Pollution-intensive Industries Research Articles

Environmental regulation and corporate green innovation: evidence from the implementation of the total energy consumption target in China

AbstractUsing a continuous difference-in-differences (DID) model, this study examines the influence of environmental regulations on corporate green innovation. By analyzing a panel dataset of Chinese publicly listed companies spanning from 2010 to 2020, this study finds that stricter total energy consumption target (TECT) policies, in line with Porter’s hypothesis, have encouraged companies to increase their development of green inventions. Additionally, the study reveals that the positive relationship between TECT policies and corporate green innovation is strengthened by market competition and institutional development. Furthermore, the study finds that the Porter effect primarily affects firms operating in pollution-intensive industries within regions characterized by high energy consumption. This suggests that the TECT policies have effectively directed regions with high energy consumption to prioritize energy control objectives over economic expansion goals. These results emphasize the importance of formulating environmental policies that are tailored to the specific characteristics of different regions, sectors, and individual firms. By doing so, a more effective and targeted approach to sustainable transformation can be achieved.

The impact of intelligent investment on corporate green innovation: Moderating effects of executive green perception and environmental regulation

As firms increasingly invest in intelligent technologies while facing environmental pressures, it is crucial to understand the relationship between these investments and green innovation. This study aims to investigate how intelligent investment influences corporate green innovation, as well as the moderating roles of executive green perception and environmental regulation. Multiple regression analyses are employed to test our hypotheses through the use of panel data from Chinese A-share listed companies (2007–2022). According to the research findings, intelligent investment has a significant positive impact on green innovation, and this effect is further amplified by stronger executive green perception and more stringent environmental regulations. It is noteworthy that various types of firms are affected differently by this effect. State-owned enterprises and pollution-intensive industries exhibit stronger positive relationships, while non-high-tech sectors show more pronounced impacts. These findings enhance our understanding of how firms leverage technology to drive sustainable innovation, offering valuable insights for managers seeking to align tech investments with their goals of sustainability, and for legislators and administrators designing effective environmental regulations. It is recommended that policymakers take into account the establishment of regulatory frameworks that are conducive to intelligent investments, thereby fostering green innovation across various industries.

Does environmental regulation truly enhance corporate green environmental investment? Evidence from the supervision of independent directors in listed companies.

With the increasingly prominent environmental issues in China, the government and citizens alike have intensified their focus on corporate investments in green environmental protection. Nevertheless, as government regulations become more stringent, there is substantial debate over whether environmental regulatory policies can consistently encourage listed companies to increase green environmental investments. Simultaneously, independent board supervision plays a crucial role in promoting the compliance and sustainability of listed companies regarding environmental protection. This paper selected a sample of 246 Chinese listed companies from 2010 to 2019, and used a fixed effects model to examine the impact of environmental regulation on the environmental investment of listed companies in China. Moreover, we used a mediation effect model to analyze the role of independent director supervision in influencing the relationship between environmental regulation and companies' green environmental investment. Additionally, we discuss the heterogeneous impact of environmental regulations on corporate environmental investments. Our findings are as follows: first, during the sample period, the tightening of environmental regulations significantly reduces the growth of environmental investment among the studied firms. As government environmental regulatory policies gradually intensify, the negative impact on environmental investments by listed companies becomes increasingly evident. Second, independent directors help alleviate the adverse impacts of environmental regulations on the environmental investment levels of listed companies. This suggests that the inclusion of independent directors in board governance plays a role in assessing government environmental regulatory policies and overseeing corporate decisions related to environmental investment. Lastly, the heterogeneity analysis indicates that environmental regulation significantly negatively impacts the environmental investment of listed companies in pollution-intensive industries and those located in the western regions. Furthermore, environmental regulatory policies impose greater constraints on the environmental investments of small-sized listed companies compared to their large-sized counterparts.

Research on Corporate Environmental Responsibility: A Case Study of Multinational Corporations

In light of the expanding global environmental challenges, multinational corporations (MNCs) are often held accountable for their disproportionate role in environmental degradation. This study looks at how MNCs safeguard the environment and what factors lead to ecological dangers that are related with them. The production volumes of MNCs and their inclination to relocate pollution-intensive industries to developing countries are the specific subjects of the study. A few of the main obstacles that the study identifies to MNCs' environmental responsibility are the deficiency of the current international legal framework, the lack of harmonization of environmental legislation, and the tendency of developing countries' economic priorities to overlook strict environmental measures. To address these issues, the study recommends the following measures: the establishment of robust monitoring and accountability mechanisms; the direct imposition of practicable environmental liabilities; the strengthening of international judicial cooperation; and the clarification of judicial ambiguities regarding MNCs' legal responsibilities in the environmental sector. The paper uses a case study methodology to provide a comprehensive review of best practices and tactics for improving MNCs' environmental management. The findings underline the importance of governments working together to ensure that multinational firms' actions are consistent with environmental sustainability ideals.

Developing environmental sustainability policy – How financing and subsidies are influencing green innovation in mineral extraction industries in China

Mineral extraction is regarded as a pollution-intensive industry and is confronted with multiple environmental sustainability challenges. This issue poses an existential crisis for mineral extraction due to continued global pressure to adopt more sustainable practices in their functioning. Despite its importance, there is a notable gap in the literature regarding how these companies encounter financial challenges, particularly in the context of high-risk, long development cycles, and the unique double externalities associated with green innovation. This research, leveraging panel data from 2016 to 2023, aims to fill this gap by examining whether Chinese mineral extraction companies demonstrate distinct preferences for specific financing sources and by evaluating the role of government in facilitating their green innovation activities. Our findings indicate that such companies utilize a mix of internal and external financing to support their green innovation projects. It is observed that the influence of external finances channels, namely government subsidies, equity financing and debt financing, on green innovation progressively weakens, a conclusion supported by multiple robustness checks. Furthermore, the study highlights the crucial role of government subsidies in motivating publicly listed companies to enhance their green innovation activities through debt and equity financing, thereby contributing to a more equitable and sustainable development paradigm in the Global South.

Green credit and firms’ span of global production stages

This paper investigates the impact of the green credit policy on firms' span of global production stages. We leverage a comprehensive dataset, including customs trade data, industrial firm data, and Chinese Input-Output tables, and employ a difference-in-differences design that accounts for the pollution spillover effect within the production network. Our findings indicate that firms in pollution-intensive industries tend to move downstream in the global production line, accompanied by an expansion in the span of production stages. We present evidence that the broader range of production stages can be attributed to increased firm productivity. The effect is more pronounced for hybrid processing firms, private firms, foreign firms, and those in industries that rely on external finance dependence. Our study provides valuable insights into the impact of green credit policies and sheds light on firms' strategies in the context of green development.

Spillover effects of structure-adjustment pollution reduction measures in China's iron and steel industry

The iron and steel industry (ISI) is a significant source of sulfur dioxide and particulate matter pollution in China. Existing research on regional environmental regulation or ISI emission reduction strategies tends to overlook spillover effects and the enterprise perspective. During the heating season, production limitations in ISI are potential policy measures for achieving structural emission reductions in heavily polluted cities in China's Jing-Jin-Ji and surrounding regions. We adopt a bottom-up modeling approach, incorporating effective production time to describe enterprise behavior and establishing a quantitative trade model based on trade theory. By modeling three types of production restriction policies outlined in policy documents, we evaluate the emission reduction effects of structure-adjustment measures using the example of reduced effective production time for steel-producing enterprises in the air pollution transmission channel in the Beijing-Tianjin-Hebei area. The results indicate the following: (1) Reducing the effective production time of ISI enterprises can help decrease domestic production value and total factor productivity in pollution-intensive industries, including but not limited to ISI. It also leads to reduced emissions of various pollutants in the implementation regions. (2) Due to interprovincial trade and input-output linkages, structural reduction measures in certain regions have implications for almost all other provinces' industrial structures. Differences in initial industrial structures, factor endowments, and geographical locations contribute to varying directions and magnitudes of industrial structural changes. Pollution-intensive industries' share tends to increase higher in less developed regions. (3) Our estimated pollution reduction is smaller compared to the literature evaluating clean air policies in similar regions using top-down strategies. This discrepancy arises because we analyze a single policy tool rather than modeling industry-wide emission fluctuations from the top down. Additionally, our modeling approach allows us to examine dynamic changes in comparative advantages. The increase in production scale for certain industries in policy-affected regions partially offsets the decline in pollution emissions. These findings enhance our understanding of structure-adjustment reduction measures' role and highlight their potential advantages and limitations.

Environmental Protection Tax Reform in China: A Catalyst or a Barrier to Total Factor Productivity? An Analysis through a Quasi-Natural Experiment

China’s 2018 environmental protection tax (EPT) reform was introduced in response to increasing concerns about environmental degradation. It aimed to use fiscal policy to enhance environmental governance while fostering economic productivity. This study employs a difference-in-differences approach to analyze panel data from publicly listed companies between 2009 and 2019. It examines the reform’s influence on total factor productivity (TFP) in pollution-intensive industries, addressing both environmental and economic objectives. The results reveal that the tax reform significantly enhances TFP, acting as a robust catalyst for economic growth rather than a barrier. This effect is particularly strong in state-owned enterprises and those with less-severe financing constraints. Mechanism analysis indicates that the reform boosts TFP through the promotion of green innovations and alleviation of financing constraints. These findings provide empirical evidence at the micro-level of the reform’s efficacy in promoting sustainable business practices. The study offers insights for future environmental tax policies in China and underscores the necessity of aligning environmental and economic strategies to achieve sustainable development.

Investigation of the causality between participation in global value chains and CO2 emissions between developed and developing countries

The production and consumption activities are cross-border and therefore, it is important to understand the role of Global Value Chains (GVCs) in fulfilling a country’s specific climate commitments. This study examines the causal relationship between selected GVC indices and CO2 emissions. We use the GVC position index, considered robust in comparison to the frequently used GVC participation index, for determining the impact on emissions. The forward and backward participation indices are considered in the analysis. The paper presents an analysis of 62 developing and developed economies from 1995 to –2018 using the Juodis A., Y. Karavias, and V. Sarafidis [2021. “A Homogeneous Approach to Testing for Granger non-Causality in Heterogeneous Panels.” Empirical Economics 60 (1): 93–112] approach, which is an improvement over the traditional approaches to analysing causality. The results show that the overall position in GVCs positively affects CO2 emissions for developing countries but a causal relationship does not exist for the developed countries. The developed countries attain a higher participation index but a lower position index. On the other hand, developing countries with fewer stringent environmental regulations may opt for an upstream position (more export-oriented) and by design specialize in more pollution-intensive industries. Noteworthy, production-based emissions in developed countries are reduced because of an increase in imports of emission-intensive products from developing countries.

Environmental Justice and Corporate Green Innovation: The Role of Legitimacy Pressures

This study examines the impact of environmental judicial reinforcement on green technology innovation, constructing a progressive difference-in-differences model using firm- and city-level panel data from 2006 to 2019 and taking the successive establishment of environmental courts by the Intermediate People’s Court in Chinese prefectural-level cities as a quasi-natural experiment. We find that establishing environmental courts in China promotes green technology innovation. This finding still holds after a series of robustness tests such as selected fixed-effects Poisson model regression. The mechanism analysis suggests that environmental courts primarily promote increased green innovation output by heavily polluting firms by exerting more substantial pressure regarding environmental legitimacy. The heterogeneity analysis reveals that the positive impact of the establishment of environmental courts on green technology innovation is more pronounced in water pollution-intensive industries and areas with high public participation and media attention. Our findings provide new insights into how environmental justice affects firms’ green innovation and validate the Porter hypothesis. Also, they serves as a reference for constructing environmental courts in China and other policy jurisdictions that may be interested.

What Attracts Green: Value Differentiation of Environmental Industry and Coagglomeration with Pollution-Intensive Industries in China

Scholars have spent decades studying how environmental (“green”) industry can promote sustainability. Few studies, however, have discussed corporate dynamics within green industry and their spatial interactions with other manufacturing and service industries. Drawing on the theoretical perspective of industrial value chain differentiation, this study unpacks the spatiotemporal dynamics of environmental enterprises by various types in China. We use the Wasserstein coagglomeration index and Poisson regression to identify the spatial coagglomeration of green and pollution-intensive (“brown”) industries. The results show that (1) China’s environmental industry is still in the early and middle stages of development with low and medium added value as the core; (2) green enterprises are mainly distributed in the eastern coastal areas and a few inland provinces with developed infrastructure; and (3) the entry and spatial distribution of equipment and engineering enterprises are highly correlated with local brown industries, whereas high-end service enterprises tend to concentrate in economically developed urban agglomerations. This research hopes to reveal the spatial characteristics of environmental industry in the regional green transition through the decomposition of its value chain and the analysis of the spatial coagglomeration effect.

Robots, firm relocation, and air pollution: unveiling the unintended spatial spillover effects of emerging technology

Amidst the global upsurge in industrial robot deployment, there remains a notable gap in our understanding of their environmental impact. This paper explores how the introduction of industrial robots has changed air quality at both the local and neighborhood levels in China. Using the Spatial Durbin Model, we investigate the regional spillovers of PM 2.5 concentration and the diffusion of this innovative technology. Our findings reveal that the rise of robots significantly reduces air pollution in the local area, while exacerbating it in neighboring regions. This contrast is mainly because pollution-intensive industries are more inclined to relocate to neighboring regions than their cleaner counterparts, after the local use of robots increases. Throughout the process, internal costs rather than external costs dominate firms’ relocation decisions. This study provides novel insights into the complex environmental externalities associated with the spread of industrial robots and highlights the critical issue of growing environmental inequality in the era of emerging technologies.

The role of related variety and exporting on a firm’s labour productivity in pollution-intensive industries in China

ABSTRACT This study investigates the influence of regional industrial variety and export activities on labour productivity in China’s pollution-intensive manufacturing sectors from 2003 to 2009. Analysing data from 345,654 firms, we discover that regional related variety significantly boosts labour productivity. Moreover, this study reveals that firms with a higher export ratio experience an amplified benefit from the related variety on labour productivity. Our findings suggest the need for comprehensive policies that balance economic growth with environmental sustainability, emphasizing the nuanced role of industrial variety and global market integration in shaping productive efficiency.

The pathway to curb greenwashing in sustainable growth: The role of artificial intelligence

Artificial Intelligence (AI) can improve production efficiency and general quality of life through assisting human labor, potentially leading to the conversion of employment types, enhancing industrialization, and upgrading energy structure. This paper enriches the role of AI in improving sustainable growth by curbing hypocritical sustainable and greenwashing behaviors. By accessing the panel data from Chinese listed-firms for the period 2014–2021, we have shown that AI can significantly mitigate the existence of greenwashing behaviors by raising the disclosure quality of ESG rating scores. Moreover, the role of AI in mitigating greenwashing behaviors performs significantly in SOEs, less pollution-intensive industries, high environmental regulation and less developed green finance regions. Furthermore, the potential mechanisms of AI in mitigating greenwashing behaviors are displayed, including alleviating financial constraints, easing management cost, improving green innovations.

Has the digital transformation promoted energy-saving-biased technological progress in China’s manufacturing sector?

ABSTRACT In the context of ‘Digital China’ and the ‘Dual-Carbon’ targets, there is an escalating need for energy saving and pollution reduction in China’s manufacturing sector. By optimizing resource allocation, enhancing precision in energy consumption monitoring and fostering the integration of traditional production factors, digital elements are pivotal in steering the sector towards energy technology progress, thereby affecting overall energy usage and carbon emissions. This study leverages panel data from 2009 to 2020 to quantify the manufacturing sector’s digital transformation and its energy-saving technology progress bias. It also examines the catalytic role of digital transformation in fostering energy-saving technological progress. The findings reveal the following: (1) The trajectory of technological progress within China’s manufacturing sector has progressively improved and predominantly demonstrates an energy-saving bias. (2) Digital transformation has significantly catalysed energy-saving-biased technological progress across various manufacturing subsectors, this conclusion is still significantly credible after a series of robustness tests. (3) Heterogeneity analysis reveals that as the digital transformation progresses from collaborative innovation to comprehensive digitalization phases, it has dramatically optimized the energy-saving-biased technological progress in various industries, especially in pollution-intensive industries. These insights offer substantial implications for policy formulation and industrial evolution.

Energy price uncertainty, environmental policy, and firm investment: A dynamic modeling approach

Environmental quality is closely related to the production and investment behavior of enterprises, which depends on the discounted future cash flows that are affected by energy price uncertainty. Meanwhile, with the increasing awareness of environmental protection, environmental policies have been introduced to restrict firm investment choices. However, the role of environmental policy has received less attention in the previous research on energy prices and firm investment. Therefore, this paper develops a dynamic firm investment model that incorporates energy price uncertainty and environmental regulation and makes the following predictions. First, ceteris paribus, energy price uncertainty negatively impacts firm investment. Second, environmental regulations mitigate this negative impact of energy price uncertainty. Third, the mitigating effect of environmental policy is greater in pollution-intensive industries. This paper merges the micro-data on A-share listed firms in China between 2004 and 2018 with the macro-data on energy prices and environmental regulation. The empirical results align with the theoretical predictions. The robustness tests, including instrumental variables, alternative measurements, and estimation methods, validate the baseline findings. These theoretical and empirical findings yield important implications for policymakers.

Unleashing the power of artificial intelligence for climate action in industrial markets

Artificial Intelligence (AI) is a game-changing capability in industrial markets that can accelerate humanity's race against climate change. Positioned in a resource-hungry and pollution-intensive industry, this study explores AI-powered climate service innovation capabilities and their overall effects. The study develops and validates an AI model, identifying three primary dimensions and nine subdimensions. Based on a dataset in the fast fashion industry, the findings show that the AI-powered climate service innovation capabilities significantly influence both environmental and market performance, in which environmental performance acts as a partial mediator. Specifically, the results identify the key elements of an AI-informed framework for climate action and show how this can be used to develop a range of mitigation, adaptation and resilience initiatives in response to climate change.

A rapid and environment-friendly process for dolomite pellets calcination with Joule-heating

Dolomite is an important industrial raw material for the production of metal magnesium. However, the calcination of dolomite is a typical pollution-intensive industry and is one of the major contributors to CO2 emissions in China. The requirements of energy conservation and environmental protection are driving the development of new calcination technologies. Herein, we developed a rapid and environment-friendly strategy for the calcination of dolomite used in subsequent magnesium production through carbothermal reduction, in which the pellets containing dolomite and carbon additive are calcined with in-situ Joule-heating in a vacuum. The effect of input volumetric specific power, heating time, vacuum conditions, carbon additive, and the size of the pellets on the decomposition process has been systematically studied. The dolomite in the pellets can be completely decomposed within tens of seconds. And the kinetic analysis shows that the activation energy of the decomposition of dolomite with the Joule-heating method is 108.4 kJ mol−1, which is much lower than the previous reports. Note that, the novel strategy shows a reduction of calcination time by 70 times, a reduction of energy consumption by 6.22% and a reduction of direct carbon emissions by 56.77% compared to the traditional methods. Combining the results of finite element simulations and density functional theory calculations, we revealed the mechanism of Joule-heating to enhance the decomposition of dolomite. The results show that the Joule-heating method can offer a distinct heating mechanism and deteriorate the structure stability of CaMg(CO3)2.

Cross-border M&As and the export green-technological sophistication: evidence from China

ABSTRACT Based on the Chinese Annual Survey of Industrial Firms (CASIF) database, this paper constructs a PSM-DID model to analyse the impact of cross-border mergers and acquisitions (M&As) on the export green-technological sophistication of Chinese industrial firms. The results show that cross-border M&As can effectively promote the export green-technological sophistication of acquired firms. The promoting effect of M&As increases gradually over time. Further, the heterogeneity results demonstrate that the promoting effect is more significant in private firms, partially acquired firms, firms in pollution-intensive industries and eastern areas. Finally, cross-border M&As can improve the export green-technological sophistication through two channels: improving green innovation capabilities and introducing pollution control equipment. Our results are significant for developing countries’ foreign investment guidance policies and firms’ green transformation.

Temporary prosperity or sustainable development: the long-run impact of developing pollution-intensive industries

Abstract This paper proposes a dynamic model to capture the interaction among the environment, human capital accumulation, and economic growth. We emphasize the mechanism that pollution stock depresses human capital accumulation, which has received increasing support from empirical studies. The model predicts that the development of pollution-intensive industries can help an economy gear up a short-run prosperity, but it impairs the capability for long-run economic growth, trapping the economy at a low development level. The cost for a dirty economy to switch is expensive and even infeasible if the environmental degradation is irreversible. Policy interventions, such as tax on pollution and subsidy on human capital, can help alleviate but cannot eradicate the economic stagnation.