Level Of Environmental Regulation Research Articles

Environmental regulation, R&D subsidies, and industrial green total factor productivity

In the face of worsening global environmental degradation, significant attention has been devoted to the greening of industrial transformation and development, specifically by improving industrial green total factor productivity (GTFP). We explored the impact of environmental regulations on industrial GTFP and the moderating influence of R&D subsidies. We established a theoretical model in which environmental regulations affect industrial GTFP, and this relationship is moderated by R&D subsidies. The results revealed that the impact of environmental regulations on industrial GTFP is U-shaped and that the current level of environmental regulation is insufficient to boost industrial GTFP. Green technological innovation plays a mediating role in the effect of environmental regulations on industrial GTFP. Furthermore, R&D subsidies nonlinearly moderate the relationship, resulting in a steeper U-shaped curve and accelerating the arrival of the tipping point. These findings provide theoretical support and a reference for government policies that promote industrial greening.

Climate policy and corporate green transformation: Empirical evidence from carbon emission trading

The implementation of climate policies in the financial sector is a global consensus among countries committed to sustainable development. Therefore, the impact of carbon trading policy (CTP) on firms’ green transformation (GT) is examined by manually compiling a directory of emission control enterprises in China’s carbon market from 2008 to 2022, using a difference-in-differences model. This topic must be urgently explored through theoretical and empirical studies. This study found that CTP can promote corporate green transformation; however has no industry and regional spillover effects. Mechanism analyses indicate that CTP can promote a firm’s green transformation by enhancing green innovation and environmental, social, and governance (ESG) performance. Heterogeneity analysis reveals that the effect of CTP on GT is effective when firms have higher “greenwash” scores, lower financialization, weaker product market competition, and higher levels of environmental regulation. This study reveals the microeconomic effects of CTP, and the findings provide empirical evidence that China can realize Porter’s hypothesis.

The Impact of Digital Trade Development on Regional Green Innovation

Using provincial panel data from China spanning 2011 to 2022, this paper analyzes the impact, mechanisms, and regional differences in digital trade’s effects on regional green innovation. It also explores the threshold effect between digital trade and green innovation, with environmental regulation serving as the threshold variable. The results indicate the following: first, after accounting for government intervention, foreign direct investment, human capital, industrialization, information technology infrastructure, and economic development, digital trade significantly promotes regional green innovation. This conclusion remains valid after a series of robustness tests. Second, digital trade promotes regional green innovation through three mechanisms: accelerating industrial structure upgrading, promoting industrial agglomeration, and enhancing technology transfer. Third, environmental regulation leads to a non-linear relationship between digital trade and green innovation. Higher levels of environmental regulation make digital trade’s contribution to green innovation more significant. Finally, the effects of digital trade on green innovation vary by region in China. This impact is more pronounced in eastern provinces, regions with advanced digital economies, areas with well-developed transport infrastructure, and provinces with a higher degree of trade openness. These findings hold substantial implications for advancing green innovation and promoting sustainable social development in China.

Geopolitical risks and energy transition: the impact of environmental regulation and green innovation

This study examines the impact of geopolitical risk on energy transition, focusing on the moderating roles of environmental regulations and green innovation within OECD countries. By employing a multivariate linear and nonlinear regression model, we identify a substantial positive effect of geopolitical risk on energy transition. Our analysis indicates that stronger environmental regulations and advancements in green innovation significantly amplify this effect. Through threshold effect bootstrap sampling tests, we detect a nonlinear relationship between geopolitical risk and energy transition at varying levels of environmental regulation and green innovation. We also explore lag effects, revealing that the influence of geopolitical risk on energy transition grows stronger over time. The inclusion of interaction terms in our analysis further clarifies the moderating influences of environmental regulation and green innovation. Utilizing a range of geopolitical risk indicators and regression methods, our findings are robust, consistently highlighting the proactive role of geopolitical risk in fostering energy transition. These insights highlight the importance of integrated strategies that harness environmental regulations and technological innovation to facilitate a resilient and efficient energy transition in the face of challenges posed by geopolitical uncertainties.

Path dependence in environment-related innovation: evidence from listed firms in China

ABSTRACT This paper studies the path dependence effect in corporate innovation based on the patent data of Chinese listed firms. The results provide robust evidence of the path dependence in technology innovation. The accumulated stock of brown patents reduces the ratio of green patents to total patents newly granted, thus inhibiting green structural changes in innovation. The accumulated stock of green patents increases the ratio of green patents in total patents granted, promoting structural change towards green innovation. The path dependence effect exists in both green inventions and green utility model patents. The heterogeneity analysis shows that both brown and green patent stocks of heavy polluting firms have a weaker effect on the ratio of green inventions than non-heavy polluting firms. The negative path dependence effect of brown patents on green innovation is stronger in firms with large scale, state ownership, and a high level of environmental regulation. However, the negative path dependence effects on green innovation can be alleviated for firms with superior environmental and financial performance. This suggests that the government has to create economic incentives to break the path dependence and encourage firms to engage in green innovation.

The Nonlinear Effects of Digital Finance on Corporate ESG Performance: Evidence from China

Digital finance enhances corporate ESG performance and is essential for achieving sustainable development; however, its consistent effectiveness in improving ESG outcomes remains contested. Using panel data from A-share listed companies on the Shanghai and Shenzhen stock exchanges in China from 2011 to 2021, this study empirically examines nonlinear effects, transmission mechanisms, and moderating factors. The results indicate a U-shaped relationship between digital finance and ESG performance, with a positive impact becoming apparent when digital finance exceeds the threshold of 3.81. Mechanism tests reveal that green technological innovation and public environmental attention are crucial transmission channels for the nonlinear effects. Furthermore, financial regulation levels and environmental uncertainty negatively moderate this relationship, while corporate digital transformation has a positive moderating effect. Further analysis shows that the U-shaped relationship is more pronounced in areas with lesser financial advancement and higher levels of environmental regulation, as well as in non-high-tech industries, non-manufacturing sectors, smaller firms, and companies without political connections. This study provides empirical evidence and policy insights to support the promotion of financial services that better facilitate corporate sustainability.

Climate policy uncertainty and urban green total factor productivity: Evidence from China

Climate change has an impact on the environment and the economy, and green total factor productivity (GTFP here after) is a composite proxy contains both the contents of the environmental protection and the economic development. Serving the climate policy uncertainty index of China (CCPU here after) as the key explanatory variable, we employ the panel regression model to explore the influence of CCPU on GTFP of the 277 Chinese prefecture-level cities. The main findings are as follows: First, CCPU has a negative impact on GTFP; Second, the negative impact of CCPU on GTFP varies in different cities according to the population size, location, and environmental regulation level; Third, our empirical results are stable under the robustness tests; Fourth, the further analysis of this paper indicate that the negative impact of CCPU on GTFP mainly comes from the period after 2016. In addition, the negative impact of CCPU is mainly through the channel of the Technical Efficiency. Finally, the sensitivity of the Technical Efficiency to CCPU may vary according to the public environmental concerns and government science expenditures of different cities. The major findings of this paper not only have practical significance for China and its local governments, but also provide useful references for other countries, especially the developing countries.

Effects of the Policy of Re-Designation of Counties as Cities or City Districts on the Agricultural Carbon Emission: Evidence from the Yangtze River Delta Region in China

It is of great practical significance to utilize the agricultural carbon emission reduction effect of the policy of re-designation of counties as cities or city districts (RCCD) to achieve agricultural high-quality development. This paper uses panel data of 39 cities in the Yangtze River Delta region in China from 2010 to 2022, and adopts a staggered difference-in-difference model and a panel threshold model to identify the causal impact of the policy of RCCD on agricultural carbon emissions (ACE). We show that: (1) Overall, the policy of RCCD exerts a tangible dampening effect on ACE, with cities in the experimental group exhibiting a significant reduction of 0.069 in agricultural carbon emissions compared to the control group post-implementation of the policy. (2) A dual-threshold effect of environmental regulation emerges in the context of the policy of RCCD, wherein the impact on ACE varies depending on the level of environmental regulation. (3) The policy of RCCD exerts a notable inhibitory influence on urban ACE in cities with high urbanization levels, underdeveloped regions and central regions. (4) Agricultural green technology progress plays the mediating role in the relationship between the policy of RCCD and ACE. (5) The suppressive effect of the policy of RCCD on ACE is characterized by a delayed and enduring influence. Our study has both theoretical and practical implications for accelerating agricultural high-quality development.

Relationship Between Environmental Regulations and Global Value Chains in Chinese Manufacturing

While active participation in GVCs can stimulate economic growth, it has also been noted to exacerbate environmental pollution. To address environmental concerns, most countries have strengthened environmental regulations, which in turn may affect the positioning of countries within GVCs. This study empirically analyzes the impact of environmental regulations imposed by the Chinese government on the positioning of the manufacturing sector within GVCs of Chinese manufacturing industries from 2006 to 2018. The findings of the research are as follows: Firstly, the strengthening of environmental regulations has an inverted U-shaped impact on the overall GVC position of Chinese manufacturing sector, demonstrating the combined effects of cost effect and innovation compensation effect. Specifically, when environmental regulations are lower than a certain level, strengthening regulations shifts the GVC position upstream. However, when regulations are more stringent than the level, further strengthening them leads to a downstream shift in GVC position. Secondly, it seems that China's current level of environmental regulation is below the apex of the inverted U-shaped curve, and therefore, it is anticipated that further strengthening of environmental regulations in China will result in a further upstream shift in the GVC position. Thirdly, these analytical results are particularly applicable to technology-intensive industries.

The impact of peer effect of industrial robot application on enterprise carbon emission reduction.

The application of intelligent technology, such as industrial robots, is related to the environmental governance effectiveness of enterprises and the realization of the goal of "carbon peak and carbon neutrality". Due to their similar external environments, driven by economic rationality, peer enterprises will mimic the robotics applications of other enterprises, which in turn will affect the enterprises' carbon emissions. However, little literature has explored the impact of industrial robot application on enterprise carbon emissions from the perspective of peer effect. Based on the data of Shanghai and Shenzhen A-share manufacturing listed enterprises in China from 2011 to 2021, this paper explores the impact of industrial robot application on carbon emission reduction of manufacturing enterprises from the perspective of peer effect. It is found that the industry peer effect and regional peer effect brought by the application of industrial robots are conducive to promoting the carbon emission reduction of enterprises. Among them, the industry peer effect of industrial robot applications promotes carbon emission reduction by enhancing the green innovation ability of enterprises, while the regional peer effect promotes carbon emission reduction by improving the service level of enterprises. It is further found that the degree of industry competition and the level of environmental regulation have inverted U-shaped moderating effects on the industrial robot application industry peer effect, regional peer effect, and enterprises' carbon emission reduction, respectively. The results enrich the research on the impact of industrial robot application on carbon emission reduction of manufacturing enterprises and provide policy implications for improving the environmental performance of enterprises.

Female executive and energy consumption intensity: The role of green innovation

We widely explore the positive effect of female executives on ECI, the energy consumption per unit of output. We find that female executives will promote ECI reduction of corporate. And the result holds after a series of robustness and endogeneity tests. Further analysis indicates that the positive effect will be stronger in enterprises with lower level of environmental regulation, in heavily polluting industry, and whose executives with more environmental background. Moreover, female executives will reduce ECI by promoting green innovation, both in quantity and quality. Our results enrich the study of female executives on corporate environmentally friendly development, focusing on green innovation as underlying channel.

Public Perception of Climate Risk, Environmental Image, and Corporate Green Investment

Climate risk has garnered greater attention in recent years, increasing the public’s demand for climate change information. Public attention to climate risk has also increased corporate environmental governance pressure, which inevitably has an impact on the green investment of enterprises. To deepen the understanding of the issue, this article uses Chinese A-share listed manufacturing companies as a research sample from 2018 to 2022 to investigate the impact of public climate risk perception on corporate green investment. This research found that public perception of climate risk can help to promote green investment among enterprises; its route of action is generally achieved through green technological innovation; and an environmentally conscious image can strengthen the promotion effect of the public perception of climate risk on green investment. Further, public perceptions of climate risk contribute more to corporate green investment and the moderating effect of environmental image is more significant in regions with low levels of environmental regulation. This study not only helps to improve the level of public participation in climate governance, but also accounts for environmental regulation limitations. Clear enterprise differentiation and preventive green investment have a positive impact on enterprises and has the ability to improve climate governance and help companies consciously fulfill their environmental responsibility.

The impact of foreign direct investment on green innovation efficiency: Evidence from Chinese provinces.

Improving green innovation efficiency (GIE) is the key to achieve high-quality economic development in China, and the introduction of foreign direct investment (FDI) has become an important path choice to promote the GIE. Based on the data of 30 provinces in China, this paper explores the linear and nonlinear effects of FDI on GIE from both quantity and quality perspectives, and further analyzes the mediating role of environmental regulation level. The results show that: (1) From 2011 to 2020, the GIE of all provinces in China generally shows an upward trend. (2) The quantity and quality of FDI have a significant positive impact on the improvement of GIE in China's provinces, and this impact has regional heterogeneity. (3) The quantity and quality of FDI can promote the improvement of GIE in China through the level of environmental regulation (ER). (4) With the level of knowledge accumulation and GIE as the threshold variables, the quantity and quality of FDI have a single threshold effect on the GIE of China's provinces. The conclusions of this study provide some policy implications for local governments to make full use of FDI to perform green innovation activities.

Structural characteristics and influencing factors of a spatial correlation network for tourism environmental efficiency in China

The tourism industry in China presents uneven tourism efficiency but deepening spatial associations; thus, tourism resources must be more rationally allocated. In this study, the highly efficient SBM model was used to measure the tourism environmental efficiency of 31 provinces in China. A spatial correlation network is then constructed based on the gravity model, and the structural characteristics and influencing factors of the network are analyzed. The results show that (1) the overall tourism environmental efficiency in China presents a fluctuating growth trend, with significantly higher values observed in the eastern region than in the central and western regions; moreover, the growth in efficiency in the eastern region has been relatively stable in recent years, that in the central region has increased, while that in the western region has significantly declined. (2) A spatially linked network with a stable tourism environmental efficiency structure has been formed in China. The number of network relations and density of the network fluctuate and increase, while the network efficiency continues to decrease; however, a strong small-world nature is observed. (3) An obvious network core–edge structure is observed, with Shanghai, Beijing, Zhejiang, and Jiangsu at the center showing a significant intermediary role and remote provinces such as Tibet, Xinjiang, Ningxia, and Inner Mongolia at the edge showing fewer connections. (4) The four major plates of China based on the CONCOR algorithm are sparsely connected internally and show strong inter-plate connections and spillover effects. (5) The industry support capacity difference matrix, technological development level difference matrix, transportation accessibility difference matrix, and environmental regulation level difference matrix significantly and positively affect spatial associations, while the geographical distance matrix significantly and negatively affect spatial association relationship establishment. These findings have important theoretical and practical significance for the sustainable development of tourism in China's provinces and cities.

Does the Energy-Consumption Permit Trading Scheme Improve Carbon Emission Performance? Evidence from a Quasi-Natural Experiment in China

The Chinese government launched the Energy-Consumption Permit Trading Scheme (ECPT) in 2016 as a pilot policy initiative to achieve energy conservation and emissions reduction goals. To generate a quasi-natural experiment, this study used a difference-in-differences (DID) approach with panel data from 2006 to 2020 in China. The goal was to explore the impact of the ECPT policy on the carbon emission performance (CEP) as well as analyze the underlying influence processes. The findings indicate that applying the ECPT has a considerable positive influence on the CEP. In comparison to provinces that did not engage in the pilot program, those that did reported a 4.5% improvement in CEP. We can safely declare that the results remain consistent and trustworthy after undergoing a battery of rigorous tests to assess the robustness of our findings. The mechanism’s evaluation revealed that the ECPT has the potential to improve the CEP, mostly via changing energy consumption patterns and stimulating technological innovation. Furthermore, when we considered heterogeneity, we discovered that factors such as geographical location, the level of green financing development, and the level of environmental regulation may affect the ECPT policy effects.

Environmental regulation, energy consumption structure, and industrial pollution emissions

China has become the world’s largest carbon emitter due to its high-investment, low-efficiency development model. It is urgent to reduce industrial pollution emissions. This study analyzes the impact of environmental regulation intensity and energy consumption structure on industrial SO2 pollution emissions by establishing a fixed-effect regression model based on panel data from 2009 to 2018 in China. The results show that the overall environmental regulation intensity in China has a significant negative effect on industrial pollution emissions. In other words, increasing the level of environmental regulation is conducive to reducing industrial pollution emissions. The proportion of coal consumption in the overall national energy consumption structure directly and positively correlated with the concentration of industrial pollution emissions. Due to the differences in economic development and industrial foundation, the pollution emissions effect shows significant heterogeneity in the eastern and western regions of China under the constraint of environmental regulation. Based on these conclusions, this article proposes policy recommendations from four aspects: (1) strengthen environmental regulation, and pay attention to optimize the form of environmental regulation. For example, in the West of China, the government can encourage enterprises to carry out technological innovation and develop green energy hubs by policy and financial support; (2)improve the energy consumption structure, such as encouraging green production; (3) promote industrial structure adjustment and upgrading, such as promoting the energy saving transformation of energy-intensive enterprises, developing green technologies, and reducing the carbon emissions of industrial industries; (4)improve the foreign investment access system and guiding foreign investment to invest in key environmental protection projects.

Environmental Regulation, Institutional Distance and China’s Outward Foreign Direct Investment in the Belt and Road Countries

Purpose - This study aims to explore the direct impact of environmental regulation on outward foreign direct investment (OFDI), and the moderating role of institutional distance in the relationship between the two, focusing on China’s OFDI in 58 countries along the Belt and Road (BRCs) during the period 2003-2021.
 Design/Methodology/Approach - The fixed effects model, DID model and panel threshold model are adopted in the basic estimation and heterogeneity tests.
 Findings - The results show that environmental regulation has a significant positive impact on China’s OFDI into the BRCs, and institutional distance has strengthened this positive impact. But this moderating effect can only be detected when the institutional distance is positive. Comparative analysis before and after the Belt and Road Initiative (BRI) showed that the impact of environmental regulation on China’s OFDI was greater after BRI than before BRI. Furthermore, the significant impact of environmental regulation on OFDI could only be observed in countries with relatively stringent environmental regulation. Threshold tests found that there is a threshold value in the impact of environmental regulation on OFDI. The DID estimation results showed that when the institutional level and environmental regulation level of the host country are lower than that of China, the BRI plays a greater role in promoting China’s OFDI into the BRCs.
 Research Implications - The findings have significant implications for understanding how China’s OFDI responds to the environmental regulation of the host countries, simultaneously considering the impact of institutional distance.

The Regionally Heterogeneous Impact of China’s Environmental Regulation on the Transformation and Upgrading of Its Industrial Structure

Approaches to promoting the transformation and upgrading of China’s industrial structure represent an important issue in high-quality economic development. The upgrading of industrial structures is beneficial not only for environmental protection but also for sustainable economic development. This article first tests the correlation between environmental regulation and the transformation and upgrading of industrial structure through an impulse response function and then uses provincial panel data to analyze the regionally heterogeneous impact of environmental regulation on industrial structure upgrading. The research results indicate that: (1) the presented impulse response graph indicates that environmental regulation shocks have a significant impact on the rationalization and upgrading of industrial structure, and subsequent variance decomposition indicates that environmental regulation has a strong explanatory power on the transformation and upgrading of industrial structure; (2) overall, strengthening the level of environmental regulation is not conducive to the rationalization of industrial structure (RIS), but a strong level of environmental regulation can significantly promote the upgrading of industrial structure (UIS); and (3) at the regional level, there is significant regional heterogeneity in the impact of environmental regulation on the transformation and upgrading of industrial structure in different regions. Environmental regulation can promote UIS in China’s eastern and western regions, but it is not conducive to RIS. Environmental regulation can promote RIS in China’s central region, but it has a negative impact on UIS. The conclusion of this article provides inspiration for sustainable economic development.

The dynamic characteristics of multi‐media carbon pollution and their spatial influencing factors: A case study of the Greater Bay Area of China

AbstractFor urban agglomerations that contain multiple interconnected cities, carbon pollution mitigation is particularly challenging due to the complex pollution transfer among environmental media and among cities. Insufficient attention has been paid to the city‐level metabolic processes of carbon in diverse physicochemical forms and their spatial interactions, impeding the identification and management of multi‐media carbon pollution from the integrated perspective of the whole urban agglomeration. Using the Greater Bay Area of China as a case, this study reveals the dynamic characteristics and spatial influencing factors of multi‐media carbon pollution covering 30 consecutive years based on substance flow analysis and a spatial econometric model. We find increasing necessity for controlling carbon pollution in the solid state, which reached 1890 Gg C/a in 2018 and was significantly higher than that in the gaseous (290 Gg C/a) and liquid (730 Gg C/a) state. Cross‐media transfer of carbon pollution made an increasingly substantial contribution to total carbon pollution from 14.6% to 20.7%, stressing the need for treatment and harmless disposal of sludge and the control of CH4 produced from waste landfilling, wastewater treatment, and livestock manure. Relocation of heavily polluting industries and variances at the level of environmental regulation between cities causes spatial transfer of carbon pollution, while the improvement of industrial structure and the advancement of pollution treatment technology have a positive demonstration effect for carbon pollution abatement of the neighboring cities. This study demonstrates the necessity of multi‐media and multi‐city integrities in carbon pollution mitigation within clustered cities.

Different types of environmental concerns and heterogeneous influence on green total factor productivity: Evidence from Chinese provincial data

Environmental issues have been the focus of attention worldwide, and achieving green development is crucial for solving such issues. This study uses the panel data of 30 Chinese provinces (municipalities and regions) for the period 2010–2020 to examine the general, long-term, short-term, and threshold effects of public environmental concerns and government environmental concerns on the development of green total factor productivity (GTFP). The method of GML index based on SBM-DDF is employed to measure and analyze the spatial and temporal evolution of China's GTFP. Text mining in Python is adopted to estimate the index of these two different types of environmental concerns. The empirical results show that: (1) GTFP demonstrates a distinct pattern of "down - up - down" during the period 2011–2020. (2) Public environmental concern is essential in accelerating the development of GTFP, and it is more significant in areas with higher industrialization and lower environmental pollution. Government environmental concern plays a crucial role in accelerating the development of GTFP, and it is especially significant in areas with lower levels of industrialization and reduced environmental pollution. (3) In terms of long-term and short-term effects, both public environmental concerns and government environmental concerns are essential long-term drivers for enhancing GTFP, rather than short-term ones.(4) Public and government environmental concerns are more effective in promoting GTFP in more economically developed regions. Furthermore, as the intensity of environmental regulation increases, the impact of public environmental concern on GTFP strengthens. Government environmental concerns should be aligned with a higher level of environmental regulation to maximize their contribution to GTFP. The findings above clarify the relationship among public environmental concerns, government environmental concerns, and GTFP, providing a realistic basis for achieving green, low-carbon, and sustainable economic development.