Date of Award

2019

Document Type

Thesis

Degree Name

Bachelor of Arts

Department

Economics

First Advisor

Monica Das

Abstract

This research explores the effects of Uber entry on New York City’s traffic. The two major questions I am trying to answer that might be of vital importance to transportation authorities are 1) does Uber substitute public transits? 2) does an introduce of Uber slow down average travel speed? After Uber was first introduced in year 2009, there are continuous debates on distinguishing its impact on traffic (Rayle et al., 2014; Li et al., 2016; Schaller, 2018; Castiglione et al., 2018). Considering that Uber is relatively new, relevant traffic data such as congestion indices are in general unavailable, which appears as a common limitation in previous analysis. In this research, I use monthly number of public transit trips in NYC to estimate a substitution effect of Uber on public transit ridership. To measure its direct impact on road traffic, I use Average Travel Speed generated from NYC yellow cab trips as a proxy for the citywide Average Travel Speed. A further application of monthly number of vehicles crossing nine major bridges and tunnels is used to capture a trend of traffic volume in NYC. The final dataset comprises 133 observations range from January 2008 to January 2018. Perceiving that Uber was introduced to NYC on May 2011 and was suspended on issuance of new vehicle licenses starting from August 2018, I use a regression discontinuity (RD) design and set the two events as cutoff points in the model. Additional use of Google Trend helps to more precisely determine the cutoff point. The regression results suggest that after Uber was introduced to NYC, 1) number of public transit trips has increased by about 3%; 2) average travel speed has decreased by .127 mph; and 3) traffic volume was not affected.

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