Evaluating Urban Transportation Policies.

• Author: Barwick, Panle Jia

Traffic congestion poses a significant challenge in urban centers, especially in fast-growing emerging economies where rapid urbanization and increased travel demand have outpaced road infrastructure and regulations. Longer travel times and worsened air quality resulting from congestion hinder mobility and urban development while reducing the overall quality of life. In the 2018 TomTom Traffic Index, which is based on realtime GPS traffic data from 403 cities in 56 countries, the 10 most congested cities were all in developing and emerging economies. In these cities, commuters spent over 200 hours of extra travel time per year relative to when transport was flowing freely.

Local governments have implemented a range of policies to address traffic congestion, targeting both the demand and supply sides of road infrastructure. On the demand side, policies encompass command-and-control style driving restrictions, vehicle purchase quota systems, and market-based congestion pricing. On the supply side, efforts have been made to expand public transit options and to enhance road capacity.

This summary describes our research on the impact of various urban transportation policies aimed at alleviating traffic congestion and air pollution. We focus on measuring crucial quantities, including the marginal external cost of traffic congestion, and evaluating different policies in terms of both efficiency and equity within an integrated framework. Much of our analysis focuses on Beijing. With a population of over 21 million, the city has consistently ranked among the most congested in the world. Its municipal government has implemented aggressive demand-side and supply-side policies over the past 15 years, making it an ideal setting for studying urban transportation policies.

Estimating the Marginal External Cost of Congestion

Economic theory indicates that the optimal congestion charge is equal to the marginal external cost of congestion (MECC) at the socially optimal level of traffic. The MECC critically hinges on the incremental effect of traffic density on traffic speed: how much an additional vehicle on the road slows down the traffic. Empirical estimation of the density-speed relationship is subject to the endogeneity challenge, as speed and density affect each other and both are equilibrium outcomes influenced by idiosyncrasies. Our study provides, to our knowledge, the first causal estimate of the density-speed relationship by leveraging plausibly exogenous variations in traffic introduced by Beijing's driving restriction policy. (1)

There are six circumferential or "ring" roads around central Beijing. Government policy prohibits certain vehicles from driving within the fifth ring road from 7 am to 8 pm during workdays. There is a predetermined rotation schedule based on the last digit of a vehicle's license plate. There are days for numbers 1 and 6, 2 and 7, 3 and 8, 4 and 9, and 5 and 0. Due to the nonuniform distribution of the last digit of license plate numbers, the policy exogenously shifts the number of vehicles on the road. Notably, vehicles with license plates ending in the number 4 constitute only about 2 percent of all vehicles due to Chinese cultural aversion to the number 4. Consequently, on...