DocumentCode
2654881
Title
Multivariate Cointegration Analysis of the Relationship between Electricity Consumption and Economic Growth in China
Author
Xing-ping, ZHANG ; Yu-qin, NIU ; Jian-jun, JI
Author_Institution
North China Electr. Power Univ., Beijing
fYear
2007
fDate
20-22 Aug. 2007
Firstpage
2110
Lastpage
2115
Abstract
Many scholars research deeply the relationship between the electricity consumption and GDP. In my view, the composing factors of GDP impact on the electricity consumption in different ways, so the relationship between the electricity consumption and the composing factors of GDP is studied in the paper. Electricity consumption is chosen as the explained variable, and Fixed asset investment, disposal income per capita, export, and electricity power price are chosen as the explanatory variables, twenty-five years (from 1980 to 2004) real data of all the variables (deducted the influence of inflation) in China are taken as the samples. Based on the unit root test and cointegration test, the model is found to analyze the cointegration relationship between the explained variable and explanatory variables, and it is suitable to forecast the electricity demand in long-term. Owing to the existence of equilibrium mechanism, the error correction model is applied to analyze the degree that the short-term electricity consumption deviate the long-term equilibrium state.
Keywords
economic indicators; error correction; investment; power consumption; power system economics; pricing; China; GDP; disposal income per capita; economic growth; electricity consumption; electricity power price; error correction model; export; fixed asset investment; multivariate cointegration analysis; Conference management; Economic forecasting; Economic indicators; Energy consumption; Energy management; Engineering management; Error correction; Industrial relations; Investments; Testing; cointegration analysis; electricity consumption; error correction model; unit root test;
fLanguage
English
Publisher
ieee
Conference_Titel
Management Science and Engineering, 2007. ICMSE 2007. International Conference on
Conference_Location
Harbin
Print_ISBN
978-7-88358-080-5
Electronic_ISBN
978-7-88358-080-5
Type
conf
DOI
10.1109/ICMSE.2007.4422151
Filename
4422151
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