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Valuation of Water Resource Green Efficiency Based on SBM–TOBIT Panel Model: Case Study from Henan Province, China

Author

Listed:
  • Yiru Guo

    () (School of Management, Wuhan University of Technology, Luoshi Road No. 122, Wuhan 430070, China)

  • Yan Hu

    () (School of Management, Wuhan University of Technology, Luoshi Road No. 122, Wuhan 430070, China)

  • Ke Shi

    () (School of Public Policy & Management, Zhengzhou University, Kexue Road NO. 101, Zhengzhou 450001, China)

  • Yuriy Bilan

    () (Institute of Management, University of Social Sciences, 9 Sienkiewicza St., 90-113 Lodz, Poland)

Abstract

With progress in China’s industrialization and urbanization, the contradiction of social and economic development with water resource supply–demand and water environmental pollution becomes increasingly prominent. To cope with the dual constraints of resource shortage and environmental regulations, the concept of water resource green efficiency that considers economic, environmental, and ecological factors is highly involved to promote sustainable economic development. The theoretical and practice circle devote to scientific green efficiency assessment of water resources and effective recognition of relevant influencing factors. However, to an extent they neglect social benefits brought by sustainable development and possible influences of industrial restructuring on green efficiency. They also lack concern on green efficiency of water resources in inland arid areas. To offset the disadvantages of existing studies, the philosophy of sustainable development was integrated into the input–output assessment system of green efficiency of water resources, and an assessment model was constructed using the SBM–Tobit (slack-based measure and Tobit) method. Moreover, a case study based on Henan Province, China was carried out. The green efficiencies of water resources in 18 cities of Henan Province during 2011–2018 were calculated. The operation mechanism of relevant influencing factors was discussed, and the methods to improve green efficiency of water resources were determined. Results reveal that the sustainable green efficiency of water resources in Henan Province increased in fluctuation during 2011–2018. The mean green efficiency increased from 0.425 in 2011 to 0.498 in 2018. At present, green efficiency of water resources in Henan Province remains at a low level, with a mean of 0.504. Reducing water consumption intensity and increasing investment to water environmental pollution technologies can promote green efficiency of water resources significantly. Conclusions provide a new method for scientific measurement and green efficiency assessment of water resources in inland arid areas.

Suggested Citation

  • 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 1-17, August.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:17:p:6944-:d:404423
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    References listed on IDEAS

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    1. Ching‐Hsun Chang, 2018. "How to Enhance Green Service and Green Product Innovation Performance? The Roles of Inward and Outward Capabilities," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 25(4), pages 411-425, July.
    2. 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.
    3. Jintao Lu & Licheng Ren & Siqin Yao & Dan Rong & Marinko Skare & Justas Streimikis, 2020. "Renewable energy barriers and coping strategies: Evidence from the Baltic States," Sustainable Development, John Wiley & Sons, Ltd., vol. 28(1), pages 352-367, January.
    4. Tone, Kaoru & Tsutsui, Miki, 2010. "Dynamic DEA: A slacks-based measure approach," Omega, Elsevier, vol. 38(3-4), pages 145-156, June.
    5. Omezzine, Abdallah & Zaibet, Lokman, 1998. "Management of modern irrigation systems in oman: allocative vs. irrigation efficiency," Agricultural Water Management, Elsevier, vol. 37(2), pages 99-107, July.
    6. Xianguo Li & Qian Zhang, 2015. "AHP-based resources and environment efficiency evaluation index system construction about the west side of Taiwan Straits," Annals of Operations Research, Springer, vol. 228(1), pages 97-111, May.
    7. Yande Gong & Joe Zhu & Ya Chen & Wade D. Cook, 2018. "DEA as a tool for auditing: application to Chinese manufacturing industry with parallel network structures," Annals of Operations Research, Springer, vol. 263(1), pages 247-269, April.
    8. Zhou, Yuanchun & Ma, Mengdie & Gao, Peiqi & Xu, Qiming & Bi, Jun & Naren, Tuya, 2019. "Managing water resources from the energy - water nexus perspective under a changing climate: A case study of Jiangsu province, China," Energy Policy, Elsevier, vol. 126(C), pages 380-390.
    9. 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 1-16, April.
    10. Bao, Chao & Fang, Chuang-lin, 2007. "Water resources constraint force on urbanization in water deficient regions: A case study of the Hexi Corridor, arid area of NW China," Ecological Economics, Elsevier, vol. 62(3-4), pages 508-517, May.
    11. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
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    More about this item

    Keywords

    green efficiency of water resources; undesirable output; slack-based measure and data envelopment analysis; Tobit regression model;
    All these keywords.

    JEL classification:

    • Q - Agricultural and Natural Resource Economics; Environmental and Ecological Economics
    • Q0 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General
    • Q2 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation
    • Q3 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation
    • Q5 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics
    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products

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