Disruption on the Streets: A Case Study on the Impact of Uber’s Entry on the Taxi Business

52 Pages Posted: 16 Mar 2022

See all articles by SunAh Kim

SunAh Kim

University of New South Wales (UNSW)

Pradeep K. Chintagunta

University of Chicago

Jia Li

Wake Forest University

Date Written: March 7, 2022


The disruptive effects of the sharing economy have received considerable attention from the press, researchers and policymakers. We empirically study whether and to what extent the entry of ridesharing programs (e.g., Uber) in a city changes the outcomes and behaviors of taxi drivers in that city. Using unique data that contain high frequency GPS and trip information from all taxis in a Chinese city, we examine the impact of Uber’s entry on taxi drivers’ work output and input behaviors, and importantly, their earnings. We use a “regression discontinuity in time” approach based on the temporal discontinuity in treatment (i.e., Uber entry date), and leverage high-frequency outcome data along with an extensive set of trend and control variables. We find that taxi drivers’ hourly earnings decreased by 6% after Uber entry. This net effect reflects the entry itself, as well as drivers’ responses to it. We show that a reduced number of trips accounts for the taxi drivers’ decreasing income. Further, we find that fulfilled trip distances are shorter after Uber entry, implying that trip characteristics have changed. Additionally, after Uber’s entry, taxi drivers take shorter driving paths for trips that have similar pick-up and drop-off locations as those before entry. We observe differences in the effects of Uber entry on taxi drivers’ behaviors between self-employed drivers (“entrepreneurial small businesses”) and fleet drivers. The former tend to respond differently to Uber entry by searching over longer distances for their next passengers, thereby mitigating the income lost due to the entry. We also find that trips after entry focus more on “parks and outdoor recreation areas” rather than on “tourism-related” locations. In terms of input factors, we find that taxi drivers increase their geographic coverage in the city to find passengers. We check the robustness of our results to various assumptions.

Keywords: Uber, Sharing Economy, Taxi, Regression Discontinuity in Time, Quasi-Experiment

Suggested Citation

Kim, SunAh and Chintagunta, Pradeep K. and Li, Jia, Disruption on the Streets: A Case Study on the Impact of Uber’s Entry on the Taxi Business (March 7, 2022). Available at SSRN: https://ssrn.com/abstract=4051063 or http://dx.doi.org/10.2139/ssrn.4051063

SunAh Kim (Contact Author)

University of New South Wales (UNSW) ( email )

High St
Sydney, NSW 2052

Pradeep K. Chintagunta

University of Chicago ( email )

5807 S. Woodlawn Avenue
Chicago, IL 60637
United States
773-702-8015 (Phone)
773-702-0458 (Fax)

Jia Li

Wake Forest University

1834 Wake Forest Road
Winston-Salem, NC 27109
United States

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