How can innovative financing create measurable change for communities living in extreme poverty?
Village Enterprise, a pioneer in extreme poverty alleviation, launched the first-ever Development Impact Bond (DIB) for poverty reduction in sub-Saharan Africa. This funding model ties financial investment to measurable outcomes, ensuring accountability and maximizing real-world results.
Through the Village Enterprise DIB, thousands of families in rural Kenya and Uganda have experienced measurable improvements in their lives, even amidst challenges like the COVID-19 pandemic. To help you better understand the DIB and its far-reaching impact, we’ve compiled answers to the most frequently asked questions below.
For a deeper dive, explore our DIB results page or read the full IDinsight report. You can also check out IDinsight’s own FAQ for additional insights.
IDinsight found that households participating in the Village Enterprise program had about a 6% increase in consumption. What is important about these increases?
Proven solutions to sustainably improve the well-being of families living in extreme poverty are rare. However, graduation programs—an approach designed to lift households out of poverty—have shown promising results. A 2015 study published in Science evaluated graduation programs across six countries and found a 5% increase in household consumption for participants compared to control groups. While modest, this increase translated into life-changing improvements: increased food intake, could purchase basic necessities, and experienced an overall boost in well-being.
We set out to build on this evidence by rigorously evaluating our own poverty graduation program to enhance effectiveness, improve outcomes for the entrepreneurs we serve, and push for greater accountability across the poverty alleviation sector. The results of our program, evaluated through an independent randomized controlled trial (RCT) conducted by IDinsight, exceeded expectations:
Households in the Village Enterprise program experienced a 6.3% increase in consumption, outperforming the 5% effect observed in the Science study.
In Kenya, participating households increased their consumption of green maize, beef, fish, maize flour, and chicken.
In Uganda, households reported higher consumption of chicken, fish, and tomatoes.
What makes these results especially significant is that our program is a lighter-touch, cost-effective model compared to earlier programs. Despite requiring fewer resources, it delivered greater benefits.
Village Enterprise achieved a 140% benefit-cost ratio, significantly higher than the 88% benchmark in the Science study. This efficiency demonstrates that streamlined, well-executed programs can achieve exceptional results while using fewer resources—critical for scaling solutions in resource-limited regions.
Village Enterprise’s success sets a new standard for poverty alleviation initiatives. By proving that cost-effective models can achieve measurable and life-changing outcomes, we are charting a path forward for sustainable solutions that improve the lives of families living in extreme poverty.
Why is increasing cost effectiveness important?
Increasing cost-effectiveness is critical because many countries face severe resource constraints. Even before the pandemic, lower-income nations struggled with an annual funding gap of USD 2.5 trillion to achieve the Sustainable Development Goals (SDGs). In this context, maximizing the impact of every dollar spent is essential to addressing poverty at scale.
Our three-year benefit-cost ratio (BCR) of 140% represents significant progress toward this goal. It demonstrates that achieving measurable improvements in the well-being of families living in extreme poverty is possible, even with limited resources. Looking ahead, we remain committed to further improving cost-effectiveness by continuing to innovate and refine our program to deliver greater outcomes for people living in poverty.
When did the RCT take place? Was it during the pandemic?
The RCT took place between November 2017 and August 2021, covering multiple program cohorts. The first four of seven cohorts graduated from the Village Enterprise program before the onset of the COVID-19 pandemic. The remaining three cohorts received ongoing mentoring and support during the pandemic, ensuring continuity despite the challenging environment.
End-line data collection occurred:
One year into the pandemic (six months after the last cohort graduated); and
2.5 years after the first cohort completed the program, providing critical insights into the lasting impacts of our intervention.
The RCT results showed sustained improvements in household well-being despite the economic disruptions of the pandemic. This is important as it highlights the resilience-building effects of graduation programming. In Sub-Saharan Africa, where families face ongoing shocks, building resilience is foundational for achieving long-term improvements in poverty alleviation.
The results not only reaffirm the sustainability of Village Enterprise’s program outcomes but also quantify its long-term benefits. According to IDinsight’s analysis, the lifetime impact of the Village Enterprise program in that project is estimated at $21.06 million, over five times the cost to implement the program, underscoring its ability to drive real change cost-effectively.
Village Enterprise’s pre-pandemic impact data found annual household per-capita consumption and expenditure increased by 71%. Why is this increase larger than the 6% increase in consumption plus expenditure that IDinsight found?
Several factors can explain the difference between the increases in consumption and expenditure measured by Village Enterprise’s Monitoring and Evaluation (M&E) and by the RCT. These include:
Our RCT used an intention-to-treat estimate—this means it measured impact amongst everyone who was offered the program (whether or not they accepted participation). In contrast, Village Enterprise’s M&E looks only at those who successfully completed the program.
Village Enterprise’s pre/post evaluation does not account for external factors that may also contribute to income growth for our program participants. The RCT was designed to exclude external factors and tell us only what the attributable change was.
Our internal data collected before the pandemic showed the DIB’s strong progress toward our goal of elevating the extremely poor in rural Africa out of poverty. We believe the RCT results would have been higher if evaluated outside the pandemic context, particularly if there had been an evaluation of only the first few cohorts before the pandemic began or if the pandemic had not taken place. During the pandemic, our entrepreneurs in rural Uganda faced strict lockdowns, with months of closed borders, suspended public transport, restricted cross-district movement, and nationwide curfews. As the evaluators noted, “conducting fieldwork during the Covid-19 pandemic exacerbated some technical risks and may have affected the generalizability of the findings to a non-pandemic context.”
We recognize there could be a response bias that is greater when our entrepreneurs interact with Village Enterprise enumerators than when they interact with entirely independent enumerators. However, to ensure Village Enterprise is following best practices and to control for this potential response bias, the enumerators who work with Village Enterprise are not our Business Mentors, Field Associates, or any other staff members who work closely with our entrepreneurs.
Why were the outcomes of the DIB measured through a randomized controlled trial?
This impact bond was meant to reward improvements in income. To approximate income as precisely as possible, the project measured two uses of income at the household level: consumption and assets. By doing so, and comparing the results with those of a control group as part of the RCT, the impact of the Village Enterprise intervention on income could be estimated.
What do these results mean for the future of results-based financing and the poverty alleviation sector?
The success of the Village Enterprise DIB offers a powerful proof of concept for results-based financing. It demonstrates that service provision can be commissioned based on a predefined fixed price-per-outcome model, even for outcomes directly targeting poverty alleviation. This approach not only incentivizes innovation and accountability but also creates space for continuous improvement and iteration.
Village Enterprise believes this successful model can inspire commissioners, service providers, and investors to consider outcomes-based contracting mechanisms for their own portfolios. As the outcomes-based financing sector grows, it can improve the effectiveness of development dollars by enhancing transparency, encouraging innovation, and directing funding toward scalable solutions that work.
Increased efficiency in aid spending may also attract new funders to the sector. The guarantee of predefined fixed price-per-outcomes could further expand the pool of funding available for poverty alleviation initiatives, ultimately accelerating progress toward ending extreme poverty.
How were the outcomes for this DIB selected?
The outcomes for this DIB were chosen to be closely tied to the ultimate impact and to be applicable across a wide range of livelihoods or income-generating projects. To achieve this, the DIB focused on improvements in income, a key indicator of poverty graduation that is common across many livelihoods, income-generation, and workforce development programs.
Given the challenges of measuring income in low-data, resource-constrained settings, the DIB used two household-level indicators—consumption and assets—to approximate income as accurately as possible. This approach allowed for a more reliable measure of income impact in these contexts.
How were the outcome prices determined in the DIB?
There were two key considerations to determine the specific price per unit of outcome:
1. Capturing the social value generated
The price paid for an outcome should not exceed the social benefits created. In this case, a conservative view on social benefits tied payments to incremental income generated for the treated households—$1 paid for every $1 increase in income. This is a conservative estimate because the poverty graduation model’s theory of change also aims to build social capital, increase financial literacy, and build business skills in a way that the monetary gains do not necessarily capture. As a result, the outcome funders were confident that the payment structure represented a fair and justifiable approach based on the evidence presented.
2. Sufficient incentives to encourage progress and compensate for risks
The price per unit also had to incentivize progress while compensating for risks taken by investors and service providers. The outcome funders wanted to ensure that the price was such that with the expected results and the planned program size, Village Enterprise and its investors received adequate compensation for the risks involved, while also providing strong incentives to drive performance improvement.
During design, the team built several simulations based on previous RCT data and a financial model. These simulations confirmed that using the proposed payment formula, Village Enterprise and the investors could earn a reasonable return, in line with relevant benchmarks from other impact bonds and impact investing opportunities.
Taking these factors into account, the price was set at $1 per $1 increase in household consumption. To account for the program’s long-term impact, increases in household assets were used as an indicator for estimating sustained income generation and future consumption potential.
How were the targets set for the DIB?
Household targets: Village Enterprise committed to serving a minimum of 12,660 households during the project. Based on internal capacity assessments, we set a higher target of 13,830 households. By the end of the project, we exceeded this goal, reaching 14,100 households.
Consumption targets: At the project’s outset, we aimed to increase consumption impacts by 15% over results from our first RCT in Uganda. We significantly outperformed this target, achieving 151% higher consumption impacts—a 10X increase over expectations. This remarkable result was driven by impacts in Kenya.
Where can I learn more about the Village Enterprise DIB?
To learn more about the Village Enterprise Development Impact Bond, visit our DIB results page or explore the full IDinsight report. You can also read our feature on Devex or discover how we’re using innovative financing to end extreme poverty in rural Africa.