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The stabilization of growth and preservation of employment are the primary objectives of the current new economic normal. Investigating whether the low-carbon transition can be an opportunity or a shock for employment expansion in green development requires thorough examination. This study utilizes multi-temporal difference-in-difference (DID) models, analyzing comprehensive panel data from China (2007–2019) to assess the impact of the Low-carbon City Pilot (LCCP) policy on employment at meso-regional and micro-firm levels. Empirical findings robustly reveal that LCCP significantly boosts employment, with average treatment effects of approximately 0.548% and 5.892% at regional and firm scales, respectively. Positive impacts vary based on ownership, location, industry type, and energy consumption within enterprises. Notably, state-owned enterprises, those in the eastern region, engaged in secondary industries, and with high energy consumption experience pronounced positive effects. Mechanism analysis further reveals that LCCP boosts employment via promoting government environmental subsidies and expanding enterprise investment scale to create more jobs. These findings provide policy recommendations for further promoting low-carbon transition and expanding employment to achieve the win-win goal of sustainable development. • Low Carbon City Pilot Policies (LCCP) can promote employment both at the regional and firm level. • The role of LCCP is achieved via two channels. • The facilitation effect of LCCP varies across cities, firms and industries. [ABSTRACT FROM AUTHOR]

Improving corporate green technology innovation is a key link in achieving green transformation and development. Compared with formal environmental regulations that force companies to carry out green innovation passively, ESG ratings under soft environmental regulations can better stimulate the internal motivation of companies. This study uses the ESG ratings of listed companies published for the first time by SynTao Green Finance as an exogenous impact. Taking China's A-share listed companies from 2011 to 2022 as a research sample, the multi-period differences-in-differences model was used to empirically test the impact of ESG rating soft supervision on corporate green technology innovation. The results show that the impact of ESG rating events as a soft market regulation has a significant positive impact on the improvement of corporate green technology innovation. This conclusion still holds after a series of robustness tests. Meanwhile, enterprise digital transformation plays a positive regulatory role. The heterogeneity test shows that the green technology innovation of state-owned enterprises is more affected by ESG ratings. Mechanism research has found that ESG rating events promote corporate green technology innovation by easing corporate financing constraints and reducing managerial myopia. Further research found that under the influence of the external environment, intensified market competition and increased attention from the capital market are also conducive to the improvement of corporate green technology innovation. This study strengthens the corporate ESG concept under the guidance of green development and provides empirical evidence for promoting corporate green transformation. • The difference-in-differences method is employed to verify the causal effect of ESG rating. • Incorporate digital transformation of enterprises, financing constraints, and managerial myopia into the research content. • Consider the impact of external market environment on research results. [ABSTRACT FROM AUTHOR]

The increasing volume of electronic waste (e-waste) poses significant challenges for efficient collection in China. Despite many measures were taken over the past two decades, the e-waste collection rate was still not high. To this end, the Chinese government issued a new policy, the collection target responsibility (CTR) policy. Under the CTR policy, however, it is essential for participants to know how to share the responsibility of collection and how much reasonable targets are set to ensure the efficiency of the collection models. Therefore, the purpose of this paper is to explore the determination of optimal collection targets and the corresponding performance from the perspective of responsibility sharing to support the successful implementation of the CTR. Firstly, the study focuses on participants including the government, manufacturers, and recyclers, and develops three CTR models, independent collection model, government cost-sharing model, and enterprise collaboration model. Secondly, collection target equations for each model are established by employing dynamic differential game analysis, and corresponding collection performances are derived. Thirdly, through practical case simulations, the evolution of collection performance is dynamically analyzed to determine reasonable collection targets for the three models, as 23.8%, 32.3%, and 34.4%, respectively. The findings highlight the effectiveness of CTR in improving e-waste collection targets and performance, with the highest levels attained when the collection responsibilities are shared by government cost-sharing and enterprise collaboration. This study provides theoretical support for setting reasonable collection targets under CTR, and assists decision-makers in developing targeted CTR implementation measures. • The CTR model frameworks involving the main participants are developed. • Three CTR models are constructed from the perspective of shared responsibility. • The collection target for each CTR model is analyzed and determined. • The performances of CTR models are analyzed and compared. • Differences in the CTR models from cost-sharing and enterprises collaboration are observed. [ABSTRACT FROM AUTHOR]

Traditional manufacturing industry is in the early stages of transition to low-carbon innovative production, and is in urgent need of a low-carbon innovation system to achieve the goal of carbon neutrality. In order to realize the effective supervision of enterprise carbon emissions, this paper constructs a tripartite evolutionary game model among the corporate, government and public from the perspective of dynamic subsidies and taxes. The main results are as follows. First, the increase in government subsidies to a certain extent will help encourage companies to choose low-carbon innovative production strategies, but more subsidies are not always better. Excessive subsidies will increase the cost of government regulation and reduce the probability of government regulation. Second, the tripartite evolutionary game system does not converge under the static subsidies and taxes mechanism. But the system could quickly converges to the stable condition under dynamic subsidies and taxes. The stable point is the situation of corporate low-carbon innovation, government regulation, and public supervision. Third, the public intervention and supervision can effectively prevent the phenomenon of government misconduct and enterprises over-emission production. And the influence of public reward and punishment is more effective for the government than for enterprises. • A tripartite evolutionary game of low-carbon innovation system among enterprises, government and the public. • Dynamic subsidy and tax mechanisms drive the model to converge to the ideal state. • Increased government subsidies will promote low-carbon innovation, but it isn't the more the better. • The same degree of public supervision is more effective for governments than for enterprises. [ABSTRACT FROM AUTHOR]

Green innovation (GI) is increasingly recognised as an effective strategy for tackling climate change, mitigating environmental issues, and promoting sustainable development. Using panel data of the Chinese listed firms from 2007 to 2019, this study adopts the difference-in-differences approach to assess the impact of the green finance policy (GFP) initiated by the Chinese government in 2012 on the green innovation performance of firms. The findings reveal that the GFP significantly boosts the green innovation performance of heavily polluting enterprises (HPEs). Notably, this effect is more pronounced in state-owned enterprises and firms with high dependence on external finance. Compared with penalty-based regulations, incentive-based and voluntary environmental regulations demonstrate more significant moderating effects on the relationship between the GFP and green innovation performance for HPEs. We also identify improved efficiency in the usage of green investments as a potential mechanism through which the GFP enhances the green innovation performance of HPEs. Further comparative analysis shows that green enterprises can achieve simultaneous improvement in both the quality and quantity of green innovation, whereas HPEs predominantly exhibit enhancements in innovation quantity. To maximise the GFP's positive effects, it is recommended to facilitate more targeted bank lending towards HPEs to support their structural transformation. Additionally, the coordinated deployment of diverse environmental policy instruments is advised to exploit their synergistic effects. • This paper confirms the positive relationship between Green Finance Policy (GFP) and the green innovation. • We develop a novel machine learning approach to enhance the accuracy of variable measurements. • Firms with different ownership structure and external finance reliance are impacted differently by the GFP. • Both incentive-based and voluntary environmental regulations have positive moderation effects. • GFP can improve the green innovation by enhancing the green investment efficiency. [ABSTRACT FROM AUTHOR]

In this paper, we solve the urgent problem to construct a recycling network of decommissioned batteries of Electric Vehicles (EVs) and clarify the recycling entities that will be responsible for its reverse logistics (RL) process. We consider the third-party recycling entities to develop a recycling network and conduct a case-study of Xi'an, a key industry of EVs in China to provide a reference for the government and enterprises to develop recycling plans. We scientifically optimize our recycling network, which will have a significant impact on the environmental and economic benefits of electric vehicles (EVs) in Xi'an in the future. Specifically, we consider the costs of transportation, construction, operation, recycling, packaging, and emission, as well as the profits achieved through sales revenue and subsidy offerings. We collect the actual data of potential facility locations in Xi'an, predict the quantity of decommissioned batteries in the future, and develop a fuzzy-based model to solve the optimal results of battery traveling path and distribution in the recycling process network. Our results show that with the rapid growth of the number of decommissioned batteries, third-party revenues will reach about 53.08 billion by 2035. When the facilities split the recycling process load appropriately, the network has increase in revenue while the utilization rate of facilities will decrease. We expect that splitting will be a major trend in the future development of recycling network in Xi'an. Finally, a sensitivity analysis finds that with the environmentally conscious and safe operation of recycling, the negative impact on the third-party enterprises' revenue will be small. Our proposed methodology can serve as a critical framework for other cities and governments to plan their recycling networks and formulate regulations, reflecting on the realistic projection of the scale of decommissioned batteries of EVs and the potential siting and sizing of the recycling facilities. • Design of recycling network for decommissioned batteries from EVs. • Third-party enterprises to gain a large revenue in recycling. • Sensitivity analysis on economic, environmental, and safety goals. • A case study of Xi'an, China, with realistic future projections of recycling. • Splitting recycling processes across multiple facilities to be recommended. [ABSTRACT FROM AUTHOR]

Green power trading is an institutional innovation proposed by China to promote green and sustainable development. This policy aims to relieve the serious debt pressure of renewable energy generation enterprises, thus laying the foundation for achieving carbon reduction targets. This paper empirically examines the role of green power trading by constructing the difference-in-differences (DID) model. Our findings indicate that green power trading significantly reduces the debt levels of policy-covered generation enterprises. This effect is more pronounced for state-owned enterprises, companies with better ESG performance, companies in regions with higher degree of marketization and companies specializing in renewable energy power generation. Further research discusses the impact mechanism of green power trading in terms of external and internal environmental channels. We find that a strong green development atmosphere, especially the external atmosphere, will significantly reinforce the weakening effect of green power trading on corporate debt. Our research provides empirical evidence for the success of green power trading policy in its pilot phase. • Green power trading significantly alleviates the policy-covered firms' debt burden. • The role of green power trading presents heterogeneity in enterprise characteristics. • A better regional environment for green growth can stimulate the effect of green power trading. [ABSTRACT FROM AUTHOR]

Green credit is a major policy innovation to guide enterprises to participate in environmental governance actively. This study uses the data of Chinese A-share listed companies from 2007 to 2016, takes the green credit guideline (GCG) issued in 2012 as a quasi-natural experiment, and uses a difference in difference (DID) model to test the effect of GCG on the enterprises' export green-sophistication (EGS) and its internal and external mechanisms. The study finds that GCG improves enterprises' EGS and research and development (R&D) investment is the intermediation channel for GCG to affect EGS. Results of heterogeneity analysis show that the role of GCG in promoting EGS is significantly reflected in enterprises that the government does not subsidize, enterprises in areas with a low degree of financial marketization development, state-owned enterprises, and enterprises with a high degree of equity incentive. • GCL can significantly improve enterprises' EGS. • Firms' research and development expenditure have a positive mediating effect. • The improvement effect of GCL on EGS is stronger in state-owned firms. [ABSTRACT FROM AUTHOR]

Existing research on state capital injection (SCI) has not yet explored its environmental effects. Using Chinese firm level data and the difference-in-difference estimator, we estimated the effect of SCI on firms' sulfur dioxide (SO 2) emissions. The results show that the SCI reduced firms' SO 2 emissions significantly but have no effect on SO 2 emissions intensity. Moreover, robustness tests show that SCI also reduced the emissions of industrial exhaust and chemical oxygen demand but not their emissions intensity. Further analysis reveals that the abatement effects of SCI are at the expense of capacity utilization reduction and then the sacrifice of economic output, thus failing to achieve a win-win situation for both pollution abatement and economic benefits. Firms accepting SCI do not significantly increase their use of pollution treatment technologies, either source control technologies or end-of-pipe treatment technologies. The reason may be that after accepting SCI, firms are required to take on more environmental social responsibility and are under higher pressure of pollution abatement. However, their managers may be more inclined to respond to environmental regulation and pollution control through non-market-based approaches rather than through technological innovation. In addition, heterogeneity analysis shows the pollution abatement effect of SCI only exists in small or lower administrative hierarchy firms. This study has shed some lights on the reform of the environmental regulatory system and the environmental performance management of state-owned enterprises. • The environmental effects of state capital injection are empirically investigated. • State capital injection has a pollution reduction effect. • The reduction effect only exists in small or lower administrative hierarchy firms. • State capital injection will decrease the capacity utilization of firms. • State capital injection does not improve the pollution control technologies of firms. [ABSTRACT FROM AUTHOR]

Despite increasing evidence documenting the role of the outgoing audit of natural resources (OANRA) in environmental governance and enterprise innovation, little is known about its impact on enterprises' total factor productivity (TFP). To address this question, we treat the OANRA policy launched in 2014 in China as a quasi-natural experiment. We adopt a difference-in-differences-in-differences (DDD) method that exploits three-dimensional variations: city (i.e., OANRA cities versus non-OANRA cities), industry (i.e., more polluting industries versus less polluting ones), and year (i.e., before and after the OANRA policy). Employing a dataset of Chinese industrial listed companies from 2012 to 2019, we reveal that after the OANRA implementation, enterprises' TFP in more polluting industries of OANRA cities decreases by 4.0%. Our mechanism analysis shows that the OANRA restrains the TFP by reducing the financing scale of enterprises and increasing environmental investment of governments. Further, the heterogeneity analysis finds the inhibitory effect of the OANRA is more prominent in large-scale and state-owned enterprises, as well as enterprises located in eastern, low fiscal pressure, and high pollutant emission cities. Our findings provide support for the neoclassical economics hypothesis that the OANRA increases enterprises' compliance costs and decreases their productivity. • We study the relationship between the outgoing audit of natural resources assets (OANRA) and enterprise productivity. • We exploit the difference-in-differences-in-differences analyses and an instrumental variable design. • Evidence suggests enterprises' TFP in more polluting industries of OANRA cities decreases by 4.0%. • Evidence shows the OANRA restrains enterprises' TFP by reducing financing scale and increasing environmental investment. • Our study reveals the possible negative economic impacts of the OANRA and provides recommendations for policy optimization. [ABSTRACT FROM AUTHOR]

Strict environmental governance urges firms to implement higher sustainable production requirements and environmental standards for export products, making it challenging for firms to maintain export competitiveness. This study constructs firm-product level markups as the measure of export competitiveness using microdata of millions of observations from Chinese industrial firms. It then empirically investigates the impact of environmental regulations on those firms' export competitiveness. The empirical study finds: 1) environmental regulations have significantly increased the markups of Chinese firms' export products, indicating that firms' export competitiveness is enhanced, verifying the validity of the Porter Hypothesis. 2) Environmental regulations have a greater effect on increasing the markups of non-core products than that of core products. 3) Environmental regulations have significantly increased the markups for private-owned firms, foreign-invested firms, and firms in the eastern region, but not for state-owned and non-eastern firms. 4) Environmental regulation mainly enhances firms' export competitiveness mainly through the TFP channel. Moreover, a series of robustness tests support the empirical results. This research recognizes the positive achievements and benefits of China's environmental governance. It recommends that the Chinese government strengthen the supervision of state-owned enterprises and help enterprises in economically underdeveloped areas overcome the challenges brought by environmental regulation. • The impact of environmental regulation on export competitiveness is discussed. • Export competitiveness is measured by a new indicator: firm-product level markups. • Environmental regulations have significantly increased the export competitiveness of Chinese firms. • Environmental regulation enhances firms' export competitiveness mainly through the TFP channel. [ABSTRACT FROM AUTHOR]

The pollution control of local government to industrial enterprises is actually a long-term, complex and dynamic game process. This study develops an evolutionary game model to analyze the operation mechanism of local governments' different expenditure preferences on the production behavior of industrial polluting enterprises, so as to specify the behavioral characteristics and optimal strategy of local environmental governance. The results indicated that whether the relationship between local governments and polluting enterprises in environmental governance becomes cooperative or collusive depends on their game sequence and initial endowment. Under the condition of realizing a steady state of cooperation, polluting enterprises would advance faster toward clean production if local governments distribute more environmental expenditures on cost subsidies for enterprises to implement clean production. The findings of this study provide decision-making basis for local governments to control industrial pollution. • Government environmental control is studied using an evolutionary game model. • The behavior and optimal strategies for environmental control are revealed. • The evolution result is influenced by the game order and initial endowment. • Realizing a steady state of cooperation requires an incentive mechanism. [ABSTRACT FROM AUTHOR]

Pollution emissions in China are associated with the relationship between local governments and enterprises, especially in those cities with government-enterprise collusion (GEC). We evaluate the causal relationships between GEC and SO 2 emissions at the enterprise level, by adopting the Propensity Score Matching–Difference in Difference method from a comprehensive environmental database. The empirical results show that, compared with those in the cities without collusion, SO 2 emissions of enterprises in the colluded cities increase by 11.3% (95% Confidence Interval (CI): 0.041–0.186). These GEC effects are more substantial in the cities whose regional officials work with longer terms, in the foreign-owned or small-scale enterprises, and the labour-intensive industries. The findings suggest the existing environment and personnel management policies in China should be adjusted for more sustainable development. • New government-enterprise collusion (GEC) measure is examined. • The GEC increase SO 2 emissions. • PSM-DID models show strong causation between collusion and pollution emissions. • Effects of GEC on SO 2 emissions are dependent on the characteristics of officials, enterprises, and industries. [ABSTRACT FROM AUTHOR]