TY - JOUR
T1 - The short-term impact of congestion taxes on ridesourcing demand and traffic congestion
T2 - Evidence from Chicago
AU - Liang, Yuan
AU - Yu, Bingjie
AU - Zhang, Xiaojian
AU - Lu, Yi
AU - Yang, Linchuan
PY - 2023/6
Y1 - 2023/6
N2 - 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. © 2023 Elsevier Ltd
AB - 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. © 2023 Elsevier Ltd
KW - Congestion tax
KW - Regulation
KW - Ride-hailing
KW - Ridesourcing
KW - Traffic congestion
KW - Transportation network company
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UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85151697804&origin=recordpage
U2 - 10.1016/j.tra.2023.103661
DO - 10.1016/j.tra.2023.103661
M3 - RGC 21 - Publication in refereed journal
SN - 0965-8564
VL - 172
JO - Transportation Research Part A: Policy and Practice
JF - Transportation Research Part A: Policy and Practice
M1 - 103661
ER -