STEM training for the educated poor

Last registered on June 23, 2026
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Pre-Trial

Trial Information

General Information

Title
STEM training for the educated poor
RCT ID
AEARCTR-0018973
Initial registration date
June 22, 2026

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
June 23, 2026, 8:45 AM EDT

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

Locations

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Primary Investigator

Name
Manuela Angelucci
Affiliation
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Other Primary Investigator(s)

PI Name
Ketki Sheth
PI Affiliation
Contact Investigator

Additional Trial Information

Status
On going
Start date
2025-06-30
End date
2029-12-31
Keywords
Education, Labor
Additional Keywords
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This study evaluates the impacts and mechanisms of the DeepTech training program among the ``educated poor," low-income young adults in India who have invested in higher education and are seeking labor market opportunities, particularly in the technology sector. The project studies a central question: why do labor market opportunities remain weak among educated low-income youth, especially women, even after investing in higher education?
External Link(s)

Registration Citation

Citation
Angelucci, Manuela and Ketki Sheth. 2026. "STEM training for the educated poor." AEA RCT Registry. June 23. https://doi.org/10.1257/rct.18973-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
This study evaluates the impacts and mechanisms of the DeepTech training program among the ``educated poor," low-income young adults in India who have invested in higher education and are seeking labor market opportunities, particularly in the technology sector. The project studies a central question: why do labor market opportunities remain weak among educated low-income youth, especially women, even after investing in higher education?

The intervention is implemented over three years, recruiting about 5,000 eligible applicants to the DeepTech program, a course that provides both hard and soft skills for engineering and computer science graduates who seek to work in the tech sector. Individuals are randomly assigned at the individual level to treatment or control.

The sample consists of approximately 5,000 study participants, with approximately 3,750 assigned to treatment and 1,250 assigned to control. Data collection includes a baseline survey and up to 2 follow-ups approximately 6 months after baseline, with the idea of continuing to follow up participant at 6-12 month intervals for up to three years depending on successful fundraising.
Intervention Start Date
2025-12-31
Intervention End Date
2028-12-31

Primary Outcomes

Primary Outcomes (end points)
Employment status
Employment in the tech sector
Compensation and earnings
Job categories in tech
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The sample consists of approximately 5,000 study participants (low-income, disadvantaged engineering and CS college graduates who are eligible applicants to the DeepTech program), with approximately 3,750 assigned to treatment (the DeepTech program) and 1,250 assigned to control (excluded from the DeepTech program). Participants are enrolled in the study over 3 years. Data collection includes a baseline survey and follow-ups starting approximately 6-12 months after baseline, with the idea of continuing to follow up participant at 6-12 month intervals for up to three years depending on successful fundraising.
Experimental Design Details
Not available
Randomization Method
randomization done in office by a computer
Randomization Unit
person
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
no clusters
Sample size: planned number of observations
5000 people
Sample size (or number of clusters) by treatment arms
approximately 3,750 assigned to treatment and 1,250 assigned to control
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 Approval Date
IRB Approval Number
Analysis Plan

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