The Return to Data Analysis Skill in the Labor Market

Last registered on July 29, 2022
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Pre-Trial

Trial Information

General Information

Title
The Return to Data Analysis Skill in the Labor Market
RCT ID
AEARCTR-0009808
Initial registration date
July 27, 2022

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
July 29, 2022, 10:54 AM EDT

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

Locations

Country
China
Region
online

Primary Investigator

Name
Menghan Shen
Affiliation
Sun Yatsen University, China
Contact Primary Investigator

Other Primary Investigator(s)

Additional Trial Information

Status
On going
Start date
2022-06-01
End date
2022-08-15
Keywords
Education, Labor
Additional Keywords
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
We examine whether there is return to the ability of analyzing data in the labor market in China for undergraduate students majoring in economics. We are conducting a large-scale audit study and submitted resumes of fictitious candidates to job advertisements positions posted on a popular job search platform. To manipulate perceived data analysis ability, resumes are randomly assigned different levels of data analysis skills.

External Link(s)

Registration Citation

Citation
Shen, Menghan. 2022. "The Return to Data Analysis Skill in the Labor Market ." AEA RCT Registry. July 29. https://doi.org/10.1257/rct.9808-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2022-06-01
Intervention End Date
2022-08-15

Primary Outcomes

Primary Outcomes (end points)
whether employers call back a job applicant and the type of companies that call back (e.g. whether they are a start-up or not, the size of the company, the work expectation, the work content)
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We submitted resumes from fictitious candidates to job openings in major Chinese cities on a large job search website. While we keep the content of the resume largely the same, we randomly vary the ability of data analysis skills in the resume. The control resume includes seniors majoring in economics who do not indicate that they have any data analysis skills. The treatment one resume includes seniors majoring in economics who indicate that they knows stata programming skills. The treatment two resume includes seniors majoring in economics who indicate that they knows python programming skills. In both treatment group and control group, they conducted internships but differed in their capacity of analyzing data. Otherwise the resume are identical in three groups.
Experimental Design Details
Randomization Method
randomization done in office by a computer
Randomization Unit
individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
N/A
Sample size: planned number of observations
3000~5000 depending on the job market
Sample size (or number of clusters) by treatment arms
one third in control group, one third in treatment one group, and one third in treatment two group
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Office, School of Government, Sun Yatsen University
IRB Approval Date
2022-05-02
IRB Approval Number
School of Government202202
Analysis Plan

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials