Spatial Distribution Pattern of China’s County Economy and Its Evolution: from 1990 to 2010
LUO Qing1,2, LI Xiao-jian1,2,3, YANG Hui-min1
1.School of Resources and Environment/Institute of Regional Sustainable Development, Henan University of Economics and Law, Zhengzhou 450002, China 2. Collaborative Innovation Center of Three-aspect Coordination of Central-China Economic Region, Henan University of Economics and Law, Zhengzhou 450002, China; 3.Research Institute of Yellow River Civilization and Sustainable Development, Henan University, Kaifeng 475001, China
Abstract County is the basic unit of economic development measurement, and the implementation effect of regional development policy is especially shown on the county level. Using the ESDA,this paper demonstrates the spatial evolution of economic pattern of China’s county during 1990-2010. The study finds that in the general economic pattern, the development of China’s county economy has a relatively strong spatial autocorrelation with similar regions clustering in space, hot spots centering in the Yangtze River Delta, the Pearl River Delta and regions round the Bohai Sea, cold spots assembling in northwest and southwest China. From the space-time transition of the hot spots and cold spots, self-organizing ability of the county economy is growing stronger. The random components in space differentiation pattern are becoming less. Hot spots continue to expend, moving from the north to the west, while the range of the cold spots tends to shrink. During 1990-2010, the spatial pattern of China’s county economy growth has notable changes. While the hot spots keep migrating to the north and west areas, the cold spots began to transfer to the coastal regions. Finally, the driving force of evolution of China’s county economic pattern can be summed up in three aspects: geographical location, resource endowment and regional economic development policy.
LUO Qiang,LI Xiao-Jian,YANG Hui-Min. Spatial Distribution Pattern of China’s County Economy and Its Evolution: from 1990 to 2010. Economic Survey, 2014, 31(1): 01.
2014, Vol. 31 
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