The average environmental efficiency technique and its application to Chinese provincial panel data

In this study, we propose average environmental efficiency, a more comprehensive, fair, comparable, and robust environmental efficiency measurement considering all projection directions to the efficient frontier, and then it is used to evaluate the environmental efficiency of Chinese provinces from 2006 to 2017. Furthermore, we investigate the most influential factors of regional environmental efficiency via a feasible generalized least squares regression approach. The empirical results show that only nine Chinese provinces have average environmental efficiency greater than the national average, implying that two-thirds of the provinces still have much room for improvement. Additionally, environmental efficiency disparities exist between provinces and between four larger geographical areas. The east area achieved the best environmental efficiency over the studied period, better than the whole country, followed in order by the west area, central area, and northeast area. Moreover, we find that the energy consumption structure, government intervention, and economic openness significantly and negatively influence regional environmental efficiency. Finally, we provide policy implications in terms of energy consumption structure optimization, government supervision, and foreign investment introduction while considering the local conditions in different provinces.

How does green technology innovation affect urbanization? An empirical study from provinces of China

The construction of new-type urbanization with the theme of innovation, green, and smart development is becoming the endogenous driving force of China's economic transformation and upgrading, and green technological innovation is a key factor in cracking the problems of development motivation and environmental constraints in urbanization construction. This paper investigates the impact of green technology innovation on urbanization based on a panel dataset covering 30 provinces in China from 2005 to 2019. First, we use the entropy method and the super-efficiency DEA method to measure the level of urbanization and green technology innovation, respectively. Moreover, on this basis, we use panel regression model and FGLS model to estimate the direct impact of green technological innovation on urbanization and its three dimensions-population urbanization, industrial urbanization, and ecological urbanization. Then, the mediating effect model is used to further study the indirect impact of green technological innovation on urbanization. The results indicate that green technological innovation is the most effective way to promote the development of new urbanization currently. In addition, green technology innovation can indirectly affect urbanization through the effects of foreign capital, energy consumption and information development, while the effect of industrial structure optimization effects is not significant. Finally, some policy suggestions are discussed to better promote the development of urbanization in China.