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Measuring Economic and Environmental Performance of Energy Resources in ISIC codes: Evidence from Iran’s Industry Sector

Author

Listed:
  • Payam Rashidi
  • Masoud Homayounifar
  • Taghi Ebrahimi Salari
  • Modjtaba Rouhani

Abstract

Recently, in accordance with global environmental conservation awareness, undesirable outputs of production and social activities (e.g., air pollutants) have harmful social and environmental dimensions especially in developing countries. Therefore, this study discusses how to apply Data Environment Analysis (DEA) for environmental assessment. However, previous DEA research has documented a limited use of DEA on environmental assessment. A unique feature of DEA-based environmental assessment is that it needs to classify outputs into desirable and undesirable outputs. On the other hand, there is a lack of literatures in field of measuring on economic and environmental energy efficiency between ISIC codes. Therefore, this paper measured the energy efficiency of Iran’s main ISIC sub sectors using non linear DEA approach. Results indicated that between studied ISIC codes, the codes 15 and 24 have most economic (0.97 and 1.00) and environmental (1.00 and 0.82) efficiency, respectively. Also, in comparison with the other studied ISIC codes, the code 23 is economically and environmentally inefficient (0.28 and 0.32).

Suggested Citation

  • Payam Rashidi & Masoud Homayounifar & Taghi Ebrahimi Salari & Modjtaba Rouhani, 2017. "Measuring Economic and Environmental Performance of Energy Resources in ISIC codes: Evidence from Iran’s Industry Sector," Modern Applied Science, Canadian Center of Science and Education, vol. 11(12), pages 109-109, December.
    • Handle: RePEc:ibn:masjnl:v:11:y:2017:i:12:p:109
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    References listed on IDEAS

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    1. Peng Zhou & Kim Leng Poh & Beng Wah Ang, 2016. "Data Envelopment Analysis for Measuring Environmental Performance," International Series in Operations Research & Management Science, in: Shiuh-Nan Hwang & Hsuan-Shih Lee & Joe Zhu (ed.), Handbook of Operations Analytics Using Data Envelopment Analysis, chapter 0, pages 31-49, Springer.
    2. Kumar Mandal, Sabuj & Madheswaran, S., 2010. "Environmental efficiency of the Indian cement industry: An interstate analysis," Energy Policy, Elsevier, vol. 38(2), pages 1108-1118, February.
    3. Jamasb, Tooraj & Nillesen, Paul & Pollitt, Michael, 2004. "Strategic behaviour under regulatory benchmarking," Energy Economics, Elsevier, vol. 26(5), pages 825-843, September.
    4. Zhou, P. & Ang, B.W. & Poh, K.L., 2006. "Decision analysis in energy and environmental modeling: An update," Energy, Elsevier, vol. 31(14), pages 2604-2622.
    5. Ang, B.W. & Zhang, F.Q., 2000. "A survey of index decomposition analysis in energy and environmental studies," Energy, Elsevier, vol. 25(12), pages 1149-1176.
    6. Sueyoshi, Toshiyuki & Goto, Mika & Ueno, Takahiro, 2010. "Performance analysis of US coal-fired power plants by measuring three DEA efficiencies," Energy Policy, Elsevier, vol. 38(4), pages 1675-1688, April.
    7. Zhou, P. & Ang, B.W. & Wang, H., 2012. "Energy and CO2 emission performance in electricity generation: A non-radial directional distance function approach," European Journal of Operational Research, Elsevier, vol. 221(3), pages 625-635.
    8. 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.
    9. Fare, R. & Grosskopf, S. & Hernandez-Sancho, F., 2004. "Environmental performance: an index number approach," Resource and Energy Economics, Elsevier, vol. 26(4), pages 343-352, December.
    10. Jebaraj, S. & Iniyan, S., 2006. "A review of energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 10(4), pages 281-311, August.
    11. Sueyoshi, Toshiyuki & Goto, Mika, 2010. "Should the US clean air act include CO2 emission control?: Examination by data envelopment analysis," Energy Policy, Elsevier, vol. 38(10), pages 5902-5911, October.
    12. Abbott, Malcolm, 2005. "Determining Levels of Productivity and Efficiency in the Electricity Industry," The Electricity Journal, Elsevier, vol. 18(9), pages 62-72, November.
    13. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2006. "Introduction to Data Envelopment Analysis and Its Uses," Springer Books, Springer, number 978-0-387-29122-2, March.
    14. Seiford, Lawrence M. & Thrall, Robert M., 1990. "Recent developments in DEA : The mathematical programming approach to frontier analysis," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 7-38.
    15. Huang, J.P. & Poh, K.L. & Ang, B.W., 1995. "Decision analysis in energy and environmental modeling," Energy, Elsevier, vol. 20(9), pages 843-855.
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    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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