Abstract
Industrial agglomeration has gradually become an economic focus in recent years. Scholars has done a lot of research about the formation mechanism of industry agglomeration and its influencing factors, but the spatial correlation of variables has still been neglected. Firstly this paper gives a brief introduction about Geoda software and Matlab neural network toolbox, then use spatial statistical methods to describe the 1999-2008 China's manufacturing industry agglomeration. Secondly this paper uses spatial econometric methods to analyze the influencing factors of China’s provincial manufacturing Agglomeration. The results show that the spatial econometric model is superior to the traditional econometric models and the analysis based on spatial econometric model are more accurate. Finally, the paper also gives a brief forecast of the manufacturing Agglomeration.
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