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中国管理科学 ›› 2017, Vol. 25 ›› Issue (9): 125-132.doi: 10.16381/j.cnki.issn1003-207x.2017.09.014

• 论文 • 上一篇    下一篇

我国能源强度变动的影响因素分析——基于SDA分解技术

李玲1, 张俊荣2, 汤铃1, 余乐安2   

  1. 1. 北京航空航天大学经济管理学院, 北京 100191;
    2. 北京化工大学经济管理学院, 北京 100029
  • 收稿日期:2016-06-29 修回日期:2017-01-24 出版日期:2017-09-20 发布日期:2017-11-24
  • 作者简介:汤铃(1983-),女(汉族),广西桂林人,北京航空航天大学经济管理学院教授,研究方向:能源市场预测、能源政策仿真与分析,E-mail: tangling_00@126.com.
  • 基金资助:

    国家优秀青年基金项目(71622011);国家重点研发计划重点专项(2016YFF0204405);北京市社会科学基金项目(14JGC094);国家电网公司科技项目

Analysis on Factors of China's Energy Intensity Changes for 1997-2012:Based on Structural Decomposition Analysis

LI Ling1, ZHANG Jun-rong2, TANG Ling1, YU Le-an2   

  1. 1. School of Economics and Management, Beihang University, Beijing 100191, China;
    2. School of Economics and Management, Beijing University of Chemical Technology, Beijing 100029, China
  • Received:2016-06-29 Revised:2017-01-24 Online:2017-09-20 Published:2017-11-24

摘要: 随着我国经济的快速发展及能源消耗的急剧增加,深入分析我国能源强度变动的影响因素成为一个热点研究议题。基于结构分解分析方法(SDA),本文将能源强度变动因素分解成能源消耗系数、完全需要系数、最终需求、最终需求结构系数和最终能源消耗五个因素,并编制了1997、2002、2007、2012年我国实物价值型能源投入产出可比价序列表,以探索影响我国能源强度变动的主导因素。实证研究结果表明:(1)1997-2012年,我国能源总消费呈持续上升趋势,而能源强度波动性下降;(2)能源消耗系数一直是影响我国能源强度下降的主导因素;(3)然而,完全需要系数(即技术系数)对能源强度下降的影响效力在近年来逐步上升,并在2007-2012年间超过了能源消耗系数。

关键词: 能源强度, 结构分解分析, 投入产出表, 能源消耗系数, 完全需要系数

Abstract: With the rapid development of China's economy, two conflicting problems arise, i.e., increase of energy consumption and shortage of energyresources. Energy intensity, measured as energy use per unit of output,can well reflect comprehensiveenergy utilization efficiency. Thus analyzing the major factors of energy intensity changes becomes a basic issue for improving energy intensity.Under such a background,the structural decomposition analysis (SDA) is used to capture the driven factors of China's energy intensity changes. First, energy intensity changes are decomposed into five components-energy consumption coefficient, Leontief inverse coefficient, final demand structure, final demands by category, and final energy consumption coefficient. Second,the contribution of each component to China's energy intensity changes is evaluated to determine the predominant factors. As for database, monetary input-output table is coupled with energy consumption to establish physical-monetary energy input-outputtables for the years 1997, 2002, 2007 and 2012, ata constant price level of 2002. Some interesting findings are obtained in the empirical study:(1) From 1997 to 2012, China's energy consumption keptan increasing trend, whilethe energy intensity reduced with fluctuations.(2) The energy consumption coefficient wasthe leading factorfor China's energy intensity changes.(3) However, the influence of technology coefficient (Leontiefinverse)gradually increased and exceededthat of energy consumption coefficient during 2007-2012.Furthermore, these results provide helpful insights into policy designs for energy conservation and emissions reduction in China.

Key words: energy intensity, structural decomposition analysis, input-output table, energy consumption coefficient, leontief inverse coefficient

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