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The Chinese economy has been steadily growing since 1978. During most of the period energy intensity fell. Between 2002 and 2005 however energy intensity increased. In this paper we seek an answer for the overall decrease in energy intensity and temporary increase between 2002 and 2005. Index decomposition analysis is used to decompose energy intensity changes between 2000 and 2009 into three factors:...
Building energy performance indicators is the objective need of achieving energy reduction targets and providing decision support for carrying out relevant policies and measures. The article establish accounting frameworks of energy performance index(EPI) based on Logarithmic Mean Divisia Index(LMDI) decomposition technology which considering the activity effect, structure effect, intensity effect...
The paper decomposed the energy intensity of Shanghai based on the adaptive weighted index decomposition method (AWD) into subdivided six sectional energy consumption in Shanghai. The results show that the main cause of decreasing energy intensity in Shanghai was the reduction of sectional energy intensity, and the structure effect from industrial structure adjustment was not obvious. Industry sector,...
Divisia decomposition is an important method to study the changes of indices. Based on the sample data of major industries in China and other 11 OECD countries from 1997 to 2005, this paper uses logarithmic mean Divisia index decomposition approach for analysing empirically the characteristics of energy density changes in these countries. The results of empirical analysis explain the main factors...
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...
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