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Two-Stage Super-Efficiency Slacks-Based Model to Assess China’s Ecological Wellbeing

Author

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  • Jundong Hou

    (School of Economics & Management, China University of Geosciences, Wuhan 430074, China)

  • Xinxin Ruan

    (School of Economics & Management, China University of Geosciences, Wuhan 430074, China)

  • Jun Lv

    (School of Economics & Management, China University of Geosciences, Wuhan 430074, China)

  • Haixiang Guo

    (School of Economics & Management, China University of Geosciences, Wuhan 430074, China)

Abstract

As industrialization and urbanization in China have significantly increased ecological problems such as environmental pollution and resource waste, it has become important to be able to comprehensively assess ecological wellbeing performance (EWP) when seeking high-quality human wellbeing and economic growth within specific ecological limits. Therefore, to explore the EWP spatial and temporal distribution characteristics, this paper established an evaluation index system that considers ecological economic efficiency and economic welfare efficiency from input and output perspectives. The EWPs in 30 Chinese provinces (autonomous regions, municipalities) from 2006 to 2017 were then measured using a two-stage super-efficiency slacks-based model (Super-SBM) and data envelopment analysis (DEA) window analysis method. It was found that: (1) the average EWP value in the Chinese provinces was relatively low at 0.698, with the highest EWP in Beijing, Hainan, and Shanghai and the lowest in Xinjiang, Ningxia, and Qinghai; (2) the average provincial EWP fluctuated from 2006 to 2017 with a “decline-rise-decline-rise” feature; (3) China’s EWP value was spatially supported by the quadrangular “Beijing-Shanghai-Hainan-Sichuan” pole and continued to radiate to areas along these lines. These research findings provide theoretical insights and practical implications for regional ecological protection and human welfare improvements in China.

Suggested Citation

  • Jundong Hou & Xinxin Ruan & Jun Lv & Haixiang Guo, 2020. "Two-Stage Super-Efficiency Slacks-Based Model to Assess China’s Ecological Wellbeing," IJERPH, MDPI, vol. 17(19), pages 1-19, September.
  • Handle: RePEc:gam:jijerp:v:17:y:2020:i:19:p:7045-:d:420035
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    References listed on IDEAS

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    1. Jundong Hou & Jun Lv & Xin Chen & Shiwei Yu, 2016. "China’s regional social vulnerability to geological disasters: evaluation and spatial characteristics analysis," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 84(1), pages 97-111, November.
    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. Tone, Kaoru & Tsutsui, Miki, 2010. "Dynamic DEA: A slacks-based measure approach," Omega, Elsevier, vol. 38(3-4), pages 145-156, June.
    4. Jorgenson, Andrew K. & Alekseyko, Alina & Giedraitis, Vincentas, 2014. "Energy consumption, human well-being and economic development in central and eastern European nations: A cautionary tale of sustainability," Energy Policy, Elsevier, vol. 66(C), pages 419-427.
    5. Ruut Veenhoven, 1995. "World Database of Happiness," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 34(3), pages 299-313, March.
    6. Daly, Herman E, 1974. "The Economics of the Steady State," American Economic Review, American Economic Association, vol. 64(2), pages 15-21, May.
    7. Common, Mick, 2007. "Measuring national economic performance without using prices," Ecological Economics, Elsevier, vol. 64(1), pages 92-102, October.
    8. Moran, Daniel D. & Wackernagel, Mathis & Kitzes, Justin A. & Goldfinger, Steven H. & Boutaud, Aurelien, 2008. "Measuring sustainable development -- Nation by nation," Ecological Economics, Elsevier, vol. 64(3), pages 470-474, January.
    9. Michael Redclift, 2005. "Sustainable development (1987-2005): an oxymoron comes of age," Sustainable Development, John Wiley & Sons, Ltd., vol. 13(4), pages 212-227.
    10. Li, Zhi & Ouyang, Xiaoling & Du, Kerui & Zhao, Yang, 2017. "Does government transparency contribute to improved eco-efficiency performance? An empirical study of 262 cities in China," Energy Policy, Elsevier, vol. 110(C), pages 79-89.
    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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    Cited by:

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