Does Environmental Policy Affect Green Total Factor Productivity? Quasi-Natural Experiment Based on China's Air Pollution Control and Prevention Action Plan

Influence of local governments on the greening of the manufacturing sector: A perspective on environmental governance objectives

The green development of manufacturing industries is significantly impacted by local governments. In this study, we focus on assessing the environmental governance effectiveness by examining the tasks assigned by the central government to each province under the Comprehensive Work Program for Energy Conservation and Emission Reduction. By utilizing panel data from 30 provinces and cities in China from 2011 to 2020, we employ the super-efficient SBM model to evaluate China's manufacturing industry's green total factor productivity. Through various models, including the double-fixed effect and the mediation effect, we investigate the influence of environmental governance targets on the green total factor productivity of the manufacturing industry. Our findings reveal a U-shaped relationship between the environmental governance target and the green total factor productivity of the manufacturing industry. When the pressure of environmental governance targets is below a certain critical value, the green total factor productivity decreases as the target pressure increases. However, once the target pressure surpasses this critical value, the green total factor productivity experiences a positive correlation with the target pressure. Further analysis demonstrates that this U-shaped relationship is observed in regions with low and medium marketization, while regions with high marketization remain unaffected. Moreover, the impact of environmental governance target pressure on green total factor productivity in manufacturing is facilitated by the promotion of green innovation. Furthermore, the relationship between environmental governance target pressure and green total factor productivity in manufacturing is moderated by local government fiscal expenditures. In regions where fiscal expenditures are higher, the influence of environmental governance target pressure on green total factor productivity in manufacturing is more pronounced.

Environmental regulation effect on green total factor productivity in the Yangtze River Economic Belt

As a typical watershed ecological economy in China, the Yangtze River Economic Belt has two equally important objectives, namely ecological protection and economic development. Improving green total factor productivity is an essential approach to achieve these two objectives and promote sustainable growth in this area as well as the whole country. Therefore, this study explores the impact of environmental regulation on green total factor productivity with a panel data of 108 cities in the Yangtze River Economic Belt between 2003 and 2019. We first adopt the super slacks-based measure model to estimate city-level green total factor productivity. With kernel density curve, we find that green total factor productivity shows a downward pressure, and its absolute difference among cities shows a narrowing trend. Trend surface analysis displays an inverted U-shaped as well as a U-shaped spatial structures of green total factor productivity in the north-south as well as east-west directions, respectively. By using Spatial Durbin Model, we find a U-shaped direct impact of environmental regulation on green total factor productivity for the entire sample and three subsamples. For an indirect effect, environmental regulation has a positive spatial spill-over impact in the entire area; an insignificant effect in upstream and midstream areas; and an inverted U-shaped spatial spill-over in downstream area. Besides, we utilize threshold effect analysis to explore the impacts of technology innovation. The results show a single-threshold effect of technology innovation and the promotion effect decreases when technology innovation expenditure exceeds the threshold value. Based on our research findings, we suggest that the authorities should adhere to implementing and increasing the intensity of environmental regulation, so as to achieve better policy results. Moreover, local governments should keep technological innovation expenditure at a reasonable level to maximize the promoting effect of environmental regulation on green total factor productivity.

Winning the Blue Sky Defense War: Assessing Air Pollution Prevention and Control Action Based on Synthetic Control Method

Undoubtedly, the rapid development of urbanization and industrialization in China has led to environmental problems, among which air pollution is particularly prominent. In response, the Chinese government has introduced a series of policies, including the Air Pollution Control and Prevention Action Plan (APPA), which is one of the most stringent environmental regulations in history. The scientific evaluation of the implementation of this regulation is important for China to win the battle of blue sky. Therefore, this study uses a synthetic control method to explore the effects of APPA on air pollution (AP) based on data of 30 provinces from 2000 to 2019. The study concludes that (1) APPA significantly reduces AP in the treatment provinces, and subsequent robustness tests validate our findings. However, the persistence of the policy effect is short in some provinces, and the rate of AP reduction slows down or even rebounds in the later stages of the policy. (2) The reduction effect of APPA varies significantly between regions and provinces. (3) The results of mechanism tests show that APPA reduces AP through high-quality economic development, population agglomeration, control of carbon emissions, and optimization of energy structure. Based on the above findings, targeted recommendations are proposed to promote AP control in China and win the blue sky defense war.

The Nonlinear Influence of Environmental Regulation on the Transformation and Upgrading of Industrial Structure

This paper measures the transformation and upgrading of industrial structure from two aspects of rationalization and upgrading of industrial structure, and empirically analyzes the impact of environmental regulation on industrial structure transformation and upgrading by using data of 29 provinces in China from 2004 to 2015. It was found that there is a significant nonlinear effect between environmental regulation and the transformation and upgrading of industrial structure. Specifically, environmental regulation is not conducive to the rational development of industrial structure, but with the continuous improvement of economic development level and human capital level, the inhibitory effect of environmental regulation on the rationalization of industrial structure is gradually weakened. The influence coefficient of environmental regulation on the rationalization of industrial structure is 0.0619~0.2648. Moreover, environmental regulation effectively drives the upgrading of industrial structure, and when the level of economic development and human capital are higher than the threshold, the role of environmental regulation in promoting the high development of industrial structure is gradually enhanced. The influence coefficient of environmental regulation on the upgrading of industrial structure is 0.0540~0.5626. Therefore, it is of great significance to formulate appropriate environmental regulation policies according to local conditions in the transformation and upgrading of industrial structure.

Evaluation of Industrial Green Transformation in the Process of Urbanization: Regional Difference Analysis in China

Population mobility and the expansion of construction land in industrial development promote urbanization, and the sustainable development of cities creates requirements for the green transformation of industry. This paper uses the directional distance function (DDF) and the global Malmquist–Luenberger (GML) index method—including urbanization factors—to calculate the industrial green transformation (IGT) index in China, and to analyze its evolution and spatial distribution characteristics. The results show that ignoring the urbanization factor will lead to the overestimation of the IGT. The growth of the index has multiple stages, and it shows a decreasing order in the middle, east and west regions. Overall, the distribution of the index spreads out over time, and the gap widens. In terms of spatial correlation, high values are mostly concentrated in the eastern region and low values are mostly concentrated in the western region, and the gap in the eastern region is larger than those in the central and western regions. Therefore, in addition to the transformation of industrial production into a circular economy model, it is also necessary to promote the circulation of technical talent between regions in the development of urbanization, reducing the unbalanced development between regions and comprehensively promoting the green transformation of industry.

Does Environmental Regulation Help Mitigate Factor Misallocation?-Theoretical Simulations Based on a Dynamic General Equilibrium Model and the Perspective of TFP

How environmental regulation affects factor allocation is becoming an emerging hot topic in academia. In this paper, we construct a dynamic general equilibrium model accommodating environmental regulatory shock based on the H-K framework to explain the impact of environmental regulation on factor misallocation from the perspective of aggregate total factor productivity loss changes, and numerical simulation results are provided for several representative scenarios. The results show that environmental regulation has a significant effect on factor market misallocation, but this effect is not simply positive or negative, and it mainly depends on the firms’ initial factor allocation status and the intensity of the shock. Reducing the intensity of environmental regulation for firms that face stronger distortion helps mitigate factor misallocation and, on the contrary, the same policy could exacerbate factor market misallocation. Under the environmental regulatory shock condition, firms’ overhead labor input has a moderating effect on the factor allocation mitigation of environmental regulation. Distorted firms’ higher overhead labor share inhibits the correction of factor misallocation by environmental regulation. And reducing firms’ overhead labor share amplifies the correcting effect of environmental regulation on factor misallocation.

Impact of Environmental Regulations on Energy Efficiency: A Case Study of China’s Air Pollution Prevention and Control Action Plan

Scientific environmental policies promote energy efficiency improvement by influencing the industrial structure and investment in R&D and innovation. In view of the insufficient impact of the Air Pollution Prevention and Control Action Plan (Action Plan for short) on energy efficiency, this paper takes 30 provinces and municipalities of the Chinese Mainland during 2004–2017 as samples and investigates the impact of China’s Action Plan on energy efficiency as well as the impact path by means of the DID method. This paper finds a significant statistical relationship between the two. The following conclusions are drawn. Firstly, the Action Plan significantly promotes the improvement of provincial energy efficiency. Secondly, the Action Plan has heterogeneous impacts on the energy efficiency in different provinces. This heterogeneity is mainly reflected in the differences in resource endowments and the different intensities of environmental governance in different provinces. Thirdly, the upgrading and rationalization of the industrial structure and the investment in R&D and innovation have significantly different moderating effects on the Action Plan’s impact on energy efficiency. The industrial structure rationalization and the investment in R&D and innovation will enhance the promotion effect of the Action Plan on energy efficiency, while the “quantity” of the industrial structure upgrading will weaken this promotion effect, and the moderating effect of the “quality” of the industrial structure upgrading is not significant.

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

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.

Assessment of the Carbon Emission Reduction Effect of the Air Pollution Prevention and Control Action Plan in China

In this study, we propose an integrated econometric framework incorporating the difference-in-differences model, the propensity-score-matching difference-in-differences model, and the spatial difference-in-differences model to explore the effect of the Air Pollution Prevention and Control Action Plan on per capita carbon emission in China at the national, regional, and administrative levels. Contradictory results are supported under different econometric models, which highlight the importance and necessity of comprehensive analysis. Taking 285 prefecture-level and above cities as an example, the empirical results show that APPCAP has effectively reduced per capita carbon emission in China at the national level without the consideration of the spatial spillover effect. However, with the consideration of the spatial spillover effect, APPCAP has effectively and directly increased per capita carbon emission in local pilot cities at the national level, and reduced it among pilot cities via the spatial spillover effect, but the effects have become invalid in the non-pilot cities neighboring the pilot cities. Furthermore, the spatial heterogeneity of the effects of APPCAP on per capita carbon emission are supported at the regional and administrative levels. Finally, some specific policy implications are provided for achieving the “win-win” situation of energy saving, emission reduction, and economic development.