Na Lu

Public data openness (PDO) is critical for advancing digital government initiatives and sustainable development. This study investigates the impact and underlying mechanisms of PDO on carbon emission efficiency (CEE) using a staggered difference-in-differences (DID) approach. The results reveal that the PDO significantly improves CEE. Mechanism analysis demonstrates that PDO enhances CEE by facilitating digital technology innovation, improving capacity utilization, and fostering industrial structure upgrading. The positive effect of PDO on CEE exhibits heterogeneity across the dimensions of data themes, human capital, green finance development, and land marketization. Furthermore, the Broadband China Strategy (BCS) and the New Energy Demonstration City (NEDC) policy amplify PDO’s positive effect on CEE. This study quantitatively evaluates the economic and environmental effects of data resource openness and sharing, offering insights into deepening data infrastructure development and unleashing data’s potential to promote sustainable development.

Land is a critical factor of production that contributes significantly to economic growth. However, conventional land use pattern in China has resulted in serious environmental pollution. Now enhancing green land use efficiency (GLUE) has emerged as an effective strategy for improving environmental quality. The development of the digital economy (DE), characterized by low cost and high efficiency, has demonstrated considerable potential in reducing environmental pollutants and enhancing resource allocation. This study employs an extensive analytical framework to analyze the impact of DE development on GLUE across 267 cities in China from 2011 to 2019. The results show that DE exerts a significant effect on improving GLUE, which remains valid after the execution of endogeneity and robustness tests. The research on mechanisms indicates that this promotional effect is primarily achieved through the innovation in green technology and the optimization of industrial structure. Extended empirical tests indicate there is a nonlinear trend, wherein the positive effect increasingly intensifies after green industry innovation and industrial structure optimization exceeds threshold values. There is also a significant short term spillover effect of DE on GLUE, supplemented by long term effects. These findings substantially improve our comprehension of the connection of DE and land use, while providing practical policy recommendations for promoting environmentally sustainable development and land green utilization.

The construction of pilot zones for green finance reform and innovations (GFRI) is an important initiative for the Chinese government to develop a green economy. Based on 3236 A-share listed enterprises from 2011 to 2018, this paper uses the difference-in-differences method (DID) to examine whether GFRI can promote enterprise green technology innovation. The results show that GFRI can significantly enhance enterprise green technology innovation. This conclusion is still robust after the parallel trend test, PSM-DID and placebo inspection. The mechanism research shows that GFRI can relocate the internal and external financing constraints, and then promote enterprise green technology innovation. Further, heterogeneity analysis shows that GFRI’s green technological innovation incentives only exist in the eastern region and non-state-owned enterprises, which not only significantly improves the total green technology patents, but also significantly improves the green invention patents and green practical patents. For the central and western regions and state-owned enterprises, GFRI can only enhance the green invention patents. From the perspective of enterprise green technology innovation, this paper assesses the implementation effect of GFRI, providing theoretical support and empirical evidence for green finance policies to serve China’s green economy.

As the largest carbon emitter in the world, China is confronted with great challenges of mitigating carbon emissions, especially from its construction industry. Yet, the understanding of carbon emissions in the construction industry remains limited. As one of the first few attempts, this paper contributes to the literature by identifying the determinants of carbon emissions in the Chinese construction industry from the perspective of spatial spillover effects. A panel dataset of 30 provinces or municipalities from 2005 to 2015 was used for the analysis. We found that there is a significant and positive spatial autocorrelation of carbon emissions. The local Moran’s I showed local agglomeration characteristics of H-H (high-high) and L-L (low-low). The indicators of population density, economic growth, energy structure, and industrial structure had either direct or indirect effects on carbon emissions. In particular, we found that low-carbon technology innovation significantly reduces carbon emissions, both in local and neighboring regions. We also found that the industry agglomeration significantly increases carbon emissions in the local regions. Our results imply that the Chinese government can reduce carbon emissions by encouraging low-carbon technology innovations. Meanwhile, our results also highlight the negative environmental impacts of the current policies to promote industry agglomeration.

The cities of China are different in scale, studying the decoupling relationship between economic growth and carbon emissions, and the influencing factors will help to achieve China’s “low carbon economy” development strategy. In this paper, the Tapio decoupling model is used to study the decoupling relationship between carbon emissions and economic growth in six different scale cities, including Shanghai, Wuhan, Xianyang, Qinhuangdao, Shizuishan and Jinchang. The conclusions are as follows: the greater the scale of the city, the stronger ability of decoupling; compared with the population, the per capita GDP, the industrial structure has the most positive effect on the decoupling; only the energy intensity has a negative effect, but the effect is greater. Therefore, we should focus on industrial structure optimization and energy intensity reduction.

China’s technological efforts to tackle climate change have lasted for many years. It is necessary to test the effect of these efforts with quantitative method. To be exact, whether and how China’s low-carbon technology innovation responds to climate change should be tested. Based on the 2004–2015 panel data of 30 provinces in China, we use the method of ESDA analyzing the spatial correlation of China’s low-carbon innovation technology. Furthermore, we use the spatial Durbin model empirically analyzing the spatial spillover effects. The results obtained are as follows: first, supply and demand of Chinese low-carbon innovation has some deviation in the spatial distribution. The low-carbon technology innovation as the supply factor shows the characteristics of expanding from the east to the west. Innovation in eastern China has always been the most active, but innovative activities in the middle and western China are gradually decreased. However, carbon emissions have the characteristics of moving westward, implying the change of technology demand different from technology supply. Second, China’s low-carbon innovation actively responds to the trend of climate change, indicating China’s technological efforts have paid off. However, the spatial spillover effects are not significant, showing that the efforts in each region of China still work for himself. Third, environmental regulation and market pull are important factors for low-carbon technology innovation. Among them, both supporting policy and inhibitory policy have significant impact on the local low-carbon technology innovation, but no significant spatial spillover effects. It shows that environmental policies in different regions are competitive and lack of demonstration effects. Economic growth and export as market pull have higher level of effect on low-carbon technology innovation for both local and adjacent areas. Some policy implications are proposed based on these results finally.