Research On The Total Factor Productivity Growth In China Under The Constraints Of Resources And Environment

Since reform and opening up,China has made major achievements in economic development,and the quality and efficiency of its development have been continuously improved.By 2019,China’s GDP grew to about 99 trillion yuan,ranking second in the world and contributing more than 30 percent to world economic growth.But China is under greater pressure on resources and the environment with its economy growing at a medium-high speed and its growing international influence.At the same time,it is also facing problems such as inefficient use of natural resources and declining environmental quality.The cost of serious environmental pollution and damage brought about by economic development have attracted the attention of people.Faced with multiple pressures such as economic growth,resource supply and environmental pollution,how to improve the quality of economic development and achieve regional coordinated development has become the primary issue that must be considered in sustainable development.Total Factor Productivity(hereinafter referred to as TFP)is the main index to measure production efficiency.The higher the TFP,the higher the quality of economic development.With this in mind,the report to the 19 th national congress of the communist party of China(CPC)in October 2017 clearly pointed out that in order to achieve the strategic goal of building a modern economic system,we must promote the reform of the quality and efficiency of economic development and improve TFP.At the same time,we will make ecological progress one of the basic strategies of socialism with Chinese characteristics for the new era,advocate the adherence to the basic state policy of conserving resources and protecting the environment,and foster a green development model.In this article,provinces and autonomous regions,industry,international economies were studied respectively as the research object from different aspects,taking resources and environment constraints into account.On the basis of the theory of TFP,using data envelopment analysis method combined with the directional distance function and Malmquist index method,the efficiency of the technology in China from 2004 to 2017 was studied.Meanwhile the characteristics of the change of TFP and enhance source were analyzed.The differences in various provinces and regions were studied The convergence of interprovincial TFP growth was tested by using the spatial panel model,and the influencing factors of interprovincial TFP growth were empirically analyzed.The role of industry in promoting interprovincial TFP was empirically studied from the perspective of promoting new industrialization.Finally the differences in China and OECD countries TFP growth were compared from the international perspective.Specific research contents are as follows.Chapter one is the theory of TFP.Firstly,this paper summarized the historical development of economic growth theory,the measurement method of TFP and the influencing factors of TFP.These theoretical studies lay a foundation for further empirical analysis.Chapter two is the research on the calculation of TFP growth between provinces in China under the constraint of resources and environment.First,the global Malmquist Luenberger(GML)index was constructed by using directional distance function to measure the TFP growth in each province under the constraint of resource environment,and then it was decomposed to analyze its dynamic growth characteristics and growth sources.Secondly,the technological efficiency of China’s provinces under the constraint of resources and environment was calculated,and the TFP characteristics of each province and the three regions from a static perspective was analyzed.Chapter three is the convergence of TFP between provinces in China under the constraint of resources and environment.Firstly,the convergence hypothesis and mechanism were theoretically sorted out.Then,the research methods of convergence were explained.Spatial measurement model was used to test the absolute convergence and conditional convergence of inter-provincial TFP growth under the constraints of resource and environment.Chapter four is the research on the factors influencing the growth of TFP in China under the constraint of resources and environment.After analyzing the mechanism of the influence of resource and environment factors on TFP growth,an appropriate panel model was selected based on the GML index calculated in chapter 2 to make an empirical analysis on the factors affecting TFP growth and regional differences.Chapter five is the influence of industry on provincial TFP growth under the constraint of resources and environment.Because industry is the main force that promotes the economic development of provinces,meanwhile it is also an important source of energy consumption and pollution emissions,it assumes the main responsibility in realizing green development.Therefore,this chapter focuses on the analysis of the influence of industry on inter-provincial TFP growth under the constraints of resources and environment.First of all,due to the limited access to industrial data,the industrial TFP of 30 provinces,cities and autonomous regions was calculated only from 2004 to 2016.Then,the characteristics of industrial TFP growth and its relationship with provincial TFP was analyzed.Finally,the panel smooth transformation(PSTR)model was used to study the effect of resource and environment constraints on TFP growth in provinces.The path to promote TFP growth in provinces in the process of promoting new industrialization was discussed,so as to enhance the coordination of regional development.Chapter six is the international comparative analysis of TFP growth under the constraint of resources and environment.From an international perspective,this chapter compared the differences and dynamic changes of TFP growth among countries under the constraints of resources and environment.First,the GML index and its decomposition factors of a total of 20 countries including China were calculated from 2001 to 2013,and the growth rate and quality of TFP of each economy were compared and analyzed.Then,the factors influencing the growth of TFP were empirically analyzed with the panel binary selection model,and the reasons for the growth difference were discussed.Finally,it is the conclusion and prospect of this paper.Main research conclusions are as follows:(1)The growth level of TFP will be overestimated without considering resource and environmental constraints.According to the GML index,only the index from 2005 to 2008 and the index from 2015 to 2017 were greater than 1,that is,the national average productivity was in a state of improvement,while the national average productivity decreased in other years.From the perspective of regional horizontal comparison,there was a significant difference in TFP growth in the eastern and western regions from 2004 to 2017,in which the average productivity of the eastern and western regions increased,while the average productivity of the central regions decreased.Technological progress is the main driving force of TFP growth in China and its provinces,followed by technological efficiency.From the perspective of time trend,the TFP changes in the eastern and western regions of the sample period showed a common phased feature,which was closely related to the change of pollution emissions in the corresponding year,the implementation of environmental regulation policies and the global economic environment.(2)There was absolute convergence in the TFP growth of the whole country,the east and the central,which means the growth gap is gradually narrowing.However,there was no absolute convergence in the west,and the growth gap between the provinces still existed and the development was unbalanced.Conditional convergence existed in China and its three regions.Under the economic environment differences determined by control variables,TFP growth in three regions of China converged to their respective equilibrium levels at different convergence rates.(3)The industrial structure has the largest effect on TFP growth,while the endowment structure has the smallest effect.The impact of environmental factors on TFP growth in provinces was not statistically significant,indicating that the impact of environmental governance investment on TFP growth in the sample period selected in this paper was not clear,which was related to the selection of environmental indicators and the limitation of sample data.There were some differences in the direction and magnitude of the influence of different factors on inter-provincial TFP growth.Among the factors,economic development level,endowment structure,resource factor,foreign capital factor restricted TFP growth while industrial structure,science and technology factor promoted TFP growth.(4)There was a high positive correlation between industrial TFP growth and provincial TFP growth.During 2004-2016,the industrial productivity of most of the provinces increased,among which the west was the fastest,presenting a fast chase speed,while the middle was the slowest.Industrial technology productivity improved in general,the difference of which led to the TFP growth difference of 30 provinces,cities and autonomous regions.However,from the point of time dimension,industrial TFP growth was still mainly rely on technological progress to promote.The threshold effect of resource and environmental factors on industrial TFP growth was nonlinearity.According to these conclusions,the path to promote the growth of TFP in China’s provinces can be drawn.(5)The average TFP level of OECD countries was basically higher than that of China,and only lower from 2006 to 2009,indicating that the economic crisis that broke out in 2008 had a greater impact on OECD countries,resulting in a sharp decline in TFP.This paper innovation points are:(1)A global DEA linear programming model,SBM model,directional distance function combined with global Malmquist index method were used in this paper,using the latest data of all provinces and cities to calculate TFP growth under the constraint of resources and environment.The GML index can avoid the problem of no feasible solution when measuring TFP in traditional Malmquist index or including only environmental constraints of ML index.It also has the transitivity and decomposition is more reasonable.(2)With the addition of spatial correlation factors,the convergence of TFP were tested by spatial econometric model and the influence factors of TFP were studied by nonlinear model,which can reasonably describe the relationship between various factors and indicators in economic growth and is more operable to promote industrial and inter-provincial TFP growth.(3)Compared with international economies,it is expected that the study of driving factors of TFP will be more practical and comprehensive,taking into account China’s actual situation and technological progress,scale efficiency,allocation efficiency,demographic dividend,etc.