scholarly journals Nonlinear Effects of Governmental and Civil Environmental Regulation on Green Total Factor Productivity in China

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Xubin Lei ◽  
Shusheng Wu
Keyword(s):  
Environmental Regulation ◽  
Total Factor Productivity ◽  
Environmental Awareness ◽  
Nonlinear Effects ◽  
Threshold Value ◽  
Policy Implications ◽  
Eastern Region ◽  
Factor Productivity ◽  
Cyclical Fluctuation ◽  
Panel Model

This paper employs metafrontier Malmquist-Luenberger index to measure green total factor productivity and then builds panel model to investigate the nonlinear effects of both governmental and civil environmental regulation on green total factor productivity in 30 provinces of China in 2007–2016, where the threshold variables are environmental awareness and regulatory foundation. The results show that green total factor productivity takes the characteristic of cyclical fluctuation, and the magnitude and its growth rate in the eastern region are higher than those in the midwestern region. The degrees of the governmental and civil environmental regulation and green total factor productivity display single environmental awareness threshold and regulatory foundation threshold. It should be noted that the sign of governmental and civil environmental regulation on green total factor productivity will transform from negative to positive, if and only if threshold variables ascend and surpass the threshold value. Under the condition of metafrontier technology, governmental environmental awareness threshold value, based on the investigated corruption and malpractice cases by the procuratorates among every hundred thousand people, reaches 0.2158, and civil environmental awareness threshold value based on the per capita education level will attain 12.2330 years, and the corresponding regulatory foundation index threshold values are 0.0163 and 0.0154. These findings show clear policy implications: rather than continually promoting the level of governmental environmental regulation, civil performance, environmental awareness, and regulatory foundation should be considered.

scholarly journals Study on the Effect of Environmental Regulation on the Green Total Factor Productivity of Logistics Industry from the Perspective of Low Carbon

2019 ◽  
Vol 12 (1) ◽  
pp. 175 ◽  
Author(s):  
Zijing Liang ◽  
Yung-ho Chiu ◽  
Xinchun Li ◽  
Quan Guo ◽  
Yue Yun
Keyword(s):  
Environmental Regulation ◽  
Total Factor Productivity ◽  
Jiangsu Province ◽  
Spatial Effects ◽  
Low Carbon ◽  
Method Of Moment ◽  
Factor Productivity ◽  
Logistics Industry ◽  
Forward Logistics ◽  
The Government

Under the low-carbon background, with the aid of the Malmquist–Luenberger SBM (Slack-based Measure) model of unexpected output, the green total factor productivity (GTFP) of the logistics industry in Jiangsu Province, China, was measured and decomposed in this study based on the reality and experience of logistics industry development in 13 cities in three regions of Jiangsu Province in the years 2006–2018 by taking resource consumption into the input system and discharged pollutants into the output system. It is concluded that the environmental regulation (ER) has a significant positive effect on the growth of the GTFP of the logistics industry, and technological progress has become an important endogenous force that promotes the GTFP of the logistics industry in Jiangsu Province. On this basis, a dynamic GMM (Generalized method of moment) model and a Tobit model were constructed to further study the possible temporal and spatial effects of ER on the GTFP of the logistics industry. The research results reveal that the ER can exert both promoting and inhibitory effects on the GTFP of the logistics industry, and there is a temporal turning point for the effects. Besides, the effects notably differ spatially and temporally. Finally, some policies and advice for the green sustainable development of the logistics industry were proposed. For example, the government and enterprises should pay attention to the green and efficient development of the logistics industry and dynamically adjust the ER methods. They should consider the greening of both forward logistics links and reverse logistics system in the supply chain.

scholarly journals The Impact of Participation in PPP Projects on Total Factor Productivity of Listed Companies in China

2021 ◽  
Vol 13 (14) ◽  
pp. 7603
Author(s):  
Xiangdong Liu ◽  
Guangxi Cao
Keyword(s):  
Total Factor Productivity ◽  
High Speed ◽  
Operation Mode ◽  
Listed Companies ◽  
Financing Constraints ◽  
Eastern Region ◽  
Time Varying ◽  
Factor Productivity ◽  
The Impact ◽  
China’S Economy

The key to transforming China’s economy from high-speed growth to high-quality development is to improve total factor productivity (TFP). Based on the panel data of China’s listed companies participating in PPP (Public–Private Partnerships) projects from 2010 to 2019, this paper constructs the time-varying DID method to test the impact of participation in PPP projects on the company’s TFP empirically, explore the mechanism of the effect of participation in PPP projects on the company’s TFP, and then conduct heterogeneous analysis from four perspectives: region, industry, ownership form, and operation mode. The empirical results show that participation in PPP projects can significantly promote the growth of the company’s TFP, which mainly comes from the promotion of the innovation level of listed companies and the alleviation of financing constraints by participating in PPP projects. In addition, participation in PPP projects has a significant impact on TFP of listed companies in the eastern region, listed companies in the secondary and tertiary industries, state-owned listed companies, and listed companies participating in PPP projects under the BOT mode.

scholarly journals Research on Green Total Factor Productivity of Logistics Industry and its threshold effect of Environmental Regulation

2021 ◽  
Vol 235 ◽  
pp. 02022
Author(s):  
Wanchun Li
Keyword(s):  
Environmental Regulation ◽  
Total Factor Productivity ◽  
Threshold Model ◽  
Intermediate Stage ◽  
Threshold Effect ◽  
Inhibitory Effect ◽  
Regulation System ◽  
Factor Productivity ◽  
Logistics Industry ◽  
The Government

This paper is based on the input-output panel data of logistics industry in 30 provinces and regions in China from 2005 to 2017, using nonparametric DEA model to evaluate the green total factor productivity of logistics industry, and build a panel threshold model to empirically test the nonlinear impact of environmental egulation. It is found that environmental regulation has a double threshold effect on green total factor productivity of logistics industry, the estimated threshold values are 89.85 and 211.27 respectively; when environmental regulation is at a low level below 89.85, environmental regulation has a positive effect of 2.09% on green total factor productivity of logistics industry, when environmental regulation is in the intermediate stage of 89.85 to 211.27, environmental regulation has a positive improvement effect of 6.41% on green total factor productivity of logistics industry; when environmental regulation is at a higher level than 211.27, environmental regulation has a negative inhibitory effect of 1.57% on green total factor productivity of logistics industry. Based on the empirical conclusion, this paper puts forward: First, using the performance assessment as the baton to urge the local government to establish an effective environmental regulation system; second, the government should plan to guide the green transformation and upgrading of the logistics industry to avoid “one size fits all” environmental regulation.

scholarly journals The Relationship between Environmental Regulation and Green Total Factor Productivity in China: An Empirical Study Based on the Panel Data of 177 Cities

2020 ◽  
Vol 17 (15) ◽  
pp. 5287 ◽  
Author(s):  
Mingliang Zhao ◽  
Fangyi Liu ◽  
Wei Sun ◽  
Xin Tao
Keyword(s):  
Economic Development ◽  
Panel Data ◽  
Environmental Regulation ◽  
Total Factor Productivity ◽  
Inflection Point ◽  
Factor Productivity ◽  
Positive Effects ◽  
Development Level ◽  
The Mean ◽  
The Relationship

Promoting the coordinated development of industrialization and the environment is a goal pursued by all of the countries of the world. Strengthening environmental regulation (ER) and improving green total factor productivity (GTFP) are important means to achieving this goal. However, the relationship between ER and GTFP has been debated in the academic circles, which reflects the complexity of this issue. This paper empirically tested the relationship between ER and GTFP in China by using panel data and a systematic Gaussian Mixed Model (GMM) of 177 cities at the prefecture level. The research shows that the relationship between ER and GTFP is complex, which is reflected in the differences and nonlinearity between cities with different monitoring levels and different economic development levels. (1) The relationship between ER and GTFP is linear and non-linear in different urban groups. A positive linear relationship was found in the urban group with high economic development level, while a U-shaped nonlinear relationship was found in other urban groups. (2) There are differences in the inflection point value and the variable mean of ER in different urban groups, which have different promoting effects on GTFP. In key monitoring cities and low economic development level cities, the mean value of ER had not passed the inflection point, and ER was negatively correlated with GTFP. The mean values of ER variables in the whole sample, the non-key monitoring and the middle economic development level cities had all passed the inflection point, which gradually promoted the improvement of GTFP. (3) Among the control variables of the different city groups, science and technology input and the financial development level mainly had positive effects on GTFP, while foreign direct investment (FDI) and fixed asset investment variables mainly had negative effects.

scholarly journals Economic Efficiency and Its Influencing Factors on Urban Agglomeration—An Analysis Based on China’s Top 10 Urban Agglomerations

2019 ◽  
Vol 11 (19) ◽  
pp. 5380 ◽  
Author(s):  
Junwei Ma ◽  
Jianhua Wang ◽  
Philip Szmedra
Keyword(s):  
Total Factor Productivity ◽  
Influencing Factors ◽  
Economic Efficiency ◽  
Policy Implications ◽  
Factor Productivity ◽  
Urban Agglomerations ◽  
Capital Productivity ◽  
Industrial Specialization ◽  
New Findings ◽  
The Impact

Economic efficiency is the key issue of sustainable development in urban agglomerations. To date, more attention has been paid to the estimates of productivity gains from urban agglomerations. Differing from the previous studies, this paper focuses on the influencing factors and mechanisms of the economic efficiency of urban agglomerations, and check the effects of three different externalities (industrial specialization, industrial diversity and industrial competition) on the economic efficiency of urban agglomerations. The selected samples are multiple urban agglomerations, and the economic efficiency of urban agglomerations includes single factor productivity and total factor productivity. China’s top 10 urban agglomerations are selected as the case study and their differences in economic efficiency are portrayed comparatively. Firstly, a theoretical analysis framework for three different externalities effect mechanisms on the economic efficiency of urban agglomerations is incorporated. Secondly, economic efficiency measurement index system composes of labor productivity, capital productivity, land productivity and total factor productivity, and the impact of various factors on the economic efficiency of urban agglomerations is tested. The results confirm some phenomena (MAR externality, Jacobs externality and Porter externality) discussed or mentioned in the literature and some new findings regarding the urban agglomerations, derive policy implications for improving economic efficiency and enhancing the sustainability of urban agglomerations, and suggest some potentials for improving the limitations of the research.

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