Spatial Econometrics Analysis on Regional Economic Disparity of National-Level Poor Counties in China

Regional disparity has always been a greatly significant issue to both academic enquiry and government policy. Modern disparity in regional economic development facilitate the efficient allocation of resources and the shift of industries between regions, however,the oversized differences will weaken the existing division of labor and economic cooperation,or even do harm to the regional social stability. Despite the tremendous scholars' interest in regional disparity in China,the current research work ignores the spatial effects at the county level. Taking the GDP per capita as the measuring indicator,this paper analyses the spatial pattern of economic disparities of national-level poor counties in China from 2000 to 2010 by use of exploratory spatial data analysis( ESDA) and GIS. For per capita GDP,this paper distinguishes among 4 classes based on the average of all the 592 county units,computes their Markov chain matrix and spatial Markov chain matrix,and then analyzes the changing spatial patterns of the class transitions and their surrounding counterparts. The conclusions can be drawn as follows. ①A non-balanced development pattern of quantity has been presented,which indicates that the strong ones take the trend of polarization,and the weak ones become weaker. The regional spatial structure presents that the national-level poor counties increases from east to west and decreases from south to north. ②In the 11 selected years,the estimate values of Global Moran's I raised,so it showed that spatial correlation increased. The calculation results of local Moran's I( LISA) indicated that the county economy developed during these years,but the development was of spatially imbalance. ③The process of regional convergence of national-level poor counties in China has been characterized by‘convergence clubs' since 2000. The Markov chain matrix indicates that the richest and the poorest counties do not seem to change their relative position over time. The most affluent counties appear persistent—the 94. 2% probability of the richest remaining richest. And 95. 7% probability of the poorest remaining poorest is the largest entry in the transition matrix. Furthermore,the maps of spatial Markov transitions show that the per capita GDP class transitions are greatly affected by their spatial neighbors. Neighborhood environment has the promotion or restriction on the evolution of regional development level. ④Great changes of hot spots and cold spots spatial pattern have taken place over the past 11 years. Spatial pattern of‘three vertical and two horizontal distributions' is presented,which construct a national system of cold spots of national-level poor counties. ⑤Historical development foundation,geographical location and spatial proximity effect account for economic spatial disparities of national-level poor counties. Based on the above conclusions,this paper also proposed some suggestions to accelerate the county economic development in national-level poor counties from making multi-central spatial development policy, strengthening cross-administration region cooperation between counties and promoting spatial radiation effect of spread regions.