The efficiency improvement potential for coal, oil and electricity in China's manufacturing sectors

This paper introduces an improved total-factor ESTR (energy-saving target ratio) index, which combines the sequence technique and the “energy direction” to a DEA (data envelopment analysis) model, in order to measure the possible energy saving potential of a manufacturing sector. Afterward, the energy saving potentials of four different energy carriers, namely coal, gasoline, diesel oil and electricity, for 27 manufacturing sectors during the period of 1998–2011 in China are calculated. The results and its policy implications are as follows: (1) the average ESTRs of coal, gasoline, diesel oil and electricity are 1.714%, 49.939%, 24.465% and 3.487% respectively. Hence, energy saving of manufacturing sectors should put more emphasis on gasoline and diesel oil. (2) The key sectors for gasoline saving is the energy-intensive sectors, while the key sectors for diesel oil saving is the equipment manufacturing sectors. (3) The manufacture of raw chemical materials and chemical products sector not only consumes a large amount of oil, but also has a low efficiency of oil usage. Therefore, it is the key sector for oil saving. (4) Manufacture of tobacco and manufacture of communication equipment, computers and other electronic equipment are the benchmark for the four major energy carriers of energy-saving ratios.

[1]  Zhao Xiaoli,et al.  China's total factor energy efficiency of provincial industrial sectors , 2014 .

[2]  Jin-Li Hu,et al.  Efficient energy-saving targets for APEC economies , 2007 .

[3]  H. Chenery,et al.  Industrialization and Growth: A Comparative Study , 1986 .

[4]  Huifeng Pan,et al.  China's provincial industrial energy efficiency and its determinants , 2013, Math. Comput. Model..

[5]  P. He,et al.  Estimation of potential energy saving and carbon dioxide emission reduction in China based on an extended non-radial DEA approach , 2013 .

[6]  Shiyi Chen,et al.  The evaluation indicator of ecological development transition in China's regional economy , 2015 .

[7]  Jin-Li Hu,et al.  Ecological total-factor energy efficiency of regions in China , 2012 .

[8]  Ming-Chung Chang,et al.  A comment on the calculation of the total-factor energy efficiency (TFEE) index , 2013 .

[9]  G. Boyd,et al.  Estimating the linkage between energy efficiency and productivity , 2000 .

[10]  Fan Ying,et al.  Research on change features of Chinese energy intensity and economic structure , 2004 .

[11]  Wei Zhang,et al.  China's regional energy and environmental efficiency: A DEA window analysis based dynamic evaluation , 2013, Math. Comput. Model..

[12]  Ming-Chung Chang,et al.  Energy intensity, target level of energy intensity, and room for improvement in energy intensity: An application to the study of regions in the EU , 2014 .

[13]  Li Zhang,et al.  Estimates of the potential for energy conservation in the Chinese steel industry , 2011 .

[14]  Feng He,et al.  Energy efficiency and productivity change of China’s iron and steel industry: Accounting for undesirable outputs , 2013 .

[15]  Xiaolong Xue,et al.  Measuring energy consumption efficiency of the construction industry: the case of China , 2015 .

[16]  M. Farrell The Measurement of Productive Efficiency , 1957 .

[17]  Guanghui Zhou,et al.  Measuring energy efficiency performance of China's transport sector: A data envelopment analysis approach , 2014, Expert Syst. Appl..

[18]  B. W. Ang,et al.  Measuring environmental performance under different environmental DEA technologies , 2008 .

[19]  Jiahai Yuan,et al.  Total-factor energy efficiency in developing countries , 2011 .

[20]  Jin-Li Hu,et al.  Total-factor energy efficiency of regions in China , 2006 .

[21]  Chu Wei,et al.  China's energy inefficiency: A cross-country comparison , 2011 .

[22]  Ke Li,et al.  The nonlinear impacts of industrial structure on China's energy intensity , 2014 .

[23]  C. Shiyi Reconstruction of Sub-industrial Statistical Data in China(1980—2008) , 2011 .

[24]  Victoria Shestalova,et al.  Sequential Malmquist Indices of Productivity Growth: An Application to OECD Industrial Activities , 2003 .

[25]  Jin-Li Hu,et al.  Efficient saving targets of electricity and energy for regions in China , 2011 .

[26]  Peng Zhou,et al.  A survey of data envelopment analysis in energy and environmental studies , 2008, Eur. J. Oper. Res..

[27]  Ke Wang,et al.  A comparative analysis of China’s regional energy and emission performance: Which is the better way to deal with undesirable outputs? , 2012 .

[28]  Yi-Ming Wei,et al.  Regional total factor energy efficiency: An empirical analysis of industrial sector in China , 2012 .

[29]  David I. Stern,et al.  Modeling international trends in energy efficiency , 2012 .

[30]  Boqiang Lin,et al.  The improvement gap in energy intensity: Analysis of China's thirty provincial regions using the improved DEA (data envelopment analysis) model , 2015 .

[31]  Ning Zhang,et al.  Measuring ecological total-factor energy efficiency incorporating regional heterogeneities in China , 2015 .

[32]  Boqiang Lin,et al.  Metafroniter energy efficiency with CO2 emissions and its convergence analysis for China , 2015 .

[33]  Yi-Ming Wei,et al.  An empirical analysis of energy efficiency in China's iron and steel sector , 2007 .

[34]  Zhaohua Wang,et al.  An empirical analysis of China's energy efficiency from both static and dynamic perspectives , 2014 .

[35]  Dong-hyun Oh,et al.  A global Malmquist-Luenberger productivity index , 2010 .