IDEAS home Printed from https://ideas.repec.org/p/mos/moswps/2015-09.html
   My bibliography  Save this paper

A multicomponent DEA approach to measure the economic and energy efficiencies of OECD countries

Author

Listed:
  • Abbas Valadkhani
  • Israfil Roshdi
  • Russell Smyth

Abstract

We employ a multicomponent Data Envelopment Analysis (DEA) framework to examine the interplay between economic and energy efficiency for all 29 OECD countries and then classify each country into one of four categories in terms of their relative economic and energy efficiency. In addition to using a broader set of inputs and improved measure of labour compared with prior studies, we make a methodological contribution in that we develop a new complete multi-component DEA measure for examining the efficiency performance of individual countries. Our proposed measure provides an efficiency index, not only at the country level, but also decomposes overall efficiency into economic and energy components. The G7 countries display the worst performance, in terms of CO2 and energy efficiencies. For the sample as a whole, there is a positive and marginally significant relationship between economic efficiency and energy efficiency. This finding suggests that higher economic and energy efficiencies are not necessarily incompatible goals.

Suggested Citation

  • Abbas Valadkhani & Israfil Roshdi & Russell Smyth, 2015. "A multicomponent DEA approach to measure the economic and energy efficiencies of OECD countries," Monash Economics Working Papers 09-15, Monash University, Department of Economics.
  • Handle: RePEc:mos:moswps:2015-09
    as

    Download full text from publisher

    File URL: http://www.buseco.monash.edu.au/eco/research/papers/2015/0915deavaladkhaniroshdismyth.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Robert C. Feenstra & Robert Inklaar & Marcel P. Timmer, 2015. "The Next Generation of the Penn World Table," American Economic Review, American Economic Association, vol. 105(10), pages 3150-3182, October.
    2. Charles Blackorby & R. Russell, 1999. "Aggregation of Efficiency Indices," Journal of Productivity Analysis, Springer, vol. 12(1), pages 5-20, August.
    3. Silvia Albrizio & Tomasz Koźluk & Vera Zipperer, 2014. "Empirical Evidence on the Effects of Environmental Policy Stringency on Productivity Growth," OECD Economics Department Working Papers 1179, OECD Publishing.
    4. Apergis, Nicholas & Payne, James E., 2010. "The emissions, energy consumption, and growth nexus: Evidence from the commonwealth of independent states," Energy Policy, Elsevier, vol. 38(1), pages 650-655, January.
    5. Cinzia Daraio & Léopold Simar, 2005. "Introducing Environmental Variables in Nonparametric Frontier Models: a Probabilistic Approach," Journal of Productivity Analysis, Springer, vol. 24(1), pages 93-121, September.
    6. Coers, Robin & Sanders, Mark, 2013. "The energy–GDP nexus; addressing an old question with new methods," Energy Economics, Elsevier, vol. 36(C), pages 708-715.
    7. 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.
    8. Lorenzo Castelli & Raffaele Pesenti & Walter Ukovich, 2010. "A classification of DEA models when the internal structure of the Decision Making Units is considered," Annals of Operations Research, Springer, vol. 173(1), pages 207-235, January.
    9. Ewing, Bradley T. & Payne, James E. & Caporin, Massimilano, 2022. "The Asymmetric Impact of Oil Prices and Production on Drilling Rig Trajectory: A correction," Resources Policy, Elsevier, vol. 79(C).
    10. William Cooper & Kyung Park & Jesus Pastor, 1999. "RAM: A Range Adjusted Measure of Inefficiency for Use with Additive Models, and Relations to Other Models and Measures in DEA," Journal of Productivity Analysis, Springer, vol. 11(1), pages 5-42, February.
    11. Arouri, Mohamed El Hedi & Ben Youssef, Adel & M'henni, Hatem & Rault, Christophe, 2012. "Energy consumption, economic growth and CO2 emissions in Middle East and North African countries," Energy Policy, Elsevier, vol. 45(C), pages 342-349.
    12. Marta Aloi & Frederic Tournemaine, 2013. "Inequality, growth, and environmental quality trade‐offs in a model with human capital accumulation," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 46(3), pages 1123-1155, August.
    13. Baek, Jungho & Kim, Hyun Seok, 2013. "Is economic growth good or bad for the environment? Empirical evidence from Korea," Energy Economics, Elsevier, vol. 36(C), pages 744-749.
    14. Cook, Wade D. & Hababou, Moez, 2001. "Sales performance measurement in bank branches," Omega, Elsevier, vol. 29(4), pages 299-307, August.
    15. 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.
    16. Chien, Taichen & Hu, Jin-Li, 2007. "Renewable energy and macroeconomic efficiency of OECD and non-OECD economies," Energy Policy, Elsevier, vol. 35(7), pages 3606-3615, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Borozan, Djula, 2018. "Technical and total factor energy efficiency of European regions: A two-stage approach," Energy, Elsevier, vol. 152(C), pages 521-532.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Halkos, George & Tzeremes, Nickolaos, 2013. "Renewable energy consumption and economic efficiency: Evidence from European countries," MPRA Paper 44136, University Library of Munich, Germany.
    2. Jradi, Samah & Bouzdine Chameeva, Tatiana & Aparicio, Juan, 2019. "The measurement of revenue inefficiency over time: An additive perspective," Omega, Elsevier, vol. 83(C), pages 167-180.
    3. Tiba, Sofien & Omri, Anis, 2017. "Literature survey on the relationships between energy, environment and economic growth," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 1129-1146.
    4. Sofien, Tiba & Omri, Anis, 2016. "Literature survey on the relationships between energy variables, environment and economic growth," MPRA Paper 82555, University Library of Munich, Germany, revised 14 Sep 2016.
    5. Fukuyama, Hirofumi & Weber, William L., 2009. "A directional slacks-based measure of technical inefficiency," Socio-Economic Planning Sciences, Elsevier, vol. 43(4), pages 274-287, December.
    6. Kao, Chiang, 2014. "Network data envelopment analysis: A review," European Journal of Operational Research, Elsevier, vol. 239(1), pages 1-16.
    7. Daniel Armeanu & Georgeta Vintilă & Jean Vasile Andrei & Ştefan Cristian Gherghina & Mihaela Cristina Drăgoi & Cristian Teodor, 2018. "Exploring the link between environmental pollution and economic growth in EU-28 countries: Is there an environmental Kuznets curve?," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-28, May.
    8. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min, 2016. "Research fronts in data envelopment analysis," Omega, Elsevier, vol. 58(C), pages 33-45.
    9. Emrouznejad, Ali & De Witte, Kristof, 2010. "COOPER-framework: A unified process for non-parametric projects," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1573-1586, December.
    10. Ying Li & Yung-ho Chiu & Liang Chun Lu, 2019. "New Energy Development and Pollution Emissions in China," IJERPH, MDPI, vol. 16(10), pages 1-24, May.
    11. Meng, Fanyi & Su, Bin & Thomson, Elspeth & Zhou, Dequn & Zhou, P., 2016. "Measuring China’s regional energy and carbon emission efficiency with DEA models: A survey," Applied Energy, Elsevier, vol. 183(C), pages 1-21.
    12. Rita Shakouri & Maziar Salahi & Sohrab Kordrostami & Jie Wu, 2019. "Flexible measure in the presence of the partial input to output impacts process," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 29(3), pages 77-98.
    13. Cook, Wade D. & Green, Rodney H., 2004. "Multicomponent efficiency measurement and core business identification in multiplant firms: A DEA model," European Journal of Operational Research, Elsevier, vol. 157(3), pages 540-551, September.
    14. Bölük, Gülden & Mert, Mehmet, 2015. "The renewable energy, growth and environmental Kuznets curve in Turkey: An ARDL approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 587-595.
    15. Lorenzo Castelli & Raffaele Pesenti & Walter Ukovich, 2010. "A classification of DEA models when the internal structure of the Decision Making Units is considered," Annals of Operations Research, Springer, vol. 173(1), pages 207-235, January.
    16. Akther, Syed & Fukuyama, Hirofumi & Weber, William L., 2013. "Estimating two-stage network Slacks-based inefficiency: An application to Bangladesh banking," Omega, Elsevier, vol. 41(1), pages 88-96.
    17. Sueyoshi, Toshiyuki & Sekitani, Kazuyuki, 2009. "An occurrence of multiple projections in DEA-based measurement of technical efficiency: Theoretical comparison among DEA models from desirable properties," European Journal of Operational Research, Elsevier, vol. 196(2), pages 764-794, July.
    18. Aparicio, Juan & Borras, Fernando & Pastor, Jesus T. & Vidal, Fernando, 2013. "Accounting for slacks to measure and decompose revenue efficiency in the Spanish Designation of Origin wines with DEA," European Journal of Operational Research, Elsevier, vol. 231(2), pages 443-451.
    19. Yongqi Feng & Haolin Zhang & Yung-ho Chiu & Tzu-Han Chang, 2021. "Innovation efficiency and the impact of the institutional quality: a cross-country analysis using the two-stage meta-frontier dynamic network DEA model," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3091-3129, April.
    20. Feng Li & Qingyuan Zhu & Jun Zhuang, 2018. "Analysis of fire protection efficiency in the United States: a two-stage DEA-based approach," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(1), pages 23-68, January.

    More about this item

    Keywords

    Energy efficiency; CO2 emissions; Real GDP; Data envelopment analysis;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • O44 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Environment and Growth
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:mos:moswps:2015-09. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Simon Angus (email available below). General contact details of provider: https://edirc.repec.org/data/dxmonau.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.