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Total-Factor Energy Efficiency and Its Extensions: Introduction, Computation and Application

In: Data Envelopment Analysis

Author

Listed:
  • Jin-Li Hu

    (National Chiao Tung University)

  • Tzu-Pu Chang

    (National Yunlin University of Science and Technology)

Abstract

This chapter demonstrates how to use different types of DEA models to compute the total-factor energy efficiency (TFEE) scores, including CCR, Russell, QFI, SBM, DF, and DDF models. The TFEE is a disaggregate input efficiency index. Moreover, the TFEE framework which uses cross-section data can be extended to the total-factor energy productivity (TFEP) growth index by following Malmquist, Leunberger, and Malmquist-Leunberger models which use panel data. Finally, the regional data of Chinese regions during 2010–2011 with inputs and desirable as well as undesirable outputs are used for illustrating the computation of TFEE and TFEP scores.

Suggested Citation

  • Jin-Li Hu & Tzu-Pu Chang, 2016. "Total-Factor Energy Efficiency and Its Extensions: Introduction, Computation and Application," International Series in Operations Research & Management Science, in: Joe Zhu (ed.), Data Envelopment Analysis, chapter 0, pages 45-69, Springer.
    • Handle: RePEc:spr:isochp:978-1-4899-7684-0_3
    DOI: 10.1007/978-1-4899-7684-0_3
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    Citations

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    Cited by:

    1. Yang Li & An-Chi Liu & Shu-Mei Wang & Yiting Zhan & Jingran Chen & Hsiao-Fen Hsiao, 2022. "A Study of Total-Factor Energy Efficiency for Regional Sustainable Development in China: An Application of Bootstrapped DEA and Clustering Approach," Energies, MDPI, vol. 15(9), pages 1-13, April.
    2. Wen-Ling Hsiao & Jin-Li Hu & Chan Hsiao & Ming-Chung Chang, 2018. "Energy Efficiency of the Baltic Sea Countries: An Application of Stochastic Frontier Analysis," Energies, MDPI, vol. 12(1), pages 1-11, December.
    3. Chang-Tai Lee & Jin-Li Hu & Ming-Hsin Kung, 2022. "Economic Resilience in the Early Stage of the COVID-19 Pandemic: An Across-Economy Comparison," Sustainability, MDPI, vol. 14(8), pages 1-25, April.
    4. Ya Chen & Wade D. Cook & Juan Du & Hanhui Hu & Joe Zhu, 2017. "Bounded and discrete data and Likert scales in data envelopment analysis: application to regional energy efficiency in China," Annals of Operations Research, Springer, vol. 255(1), pages 347-366, August.
    5. Kuo-Feng Wu & Jin-Li Hu & Hawjeng Chiou, 2021. "Degrees of Shortage and Uncovered Ratios for Long-Term Care in Taiwan’s Regions: Evidence from Dynamic DEA," IJERPH, MDPI, vol. 18(2), pages 1-17, January.
    6. Jin-Li Hu & Min-Yueh Chuang & Shang-Ho Yeh, 2023. "A Dynamic DEA Analysis of Health Output Efficiencies of Cities and Counties in Taiwan," IJERPH, MDPI, vol. 20(6), pages 1-12, March.
    7. Lan-Bing Li & Cong-Cong Zhang & Jin-Li Hu & Ching-Ren Chiu, 2021. "Disaggregate productivity growth sources of regional industries in China," Empirical Economics, Springer, vol. 60(3), pages 1531-1557, March.
    8. Jin-Li Hu & Tzu-Pu Chang, 2021. "Evaluating the Context-Dependent Total-Factor Energy Efficiency of Counties and Cities in Taiwan," Energies, MDPI, vol. 14(15), pages 1-10, July.
    9. Hu, Jin-Li & Chang, Ming-Chung & Tsay, Hui-Wen, 2017. "The congestion total-factor energy efficiency of regions in Taiwan," Energy Policy, Elsevier, vol. 110(C), pages 710-718.
    10. Jin-Li Hu & Tien-Yu Chang, 2023. "Energy Resilience: A Cross-Economy Comparison," Energies, MDPI, vol. 16(5), pages 1-21, February.

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