Working Paper: NBER ID: w24732
Authors: Cody Cook; Rebecca Diamond; Jonathan Hall; John A. List; Paul Oyer
Abstract: 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 completely explain this gap and show that it 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 within-week 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.
Keywords: gender earnings gap; gig economy; rideshare drivers; Uber
JEL Codes: J16; J31
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Men's location and time preferences (J29) | Men's earnings (J31) |
| Experience on the platform (C90) | Men's earnings (J31) |
| Driving speed (R48) | Men's earnings (J31) |
| Experience on the platform (C90) | Gender earnings gap (J31) |
| Men's driving speed (R48) | Gender earnings gap (J31) |
| Location and time preferences, Experience on the platform, Driving speed (R41) | Gender earnings gap (J31) |