资源科学 ›› 2019, Vol. 41 ›› Issue (5): 847-859.doi: 10.18402/resci.2019.05.03

• 能源与矿产资源 • 上一篇    下一篇

中国省际能源尾效及其影响因素

谢品杰(), 穆卓文()   

  1. 上海电力大学 经济与管理学院,上海 200090
  • 收稿日期:2018-11-21 修回日期:2019-02-13 出版日期:2019-05-25 发布日期:2019-05-25
  • 作者简介:

    作者简介:谢品杰,男,浙江永嘉人,副教授,博士,从事能源经济研究。E-mail: yjzxpj@163.com

  • 基金资助:
    国家自然科学基金青年项目(71103120;51507099);上海市社科规划一般项目(2018BGL019)

Measurement and influencing factors of the growth drag of energy in China

Pinjie XIE(), Zhuowen MU()   

  1. College of Economics and Management, Shanghai University of Electric Power, Shanghai 200090, China
  • Received:2018-11-21 Revised:2019-02-13 Online:2019-05-25 Published:2019-05-25

摘要:

研究能源尾效的影响因素,探究能源尾效的约束机制,能为当前中国破解经济发展难题提供新思路。本文采用省际面板数据,运用偏最小二乘法测算了中国30省(市、区)1997—2016年间各期能源尾效,利用动态面板模型对全国及分组层面的尾效影响因素展开实证分析。研究表明:①中国存在着能源尾效的约束问题,且在不同发展时期呈现出阶段性特征。②全国层面回归结果显示,尾效滞后项、产业结构、经济发展水平和能源价格对能源尾效的增长具有显著的正向推动作用,而科技投入水平、城市化水平和能源结构对能源尾效具有负向贡献,有利于尾效的削减。③分组层面回归结果显示,尾效滞后项、经济发展水平和能源价格仍为推动尾效增长的不良因素所在,而产业结构、科技投入水平、城市化水平和能源结构则在不同的组别呈现出差异性作用效果。根据研究结论,本文从经济发展质量、能源市场价格调控以及城市化发展等方面提供建议,以寻求合理削减尾效的路径。

关键词: 能源尾效, 影响因素, 面板数据, 偏最小二乘法, 系统GMM

Abstract:

Studying the influencing factors and the mechanism of growth drag of energy can provide new ideas for solving the problem in China’s economic development. Based on provincial panel data, this study measured the growth drag of energy of 30 provinces in China from 1997 to 2016 by using the partial least squares (PLS) method. The dynamic panel model was used to empirically analyze the influencing factors at the national and group levels. The results show that: (1) Growth drag of energy is a constraint in China, which shows different characteristics in different development periods. (2) The results of the national level analyses show that lag term of growth drag, industrial structure, economic development level, and energy price have a significant positive effect on the growth drag of energy. The level of input in science and technology, level of urbanization, and energy structure have negative contributions, which are conducive to the reduction of grow drag. (3) The results of the group level analyses show that lag item of growth drag, economic development level, and energy price are still unfavorable factors that promote growth drag, while industrial structure, level of input in science and technology, level of urbanization, and energy structure have double sided effects, which differ in different groups. Based on these conclusions, this article provides some recommendations with regard to the quality of economic development, price regulation of the energy market, and urbanization development, in order to find reasonable methods to reduce the growth drag of energy.

Key words: growth drag of energy, influencing factors, panel data, partial least squares method, system GMM