| The geographical concentration of economic activity is a common space phenomenon. Competitive industries (enterprises) concentrate in certain areas, dominating the pattern of local economic development. As an important research area, much attention has been paid to industrial geographic concentration since 1980s. Especially, it is an important aspect for regional differences to study spatio-temporal changes pattern on industrial geographic concentration, exploring its influence factors of great significance for regional development.A theoretical framework of learning industrial district is constructed after summarizing the relevant industrial geographical concentration literatures. Then, using Gini coefficient and spatial autocorrelative model, the spatio-temporal pattern changes of industrial geographical concentration is explored. Next, based on the spatial concentration and spatial difference of two-digit manufacturing industries in 2004, some detailed analysis is made on the influencing factors of the industrial geographic concentration by geographical weighted regression model.The results show that: at theory level, industrial district's technological learning and innovation and learning industrial district has become the core to location theory, regional development theory and economic geography theory. At method level, exploratory spatial data analysis techniques provide the effective support to measure the degree of agglomeration and spatial differences; meanwhile, spatial econometric model overcomes the traditional econometric models'set deviation, improving the explanation and persuasion for spatial influencing factors of industrial geographic concentration.Empirical study concludes that: Firstly, the industrial concentration is low and little changed in municipal geographical unit, and it is stable before 2003 and has a large decline considering the municipal district at county level. While the degree of industrial concentration inclines to rise if the municipal district is not considered, suggesting the spillover effects after Zhongyuan urban agglomeration's integration. Secondly, there exists significant space relevance for industrial geographical concentration in Zhongyuan urban agglomeration. As a"hot zone"of industrial development, the county's industry highly concentrates in Zhengzhou, showing diffusion effect. However, that is very low in Kaifeng and its adjacent areas, which means Kaifeng has became the"collapse zone"of industrial development. Thirdly, the spatial pattern of geographical concentration for manufacturing is similar to that for industry, but the former location Gini coefficient is higher than the latter, of which the tobacco industry is in the highest concentration, chemical materials and chemical products the lowest. Fourthly, the potential industrial clusters of strong spatial association could be drawn to detect the spatial distribution's"hot spots"for two-digit industry. Fifthly, the results are similar among spatial lag and spatial error model and classical OLS estimation model, because of small study scope and rough industrial classification, which only impacts the regression coefficients. Sixthly, at current stage, the capital investment contributes most to the patterns of industrial concentration at county level in Zhongyuan urban agglomeration. Policies and institutions are also important factors to cause industry scattered. The regions of high labor quality have a clear tendency to promote industrial concentration. Local industry development environment (localization economies and urbanization economies) and participation in globalization also contributes the industrial concentration at county level in Zhongyuan urban agglomeration, but which is not very significant in contract to capital investment, the proportion of state-owned enterprises, government interference, and the number of patents. |
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