Multidimensional performance assessment, government competition and ecological welfare performance.

Improving the efficiency of converting natural resources into social benefits is an important issue for sustainable development in today's world. Based on this background this paper applies the super-efficient SBM model with non-expected output to measure the ecological welfare performance (EWP) of Chinese provinces from 2005-2019, and explores the relationship between government competition and EWP under different assessment systems. The research results show that government competition under economic performance assessment is self-interested and short-sighted, which can negatively affect ecological welfare performance in the current period as well as in the next four years. In contrast, government competition under the environmental assessment system promotes EWP in both the current and long term, balancing short-term and long-term benefits. The results of the spatial GMM found that government competition under economic performance appraisal can deteriorate EWP in local as well as surrounding areas, but government competition under the environmental assessment system can achieve an increase in local ecological welfare performance and the spillover effect is not significant. To alleviate the limitations of a single appraisal system, this paper incorporates both economic and ecological appraisals into the multidimensional appraisal system. When the weights of both are between 1:9 and 3:7, the government competition under multidimensional performance appraisal can promote both current and longer-term EWP, and achieve its own ecological welfare performance without affecting the surrounding areas.

Research on the evolution and driving factors of digitalization of energy in China-A new perspective based on coupling coordination.

The world is experiencing the tide of digital transformation. Promoting the digitalization of energy is an important measure to realize energy sustainability. The digitalization of energy is a product of the coupled and coordinated development of the energy industry and the digital economy. This paper takes 30 provinces in China from 2011 to 2020 as research objects. The Entropy Weight Method is used to measure the development level of China's energy industry and digital economy, and the Coupling Coordination Degree Model is used to measure the digitalization of energy (DE). Then, the evolution characteristics and driving factors of China's DE are studied by using Grey Prediction Model, Kernel Density Analysis Method and Geodetector Model. The conclusions are mainly as follows: (1) Though the development level of energy industry and digital economy in China are both growing over time, there are distinct features in their spatial distribution. (2) The DE is in a disorderly state as a whole, but it will be upgraded to the stage of barely coordinated during China's 14th Five-Year Plan period (2021-2025). From the evolutionary process, the distribution pattern and trend changes of DE are characterized by obvious polarization distribution and increasing absolute differences, and this feature is more obvious in the central and western regions. (3) Government support, FDI, and pollution governance have an increasing impact on DE, but this impact varies considerably between the east and central-west regions. Therefore, this paper suggests that local governments should formulate policies to promote the DE according to local conditions. The central government should focus on accelerating the construction of the "East Digital West Computing" project and the development of the energy Internet to solve the problem of uneven regional development.

Economic Growth Targets and Carbon Emissions: Evidence from China.

Carbon emissions have become a new threat to sustainable development in China, and local government actions can play an important role in energy conservation and emission reduction. This paper explores the theoretical mechanisms and transmission paths of economic growth targets affecting carbon emissions from the perspective of economic growth targets and conducts an empirical analysis based on 30 provincial panel data in China from 2003 to 2019. The results show that: economic growth targets are positively correlated with carbon emissions under a series of endogeneity and robustness; there are regional heterogeneity, target heterogeneity and structural heterogeneity in the impact of economic growth targets on carbon emissions; after economic growth targets are set, government actions can influence carbon emissions by affecting resource mismatch and industrial restructuring; It is further found that there is a "U" shaped relationship between economic pressure and carbon emissions. Based on the above findings, this paper further proposes that a high-quality performance assessment mechanism should be developed to bring into play the active role of local governments in achieving carbon reduction goals, and thus contribute to high-quality economic development.