Interesting Numbers:
Notes & Derivation For Data Used
In order to assess the distribution of outcomes funds money deployed to developed versus less-developed countries, INDIGO’s deployed outcomes funds data was combined with the 2022 UN Human Development Index (the latest year for which full data was available). The HDI index for each of these countries was appended to the total outcomes funds deployed. The US dollar (USD) was used for standardisation.
The calculations show that significantly more outcomes funds dollars have been deployed in wealthy nations to date as compared to poorer ones ($545M to countries with a HDI of ‘very high,’ the top classification vs. only $50M deployed in countries with a HDI of ‘high’ or lower). By comparison only $5M worth of outcomes funds have been deployed to date in countries with a HDI status of ‘medium’.
![](https://impactdatabase.org/wp-content/uploads/2024/06/outcomes_thumb-1024x536.png)
More than 90% of outcome fund dollars deployed to date have gone to more developed countries
(As assessed by their ranking in the 2022 Human Development Index).
While these numbers will likely shift during this year as more projects come online on the African continent, they show that, to date, outcomes funds have primarily been adopted in wealthier nations. Two factors account for this: the fact that the UK (a wealthy nation) has been the most active user of this instrument to date (by monetary value) with $347M deployed. But equally (and more problematically) the relative paucity of projects deployed into less developed nations.
The percentages tell a more interesting story than the figures: 92% of funds were deployed into countries with the highest HDI tier of ‘very high’ (HDI of > 0.8). To meet their oft-stated aim of making development finance more efficient, outcomes funds need to step up their efforts in the poorer parts of the globe.
Outcomes Funds Need More Geographical Reach Too
Number of countries with active outcomes funds
(INDIGO, March 2024)
According to the dataset, to date, outcomes funds have been deployed in 10 countries worldwide.
Clearly, this constitutes a slim minority of the world’s nations. For outcomes funds to make a meaningful contribution to global aid challenges, they are going to have to increase in geographical breadth.
About Outcomes Funds
Outcomes funds are pools of grant capital which are typically deployed to target specific development challenges. Commonly, they mix philanthropic and government money.
![](https://impactdatabase.org/wp-content/uploads/2024/06/Outcomes-Funds-Are-Pools-Of-Grant-Capital-1024x341.png)
INDIGO – which has done more than any other body to map the evolution of outcomes-based finance approaches – notes that there is, to date, no universally agreed definition of what constitutes an ‘outcomes fund’.
Tellingly, however, they include the willingness to consider (for profit) impact investing as one of three fundamental characteristics.
In other words, the defining quality of outcomes funds is less their constitution of capital sources and more their focus on outcomes-based finance (pay for success) and their tendency to focus on thematic approaches (such as ensuring basic literacy in less developed nations). The latter is almost inherent to their design: to focus on achieving ‘outcomes,’ they need to be defined. By doing so, groups of donors and impact investors with aligned focuses can be brought together.
Stratifying outcomes funds deployments by HDI in this manner highlights the need for outcomes funds to both increase in geographic breadth and ensure that more capital is mobilised towards emerging markets and developing economies (EMDEs).
The finding accords with a key recommendation for capital mobilisation articulated by GSG Impact in their 2023 State of Play Report.
About The Data Source
INDIGO outcomes funds dataset
Import date: 14/03/2024
This dataset is intended to track deployed outcomes funds. The conversion to US dollars (USD) was made at the time the dataset was originally compiled. In future analyses, live FX rates will be added to the INDIGO data.
The Methodology Applied
The data was filtered according to the country
variable and grouped on the sum of total outcomes value USD)
variable.
You can use this query to replicate the process in SQL:
SELECT totaloutcomesvalue_usd, fund_country FROM deployed_funds ORDER BY totaloutcomesvalue_usd DESC, fund_country;
Outcomes Funds Deployed By Human Development Index (HDI) Tier
The 10 countries with active outcomes funds according to the INDIGO data were in turn stratified into developed and less-developed countries according to the 2022 HDI.
Total Outcome Funds Deployed By Country (With HDI Tier)
wdt_ID | wdt_created_by | wdt_created_at | wdt_last_edited_by | wdt_last_edited_at | Country | HDI (2022) | Funds Deployed (USD) | HDI Tier |
---|---|---|---|---|---|---|---|---|
1 | daniel | 06/06/2024 08:57 PM | daniel | 06/06/2024 09:01 PM | United States of America | 0.927 | 100,000,000 | Very high |
2 | daniel | 06/06/2024 08:57 PM | daniel | 06/06/2024 09:32 PM | United Kingdom | 0.940 | 346,667,863 | Very high |
3 | daniel | 06/06/2024 08:57 PM | daniel | 06/06/2024 09:00 PM | South Africa | 0.717 | 31,000,100 | Very high |
4 | daniel | 06/06/2024 09:02 PM | daniel | 06/06/2024 09:02 PM | Ghana | 0.602 | 25,000,000 | Medium |
5 | daniel | 06/06/2024 09:03 PM | daniel | 06/06/2024 09:03 PM | Sierra Leone | 0.458 | 20,000,000 | Medium |
6 | daniel | 06/06/2024 09:03 PM | daniel | 06/06/2024 09:03 PM | France | 0.910 | 23,521,000 | Very high |
7 | daniel | 06/06/2024 09:04 PM | daniel | 06/06/2024 09:04 PM | Portugal | 0.874 | 22,312,000 | Very high |
8 | daniel | 06/06/2024 09:04 PM | daniel | 06/06/2024 09:04 PM | Australia | 0.946 | 20,639,700 | Very high |
9 | daniel | 06/06/2024 09:05 PM | daniel | 06/06/2024 09:05 PM | Colombia | 0.758 | 5,287,930 | High |
10 | daniel | 06/06/2024 09:05 PM | daniel | 06/06/2024 09:05 PM | Netherlands | 0.946 | 1,149,600 | Very high |
Country | HDI (2022) | Funds Deployed (USD) | HDI Tier | |||||
∑ = 595,578,193 | ||||||||
Average 59,557,819.3 |
Total Outcome Funds Deployed By HDI Tier
wdt_ID | wdt_created_by | wdt_created_at | wdt_last_edited_by | wdt_last_edited_at | HDI Tier | Total Funds Deployed (USD) |
---|---|---|---|---|---|---|
1 | daniel | 06/06/2024 09:19 PM | daniel | 06/06/2024 09:37 PM | Very high | 545,290,263 |
2 | daniel | 06/06/2024 09:19 PM | daniel | 06/06/2024 09:36 PM | High | 5,287,930 |
3 | daniel | 06/06/2024 09:19 PM | daniel | 06/06/2024 09:37 PM | Medium | 45,000,000 |
5 | daniel | 06/06/2024 09:21 PM | daniel | 06/06/2024 09:37 PM | Very high + high | 550,578,193 |
HDI Tier | Total Funds Deployed (USD) |
![](https://impactdatabase.org/wp-content/uploads/2024/05/daniel_rosehill.jpg)
Daniel Rosehill created the Impact Database (ImpactDB) in March 2024 as a data publishing platform to share analysis and insights into impact-relevant data.
Daniel’s foray through the world of impact kicked off when he began working as the communications manager for Sir Ronald Cohen, a notable figure in the world of impact investing.
Prior to this adventure, Daniel managed communications on behalf of companies in the technology sector (IoT, political technology) in Ireland (where he was born) and in Israel (where he lives now).