Microequity for women led microenterprises - Experimental evidence from India

Last registered on July 26, 2022


Trial Information

General Information

Microequity for women led microenterprises - Experimental evidence from India
Initial registration date
July 22, 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 26, 2022, 1:45 PM EDT

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


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Primary Investigator

University of Oxford

Other Primary Investigator(s)

PI Affiliation
Lecturer, Department of International Development, and Fellow, Centre for Islamic Studies, University of Oxford
PI Affiliation
Associate Professor, University of Oxford

Additional Trial Information

In development
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Nearly 98 percent of businesses in India are microenterprises that are susceptible to income shocks and lack access to capital. These conditions challenge their growth, profitability and survival, particularly for women led microenterprises. While many entrepreneurs have access to microcredit, these loans typically come with rigid repayment schedules that often deter entrepreneurs from channeling money into their business. We run a field experiment to test the effectiveness of microequity contracts, which are characterized by revenue contingent repayments over a three-year term. Working with women microentrepreneurs, we explore how microequity contracts affect microenterprise growth.
External Link(s)

Registration Citation

Meki, Muhammad , Sanghamitra Mukherjee and Simon Quinn. 2022. "Microequity for women led microenterprises - Experimental evidence from India." AEA RCT Registry. July 26. https://doi.org/10.1257/rct.9675-1.0
Sponsors & Partners

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Experimental Details


Working with Buzz Women, an NGO, and Yunus Social Business (YSB), a financing institution, we are running a field experiment that offers microequity contracts in two sectors of particular relevance for rural and peri-rural areas: (i) animal husbandry and (ii) tailoring. By randomizing access to microequity contracts, we will quantify the impact of microequity contracts on business and socioeconomic outcomes by comparing the microenterprises that were offered the contract to those that were not.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Firm revenues, expenditure and profit; Repayment data
Primary Outcomes (explanation)
Daily self-reported data on revenues, expenditure and profit are aggregated on a weekly basis; Repayment data from YSB is collected on a monthly basis

Secondary Outcomes

Secondary Outcomes (end points)
Compliance, work days, household consumption, employment, fixed capital investments, missed reporting
Secondary Outcomes (explanation)
Compliance - Weekly measure of compliance on daily reports;
Work days - Number of days worked per week collected using daily self reported data;
Household consumption - Calculated using 30 day recall from quarterly phone surveys
Employment -Number of workers employed from quarterly phone surveys
Fixed capital investments - For HH or business from quarterly phone surveys
Missed reporting - Difference between self-reported revenue and monitoring revenue

Experimental Design

Experimental Design
In this study, we have two groups - a treatment group that is offered a microequity contract and a control group that is offered no funding (they have business as usual access to regular loans). We have designed a microequity contract that facilitates the purchase of these assets through a performance-contingent repayment schedule. Monthly repayments under the equity contract will be calculated based on self-reported revenues; these self reports will then be verified using several monitoring technologies. Using daily self reported data, quarterly phone surveys and two in person follow-up surveys we study the impact of these contracts on our key outcomes of interest.

This pre-analysis plan was registered shortly after the loans were disbursed. At the time of writing this pre-analysis plan we were blinded to any post-intervention data.
Experimental Design Details
Not available
Randomization Method
Individual level randomization. For entrepreneurs engaged in animal husbandry we randomise with stratification. The sample is stratified based on median revenue in the three months before contract signing. Within tailoring, the sample is very small and therefore, no stratification was done.
Randomization Unit
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
28 entrepreneurs
Sample size: planned number of observations
28 entrepreneurs
Sample size (or number of clusters) by treatment arms
15 entrepreneurs in the treatment group and 13 entrepreneurs in the control group
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
For variables where we have daily pre-intervention data, we present power calculations based on simulated data. We have collected over one year of pre-intervention daily data (on revenue, expenditure and profit) for all participants in the study. We use this pre-intervention data to simulate a 50% increase in revenue due to the intervention over a period of three years. Based on simulated post intervention data, we check for power by estimating the primary ANCOVA specification using OLS and clustered poisson and conducting inference by randomization inference. We cluster at the firm level, and re sample according to the underlying stratification scheme. Despite the small sample size, we are powered to detect treatment effects equivalent to a 50\% increase in revenue (which is a reasonable effect size given the large capital injection). For variables collected using the quarterly phone surveys, preliminary power calculations suggest that with full take-up, a sample size of 30 is powered (at 77\%) to detect effect sizes of greater than 0.45sd.

Institutional Review Boards (IRBs)

IRB Name
Department of Economics, University of Oxford
IRB Approval Date
IRB Approval Number
ECONCIA19-20-18 28th
Analysis Plan

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