Micro-enterprise saturation and poverty graduation at high frequency

Last registered on July 28, 2023


Trial Information

General Information

Micro-enterprise saturation and poverty graduation at high frequency
Initial registration date
July 21, 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 28, 2023, 10:55 AM EDT

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


Primary Investigator

Brown University

Other Primary Investigator(s)

Additional Trial Information

In development
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Ultra-poor graduation programs (UPGs) aimed at creating sustainable livelihoods are the closest that development economics has come to a silver bullet for ultra-poverty alleviation. While in-kind, conditional and unconditional cash transfers have been shown to provide effective poverty relief and invigorate micro-enterprises in the short run, in-kind transfers or strong-handed conditionalities may induce distortionary effects, and the evidence on long-term effects is mixed at best. Skills training, coaching, or access to loans or savings facilities by themselves show few if any impacts. On the other hand, UPGs following the BRAC model (studied here) – monthly cash transfers, business start-up grants or productive assets, training, formation of savings groups, and one-on-one coaching – seem to be standing the test of time while providing results that are larger than the sum of their parts in response to the highly complex challenge that multidimensional poverty traps pose. I leverage the roll-out of a large UPG (monthly cash transfers + training + business start-up grant + ongoing coaching) for ultra-poor households in Malawi to conduct a randomized control trial that generates unique high frequency data and investigates the following sets of questions:

(0) The research study is built around an impact evaluation of the implementing NGO's "Childhoods and Livelihoods" child-focused UPG.

(1) By experimentally varying the program saturation, I provide evidence on whether livelihood-creation interventions can lead to self-defeating overcrowding or virtuous critical mass of micro-enterprises in small village economies.

(2) Poverty and economic shocks in Malawi are highly seasonal and exacerbated by climate change. We administer the program to three cohorts at different times in the agricultural season and ask: Is it best to provide households with the means to start businesses pre- or post-harvest or in the lean season?

(3) Throughout the program, treatment and control households are surveyed at (novel) high frequency to allow us to trace their path out of poverty and illuminate the role of seasonal shocks in upsetting their progress. What role do small and large day-to-day shocks play in turning poverty into a trap? How are UPGs, that have been shown elsewhere to effectively resolve poverty traps, able to overcome this challenge? What combination of shock resilience strategies does the UPG induce for treated households?

(4) A large literature aims to target entrepreneurship programs to the most promising beneficiaries, with only moderate success. I recast this prediction problem into a decomposition exercise between factors like ability that are at least in principle knowable and adverse shocks that afflict the firm or the household that runs it that we couldn’t hope to predict and are therefore unknowable. In a study design that allows me to leverage exogenous variation in entrepreneurs’ exposure to shocks, I estimate what share of the outcome heterogeneity observed in an entrepreneurship promotion program is due purely to events such as weather, health, social network, or price shocks, which in most contexts are beyond the control of implementers.
External Link(s)

Registration Citation

Poll, Moritz. 2023. "Micro-enterprise saturation and poverty graduation at high frequency." AEA RCT Registry. July 28. https://doi.org/10.1257/rct.11789-1.0
Experimental Details


Context: Worldwide, 650 to 670 million people live in extreme poverty. Malawi is one of the poorest countries on Earth and 70% of the population lives in extreme poverty. Ultra-poor graduation programs (UPGs) are the closest development economics research has come to a silver bullet for ultra-poverty alleviation. The UN SDG 1.1 commits the world to "Eradicate extreme poverty by 2030". If SDG 1.1 is to be achieved, the development community needs to better understand how and why UPGs work, how well they scale, and how to make them more cost-effective.
Location: Within Malawi, Mangochi district at the Southern shore of Lake Malawi is among the poorest districts and the district government selected four subdistricts ("Traditional Authorities" or TAs Nankumba, Mponda, Chimwala, and Makanjila) for consideration as the study site for being currently under-served when it comes to poverty alleviation programming. TA Nankumba was selected among the four by the implementing NGO for its accessibility, both for program staff going to the area and for program participants to access urban markets and Lake Malawi for potential business ventures they may engage in.
Program and implementing partner: The implementing partner for this study, Yamba Malawi, is a Malawian and US non-profit founded in 2006 that has transitioned from a purely in-kind donation focus to a child-centered UPG modeled on the approach by the Bangladeshi NGO BRAC, but adapted to their specific ECD focus and the local context. At the household level, the all-female program participants receive monthly cash transfers of the equivalent of $20 for twelve months, business start-up grants of $125 at the end of a six-month weekly training in ECD and micro-entrepreneurship, a basic phone, support for the formation of savings groups, and fortnightly one-on-one coaching and monitoring visits. At the community level, the NGO supports community structures (community-based organizations and community-based childcare centers) financially and with trainings. After several iterations of refining the model, the NGO seeks to evaluate its impact with an openness for further-reaching research questions. The program evaluation that underlies this research study isolates the household component of the program. The control group will receive a basic phone as well, survey incentives (which are modest relative to the cash transfers of the UPG), and fortnightly monitoring visits that will share some of the coaching components of the treatment group. The community component lacks excludability and is extended to all households in the study area, also to secure local buy-in.
Sample: The implementing partner, Yamba Malawi, will collect a household census as well as community wealth rankings to determine program eligibility using the Simple Poverty Score Card. To be eligible for the program, households need to have a mother of a child under the age of 5, be classified as ultra-poor, not state any intentions of migrating in the foreseeable future, and the mother needs to be able to work.
Household clusters: We expect the study area to contain far more eligible households than the NGO has funds to serve. This provides an opportunity of strategically selecting the sample. Note first that in the local context, villages are fairly fluid concepts. Households routinely split off their village to form new villages and the area can be thought of as more or less continuously populated. The study therefore assigns all eligible households to clusters by proximity, regardless of village. It then selects 72 household clusters in a way that bolsters statistical power for research question (1).
Timeline: This is a multi-year program and project. The tentative timeline is to conduct a household census in August of 2023 and launch the first of three cohorts at the end of 2023 with cohorts 2 and 3 scheduled for 2024 and 2025.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Each research question has its own set of key outcome variables.
(0) & (2) The outcome variables used to evaluate the program are defined by the implementing NGO as their graduation criteria and attached to the pre-analysis plan.
(1) & (2) Business success will be measured as the number of distinct businesses the household runs, industry choice of the business(es), monthly income (net of NGO transfers), value of business assets.
(3) Occurrence, severity, and frequency of shocks, as well as coping behavior are used in addition to the above final outcomes as intermediary outcomes.
Primary Outcomes (explanation)
Please refer to the pre-analysis plan which includes the exact survey questions for all outcomes as an appendix.

Secondary Outcomes

Secondary Outcomes (end points)
Outcomes marked with an * are collected at high frequency.

Economic outcomes
* Income
* Income sources / diversity
* Spending
* Entrepreneurship activity
* Shocks and coping
* Savings
* Investment
* Migration decisions
* Farming/business practices
State of the dwelling
Child wellbeing outcomes
Childcare/school attendance
* Anthropometrics
Teenage marriage and pregnancy
Parenting behavior
Health outcomes
* Morbidity (acute and chronic)
* Mortality
* Fertility
* Mosquito net availability
* Health-seeking behavior
Nutrition (quantity, quality, diversity)
Vaccination status
Social outcomes
Community engagement
Household decision-making
Non-standard outcome data
Narrative of business idea
* Monthly household budgets
* Mobile money transactions
Secondary Outcomes (explanation)
Please refer to the pre-analysis plan which includes the exact survey questions for all outcomes in the appendix.

Experimental Design

Experimental Design
This study contains the following experimental design elements:
- Randomized control trial: This is an RCT, so households will be randomly assigned to either a treatment group that receives the UPG or a control group that does not.
- Random cohort assignment: The program will be rolled out in three evenly sized cohorts scattered in the same area to which household clusters are assigned at random.
- Treatment saturation: Household clusters are assigned to one of three treatment saturation levels (all households treated, half treated, none treated).
- Business coordination intervention: Half of the treated clusters of each saturation level are assigned to receive an additional light-touch intervention lesson in their curriculum in which they are encouraged to share their business ideas with each other and coordinate within the group so that different households start different businesses.
- Randomized reminders: In order to induce exogenous variation in shock arrivals, I randomize the order in which households are asked whether they have already taken certain recommended preventive actions (such as procuring a bed net, building a handwashing station, etc.).
Experimental Design Details
Not available
Randomization Method
By a computer
Randomization Unit
Two levels of randomization: Household clusters are randomly assigned to high saturation (everybody treated), low saturation (half treated randomly at the household level), or pure control (nobody treated). Household clusters are assigned to field facilitators (FFs) where each FF is assigned one of each type of clusters. FF clusters are also assigned randomly to start as part of cohorts 1, 2, or 3. Half of treated household clusters are assigned to receive one extra lesson where they are encouraged to coordinate their business ideas with each other. At the individual level, I also randomize the order in which households are prompted to take certain preventive steps to avoid various shocks.
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
72 household clusters
Sample size: planned number of observations
1,500 households, surveyed once at baseline, midline, and endline as well as fortnightly on certain outcomes for at least one year (T = 26) or longer depending on the availability of funding.
Sample size (or number of clusters) by treatment arms
N = 1,500: 900 treated and 600 control households across 72 household clusters (24 high saturation, 24 low saturation, and 24 control group) and 3 evenly sized cohorts of 300 treated and 200 control households each.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
I conducted extensive power calculations in which I simulate and estimate each of the above specifications 1000 times. For specifications (0) and (3), the study is 80% powered to detect treatment effect sizes of the program of at least 0.15 SDs. The spillover specification for research question (1) is powered to detect treatment effect sizes of at least 0.1 SDs. For specification (2), power is somewhat lower, achieving an 80% probability of detecting an effect size of 0.3 SDs or larger of ranking cohorts against each other.

Institutional Review Boards (IRBs)

IRB Name
National Committee of Research in the Social Sciences and Humanities (NCRSH), Malawi
IRB Approval Date
IRB Approval Number
IRB Name
Brown University IRB
IRB Approval Date
IRB Approval Number