Abstract
Climate change is a challenge for all of humanity. Should financial be environmentally responsible? This paper uses the Toda–Yamamoto test and the extended Fourier Toda–Yamamoto test re-examine the relationship between financial development and environmental quality in 31 provinces and municipalities in China during the period 2000–2018. We find that financial development in certain regions has effectively reduced the concentration of PM2.5, which indicates that it has a significantly positive effect on environmental quality, though with regional differences. After considering structural shifts, the relationship between financial development and environmental improvement is found to be significant in more regions, indicating that China has undergone structural shifts in these aspects. The aforementioned conclusions are also supported by further robustness tests. China can consequently utilize the positive impact of finance for advocating carbon emission reduction and improving environment quality, therefore contributing to the response to global climate change.
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The data can be available upon request.
Notes
The data for 2019 and 2020 are affected by the epidemic; hence, the analysis sample only includes data before 2018.
By setting different fitting parameters, the goodness of fit of the fitting curve to the index reaches over 0.5.
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This work was supported by Youth Foundation of Social Science and Humanity, China Ministry of Education (20YJC790133).
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All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Yiguo Chen, Peng Luo, Teng Tong, and Jing Wang. The first draft of the manuscript was written by Yiguo Chen and all authors commented on previous versions of the manuscript. Tsangyao Chang revised it critically for important intellectual content. All authors read and approved the final manuscript.
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Chen, Y., Luo, P., Tong, T. et al. Revisit causal nexus between financial development and environmental quality in China: a structural shift panel data analysis. Environ Sci Pollut Res 29, 89969–89985 (2022). https://doi.org/10.1007/s11356-022-21684-y
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DOI: https://doi.org/10.1007/s11356-022-21684-y