Coding Bootcamps for Female Digital Employment: Evidence from an RCT in Argentina and Colombia

Last registered on May 16, 2022
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Pre-Trial

Trial Information

General Information

Title
Coding Bootcamps for Female Digital Employment: Evidence from an RCT in Argentina and Colombia
RCT ID
AEARCTR-0003850
Initial registration date
March 11, 2020

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
March 12, 2020, 7:00 PM EDT

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

Last updated
May 16, 2022, 11:22 AM EDT

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Country
Argentina
Region
Buenos Aires
Country
Colombia
Region
Bogota

Primary Investigator

Name
Julian Aramburu
Affiliation
Yale University
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Other Primary Investigator(s)

PI Name
Gonzalo Rivera Gallegos
PI Affiliation
Yale University
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PI Name
Ana Goicoechea
PI Affiliation
The World Bank
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PI Name
Ahmed Mushfiq Mobarak
PI Affiliation
Yale University
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Additional Trial Information

Status
On going
Start date
2018-11-01
End date
2022-12-15
Keywords
Education, Gender, Labor
Additional Keywords
JEL code(s)
C21, I26, J16, J21, J24, J48, O12
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This paper evaluates the causal effects of a high-quality, intensive, part-time computer coding Bootcamp on skill acquisition and employment outcomes on a sample of young female participants. Spots ar offered in an oversubscribed coding course to a random subset of applicants in Buenos Aires, Argentina, and Bogotá, Colombia. We do a cross-cut random assignment of: (i) a spot in the course with a scholarship to cover most of the cost of the tuition, and (ii) access to a female peer (in the form of an encouragement to form a work team with another female classmate). We evaluate the impact of the BootCamp on females' labor market and educational outcomes. In particular, we aim to answer the following questions: (i) Does the BootCamp increase participants' skills demanded by the IT sector? (ii) Does the Bootcamp help participants access a job in the IT sector? (ii) Does access to a female peer increase the probability of acquiring these skills (taking up the BootCamp)?
External Link(s)

Registration Citation

Citation
Aramburu, Julian et al. 2022. "Coding Bootcamps for Female Digital Employment: Evidence from an RCT in Argentina and Colombia." AEA RCT Registry. May 16. https://doi.org/10.1257/rct.3850-1.2
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Experimental Details

Interventions

Intervention(s)
We do a cross-cut random assignment of: (i) a spot in the Bootcamp together with a scholarship to cover between 60 and 80% of the cost of a ready-to-work computer programming Bootcamp, and (ii) access to a female peer (in the form of an encouragement to form a work team with another female classmate).

The Bootcamp is a 170-hour (four-month) course that requires 10.5 hours a week, and it provides training on both computational and soft skills. Computational training is mandatory, and it teaches basic programming skills that are designed based on the market demands. The soft skill module is optional, and it entails confidence-building, leadership, personal initiative, communication and presentation skills, and team work among others. The program also offers a professional development component through which students are trained in job-application practices, and a job bank where trainees are given the possibility to apply for different jobs connected to the Bootcamp providers. After completion, participants are expected to be able to build complex web pages and understand programming fundamentals.

The peer component consists of matching two beneficiaries of the scholarship (based on observable characteristics) and encouraging them to form a work team. They are encouraged to work together over the course material, help each other prepare for job interviews. Beneficiaries know they are matched with another one the moment they receive the offer to participate in the Bootcamp.
Intervention Start Date
2019-02-13
Intervention End Date
2019-12-20

Primary Outcomes

Primary Outcomes (end points)
Employment outcomes (employment, employment in tech, wages, occupation, quality of the job, amenities of the firm); educational outcomes (programming skills, enrollment in other coding courses, enrollment in STEM and computer science superior education).
Primary Outcomes (explanation)
Programming skills will be measured in the short term with an exam that resembles coding questions that a candidate may get in a job interview for an entry-level job in the tech sector.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
To analyze the differential causal effect of skill acquisition vis-à-vis access to the peer, the RCT consists of the following arms:

Arm 1: Spot in the course with a scholarship to cover most of the cost of the tuition.
Arm 1.1 - Individual Offer: the offer is allocated individually to women.
Arm 1.2 - Paired Offer: in addition to receiving the offer, women are paired with another beneficiary on the basis of similar backgrounds (education), and they are encouraged to work together on coursework material, homework, and job interview preparations, among other activities. Beneficiaries know they are matched with another one the moment they receive the offer to participate in the Bootcamp.
Arm 2 – Control group: receives neither the offer of the spot and scholarship nor the access to the peer.
Experimental Design Details
Randomization Method
Randomization done in office by a computer (Stata).
Randomization Unit
Individual.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
Randomization is at the individual level.
Sample size: planned number of observations
803 eligible applicants to the bootcamp course.
Sample size (or number of clusters) by treatment arms
Arm 1 (Treatment): 402
Arm 1.1: 210
Arm 1.2: 192
Arm 2 (Control): 401
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Yale University
IRB Approval Date
2020-04-01
IRB Approval Number
2000025881
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