Investigating the influence of the new ride-hailing policy on air quality using regression discontinuity design

With the increase of the number of ride-hailing, the traffic congestion and environmentalpollution has exacerbated. A new ride-hailing policy was formed as a means of administrative control to improve the negative externality. However, the improvement of air quality caused by the new ride-hailing policy has not been effectively verified. This study employed regression discontinuity design (RDD) to explore the causal relationship between the air quality in Beijing and the new ride-hailing policy to reduce the endogeneity problems. The main results show that the implementation of the new policy reduces air quality index (AQI), particulate matter 10(PM 10 ), and ozone(O 3 ) by 14%, 12%, and 16%, respectively in the OLS regression analysis. After applying the RDD, this study found that the implementation of the new policy reduced AQI, PM 10 , and O 3 by 43%, 30%, and 42%. The regression value of regression discontinuity was higher than that of OLS. Additionally, the robustness test reveals that RDD is reasonable. The findings suggest that the implementation of the new ride-hailing policy exerts an improvement effect on air quality. Policy implications to further promote the new ride-hailing policy are hence discussed.