The gender wage gap (i.e., women receiving less than men for equivalent work) in traditional labor markets has been attributed in part to a motherhood penalty and to women having a preference of job flexibility. There is preliminary evidence suggesting there is also a gender wage gap in the gig economy. If so, it poses a puzzle to the extent that neither the motherhood penalty nor flexibility preference explanations are readily applicable to the online gig economy. This Doctoral Dissertation Improvement Grant research seeks to confirm the existence of the gender wage gap in the online gig economy and explore a potential supply side explanation: that the gap arises due to differences in job application strategies between men and women resulting from differences in expectations. If differences in expectations are responsible for the gap, a possible solution is to provide bidders with accurate information. This project will ascertain whether this is the case.
Gender differences in job application strategies will be studied using proprietary data from a major online labor market platform. Two differences in beliefs will be explored: one arising from a difference in beliefs regarding expected wages or costs and the other arising from a difference in the perceived uncertainty of expected wages or costs. To identify which difference in beliefs is at work, the research will combine results from a large-scale survey of labor market expectations with an information experiment in which expectations will be systematically manipulated. Overall, this project can provide insights on how information policy may reduce or eliminate expectation biases and therefore narrow the gender wage gap.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
