ORIGINAL RESEARCH article
Front. Public Health
Sec. Environmental Health and Exposome
Volume 12 – 2024 |
doi: 10.3389/fpubh.2024.1415309
Provisionally accepted
- 1
Institute of big data, Zhongnan University of Economics and Law, Wuhan, China - 2
School of Mathematics and Statistics,, Zhongnan University of Economics and Law, Wuhan, China
The final, formatted version of the article will be published soon.
Horizontal ecological compensation (HEC) has the potential to incentivize inclusive green growth in cities. Using the multi-stage difference-in-differences (DID) method, this study examines the impact of HEC policies as a quasi-natural experiment. Panel data are analyzed; the data pertain to 87 cities in the Yangtze River Basin, from 2007 to 2020. The findings indicate that HEC policies significantly contribute to inclusive green growth, with consistent effects across different estimators. The moderating effect test reveals that urban industrial pollution levels and green innovation are key pathways through which HEC policies influence inclusive green growth. Further analysis shows that the positive impact of HEC is more pronounced in watersheds with high marketization and in downstream regions, suggesting that HEC may exacerbate regional disparities in inclusive green growth. This study offers insights for China and also for other developing countries seeking to promote urban inclusive green growth and achieve sustainable development goals.
Keywords:
horizontal ecological compensation, Ecological compensation, Inclusive green growth, Inequitable environment, Green development
Received:
10 Apr 2024;
Accepted:
14 Aug 2024.
Copyright:
© 2024 Wang, LI, Xiao and Wang. This is an
open-access article distributed under the terms of the
Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted,
provided the original author(s) or licensor are credited and that the
original publication in this journal is cited, in accordance with accepted
academic practice. No use, distribution or reproduction is permitted which
does not comply with these terms.
* Correspondence:
Hengli Wang, Institute of big data, Zhongnan University of Economics and Law, Wuhan, China
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