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

Author

Listed:
  • Cook, Cody

    (Uber Technologies, Inc)

  • Diamond, Rebecca

    (Stanford University)

  • Hall, Jonathan

    (Uber Technologies, Inc)

  • List, John A.

    (University of Chicago)

  • Oyer, Paul

    (Stanford University)

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 amongst 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

  • Cook, Cody & Diamond, Rebecca & Hall, Jonathan & List, John A. & Oyer, Paul, 2018. "The Gender Earnings Gap in the Gig Economy: Evidence from over a Million Rideshare Drivers," Research Papers repec:ecl:stabus:3637, Stanford University, Graduate School of Business.
    • Handle: RePEc:ecl:stabus:repec:ecl:stabus:3637
    as

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    References listed on IDEAS

    as
    1. Andreas Leibbrandt & John A. List, 2015. "Do Women Avoid Salary Negotiations? Evidence from a Large-Scale Natural Field Experiment," Management Science, INFORMS, vol. 61(9), pages 2016-2024, September.
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    6. Ghazala Azmat & Rosa Ferrer Zarzuela, 2012. "Gender gaps in performance: Evidence from young lawyers," Economics Working Papers 1300, Department of Economics and Business, Universitat Pompeu Fabra, revised Oct 2015.
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    9. Nabanita Datta Gupta & Donna S. Rothstein, 2005. "The Impact of Worker and Establishment‐level Characteristics on Male–Female Wage Differentials: Evidence from Danish Matched Employee–Employer Data," LABOUR, CEIS, vol. 19(1), pages 1-34, March.
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    11. Jeffrey A. Flory & Andreas Leibbrandt & John A. List, 2015. "Do Competitive Workplaces Deter Female Workers? A Large-Scale Natural Field Experiment on Job Entry Decisions," Review of Economic Studies, Oxford University Press, vol. 82(1), pages 122-155.
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    Cited by:

    1. Bharat K. Chandar & Ali Hortaçsu & John A. List & Ian Muir & Jeffrey M. Wooldridge, 2019. "Design and Analysis of Cluster-Randomized Field Experiments in Panel Data Settings," NBER Working Papers 26389, National Bureau of Economic Research, Inc.
    2. 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.
    3. Yang Pan & LiangFei Qiu, 2018. "Is Uber Helping or Hurting Mass Transit? An Empirical Investigation," Working Papers 18-11, NET Institute.
    4. Abel, Martin, 2019. "Do Workers Discriminate against Female Bosses?," IZA Discussion Papers 12611, Institute of Labor Economics (IZA).
    5. Yana Gallen, 2018. "Motherhood and the Gender Productivity Gap," Working Papers 2018-091, Human Capital and Economic Opportunity Working Group.
    6. 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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