The implementation of green finance is a powerful measure to promote global carbon emissions reduction that has been highly valued by academic circles in recent years. However, the role of green credit in carbon emissions reduction in China is still lacking testing. Using a set of panel data including 30 provinces and cities, this study focused on the impact of green credit on carbon dioxide emissions in China from 2006 to 2016. The empirical results indicated that green credit has a significantly negative effect on carbon dioxide emissions intensity. Furthermore, after the mechanism examination, we found that the promotion impacts of green credit on industrial structure upgrading and technological innovation are two effective channels to help reduce carbon dioxide emissions. Heterogeneity analysis found that there are regional differences in the effect of green credit. In the western and northeastern regions, the effect of green credit is invalid. Quantile regression results implied that the greater the carbon emissions intensity, the better the effect of green credit. Finally, a further discussion revealed there exists a nonlinear correlation between green credit and carbon dioxide emissions intensity. These findings suggest that the core measures to promote carbon emission reduction in China are to continue to expand the scale of green credit, increase the technology R&D investment of enterprises, and to vigorously develop the tertiary industry.

This study examines the influence of industrial structure upgrading in China on urban-rural income disparity. Using panel data from 30 provinces with the empirical analysis methodology, we find that, during 2013 and 2018, industrial structure upgrading in China plays a significantly positive role in narrowing urban-rural income disparity. By the mechanism analysis, we find that urbanization rate is an intermediary variable which affects this causation. Further, urbanization in industrial structure upgrading for the influence of narrowing rural-urban income disparity existing in threshold effects, and threshold levels present a regional difference. Using the urban-rural consumption gap as the proxy variable of income gap, the result is still stable.

Improving the low-carbon utilization efficiency of urban land is crucial to the low-carbon transformation and sustainable development of China and the world economy. Innovation-driven development, especially the construction of National Independent Innovation Demonstration Zones (NIIDZs), is an important measure to realize the low-carbon transformation of urban land use and sustainable economic development in China. However, previous studies have neglected to study the impact of the construction of NIIDZs on the low-carbon utilization efficiency of urban land. Based on a theoretical analysis and using the panel data of 283 cities in China from 2006 to 2019, we took NIIDZ construction in China as a quasi-natural experiment and adopted the progressive difference-in-differences method (DID) to evaluate the impact and action mechanism of NIIDZ construction on urban land low-carbon utilization efficiency. We found that NIIDZ construction can significantly promote the improvement of the low-carbon utilization efficiency of urban land, and a series of robustness analysis results support this research conclusion. With the passage of time, this kind of promotion effect shows a trend of increasing fluctuation. NIIDZ construction mainly improves the low-carbon utilization efficiency of urban land by promoting green technology innovation and generating economies of scale. In addition, compared with eastern cities, small-scale cities and resource-based cities, the promotion effect of NIIDZ construction in central and western cities, large cities, and non-resource-based cities is more obvious. This study provides a theoretical basis and practical reference for the low-carbon utilization of urban land from the perspective of innovation in China.

Against the background of global climate change and the rapid rise of the digital economy, the digital transformation of agriculture is profoundly changing the agricultural production and operation mode with the help of digital technology, becoming a new driving force for low-carbon and sustainable development of agriculture. However, previous studies rarely examined the impact of agricultural digital transformation on agricultural low-carbon transformation from the perspective of carbon productivity. To fill this gap, this study attempts to build a theoretical analysis framework for the impact of agricultural digital transformation on agricultural carbon productivity (ACP). By using a set of panel data from 30 provinces (cities) in China from 2011 to 2019, this study explores the impact of agricultural digital transformation on ACP, as well as its conduction mechanism and the non-linear mechanism. Empirical results show that the transformation of agricultural digitalization is conducive to the promotion of ACP. A series of robustness analyses support this conclusion. The main transmission mechanisms for digital transformation to affect ACP include agricultural industrial structure upgrading, and the agricultural scale operation. In addition, with the improvement of urbanization level and rural human capital, the impact of agricultural digital transformation on ACP presents a “U” type non-linear feature of inhibition first and promotion later. Furtherly, heterogeneity analysis shows that the impact of digital transformation on ACP will vary greatly depending on the levels of ACP, the geographical location of the studied area and whether it is a main grain-producing area. This study provides a theoretical and empirical basis for the improvement of China’s agricultural carbon productivity from the perspective of the digital economy.

In the context of global climate change, improving agricultural carbon productivity is an important channel to cope with climate change, reduce agricultural carbon emissions and maintain agricultural growth. For a long time, agricultural development in China mainly depends on the government's fiscal expenditure. However, does fiscal support helps to promote carbon productivity of agriculture? This question remains to be answered. Using a set of panel data covering 31 provinces and cities from 2003 to 2019, this study empirically explores the impact of agricultural fiscal support on agricultural carbon productivity in China. Benchmark regression results indicate that after controlling other influential factors, regional fiscal expenditure on agricultural has a significantly positive impact on agricultural carbon productivity. In addition, the promotion impacts of fiscal support on agricultural technological innovation and scale operation efficiency are two effective channels by which to help promote agricultural carbon productivity. By using a panel threshold regression model, we find that there exists a nonlinear relationship between fiscal support and agricultural carbon productivity. The input of agricultural machinery and chemical fertilizer are two threshold variables. Further, this causal linkage between fiscal support and agricultural carbon productivity exists differences because of the different levels of agricultural carbon productivity and regions. Our research provides Chinese theoretical basis and practical reference for improvement of agricultural carbon productivity from the perspective of fiscal expenditure.