Energy efficiency of selected OECD countries: A slacks based model with undesirable outputs

Energy Economics

Volumn 51, Issue , 2015, Pages 45-53

  Apergis, Nicholas ^a   Aye, Goodness C ^b   Barros, Carlos Pestana ^c   Gupta, Rangan ^b   Wanke, Peter ^d  

^a NORTHUMBRIA UNIVERSITY   (United Kingdom)

^b UNIVERSITY OF PRETORIA   (South Africa)

^c ISEG LISBON SCHOOL OF ECONOMICS AND MANAGEMENT   (Portugal)

^d FEDERAL UNIVERSITY OF RIO DE JANEIRO   (Brazil)

Author keywords

Energy; OECD; SBM Undesitable; Two stage GLMM MCMC

Indexed keywords

ECONOMICS; ENERGY RESOURCES;

CONTEXTUAL VARIABLES; EFFICIENCY ASSESSMENT; ENERGY; OECD; PREDICTIVE ABILITIES; RELATIVE EFFICIENCY; SBM-UNDESITABLE; TWO-STAGE GLMM-MCMC;

ENERGY EFFICIENCY;

ENERGY EFFICIENCY; ENERGY MARKET; MODELING; OECD; PERFORMANCE ASSESSMENT;

EID: 84936932109     PISSN: 01409883     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eneco.2015.05.022     Document Type: Article

References (56)

1. Ang B.W. Monitoring changes in economy-wide energy efficiency: from energy-GDP ratio to composite efficiency index. Energ Policy 2006, 34:574-582.
2. Azadeh A., Amalnick M.S., Ghaderi S.F., Asadzadeh S.M. An integrated DEA PCA numerical taxonomy approach for energy efficiency assessment and consumption optimization in energy intensive manufacturing sectors. Energ Policy 2007, 35:3792-3806.
3. Xie B.-C.Bai-Chen, Shang L.-F., Yang S.-B., Yi B.-W. 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. Energy 2014, 74:147-157.
4. Balachandra P., Ravindranath D., Ravindranath N.H. Energy efficiency in India: assessing the policy regimes and their impacts. Energ Policy 2010, 38:6428-6438.
5. Banaeian N., Namdari M. Effect of ownership on energy use efficiency in watermelon farms - a data envelopment analysis approach. Int. J. Renew. Energy Res. 2011, 1(3):75-82.
6. Boyd G.A., Pang J.X. Estimating the linkage between energy efficiency and productivity. Energ Policy 2000, 28:289-296.
7. Chang T.-P., Hu J.-L. Total-factor energy productivity growth, technical progress, and efficiency change: an empirical study of China. Appl. Energy 2010, 87:3262-3270.
8. Cooper W., Seiford L.M., Tone K. Data envelopment analysis: a comprehensive text with models applications 2007, Springer Science, New York.
9. Diggle P., Heagerty P., Liang K.-Y., Zeger S. Analysis of Longitudinal Data 2002, Oxford University Press, Oxford. 2nd ed.
10. Färe R., Grosskof S. Modeling undesirable factors in efficiency evaluation: comment. Eur. J. Oper. Res. 2004, 157:242-245.
11. Färe R., Grosskof S., Lovell C.A.K., Pasurka C. Multilateral productivity comparisons when some outputs are undesirable: a nonparametric approach. Rev. Econ. Stat. 1989, 70(1):90-98.
12. Fong Y., Rue H., Wakefield J. Bayesian inference for generalized linear mixed models. Biostatistics 2010, 11(3):397-412.
13. Gamerman D. Sampling from the posterior distribution in generalized linear mixed models. Stat. Comput. 1997, 7(1):57-68.
14. Gielen D., Taylor P. Indicators for industrial energy efficiency in India. Energy 2009, 34:962-969.
15. Greene W., Hill R. Maximum ications. Advances in Econometrics 2010, vol. 26. Emerald, United Kingdom.
16. Grösche P. Measuring residential energy efficiency improvements with DEA. J. Prod. Anal. 2009, 31:87-94.
17. Hadfield J. MCMC methods for multi-response generalized linear mixed models: the MCMCglmm R package. J. Stat. Softw. 2010, 33(2):1-22.
18. Hadfield J. MCMCglmm course notes Available at, (accessed 26 September 2014). http://cran.r-project.org/web/packages/MCMCglmm/vignettes/CourseNotes.pdf.
19. Honma S., Hu J.-L. Total-factor energy efficiency of regions in Japan. Energ Policy 2008, 36:821-833.
20. Honma S., Hu J.-L. Total-factor energy productivity growth of regions in Japan. Energ Policy 2009, 37:3941-3950.
21. Hu J.-L., Kao C.-H. Efficient energy-saving targets for APEC economies. Energ Policy 2007, 35:373-382.
22. Hu J.-L., Wang S.-H. Total-factor energy efficiency of regions in China. Energ Policy 2006, 34:3206-3217.
23. IEA World Key Energy Statistics 2013.
24. IEA (International Energy Agency) Energy Technology Perspectives-in Support of the G8 Plan of Action 2008, International Energy Agency, Paris.
25. IPCC Climate change-2007: mitigation of climate change. Working Group III Report to the Fourth Assessment, Intergovernmental Panel on Climate Change 2007, Cambridge University Press, New York, (http://www.ipcc.ch/ipccreports/ar4-wg3.htm).
26. Iribarren D., Vázquez-Rowe I., Rugani B., Benetto E. On the feasibility of using emergy analysis as a source of benchmarking criteria through data envelopment analysis: a case study for wind energy. Energy 2014, 67:527-537.
27. Khoshnevisan B., Rafiee S., Omid M., Mousazadeh H. Applying data envelopment analysis approach to improve energy efficiency and reduce GHG (greenhouse gas) emission of wheat production. Energy 2013, 58:588-593.
28. Korsgaard I., Lund M., Sorensen D., Gianola D., Madsen P., Jensen J. Multivariate Bayesian analysis of Gaussian, right censored Gaussian, ordered categorical and binary traits using Gibbs sampling. Genet. Sel. Evol. 2003, 35(2):159-183.
29. Lange K. Numerical Methods for Statisticians 2010, Springer, New York.
30. Mandal S.K., Madheswaran S. Measuring energy use efficiency in presence of undesirable output: an application of Data Envelopment Analysis (DEA) to Indian cement industry. Working Paper 235 2009, The Institute for Social and Economic Change, Bangalore.
31. Martínez C.I.P. Energy efficiency developments in the manufacturing industries of Germany and Colombia, 1998-2005. Energy Sustain. Dev. 2009, 13:189-201.
32. Mccullagh P., Nelder J.A. Generalized Linear Models 1989, Chapman and Hall, London. 2nd ed.
33. Mcculloch C.E., Searle S.R., Neuhaus J.M. Generalized, Linear, and Mixed Models 2008, John Wiley and Sons, New York. 2nd ed.
34. Mukherjee K. Energy use efficiency in U.S. manufacturing: a nonparametric analysis. Energy Econ. 2008, 30:76-96.
35. Mukherjee K. Energy use efficiency in the Indian manufacturing sector: an interstate analysis. Energ Policy 2008, 36:662-672.
36. Mukherjee K. Measuring energy efficiency in the context of an emerging economy: the case of Indian manufacturing. Eur. J. Oper. Res. 2010, 201:933-941.
37. Nelder J., Wedderburn R. Generalized linear models. J. R. Stat. Soc. Ser. A 1972, 135:370-384.
38. OECD OECD Green Growth Strategies: Energy 2011, OECD Publishing.
39. Ramanathan R. A holistic approach to compare energy efficiencies of different transport modes. Energ Policy 2000, 28:743-747.
40. Ramanathan R. An analysis of energy consumption and carbon dioxide emissions in countries of the Middle East and North Africa. Energy 2005, 30:2831-2842.
41. Scheel H. Undesirable outputs in efficiency valuations. Eur. J. Oper. Res. 2001, 132:400-410.
42. Seiford H., Zhu J. Modeling undesirable factors in efficiency evaluation. Eur. J. Oper. Res. 2002, 142:16-20.
43. Song M.-L., Zhang L.-L., Liu W., Fisher R. Bootstrap-DEA analysis of BRICS' energy efficiency based on small sample data. Appl. Energy 2013, 112:1049-1055.
44. Sorensen D.A., Gianola D., Korsgaard I.R. Bayesian mixed-effects model analysis of a censored normal distribution with animal breeding applications. Acta Agric. Scand. Sect. A Anim. Sci. 1998, 48(4):222-229.
45. Taghizadeh H., Pourrabbi M.V. Energy cost versus production as a performance benchmark for analysis of companies. J. Energy South. Afr. 2013, 24(1):1-8.
46. Tanner M.A., Wong W.H. The calculation of posterior distributions by data augmentation. J. Am. Stat. Assoc. 1987, 82(398):528-540.
47. Tobin J. Estimation of relationships for limited dependent variables. Econometrica 1958, 26:24-36.
48. UNEP (United Nations Environment Programme) Decoupling and Sustainable Resource Management: Scoping the Challenges 2011, UNEP, Paris.
49. Verbeke G., Molenberghs G. Linear Mixed Models for Longitudinal Data 2000, Springer, New York.
50. Verbeke G., Molenberghs G. Models for Discrete Longitudinal Data 2005, Springer, New York.
51. Wang K., Lu B., Wei Y.-M. China's regional energy and environmental efficiency: a range-adjusted measure based analysis 2013.
52. Wei G.C.G., Tanner M.A. Posterior computations for censored regression data. J. Am. Stat. Assoc. 1990, 85:829-839.
53. Wei Y.-M., Liao H., Fan Y. An empirical analysis of energy efficiency in China's iron and steel sector. Energy 2007, 32:2262-2270.
54. Zhang X.-P., Cheng X.-M., Yuan J.-H., Gao X.-J. Total-factor energy efficiency in developing countries. Energ Policy 2011, 39(2011):644-650.
55. Zhou P., Ang B.W. Linear programming models for measuring economy-wide energy efficiency performance. Energ Policy 2008, 36:2911-2916.
56. Zhu H., Lee S. Analysis of generalized linear mixed models via a stochastic approximation algorithm with Markov chain Monte-Carlo method. Stat. Comput. 2002, 12(2):175-183. 10.1023/A:1014890720461.