scholarly journals Environmental Regulation Intensity, Carbon Footprint and Green Total Factor Productivity of Manufacturing Industries

2022 ◽  
Vol 19 (1) ◽  
pp. 553
Author(s):  
Lei Wang ◽  
Yu Yan
Keyword(s):  
Environmental Regulation ◽  
Total Factor Productivity ◽  
Carbon Footprint ◽  
Manufacturing Industry ◽  
Economic Benefits ◽  
Manufacturing Industries ◽  
Green Economy ◽  
Chinese Government ◽  
Factor Productivity ◽  
The Impact

In terms of the development of the manufacturing industry, the Chinese government has carried out environmental regulations and set up production standards for related industries. This is an environmentally-friendly and economic action, which is also in line with the requirements of building a green economy for China. Meanwhile, whether from the micro regulatory measures or the macro government policies, carbon emission is an inevitable problem in the study of environmental problems. This paper will explore the impact of environmental regulation on the green economy based on carbon emissions and study the optimal environment regulation intensity that relates to a direct carbon footprint under the maximum green economic benefits. A SBM-MALMQUIST model is established to measure the green total factor productivity according to 27 Chinese manufacturing industries through the MAXDEA software. It is found that the intensity of environmental regulation has a significant impact on green total factor productivity, and direct carbon footprint also exhibits a partial intermediary effect, participating in the mechanism that affects green total factor productivity. Combined with the industrial characteristics and the above research results, this paper puts forward the adjustment strategy of reasonable environmental regulation for the manufacturing industry, which conforms to the national policy guidance, and will be beneficial in promoting the economic development of the green manufacturing industry.

scholarly journals Environmental Regulation, Trade Comparative Advantage, and the Manufacturing Industry’s Green Transformation and Upgrading

2020 ◽  
Vol 17 (8) ◽  
pp. 2823 ◽  
Author(s):  
Mengqi Gong ◽  
Zhe You ◽  
Linting Wang ◽  
Jinhua Cheng
Keyword(s):  
Environmental Regulation ◽  
Total Factor Productivity ◽  
Comparative Advantage ◽  
Manufacturing Industry ◽  
Environmental Regulations ◽  
Manufacturing Industries ◽  
Productivity Index ◽  
Chinese Government ◽  
Factor Productivity ◽  
Trade Patterns

This paper is the first to systematically review the theoretical mechanisms of environmental regulation and trade comparative advantage that affect the green transformation and upgrading of the manufacturing industry. On this basis, corresponding hypotheses are put forward. The non-radial and non-angle SBM (slacks-based measure) efficiency measurement model with undesirable outputs was used, combined with the use of the ML (green total factor productivity index) productivity index to measure green total factor productivity. Finally, the theoretical hypothesis was empirically tested using data from 27 manufacturing industries in China from 2005 to 2017. The results show the following: (1) There is a significant inverted U-shaped curve relationship between environmental regulation and the transformation of the manufacturing industry. In other words, as environmental regulation increases, its impact on the transformation and upgrading of the manufacturing industry is first promoted and then suppressed. (2) When there are no environmental regulations, the trade comparative advantage of the manufacturing industry is not conducive to industrial transformation. However, under the constraints of environmental regulations, the comparative advantage of trade will significantly promote the green transformation and upgrading of manufacturing. Therefore, in order to effectively promote transformation and upgrading of the manufacturing, this paper proposes the following policy recommendations: (1) The Chinese government should pay more attention to the impact of environmental regulation intensity on the transformation of manufacturing industries, further increase the intensity of environmental regulation within the reasonable range, and fully exert the positive effects of environmental regulation on the trade patterns and manufacturing industry transformation. (2) We should further optimize the structure of trade, realize the diversification of manufacturing import and export, and promote its transformation into high-end manufacturing. On this basis, green production technology in the manufacturing industry can be improved through the technology spillover effect. (3) Efforts should be made to improve the level of collaborative development between environmental regulation and trade patterns and to explore the transformation path of the manufacturing industry with the integration of environmental regulation and trade patterns.

Examining the Impact and Influencing Channels of Emission Trading Pilot Markets in China

2020 ◽  
Vol 11 (1) ◽  
pp. 136-136
Author(s):  
Qiong Wu ◽  
Kanittha Tambunlertchai ◽  
Pongsa Pornchaiwiseskul
Keyword(s):  
Total Factor Productivity ◽  
Co2 Emission ◽  
Carbon Emission ◽  
Emission Trading ◽  
Chinese Government ◽  
Synergy Effect ◽  
Factor Productivity ◽  
Plan Period ◽  
Carbon Emission Trading ◽  
The Impact

The global warming has become a serious issue in the world since the 1980s. The targets for the first commitment period of the Kyoto Protocol cover emissions of the six main greenhouse gasses (GHGs). China is the world's largest CO2 emitter and coal consumer and was responsible for 27.3 percent of the global total CO2 emission and 50.6 percent of the global total coal consumption in 2016 (BP, 2017). As China plays an important role in the global climate change, China has set goals to improve its environmental efficiency and performance. In 2011, the Chinese government for the first time announced an intent to establish carbon emission trading market in China. Eight regional emission trading schemes have been operating since 2013 (seven pilot markets during the 12th Five Year Plan period and one pilot market during the 13th Five Year Plan period) including provinces of Guangdong, Hubei, and Fujian, and cities of Beijing, Tianjin, Shanghai, Shenzhen, and Chongqing. The goal of these regional emission trading pilot markets is to help the government establish an efficient carbon emission trading scheme at national level. Some researchers have been focused on examining the impact of emission trading schemes in China using CGE model by constructing different scenarios and ex-ante analysis using data prior to emission trading pilot markets implementation. While this paper tries to conduct an ex-post analysis with data of 2005-2017 to evaluate the impact of emission trading pilot markets in China at provincial level using difference-in-difference (DID) model. By including both CO2 and SO2 as undesirable outputs to calculate Malmquist-Luenberger (ML) Index to measure green total factor productivity, this paper plans to evaluate the impact of carbon emission trading pilot markets in China via emission reduction, regional green development, synergy effect and influencing channels. This paper tries to answer the following research questions: (1) Do emission trading pilot markets reduce CO2 emission and increase regional green total factor productivity? (2) Is there any synergy effect from emission trading pilot markets? (3) What are the influencing channels of emission trading pilot markets? Keywords: Emission trading, CO2 emissions, Different-in-difference

scholarly journals The Effect of Environmental Performance on Employment: Evidence from China’s Manufacturing Industries

2019 ◽  
Vol 16 (12) ◽  
pp. 2232 ◽  
Author(s):  
Wei Shan ◽  
Jingyi Wang
Keyword(s):  
Environmental Performance ◽  
Manufacturing Industry ◽  
Early Stage ◽  
Correlation Effect ◽  
Economic Benefits ◽  
Manufacturing Industries ◽  
Practical Significance ◽  
Production Scale ◽  
Vector Autoregressive ◽  
The Impact

This research aims to explore the interaction between environmental performance and employment China’s manufacturing industries. Based on the environmental performance of 32 industries in China’s manufacturing industry during 2006–2015, a panel vector autoregressive model was constructed to study the interaction between industry output and employment in clean industries and dirty industries. The dynamic impact and internal transmission mechanism between environmental performance is analyzed. The study found that in the early stage, due to the reduction of production scale, there was a weak and short-term negative correlation effect on employment, and the mutual promotion relationship between economic benefits and employment was unsustainable. In return, employment affects environmental performance, but the effect differs due to the different forms of environmental performance. For dirty industries, the impact of environmental performance on employment through technical effects is more significant and, thus, a win–win situation of ecological environment and employment stability will be achieved. This research has practical significance regarding how to scientifically and effectively carry out environmental regulation and green management.

scholarly journals Energy Efficiency, Policy and GTFP

2018 ◽  
Vol 53 ◽  
pp. 01033
Author(s):  
Fangqing Yi ◽  
Zenglian Zhang
Keyword(s):  
Economic Growth ◽  
Energy Efficiency ◽  
Environmental Regulation ◽  
Total Factor Productivity ◽  
Industrial Structure ◽  
Provincial Government ◽  
Factor Productivity ◽  
Linkage Mechanism ◽  
The Government ◽  
The Impact

The environmental and resource constraints on economic growth are increasingly evident. China urgently needs to reshape its economic growth momentum. The increase in green total factor productivity is particularly necessary for the growth of the quantity and quality of the economy. This paper selects the provincial panel data of 30 provinces in China from 2001 to 2015, and establishes a panel exchangeable errors model to analyze the impact of eight indicators on green total factor productivity (GTFP) and verifies its effectiveness. Empirical analysis shows that inter-provincial government competition, environmental regulation, energy consumption, and capital stock have a significant impact on green total factor productivity. The influence of foreign direct investment, industrial structure, and industrialization level on the total factor productivity of green is not significant. Therefore, the government should adopt suitable, flexible and diverse environmental regulation policies, promote energy-saving emission reduction and technology innovations through policies such as taxes and subsidies, strengthen the linkage mechanism between industrial structure upgrading and energy efficiency, to increase green total factor productivity.

scholarly journals Impact of Energy Price Distortion on Green TFP Based on Spatial Econometric Model

2022 ◽  
Vol 2022 ◽  
pp. 1-8
Author(s):  
Huayu Guan ◽  
Mengyue Xing
Keyword(s):  
Energy Conservation ◽  
Environmental Protection ◽  
Environmental Regulation ◽  
Total Factor Productivity ◽  
Mediating Effect ◽  
Factor Price ◽  
Energy Price ◽  
Factor Productivity ◽  
Price Distortion ◽  
The Impact

With environmental regulation as the intermediary, this paper studies the influence mechanism and mediating effect of energy price distortion on green total factor productivity. On the basis of the panel data of 30 provinces in China (except Tibet, Hong Kong, Macao, and Taiwan), the research results from the study of panel and spatial metrology show that energy price distortion has a significant negative effect on the improvement of green total factor productivity. Different environmental regulation tools have different impacts, and the impact effect of fiscal energy conservation and environmental protection expenditure is better than that of pollution punishment. The transmission effect of energy price on environmental regulation policies is different when environmental regulation is the intermediary. The increase of the degree of energy price distortion will increase the financial expenditure of energy conservation and environmental protection, while the energy factor price will increase the green total factor productivity with the increase of pollution punishment.

Trade Liberalisation and Industrial Productivity: Evidence from Manufacturing Industries in Pakistan

2017 ◽  
Vol 56 (4) ◽  
pp. 319-348
Author(s):  
Gulzar Ahmed ◽  
Muhammad Arshad Khan ◽  
Tahir Mahmood ◽  
Muhammad Afzal
Keyword(s):  
Total Factor Productivity ◽  
Negative Impact ◽  
Raw Materials ◽  
Manufacturing Sector ◽  
Industrial Sector ◽  
Manufacturing Industries ◽  
Trade Liberalisation ◽  
Factor Productivity ◽  
Industrial Productivity ◽  
The Impact

This study examines the impact of trade liberalisation on the industrial productivity for a panel of twenty seven 3-digit manufacturing industries in Pakistan over the period 1980-2006. Using a variant of the Cobb-Douglas production function for industrial sector, we estimated output elasticities. The results show positive output elasticities with respect to labour, capital and raw materials for the pre-trade liberalisation period (1981 –1995) as well as post-trade liberalisation period (1996-2006). For the pre-liberalisation period, we observe positive output elasticity with respect to energy, while it turns out to be negative in the post-liberalisation period probably due to energy crisis in Pakistan. In the second stage, we calculate total factor productivity (TFP) and examine the impact of trade liberalisation on TFP for pre-and post-trade liberalisation periods. The results reveal that trade liberalisation proxied by import duty has positive but negligible impact on the TFP in the pre-as well as post-liberalisation periods. On the other hand, effective rates of protection exert large negative impact on the TFP in the post-liberalisation than the pre-liberalisation period. JEL Classifications: F14, F13, O53, L60 Keywords: Trade Liberalisation, Total Factor Productivity, Manufacturing Sector of Pakistan

Total Factor Productivity in Manufacturing Industry for Delhi for Last Thirty Years

2014 ◽  
Vol 1 (1) ◽  
pp. 18-36
Author(s):  
Anindya Bhattacharya
Keyword(s):  
Total Factor Productivity ◽  
Manufacturing Industry ◽  
Time Series Data ◽  
Manufacturing Sector ◽  
National Level ◽  
Recent Time ◽  
Manufacturing Industries ◽  
Series Data ◽  
Factor Productivity ◽  
Level Data

This paper attempts to give an overview of the Total Factor Productivity Growth (TFPG) for the NCR or Delhi for the period from 1981-82 to 2011-12 for the manufacturing sector. Using the ASI time series data and Growth Accounting Approach the TFPG Index values are computed. The study reveals that for most of the major group or 2-digit level of manufacturing industries the respective TFPG values are declining over time. The results indicate that the lacklustre performance of the manufacturing sector equally holds in Delhi as it is already verified for the national level data of the sector through many other studies in recent time.

scholarly journals Improvement of Different Types of Environmental Regulations on Total Factor Productivity: A Threshold Effect Analysis

2019 ◽  
Vol 2019 ◽  
pp. 1-12
Author(s):  
Xubin Lei ◽  
Shusheng Wu
Keyword(s):  
Environmental Regulation ◽  
Total Factor Productivity ◽  
Environmental Regulations ◽  
Threshold Model ◽  
Threshold Effect ◽  
Impact Behavior ◽  
Factor Productivity ◽  
Data Set ◽  
Different Types ◽  
The Impact

Based on the distinction of different types of environmental regulations, this paper attempts to test the threshold effect of environmental regulation on the total factor productivity (TFP) by employing a panel threshold model and a province-level panel data set during 2006–2016. Research results show that the influence of command-and-control and market incentive environmental regulation on the total factor productivity has a single threshold conversion characteristic of foreign direct investment (FDI) and financial scale, but the impact behavior and influence degree around the threshold are inconsistent. The effect of voluntary conscious environmental regulation on the total factor productivity has a single threshold conversion feature of human capital, and moderately enhanced intensity of environmental regulation is conducive to promoting the total factor productivity after crossing the threshold. Finally, in order to enhance the regional total factor productivity, relevant policy recommendations are proposed.

scholarly journals Intelligence and Green Total Factor Productivity Based on China’s Province-Level Manufacturing Data

2021 ◽  
Vol 13 (9) ◽  
pp. 4989
Author(s):  
Yining Zhang ◽  
Zhong Wu
Keyword(s):  
Total Factor Productivity ◽  
Manufacturing Industry ◽  
Positive Impact ◽  
Mechanism Analysis ◽  
Factor Productivity ◽  
Green Development ◽  
Central Regions ◽  
Intelligent Technology ◽  
Deep Integration ◽  
The Impact

The application of intelligent technology has an important impact on the green total factor productivity of China’s manufacturing industry. Based on the provincial panel data of China’s manufacturing industry from 2008 to 2017, this article uses the Malmquist–Luenburger (ML) model to measure the green total factor productivity of China’s manufacturing industry, and further constructs an empirical model to analyze the impact mechanism of intelligence on green total factor productivity. The results show that intelligence can increase the green total factor productivity of the manufacturing industry. At the same time, mechanism analysis shows that intelligence can affect manufacturing green total factor productivity by improving technical efficiency. However, the effect of intelligence on the technological progress of the manufacturing industry is not significant. In addition, the impact of intelligence has regional heterogeneity. It has significantly promoted the green total factor productivity in the eastern and central regions of China, while its role in the western region is not obvious. The research in this article confirms that intelligence has a significant positive impact on the green total factor productivity of the manufacturing industry, and can provide suggestion for the current further promotion of the deep integration of intelligence and the green development of the manufacturing industry to achieve the strategic goal of industrial upgrading.

scholarly journals The Influence Study on Environmental Regulation and Green Total Factor Productivity of China’s Manufacturing Industry

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Ying Li ◽  
Siyu Li
Keyword(s):  
Technical Efficiency ◽  
Environmental Regulation ◽  
Total Factor Productivity ◽  
Manufacturing Industry ◽  
Environmental Regulations ◽  
Environmental Benefits ◽  
Productivity Index ◽  
Factor Productivity ◽  
Green Development ◽  
High Investment

Green development is the theme of the current era. Environmental regulation is an essential means to achieve environmental benefits and improve the total green factor productivity of manufacturing facing a series of problems brought by the development model of “high investment, high pollution, and high consumption.” Appropriate environmental regulations need to be implemented to achieve economic and environmental harvest. Based on the panel data of 25 manufacturing industries from 2003 to 2016 in China, this thesis constructs a comprehensive indicator of environmental regulation and calculates the green total factor productivity, and its decomposition applied SBM directional distance function and Malmquist–Luenberger productivity index. Besides, this thesis conducts an empirical analysis of environmental regulation’s effect on green productivity in China. The main conclusions showed that the green total factor productivity of China’s manufacturing industry maintains an upward trend on the whole, and the growth of GTFP mainly depends on technological progress rather than the improvement of technical efficiency. The great differences have significant industrial heterogeneity characteristics of GTFP. A single threshold in the whole manufacturing industry, environmental regulation, and GTFP of industries are shown to be “U shape,” and the left of the inflection point is not significant. Environmental regulations and GTFP of moderation and slightly pollution industries are “U shape,” and there is no nonlinear relationship between environmental regulation intensity and GTFP in light pollution industries. Therefore, the government’s optimal environmental regulation intensity should be implemented according to the industry’s heterogeneity to prevent the phenomenon of “ineffective regulation;” it is necessary to pay attention to both technological innovation and technical efficiency.

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