The haven paradise hypothesis has been widely supported in the international carbon transfer, but there is still a lack of inter-city evidence. The emergence of the digital economy in recent years has introduced unprecedented opportunities and challenges for carbon emissions reduction and carbon transfer. As the world’s largest carbon emitter and a major player in the digital economy, exploring whether the pollution haven hypothesis exists among cities in China and how the digital economy affects inter-city carbon transfer is crucial for countries to optimize their domestic carbon reduction structures. To this end, this paper employs the 2012 and 2015 Chinese Urban Household Survey data alongside input-output tables based on the life cycle assessment method to quantify the inter-city carbon transfer. In addition, the impact and mechanisms of the digital economy on inter-city carbon transfer are explored using the two-way fixed effects model. The results show that 54% of Chinese cities’ carbon emissions come from outside, with third-tier cities bearing high carbon transfer pressures, indicating the presence of the pollution haven hypothesis. The digital economy exacerbates inter-city carbon transfer by promoting market integration and facilitating industrial transfer, and it mainly promotes the transfer of high-intensity carbon emissions to third-tier cities. Considering carbon emission reduction targets, mandatory environmental regulations have strengthened the effect of the digital economy on carbon transfer. Therefore, the Chinese government needs to properly address carbon transfer by improving the collaborative carbon reduction system, enhancing carbon emission reduction efficiency, and accelerating the equitable progress of the digital economy.
CITATION STYLE
Luan, B., Yang, H., Zou, H., & Yu, X. (2023). The impact of the digital economy on inter-city carbon transfer in China using the life cycle assessment model. Humanities and Social Sciences Communications, 10(1). https://doi.org/10.1057/s41599-023-02100-3
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