Considering the current energy efficiency calculation hasn't included the grey haze as the environmental constraint, a Nonseparable Hybrid DEA Model is constructed based on the non-parametric frontier. Taking SO2, NOx, CO2, smoke(dust) who cause haze as undesirable output of energy consumption, the provincial energy efficiency in 2010-2013 under haze environment constraint is measured more scientific. The result suggests that: difference of provincial energy in China is significant; energy efficiency in the eastern China is the highest, followed by central China and western China is the worst; the overall energy efficiency in China is 0.63. Then the influence factors of energy efficiency are analyzed through Tobit model and it is found that energy endowment, industrial structure, the government influence have significant negative effect on energy efficiency, and technological progress has significantly positive effect on energy efficiency. The influence degrees of various factors varies on eastern, central, western China are different. From the perspective of energy conservation and emissions reduction potential, potential of energy saving and pollutants caused haze reduction are both huge. Research results will help different provinces to establish energy saving and gray haze management planning.
[1] BP Amoco. BP statistical review of world energy[R]. Report, London: BP Amoco, 2014-2015.
[2] Lin Chang, Ma Qingxin, Liu Yongchun, et al. Synergistic reaction between SO2 and NO2 on mineral oxides: A potential formation pathway of sulfate aerosol[J]. Physical Chemistry Chemical Physics, 2012, 14(5):1668-76.
[3] 齐晔. 中国低碳发展报告2014[R]. 北京: 清华大学气候政策研究中心, 2014.
[4] Patterson MG. What is energy efficiency? Concepts, indicators, and methodological issues[J]. Energy Policy, 1996,24(5): 377-390.
[5] Phylipsen G J M, Blok W, Worrell E. Handbook on international comparisons of energy efficiency in the manufacturing industry[M]. Netherlands: Utrecht University, 1998.
[6] Boyd G A, Pang J X. Estimating the linkagebetween energy efficiency and productivity[J]. Energy Policy, 2000, 28(5): 289-296.
[7] Hu Jin-li, Wang S C. Total factor energy efficiency of regions in China[J]. Energy Policy, 2006,34(17): 3206-3217.
[8] 魏楚, 沈满洪. 能源效率及其影响因素:基于DEA的实证分析[J]. 管理世界, 2007,(8): 66-76.
[9] 汪克亮, 杨宝臣, 杨力. 基于环境效应的中国能源效率与节能减排潜力分析[J]. 管理评论, 2012, 24(8):40-50.
[10] 屈小娥. 中国省际全要素能源效率变动分解-基于Malmquist指数的实证研究[J]. 数量经济技术经济研究, 2009,(8):29-44.
[11] 李金铠, 沈波, 韩亚峰, 等. 中国区域能源效率比较-基于DEA_Malmquist和聚类分析[J]. 北京理工大学学报(社会科学版), 2012, 14(6):1-6.
[12] 师博, 沈坤荣. 市场分割下的中国全要素能源效率-基于超效率DEA方法的经验分析[J]. 世界经济, 2008,(9): 49-59.
[13] 马海良, 黄德春, 姚惠泽. 中国三大经济区域全要素能源效率研究-基于超效率DEA模型和Malmquist指数[J]. 中国人口·资源与环境, 2011, 21(11):38-43.
[14] 赵金楼, 李根, 苏屹,等. 我国能源效率地区差异及收敛性分析——基于随机前沿分析和面板单位根的实证研究[J]. 中国管理科学, 2013, 21(2): 175-184.
[15] 蔡圣华, 杜立民, 毕清华. 我国提高能源效率的目标设计[J]. 中国管理科学, 2012, 20(3):152-160.
[16] Choi Y, Zhang Ning, Zhou Peng. Efficiency and abatement costs of energy-related CO2 emissions in China: A slacks-based efficiency measure[J]. Applied Energy, 2012, 98(5):198-208.
[17] Bian Yiwen, Hu Miao, Wang Yousen, et al. Energy efficiency analysis of the economic system in China during 1986-2012: A parallel slacks-based measure approach[J]. Renewable & Sustainable Energy Reviews, 2016, 55: 990-998.
[18] Meng Ming, Shang Wei, Zhao Xiaoli, et al. Decomposition and forecasting analysis of China's energy efficiency: An application of three-dimensional decomposition and small-sample hybrid models[J]. Energy, 2015, 68(1):366-369.
[19] Wei Yiming, Liao Hua, Fan Ying. An empirical analysis of energy efficiency in China's iron and steel sector[J]. Energy, 2007, 32(12):2262-2270.
[20] 李廉水, 周勇. 技术进步能提高能源效率吗?-基于中国工业部门的实证检验[J]. 管理世界, 2006,(10):82-89.
[21] Zhao Xiaoli, Rui Yang, Qian Ma. China's total factor energy efficiency of provincial industrial sectors[J]. Energy, 2014, 65: 52-61.
[22] Wang Zhaohua, Zeng Hualin, Wei Yiming, et al. Regional total factor energy efficiency: An empirical analysis of industrial sector in China[J]. Applied Energy, 2012, 97(9):115-123.
[23] 唐玲, 杨正林. 能源效率与工业经济转型-基于中国1998-007年行业数据的实证分析[J]. 数量经济技术经济研究, 2009, (10):34-48.
[24] Farrell M J. The measurement of productive efficiency[J]. Journal of the Royal Statistical Society, 1957, 120(3):253-290.
[25] Charnes A, Cooper W W, Rhodes E. Measuring the efficiency of decision making units[J]. European Journal of Operational Research, 1978, 2(6):429-444.
[26] Banker R D, Charnes A, Cooper W W. Some models for estimating technical and scale inefficiencies in data envelopment analysis[J]. Management Science, 1984, 30(9):1078-1092.
[27] Tone K. A slacks-based measure of efficiency in data envelopment analysis[J]. European Journal of Operational Research, 2001, 130(3):498-509.
[28] Tone K, Tsutsui M. Applying an efficiency measure of desirable and undesirable outputs in DEA to US electric utilities[J]. Journal of CENTRUM Cathedra: The Business and Economics Research Journal, 2011, 4(2): 236-249.
[29] 史丹, 吴利学, 傅晓霞, 等. 中国能源效率地区差异及其成因研究-基于随机前沿生产函数的方差分解[J]. 管理世界, 2008, (2):35-43.
[30] 袁晓玲, 张宝山, 杨万平. 基于环境污染的中国全要素能源效率研究[J]. 中国工业经济,2009, (2):76-86.
[31] Wang Zhaohua, Feng Chao, Zhang Bin. An empirical analysis of China's energy efficiency from both static and dynamic perspectives[J]. Energy, 2014, (74): 322-330.
[32] 张军, 吴桂英, 张吉鹏. 中国省际物质资本存量估算: 1952-2000[J]. 经济研究, 2004,(10):35-44.
[33] Shi Yun, Xia Yinfang, Lu Bihong, et al. Emission inventory and trends of NOx for China, 2000-2020[J]. Journal of Zhejiang University Science A, 2014, 15(6):454-464.
[34] 王志刚, 龚六堂, 陈玉宇. 地区间生产效率与全要素生产率增长率分解(1978-2003)[J]. 中国社会科学, 2006,(2):55-66.
