Resources Science ›› 2018, Vol. 40 ›› Issue (4): 759-772.doi: 10.18402/resci.2018.04.10

• Orginal Article • Previous Articles     Next Articles

The spatial network structure of energy-environmental efficiency and its determinants in China

Jie HUANG()   

  1. School of Business, Xinyang Normal University, Xinyang 464000, China
  • Received:2017-03-13 Revised:2017-10-06 Online:2018-05-02 Published:2018-05-02

Abstract:

Improving energy-environmental efficiency is not only an objective requirement of ecological civilization construction in China, but also an inevitable choice in sustainable economic and social development. In order to measure the energy-environmental efficiency of 30 provinces in China, we used the non-radial, non-angle, dual-oriented DEA window model on the basis of interprovincial panel data from 1995 to 2015. In addition, using the VAR Granger causality test method we identified the spatial association of energy-environmental efficiency in China. Through the use of Social Network Analysis (SNA) methods we revealed the characteristics of the spatial correlation network and its determinants of interprovincial energy-environmental efficiency in China. The results show that there exists a significant and complex spatial network structure in China’s interprovincial energy-environmental efficiency. In the blocks of the spatial association network of energy-environmental efficiency, eastern provinces are mainly located in the “net spillover block”, playing the role of “engine” in the process of improving China’s energy-environmental efficiency. Most of the eastern provinces are in a central location, while western provinces are mainly in the “net benefit block” which lies at an edge position of the spatial correlation network of energy-efficiency. Thus, differences in economic development level, energy consumption structure, industrial structure, environmental regulation and technological innovation were significantly correlated with the spatial correlation network of energy and environmental efficiency. In the meantime, similar economic performance level, industrial structure and technical competence contribute to interprovincial spatial networks of energy-environmental efficiency in China. The spatial correlation network structure of energy-environmental efficiency poses serious challenges to the formulation and implementation of energy efficiency policy, but also creates favorable conditions for the implementation of regional coordinated development and construction of synergy promotion mechanisms of inter-regional energy-environmental efficiency.

Key words: energy-environmental efficiency, DEA window model, Granger Causality Test, spatial network structure, determinants, China