TY - JOUR
T1 - The fluctuations of China's energy intensity
T2 - Biased technical change
AU - Wang, Ce
AU - Liao, Hua
AU - Pan, Su Yan
AU - Zhao, Lu Tao
AU - Wei, Yi Ming
N1 - Publisher Copyright:
© 2014 Elsevier Ltd.
PY - 2014/12/5
Y1 - 2014/12/5
N2 - The fluctuations of China's energy intensity have attracted the attention of many scholars, but fewer studies consider the data quality of official input-output tables. This paper conducts a decomposition model by using the Divisia method based on the input-output tables. Because of the problems with input-output tables and price deflators, we first produce constant prices to deflate the input-output tables. And then we consider different levels of biased technical change for different sectors in the adjusting the input-output table. Finally, we use RAS technique to adjust input-output matrix. Then the decomposition model is employed to empirically analyze the change of China's energy intensity. We compare the decomposition results with and without biased technical change and do sensitive analysis on the level of biased technical change. The decomposition results are that during 2002-2007, the energy intensity of coal and electricity increased, the changes were mostly attributed to the structural change and the contribution was 594.08%, 73.88%, respectively; as for crude oil and refined oil, the energy intensity decreased, the changes were mostly attributed to the changes in the production technology and the contribution was 978.89%, 246.95%, respectively. And the results of sensitive analysis shows that 1% variation of the level of biased technical change will cause at most 0.6% change of decomposition results. Therefore, we can draw our conclusions: compared to the decomposition without biased technical change, decomposition results are sensitive to the level of biased technical change; the level of biased technical change can be determined by the difference in the change rate of total factor productivity and energy efficiency.
AB - The fluctuations of China's energy intensity have attracted the attention of many scholars, but fewer studies consider the data quality of official input-output tables. This paper conducts a decomposition model by using the Divisia method based on the input-output tables. Because of the problems with input-output tables and price deflators, we first produce constant prices to deflate the input-output tables. And then we consider different levels of biased technical change for different sectors in the adjusting the input-output table. Finally, we use RAS technique to adjust input-output matrix. Then the decomposition model is employed to empirically analyze the change of China's energy intensity. We compare the decomposition results with and without biased technical change and do sensitive analysis on the level of biased technical change. The decomposition results are that during 2002-2007, the energy intensity of coal and electricity increased, the changes were mostly attributed to the structural change and the contribution was 594.08%, 73.88%, respectively; as for crude oil and refined oil, the energy intensity decreased, the changes were mostly attributed to the changes in the production technology and the contribution was 978.89%, 246.95%, respectively. And the results of sensitive analysis shows that 1% variation of the level of biased technical change will cause at most 0.6% change of decomposition results. Therefore, we can draw our conclusions: compared to the decomposition without biased technical change, decomposition results are sensitive to the level of biased technical change; the level of biased technical change can be determined by the difference in the change rate of total factor productivity and energy efficiency.
KW - Biased technical change
KW - China
KW - Divisia decomposition
KW - Energy intensity
KW - Input-output analysis
KW - RAS technique
UR - http://www.scopus.com/inward/record.url?scp=84907181269&partnerID=8YFLogxK
U2 - 10.1016/j.apenergy.2014.06.088
DO - 10.1016/j.apenergy.2014.06.088
M3 - Article
AN - SCOPUS:84907181269
SN - 0306-2619
VL - 135
SP - 407
EP - 414
JO - Applied Energy
JF - Applied Energy
ER -