Spatially differentiated environmental regulation can induce pollution leakage through intra-firm relocation of pollution-intensive activities to less-regulated regions. This mechanism remains underexplored, especially in developing countries, where data limitations make intra-firm relocation difficult to measure and existing investment-based proxies often miss expansions within existing subsidiaries. Using manually collected subsidiary-level investment data for 411 listed pollution-intensive firms in China and a difference-in-differences framework, we examine whether regionally differentiated regulation under the 2013 Clean Air Plan led to intra-firm investment reallocation consistent with production relocation and potential domestic pollution leakage. We find that regulated firms increased pollution-intensive investment in subsidiaries located in less-regulated areas following the policy, accompanied by declines in parent-firm output and rising PM₂.₅ concentrations around subsidiary locations. Adjustment patterns differ across regions: firms in the three key regions centered on Beijing, Shanghai, and Guangzhou reallocate investment from eastern regulated areas to distant western regions, mainly through new subsidiary entry, whereas firms in ten other major city clusters mainly expand existing subsidiaries located nearby. Reallocated investment is disproportionately directed toward regions with stronger agglomeration economies and transportation advantages rather than environmentally fragile areas. These findings suggest that investment flows offer a valuable lens for detecting potential pollution leakage and that unintended east-to-west transfers may undermine environmental gains, highlighting the need for stronger disclosure requirements and targeted pollution-control policies in recipient regions.

Green credit policies direct financial resources to sustainable firms while restricting polluting ones, promoting environmental goals, and mitigating climate change. Despite extensive research on how China's punitive green credit policy (GCP) affects polluting firms, far less attention has been paid to how local governments respond to the policy and shape its overall impact. This study explores how the punitive GCP affects local government responses, particularly through subsidies. Using a staggered difference-in-differences approach based on variation in firm-level exposure to the GCP, we analyze data on Chinese A-share listed firms from 2010 to 2018. Our findings indicate that the GCP led to approximately a 30% increase in non-tax subsidies from local governments to polluting firms as short-term economic relief. This suggests that such subsidies may partly offset the financial constraints imposed by the central policy. We further categorize these subsidies into 'green' and 'non-green' and observe regional divergences: while all regions increased non-green subsidies post-GCP, only developed eastern regions saw a marginally significant rise in green subsidies. This highlights differing local strategies in supporting firms' green transformation. Our results contribute to the ongoing debate on the GCP's effectiveness, emphasizing the importance of aligning local incentives. Policymakers should avoid a one-size-fits-all approach and refine the GCP to better support green projects in polluting firms. Poorly designed local subsidies may undermine the intended impact of the central government's GCP, while well-structured local subsidies can enhance it. Clearer guidance is needed to align local subsidies with national green goals and support firms' green transformations.

The Chinese central government introduced the Cadre Evaluation System (CES) reform in December 2013 to prioritize environmental protection in performance evaluation. However, the impact of the reform on local environmental governance behavior remains uncertain. This study analyzed the panel data of 113 prefecture-level cities in China from 2009 to 2016, using a regression discontinuity design in time to evaluate the effect of the CES reform on local governments' environmental information disclosure performance. The results indicate that the reform effectively disrupts the race-to-the-bottom trend in environmental information disclosure, which had been adopted by bottom-ranked local governments as characterized by the Pollution Information Transparency Index (PITI). The reform served as a deterrent and was successful in motivating bottom-ranked local governments to adopt a more environmentally responsible approach of development, which involved increased environmental information disclosure. However, it had no substantially comparable impact on top-ranked cities, which maintained high disclosure levels due to existing reputation effects from PITI rankings prior to the reform.

Purpose - While the impact of artificial intelligence (AI) on organizational innovation is increasingly acknowledged, empirical investigations exploring its effect on product innovation efficiency, particularly through the lens of knowledge innovation at various modes, remain scarce. This study aims to address this gap by empirically examining the influence of AI application on product innovation efficiency within firms. It further investigates the mediating role of knowledge innovation within the SECI model and the moderating effect of technological perception characteristics. Design/methodology/approach - Data were collected through a questionnaire survey administered to managers in intelligent manufacturing enterprises across China. The proposed hypotheses were tested using the PROCESS macro for SPSS, employing the bootstrapping method to assess mediation and moderation effects. Findings - Enterprise application of AI significantly influences both knowledge innovation within the SECI model and product innovation efficiency. Knowledge innovation occurring in the socialization and combination modes of the SECI model mediates the relationship between AI application and product innovation efficiency. Perceived ease of use of AI exhibits a contrasting moderating effect on AI-related relationships, while perceived usefulness does not demonstrate a significant moderating effect. Originality/value - This study contributes to the existing literature by empirically examining the influence of AI application on product innovation efficiency, mediated by knowledge innovation within the SECI model. Additionally, it explores the nuanced moderating role of AI perception characteristics, highlighting the potential duality of AI technology in driving innovation outcomes. These findings offer valuable insights for managers seeking to leverage AI for enhancing product innovation and knowledge management practices.

While tax distortion on capital can significantly impact resource allocation in developing economies, credible causal evidence remains scarce. This study provides novel evidence by examining China’s 2009 value-added tax (VAT) reform, which allowed specific firms to deduct taxes on capital inputs, thereby mitigating distortions in the taxation of capital. Using firm-level tax return data from 2006 to 2015, we demonstrate that the reform enhanced the allocative efficiency of capital by reducing the dispersion in marginal revenue product of capital (MRPK) within industries. Our empirical results show that firms with high ex-ante MRPK experienced a 10.5% increase in physical capital and a 6.0% decrease in MRPK post-reform, relative to low-MRPK firms within the same industry. The effects were particularly pronounced among smaller firms, those with restricted access to debt, and those located in areas with greater access to banking services, supporting the financial constraints channel. Moreover, the reform improved labor allocation through input complementarity and the alleviation of financial constraints. Our calibration exercise suggests that the reform increased the aggregate productivity of treated firms by 3.1–4.0%, with nonlinear approximations that account for cumulative dynamics yielding estimates of up to 7.8%. These findings highlight the importance of addressing tax distortions for efficient resource allocation in developing economies.

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This study examined the location preferences and changes in pollution-intensive firms by analyzing the spatiotemporal distribution and drivers in the Yangtze River Economic Belt, a transitional manufacturing region in China. To analyze the distribution of firms under natural growth conditions prior to the implementation of the national “Great Protection of the Yangtze River” policy in 2016, this study utilized data on newly expanded industrial land use from 2007 to 2016. The results indicated that new pollution-intensive firms predominantly focused on water pollution, occupying over 40% of the total area annually. The new pollution-intensive firms preferred the geographic agglomeration siting strategy, mostly along the Yangtze River or in urban agglomerations, while gradually moving westward. The total area and number of new pollution-intensive firms in the Yangtze River Economic Belt showed an overall trend of “inverted U-shaped” variation during the study period, and the average size of the pollution-intensive firms gradually decreased. GeoDetector analysis revealed that geographical factors have always been significant. Local economic factors attracted new pollution-intensive firms, but later in the study period, these factors showed some inhibitory effect on the increase in pollution-intensive firms in the lower reaches. Government intervention worked less effectively but was significantly enhanced after interaction with other factors. Finally, the results suggested that local governments should build a stronger synergy between industrial land policies and environmental regulations to ensure sustainable growth and rational allocation of pollution-intensive firms.

At present, the scale of global subsidies for fossil fuels is still huge, and their energy, economic, environmental, and technological impacts cannot be ignored. This chapter reviews the previous literature to answer three questions: What are the impacts of fossil fuel subsidies? What are the benefits of reforms in fossil fuel subsidies? How can fossil fuel subsidy reforms be successfully implemented? Specifically, subsidies lead to excessive use of fossil fuels, resulting in wasted resources, increase the fiscal burden on governments and lead to smuggling of fossil fuels among some countries, are distributed unequally between rich and poor residents, increase emissions of carbon dioxide, and discourage the use and development of clean energy. Reforming fossil fuel subsidies might gradually mitigate the problems caused by subsidies. The increase in fuel prices after the removal of subsidies might enable more efficient use of fuels and affect a country's gross domestic product, reducing the welfare of residents overall, but with a smaller effect on the interests of the poor than the rich, and affecting carbon emissions and promoting the development of clean energy. In the process of implementing subsidy reform, policymakers should pay attention to the method of reform. It is important to adjust subsidies based on local conditions, using cash transfer and other forms of compensation for residents, shifting to subsidies for clean energy, and gradually reducing subsidies of all types.

The widespread implementation of feed-in tariff (FIT) policies has played a crucial role in fostering the development of wind power, with their positive effects firmly established in numerous studies. However, the impact of regionally differentiated FIT policies on the misallocation of wind power resources remains a topic of contention, with limited research dedicated to this area. This paper aims to address this gap by examining the implications of such policies on the intensive and extensive margins of wind power installed capacity in China, shedding light on the underlying mechanisms driving resource misallocation. Empirical findings indicate that, concerning the intensive margin, the policy amplifies the concentration of wind power investments in regions characterized by abundant wind resources but low electricity demand. These regions present favorable conditions for large-scale wind farms with cost advantages, consequently exacerbating the misallocation of wind power resources. However, on the extensive margin, the policy promotes the likelihood of locating small and medium-sized wind farms in regions with poor wind resources but higher tariff rates, thus partially mitigating resource misallocation. In summary, China's policy hampers wind power investments in regions characterized by high electricity demand but limited wind resources. This suggests that the negative impact on the intensive margin outweighs the positive impact on the extensive margin. The findings of this study bear significant implications for the development of renewable energy support policies, particularly in countries grappling with substantial regional disparities in renewable energy resources.

With the world's second-largest rural population, China faces the complex challenge of energy poverty in rural areas, and it is important to identify effective policy tools to alleviate energy poverty. The Rural Centralized Residence (RCR), a rural development policy, has been implemented in 24 provinces in China since 2004. This study was consequently motivated to formulate a hypothesis that RCR could reduce energy poverty in China's rural areas. The study used field survey data on 3484 rural households and employed the instrumental variable method to test the above hypothesis. It demonstrated that RCR can significantly cause the decline of the energy poverty in rural China by 14.5 percentage points in terms of composite energy poverty index. Further analyses showed that RCR could significantly improve household income, use of energy-efficient materials, and energy infrastructure supply, ultimately reducing the energy poverty in rural China. The newly found effect of RCR on energy poverty and its relevant mechanisms could help policymakers in China and elsewhere to deliberate, adopt and implement similar policies.

To achieve the efficient operation of the smart grid, appropriate energy trading strategy plays an important role in reducing multi-agent costs in the trading process as well as alleviating grid pressure. However, with the increase of the number of participants in smart grid, energy trading has been greatly challenged in terms of stable and effective operation. In this paper, we use the method of deep reinforcement learning to simulate generation companies (GenCos) price-quantity pair bidding in electricity markets. Through the deep reinforcement learning algorithm, agents can gradually learn the environment by treating the nodal prices of previous time interval and the total load demand of current time interval as the state variables, and the bidding price and quantity as the bidding strategy. The simulation results show that with the continuation and convergence of learning, more agents will profit from trading.

The integrated energy system (IES) coupled with different equipment has attracted widespread interest owing to its high efficiency. However, the dynamic characteristics are rarely considered in configuration, which may leave little optimization room for dispatch. Hence this paper proposes a dynamic performance index to take the dynamic characteristics into full consideration. Firstly, the static model and dynamic model of each device are formulated, and PI controllers are implemented. Secondly, the mathematical description of the optimization problem is given, including the objective function, optimization strategy and constraints. It is worth mentioning that the dynamic objective is derived from the time scale. Afterwards, the economic and comprehensive objective combining economic and dynamic objectives are implemented. Finally, in order to testify the availability of the comprehensive objective, dynamic deviation of the configuration results is computed. The results indicate that the configuration strategy using the comprehensive objective reduces the total deviation by 5.56% in dynamic dispatch.

China's district heating system for urban residences has achieved remarkable progress in terms of scale, coverage, and growth. However, its development imposes great challenges to the country's energy infrastructure, environmental sustainability, and climate change policy. To tackle these problems, the central government has implemented numerous public policies in the past decades. However, few studies have focused on the policies themselves. This study aimed to analyze systematically the historical development of the residential heating policy, reveal the administrative system's evolution, and quantify the mix of different policy instruments. We applied text-based analysis to 146 policy documents issued by the central government from 1986 to 2019. We identified four different development stages with varying objectives and constraints in the past four decades. To harmonize the various tasks in these four stages, China's administrative system gradually evolved from a single-function management agency to one with multidimensional objectives and a mechanism for sound coordination. The analysis also revealed the regulation instrument as the most preferred in the policy toolbox, whereas the economic tool has garnered increasing attention. The standard-based instrument showed a moderate growth pattern in terms of quantity and intensity. (c) 2021 Elsevier B.V. All rights reserved.

Subsidies and policy support are critical for the development of renewable energy industries such as solar photovoltaics (PV). One of the most important policy instruments for supporting renewable energy development is the feed-in tariff (FIT), which is intended to have a significant, facilitating impact on the steady development of the PV industry. The questions are how strong market reactions are to FIT policies and what forms of policies are more effective. To investigate these questions, this paper uses an event study approach and pays special attention to the responses of the capital market. The empirical results show that the stock returns of listed PV companies in China respond significantly to FIT policies. The capital market responses of these policy shocks differ significantly over time and across companies. Manufacturing companies and companies receiving large subsidies are more sensitive to policy shocks. Given the importance of equity financing to the renewable energy industry, policymakers should take into account the potential uncertainties in the sector that are caused by policy changes.

Historically, coal has been a primary input driving China's economic growth. However, it has impacted air quality significantly and negatively in the past decades. Among all efforts and measures, the Residential Coal Switch Policy (RCSP), implemented in the 1990s, is considered the most fundamental but challenging pathway toward reducing pollution. This study offers a comprehensive policy panorama to policymakers and researchers, explaining the dynamic evolution of the RCSP under varying objectives and constraints. Based on 66 policy documents issued by the central government during the years 2012–2019, the study reviews the RCSP systematically and presents three development stages. We create an index to measure policy-enforcement intensity at each stage and find that policymakers have become more sophisticated in identifying specific target groups, increasing the use of target-management tools over time. Results indicate that most of the Beijing-Tianjin-Hebei and surrounding areas have achieved and exceeded established targets. Command and control, financial support, competitive funds, and residential willingness to pay for air quality are the primary factors related to achievement. Future challenges are also presented, including the unsustainability of subsidies, the absence of building-reconstruction investment, and the scarcity of clean energy.

Electricity regulators pay attention to electricity supply reliability in many countries, considering that power interruption can cause damage and destruction as modern societies increasingly rely on electricity. Since 2020, China's regulators have designed incentive schemes to encourage power grid firms to improve electricity supply reliability in some regions. An effective incentive scheme requires that regulators identify the cost of reliability improvement and match it to the incentive scheme. Using provincial panel data for 2012-2018, this paper employs the directional output distance function approach to estimate the shadow price of power interruptions in China's grid systemdthat is, the marginal cost of electricity supply reliability improvements. Results indicate that the shadow price of 1 min of interruption per customer ranged from 59.66 to 74.65 RMB in 2012-2018. This estimation also shows that the shadow price of 1 min of interruption varies substantially among provincial grid utilities. The marginal cost of improving electricity supply reliability in China's grid system is lower than in developed countries. Since the incentives far from cover the cost of improvement, the schemes implemented in some Chinese regions cannot provide incentives for quality improvements. (c) 2021 Elsevier Ltd. All rights reserved.

Deepening the electric power system reform and building a new power system with new energy as the main body are the top priorities in the development of the energy and power field. The participation of new energy in electricity market transactions is in the early stage of development, and there are many problems in the mechanism design. Aiming at the problem of new energy participating in electricity market transactions, this paper summarizes and analyzes the current situation of new energy participating in the electricity markets at home and abroad, then puts forward the incentive mechanism and price mechanism of new energy participating in electricity market transactions, and finally makes some suggestions about this problem. The research objective is to better promote the participation of new energy in the electricity market, realize the efficient use of new energy, and help to achieve carbon peak and neutrality goals.

ADVERTISEMENT RETURN TO ISSUEPREVViewpointNEXTThe World'S Largest Residential Energy Switching Program Is at RiskChang LiuChang LiuSchool of Business Administration, Faculty of Business Administration, Southwestern University of Finance and Economics, Chengdu, 610074, ChinaMore by Chang Liu and Chu Wei*Chu WeiSchool of Applied Economics, Renmin University of China, Beijing, 100872, China*Email: [email protected]More by Chu WeiView Biographyhttps://orcid.org/0000-0002-7704-5544Cite this: Environ. Sci. Technol. 2021, 55, 22, 15004–15006Publication Date (Web):October 25, 2021Publication History Received27 September 2021Published online25 October 2021Published inissue 16 November 2021https://pubs.acs.org/doi/10.1021/acs.est.1c06544https://doi.org/10.1021/acs.est.1c06544article-commentaryACS PublicationsCopyright © 2021 American Chemical Society. This publication is available under these Terms of Use. Request reuse permissions This publication is free to access through this site. Learn MoreArticle Views1455Altmetric-Citations3LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail PDF (2 MB) Get e-AlertscloseSUBJECTS:Climate,Coal,Energy,Natural resources,Redox reactions Get e-Alerts

The Chinese government has implemented the rural centralized residence (RCR) policy to promote rural development in 24 provinces since 2005. This study aims to estimate the effects of RCR on households' choice of clean cooking fuels by applying the instrumental variable approach on a dataset with 3685 observations in Sichuan Province. The empirical analysis showed that RCR has a significant positive effect on the choice of clean cooking fuels. We also found that RCR makes farmer households shift from using non-clean energy to clean energy for cooking by increasing both their total income and the cost of collecting and storing traditional fuels. Peer effects also motivate households to use clean cooking fuels. Further analysis indicates that an increase in the expenditure on clean energy due to RCR does not increase the farmer households' living burden, since the increase in the total income caused by RCR is much greater. Considering the accessibility and affordability of clean energy, the RCR policy could improve the standards of living among rural residents and synergistically promote energy transition in rural China.