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Comparing Economics, Environmental Pollution and Health Efficiency in China

Author

Listed:
  • Zhen Shi

    (Business School, Hohai University, Nanjing 211100, China
    School of Business Administration, Hohai University, Changzhou 213022, China)

  • Fengping Wu

    (Business School, Hohai University, Nanjing 211100, China)

  • Huinan Huang

    (School of Business Administration, Hohai University, Changzhou 213022, China)

  • Xinrui Sun

    (School of Business Administration, Hohai University, Changzhou 213022, China)

  • Lina Zhang

    (School of Business Administration, Hohai University, Changzhou 213022, China)

Abstract

As the modern economy develops rapidly, environmental pollution and human health have also been threatened. In recent years, relevant research has focused on subjects such as energy and economic, environmental pollution and health issues. Yet this has not considered the use of water resources and the impact of wastewater pollutant emissions on the economy and health. This article has combined the following factors like water consumption with wastewater discharge, pollutant concentration in sewage and local medical care expenditure and put them into the model of water resources, energy and health measurement, and a two-stage dynamic data envelopment analysis (DEA) model considering undesirable outputs is applied to 30 provinces (including autonomous regions and municipalities) to calculate the total efficiency, production efficiency and health efficiency in 2014–2017.The results show that the total efficiency values of most provinces are between 0.2 and 0.4, providing large room for improvement. Production efficiency and health efficiency have increased in recent years, but the health efficiency values of most provinces are still so low that they have dragged back the overall efficiency. The key impact indicators of different provinces are different, and each province should formulate different policies according to its own specific conditions so as to purposefully to deepen the energy, economic and medical reforms in each province, and also to promote sustainable economic development while improving health efficiency.

Suggested Citation

  • Zhen Shi & Fengping Wu & Huinan Huang & Xinrui Sun & Lina Zhang, 2019. "Comparing Economics, Environmental Pollution and Health Efficiency in China," IJERPH, MDPI, vol. 16(23), pages 1-30, December.
  • Handle: RePEc:gam:jijerp:v:16:y:2019:i:23:p:4827-:d:292803
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    as
    1. Muhammad Shahbaz & Smile Dube & Ilhan Ozturk & Abdul Jalil, 2015. "Testing the Environmental Kuznets Curve Hypothesis in Portugal," International Journal of Energy Economics and Policy, Econjournals, vol. 5(2), pages 475-481.
    2. Choi, Yongrok & Zhang, Ning & Zhou, P., 2012. "Efficiency and abatement costs of energy-related CO2 emissions in China: A slacks-based efficiency measure," Applied Energy, Elsevier, vol. 98(C), pages 198-208.
    3. Tone, Kaoru & Tsutsui, Miki, 2009. "Network DEA: A slacks-based measure approach," European Journal of Operational Research, Elsevier, vol. 197(1), pages 243-252, August.
    4. 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.
    5. Kaoru Tone & Miki Tsutsui, 2014. "Slacks-Based Network DEA," International Series in Operations Research & Management Science, in: Wade D. Cook & Joe Zhu (ed.), Data Envelopment Analysis, edition 127, chapter 0, pages 231-259, Springer.
    6. Kyriaki Remoundou & Phoebe Koundouri, 2009. "Environmental Effects on Public Health: An Economic Perspective," IJERPH, MDPI, vol. 6(8), pages 1-19, July.
    7. Al-Mulali, Usama & Saboori, Behnaz & Ozturk, Ilhan, 2015. "Investigating the environmental Kuznets curve hypothesis in Vietnam," Energy Policy, Elsevier, vol. 76(C), pages 123-131.
    8. Guo, Xiaoying & Lu, Ching-Cheng & Lee, Jen-Hui & Chiu, Yung-Ho, 2017. "Applying the dynamic DEA model to evaluate the energy efficiency of OECD countries and China," Energy, Elsevier, vol. 134(C), pages 392-399.
    9. Emil Georgiev & Emil Mihaylov, 2015. "Economic growth and the environment: reassessing the environmental Kuznets Curve for air pollution emissions in OECD countries," Letters in Spatial and Resource Sciences, Springer, vol. 8(1), pages 29-47, March.
    10. Sun, Chuanwang & Yuan, Xiang & Yao, Xin, 2016. "Social acceptance towards the air pollution in China: Evidence from public's willingness to pay for smog mitigation," Energy Policy, Elsevier, vol. 92(C), pages 313-324.
    11. Benhong Peng & Yue Li & Guo Wei & Ehsan Elahi, 2018. "Temporal and Spatial Differentiations in Environmental Governance," IJERPH, MDPI, vol. 15(10), pages 1-14, October.
    12. Li, Lan-Bing & Hu, Jin-Li, 2012. "Ecological total-factor energy efficiency of regions in China," Energy Policy, Elsevier, vol. 46(C), pages 216-224.
    13. Zhang, Ning & Zhou, P. & Choi, Yongrok, 2013. "Energy efficiency, CO2 emission performance and technology gaps in fossil fuel electricity generation in Korea: A meta-frontier non-radial directional distance functionanalysis," Energy Policy, Elsevier, vol. 56(C), pages 653-662.
    14. Xiaosheng Li & Xia Yan & Qingxian An & Ke Chen & Zhen Shen, 2016. "The coordination between China’s economic growth and environmental emission from the Environmental Kuznets Curve viewpoint," 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. 83(1), pages 233-252, August.
    15. Tone, Kaoru & Tsutsui, Miki, 2010. "Dynamic DEA: A slacks-based measure approach," Omega, Elsevier, vol. 38(3-4), pages 145-156, June.
    16. Fare, Rolf & Grosskopf, Shawna & Pasurka, Carl Jr., 2007. "Pollution abatement activities and traditional productivity," Ecological Economics, Elsevier, vol. 62(3-4), pages 673-682, May.
    17. Wang, H. & Ang, B.W. & Su, Bin, 2017. "Assessing drivers of economy-wide energy use and emissions: IDA versus SDA," Energy Policy, Elsevier, vol. 107(C), pages 585-599.
    18. 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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    3. Shu Wang & Jipeng Pei & Kuo Zhang & Dawei Gong & Karlis Rokpelnis & Weicheng Yang & Xiao Yu, 2022. "Does Individuals’ Perception of Wastewater Pollution Decrease Their Self-Rated Health? Evidence from China," IJERPH, MDPI, vol. 19(12), pages 1-18, June.

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