A comprehensive analysis of China's regional energy saving and emission reduction efficiency: From production and treatment perspectives

Energy and environmental issues have recently aroused increasing interest in China and many approaches are used to evaluate energy and environmental performance. In this paper, a two-stage network DEA framework is applied to evaluate the efficiency of energy saving and emission reduction in China during the period of the eleventh five-year plan, from 2006 to 2010. In this study, economic activities are divided into production and treatment processes. This is different from previous research which generally focused on either environmental efficiency or energy efficiency, omitting the integration of energy and environmental measures. Today, energy saving and emission reduction are both parts of the basic state policy of China and are equally important. The empirical results in this study show that: (i) eastern China has the best energy saving and emission reduction efficiency, performing is better than western and central China. (ii) The efficiency of the production process in central China is better than that in western China while the western area performs better than the central area in term of treatment efficiency. (iii) Integrated efficiency of energy saving and emission reduction of China was relatively stable in the five years and the pollution treatment efficiency maintained a rising trend.

[1]  H. O. Fried,et al.  Accounting for Environmental Effects and Statistical Noise in Data Envelopment Analysis , 2002 .

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

[3]  Yan Luo,et al.  Environmental performance analysis of Chinese industry from a slacks-based perspective , 2015, Ann. Oper. Res..

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

[5]  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 .

[6]  Yi-Ming Wei,et al.  China’s regional energy and environmental efficiency: A Range-Adjusted Measure based analysis , 2013 .

[7]  Patrick Y. K. Chau,et al.  Cooperative advertising, game theory and manufacturer-retailer supply chains , 2002 .

[8]  Qiang Wang,et al.  Effective policies for renewable energy--the example of China's wind power--lessons for China's photovoltaic power , 2010 .

[9]  B. W. Ang,et al.  Linear programming models for measuring economy-wide energy efficiency performance , 2008 .

[10]  Jie Wu,et al.  Environmental efficiency evaluation based on data envelopment analysis: A review , 2012 .

[11]  C.A.K. Lovell,et al.  Multilateral Productivity Comparisons When Some Outputs are Undesirable: A Nonparametric Approach , 1989 .

[12]  Rolf Färe,et al.  Productivity and Undesirable Outputs: A Directional Distance Function Approach , 1995 .

[13]  Malin Song,et al.  The electronic government performance of environmental protection administrations in Anhui province, China , 2015 .

[14]  Joe Zhu,et al.  DEA models for supply chain efficiency evaluation , 2006, Ann. Oper. Res..

[15]  Kuangnan Fang,et al.  Evaluation of regional environmental efficiencies in China based on super-efficiency-DEA , 2015 .

[16]  Yanrui Wu,et al.  Energy intensity and its determinants in China's regional economies , 2012 .

[17]  Lawrence M. Seiford,et al.  Modeling undesirable factors in efficiency evaluation , 2002, Eur. J. Oper. Res..

[18]  A. Hailu,et al.  Non‐Parametric Productivity Analysis with Undesirable Outputs: An Application to the Canadian Pulp and Paper Industry , 2001 .

[19]  S. H. Wang,et al.  DEA decomposition of China's environmental efficiency based on search algorithm , 2014, Appl. Math. Comput..

[20]  Kaoru Tone,et al.  Network DEA: A slacks-based measure approach , 2009, Eur. J. Oper. Res..

[21]  Jun Bi,et al.  Chinese regional industrial energy efficiency evaluation based on a DEA model of fixing non-energy inputs , 2010 .

[22]  S Eilon Management Science: An Anthology Volumes I–III , 1997 .

[23]  Timo Kuosmanen Weak Disposability in Nonparametric Production Analysis with Undesirable Outputs , 2005 .

[24]  Abraham Charnes,et al.  Measuring the efficiency of decision making units , 1978 .

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

[26]  Chien-Ming Chen,et al.  Measuring Eco-Inefficiency: A New Frontier Approach , 2011, Oper. Res..

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

[28]  William W. Cooper,et al.  Handbook on data envelopment analysis , 2011 .

[29]  B. Verspagen,et al.  Localized innovation, localized diffusion and the environment: an analysis of reductions of CO2 emissions by passenger cars , 2009 .

[30]  Feng Yang,et al.  Resource and environment efficiency analysis of provinces in China: A DEA approach based on Shannon’s entropy , 2010 .

[31]  Tser-yieth Chen,et al.  A comparative study of energy utilization efficiency between Taiwan and China , 2010 .

[32]  Qunwei Wang,et al.  Efficiency measurement with carbon dioxide emissions: The case of China , 2012 .

[33]  Bai-Chen Xie,et al.  Dynamic environmental efficiency evaluation of electric power industries: Evidence from OECD (Organization for Economic Cooperation and Development) and BRIC (Brazil, Russia, India and China) countries , 2014 .

[34]  R. Färe,et al.  Intertemporal Production Frontiers: With Dynamic DEA , 1996 .