Xiuwu Zhang’s research while affiliated with Huaqiao University and other places

Introduction Promoting the development of digital technology is an important step in meeting the challenge of global climate change and achieving carbon peaking and carbon neutrality goals. Methods Based on panel data of Chinese cities from 2006 to 2020, this paper used econometrics to investigate the impact and mechanism of digital technology on carbon emissions. Results The results showed that digital technology can significantly reduce carbon emission intensity and improve carbon emission efficiency. These results remained robust after changing the estimation method, adding policy omission variables, replacing core variables, and solving the endogeneity problem. Digital technology can indirectly reduce carbon emissions by promoting green technological innovation and reducing energy intensity, and it plays a significant role in the carbon emission reduction practices of carbon emission trading policies and comprehensive national big data pilot zones. The replicability, non-exclusivity, and high mobility of digital technology help to accelerate the spread of knowledge and information between different cities, which leads to a spillover effect on carbon emission reductions. Our unconditional quantile regression model results showed that digital technology’s carbon emission reduction effect continuously decreases with increases in carbon dioxide emissions. Discussion The results of this paper provide evidence for the potential use of digital technology in achieving the goal of carbon neutrality, which is of great significance for achieving high-quality innovation and promoting the green transformation of the economy and society.

Improving agricultural green total factor productivity is important for achieving high-quality economic development and the SDGs. Digital inclusive finance, which combines the advantages of digital technology and inclusive finance, represents a new scheme that can ease credit constraints and information ambiguity in agricultural production. First, this study focused on agro-ecological functions; we incorporated total agricultural carbon sequestration and emissions extraction into the evaluation system and used the mixed-direction-distance function to calculate agricultural green total factor productivity. Then, based on panel data from 31 provinces in China collected from 2011 to 2021, we used the two-way fixed effect model, the interactive fixed effect, and the plausibly exogenous variable method to test the impact of digital financial inclusion on agricultural green total factor productivity, and its mechanism of action. The panel-corrected standard error and fixed effect Driscoll–Kraay methods were used to account for the unobserved heterogeneity and cross-section dependence in the panel data. The results showed that digital financial inclusion can significantly improve agricultural green total factor productivity. This conclusion remained valid following robustness tests using the spatial econometric model and the method of changing explanatory variables. Digital financial inclusion can improve agricultural green total factor productivity by facilitating the transfer of agricultural land. Sound digital infrastructure and strict green credit policies enhance the role of digital inclusive finance in promoting the green development of agriculture. These conclusions could help the financial sector to formulate flexible, accurate, reasonable, and appropriate financial policies and products that would support agriculture, and enhance the role of digital inclusive finance in promoting sustainable agricultural development.

Green development is the only way to realize harmonious coexistence between people and nature, so it is of great significance to create a benchmark for high-quality development. Based on the panel data of 30 provinces (except Tibet, Hong Kong, Macao, and Taiwan) in China from 2009 to 2020, the super-efficiency slacks-based measure model was used to calculate the green economic efficiency of various regions in China, and a related statistical model was used to verify the influence of different types of environmental regulation policies on green economic efficiency and the intermediary effect of innovation factor agglomeration. The results show that: (1) during the inspection period, the influence of public-participation environmental regulation on the efficiency of the green economy presents an “inverted U” trend, while command-control and market-incentive environmental regulation policies inhibit the improvement of green economic efficiency; (2) the agglomeration of innovative elements plays a significant intermediary role in the transmission path of environmental regulation affecting green economic efficiency, but the intermediary effects of different types of environmental regulation are slightly different. Finally, we discuss environmental regulation and innovative elements, and some corresponding suggestions are put forward.

Tax revenue is one of the essential means through which the government controls the macro-economy and plays a vital role in promoting environmental protection and sustainable development. This study takes Chinese panel data from 2004 to 2020 as sample observations, uses the SBM-GML index method to measure industrial green total factor productivity, and then uses econometric methods such as the two-way fixed effects model and instrumental variable method to analyze the impact of an environmental tax on industrial green transformation. It is found that the generalized environmental tax represented by vehicle and vessel tax, resource tax, and urban land use tax has a significant positive effect on industrial green transformation. After a series of robustness tests and the exclusion of endogeneity, this conclusion remains valid. The research shows that credit governance, the agglomeration of producer service, and their co-agglomeration with manufacturing are important adjustment mechanisms. Among them, credit management is special and compulsory, greatly restricting the environmental pollution behavior of industrial enterprises, and encourages enterprises to make green investments and to actively improve production processes.