The Impact of Urbanization on CO₂ Emissions in China: The Key Role of Foreign Direct Investment

ABSTRACT

By adopting the dynamic panel threshold approach, this study assesses how foreign direct investment (FDI) shapes the causality between urbanization and CO₂ emissions in China from 1996–2018. The results suggest that a rise in the pace of urbanization increases CO₂ emissions, but this harmful effect becomes weaker after achieving a certain level of foreign capital. We also find that the more developed the technology, financial and government sectors, the more it can promote urbanization to reduce CO₂ emissions. These results offer policy implications for China’s urban planning and environmental policy.

KEYWORDS:

• Urbanization
• CO₂ emissions
• FDI
• dynamic panel threshold model
• China

JEL:

• C33
• F21
• O13
• Q43
• Q53
• R11

Acknowledgments

The authors are grateful to the Editor and the anonymous referees for their highly constructive comments and suggestions that substantially improved the article.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplementary Material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/1540496X.2022.2106843

Notes

1. The detailed theoretical foundations are presented in the Supplementary Material A.

2. The detailed discussions are also presented in the Supplementary Material A.

3. For further specification of the IPAT identity and the STIRPAT model, please see the Supplementary Material C.

4. The detail classifications are listed in Table S2 in the Supplementary Material D.

5. Given that 2001 was a year of crucial importance to China’s economic revolution, we replicate the analysis for the sub-sample period after 2001, please see the Supplementary Material F.

6. The graphs of the threshold tests are in the top right and bottom panels of Figure S2.

Additional information

Funding

This paper is supported by the 111 Project “Innovation and Talents Base of Financial Security and Development” [grant number B18] and the Major Project of National Social Science Fund [grant number 22ZDA108].