Sources of the potential CO2 emission reduction in China: A nonparametric metafrontier approach

Applied Energy

Volumn 115, Issue , 2014, Pages 491-501

  Du, Kerui ^a   Lu, Huang ^b   Yu, Kun ^c  

^a XIAMEN UNIVERSITY   (China)

^b UNIVERSITY OF CONNECTICUT   (United States)

^c FUDAN UNIVERSITY   (China)

Author keywords

Carbon dioxide emissions; China; Directional distance function; Metafrontier analysis; Technology heterogeneity

Indexed keywords

CARBON DIOXIDE; GLOBAL WARMING; LINEAR PROGRAMMING;

CARBON DIOXIDE EMISSIONS; CHINA; CO2 EMISSION REDUCTION; DIRECTIONAL DISTANCE FUNCTION; EMISSION REDUCTION; METAFRONTIER; NON-PARAMETRIC; TECHNOLOGY GAP;

EMISSION CONTROL;

CARBON DIOXIDE; CARBON EMISSION; EMISSION CONTROL; HETEROGENEITY; NUMERICAL MODEL; TECHNOLOGICAL DEVELOPMENT; TEMPORAL ANALYSIS;

CHINA;

EID: 84891153526     PISSN: 03062619     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apenergy.2013.10.046     Document Type: Article

References (59)

1. World Development Indicators; 2012. <>. http://data.worldbank.org/data-catalog/world-development-indicators.
2. Guo X.D., Zhu L., Fan Y., Xie B.C. Evaluation of potential reductions in carbon emissions in Chinese provinces based on environmental DEA. Energy Policy 2011, 39:2352-2360.
3. Wang K., Yu S., Zhang W. China's regional energy and environmental efficiency: a DEA window analysis based dynamic evaluation. Math Comput Model 2013, 58:1117-1127.
4. 2 emissions in China: a slacks-based efficiency measure. Appl Energy 2012, 98:198-208.
5. Wang Q., Zhou P., Zhou D. Efficiency measurement with carbon dioxide emissions: the case of China. Appl Energy 2012, 90:161-166.
6. Wang K., Lu B., Wei Y.M. China's regional energy and environmental efficiency: a range-adjusted measure based analysis. Appl Energy 2013, 112:1403-1415.
7. Wang K., Wei Y.-M., Zhang X. Energy and emissions efficiency patterns of Chinese regions: a multi-directional efficiency analysis. Appl Energy 2013, 104:105-116.
8. Song M., An Q., Zhang W., Wang Z., Wu J. Environmental efficiency evaluation based on data envelopment analysis: a review. Renew Sustain Energy Rev 2012, 16:4465-4469.
9. Rose A., Casler S. Input-output structural decomposition analysis: a critical appraisal. Econ Sys Res 1996, 8:33-62.
10. Hoekstra R., Van den Bergh J.C. Comparing structural decomposition analysis and index. Energy Econ 2003, 25:39-64.
11. Ang B.W. Decomposition analysis for policymaking in energy: which is the preferred method?. Energy Policy 2004, 32:1131-1139.
12. Greening L.A., Davis W.B., Schipper L. Decomposition of aggregate carbon intensity for the manufacturing sector: comparison of declining trends from 10 OECD countries for the period 1971-1991. Energy Econ 1998, 20:43-65.
13. Nag B., Parikh J. Indicators of carbon emission intensity from commercial energy use in India. Energy Econ 2000, 22:441-461.
14. Fan Y., Liu L.C., Wu G., Tsai H.T., Wei Y.M. Changes in carbon intensity in China: empirical findings from 1980-2003. Ecol Econ 2007, 62:683-691.
15. Chen S. The Abatement of carbon dioxide intensity in China: factors decomposition and policy implications. World Econ 2011, 34:1148-1167.
16. Zhou P., Ang B.W., Poh K.-L. A survey of data envelopment analysis in energy and environmental studies. Eur J Oper Res 2008, 189:1-18.
17. Haynes KE, Ratick S, Cummings-Saxton J. Pollution prevention frontiers: a data envelopment simulation. Environmental program evaluation: a primer; 1998. p. 270-90.
18. Lee J.D., Park J.B., Kim T.Y. Estimation of the shadow prices of pollutants with production/environment inefficiency taken into account: a nonparametric directional distance function approach. J Environ Manage 2002, 64:365-375.
19. Hailu A., Veeman T.S. Non-parametric productivity analysis with undesirable outputs: an application to the Canadian pulp and paper industry. Am J Agric Econ 2001, 83:605-616.
20. Scheel H. Undesirable outputs in efficiency valuations. Eur J Oper Res 2001, 132:400-410.
21. Seiford L.M., Zhu J. Modeling undesirable factors in efficiency evaluation. Eur J Oper Res 2002, 142:16-20.
22. Hua Z., Bian Y., Liang L. Eco-efficiency analysis of paper mills along the Huai River: an extended DEA approach. Omega 2007, 35:578-587.
23. Hoang V.-N., Coelli T. Measurement of agricultural total factor productivity growth incorporating environmental factors: a nutrients balance approach. J Environ Econ Manage 2011, 62:462-474.
24. Murty S., Robert Russell R., Levkoff S.B. On modeling pollution-generating technologies. J Environ Econ Manage 2012, 64:117-135.
25. Färe R., Grosskopf S., Lovell C.K., Pasurka C. Multilateral productivity comparisons when some outputs are undesirable: a nonparametric approach. Rev Econ Stat 1989, 71:90-98.
26. Chung Y.H., Färe R., Grosskopf S. Productivity and undesirable outputs: a directional distance function approach. J Environ Manage 1997, 51:229-240.
27. Zaim O., Taskin F. Environmental efficiency in carbon dioxide emissions in the OECD: a non-parametric approach. J Environ Manage 2000, 58:95-107.
28. Zhou P., Ang B.W., Han J. Total factor carbon emission performance: a Malmquist index analysis. Energy Econ 2010, 32:194-201.
29. Yang H., Pollitt M. The necessity of distinguishing weak and strong disposability among undesirable outputs in DEA: environmental performance of Chinese coal-fired power plants. Energy Policy 2010, 38:4440-4444.
30. Boyd G.A., McClelland J.D. The Impact of Environmental Constraints on Productivity Improvement in Integrated Paper Plants. J Environ Econ Manage 1999, 38:121-142.
31. Färe R., Grosskopf S., Pasurka C.A. Environmental production functions and environmental directional distance functions. Energy 2007, 32:1055-1066.
32. Oggioni G., Riccardi R., Toninelli R. Eco-efficiency of the world cement industry: a data envelopment analysis. Energy Policy 2011, 39:2842-2854.
33. Riccardi R., Oggioni G., Toninelli R. Efficiency analysis of world cement industry in presence of undesirable output: application of data envelopment analysis and directional distance function. Energy Policy 2012, 44:140-152.
34. Färe R., Grosskopf S. Directional distance functions and slacks-based measures of efficiency. Eur J Oper Res 2010, 200:320-322.
35. 2 emission performance in electricity generation: a non-radial directional distance function approach. Eur J Oper Res 2012, 221:625-635.
36. Tone K. Dealing with undesirable outputs in DEA: a Slacks-Based Measure (SBM) approach. In: Presentation at NAPW III, Toronto; 2004.
37. Zhou P., Ang B.W., Poh K. Slacks-based efficiency measures for modeling environmental performance. Ecol Econ 2006, 60:111-118.
38. Zhang N., Choi Y. Environmental energy efficiency of China's regional economies: a non-oriented slacks-based measure analysis. Soc Sci J 2013, 50:225-234.
39. 2 emissions. Environ Econ Policy Stud 2011, 13:89-102.
40. Sueyoshi T., Goto M., Ueno T. Performance analysis of US coal-fired power plants by measuring three DEA efficiencies. Energy Policy 2010, 38:1675-1688.
41. D-h Oh. A metafrontier approach for measuring an environmentally sensitive productivity growth index. Energy Econ 2010, 32:146-157.
42. Battese G.E., Rao D.P. Technology gap, efficiency, and a stochastic metafrontier function. Int J Bus Econ 2002, 1:87-93.
43. Battese G.E., Rao D.P., O'Donnell C.J. A metafrontier production function for estimation of technical efficiencies and technology gaps for firms operating under different technologies. J Prod Anal 2004, 21:91-103.
44. O'Donnell C.J., Rao D.P., Battese G.E. Metafrontier frameworks for the study of firm-level efficiencies and technology ratios. Empir Econ 2008, 34:231-255.
45. Chiu C.R., Liou J.L., Wu P.I., Fang C.L. Decomposition of the environmental inefficiency of the meta-frontier with undesirable output. Energy Econ 2012, 34:1392-1399.
46. 2 emission performance and technology gaps in fossil fuel electricity generation in Korea: a meta-frontier non-radial directional distance function analysis. Energy Policy 2013, 56:653-662.
47. Zhou P., Poh K.L., Ang B.W. A non-radial DEA approach to measuring environmental performance. Eur J Oper Res 2007, 178:1-9.
48. Simar L., Wilson P.W. Non-parametric tests of returns to scale. Eur J Oper Res 2002, 139:115-132.
49. Färe R., Grosskopf S., Norris M. Productivity growth, technical progress, and efficiency change in industrialized countries: reply. Am Econ Rev 1997, 87:1040-1044.
50. Wang C. Decomposing energy productivity change: a distance function approach. Energy 2007, 32:1326-1333.
51. National Bureau of Statistics of China (NBSC). China statistical yearbook. Beijing: China Statistics Press; 2007-2011 [in Chinese].
52. Shan H.J. Reestimating the capital stock of China: 1952-2006. J Quant Tech Econ 2008, 17-31. [in Chinese].
53. China Premium Database; 2012. <>. http://www.ceicdata.com.
54. 2 emissions in China: a nonparametric analysis. Energy Policy 2012, 49:164-172.
55. National Bureau of Statistics of China (NBSC). China energy statistical yearbook. Beijing: China Statistics Press; 2007-2011 [in Chinese].
56. Oh Dh., Lee Jd. A metafrontier approach for measuring Malmquist productivity index. Empir Econ 2010, 38:47-64.
57. Hu J.L., Wang S.C. Total-factor energy efficiency of regions in China. Energy Policy 2006, 34:3206-3217.
58. Chen Z., Song S. Efficiency and technology gap in China's agriculture: a regional meta-frontier analysis. Chin Econ Rev 2008, 19:287-296.
59. 2 emission performance of fossil fuel power plants in China: a metafrontier non-radial Malmquist index analysis. Energy Econ 2013, 40:549-559.