The Research On Spatial Correlation Network Structure Characteristics Of China’s Economic Growth: 1978-2013

Combined with high economic growth in China is still a large gap between the region’s economic development, spatial association between economic growth has exceeded the traditional linear model, and gradually showing a complex, multi-threaded spatial structure of the network. Based on this reality, this paper takes the spatial correlation “relationship” of China’s economic growth as the research object, and uses the research paradigm of social network analysis(SNA) to reveal the spatial correlation network structure characteristics of China’s economic growth and the spatial-temporal evolution patterns. Firstly, we use AarcGIS software to draw China’s provincial spatial distribution of economic growth. Secondly, this paper uses the nonlinear Granger causality test and the modified gravity model to identify the spatial correlation relationship. Thirdly, the method of social network analysis is used to comprehensively deconstruct the spatial correlation network structure characteristic of economic growth and evolution trend. Specifically, this paper uses such as network density, correlation to reflect the overall characteristics of economic growth and evolution trend; uses centrality to examine the status and role of the provinces in economic growth in spatial correlation network; and using the block model to reveal spatial clustering of economic growth mode. Finally, based on network effects and geographical neighborhood effect of two dimentions, the paper empirically examines impacts of the regional spatial correlations on regional disparity.The results show that:(1)China’s economic growth is characterized by significant spatial inequality from 1978 to 2013.(2)The nonlinear Granger causality test technology not only can reveal the more spatial relationships, but also can identify more possible spatial overflow pipe, While linear Granger causality tests underestimates seriously spatial correlation of economic growth in China, This provides further empirical support for promoting spatial synergies of economic growth.(3)None province can be "independent" of overall network in maximum likelihood network(ML-Network), the overall network density of spatial correlation of regional economic growth in China reaches 0.452, which is larger than outcome of lag length 1-3 year and Li Jing, et al.(2014), it provides empirical support to further exert spatial spillover effect and realize the coordinated development of spatial regional economy.(4)The measurement results of the gravity model method show that economic growth of the overall network density gradually increases, with an average annual growth rate of 12.94%, network hierarchical structure is gradually broken,China’s provincial economic growth shows a closer and more stable network structure from whole. Further the block model analysis shows that eastern coastal provinces play net spillover and broker dual role, central region province play bi-direction, and western region province play net beneficial role.(5)OLS regression results show that the relationship between spatial network structure of economic growth and regional disparity presents inverted “U” type.“Those who do not seek a global lack seek a domain”, we must re-examine China’s coordinated regional economic development from the perspective of overall and global, explore and create more spatial spillover channels to make economic growth in different sectors and realize the spatial coordinated development of regional economy.