Doctoral Dissertation Research in DRMS: Expectation Bias and the Gender Wage Gap in the Online Gig Economy

性别工资差距（即，妇女在传统劳动力市场上的收入低于男子（从事同等工作的妇女收入低于男子），部分原因是母亲的惩罚和妇女更喜欢工作的灵活性。 初步证据表明，零工经济中也存在性别工资差距。如果是这样的话，这就构成了一个难题，即无论是母性惩罚还是灵活性偏好的解释都不适用于在线零工经济。这项博士论文改进补助金研究旨在确认在线零工经济中存在性别工资差距，并探索潜在的供给侧解释：差距是由于男女之间的期望差异导致的求职策略差异而产生的。如果期望的差异是造成差距的原因，一个可能的解决办法是向投标人提供准确的信息。该项目将确定情况是否如此，并将利用来自一个主要在线劳动力市场平台的专有数据，研究求职策略中的性别差异。两个信念的差异将被探讨：一个是由于对预期工资或成本的信念不同而产生的，另一个是由于预期工资或成本的不确定性不同而产生的。为了确定是哪种信念差异在起作用，该研究将联合收割机的劳动力市场预期的大规模调查结果与信息实验相结合，在实验中，预期将被系统地操纵。总的来说，这个项目可以提供关于信息政策如何减少或消除期望偏差的见解，从而缩小性别工资差距。这个奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估来支持。

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.