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Energy-environmental efficiency and optimal restructuring of the global economy

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  • Vaninsky, Alexander

Abstract

The primary objective of this study is to investigate the opportunities for economic restructuring, resulting in an optimal increase in the energy-environmental efficiency of the global economy. A novel stochastic data envelopment analysis with a perfect object method (SDEA PO) constitutes the methodology of the research. We equip SDEA PO with the projected gradient of the efficiency score. We employ the indicators of the gross domestic product (GDP) and carbon dioxide emissions (CO2) as output and undesirable output, respectively, and population and clean energy consumption as input and undesirable input, respectively. By using the SDEA PO, we obtain a group efficiency score for the global economy; the projected gradient identifies the direction of optimal economic restructuring. The indicator-wise components of the projected gradient determine locally optimal changes in the shares of each economy, serving particular goals. We use a factor analysis technique to aggregate them into one factor vector that determines the multicriteria optimal structural change. The factor vector determines the redistribution of the GDP, clean energy consumption, CO2 emissions, and population, leading to the maximum possible increase in the energy-environmental efficiency. The suggested approach may be used as a tool for decision-making in a variety of two-tier economic systems.

Suggested Citation

  • Vaninsky, Alexander, 2018. "Energy-environmental efficiency and optimal restructuring of the global economy," Energy, Elsevier, vol. 153(C), pages 338-348.
  • Handle: RePEc:eee:energy:v:153:y:2018:i:c:p:338-348
    DOI: 10.1016/j.energy.2018.03.063
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    References listed on IDEAS

    as
    1. Leopold Simar & Paul Wilson, 2000. "A general methodology for bootstrapping in non-parametric frontier models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(6), pages 779-802.
    2. Dieter Gstach, 1998. "Another Approach to Data Envelopment Analysis in Noisy Environments: DEA+," Journal of Productivity Analysis, Springer, vol. 9(2), pages 161-176, March.
    3. de la Rue du Can, Stephane & Price, Lynn & Zwickel, Timm, 2015. "Understanding the full climate change impact of energy consumption and mitigation at the end-use level: A proposed methodology for allocating indirect carbon dioxide emissions," Applied Energy, Elsevier, vol. 159(C), pages 548-559.
    4. Beltrán-Esteve, Mercedes & Picazo-Tadeo, Andrés J., 2017. "Assessing environmental performance in the European Union: Eco-innovation versus catching-up," Energy Policy, Elsevier, vol. 104(C), pages 240-252.
    5. repec:spr:envpol:v:19:y:2017:i:4:d:10.1007_s10018-016-0172-3 is not listed on IDEAS
    6. William Cooper & Zhimin Huang & Vedran Lelas & Susan Li & Ole Olesen, 1998. "Chance Constrained Programming Formulations for Stochastic Characterizations of Efficiency and Dominance in DEA," Journal of Productivity Analysis, Springer, vol. 9(1), pages 53-79, January.
    7. Wade D. Cook & Joe Zhu, 2006. "Incorporating Multiprocess Performance Standards into the DEA Framework," Operations Research, INFORMS, vol. 54(4), pages 656-665, August.
    8. repec:eee:rensus:v:82:y:2018:i:p2:p:1813-1822 is not listed on IDEAS
    9. Apergis, Nicholas & Aye, Goodness C. & Barros, Carlos Pestana & Gupta, Rangan & Wanke, Peter, 2015. "Energy efficiency of selected OECD countries: A slacks based model with undesirable outputs," Energy Economics, Elsevier, vol. 51(C), pages 45-53.
    10. repec:eee:energy:v:134:y:2017:i:c:p:991-1000 is not listed on IDEAS
    11. O. B. Olesen & N. C. Petersen, 1995. "Chance Constrained Efficiency Evaluation," Management Science, INFORMS, vol. 41(3), pages 442-457, March.
    12. repec:spr:envpol:v:19:y:2017:i:4:d:10.1007_s10018-016-0168-z is not listed on IDEAS
    13. repec:eee:energy:v:134:y:2017:i:c:p:392-399 is not listed on IDEAS
    14. Jati K Sengupta, 2000. "Dynamic and Stochastic Efficiency Analysis:Economics of Data Envelopment Analysis," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 4385.
    15. Yanni Yu & Yongrok Choi, 2015. "Measuring Environmental Performance Under Regional Heterogeneity in China: A Metafrontier Efficiency Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 46(3), pages 375-388, October.
    16. William W. Cooper & Kyung Sam Park & Gang Yu, 1999. "IDEA and AR-IDEA: Models for Dealing with Imprecise Data in DEA," Management Science, INFORMS, vol. 45(4), pages 597-607, April.
    17. Kao, Chiang, 2006. "Interval efficiency measures in data envelopment analysis with imprecise data," European Journal of Operational Research, Elsevier, vol. 174(2), pages 1087-1099, October.
    18. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    19. Thanassoulis, E. & Dyson, R. G., 1992. "Estimating preferred target input-output levels using data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 56(1), pages 80-97, January.
    20. W. Liu & W. Meng & X. Li & D. Zhang, 2010. "DEA models with undesirable inputs and outputs," Annals of Operations Research, Springer, vol. 173(1), pages 177-194, January.
    21. Huang, Zhimin & Li, Susan X., 1996. "Dominance stochastic models in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 95(2), pages 390-403, December.
    22. repec:eee:energy:v:134:y:2017:i:c:p:659-671 is not listed on IDEAS
    23. repec:spr:jecstr:v:6:y:2017:i:1:d:10.1186_s40008-017-0076-9 is not listed on IDEAS
    24. repec:pal:jorsoc:v:53:y:2002:i:12:d:10.1057_palgrave.jors.2601433 is not listed on IDEAS
    25. Thore, Sten, 1987. "Chance-constrained activity analysis," European Journal of Operational Research, Elsevier, vol. 30(3), pages 267-269, June.
    26. Despotis, Dimitris K. & Smirlis, Yiannis G., 2002. "Data envelopment analysis with imprecise data," European Journal of Operational Research, Elsevier, vol. 140(1), pages 24-36, July.
    27. 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.
    28. repec:taf:applec:v:50:y:2018:i:4:p:335-353 is not listed on IDEAS
    29. Seiford, Lawrence M. & Zhu, Joe, 2002. "Modeling undesirable factors in efficiency evaluation," European Journal of Operational Research, Elsevier, vol. 142(1), pages 16-20, October.
    30. repec:spr:jecstr:v:6:y:2017:i:1:d:10.1186_s40008-017-0073-z is not listed on IDEAS
    31. repec:eee:jeeman:v:88:y:2018:i:c:p:35-68 is not listed on IDEAS
    32. Kumbhakar,Subal C. & Lovell,C. A. Knox, 2003. "Stochastic Frontier Analysis," Cambridge Books, Cambridge University Press, number 9780521666633.
    33. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "Measuring environmental performance under different environmental DEA technologies," Energy Economics, Elsevier, vol. 30(1), pages 1-14, January.
    34. Maital, Shlomo & Vaninsky, Alexander, 1999. "Data envelopment analysis with a single DMU: A graphic projected-gradient approach," European Journal of Operational Research, Elsevier, vol. 115(3), pages 518-528, June.
    35. Rajiv D. Banker, 1993. "Maximum Likelihood, Consistency and Data Envelopment Analysis: A Statistical Foundation," Management Science, INFORMS, vol. 39(10), pages 1265-1273, October.
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    3. repec:eee:energy:v:161:y:2018:i:c:p:725-736 is not listed on IDEAS

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