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Paid Maternity Leave and Gender Discrimination: A Field Experiment on Labor Market
Last registered on March 01, 2021

Pre-Trial

Trial Information
General Information
Title
Paid Maternity Leave and Gender Discrimination: A Field Experiment on Labor Market
RCT ID
AEARCTR-0007216
Initial registration date
March 01, 2021
Last updated
March 01, 2021 10:42 AM EST
Location(s)
Region
Primary Investigator
Affiliation
ShanghaiTech University
Other Primary Investigator(s)
PI Affiliation
Shenzhen University WeBank Institute of Fintech and Shenzhen Audencia Business School, Shenzhen University
PI Affiliation
Shenzhen University
PI Affiliation
Shenzhen University WeBank Institute of Fintech and Shenzhen Audencia Business School, Shenzhen University
Additional Trial Information
Status
On going
Start date
2020-12-28
End date
2021-12-31
Secondary IDs
Abstract
Despite improving trends in gender equality, gender gaps remain pronounced in modern societies, especially in the labor market. Conventional and restrictive gender norms, which stress women’s family-focused role and men’s career-focused role, further reinforce and reproduce gender inequality. With such gender ideology, employers may think of female employees as less career-minded and potentially incur higher labor costs due to the paid maternity leave. Therefore, female employees would be less favorable than their male counterparts would. Policy interventions, for instance, a rational-designed parental leave policy may help to reduce such gender discrimination in the labor market. In this study, we conduct an experiment using the correspondence testing method on the Chinese labor market. We investigate whether and to what extent gender discrimination exists in the labor market of China. If so, whether the current paid maternity leave plays an unintended role in exacerbating this situation. Understanding these questions is crucial for policymakers to improve the current parental leave policies and reduce the gender gap in the labor market.
External Link(s)
Registration Citation
Citation
Li, King King et al. 2021. "Paid Maternity Leave and Gender Discrimination: A Field Experiment on Labor Market." AEA RCT Registry. March 01. https://doi.org/10.1257/rct.7216-1.0.
Experimental Details
Interventions
Intervention(s)
We are conducting a large-scale correspondence study to investigate gender discrimination in the Chinese labor market. The intervention is the gender and age of the job applicant, as signaled by the name and relevant information on the resume.
Intervention Start Date
2021-03-15
Intervention End Date
2021-05-16
Primary Outcomes
Primary Outcomes (end points)
The primary outcome of interest is whether a job applicant receives a positive response (callback) from an employer via email, phone call, or text message.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
The secondary outcome is how many times each resume is opened or viewed.
Secondary Outcomes (explanation)
There is a section on the online job application platform called “Who is searching me”, in which candidates can check when, how many times, and to what extent companies have interests in them.
Experimental Design
Experimental Design
We conduct a correspondence study by sending fictitious resumes to apply to online job postings from different firms. We create resumes for female and male candidates, which are similar in all dimensions (education background, previous work experience, professional skills, etc.), except for the names. The name on each resume is purposely designed to signal the job seeker’s gender. We collect related background information and baseline data via surveys and web scraping techniques in the targeted cities and platforms before the intervention starts.
Experimental Design Details
Not available
Randomization Method
Randomization done in office by a computer.
Randomization Unit
The randomization units are firms that posted job openings online.
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
Planned number of clusters: 24 clusters
The cluster unit: 1000 firms
Sample size: planned number of observations
1000 firms * 3 age categories * (8 * 3) clusters = 72000 job applications
Sample size (or number of clusters) by treatment arms
Treatment group: 36000 female job applications
Control group: 36000 male job applications
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
ShanghaiTech University Institutional Review Boards (IRB)
IRB Approval Date
2020-05-21
IRB Approval Number
ShanghaiTech SEM IRB#2020-005