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Is the Ecological and Environmental Protection Supervision Policy a Response to Promote Residents’ Health? An Empirical Study Based on Double Machine Learning

Author

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  • Baiyang Zhang

    (School of Science, Jiangsu University of Science and Technology, Zhenjiang 212100, China)

  • Mengyu Wang

    (School of Humanities and Social Sciences, Jiangsu University of Science and Technology, Zhenjiang 212100, China)

  • Bingnan Guo

    (School of Humanities and Social Sciences, Jiangsu University of Science and Technology, Zhenjiang 212100, China)

Abstract

Residents’ health is the foundation of social civilization and progress, an important symbol of national prosperity and strength, and a common pursuit of the general public. Ecological environment quality, as a key link connecting sustainable development and residents’ health, its governance effect is directly related to the achievement of Sustainable Development Goals. Based on the data of 31 provinces in China from 2010 to 2022, this paper empirically tests the impact of the ecological and environmental protection supervision policy (EEPS) on residents’ health by adopting the double machine learning method. The research results show that (1) the ecological and environmental protection supervision policy can significantly improve residents’ health level, laying a solid human capital foundation for sustainable development. (2) In contrast, the policy has a more prominent effect in areas with low population density, regions where government attention is below the median, and areas with relatively weak economic development. (3) The policy can enhance residents’ health through the synergistic effect of government environmental investment and public environmental participation. This study strengthens the research on how environmental policies promote residents’ health and provides valuable references for advancing sustainable development.

Suggested Citation

  • Baiyang Zhang & Mengyu Wang & Bingnan Guo, 2025. "Is the Ecological and Environmental Protection Supervision Policy a Response to Promote Residents’ Health? An Empirical Study Based on Double Machine Learning," Sustainability, MDPI, vol. 17(24), pages 1-25, December.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:24:p:11014-:d:1813810
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