The empowerment of smart city construction on the synergy effect of pollution control and carbon reduce in China: Empirical analysis with double machine learning method
Neng Shen, Lin Zhang, Qunwei Wang
Abstract
Smart city development offers a novel solution to overcome the environmental challenges associated with conventional urban development models, thereby amplifying the synergy effect of pollution control and carbon reduction (SEPCCR). This study uses advanced double machine learning methods, analyzing panel data from 273 Chinese cities spanning 2006 to 2022 to explore the effects of smart city policy (SCP) on urban SEPCCR. The research reveals that SCP significantly enhances the SEPCCR, a conclusion that remains robust after a series test such as model replacements and addressing potential endogeneity issues. This study aims to elucidate the mechanisms through which SCP influences SEPCCR, illustrating that the policy can enhance the synergy effect by strengthening government modern governance, promoting intelligent development in enterprises, driving industrial upgrading, and guiding the public participation in green initiatives. Heterogeneity analysis shows that the promoting effects of SCP are more pronounced in cities in eastern region, large cities, cities with higher administrative levels, non-old industrial base cities, and cities with a focus on environmental protection, highlighting the necessity of tailored advancement of SCP. This research provides valuable insights to fortify smart city development endeavors, effectively enhance SEPCCR, and achieve future "dual-carbon" objectives.