Spatial Correlation Network and Driving Mechanism of Provincial Common Prosperity in China
Based on the panel data of China's inter-provincial from 2010 to 2020,this paper uses the entropy method to measure the common prosperity level in China,and the modified gravity model and social network analysis to explore the spatial correlation network structure characteristics and driving mechanism.The results show that:1)In 2010-2020,the common prosperity level showed a gradually decreasing gradient from the east of China to the west of China,and the optimal equilibrium degree of the common prosperity level in the north-south direction was higher than that in the east-west direction.2)The spatial correlation of common prosperity was becoming closer at the provincial level,the spatial network structure was complicated,multi-threaded,and dense,and the spatial correlation flow was"strong in the east of China and weak in the west of China".Beijing,Shanghai,Jiangsu,Zhejiang and other provinces occupied the core position in the spatial correlation network of common prosperity,controlling and influencing the external radiation and spatial spillover of common prosperity level,while Tibet,Xinjiang,Qinghai and other provinces had less influence in the network,and were in the marginal position,difficult to control and influence other regions.3)Spatial adjacency relation,the difference in economic development level,the difference in urbanization level,and the difference in the degree of opening to the outside world jointly drove the optimization and evolution of the spatial correlation network structure of common prosperity.
common prosperityspatial correlation networksocial network analysisdriving mechanismregional coordination policysharing
万方数据
维普
