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Measurement And Influencing Factors Of Green Total Factor Productivity In The Yangtze River Economic Belt

Posted on:2020-10-15Degree:MasterType:Thesis
Country:ChinaCandidate:X Y YangFull Text:PDF
GTID:2429330572466731Subject:Economic statistics
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The Yangtze River Economic Belt is connected to the 21 st Century Maritime Silk Road in the east and the Silk Road Economic Belt in the west.It is an important densely populated area and industrial carrying area in China.The construction of the Yangtze River Economic Belt is an important national strategy for China's economic development.However,with the rapid economic development,the contradiction between resources and environment in the Yangtze River Economic Belt has become increasingly prominent,resources are depleted and environmental conditions are deteriorating.Improving the quality of economic growth and realizing economic green development have become an inevitable choice,that is,to achieve the organic unity of “economy strong,people's wealth” and “excellent ecology,environmental harmony ”.At the same time,the report of the 19 th National Congress also pointed out that economic growth should focus on "quality,efficiency,fairness,sustainability",and not pursue economic growth blindly.According to the framework of modern economic growth theory analysis,the core of achieving economic growth quality is to improve green total factor productivity.So,what is the quality of economic growth in the Yangtze River Economic Belt? How to improve green total factor productivity to achieve sustainable economic development?For above problems,this paper summarizes the theory of economic growth,green total factor productivity theory and measurement method at first.and then adopts output distance function based stochastic frontier analysis method to measure the green total factor productivity of the Yangtze River Economic Belt from 2004 to 2016,and further decomposes it into five parts: output price effect,input price effect,scale return effect,technological efficiency effect and technological progress effect;finally,discussing the influencing factors of the change of green total factor productivity by using panel measurement model from infrastructure,industrial structure,environmental regulation,opening-up,technology,information.This paper discusses the influencing factors of the change of green total factor productivity in the Yangtze River Economic Belt.Based on the research conducted in this paper,the main conclusions are as follows.(1)The growth trend of green total factor productivity in the Yangtze River Economic Belt decreased from 7.76% in 2004 to 0.92% in 2014.After 2014,it showed negative growth.In 2016,green total factor productivity decreased by 2.18%,with the average annual growth reduced by 0.9%.From 2004 to 2014,technological efficiency and technological progress were the sources of growth of green total factor productivity.After 2014,technical efficiency became the sole source of green total factor productivity.output price effect promoted green total factor productivity,with an average annual contribution of 0.06%;the input price effect has a sporadic effect on green total factor productivity,but during the sample period,some provinces have shown reverse production.the scale return effect counter green total factor productivity for the scale return coefficient is less than 1.(2)In terms of influencing factors,the improvement of infrastructure,import and export trade,technology and informatization can promote the growth of GTFP,with the coefficient of action being 0.1494,0.1862,7.1399,and 0.0123,respectively.From the relationship between the coefficients,the technology is the first productivity,and it is the growth source of GTFP.There is no significant positive impact between foreign direct investment and GTFP.The proportion of secondary industry has a negative impact on GTFP with a coefficient-0.2508.There is an inverted U-shaped relationship with an inflection point of 0.0183.Based on the above empirical results,the following suggestions are proposed for the green development of the Yangtze River Economic Belt: strengthening scientific and technological innovation capabilities and increasing R&D intensity;forming experience that can be replicated and promoted to facilitate “technology sharing” among provinces and cities,improve information equipment,and make full use of Information technology such as "Internet +" provides direct channels for technology and knowledge diffusion;optimizes the industrial structure,shifts from "two three ones" to "three two ones",realizes the rational allocation of resources;keeps pace with the "Belt and Road" and expands Opening-up,providing more channels for international trade;rationally investing in pollution control to prevent excessive investment in pollution control from squeezing capital investment benefits.The main contributions of this paper are as follows: First,using output distance function based stochastic frontier analysis to measure the green total factor productivity of the Yangtze River Economic Belt.At present,there are few research literatures on the green total factor productivity of the Yangtze River Economic Belt,and most of them use the data envelopment analysis method,and do not consider the influence of random factors,while in contrast,stochastic frontier analysis considering random factors is closer to economic reality.Second,the energy value analysis method is used to measure the undesired output prices of SO2,waste water and solid waste.In the past,the total amount of pollution control investment was used as a measure.However,the environmental pollution situation facing the Yangtze River Economic Belt clearly indicates that the environmental pollution control is not strong,and the measurement of the use of environmental pollution control investment is biased.Using the energy value analysis method,using the energy conversion rate of each pollutant and GDP to convert the pollutant discharge into a currency measured in billions is the most reasonable measure.
Keywords/Search Tags:green total factor productivity, Yangtze river economic belt, stochastic frontier analysis, emergy analysis, influencing factor
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