DocumentCode
3460414
Title
A Decomposition Analysis on Influencing Factors of Industrial Energy Consumption: A Case Study on "The Tenth Five-Year Plan" for Beijing
Author
Zhao, Xiao-li ; Yang, Juan
Author_Institution
Sch. of Bus. Adm., North China Electr. Power Univ., Beijing
fYear
2008
fDate
12-14 Oct. 2008
Firstpage
1
Lastpage
4
Abstract
Energy consumption decomposition is a commonly used method when studying on influencing factors of energy consumption. The paper introduced a relatively reasonable decomposition method-logarithmic mean Divisia index decomposition (LMDI), and decomposed influencing factors of energy consumption into three parts: Scale effect affected by changes in gross production value, structural effect affected by changes in production value of sectors, and efficiency effect affected by energy improvement within industry. The data of industrial energy consumption and gross production value for Beijing during the period of "The 10th five-year plan" were selected in following empirical analysis. The results showed the decrease of efficiency effect and structural effect promoted the falling of energy intensity together, and the action of former factor was larger than later, what was more, the increase of scale effect led the same changes in energy consumption. According to research ,the author suggests industrial energy consumption reduction strategies should aim at accelerate technological innovation and industrial structural adjustments, develop resource-saving economy and take advantage of industrial structural adjustments.
Keywords
energy consumption; innovation management; macroeconomics; technology management; Beijing; decomposition analysis; energy consumption decomposition; gross production value; industrial energy consumption; industrial energy consumption reduction strategies; industrial structural adjustments; logarithmic mean divisia index decomposition; resource-saving economy; technological innovation; Aggregates; Econometrics; Economic forecasting; Economic indicators; Energy consumption; Load forecasting; Power generation economics; Prediction methods; Predictive models; Production;
fLanguage
English
Publisher
ieee
Conference_Titel
Wireless Communications, Networking and Mobile Computing, 2008. WiCOM '08. 4th International Conference on
Conference_Location
Dalian
Print_ISBN
978-1-4244-2107-7
Electronic_ISBN
978-1-4244-2108-4
Type
conf
DOI
10.1109/WiCom.2008.1911
Filename
4680100
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