About
I am a Data Scientist at Uber Technologies, where I research the economic behavior of drivers. I work on projects regarding driver structural and realtime pricing, developing algorithms and experimental designs to optimize these separate pricing policies.
With Keith Chen of UCLA, I have studied the reaction of driver supply to unanticipated short-term variation in earnings; our current working paper discusses behavior heuristics such as "income-targeting" and the role they play in the supply of labor.
Working Papers
Dynamic Pricing in a Labor Market: Surge Pricing and Flexible Work on the Uber Platform
Joint with Keith Chen
Last Edited: 12/11/2015
This paper studies how the dynamic pricing of tasks in the “gig” economy influences the supply of labor. In this paper, we study how driver-partners on the Uber platform respond to the dynamic pricing of trips, known as “surge” pricing. In contrast to income-target findings, we find that Uber partners drive more at times when earnings are high, and flexibly adjust to drive more at high surge times. A discontinuity design confirms that these effects are causal, and that surge pricing significantly increases the supply of rides on the Uber system.
Income Targeting and the Ridesharing Market
Last Edited: 02/18/2016
This paper examines the supply elasticity of individual contractors in the ridesharing market. Contrary to the results of Camerer et. al (1997) and the "income targeting" hypothesis, this study demonstrates substantial evidence of positive labor supply elasticities. Furthermore, the paper discusses the nature of measurement error in labor markets and how its presence can severely bias results downward.