As a major carbon dioxide-emitting country, China set carbon trading market to reduce enterprise carbon emissions through the rational allocation of carbon quotas among different enterprises and regions. The market has also conducted a preliminary exploration for the country to achieve carbon dioxide emissions peak in 2030 and carbon neutrality in 2060 while actively addressing the challenges of global climate change. This study analysed the emission reduction effect of China's carbon trading pilot policy, especially the role of carbon quota and carbon trading price. The analysis used county-level panel data from 1997 to 2017, regarded the implementation of the carbon trading pilot policy as a quasi-natural experiment, and used the difference-in-differences method. The results showed that, first, the policy implementation not only reduced regional carbon emissions but also inhibited carbon dioxide emissions per capita, with long-term effects. Second, the carbon emission reduction effect brought by the carbon pilot policy showed significant heterogeneous results with the different degrees of regional carbon emissions and environmental supervision. The effect was greater in areas with higher carbon emission density and stronger legal supervision. Third, the difference in carbon quota allocations resulted in different emission reduction effects, among which the historical method had the strongest effect. The carbon quota price and number of enterprises participating carbon trading market were the key factors affecting carbon emission reduction.

The digital economy is pushing more efficient and greener production and innovation processes, as well as quickening the mobility of production factors, which would have a critical impact on improving industrial green innovation efficiency. Based on the panel data of 30 Chinese provinces from 2005 to 2019, this study established a comprehensive index system to assess the level of provincial digital economy development, and adopted the SBM-DEA model including non-expected output to evaluate industrial green innovation efficiency, then adopted the Global Moran's I and Local Moran's I to test whether there is spatial autocorrelation, followed by the spatial Durbin model (SDM) and the mediating effect test model to investigate the direct impact, spatial spillover effect and indirect transmission mechanism of the digital economy on industrial green innovation efficiency. The results show that: both the development level of the digital economy and industrial green innovation efficiency show positive spatial autocorrelation; The digital economy not only has a significant direct role in promoting industrial green innovation efficiency but also has a spatial spillover effect; The digital economy can improve industrial green innovation efficiency by promoting manufacturing structure upgrading and stimulating enterprises' green technology innovation. The findings of this paper are helpful for policymakers to clarify the relationship between the digital economy and industrial green innovation efficiency and provide favorable policy directions for developing the digital economy to promote industrial green innovation efficiency.

The ‘long tail’ nature of rural special education (RSE) suggests that it simultaneously possesses the private nature of discreteness and the public nature of externalities, which can easily cause provision insufficiency. However, this mismatch may have a dynamic intertemporal correction mechanism impacted by different expenditures of supply sectors (governments and other social sectors). This paper uses different models and data from 30 provinces in China from 2003–2014 to analyze this dynamic correction mechanism. This research finds that different kinds of expenditures from different suppliers have divergent effects on this correction. Capital expenses (especially infrastructure construction) have significantly positive effects on the correction, but administrative expenses have significant dual effects on the correction. These effects may be caused by the various governance efficiencies and motivations of all stakeholders in RSE. This paper concludes that we should pay more attention to the accurate recognition and effective satisfaction of RSE affected by the governance efficiency and motivation of different suppliers to achieve this dynamic correction.

The green credit policy (GCP) is an institutional framework aimed at guiding enterprises towards green transformation and promoting high-quality development, which serves as a crucial tool for supporting the establishment of a green technology innovation system. In this study, utilizing the green credit guidelines as a quasi-natural experiment and constructed a continuous difference-in-difference (DID) model, examines the impact of GCP impact on enterprise green innovation and its internal mechanisms by analyzing data from Chinese A-share listed companies between 2006 and 2021. Our findings indicate that the GCP had a significant impact on enterprise green innovation, inhibiting companies from in-dependently developing green innovation while promoting joint green innovation with other institutions; These results were robust and consistent, even after conducting several sensitiv-ity analyses; This mechanism indicate that the commercial credit plays an important regulatory role in the process of GCP affecting green innovation of enterprises and the financing constraints act as an intermediary factor in the process of GCP affecting green innovation. Based on our research, we offer policy recommendations aimed at improving the GCP and fostering a market-oriented green technology innovation system.