scholarly journals Research on the Impact of Environmental Regulations on Industrial Green Total Factor Productivity: Perspectives on the Changes in the Allocation Ratio of Factors among Different Industries

2021 ◽  
Vol 13 (23) ◽  
pp. 12947
Author(s):  
Jiaqi Yuan ◽  
Deyuan Zhang
Keyword(s):  
Human Capital ◽  
Total Factor Productivity ◽  
Environmental Regulations ◽  
Production Factor ◽  
Regulatory Effect ◽  
Factor Productivity ◽  
Regulatory Policies ◽  
Input And Output ◽  
Allocation Ratio ◽  
The Impact

This paper constructs a two-sector manufacturer model of endogenous technological progress. We analyze the impact of environmental regulations on the factor input and output of different industries. Then, we reveal the intermediary role of inter-industry factor allocation in the impact of environmental regulations on industrial green total factor productivity (GTFP). Finally, the paper uses panel data from 30 provinces in China’s industry from 2000 to 2017 to conduct empirical tests. We can draw the following conclusions: (1) The relative magnitude of the output compensation of the production department and the innovation compensation of the R&D department could change the impact of environmental regulations on the input and output of inter-industry factors, and the comprehensive effects of both input and output will affect the level of GTFP. (2) The curve of the direct impact of environmental regulations on GTFP is in an inverted “U” shape. However, the production factor allocation ratio can “reverse” the inhibitory effect of high-intensity regulations on GTFP. (3) The capital factor has a greater impact on the regulatory effect, but the labor factor has a more lasting impact on the regulatory effect. High-strength environmental regulations can enhance manufacturers’ preference for human capital. Therefore, formulating environmental regulatory policies oriented to improve the ratio of factor allocation, mixing different types of regulatory policies, and increasing investment in human capital are all conducive to accelerating the transformation and upgrading of China’s industrial structure and achieving high-quality development of the industrial economy.

scholarly journals Can a Win–Win Situation of Economy and Environment Be Achieved in Cities by the Government’s Environmental Regulations?

2021 ◽  
Vol 13 (11) ◽  
pp. 5829
Author(s):  
Xinfei Li ◽  
Baodong Cheng ◽  
Qiling Hong ◽  
Chang Xu
Keyword(s):  
Environmental Regulation ◽  
Total Factor Productivity ◽  
Environmental Quality ◽  
Negative Impact ◽  
Environmental Regulations ◽  
Removal Rate ◽  
Utilization Rate ◽  
Factor Productivity ◽  
Regulatory Policies ◽  
The Impact

Based on the panel data of 216 prefecture-level cities in China from 2003 to 2016, this study selected five emission-reduction indicators (industrial SO2 removal rate, soot removal rate, comprehensive utilization rate of industrial solid waste, domestic sewage treatment rate, and harmless treatment of domestic waste rate) to quantify the intensity of urban environmental regulations. Based on the intensity of environmental regulations, the authors further studied the impact of environmental regulations on economic quality (green total factor productivity) and environmental quality (PM2.5). The test results showed that the impact of environmental regulation on PM2.5 is a U-type change that first declines and then rises, while the impact of the implementation of environmental regulation on green total factor productivity is an inverted U-shaped change, which first increases and then decreases. On the one hand, appropriate environmental regulations are conducive to improving environmental quality and improving urban green total factor productivity. On the other hand, excessive environmental regulations have not only failed to improve environmental quality, but also have a negative impact on the improvement of economic quality. In addition, there are regional differences in the impact of environmental regulations, so it is necessary to formulate appropriate and local environmental regulatory policies.

The Dynamic Correlation Between Capital Deepening and Total Factor Productivity in China

2020 ◽  
Vol 24 (4) ◽  
pp. 524-531
Author(s):  
Wuliu Zhang ◽  
Keyword(s):  
Human Capital ◽  
Total Factor Productivity ◽  
Negative Impact ◽  
Positive Impact ◽  
Linear Structure ◽  
Physical Capital ◽  
Influence Coefficient ◽  
Factor Productivity ◽  
Capital Deepening ◽  
The Impact

The impact of capital deepening on total factor productivity (TFP) is a significant and controversial issue. Based on the calculation of relevant indicators, this study adopts a Bayesian time-varying parameter model, Bayesian quantile regression, and adaptive Bayesian quantile models for in-depth statistical analysis. TFP was found to have a complex non-linear structure, and physical and human capital deepening indicators show a significant upward trend. The deepening of physical capital has a negative impact on TFP, while the deepening of human capital has a positive impact. In the capital deepening structure, the level of TFP has been improved and its structure optimized. Primary human and non-production physical capital deepening has no significant effect on TFP, while secondary human capital deepening has some significant effects on TFP. Tertiary and productive human capital deepening of TFP present two different forms of significant effect: the influence coefficient of the former declines in the increasing quantile and the change is larger, while the latter has a stable negative impact. The results of this study provide insights in terms of the improvement of China’s productivity.

scholarly journals Modeling the Impact of Innovation on Economic Quality and Environmental Pollution Change under Consideration of Environmental Regulation

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Xinfei Li ◽  
Yuan Tian ◽  
Yueming Li ◽  
Chang Xu ◽  
Xiaobing Liu ◽  
...  
Keyword(s):  
Sustainable Development ◽  
Environmental Pollution ◽  
Total Factor Productivity ◽  
Environmental Regulations ◽  
Pollutant Emissions ◽  
Factor Productivity ◽  
So2 Emissions ◽  
The Impact ◽  
China’S Economy

Under the constraints of resources and the environment, exploring the channels to improve the quality of China’s economy is very important for China’s current sustainable development. Therefore, this paper studies whether innovation can improve the quality of China’s economy and explore the path of sustainable development from the perspective of the city. Based on the Malmquist–Luenberger index and DEA-Malmquist index, this paper, respectively, measures the green total factor productivity (GTFP) and total factor productivity (TFP) of 193 cities in China. On the basis of obtaining the GTFP, TFP, and various pollutant emissions of 193 cities, this paper selects environmental regulations as the threshold variable and the number of urban patents as the explanatory variable to measure the level of urban innovation. On this basis, we examine the impact of innovation quality on economic quality and environmental pollution under different environmental regulatory intensities. The research results show that the impact of innovation on GTFP and TFP under different environmental regulations is always positive, but the impact coefficient and significance level vary. In addition, the impact of innovation on SO2 emissions under different environmental regulations has also changed. With the increase of environmental regulations, the effect of reducing emissions is gradually significant. The conclusion of this paper better interprets the development of TFP and GTFP under the innovation-driven strategy, provides a decision-making basis for departments at all levels to formulate innovation support policies, and explores the path of sustainable development.

Are human capital, intellectual property rights, and research and development expenditures really important for total factor productivity? An empirical analysis

2019 ◽  
Vol 46 (6) ◽  
pp. 756-774 ◽  
Author(s):  
Misbah Habib ◽  
Jawad Abbas ◽  
Rahat Noman
Keyword(s):  
Economic Growth ◽  
Human Capital ◽  
Intellectual Property ◽  
Property Rights ◽  
Research And Development ◽  
Total Factor Productivity ◽  
Intellectual Property Rights ◽  
Factor Productivity ◽  
Content Type ◽  
The Impact

Purpose The purpose of this paper is to investigate the impact of human capital (HC), intellectual property rights (IPRs) and research and development (R&D) expenditures on total factor productivity (TFP), which leads to economic growth. Design/methodology/approach The panel data technique is used on a sample of 16 countries categorized into two groups, namely Brazil, Russia, India and China (BRIC) and Central and Eastern European (CEE) countries and, in order to make a comparison for the time period of 2007–2015, the researchers used a fixed effect model as an estimation method for regression. Findings The results indicate that HC, IPRs and R&D expenditures appear to be statistically significant and are strong factors in determining changes in TFP and exhibit positive results in all sample sets. Moreover, IPRs alone do not accelerate growth in an economy, especially taking the case of emerging nations. Originality/value Considering the importance of CEE and BRIC countries, and inadequate research on these regions with respect to current study’s variables and techniques, the present research provides valuable insights about the importance of HC, IPR and R&D activities and their impact on TFP, which leads to economic growth. IPRs create a fertile environment for R&D activities, knowledge creation and economic development. Distinct nations can attain better economic status via HC, R&D activities, innovation, trade and FDI, although the relative significance of these channels is likely to differ across countries depending on their developmental levels.

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 The Impact of Foreign Direct Investment Spillover Effects on Total Factor Productivity in Sri Lanka

2020 ◽  
pp. 37-49
Author(s):  
Kalaichevi Ravinthirakumaran ◽  
Tarlok Singh ◽  
Eliyathamby Selvanathan ◽  
Saroja Selvanathan
Keyword(s):  
Human Capital ◽  
International Trade ◽  
Sri Lanka ◽  
Research And Development ◽  
Total Factor Productivity ◽  
Spillover Effects ◽  
Annual Data ◽  
Factor Productivity ◽  
Positive Effects ◽  
The Impact

This paper examines whether FDI generates productivity spillovers in Sri Lanka, using the annual data over the period from 1978 to 2015. The autoregressive distributed lag model has been estimated to investigate the effects of FDI, research and development, human capital, international trade, technological gap, rate of inflation, population growth and civil war on total factor productivity (TFP). The results reveal that FDI positively influences TFP. The results also confirm that research and development, human capital and international trade have positive effects. The findings suggest that Sri Lanka needs to increase investment in human capital and in research and development and needs to introduce policies to attract FDI inflows.

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

Impact of Determinants of Industrial Development on Employment and Wages in Indian Manufacturing

2020 ◽  
pp. 18-30
Keyword(s):  
Technical Efficiency ◽  
Total Factor Productivity ◽  
Technical Change ◽  
Positive Impact ◽  
Manufacturing Sector ◽  
Factor Productivity ◽  
Firm Level ◽  
Employment Level ◽  
The Impact ◽  
Level Performance

ABSTRACT The present study was undertaken to explore the evolution of the impact of firm-level performance on employment level and wages in the Indian organized manufacturing sector over the period 1989-90 to 2013-14. One of the major components of the economic reform package was the deregulation and de-licensing in the Indian organized manufacturing sector. The impact of firm-level performance on employment and wages were estimated for Indian organized manufacturing sector in major sub-sectors in India during the period from 1989-90 to 2013-14 of the various variables namely profitability ratio, total factor productivity change, technical change, technical efficiency, openness (export-import), investment intensity, raw material intensity and FECI in total factor productivity index, technical efficiency, and technical change. The study exhibited that all explanatory variables except profitability ratio and technical change cost had a positive impact on the employment level. Out of eight variables, four variables such as net of foreign equity capital, investment intensity, TFPCH, and technical efficiency change showed a positive impact on wages and salary ratio and rest of the four variables such as openness intensity, technology acquisition index, profitability ratio, and technical change had negative impact on wages and salary ratio. In this context, the profit ratio should be distributed as per the marginal rule of economics such as the marginal productivity of labour and capital.

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