Panacea or placebo? Exploring the causal effects of nonlocal vehicle driving restriction policies on traffic congestion using a difference-in-differences approach

Car dependence has been threatening transportation sustainability as it contributes to congestion and associated externalities. In response, various transport policies that restrict the use of private vehicles have been implemented. However, empirical evaluations of such policies’ effects on traffic congestion have been limited. To this end, we compile a fine spatiotemporal resolution data set of the floating vehicle-based traffic performance index to examine the effects of a recent nonlocal vehicle driving restriction policy in Shanghai, one of most populous cities in the world. Specifically, we explore whether and how the policy impacted traffic speeds in the short term by employing a quasi-experimental difference-in-differences modeling approach. We find that: (1) In the first month, the policy led to an increase of network-level traffic speeds by 1.47% (0.352 km/h) during evening peak hours (17:00–19:00) but had no significant effect during morning peak hours (7:00–9:00). (2) The policy also helped improve network-level traffic speeds during some unrestricted hours (6:00, 12:00, 14:00, and 20:00), although the impact was marginal. (3) The short-term effects of the policy exhibited heterogeneity across traffic analysis zones. The lower the density of metro stations, the greater the effects. We conclude that driving restrictions for non-local vehicles alone may not significantly reduce congestion, and their effects can differ both temporally and spatially. However, they can have potential positive side effects such as increased purchase and usage of new energy vehicles, owners of which can obtain a local license plate of Shanghai for free.