Spatial Econometric Analysis Of The Difference Of Industrial Structure Of Chinese Provinces

Industrial structure is the core of China’s current economic structure of the problem. Deep understanding of differences in industrial structure of provinces in China for coordinated regional economic development, upgrading of industrial structure has important theoretical significance and practical significance.Firstly, drawing figures depicts the status of industrial structure of provinces in China, and existing problems of three industries and possible factors to generate differences about provincial possible industrial structure are pointed out. Then, summarize up and absorb literatures on industrial structure status in recent,"economic growth and industrial structure""financial development and industrial structure","other factors and industry structure" etc. Based on the grasp of the research frontier of industrial structure, we have introduced briefly the theory of industrial structure, and try to describe the determinants of changes in industrial structure from both internal and external perspectives. And in order to get ready for empirical model, we analyzed the situation of various factors of different provinces. Then in the empirical part, spatial econometric models are constructed to show the provincial real difference in the performance of the industrial structure and the internal reasons. Some useful conclusions are giving below.First of all, the significant positive spatial autocorrelation which is also called spatial agglomeration effects exist among the provincial industrial structure. The places which have similar form of industrial structure are geographical proximity. The places which have different form of industrial structure are not close. But the combined effect is not fully absolute, and there is a special case. Secondly, the technological innovation, private consumer demand, economic openness and financial development play a decisive role in affecting the provincial differences about industrial structure. Among these factors, economic openness played a negative effect on it. In addition, government intervention, the level of human resources and capital investment are not determinant factors.On the third one, about the model application, the series of spatial autoregressive models reflected better than linear regression model of the ordinary least squares (OLS), and it can reveal the spatial effect of the industrial structure. The estimates of geographical weighted regression model (GWR), which is based on the assumptions that the spatial data exists Non-stationarity. is also better fit than the OLS regression of the provincial differences in industrial structure. It points out that the provincial industrial structure reflects spatial non-stationarity.Finally, some relevant policy implications are given in the end.