A Field Experiment on the Hiring Gap in AI Skills and Gender in China’s Campus Recruiting Labor Market

Last registered on November 19, 2024
View Trial History

Pre-Trial

Trial Information

General Information

Title
A Field Experiment on the Hiring Gap in AI Skills and Gender in China’s Campus Recruiting Labor Market
RCT ID
AEARCTR-0014640
Initial registration date
October 27, 2024

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
November 19, 2024, 3:47 PM EST

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information

Primary Investigator

Name
Yaping Li
Affiliation
Tsinghua University
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
Rong Ma
PI Affiliation
China Agricultural University
Contact Investigator
PI Name
Zhufeng Xu
PI Affiliation
Central University of Finance and Economics
Contact Investigator

Additional Trial Information

Status
On going
Start date
2024-10-31
End date
2025-06-30
Keywords
Gender, Labor
Additional Keywords
Human Capital, Resume Audit Study, Task, Skill-Biased Technological Change
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
The rapid development of AI technologies in recent years is reshaping the labor market. This study investigates how AI skills affect employment outcomes and whether they interact with gender. A large-scale resume field experiment will be conducted in China, sending thousands of fictitious resumes to potential employers. The resumes will vary randomly in terms of applicants’ AI skills and gender. We also explore the potential heterogeneity in outcomes based on applicant characteristics and job attributes.
External Link(s)

Registration Citation

Citation
Li, Yaping, Rong Ma and Zhufeng Xu. 2024. "A Field Experiment on the Hiring Gap in AI Skills and Gender in China’s Campus Recruiting Labor Market." AEA RCT Registry. November 19. https://doi.org/10.1257/rct.14640-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2024-10-31
Intervention End Date
2025-06-30

Primary Outcomes

Primary Outcomes (end points)
Response rates to job application in China
Primary Outcomes (explanation)
We will record the callback rates for the submitted fictitious resumes

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We will implement a resume audit experiment. For each selected job posting, a collection of four fictitious resumes will be submitted. Randomization will occur across these four resumes, categorized as follows:
• Group 1: Men with AI skills
• Group 2: Women with AI skills
• Group 3: Men without AI skills
• Group 4: Women without AI skills
The study aims to examine the causal effects of AI skills based on the callback rates observed across these four groups, and whether they interact with gender.

Additional resume details will be sourced from a pre-constructed resume bank and randomly assigned to each resume. Every resume will be proofread by the researchers to ensure authenticity. This study will also explore outcomes variations based on applicant traits and job attributes.

Resumes will be submitted to 2,500 public job postings, totaling 10,000 applications.
Experimental Design Details
Not available
Randomization Method
Randomization will be done in office by a computer.
Randomization Unit
Resumes level randomization
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
2,500 public job postings, 4 fictitious resumes for each job posting.
Sample size: planned number of observations
10,000 fictitious resumes
Sample size (or number of clusters) by treatment arms
2,500 fictitious resumes representing men possessing AI skills,
2,500 fictitious resumes representing women possessing AI skills,
2,500 fictitious resumes representing men lacking AI skills, and
2,500 fictitious resumes representing women lacking AI skills.
The fictitious resumes without AI skills are treated as the control groups.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Scientific Review Committee at the Central University of Finance and Economics
IRB Approval Date
2024-10-21
IRB Approval Number
IRB20241021001
Analysis Plan