资源科学 ›› 2018, Vol. 40 ›› Issue (4): 759-772.doi: 10.18402/resci.2018.04.10

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中国能源环境效率的空间关联网络结构及其影响因素

黄杰()   

  1. 信阳师范学院商学院,信阳 464000
  • 收稿日期:2017-03-13 修回日期:2017-10-06 出版日期:2018-05-02 发布日期:2018-05-02
  • 作者简介:

    作者简介:黄杰,男,河南驻马店人,博士,讲师,主要研究方向为资源环境经济学。E-mail:huangjiernn@163.com

  • 基金资助:
    河南省哲学社会科学项目(2017CJJ095);河南省政府决策招标项目(2017B255);信阳师范学院“南湖学者奖励计划”

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

摘要:

提升能源环境效率不仅是中国生态文明建设的客观要求,也是实现经济社会可持续发展的必然选择。文章以1995—2015年中国省际面板数据为样本,采用非径向、非角度、双导向的窗口DEA模型测度出30个省份的能源环境效率,并利用VAR格兰杰因果检验方法识别中国省际能源环境效率的空间关联关系,在此基础上通过社会网络分析(SNA)方法揭示中国省际能源环境效率的空间关联网络特征及其影响因素。结果表明,中国省际能源环境效率呈现出显著的、复杂的空间关联网络结构。板块分析显示:东部省份主要位于“净溢出板块”,是中国能源环境效率提升的“发动机”,在网络中处于核心地位,而西部省份主要位于“净受益板块”,在网络中处于边缘地位;经济发展水平、能源消费结构、产业结构、环境规制和技术创新的地区差异与能源环境效率的空间关联网络呈显著相关关系,相似的经济发展水平和产业结构及相近的技术水平有利于中国省际能源环境效率空间关联网络的形成。能源环境效率空间关联的网络结构为中国节能提效政策的制定和实施带来严峻挑战,同时也为新时代区域协调发展战略的实施、能源环境效率跨区域协同提升机制的构建创造了条件。

关键词: 能源环境效率, 窗口DEA模型, 格兰杰因果检验, 空间网络结构, 影响因素, 中国

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