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

Author

Listed:
  • Cody Cook
  • Rebecca Diamond
  • Jonathan Hall
  • John List
  • Paul Oyer

Abstract

The growth of the "gig" economy generates worker flexibility that, some have speculated, will favor women. We explore one facet of the gig economy by examining labor supply choices and earnings among more than a million rideshare drivers on Uber in the U.S. Perhaps most surprisingly, we find that there is a roughly 7% gender earnings gap among drivers. The uniqueness of our data - knowing exactly the production and compensation functions - permits us to completely unpack the underlying determinants of the gender earnings gap. We find that the entire gender gap is caused by three factors: experience on the platform (learning-by-doing), preferences over where/when to work, and preferences for driving speed. This suggests that, as the gig economy grows and brings more flexibility in employment, women's relatively high opportunity cost of non-paid-work time and gender-based preference differences can perpetuate a gender earnings gap even in the absence of discrimination.

Suggested Citation

  • Cody Cook & Rebecca Diamond & Jonathan Hall & John List & Paul Oyer, 2018. "The Gender Earnings Gap in the Gig Economy: Evidence from over a Million Rideshare Drivers," Natural Field Experiments 00634, The Field Experiments Website.
  • Handle: RePEc:feb:natura:00634
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    References listed on IDEAS

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    Cited by:

    1. Basil Halperin & Benjamin Ho & John List & Ian Muir, 2018. "Toward an understanding of the economics of apologies: evidence from a large-scale natural field experiment," Natural Field Experiments 00644, The Field Experiments Website.
    2. Yang Pan & LiangFei Qiu, 2018. "Is Uber Helping or Hurting Mass Transit? An Empirical Investigation," Working Papers 18-11, NET Institute.
    3. Yana Gallen, 2018. "Motherhood and the Gender Productivity Gap," Working Papers 2018-091, Human Capital and Economic Opportunity Working Group.
    4. Chen Liang & Yili Hong & Bin Gu & Jing Peng, 2018. "Gender Wage Gap in Online Gig Economy and Gender Differences in Job Preferences," Working Papers 18-03, NET Institute.

    More about this item

    JEL classification:

    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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