The growth of the “gig” economy generates worker flexibility that, some have speculated, will favor women. We explore this by examining labor supply choices and earnings among more than a million rideshare drivers on Uber in the U.S. We document a roughly 7% gender earnings gap amongst drivers. We show that this gap can be entirely attributed to three factors: experience on the platform (learning-by-doing), preferences over where to work (driven largely by where drivers live and, to a lesser extent, safety), and preferences for driving speed. We do not find that men and women are differentially affected by a taste for specific hours, a return to withinweek work intensity, or customer discrimination. Our results suggest that there is no reason to expect the “gig” economy to close gender differences. Even in the absence of discrimination and in flexible labor markets, women’s relatively high opportunity cost of non-paid-work time and gender-based differences in preferences and constraints can sustain a gender pay gap.Flexible work through apps like Uber has some features that should narrow the gender pay gap: there are no convex returns to long hours and earnings are determined by a gender-blind formula without negotiation. However, this paper documents an average hourly earnings gap of 7 percent between male and female Uber drivers in the US. Three factors completely explain this gap. Because drivers improve with experience on the platform, the fact that the average male driver is more experienced than the average female driver explains one third of the pay gap. Men’s slightly higher driving speed — a 2.2% difference — further explains one half of the gap. The remainder of the gap is explained by men driving in locations with higher surge and shorter wait times.
Cody Cook, Rebecca Diamond, Jonathan Hall, John A. List, Paul Oyer
Economics and Market Design