What Works for Her?: How Work-from-Home Digital Jobs Affect Female Labor Force Participation

Last registered on October 19, 2022


Trial Information

General Information

What Works for Her?: How Work-from-Home Digital Jobs Affect Female Labor Force Participation
Initial registration date
September 25, 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
September 27, 2022, 11:53 AM EDT

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

Last updated
October 19, 2022, 8:46 AM EDT

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



Primary Investigator


Other Primary Investigator(s)

PI Affiliation

Additional Trial Information

In development
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Digital jobs – jobs women can perform using their smartphones – may have the potential to alleviate some of the constraints of female labor force participation (FLFP) today. This study aims to show how providing newer digital job opportunities and paid work-from-home could affect female labor force participation. This randomized controlled trial based is conducted in Mumbai’s slum redeveloped colonies with around 3,800 households. It aims to provide evidence for understanding the difference in job offer acceptance rates among married women between offers for work-from-home (WfH) jobs and offers for (otherwise identical) local work-from-centers (WfC) jobs outside the home. Further, it alters the wages assigned at both locations to observe the difference in job take-up, among other intensive margin results. We observe how providing more suitable employment to women may change women’s employment status and job performance, if at all, and the effects of this employment on women’s overall agency, mental health, dignity, and social norms. This study also tries to further unravel the gender norms associated with women’s work in contexts where they are the strongest. By also interviewing husbands, we try to understand differences, if any, between husbands’ and wives’ perceptions on social acceptability of these new jobs and the gender norm where married women are not permitted to work, particularly for jobs where they can more than just some pocket money.
External Link(s)

Registration Citation

Jalota, Suhani and Lisa Ho. 2022. "What Works for Her?: How Work-from-Home Digital Jobs Affect Female Labor Force Participation." AEA RCT Registry. October 19. https://doi.org/10.1257/rct.10017-2.0
Sponsors & Partners

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Experimental Details


In this study, we use novel jobs that are normally performed by Business Process Outsourcing (BPO) units on Personal Computers/Desktops and convert them to smartphone-based micro-tasks that can be performed by women from home. These tasks are presented on a tailor-made Android mobile application, called Rani (Queen). This is a gig economy platform allowing for flexible work hours. They are all shown a similar set of tasks, their work is validated for accuracy, and payments are made weekly.

The intervention is about 100 hours of work per worker (or 1-1.5 months) on this digital job platform for women over their own smartphones. The treatment arms differ in the job contract offered to the women, specifically by location of job and payment level offered.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
1. The primary outcomes through the baseline survey are the job take-up results that are measured (1) at the end of the survey, (2) through downloading the job application, and then (3) through observed work completed on the application. The job acceptance results are compared across all treatment arms (home vs center, and the three payment levels, and knowledge of husband survey).
2. We also learn about women’s willingness to work, and to take on future work engagements, along with willingness to switch from WfC to WfH (at lower pay) or from WfH to WfC (at higher pay) at Endline.
3. The study also tries to understand the effects of these digital job arrangements on women’s mental health, agency, empowerment, and other well-being indicators.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
1. We measure intensive margin outcomes for women’s work, including the amount of time spent on the application, number of tasks completed, accuracy levels (measures their job productivity), and total payment earned.
2. For heterogeneity analysis, we explore the attributes of women who are more or less likely to accept job offers across the different treatment arms.
3. Husband’s perceptions and decisions: We measure the role of husbands in the decision-making process through husband surveys, and by informing some women their husbands would be surveyed
4. Time use: We understand how women are spending their time in household chores and how that might change because of the job intervention.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Women are assigned to one of seven arms (6 treatment, and 1 control). The 6 treatment arms vary in the job location (work-from-home or WfH, work-from-center or WfC) and payment level (low, medium, high). Baseline surveys are completed with all eligible women in the study. At the end of the survey, women are offered a job contract. The job contract includes details about the job task, payment details, and the location of the job. Around 20% of the women are also told that this job contract information will be informed to their husbands through another survey conducted by a male enumerator.

Women are then asked whether they accept the job contract. After the job contract offer, women do the job for about 100 hours (over ~1.5 months) before the Endline. At Endline, women are offered different job contracts, switching the location, and adding other variables of distance to center, among other job characteristics.
Experimental Design Details
Not available
Randomization Method
Randomization done by a computer.
Randomization Unit
Individual households.
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
Sample size: planned number of observations
3000-4000 households
Sample size (or number of clusters) by treatment arms
Around 500-530 per treatment arm (treatments 1, 2, 3, 4, 5, 6, 7) and around 500-530 for control.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
Stanford University
IRB Approval Date
IRB Approval Number
Analysis Plan

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