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Total-Factor Energy Efficiency in China’s Agricultural Sector: Trends, Disparities and Potentials

Author

Listed:
  • Zhihai Yang

    () (College of Economics and Management, Huazhong Agricultural University, No. 1 Shizishan Street, Wuhan 430070, China
    These authors contributed equally to this work.)

  • Dong Wang

    () (UWA School of Agriculture and Environment, The University of Western Australia, M089, 35 Stirling Highway, Crawley, WA 6009, Australia
    Australia-China Sustainable Research and Development Center, Perth, WA 6009, Australia
    Inner Mongolia Honghe Energy and Environment Consultancy, Huhhot 010020, China
    These authors contributed equally to this work.)

  • Tianyi Du

    () (School of Business and Management, Murdoch University, 90 South Street, Murdoch, WA 6150, Australia
    Australia-China Sustainable Research and Development Center, Perth, WA 6009, Australia)

  • Anlu Zhang

    () (College of Land Management, Huazhong Agricultural University, No. 1 Shizishan Street, Wuhan 430070, China)

  • Yixiao Zhou

    () (School of Economics and Finance, Faculty of Business and Law, Curtin University, Rm 3016, Bldg 408, Bentley, Perth, WA 6004, Australia)

Abstract

This paper investigates total-factor energy efficiency and analyses the trends of the efficiency changes in China’s agricultural production across 30 provinces and three regions from 2001 to 2011, based on data envelopment analysis (DEA) approach. The potential amount of energy savings and five potential factors for energy efficiency improvement are also empirically studied by Tobit regression model. The findings show that (1) total-factor energy efficiency in China’s agricultural sector is increasing over years but performs heterogeneously across regions; (2) agriculture intensive regions and energy abundant provinces tend to be relatively energy inefficient in agricultural production; and (3) economic structure, agricultural production structure, technological progress and income effect are major potentials for improving energy efficiency, whereas energy price is not a significant factor. This phenomenon results from the divergence of economic development, endowment effects as well as the scale of agricultural production. Policy implications drawn from this research are to upgrade industrial structure and promote agricultural transformation to enhance farmers’ income as well as to establish a land market with entitling land property rights to farmers. This conclusion can assist to form more scientific rural energy policy decision-making in China and also can be extended to other developing economies for sustainable agriculture.

Suggested Citation

  • Zhihai Yang & Dong Wang & Tianyi Du & Anlu Zhang & Yixiao Zhou, 2018. "Total-Factor Energy Efficiency in China’s Agricultural Sector: Trends, Disparities and Potentials," Energies, MDPI, Open Access Journal, vol. 11(4), pages 1-1, April.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:4:p:853-:d:139707
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Chang, Ming-Chung, 2020. "An application of total-factor energy efficiency under the metafrontier framework," Energy Policy, Elsevier, vol. 142(C).
    2. Geng, Zhiqiang & Zeng, Rongfu & Han, Yongming & Zhong, Yanhua & Fu, Hua, 2019. "Energy efficiency evaluation and energy saving based on DEA integrated affinity propagation clustering: Case study of complex petrochemical industries," Energy, Elsevier, vol. 179(C), pages 863-875.
    3. Yiru Guo & Yan Hu & Ke Shi & Yuriy Bilan, 2020. "Valuation of Water Resource Green Efficiency Based on SBM–TOBIT Panel Model: Case Study from Henan Province, China," Sustainability, MDPI, Open Access Journal, vol. 12(17), pages 1-1, August.
    4. Jara Laso & Daniel Hoehn & María Margallo & Isabel García-Herrero & Laura Batlle-Bayer & Alba Bala & Pere Fullana-i-Palmer & Ian Vázquez-Rowe & Angel Irabien & Rubén Aldaco, 2018. "Assessing Energy and Environmental Efficiency of the Spanish Agri-Food System Using the LCA/DEA Methodology," Energies, MDPI, Open Access Journal, vol. 11(12), pages 1-1, December.
    5. Xiaoyang Zhou & Hao Chen & Hao Wang & Benjamin Lev & Lifang Quan, 2019. "Natural and Managerial Disposability Based DEA Model for China’s Regional Environmental Efficiency Assessment," Energies, MDPI, Open Access Journal, vol. 12(18), pages 1-1, September.
    6. Tao Yi & Ling Tong & Mohan Qiu & Jinpeng Liu, 2019. "Analysis of Driving Factors of Photovoltaic Power Generation Efficiency: A Case Study in China," Energies, MDPI, Open Access Journal, vol. 12(3), pages 1-1, January.

    More about this item

    Keywords

    energy efficiency; data envelopment analysis; agriculture transformation;

    JEL classification:

    • Q - Agricultural and Natural Resource Economics; Environmental and Ecological Economics
    • Q0 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy
    • Q49 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Other

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