Font Size: a A A

Calculation And Influencing Factor Analysis Of Green Total Factor Productivity In Hebei Province

Posted on:2023-07-24Degree:MasterType:Thesis
Country:ChinaCandidate:J N LiuFull Text:PDF
GTID:2531307094989429Subject:Applied statistics
Abstract/Summary:PDF Full Text Request
At present,China’s economy is in an important stage of transformation from high-speed development to high-quality development.The problems of serious environmental pollution and excessive energy consumption caused by traditional destructive development need to be solved urgently.How to balance the relationship between environmental protection and economic development has become an important issue.At this time,green total factor productivity,which comprehensively considers the relationship between environment,energy and economic growth on the basis of total factor productivity,has become an important basis to measure the balanced development of economy and environment.Measuring and analyzing the factors affecting green total factor productivity can not only quantify the development level of environmental economy,but also find out the reasons restricting the further development of environmental economy.On the other hand,in recent years,China has continuously improved its regional coordinated development policy.As an important industrial base in Beijing Tianjin Hebei region,Hebei Province actively undertakes the relocation industry of Beijing.It is a large economic province with dense roots of heavy industry and high-tech industries such as manufacturing in the north,and its development and environmental problems are more prominent.Therefore,the research and Analysis on the green total factor productivity of 11 prefecture level cities in Hebei Province will help to put forward some targeted suggestions for the economic development of Hebei Province,further optimize the allocation of resources and improve the green development level of economy.This paper takes 11 prefecture level cities in Hebei Province from 2003 to 2018 as the research object,(1)calculate the green total factor productivity of 11 prefecture level cities in Hebei Province by using Malmquist Luenberger index under super SBM,and understand the current situation of green total factor in each prefecture level city;(2)After the calculation results are obtained,the Malmquist Luenberger index is decomposed into green technology progress and green technology efficiency change.Then study its characteristics from the provincial level,regional level and prefecture level to understand the multi-level level of green total factor productivity;(3)Then using the systematic GMM method,the * * index is selected as the influencing factor to analyze the influencing factors of green total factor productivity in Hebei Province,analyze the action direction of each index,and then test the robustness of the model.(4)Using VAR impulse response function,apply a standard deviation impact to each index,calculate the impact mode of different indicators on green total factor productivity,and put forward some policy suggestions for the economic development of Hebei Province.Research findings:(1)There is still much room for improvement in Hebei Province’s mastery of new technologies and the ability of technology diffusion;(2)The development level of green total factor productivity in northern Hebei is relatively low.The level of green total factor productivity in Zhangjiakou,Chengde,Cangzhou and Xingtai is low;(3)The level of foreign trade and energy structure have a negative effect on the green total factor productivity of Hebei Province.Actual foreign investment,government finance,scientific research investment,economic factors and industrial structure can promote green total factor productivity;(4)Foreign trade inhibited green total factor productivity at the initial stage.Foreign investment has a lagging role in promoting green total factor productivity.(5)The government’s financial scale has a positive impact on green total factor productivity in the long run.The degree of fiscal freedom has a positive role in promoting the two-order lag.The investment of scientific research funds reached the peak in a very short time,and then began to decline.Based on the above results,this paper draws the following policy recommendations:(1)Hebei Province should actively absorb and utilize foreign advanced technology,and strive to improve the innovation ability of its own products and improve the structure of import and export products.(2)Give further play to the advantages of government regulation scale.We will continue to adhere to the fiscal policy of concentrating our efforts on major issues.Gradually reduce the expenditure on economic construction and reduce the "crowding out effect".Call on local governments at all levels to increase cooperation with Tianjin and Beijing to promote the completion and development of high emerging and efficient enterprises.(3)We will continue to encourage greater investment in scientific and technological research and development.We should pay more attention to and cultivate scientific,technological and innovative talents,and encourage enterprises engaged in independent innovation activities.(4)Local governments should give full play to the allocation function of the market to resources,and focus on building a regulatory tool market to improve the nature of market economy and disclose information.For example,emissions trading can be improved.(5)Local governments should change the mode of economic growth to optimize the industrial structure and promote energy conservation and emission reduction: on the one hand,further formulate reasonable energy conservation and emission reduction targets to transform the extensive growth mode into an environment-friendly and resource-saving production mode.On the other hand,we should strengthen environmental protection,constantly explore the use methods of conventional energy,develop the intermediate link functions of conventional energy,and develop clean new energy.
Keywords/Search Tags:Green TFP, Malmquist-Luenberger index, System-GMM, VAR impulse response, Super SBM model
PDF Full Text Request
Related items