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

DRMS 博士论文研究:在线零工经济中的期望偏差和性别工资差距

基本信息

  • 批准号:
    1824432
  • 负责人:
  • 金额:
    $ 1.59万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2018
  • 资助国家:
    美国
  • 起止时间:
    2018-07-01 至 2020-06-30
  • 项目状态:
    已结题

项目摘要

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.
传统劳动力市场中的性别工资差距(即同等工作下女性的工资低于男性)部分归因于母亲的惩罚和女性对工作灵活性的偏好。 有初步证据表明,零工经济中也存在性别工资差距。如果是这样,那么这就带来了一个谜题,即母性惩罚和灵活性偏好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证实在线零工经济中性别工资差距的存在,并探讨潜在的供给方解释:这种差距的产生是由于男女期望差异导致的工作申请策略差异造成的。如果期望差异是造成差距的原因,一个可能的解决方案是向投标人提供准确的信息。该项目将确定情况是否如此。工作申请策略中的性别差异将使用主要在线劳动力市场平台的专有数据进行研究。我们将探讨信念上的两种差异:一种是由于对预期工资或成本的信念不同而产生的,另一种是由于对预期工资或成本的感知不确定性的差异而产生的。为了确定哪种信念差异在起作用,该研究将把大规模劳动力市场预期调查的结果与系统地操纵预期的信息实验结合起来。总体而言,该项目可以提供关于信息政策如何减少或消除期望偏差,从而缩小性别工资差距的见解。该奖项反映了 NSF 的法定使命,并通过使用基金会的智力优点和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Gender Wage Gap in Online Gig Economy and Gender Differences in Job Preferences
在线零工经济中的性别工资差距和工作偏好的性别差异
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Yili Hong其他文献

Product Component Genealogy Modeling and Field‐failure Prediction
产品组件谱系建模和现场故障预测
On Computing the Distribution Function for the Sum of Independent and Non-identical Random Indicators Yili Hong
  • DOI:
  • 发表时间:
    2011
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Yili Hong
  • 通讯作者:
    Yili Hong
Motivating User-Generated Content with Performance Feedback: Evidence from Randomized Field Experiments
通过性能反馈激励用户生成的内容:来自随机现场实验的证据
  • DOI:
    10.2139/ssrn.2971783
  • 发表时间:
    2017-05
  • 期刊:
  • 影响因子:
    5.4
  • 作者:
    Ni Huang;Gordon Burtch;Bin Gu;Yili Hong;Chen Liang;Kanliang Wang;Dongpu Fu;Bo Yang
  • 通讯作者:
    Bo Yang
Effective Nonparametric Distribution Modeling for Distribution Approximation Applications
分布近似应用的有效非参数分布建模
  • DOI:
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    0
  • 作者:
    T. Lux;L. Watson;Tyler H. Chang;Li Xu;Yueyao Wang;Jon Bernard;Yili Hong;K. Cameron
  • 通讯作者:
    K. Cameron
User idea implementation in open innovation communities: Evidence from a new product development crowdsourcing community
开放创新社区中的用户创意实施:来自新产品开发众包社区的证据
  • DOI:
    10.1111/isj.12286
  • 发表时间:
    2020-03
  • 期刊:
  • 影响因子:
    6.4
  • 作者:
    Qian Liu;Qianzhou Du;Yili Hong;Weiguo Fan;Shuang Wu
  • 通讯作者:
    Shuang Wu

Yili Hong的其他文献

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{{ truncateString('Yili Hong', 18)}}的其他基金

Conference: The 2024 Joint Research Conference on Statistics in Quality, Industry, and Technology (JRC 2024) - Data Science and Statistics for Industrial Innovation
会议:2024年质量、工业和技术统计联合研究会议(JRC 2024)——数据科学与统计促进产业创新
  • 批准号:
    2404998
  • 财政年份:
    2024
  • 资助金额:
    $ 1.59万
  • 项目类别:
    Standard Grant
Reliability Prediction Based on Dynamic Data Collected with Modern Technology
基于现代技术采集的动态数据的可靠性预测
  • 批准号:
    1068933
  • 财政年份:
    2011
  • 资助金额:
    $ 1.59万
  • 项目类别:
    Standard Grant

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