Understanding the Heterogeneity in the Effect of Driving Restriction Policies on Air Quality: Evidence from Chinese Cities

Many cities around the world have adopted driving restriction policies to reduce vehicle emissions. However, evidence on the effectiveness of these policies is mixed. I exploit detailed and comprehensive data on Chinese cities to conduct a large-scale study of the effectiveness of a variety of driving restriction policies in a variety of locations. I estimate the monitor-specific short-run treatment effects of each driving restriction policy using a regression discontinuity in time approach, and the average treatment effect using a panel fixed-effect approach. The regression discontinuity in time estimation results show strong heterogeneity. Among the eight measures of air quality used, CO, NO2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$NO_2$$\end{document}, PM2.5, PM10, and AQI respond most to driving restriction policies. The average reduction of CO and NO2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$NO_2$$\end{document} are consistent with back-of-the-envelope calculations for policies that effectively limit vehicle use. Using detailed information on the design of each policy, I show that policy details and pollution concentration are the major factors that affect the actual and estimated effects of driving restriction policies, and also a potential explanation for earlier studies that showed driving restriction policies had little effect.