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Exploring the relationship between government subsidies, market competition, and the total factor productivity (TFP) of new energy enterprises will help countries optimize renewable energy support policies in the context of carbon neutrality constraints and energy demand growth. Based on the panel data of 145 listed new energy enterprises from 2007 to 2020, this paper investigates how government subsidies affect the TFP of new energy enterprises and the moderating effects of market competition. Our main findings are as follows: (1) Government subsidies positively affect the TFP of new energy enterprises. Heterogeneity analysis suggests that government subsidies have a larger effect on the TFP of non-SOEs, midstream and upstream enterprises, and smaller enterprises. (2) Industry market competition negatively moderates the effect of government subsidies on TFP, while enterprise competition power has a positive moderating effect. The marginal effect of government subsidies is significantly positive only when the industry market competition is below a certain threshold or the enterprise competitive power exceeds a certain threshold. (3) Government subsidies enhance the TFP by promoting invention and utility model innovation of new energy enterprises. In addition, market competition significantly moderates the relationship between government subsidies and utility model innovation, thereby moderating the marginal effect of government subsidies on TFP. The findings contribute to a better understanding of the relationship between government support, market competition, and new energy development. [ABSTRACT FROM AUTHOR]

In order to better combat environmental pollution, China promulgated the New China Environmental Protection Law (CNEPL) in 2015. Previous studies have focused more on the impact of CNEPL on the enterprise performance and green innovation, ignoring the relationship between CNEPL and industrial low-carbon development. This paper uses the implementation of CNEPL as a quasi-natural experiment and constructs a DID model to analyze whether and how government environmental regulation affect the carbon emissions intensity of heavy polluting industries. The results show that CNEPL implementation significantly reduces industrial carbon emissions intensity. Specifically, after the implementation of the CNEPL, the carbon emissions intensity of the heavy polluting industries decreased by 3.4% annually compared to non-heavily polluting industries. Heterogeneity analysis shows that the CNEPL has greater effects in industries with higher market competition degrees and larger average enterprises sizes. We further study influence mechanisms and find that re-allocation of resources, energy structure optimization, green technology innovation and energy efficiency improvement are significant influence mechanisms. Our findings provide policy insights for using government environmental regulation tools to achieve industrial carbon reduction target. • China's new environmental protection law (CNEPL) is considered as a quasi-natural experiment. • CNEPL reduces the carbon emissions intensity (CEI) of heavily polluting industries (HPIs). • Resource reallocation, green innovation, energy structure and efficiency improvement are main channels. • The effect of CNEPL on the CEI of HPIs is moderated by internal and external factors. [ABSTRACT FROM AUTHOR]

In the social context of mitigating climate change and achieving carbon neutrality, the improvement of carbon emissions efficiency and the protection of biological carbon sequestration have emerged as hot topics recently due to their prospects in carbon dioxide emissions reductions. A large volume of studies has identified the spatial distribution characteristics and influencing factors of carbon emissions efficiency. The contributions of our study lied in constructing a system to measure net carbon sink efficiency. Secondly, this study discussed the carbon neutrality performance of Chinese cities from three different aspects of carbon dioxide emissions, carbon sequestration of vegetation and net carbon sink efficiency. Thirdly, this paper identified the influencing factors of net carbon sink efficiency, and examined the direct and indirect effect of different factors. For this purpose, we evaluated the net carbon sink efficiency of 285 cities in China from 2012 to 2017 using a slacks-based measure model, and explored its spatial distribution characteristics, then employed a spatial Durbin model to explore the influencing factors of net carbon sink efficiency. Our main findings indicate that the net carbon sink efficiency steadily increased during the study period, whereas their spatial characteristics were "high at both ends and low in the middle" from the south to the north. There is a significant spatial autocorrelation in the net carbon sink efficiency of Chinese cities. Several kinds of measures can be applied to promote net carbon sink efficiency, such as increasing the proportion of tertiary industry, promoting economic growth, attracting foreign direct investment, increasing road area, promoting technological progress and strengthening environmental regulation. However, the increase of urban population may decrease efficiency. Nevertheless, an obvious spatial spillover effect exists in the net carbon sink efficiency of Chinese cities. The results can provide policy recommendations for the government to formulate differentiated carbon neutralization policies. [Display omitted] • The carbon sequestration is considered to calculate net carbon sink efficiency (NCSE). • The NCSE is used to discuss the carbon neutral performance of Chinese cities. • Chinese NCSE steadily increased and showed significant spatial autocorrelation. • Spatial Durbin model was adopted to study the influencing factors of NCSE. [ABSTRACT FROM AUTHOR]

Green credit policy (GCP) is an important practical exploration to guide green economic development by financial means. Empirically, however, little is known about the relationship between GCP and industrial carbon emissions intensity (CEI). This study aims to investigate the impact of GCP on the CEI of heavily polluting industries (HPIs) by treating Green Credit Guidelines as a quasi-natural experiment. Using Chinese industry-level panel data and a difference-in-difference model, we find that after the implementation of GCP, the CEI of HPIs decreased by an average of 0.267 tons/104 yuan per year compared to non-HPIs. Resource allocation effect and green innovation effect are two channels through which GCP reduces CEI of HPIs. Moreover, the GCP has a greater effect on the CEI of HPIs with lower state-owned ratios, higher total factor productivity and higher capital dependence. These findings provide policy insights for promoting industrial carbon emissions reduction. • The green credit policy (GCP) reduces the carbon emissions intensity (CEI) of heavily polluting industries (HPIs). • The GCP reduces the CEI of HPIs through resource allocation effect and green innovation effect. • The GCP has a greater effect on HPIs with lower state-owned ratios, higher productivity and higher capital dependence. • The GCP has an asymmetric effect on average market share, energy intensity and green innovation. [ABSTRACT FROM AUTHOR]

Digital economy development (DED) empowers rural habitat (RH) improvement and promotes the construction of harmonious villages. Based on a panel data of 30 provinces in China from 2013 to 2019, this paper empirically tests the impact of DED on RH and its endogenous mechanism in multiple dimensions using panel fixed effects model and spatial Durbin model. The results show that DED significantly improves RH, which remains robust after a series of robustness tests and dealing with endogeneity issues. The mechanism analysis shows that DED helps to bring into play the rural resource allocation effect, the innovation and entrepreneurship effect, and the carbon emission reduction effect, and improves the RH through these three effects. Further study finds that the digital application divide and regional divide are the main barriers to digital technology enabling RH improvement, there is a spatial spillover effect of DED, which helps to promote the improvement of RH in neighboring areas. The results of the study can provide theoretical support and decision-making reference for the construction of digital villages and the balanced regional development of RH in China. • Indicator system of digital economy and rural habitat was constructed. • Digital economy development significantly boosts rural habitat. • Resource allocation, rural entrepreneurship, and carbon reduction are effective transmission mechanisms. • Digital application divide has a heterogeneity impact. • The spatial spillover effect of the digital economy is significant. [ABSTRACT FROM AUTHOR]

Rural revitalization is inseparable from the construction of human habitat, the coordinated development of rural culture and physical environment profoundly affects the quality of the habitat environment, and the improvement of the habitat environment requires a "soft and hard balance". Previous studies have focused more on the overall quality of rural habitat and neglected the coordination of habitat construction. The contribution of our study is the construction of an evaluation index system for the China Rural Habitat Coordinated Degree (CRHCD). The main research results show that the level of soft and hard environment of China's rural habitat is growing, but the construction of soft environment is a shortcoming. CRHCD leaps from nearly dysfunctional (0.440) to barely coordinated (0.538), and is in a transitional stage with stable spatial structure, showing the trend of "from point to line, from line to surface", and gradually developing from coastal to inland. Spatial convergence analysis shows that CRHCD converges fastest in the eastern region, while the northeastern region shows dispersion characteristics. Our results provide a theoretical basis and policy recommendations for the systematic coordination and regional balanced development of rural habitat in China. • The China Rural Habitat Coordinated Degree from the perspective of soft and hard environments were conceptualized. • Evaluation index system and quantitative methods for the China Rural Habitat Coordinated Degree were put forward. • The China Rural Habitat Coordinated Degree was measured and the spatio-temporal divergence pattern was explored. • Rural internal and external conditions can affect the spatial convergence of the China Rural Habitat Coordinated Degree. [ABSTRACT FROM AUTHOR]