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Bootstrap-DEA analysis of BRICS’ energy efficiency based on small sample data

Author

Listed:
  • Song, Ma-Lin
  • Zhang, Lin-Ling
  • Liu, Wei
  • Fisher, Ron

Abstract

As a representative of many emerging economies, BRICS’ economies have been greatly developed in recent years. Meanwhile, the proportion of energy consumption of BRICS to the whole world consumption has increased. Therefore, it is significant to analyze and compare the energy efficiency among them. This paper firstly utilizes a Super-SBM model to measure and calculate the energy efficiency of BRICS, then analyzes their present status and development trend. Further, Bootstrap is applied to modify the values based on DEA derived from small sample data, and finally the relationship between energy efficiency and carbon emissions is measured. Results show that energy efficiency of BRICS as a whole is low but has a quickly increasing trend. Also, the relationship between energy efficiency and carbon emissions vary from country to country because of their different energy structures. The governments of BRICS should make some relevant energy policies according to their own conditions.

Suggested Citation

  • Song, Ma-Lin & Zhang, Lin-Ling & Liu, Wei & Fisher, Ron, 2013. "Bootstrap-DEA analysis of BRICS’ energy efficiency based on small sample data," Applied Energy, Elsevier, vol. 112(C), pages 1049-1055.
  • Handle: RePEc:eee:appene:v:112:y:2013:i:c:p:1049-1055
    DOI: 10.1016/j.apenergy.2013.02.064
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    as
    1. Léopold Simar & Paul Wilson, 2000. "Statistical Inference in Nonparametric Frontier Models: The State of the Art," Journal of Productivity Analysis, Springer, vol. 13(1), pages 49-78, January.
    2. Hawdon, David, 2003. "Efficiency, performance and regulation of the international gas industry--a bootstrap DEA approach," Energy Policy, Elsevier, vol. 31(11), pages 1167-1178, September.
    3. Utlu, Zafer & Hepbasli, Arif, 2007. "A review on analyzing and evaluating the energy utilization efficiency of countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 11(1), pages 1-29, January.
    4. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
    5. Mulder, Peter & de Groot, Henri L. F. & Hofkes, Marjan W., 2003. "Explaining slow diffusion of energy-saving technologies; a vintage model with returns to diversity and learning-by-using," Resource and Energy Economics, Elsevier, vol. 25(1), pages 105-126, February.
    6. Kneip, Alois & Simar, Léopold & Wilson, Paul W., 2008. "Asymptotics And Consistent Bootstraps For Dea Estimators In Nonparametric Frontier Models," Econometric Theory, Cambridge University Press, vol. 24(6), pages 1663-1697, December.
    7. Choi, Yongrok & Zhang, Ning & Zhou, P., 2012. "Efficiency and abatement costs of energy-related CO2 emissions in China: A slacks-based efficiency measure," Applied Energy, Elsevier, vol. 98(C), pages 198-208.
    8. Parajuli, Ranjan, 2012. "Looking into the Danish energy system: Lesson to be learned by other communities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(4), pages 2191-2199.
    9. David Hawdon, 2003. "Efficiency and Performance in the Gas Industry," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 106, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
    10. Y.F. Chan, Kenny & M.S. Lee, Stephen, 2001. "An exact iterated bootstrap algorithm for small-sample bias reduction," Computational Statistics & Data Analysis, Elsevier, vol. 36(1), pages 1-13, March.
    11. Hu, Jin-Li & Lio, Mon-Chi & Yeh, Fang-Yu & Lin, Cheng-Hsun, 2011. "Environment-adjusted regional energy efficiency in Taiwan," Applied Energy, Elsevier, vol. 88(8), pages 2893-2899, August.
    12. Tsolas, Ioannis E., 2011. "Performance assessment of mining operations using nonparametric production analysis: A bootstrapping approach in DEA," Resources Policy, Elsevier, vol. 36(2), pages 159-167, June.
    13. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    14. Henryson, Jessica & Hakansson, Teresa & Pyrko, Jurek, 2000. "Energy efficiency in buildings through information - Swedish perspective," Energy Policy, Elsevier, vol. 28(3), pages 169-180, March.
    15. Zhou, P. & Ang, B.W. & Zhou, D.Q., 2012. "Measuring economy-wide energy efficiency performance: A parametric frontier approach," Applied Energy, Elsevier, vol. 90(1), pages 196-200.
    16. Matthias Staat, 2006. "Efficiency of hospitals in Germany: a DEA-bootstrap approach," Applied Economics, Taylor & Francis Journals, vol. 38(19), pages 2255-2263.
    17. Pardo, Nicolás & Moya, José Antonio & Mercier, Arnaud, 2011. "Prospective on the energy efficiency and CO2 emissions in the EU cement industry," Energy, Elsevier, vol. 36(5), pages 3244-3254.
    18. Ang, B.W., 2006. "Monitoring changes in economy-wide energy efficiency: From energy-GDP ratio to composite efficiency index," Energy Policy, Elsevier, vol. 34(5), pages 574-582, March.
    19. Léopold Simar & Paul W. Wilson, 1998. "Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models," Management Science, INFORMS, vol. 44(1), pages 49-61, January.
    20. Léopold Simar & Paul Wilson, 1999. "Of Course We Can Bootstrap DEA Scores! But Does It Mean Anything? Logic Trumps Wishful Thinking," Journal of Productivity Analysis, Springer, vol. 11(1), pages 93-97, February.
    21. Markovic, Dragan & Cvetkovic, Dragan & Masic, Branislav, 2011. "Survey of software tools for energy efficiency in a community," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 4897-4903.
    22. Tone, Kaoru, 2002. "A slacks-based measure of super-efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 143(1), pages 32-41, November.
    23. Wang, Ke & Wei, Yi-Ming & Zhang, Xian, 2013. "Energy and emissions efficiency patterns of Chinese regions: A multi-directional efficiency analysis," Applied Energy, Elsevier, vol. 104(C), pages 105-116.
    24. Manan, Zainuddin Abdul & Shiun, Lim Jeng & Alwi, Sharifah Rafidah Wan & Hashim, Haslenda & Kannan, K.S. & Mokhtar, Norhasliza & Ismail, Ahmad Zairin, 2010. "Energy Efficiency Award system in Malaysia for energy sustainability," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(8), pages 2279-2289, October.
    25. Hepbasli, Arif & Utlu, Zafer, 2004. "Evaluating the energy utilization efficiency of Turkey's renewable energy sources during 2001," Renewable and Sustainable Energy Reviews, Elsevier, vol. 8(3), pages 237-255, June.
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