Malaysia Correspondence Study

Last registered on July 10, 2023

Pre-Trial

Trial Information

General Information

Title
Malaysia Correspondence Study
RCT ID
AEARCTR-0011591
Initial registration date
June 16, 2023

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 10, 2023, 4:54 PM EDT

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

Locations

Region

Primary Investigator

Affiliation
University of Illinois

Other Primary Investigator(s)

PI Affiliation
University of Illinois
PI Affiliation
World Bank
PI Affiliation
World Bank

Additional Trial Information

Status
On going
Start date
2023-05-01
End date
2024-05-01
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
In this correspondence study, we test for labor market discrimination in Malaysia by ethnicity and gender. In addition, we evaluate whether soft skill signals (leadership, teamwork, or none) are valued in the labor market, and their interaction with discriminatory behavior.
External Link(s)

Registration Citation

Citation
Binti Abdur Rahman, Amanina et al. 2023. "Malaysia Correspondence Study." AEA RCT Registry. July 10. https://doi.org/10.1257/rct.11591-1.0
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
Intervention (Hidden)
In this study we test for labor market discrimination in Malaysia by ethnicity (Malay, Chinese, Indian) and gender (male, female). In addition, we evaluate whether soft skill signals (leadership, teamwork, or none) are valued in the labor market, and their interaction with discriminatory behavior.

To assess labor market discrimination in Malaysia, we will utilize a correspondence study. Using this method, fictitious job applications are sent to employers that have advertised a job opening. Each job ad is randomly assigned a specific applicant profile. In this way, the applicant profile is the randomly assigned "treatment." The only meaningful differences between applicant profiles is the name (and contact information) of the applicant, which signals ethnicity and/or gender, and a signal of soft skills. By randomly assigning an applicant profile, these characteristics are randomly assigned. Using this method, the study will causally identify the degree of discrimination in hiring in two ways: by calculating the difference in the interview request rate between the various groups and by calculating the difference in the average number of profile views after applying to a job. We perform this analysis for five different degree specializations: Accounting, Business Administration, Computer Science, Electrical Engineering and Mechanical Engineering.

We use an online platform which creates some unique advantages relative to other studies. Specifically, we observe several characteristics of the firm and job that are not typically observable to researchers. In addition, we observe how many times employers view the application profiles and characteristics of the applicant pool. That is, how many applicants in the pool are more or less educated, and how many applicants have higher or lower expected salary. We know of no other correspondence study that has had access to this kind of information to study discrimination in any context.
Intervention Start Date
2023-05-01
Intervention End Date
2023-10-31

Primary Outcomes

Primary Outcomes (end points)
request for interview
Primary Outcomes (explanation)
request for interview is a dummy variable that takes the value of 1 if the company (employer) offered an interview to the candidate (contact).

Secondary Outcomes

Secondary Outcomes (end points)
profile viewed, and number of profile views, days to interview, days to determination of unsuitable
Secondary Outcomes (explanation)
Profile views is a dummy variable that takes the value of 1 if the employer viewed the profile of the candidate, or number of times employer viewed the profile of the candidate. For contacted profiles, we can compare the average number of days between application submission and interview offer by ethnicity and gender. We can perform a similar analysis for profiles that were declared not suitable.

Experimental Design

Experimental Design
To assess labor market discrimination in Malaysia, we will utilize a correspondence study. Using this method, fictitious job applications are sent to employers that have advertised a job opening. Each job ad is randomly assigned a specific applicant profile. In this way, the applicant profile is the randomly assigned "treatment." The only meaningful differences between applicant profiles is the name (and contact information) of the applicant, which signals ethnicity and/or gender, and a signal of soft skills. By randomly assigning an applicant profile, these characteristics are randomly assigned. Using this method, the study will causally identify the degree of discrimination in hiring in two ways: by calculating the difference in the interview request rate between the various groups and by calculating the difference in the average number of profile views after applying to a job. We perform this analysis for five different degree specializations: Accounting, Business Administration, Computer Science, Electrical Engineering and Mechanical Engineering.
Experimental Design Details
We use an online platform which creates some unique advantages relative to other studies. Specifically, we observe several characteristics of the firm and job that are not typically observable to researchers. In addition, we observe how many times employers view the application profiles and characteristics of the applicant pool. That is, how many applicants in the pool are more or less educated, and how many applicants have higher or lower expected salary.
Randomization Method
application profiles are randomly assigned to job ads in using a computer algorithm
Randomization Unit
individual job advertisement
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
3000 job ads (no clusters)
Sample size: planned number of observations
3000 job ads
Sample size (or number of clusters) by treatment arms
3000 job ads
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
7 percentage points
IRB

Institutional Review Boards (IRBs)

IRB Name
University of Illinois
IRB Approval Date
2023-01-25
IRB Approval Number
N/A

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