The Short-term Impact of Congestion Taxes on Ridesourcing Demand and Traffic Congestion: Evidence from Chicago

TL;DR

This study empirically evaluates Chicago's congestion tax policy, finding it significantly reduces ridesourcing demand especially for short trips, while only marginally alleviating traffic congestion, with results robust across various models.

Contribution

It provides the first causal evidence on the short-term effects of congestion taxes on ridesourcing demand and traffic congestion, highlighting heterogeneity based on trip distances.

Findings

Congestion tax significantly reduces overall ridesourcing demand.

Traffic congestion is only marginally alleviated by the policy.

Short-distance trips are more affected by the congestion tax.

Abstract

Ridesourcing is popular in many cities. Despite its theoretical benefits, a large body of studies have claimed that ridesourcing also brings (negative) externalities (e.g., inducing trips and aggravating traffic congestion). Therefore, many cities are planning to enact or have already enacted policies to regulate its use. However, these policies' effectiveness or impact on ridesourcing demand and traffic congestion is uncertain. To this end, this study applies difference-in-differences (i.e., a regression-based causal inference approach) to empirically evaluate the effects of the congestion tax policy on ridesourcing demand and traffic congestion in Chicago. It shows that this congestion tax policy significantly curtails overall ridesourcing demand but marginally alleviates traffic congestion. The results are robust to the choice of time windows and data sets, additional control variables, alternative model specifications, alternative control groups, and alternative modeling approaches (i.e., regression discontinuity in time). Moreover, considerable heterogeneity exists. For example, the policy notably reduces ridesourcing demand with short travel distances, but such an impact is gradually attenuated as the distance increases.