Font Size: a A A

Study On The Spatial Correlation Of Provincial Urbanization And Its Influencing Factor Analysis In China

Posted on:2020-11-21Degree:MasterType:Thesis
Country:ChinaCandidate:H Y LiFull Text:PDF
GTID:2439330620956739Subject:Statistics
Abstract/Summary:PDF Full Text Request
Since the reform and opening up,China's economy has developed rapidly and the level of urbanization has continued to rise,from 17.9% in 1978 to 58.52% in 2017.However,due to the differences in geographical location,economic development level and education level in different regions,the level of urbanization development in China's provinces is very uneven.Therefore,in order to promote the coordinated development of regional urbanization in China,it is of great theoretical and practical significance to study the spatial correlation of provincial urbanization and its influencing factors.The main research contents of the thesis include:(1)Based on the data of relevant variables from 31 provinces,municipalities and autonomous regions in China from 2004 to 2017,11 indicators under the five dimensions of infrastructure urbanization,population urbanization,ecological environment,education level and economic urbanization were selected to build provincial urbanization.The comprehensive evaluation index system uses the entropy method to calculate the comprehensive urbanization scores of 31 provinces,municipalities and autonomous regions in the country,and analyzes the spatial and temporal evolution characteristics of provincial urbanization development.(2)Using the gravity model and social network analysis method(SNA)to construct the spatial correlation and network structure characteristics of China's provincial urbanization development;(3)Using the secondary assignment procedure(QAP)analysis method to analyze the provincial urbanization development The influencing factors and the solution to the traditional spatial measurement methods are difficult to grasp the overall characteristics of the urbanization development space linkage and the defects of the network structure characteristics;(4)Under the condition of upgrading the industrial structure,the spatial lag variable coefficient panel model is used to analyze the main impact indicators of the comprehensive development of provincial urbanization.The main research results of the thesis include:(1)China's provincial urbanization development has a relatively obvious and complex network structure in terms of spatial correlation,and network stability and traffic accessibility are relatively good.(2)The urbanization development of various provinces,municipalities and autonomous regions in China is divided into four sections;the first sector is mainly the eastern and northeast regions,which is the “two-way spillover plate”;the second sector is the northwest region,which is the “main benefit segment”;The three sectors are the eastern and southernregions,which are the “net spill plate”;the fourth sector is the southwest region,which is the “broker plate” and plays the role of “bridge”.China's provincial urbanization development has obvious characteristics of energy transfer gradient.(3)China's provincial urbanization development is positively affected by per capita GDP,geographical adjacency,local fiscal expenditure,urban population share,highway mileage and regional innovation input,and the relationship between the registered urban unemployment status and the number of college graduates is not Big.(4)In the case of industrial structure upgrading,the empirical results of the panel model of spatial lag coefficient show that there is an inverted “U” curve between per capita GDP,government fiscal expenditure,and the number of college graduates and the development of urbanization.There is a “U”-shaped curve between the regional innovation investment and the development of urbanization.The development of urbanization level is not obvious with other factors.On this basis,the countermeasures,measures and suggestions for promoting the development of urbanization in China's provinces are pointed out.
Keywords/Search Tags:Urbanization, Spatial Correlation, Social Network Analysis, QAP Analysis, Spatial Hysteresis Variable Coefficient Panel Model
PDF Full Text Request
Related items