高耗能行业电力消费长期波动效应研究

中国管理科学 ›› 2014, Vol. 22 ›› Issue (6): 125-133.

高耗能行业电力消费长期波动效应研究

柳瑞禹¹, 叶子菀^1,2

1. 武汉大学经济与管理学院, 湖北武汉 430072;
2. 电力规划设计学院, 北京 100120

收稿日期:2011-07-03 修回日期:2013-03-10 出版日期:2014-06-20 发布日期:2014-06-26
作者简介:柳瑞禹（1957- ），男（汉族），辽宁大连人，武汉大学经济与管理学院，教授，博士生导师，研究方向：电力经济、系统安全.
基金资助:
中央高校基本科研业务费专项资金（201110501020003）

Long-term Fluctuation Effect of Electricity Consumption in Energy-Intensive Industries

LIU Rui-yu¹, YE Zi-wan^1,2

1. Economics and Management School, Wuhan University, Wuhan 430072, China;
2. Electric Power Planning & Engineering Institute, Beijing 100120, China

Received:2011-07-03 Revised:2013-03-10 Online:2014-06-20 Published:2014-06-26

摘要/Abstract

摘要： 为研究电力消费与影响因素之间的互动关系与因素波动冲击产生的响应持续效果，本文以高耗能行业电力消费为研究对象，从宏观经济层面与行业微观层面出发，以我国1985年-2009年为分析区间，应用SVAR模型对高耗能行业电力消费与宏微观影响变量的动态关系进行分析，并通过GIRF分析了宏微观变量与电力消费冲击产生的双向动态响应，利用VD技术分析了变量波动对电力消费的贡献率。结果表明：我国高耗能用电与GDP、行业产值、行业投资存在长期波动效应，外生变量城市化水平、投资结构与电力消费的相关程度不高；电力消费与GDP存在明显的长期效应，高耗能行业电力消费对产值冲击的响应大于行业投资额的冲击。行业微观变量对电力消费波动贡献相对突出。

关键词: 高耗能行业, 电力消费, SVAR, GIRF, 长期波动效应

Abstract: To analyze the interaction and continuing impact of impulse response between factors and electricity consumption, electricity consumption of energy-intensive industries is studied from combination of macroeconomic and microcosmic level, and SVAR model is applied to analyze dynamic relationship between electricity consumption and micro-macro variables based on times series data from 1985 to 2009. Through GIRF, the two-way dynamic effects generated by the shock of macro and micro variables and electricity consumption are also explained.Further,through the application of VD technology, the contribution rate of electricity consumption is estimated as structural impact from variables fluctuations. The results of this paper indicate that firstly,long-term fluctuation effect exists between China's energy-intensive electricity consumption and GDP, industrial output value and investment.Secondly, external variables, the investment structure, the level of urbanization, are not highly related to electricity consumption, which has obvious long-term effect on GDP. At last, as rigid variable of inner energy-intensive industry sector, the impact on electricity consumption by investment is weaker than output, though there is a certain continuity. The contributions of microeconomic variables are relatively prominent to the changes of electricity consumption.

Key words: energy-intensive industry, electricity consumption, SVAR, GIRF, long-term fluctuation effect

中图分类号:

F426

柳瑞禹, 叶子菀. 高耗能行业电力消费长期波动效应研究[J]. 中国管理科学, 2014, 22(6): 125-133.

LIU Rui-yu, YE Zi-wan. Long-term Fluctuation Effect of Electricity Consumption in Energy-Intensive Industries[J]. Chinese Journal of Management Science, 2014, 22(6): 125-133.

参考文献

[1] 张延群,娄峰.中国经济中长期增长潜力分析与预测:2008~2020年[J].数量经济技术经济研究,2009,(12):137-145.

[2] 康重庆,夏清,张伯明.电力系统负荷预测研究综述与发展方向的探讨[J].电力系统自动化,2004,28(17):1-11.

[3] 唐平雅.电力需求预测方法和能源需求预测模型探讨[J].中国电力,2000,33(4):32-34.

[4] 曹世光,柳焯,慈义.电力需求预测模型研究[J].中国电力,1997,30(11):16-18.

[5] James E. Payne. A survey of the electricity consumption-growth literature [J]. Applied Energy, 2010,87(3):723-731.

[6] Kraft J, Kraft A. On the relationship between energy and GNP [J]. Journal of Energy and Development, 1978,3(2): 401-403.

[7] Glasure U, Lee R. Cointegration,error correction,and the relationship between GDP and electricity: The case of South Korea and Singapore [J]. Resources and Electricity Economics, 1997, 20(1):17-25.

[8] Asafu A J. The relationship between electricity consumption, electricity prices and economic growth: Time series evidence from asian developing countries [J]. Energy Economics, 2000, 22:615-625.

[9] Shiu M, Lam P L. Electricity consumption and economic growth in China [J]. Energy policy, 2004, 32(1):47-54.

[10] 林伯强.电力消费与中国经济增长:基于生产函数的研究[J].管理世界,2003,(11):18-27.

[11] 侯建朝.中国能源与经济之间关系的模型及实证分析[D].北京:华北电力大学,2009.

[12] 刘希颖.中国电力需求预测与电力行业可持续发展[D].厦门:厦门大学,2009.

[13] Ozturk I, Acaravci A. The causal relationship between energy consumption and GDP in Albania, Bulgaria, Hungary and Romania: Evidence from ARDL bound testing approach [J]. Applied Energy, 2010, 87(6):1938-1943.

[14] 吴振信,薛冰,王书平.基于VAR模型的油价波动对我国经济影响分析[J].中国管理科学,2011,19(1):21-28.

[15] 张屹山,黄琨,赵继光. 基于SVAR的SHFE铜期货市场功能及国际影响实证研究[J]. 系统工程理论与实践 2006,(9):123-128.

[16] Gust C, Vigfusson R. The power of Long-Run structural VARs[R]. FRB International Finance Discussion Paper, 2009.

[17] 高铁梅.计量经济分析方法与建模[M].北京:清华大学出版社,2009.

[18] Sims C. Macroeconomics and reality [J]. Econometrica, 1980, 48(1):1-48.

[19] Cooley T, Le Roy S. Atheoretical macroeconometrics: A Critique [J]. Journal of Monetary Economics, 1985, 16: 283-308.

[20] Blanchard O, Quah D. The dynamic effects of aggregate demand and supply disturbances [J]. The American Economic Review, 1989, 79(4):655-673.

[21] Keating J. Structural approaches to vector autoregressions[J]. Federal Reserve Bank of St.louis Review,1992,74:31-56.

[22] Pfaff B, VAR, SVAR, and SVEC Models: Implementation Within R Package vars [J]. Journal of Statistical Software, 2008, 27(4):1-32.

[23] 张光南,陈广汉.基础设施投入的决定因素研究:基于多国面板数据的分析[J].世界经济,2009,(3):34-44.

[24] 周杰琦.人民币汇率变动对国内价格水平的传递效应统计研究[J] 2010,(8):33-39.

[25] Narayan P, Narayan S, Prasad A. A structural VAR analysis of electricity consumption and real GDP: Evidence from G7 countries [J]. Energy Policy, 2008,36(7): 2765-2769.