The digital economy is an important engine to promote sustainable economic growth. Exploring the mechanism by which the digital economy promotes economic development, industrial upgrading and environmental improvement is an issue worth studying. This paper takes China as an example for study and uses the data of 286 cities from 2011 to 2019. In the empirical analysis, the direction distance function (DDF) and the Global Malmquist-Luenberger (GML) productivity index methods are used to measure the green total factor productivity (GTFP), while Tobit, quantile regression, impulse response function and intermediary effect models are used to study the relationship among digital economy development, industrial structure upgrading and GTFP. The results show that: (1) The digital economy can significantly improve China’s GTFP; however, there are clear regional differences. (2) The higher the GTFP, the greater the promotion effect of the digital economy on the city’s GTFP. (3) From a dynamic long-term perspective, the digital economy has indeed positively promoted China’s GTFP. (4) The upgrading of industrial structures is an intermediary transmission mechanism for the digital economy to promote GTFP. This paper provides a good reference for driving green economic growth and promoting the environment.

In the new stage of global economic development, we hope to achieve both economic development and environmental improvement through green technology innovation. How to effectively obtain the support of technology and finance to green technology innovation is an issue worth studying. This paper constructed an improved super-SBM-DEA efficiency measurement model and combined it with the window analysis method to measure the green technology innovation efficiency (GTIE) of Chinese provinces from 2006 to 2018. Then, based on the PVAR model, the impulse response function and Monte Carlo simulation were used to study the dynamic impact of various variables of technology and finance on GTIE. Finally, the variance decomposition was used to explore the contribution degree of each variable of technology and finance to improving GTIE. The results revealed the following: (1) the average value of China’s provincial GTIE from 2006 to 2018 was 0.42, which is relatively low and shows a trend of volatility and rising. (2) From the impulse response results, it could be seen that various variables of technology and finance have always had a positive impact on GTIE. However, there are differences in the influence degree, shock effect, and dynamic transmission mechanism. (3) The results of the variance decomposition showed that government financial technology investment had the highest contribution to the improvement of GTIE, followed by bank technology credit, then by enterprise independent R&D investment, and finally venture capital. This paper offered a reference to developing countries with regard to improving their GTIE and studying the role of technology and finance.

The decline in the share of labor income is associated with rising income inequality, which raises a series of economic and social problems. These problems seriously threaten the sustainability of economic development. To maintain sustainable economic development, China’s government has invested hundreds of billions of dollars to build economic development zones by attracting high-tech enterprises into the zones. In our paper, we aim to analyze whether the construction of economic development zones can effectively increase the share of labor income. We use PSM-DID (Propensity Score Matching Difference-in-Difference) to evaluate the impact of establishing economic development zones in China on the labor income share of enterprises in economic development zones in 2006. We found that the establishment and construction of economic development zones increased the share of labor income through the “agglomeration effect” and “policy effect”. Estimation of the level of heterogeneity among economic development zones shows that, compared with provincial economic development zones, the construction of national economic development zones has a greater effect on increasing the labor income share of enterprises in those zones. Economic development zones in the eastern, central, and western regions should also increase their share of labor income areas.