Spatial-temporal pattern evolution and driving factors of China's energy efficiency under low-carbon economy

Improving energy efficiency and building a low-carbon economy are the important ways to resolve the current contradiction between economic growth and the environment in China. In this paper, we use the super efficiency Slack-Based Measure model (super-efficiency SBM model) to measure the energy efficiency of 30 provinces in China, and then conduct Empirical Orthogonal Function (EOF) to analyze its spatial-temporal evolution. Moreover, we use the Geographically and Temporally Weighted Regression (GTWR) to analyze the spatial-temporal heterogeneity of its driving factors. The results showthat: (i) during the sample period, China's energy efficiency shows a rapidly upward trend, accompanied by the gradually strengthening spatial pattern of the eastern>central>western; (ii) the spatial pattern of the southern>northern exhibited by the annual growth rate of energy efficiency experienced a process of weakening first and then gradually strengthening; (iii) the influencing effects of market openness, relative energy price and industry structure on energy efficiency have no significant heterogeneity as a whole; (iv) the effects of environmental regulation intensity, the marketization level, the technical level, energy consumption structure and economic development level have significant spatial heterogeneity, and the effects of energy conservation and emission reduction policies has significant temporal heterogeneity. (C) 2020 Published by Elsevier B.V.