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Gender Wage Gap in Online Gig Economy and Gender Differences in Job Preferences

Author

Listed:
  • Chen Liang

    (Department of Information Systems, W.P. Carey School of Business, Arizona State University, USA)

  • Yili Hong

    (Department of Information Systems, W.P. Carey School of Business, Arizona State University, USA)

  • Bin Gu

    (Department of Information Systems, W.P. Carey School of Business, Arizona State University, USA)

  • Jing Peng

    (Department of Operations and Information Management (OPIM), School of Business, University of Connecticut, USA)

Abstract

We explore whether there is a gender wage gap in the gig economy and examine to what degree gender differences in job application strategy could account for the gap. With a large-scale dataset from a leading online labor market, we show that females only earn around 81.4% of the hourly wage of their male counterparts. We further investigate three main aspects of job application strategy, namely bid timing, job selection, and avoidance of monitoring. After matching males with females using the propensity score matching method, we find that females tend to bid later and prefer jobs with a lower budget. In particular, the observed gender difference in bid timing can explain 7.6% of the difference in hourly wage, which could account for 41% of the gender wage gap (i.e. 18.6%) observed by us. Moreover, taking advantage of a natural experiment wherein the platform rolled out the monitoring system, we find that females are less willing to bid for monitored jobs than males. To further quantify the economic value of the gender difference in avoidance of monitoring, we run a field experiment on Amazon Mechanical Turk (AMT), which suggests that females tend to have a higher willingness to pay (WTP) for the avoidance of monitoring. The gender difference in WTP for the avoidance of monitoring can explain 8.1% of the difference in hourly wage, namely, 44% of the observed gender wage gap. Overall, our study reveals the important role of job application strategies in the persistent gender wage gap.

Suggested Citation

  • 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.
  • Handle: RePEc:net:wpaper:1803
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    References listed on IDEAS

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    Cited by:

    1. Ariela MICHA & Cecilia POGGI & Francisca PEREYRA, 2022. "Gender inequalities in the platform economy: The cases of delivery and private passenger transport services in the Buenos Aires Metropolitan Area," Working Paper 438e22d3-239e-468a-b317-b, Agence française de développement.
    2. Fabian Stephany & Otto Kassi & Uma Rani & Vili Lehdonvirta, 2021. "Online Labour Index 2020: New ways to measure the world's remote freelancing market," Papers 2105.09148, arXiv.org, revised Jun 2021.

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    More about this item

    Keywords

    gender wage gap; job application strategy; gig economy; quasi-natural experiment;
    All these keywords.

    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
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution

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