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Industry-level Total-factor Energy Efficiency in Developed Countries

Author

Listed:
  • Satoshi Honma

    (Faculty of Economics, Kyushu Sangyo University)

  • Jin-Li Hu

    (Institute of Business and Management, National Chiao Tung University)

Abstract

This study computes and analyzes the total-factor energy efficiency (TFEE) of 11 industries in 14 developed countries during the period of 1995-2005 using the data envelopment analysis (DEA) approach. There are four inputs: labor, capital stock, intermediate inputs other than energy, and energy. The value added is the only output. The most inefficient industry is the metal industry, which has an average TFEE of 40.6%. Australia is the most inefficient country, with the lowest weighted TFEE in every year except for 1996 and 1998. The most efficient countries are the United States from 1995 to 1998, Denmark from 1999 to 2002, and Netherlands from 2003 to 2005. Given that the number of efficient industries decreases over time, it is clear that most industries have room to improve their energy efficiency as time goes by. Moreover, based on the total-factor framework, this study finds no support for the convergence of energy efficiency levels.

Suggested Citation

  • Satoshi Honma & Jin-Li Hu, 2011. "Industry-level Total-factor Energy Efficiency in Developed Countries," Discussion Papers 51, Kyushu Sangyo University, Faculty of Economics.
    • Handle: RePEc:kyu:dpaper:51
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    File URL: http://www.ip.kyusan-u.ac.jp/keizai-kiyo/dp51.pdf
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    References listed on IDEAS

    as
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    Citations

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    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.
    2. Makridou, Georgia & Andriosopoulos, Kostas & Doumpos, Michael & Zopounidis, Constantin, 2016. "Measuring the efficiency of energy-intensive industries across European countries," Energy Policy, Elsevier, vol. 88(C), pages 573-583.
    3. Honma, Satoshi & Hu, Jin-Li, 2014. "A panel data parametric frontier technique for measuring total-factor energy efficiency: An application to Japanese regions," Energy, Elsevier, vol. 78(C), pages 732-739.
    4. Jin‐Li Hu & Satoshi Honma & Yu‐Kai Chen, 2021. "Total‐Factor Energy and Emission Efficiencies of ASEAN and Other Asian Economies," Asian Economic Policy Review, Japan Center for Economic Research, vol. 16(1), pages 92-112, January.
    5. Lina Sineviciene & Iryna Sotnyk & Oleksandr Kubatko, 2017. "Determinants of energy efficiency and energy consumption of Eastern Europe post-communist economies," Energy & Environment, , vol. 28(8), pages 870-884, December.
    6. Nela Vlahinic Lenz & Alemka egota & Dario Maradin, 2018. "Total-factor Energy Efficiency in EU: Do Environmental Impacts Matter?," International Journal of Energy Economics and Policy, Econjournals, vol. 8(3), pages 92-96.
    7. Satoshi Honma & Jin-Li Hu, 2018. "A meta-stochastic frontier analysis for energy efficiency of regions in Japan," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 7(1), pages 1-16, December.

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    More about this item

    Keywords

    Data envelopment analysis (DEA); Total-factor energy efficiency; Industry-level analysis;
    All these keywords.

    JEL classification:

    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q30 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - General
    • Q32 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Exhaustible Resources and Economic Development

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