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

33 Pages Posted: 9 Nov 2018

See all articles by Chen Liang

Chen Liang

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

Yili Hong

University of Houston - C.T. Bauer College of Business

Bin Gu

Boston University - Department of Management Information Systems

Jing Peng

University of Connecticut - Department of Operations & Information Management

Date Written: October 1, 2018

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.

Keywords: Gender Wage Gap, Job Application Strategy, Gig Economy, Quasi-Natural Experiment

Suggested Citation

Liang, Chen and Hong, Yili and Gu, Bin and Peng, Jing, Gender Wage Gap in Online Gig Economy and Gender Differences in Job Preferences (October 1, 2018). NET Institute Working Paper No. 18-03, Available at SSRN: https://ssrn.com/abstract=3266249 or http://dx.doi.org/10.2139/ssrn.3266249

Chen Liang (Contact Author)

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

Tempe, AZ
United States

Yili Hong

University of Houston - C.T. Bauer College of Business ( email )

Houston, TX 77204-6021
United States

Bin Gu

Boston University - Department of Management Information Systems ( email )

595 Commonwealth Avenue
Boston, MA 02215
United States

Jing Peng

University of Connecticut - Department of Operations & Information Management ( email )

368 Fairfield Road
Storrs, CT 06269-2041
United States

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