The Gender Earnings Gap in the Gig Economy: Evidence from over a Million Rideshare Drivers

Cody Cook, Rebecca Diamond, Jonathan Hall, John List and Paul Oyer ()

No 24732, NBER Working Papers from National Bureau of Economic Research, Inc

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.

JEL-codes: J16 J31 (search for similar items in EconPapers)
Date: 2018-06
New Economics Papers: this item is included in nep-hrm, nep-lab and nep-tre
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Citations: View citations in EconPapers (65)

Published as Cody Cook & Rebecca Diamond & Jonathan V Hall & John A List & Paul Oyer, 2021. "The Gender Earnings Gap in the Gig Economy: Evidence from over a Million Rideshare Drivers," The Review of Economic Studies, vol 88(5), pages 2210-2238.

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Related works:
Journal Article: The Gender Earnings Gap in the Gig Economy: Evidence from over a Million Rideshare Drivers (2021)
Working Paper: The Gender Earnings Gap in the Gig Economy: Evidence from over a Million Rideshare Drivers (2018)
Working Paper: The Gender Earnings Gap in the Gig Economy: Evidence from over a Million Rideshare Drivers (2018)
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