NBER Working Papers and Publications
|September 2017||Uber vs. Taxi: A Driver’s Eye View|
with Joshua D. Angrist, Sydnee Caldwell: w23891
Ride-hailing drivers pay a proportion of their fares to the ride-hailing platform operator, a commission-based compensation model used by many internet-mediated service providers. To Uber drivers, this commission is known as the Uber fee. By contrast, traditional taxi drivers in most US cities make a fixed payment independent of their earnings, usually a weekly or daily medallion lease, but keep every fare dollar net of expenses. We assess these compensation models from a driver’s point of view using an experiment that offered random samples of Boston Uber drivers opportunities to lease a virtual taxi medallion that eliminates the Uber fee. Some drivers were offered a negative fee. Drivers’ labor supply response to our offers reveals a large intertemporal substitution elasticity, on the or...
|November 2016||An Analysis of the Labor Market for Uber’s Driver-Partners in the United States|
with Alan B. Krueger: w22843
Uber, the ride-sharing company launched in 2010, has grown at an exponential rate. This paper provides the first comprehensive analysis of the labor market for Uber’s driver-partners, based on both survey and administrative data. Drivers who partner with Uber appear to be attracted to the platform largely because of the flexibility it offers, the level of compensation, and the fact that earnings per hour do not vary much with the number of hours worked. Uber’s driver-partners are more similar in terms of their age and education to the general workforce than to taxi drivers and chauffeurs. Most of Uber’s driver-partners had full- or part-time employment prior to joining Uber, and many continued in those positions after starting to drive with the Uber platform, which makes the flexibility t...
|September 2016||Using Big Data to Estimate Consumer Surplus: The Case of Uber|
with Peter Cohen, Robert Hahn, Steven Levitt, Robert Metcalfe: w22627
Estimating consumer surplus is challenging because it requires identification of the entire demand curve. We rely on Uber’s “surge” pricing algorithm and the richness of its individual level data to first estimate demand elasticities at several points along the demand curve. We then use these elasticity estimates to estimate consumer surplus. Using almost 50 million individual-level observations and a regression discontinuity design, we estimate that in 2015 the UberX service generated about $2.9 billion in consumer surplus in the four U.S. cities included in our analysis. For each dollar spent by consumers, about $1.60 of consumer surplus is generated. Back-of-the-envelope calculations suggest that the overall consumer surplus generated by the UberX service in the United States in 2015...