. While the issue of farmers is most highly concerned. Accordingly, how to solve the problems of peasants and how to increase their income by the development of urbanization are particularly important. Urbanization of Gansu also develops rapidly, while the poverty of farmers is quite prominent. Therefore, it has great theoretical and practical significance to study how to increase farmers’ income by urbanization, which is in the context of a great rural labor surplus, a low farmers’ income and a continuously enlarging gap of farmers’income compared with the national average one.In this paper, how to increase farmers’ income of Gansu by urbanization is the object of study. First, a composite index is used to conduct a comprehensive measurement of the level of urbanization by adopting factor analysis and entropy method, meanwhile the fluctuation and structure of sources of famers’ income are deeply researched by data analysis; Then the positive and negative impacts of urbanization on famers’ income and the channels of increasing farmers’ income are theoretically analyzed; afterwards the long and short-term relationship between the urbanization and farmers’ income is analyzed using co-integration and error correction model; finally, Grey incidence analysis is used to evaluate the correlation degree and positive and negative relations between urbanization and the increase in farmers’ income. The result shows that the long and short-term relationship exists. In the long term, urbanization increases one unite, farmers’ income will increases2.4592unites; error correction coefficient is-0.1132. The five factors of urbanization and farmers’ income are all positively related, and that the correlative degree descends in an order of social life factor, economy factor, population and environment factor, space factor. Finally, corresponding suggestions are proposed.