A Study On The Influential Factors Of Industrial Environment Total Factor Productivity In China

Since China’s reform and opening up, the rapid development of economy of China made remarkable achievements, especially as the dominant department of the national economy, the industrial sector continued rapid development, it will directly affect the growth of China’s economic growth speed and quality. Total factor productivity is the core of the economic growth, economic development quality not only depends on the total factor productivity contribution to economic growth but also give full consideration to resources and the environment for economic development speed and scale of constraints.However, in the process of industrial development also appeared many problems and challenges, the eastern coastal areas take the lead in the development of the unbalanced development strategy has intensified regional disparities, excessive consumption of resources and environment pressure, ecological environent worsening and so on a series of problems.For China’s industrial growth has developed rapidly,Facing the reality that the regional gap is widening and environment is worsening, scholars have done a lot of resarch.However, in the existing study of regional industrial economic disparity in China, the most study ignored elements flow between regions and spatial spillover effects on regional economy.Most literature assume economic individual independence,which have ignored the ecomomic in geographical spatial relationships between individual interaction.New economic geography believe that some economic geography phenomenon or a certain attribute values on a regional spatial unit is related to the neighborhood space unit on the same economic geography phenomenon (Anselin,1988). Due to regional openness, the elements of knowledge flow and technology diffusion and other factores make area relation become complex and changeful.Regional industrial economy not only depends on the growth itself,but also closely links with neiborhood area growth.In recent years, the development of new economic geography and space econometrics supported new ideas and method for the study of the regional economic growth.In this paper the theoretical basis is new economic geography and spatial econometrics, under the assumptions of the spatial heterogeneity and spatial correlation, surrounding the center that whether the provincial industrial environment total factor productivity exists spatial correlation,at first,using Malmquist-Luenberger index method to measure the China’s30provinces from2005to2011industrial environment total factor productivity and its decomposition. Then on the basis of total factor productivity results using statistical analysis of global Moran’s index and local Moran’s index inspects spatial correlation of TFP and regional differences. Finally, using spatial econometric model analyzes TFP’s influence factors.This paper has main four conclusion:(1) regional distribution of China’s industrial TFP exists big disparity. In general, industrial TFP, fluctuant state,2005-2007was on the rise,2008was down, in2010started to rise again.(2) In regional,the higher ecomomic development level between two provinces,the smaller industrial TFP gap.Generally high industrial TFP of eastern coastal provinces and the central and western provinces of TFP is low.Environmental technology progress made more impact on industrial TFP growth, and the environmental technology efficiency had little impact on industrial TFP.(3) Spatial statistical analysis results show that province industrial TFP in China exists strong spatial correlation, parts province’s agglomeration phenomenon is obvious. And spatial heterogeneity in the region,Some years global Moran’s I index was not significant, but quite part of provinces and cities exist local spatial autocorrelation, the eastern region industrial TFP overflow to middle region.(4) Spatial panel model is more appropriate than OLS model, and SEM model is superior to the SLM, so according to the SEM model simulation results it is concluded that human capital stock, the construction of infrastructure, the degree of opening, environmental regulation and the level of industrialization make positive effect on the industrial environment TFP, maybe due to the lagging R&D levels lead to no significant statistically.