Research On Spatial Differences And Influencing Factors Of Green Total Factor Productivity In China's Service Industry

In recent years,the added value of the service industry has become more and more important in the global economy.According to the statistics of UNCTAD,the added value of the service industry accounts for more than 70% of the global GDP,and the world has entered the service economy.In 2017,the added value of China's service industry accounted for 51.6% of GDP.It has exceeded the contribution of industry to GDP for four consecutive years,and the service industry has become more and more important in the national economy.According to the theory of economic growth,productivity growth and factor accumulation are two main aspects of promoting economic growth,but only productivity improvement is the inexhaustible driving force for sustained economic growth.Therefore,this paper first uses the 2004-2016 input-output data,using MaxDEA Pro7 software to calculate the green total factor productivity of the service industry in China's 31 provinces,and then using the descriptive analysis method,the Gini coefficient and its decomposition method,and the nuclear density estimation method.The spatial difference of green total factor productivity in China's service industry is analyzed.Finally,the spatial differentiation method of spatial Dubin model and spatial regression model is used to study the influencing factors of green total factor productivity in service industry.The article research shows that:First,using the input-output data of service industry of 31 provinces from 2004 to 2016,SBM model combined with ML index and DEA model was used to calculate the green total factor productivity of service industry with constant and variable returns to scale in all provinces(municipalities directly under the central government and autonomous regions).From the calculation results: On the one hand,the value of the green total factor productivity of the service industry under the two scale returns is about 1,and the green total factor productivity of the service industry under the variable model of scale returns is smaller than that under the condition of the same scale return.On the other hand,the growth of green total factor productivity in the service sector is mainly due to technological progress.Secondly,the Gini coefficient decomposition method and the nuclear density estimation method are used to analyze the spatial difference of green total factor productivity in the service industry.From the analysis results: The relative difference of the whole country and each district has the tendency of enlarging.The gini coefficient of the whole country and all regions showed a trend of steady expansion,indicating that the difference of green total factor productivity of service industry in the whole country and all regions was expanding.There is an increasing trend of absolute differences in services across the country and among regions.In addition to the eastern region,the distribution curve of total factor productivity of service industry in the whole country,central and western regions and northeast China shows a right trailing phenomenon,but the ductility of the distribution curve in the whole country and all regions is poor,indicating that its ductility shows a convergence trend.Thirdly,the spatial econometric model is used to analyze the factors affecting the green total factor productivity of the service industry in the country and the four major regions.The conclusions are as follows: According to the Moran`s I index,the green total factor productivity of the service industry has significant spatial correlation,whether it is adjacent weight,geographic weight or economic weight.The driving factors of green total factor productivity growth of service industry are different in China and various regions.For the whole country,the development level of the service industry,the actual use of foreign direct investment,the foreign investment,the urbanization rate,and the fiscal expenditure have a spatial spillover effect on the green total factor productivity of the service industry.The level of economic development and urbanization have an inter-regional spatial spillover effect on the growth of green total factor productivity in the service industry.The level of economic development,the actual use of foreign direct investment,the urbanization rate,and the level of fiscal expenditure have a total spillover effect on the green total factor productivity of the service industry.For the eastern region,the service industry development level,the service industry's actual use of foreign direct investment,foreign investment,urbanization rate and openness have an intra-regional spillover effect on total factor productivity.The level of economic development and the level of foreign direct investment have inter-regional spillover effects.The level of economic development,the level of service industry development,FDI,and openness have a total effect.For the central region,the level of economic development,openness to the outside world and fiscal expenditure have an intraregional spillover effect.The level of economic development and foreign investment have inter-regional spillover effects.The level of economic development,openness to the outside world,foreign investment and fiscal expenditure have a total effect.For the western region,the level of economic development,the level of development of the service industry,and the actual use of foreign capital have regional spillover effects.The level of economic development,foreign investment,and openness have an inter-regional spillover effect.The level of economic development,the level of service industry development,foreign investment,and the level of opening have a total effect.For the Northeast region,the level of human capital,urbanization,and openness have regional spillover effects.The level of service industry development has an inter-regional spillover effect.The level of economic development,the level of development of the service industry,the rate of urbanization and the degree of openness have a total effect.According to the research conclusions,the following suggestions are proposed: introducing foreign direct investment in service industry,expanding foreign direct investment in service industry;expanding trade in service industry,improving the quality of service trade;increasing human capital investment,raising the level of human capital;and promoting fiscal expenditure.Rationalize to avoid blindness and corruption.