Spatial Association Network Evolution and Variance Decomposition of Economic Sustainability Development Efficiency in China

Abstract

The economy’s sustainable development has become a national strategic deployment in China. Research on the difference between the economic sustainable development efficiency (ESDE) and the spatial network will assist the government with the deployment of sustainable development strategies and the achievement of the “peak carbon dioxide emissions”. This paper designs the input–output indicator system of sustainable economic development efficiency and builds an unexpected output super-EBM-Malmquist model to measure the ESDE of 30 provinces in China from 2008–2020. According to the ranking of ESDE, the 30 provinces in China are classified into four groups by applying the quartile method, and the difference in the ESDE in different regions and the temporal variation of different provinces are studied by using the Dagum Gini coefficient and Gaussian Kernel density. Moreover, the relationship between ESDE in different provinces is studied based on the revised gravity model and social network analysis method. The connections between provinces with related relations constitute the ESDE network. Results show that (1) the average ESDE in China shows an upward trend, the eastern region is in a leading position, the central and western regions are trying to catch up with the eastern region, and the development of the northeast region is lagging behind. (2) The level of ESDE in different provinces is clearly arranged from high to low, illuminating a distinct pattern. Moreover, provinces with high levels of development are much higher than provinces with low levels of development, presenting a phenomenon of polarization. (3) The regional ESDE development imbalance is prominent, and the ESDE in the eastern region is closely related, while the connection in the western region is lower. (4) Beijing–Tianjin Urban Agglomeration and the Yangtze River Delta have significant spatial spillover effects in the association network, while the northeast, northwest, southwest and central regions have significant spatial benefit relationships. These findings provide important enlightenment for promoting the sustainable and balanced development of China’s economy.