To realize Agenda 2030, aid agencies, private philanthropies, and their partners in the Global South need better data to monitor how official development finance (ODF) dollars advance the Sustainable Development Goals (SDGs) and avoid missing the mark. In this report, we summarize the results of a novel effort to tag and analyze 2.7 million ODF projects between 2010-2021 using machine learning to understand their contributions to the SDG thematic areas at a goal and target level. This time frame is instructive: it compares the last six years of the Millennium Development Goals era and the first six years of the new SDG age, from early optimism to later uncertainty about the resilience of the agenda to drive collective commitments amid unanticipated global shocks.
How did development donors deploy limited resources and attention in the face of the breath of the SDGs agenda?
Donor financing of the goals has been far from equitable, creating winners and losers. Good health and well-being (SDG3) and zero hunger (SDG2) were donor darlings. Peace, justice, and strong institutions (SDG16) attracted 128 times the number of projects compared to those protecting life below water (SDG14). The average project focused on affordable and clean energy (SDG7) attracted nearly 16 times the funding of a comparable project supporting gender equality (SDG5).
Donor financing increased over the twelve-year period, but there was more continuity than broadening in focus. Roughly a quarter of all ODF dollars went to non-SDG-related activities before and after adopting Agenda 2030. In both time periods, donors prioritized health, jobs, institutions, human capital, and the built environment—each of which received between 8-16 percent of SDG-linked financing. Gender equality and the environment were more resource-constrained, with related goals garnering less than 2 percent of financing.
Donors were not monolithic in their financing for the goals: they typically fell within one of four categories. Large European bilaterals and multilaterals were agenda boosters, prioritizing financing to advance the SDGs agenda writ large. Specialized multilaterals and vertical funds were goal promoters, focusing their efforts to crowd-in resources and attention to aid progress in their preferred sectors. The remaining donors spread their financing across numerous goals (aid generalists) or a small subset of goals (aid specialists).
How resilient are the SDGs as a unifying agenda for development in the face of global shocks like COVID-19?
The COVID-19 pandemic affected three areas of the SDGs disproportionately. Donors doubled down on good health (SDG3), no poverty (SDG1), and strong institutions (SDG16). Environmental goals attracted higher than expected funding. Equity-oriented goals (gender equality, SDG5 and reduced inequalities, SDG10) experienced a slight leveling off in funding levels. But three areas saw much lower levels of funding than expected based upon historical trajectories: affordable and clean energy (-US$12 billion), sustainable cities (-US$5.5 billion), and economic growth (-US$3.6 billion).
Thirty-seven percent of donors may have fully “adopted” Agenda 2030 priorities for their financing, but nearly one-fifth of peers are “detaching” from the SDGs. Adopters—including several large bilaterals (Japan, France), philanthropies (Gates Foundation), and multilaterals (Asian Development Bank, European Union)—gave a growing amount of funding towards the SDGs in absolute terms and relative to non-SDG activities. Comparatively, the 15 detachers (including the U.S., IMF, and Denmark) gave less money to SDG-themed activities after 2015 than before and this represented a declining share in their overall portfolio.
To what extent does financing for the SDGs vary by geography, and which countries are on track versus at risk of being left behind?
Regional funding for the goals varies substantially by region, and low-income countries are at greatest risk of falling behind. SDG-focused donor financing is not only moving away from the poorest places, but this shift has accelerated since the SDGs were adopted in 2015. In 2010, low-income countries (LICs) attracted US$1.54 for every US$1 for lower-middle income countries (LMICs) in SDG-related ODF. By 2021, this ratio dropped by 32 percent: US$1.05 to US$1.
This report was prepared by Bryan Burgess, John Custer, and Samantha Custer. Sarina Patterson designed the cover. Brook Lautenslager and Andrew Bengston built the autocoding tool that made this dataset possible. Ana Horigoshi provided her review and contextual insights, and Jennifer Turner contributed advice and foundational work on previous iterations of the SDG methodology. AidData’s team of student Research Assistants played a critical role in collecting underlying data for this analysis, including: Elinor Lucy Augustine, Andrea Chavez, Kira Ciccarelli, Colin Cochran, Matthew Crittenden, Alaina Dulaney, Kimberly Ferguson, Julia Filan, Emma Freiling, Anna Gleason, Amy Hilla, Hayley Hubbard, Joseph Nameth, Amy Nelson, Morgan Pincombe, Sydney Scafidi, Darrien Spitz, Aba Tieku, Madeleine Walker, Afomia Wendemagegn, and Kathryn Ziccarelli. The findings and conclusions of this report are those of the authors alone and do not necessarily reflect the views of our funders, partners, or other contributors.
Burgess, B., Custer, J., and S. Custer. Financing Agenda 2030: Are international aid donors walking the talk or missing the mark on the Sustainable Development Goals? (2023). Williamsburg, VA: AidData at William & Mary.
Figure 1. Average size versus number of disbursements, 2010-2021
Figure 2. SDG-classified funding, 2010-2021 7
Figure 3. How did proportional allocation to each SDG change after Agenda 2030 was adopted? 9
Figure 4. How might COVID have affected funding levels? 14
Table 1. Donors by funding tier
Figure 5. Post-2015 funding growth versus pre-SDG era alignment 18
Figure 6. Post-2015 changes in SDG funding growth versus prioritization 19
Figure 7. Depth versus breadth: Do donors focus on few or many goals as funding changes? 24
Figure 8. Regional view: Funding per goal 27
Figure 9. Progress since 2010? A widening chasm for low-income countries 32
Figure 10. SDG-focused aid versus GDP growth 33
Figure 11. Funding gap: SDG-focused aid versus estimated need 36
List of Acronyms
AsDB: Asian Development Bank
AfDB African Development Bank
ADF African Development Fund
AFESD Arab Fund for Economic and Social Development
BADEA Arab Bank for Economic Development in Africa
CDB Caribbean Development Bank
CEB Council of Europe Development Bank
CIF Climate Investment Funds
CRS Creditor Reporting System
DAC Development Assistance Committee
EBRD European Bank for Reconstruction and Development
EU European Union
FAO Food and Agriculture Organization
GAVI Gavi, the Vaccine Alliance
GCF Green Climate Fund
GDP Gross Domestic Product
GEF Global Environment Facility
GGGI Global Green Growth Institute
GNI Gross National Income
HIC High-Income Countries
IsDB Islamic Development Bank
IADB Inter-American Development Bank
IAEA International Atomic Energy Agency
IBRD International Bank for Reconstruction and Development
IDA World Bank Group’s International Development Association
IFAD International Fund for Agricultural Development
ILO International Labour Organization
IMF International Monetary Fund
KOICA Korea International Cooperation Agency
LICs Low-Income Countries
LMICs Lower-Middle Income Countries
MDGs Millennium Development Goals
NDF Nordic Development Fund
ODA Official Development Assistance
ODF Official Development Finance
OECD Organization for Economic Co-operation and Development
OOF Other Official Flows
OSCE Organization for Security and Co-operation in Europe
PEPFAR the U.S. President’s Emergency Plan for AIDS Relief
SDGs Sustainable Development Goals
SCA South and Central Asia
SSA Sub-Saharan Africa
UN United Nations
UNCTAD United Nations Conference on Trade and Development
UNDP United Nations Development Programme
UNECE United Nations Economic Commission for Europe
UNEP United Nations Environment Programme
UNFPA United Nations Population Fund
UNHCR United Nations High Commissioner for Refugees
UNICEF United Nations Children's Fund
UNRWA United Nations Relief and Works Agency for Palestine Refugees in the Near East
WFP World Food Programme
WHO World Health Organization
Halfway through Agenda 2030’s fifteen-year run, remarkably little is known about whether donors are walking the talk in aligning official development finance (ODF) [1] dollars with rhetorical commitments to realizing the 17 Sustainable Development Goals (SDGs). Previous studies have profiled the extent to which individual organizations have shifted their strategies in response to the SDGs agenda, or examined changes in specific project portfolios or sectors. While these context-specific studies generate useful insights, they are insufficient to provide broad-based comparability across donors, countries, and goals to understand how well the development industry as a whole has risen to the challenge of Agenda 2030.
High-profile commitments and ambitious strategies are not enough to ensure that low- and middle-income countries are on track to realize the Global Goals. As a case in point: the annual financing gap for the Global South to achieve the SDGs has actually grown to over US$4 trillion (up from US$2.5 trillion in 2014), according to UNCTAD estimates (UNCTAD, 2022; UNCTAD, 2014). Dennis Francis, President-elect of the 78th Session of the UN General Assembly, has charged member states with the imperative to “deliver the future we want by regaining the lost momentum and accelerating action towards sustainable development” (Francis, 2023).
Although the public and private sectors have developed a wide range of tools for financing sustainable development, traditional ODF will play a critical role in both regaining momentum and accelerating action for development in the coming years, particularly as anxieties about inflation chill private investment and developing countries recover from multiple economic crises and increasing debt burdens (Saldinger, 2023; OECD, 2023). Unfortunately, as this report will show, only a portion of ODF is targeted towards the sustainable development priorities detailed in Agenda 2030.
Rather than wishful thinking, aid agencies, private philanthropies, and their partners in the Global South need hard data to monitor how ODF dollars are helping countries realize Agenda 2030 and to not miss the mark. To help solve this challenge, AidData developed a novel approach which leverages artificial intelligence to analyze aid activity descriptions, apply thematic tags, and approximate the proportion of ODF dollars contributing toward SDG-themed activities. Our “SDG Autocoder” builds upon a strong foundation of AidData’s previously published methodologies and a corpus of manually tagged historical data which serves as a training dataset (see Box 1).
As a proof of concept, AidData produced a dataset of over 2.7 million SDG-themed coded projects from the OECD CRS database, covering 2010-2021. This time frame provides a crucial look at the last six years of the Millennium Development Goals (MDGs) era and the first six years of the new SDGs age, characterized by early optimism for the goals, followed by dislocation as the international community weathered unanticipated shocks from multiple crises (e.g., COVID-19, the war in Ukraine, rising inflation) which provoked questions about the continued relevance of the SDGs. Taken together, this timeframe allows us to ask whether the SDG framework is sufficiently resilient to drive collective commitments in the new era of persistent crises.
In examining historical financial data over a twelve-year period overlapping the launch of the SDGs agenda in 2015, this report provides data-driven insights on three key questions:
The remainder of this report is organized as follows. Section 2 evaluates total donor financing to each of the SDGs over the past twelve years, examining the disruptive effects of COVID-19 and shifts in revealed priorities between the end of the MDGs era and the beginning of the SDGs era. Section 3 analyzes specific donor portfolios to assess their similarity and their degree of alignment with Agenda 2030. Section 4 compares the distribution of SDG-themed funds across regions and examines the widening SDG funding gap for a selection of low- and middle-income countries. Section 5 concludes with several cross-cutting take-aways.
There have been previous attempts to track how aid financing advances the Sustainable Development Goals. For example, the Organization for Economic Cooperation and Development (OECD) incorporated an SDG tag into its Creditor Reporting System (CRS) (the main aid reporting mechanism for donors in the Development Assistance Committee’s club of advanced economies) in recent years. But this tag is only available in the post-MDG era, such that researchers and policymakers are not able to examine changes in baseline spending between the two development goal eras. Similarly, the SDG Financing Lab team of researchers at the OECD developed a separate novel approach to harness machine learning, training the XGBoost and ULMfit algorithms to code goal-level finance. This approach used the UN descriptions of the goals, numerous UN PDF reports, and hand-coded 380 projects funded by Italy in 2017 (Pincet et al., 2019). Unfortunately, this dataset is no longer sustained and only coded projects to the goal level.
At AidData, we originally piloted a target-level SDG financial tracking methodology, the results of which have been featured in publicly available reports such as Realizing Agenda 2030 (Sethi et al., 2017), Financing the SDGs (Turner, 2019), and Financing the SDGs in Colombia (AidData, 2017). However, this approach was extremely time- and labor-intensive, relying on manual coding from a team of 36 student research assistants supported by AidData staff over a period of two years, which made it difficult to keep the SDG-coded data current with the OECD’s most recent estimates of contemporary aid financing.
Fortunately, our initial manual coding efforts offered an ideal training dataset of 104,000 projects from the OECD CRS database that were already coded with AidData’s SDG financial tracking methodology. With the assistance of AidData’s in-house technology team, we were able to use this hand-coded dataset as a foundation upon which we could leverage machine learning to develop an autocoding tool which uses three deep-learning libraries for maximum accuracy. [2]
Rhetorically, UN member states set the 17 Sustainable Development Goals on equal footing when they adopted Agenda 2030 in September 2015. However, actions speak louder than words, and it is evident that donors’ financing of the goals has been far from equitable. As a case in point: the average project focused on affordable and clean energy (SDG7) attracted nearly 16 times the funding of a comparable project supporting gender equality (SDG5).
Of course, some divergence in the average dollar value of a project is to be expected, as the capital requirements and costs for infrastructure projects are likely higher than those focused in the social sectors. However, there is a fairly large discrepancy in the number of donor-financed projects across the goals. Donors bankrolled 128 times the number of projects related to peace, justice, and strong institutions (SDG16) as they did protecting life below water (SDG14). Figure 1 visualizes the average dollar value per project and the number of funded projects between 2010 and 2021 related to each of the 17 goals. [3] Figure 2 provides a breakdown of donor financing disbursed in each of the 17 goal areas over that same period.
Variations in the average dollar value and number of projects make for a two-track system for achieving the Global Goals. Some goals like good health and well-being (SDG3) and zero hunger (SDG2) are, relatively speaking, donor darlings, in that they attract a larger share of donor financing. Comparatively, lower levels of aid financing to protect the environment or tackle inequalities does not match the rhetorical importance donors have placed on these issues in recent years. Perhaps most sobering of all is the fact that the largest share of donor funding, nearly a quarter of all development assistance dollars between 2010 to 2021, does not appear to be funding any SDG-related activities.
In the remainder of this section, we examine whether and how the focus of international development assistance has changed from the MDGs to the SDGs era (section 2.1) and seek to understand the displacement effect of COVID-19 on financing for the goals (section 2.2).
The resource envelope of ODF dollars increased over the twelve year period of 2010-2021, but the thematic focus of that financing remained largely the same, even with the transition from the eight MDGs [4] to the seventeen SDGs. AidData compared ODF disbursements to SDG thematic areas during the last six years of the MDG era (2010-2015) and the first six years of the SDG era (2016-2021). In both periods, non-SDG aligned funding constituted roughly a quarter of each ODF dollar spent on average—from a high of 29 percent in 2015 to a low of 20 percent in the first few years following the adoption of Agenda 2030, before rebounding to 28 percent of ODF disbursements in 2021. [5] The remaining 75 percent of ODF financing over the period was SDG-aligned and total funding increased for all but two of the goals over time.
Although the architects of the SDGs sought to place the 17 goals on a level playing field, donors clearly had their own revealed priorities when it came to where they focused their money. Examining financing trends in the MDGs and SDGs era, a clear pecking order emerged in terms of the goals that received a larger and smaller share of the ODF funding pie (Figure 3). The priority goals—good health, more jobs, strong institutions, human capital, and the built environment—consistently received between 8 and 16 percent of SDG-linked ODF financing across the two periods. The afterthought goals—focused on basic needs, gender equality, environment, and partnerships for the goals— attracted less than 6 percent of SDG-related financing. Six of these severely resource-constrained goals each garnered under 2 percent.
Before and after 2015, global health and well-being (SDG3) was the best-funded sustainable development goal, [6] accounting for 14 percent of all SDG-aligned finance (US$140 billion) before 2015 and climbing to 16 percent (US$209 billion) in post-2015 spending. Financing in this area likely benefited from continuity in a shared emphasis across the MDGs and SDGs agendas in addressing child and maternal mortality and infectious diseases, along with funding to help countries navigate the COVID-19 pandemic.
Peace, justice, and strong institutions (SDG16) was the second-highest funded goal prior to 2015, attracting 13 percent of total ODF disbursements (129 billion). In the SDGs era, financing for good governance increased in absolute terms but declined somewhat as a relative share of the overall total resource envelope to 11 percent (-2 percentage points). Donors became somewhat more focused on decent work and economic growth (SDG8), which attracted 12 percent of ODF financing in the SDGs era, up from 10 percent prior to 2015. Similarly, zero hunger (SDG2) also gained ground in the post-2015 period, attracting 10 percent of donor financing.
Some critics of Agenda 2030 argue that the goals emphasize economic growth over human and environmental well-being (Hickel, 2019; Eisenmenger et al. 2020). If resourcing levels are indicative of relative importance, then donors have indeed placed lower priority on goals related to human capital and the built environment. Compared to the big ticket investments, the second tier of priorities only received between 4 and 8 percent of ODF funding. Clean and affordable energy (SDG7), each accounting for 9-10 percent of SDG dollars and sustaining this level across both the MDGs and SDGs periods. Quality education (SDG4), along with industry, innovation and infrastructure (SDG9) and sustainable cities (SDG11), each received roughly US$100 billion between 2016-2021, but as a share of overall ODF dollars lost some ground.
Basic needs such as clean water and sanitation (SDG6) and no poverty (SDG1) attracted roughly US$110 million from 2010-2021. Each accounted for approximately 5 percent of the ODF pie throughout the period. Yet, despite attracting similar levels of funding, these two goals had differing levels of prominence from the shift from the MDGs to the SDGs era. Poverty alleviation was arguably more visible within the MDGs as one of only 8 goals as compared to 17. Conversely, clean water and sanitation was initially subordinated as a target under environmental sustainability in the MDGs before it ascended to being a goal in its own right under the SDGs framework. Nevertheless, the relative prominence of these goals appeared to have little bearing on relative financing levels, as poverty attracted a greater share of the pie in the SDG era, while water and sanitation declined by a quarter of a percent.
The twin goals of gender equality (SDG5) and reduced inequalities (SDG10), that seek to usher in a more equitable world, consistently attracted less than 2 percent of SDG financing. Funding to gender equality nearly doubled, from US$9.7 million to US$17.8 million between the two eras, but this only led to a miniscule increase in its share of the total funding pie pre- and post-2015, from 1 to 1.4 percent. Global inequalities also saw a modest increase in its share of SDG funding (from 0.2 to 0.6 percent). To be counted as contributing towards these goals, projects had to be explicitly structured around objectives of gender equality or reducing inequalities, as opposed to only generic references to gender-sensitive implementation or ensuring that benefits accrued to women, as well as men. [7]
Despite increasing political attention and the arrival of dedicated funding facilities, the share of financing for environment and climate issues did not appear to improve from the MDGs to the SDGs era and continued to lag behind other issue areas. Among the environmentally focused goals, Life on land (SDG15) and Climate Action (SDG13) attracted somewhat larger shares at approximately 1.4 percent and 1 percent of financing between 2015 and 2021. Responsible consumption and production (SDG12), along with Life below water (SDG 14) captured the lowest levels of financing of the goals. The apparent financing gap is particularly striking in the case of protecting the oceans: over the most recent six years of data, SDG14 attracted 1.4 billion dollars, or 0.1 percent of SDG funding compared to the estimated 175 billion annually required (Johansen and Vestvik, 2020).
Partnerships for the goals (SDG17) saw the second-largest drop-off between the MDGs to the SDGs era, tapering off from 35.5 billion between 2010 and 2015 to 22.1 billion between 2016 to 2021. This could be linked to a reduction in debt relief programs, or reflect an increasing share of partnership-related funding being directed toward multilateral organizations.
The COVID-19 pandemic set back progress across the SDGs agenda. From eliminating hunger and bolstering education to advancing economic growth and women’s empowerment, most of Agenda 2030’s targets saw hard-fought wins pushed back. As policymakers assess the full repercussions of the crisis on long-term development outcomes, it is worth looking at the initial impact the pandemic has had on inputs toward sustainable development, particularly ODF.
So, what would 2020 and 2021 SDG funding have looked like if the COVID-19 shock didn’t happen? To answer this question, this section calculates the average growth rate of funding to each goal in the five years prior to COVID-19 (2015-2019), estimates a trajectory for what the 2020 and 2021 values would have looked like in the absence of a global pandemic, and then compares these estimates against the actual ODF allocations for each goal in those two years.
Three groups of goals emerge: the accelerated goals (goals attracting a net increase in funding above what was otherwise projected), the displaced goals (goals with a net loss of funding, coming in below what was otherwise projected), and steady state (goals that largely maintained pre-COVID funding levels but were knocked off promising growth trajectories).
With the arrival of the pandemic, international donors went into overdrive in saving lives and protecting vulnerable groups at a precarious moment in time, doubling down on financing for good health and well-being (SDG3) and no poverty (SDG1) (Figure 4). Global donors reversed the declining investments in peace, justice, and strong institutions (SDG16), mobilizing US$7.2 billion more than anticipated in 2020. These funds largely went to help build government capacity to respond to the unprecedented health threat at a time of plummeting government revenues, [8] and dropped off in 2021.
Given historically low levels of ODF financing for environmental goals—relative to other aspects of the SDGs agenda—one might have assumed that these portfolios would be first on the chopping block as donors scrambled to mobilize funds for COVID relief. Yet, financing for climate adaptation and life on land attracted higher than anticipated growth levels in 2020 and 2021, with the goals attracting US$588.8 million and US$1.5 billion above expected levels over these two years, respectively. The ability of these two environmental goals to attract additional funding even in the midst of a global pandemic may speak to growing international recognition of the climate crisis, and the maturation of environment-and climate-specific investment initiatives in recent years.
While there was a net increase in total ODF mobilized in 2020 and 2021, donors appeared to redirect funds that would otherwise have gone to three areas based upon their historical trajectories: affordable and clean energy (US$12 billion below expected), sustainable cities (US$5.5 billion below expected), and economic growth (US$3.6 billion below expected).
Although financing for gender equality and reduced inequalities was not displaced to the degree seen with other goals, there was a leveling off in funding levels in 2020 and 2021 from what had previously been a promising upward trajectory between 2015-2019. Funding to fight hunger initially performed better than expected in 2020 (+2.2 billion), but tapered off again in 2021 (-3.1 billion). This could be an area to revisit as financial data for 2022 and 2023 becomes available and we can assess how donors responded to disruptions in international food chains with Russia’s invasion of Ukraine in February 2022.
The adoption of Agenda 2030 may not have not dramatically shifted ODF funding priorities at a global scale, particularly among the largest international donors. The majority of donors increased funding levels in absolute terms but most were already "generally" aligned with the SDGs when Agenda 2030 was adopted. There was also remarkable consistency in the top donors funding a given goal between the MDG and SDG eras.
This continuity in funding priorities could point to stability in what donors see as their core mission and/or comparative advantage (e.g., the U.S. in health or the World Bank Group in poverty reduction and economic growth), irrespective of expansive global development agendas. Alternatively , this inertia could reflect the outsized influence of the 10 “mega” donors (see section 3.1) on the total funding landscape. Noticeably, the single largest donor remained the same in 10 out of 17 goals between the two periods. Nevertheless, smaller and emerging donors have been more varied in the degree to which their financing appears to have embraced, or ignored, the SDGs as a guiding policy framework.
In this section, we examine how individual donors vary in their financing pre- and post-2015 by assessing: (i) overall size of donors and their respective SDG funding portfolios (section 3.1); (ii) shifts in the volume of SDG-related versus non-SDG funding (section 3.2); and (ii) changes in the composition and distribution of SDG-related funding across the goals (section 3.3).
For this donor-level analysis, we draw upon AidData's Financing the 2030 Agenda for Sustainable Development Dataset, Version 1.0, which includes 83,000 SDG-theme tagged records containing project-level details on 3.2 million disbursements from 157 development partners cumulatively worth US$3 trillion. The dataset offers an unrivaled look at donors' revealed preferences before and after the Global Goals were adopted in 2015. The 89 donors which reported to the OECD’s Creditor Reporting System for both the MDG (2010-2015) and SDG eras (2016-2021) account for US$2.9 Trillion: 98 percent of the funds tracked in the dataset.
There are two different ways to think about the ‘average’ donor: the mean (the total funding divided by the number of donors) versus the media (the middle value of funding when donors are ordered from least to greatest). In terms of financing for development, these two values are highly divergent. The mean donor contributes US$20 billion; however, this is skewed by “mega” donors that each contributed more than US$100 billion between 2010 and 2021. Taken together, the top 10 mega donors accounted for roughly two-thirds of the combined US$2 trillion from all 157 SDG funders during this period.
Table 1 divides donors into four tiers. The first tier, “small” represents donors who are much closer to the median of US$1 billion than the mean of US$20 billion, while the next tier “mid” represents those who are between the median and mean. The “large” tier are those who are close-to or well-above average. As stated above, the "mega" category represents the top 10 donors who each contributed more than $100 billion between 2010 and 2021. In the remainder of this section, we incorporate the four tiers within discussions of donor financing behavior between the MDG and SDG eras (Section 3.2).
Tier |
Thresholds |
Number of Donors |
Total Amount of Funding |
Illustrative Donors |
Small |
$0-2 Billion |
42 |
$19 Billion |
Adaptation Fund, BADEA, Arcadia Fund, Arcus Foundation, Azerbaijan, Bulgaria, CDB, Comic Relief, Hilton Foundation, Croatia, Cyprus, Czech Republic, Estonia, Gatsby, GGGI, Greece, H&M Foundation, Hungary, Iceland, IKEA Foundation, IAEA, Kazakhstan, Latvia, Laudes Foundation, Liechtenstein, Lithuania, Malta, MAVA, MetLife, Montreal Protocol, NDF, OSCE, Poland, Romania, Slovak Republic, Slovenia, Taiwan (referred to as Chinese Taipei in the OECD CRS source data), Thailand, Timor-Leste, UN Peacebuilding Fund, UNECE, UNEP |
Mid |
$2-20 Billion |
28 |
$201 Billion |
AFESD, Austria, Belgium, CIF, CEB, Finland, FAO, GAVI, GEF, GCF, IFAD, ILO, Ireland, Israel, Kuwait, Luxembourg, New Zealand, OPEC Fund, Portugal, Spain, UNAIDS, UNDP, UNFPA, UNHCR, UNICEF, UNRWA, WFP, WHO |
Large |
$20-100 Billion |
19 |
$746 Billion |
AfDB, ADF (AfDB), Australia, Gates Foundation, Canada, Denmark, EBRD, Global Fund, IMF (Concessional Trust Funds), IsDB, Italy, Korea, Netherlands, Norway, Saudi Arabia, Sweden, Switzerland, Turkiye, UAE |
Mega |
$100 Billion or more |
10 |
$1.969 Trillion |
USA, EU, Germany, World Bank (IBRD), Japan, World Bank (IDA), AsDB, UK, France, IADB |
Note: this table records total ODF disbursements, inclusive of both SDG-related and non-SDG related funding.
To what extent are international donors putting their money where their mouth is in increasing financing for Agenda 2030 in absolute terms and as a share of their overall portfolios? In this report, we examine whether and how individual donor funding for the SDGs as a whole (and in relation to non-SDG activities) has changed with the adoption of the new global development agenda. Figure 5 compares the percentage of each donor’s funding that was already aligned with the SDG themes at the end of the MDGs period (2010-2015) with the share at the start of the SDGs period (2016-2021).
Far from monolithic, donors typically fell within one of four categories (Figure 6): adaptation (total SDG funding is growing and outpacing the share of non-SDG funding); alignment (total SDG funding is shrinking but still outpacing the share of non-SDG funding); expansion (total SDG funding is growing but falling behind relative to non-SDG funding), and detachment (total SDGs funding is shrinking and falling behind relative to non-SDG funding). Most donors focused on the SDGs to about the same degree after 2015 as the period before, though there were some noticeable changes. Nineteen donors saw at least a 10 percentage point dip in SDG funding as a percentage of their total portfolio. [9] A roughly similar number, 17 donors, charted at least a 10 percentage point increase in the SDG-related proportion of their total funding. [10]
Thirty-seven percent of donors reporting to the OECD Creditor Reporting System before and after 2015 (33 of 89) appear to have “adopted” Agenda 2030 priorities for their financing. For this group, funding for the SDGs grew in absolute terms and outpaced non-SDG funding as a share of overall resource flows. This group is diverse in profile, including large bilaterals (e.g., Japan, France, and Korea), multilateral organizations (e.g., Asian Development Bank, European Union, IADB, and Islamic Development Bank), high profile private philanthropies (e.g., Bill & Melinda Gates Foundation), along with smaller players like Kuwait and Lithuania.
However, these donors do share a common attribute: each has explicitly incorporated the SDGs into their core policy frameworks—from incorporating the SDGs within operating guidelines [11] to conducting voluntary national reviews, to even doing both (e.g. Lithuania). [12] In some cases, goal-specific imperatives have also been effective. For example, the Asian Development Bank’s 2021 update of its Energy Policy explicitly focused its energy programs on alignment with affordable and clean energy (SDG7), which make up a significant portion of its external funds (AsDB, 2021).
Seven donors—including the Netherlands, Finland, Spain, Portugal, and the Organization for Security Cooperation in Europe (OSCE)—were somewhat anomalous compared to their peers in other categories. On the one hand, these donors invested less money in SDG-related projects in 2016-2021 than they did in 2010-2015. However, as a share of their overall financing, non-SDG activities fared even worse, increasing the relative emphasis on SDGs in their portfolio.
Dutch development aid faces close political scrutiny and the total official development assistance (ODA) envelope has shrunk in the face of budget cuts and a push to report in-country climate and refugee spending against their 0.7 percent target (OECD, 2017). This negatively impacted SDG financing in absolute terms, as the Netherlands disbursed 1.1 billion less to SDG-related projects post-2015 than in the six years prior. Nevertheless, it is apparent that the Dutch government still prioritized what funds it had available to advance the SDGs as a core part of the Dutch development agenda even amid budget pressures for non-SDG funding saw larger cuts (1.8 billion) over the same period.
Rather than adopting the entirety of the SDGs agenda, the OSCE is more of a single issue organization that closely aligns with the SDG16 focus on peace, justice, and strong institutions. While the OSCE’s ODA disbursements steadily dropped for most of the past decade, its expenditures on SDG-themed peace and security activities declined more slowly than multi-sector or administrative costs. Interestingly, the OSCE has taken a different track than the Netherlands in that the former has not enshrined the SDG framework within its guiding policy documents (OSCE, 2013, 2014, 2019; UNECE, 2011). Instead, the OSCE has referenced its contributions to peace and institution building, the commonalities between its mandate and Agenda 2030, and a commitment to sustainability in a broader sense, such as through a number of MDG-era energy efficiency projects.
Thirty-eight percent of donors (34 of 89) increasingly channeled more funding to support the SDGs but this has not yet eclipsed the proportion of their portfolios focused in other areas. This includes a mix of emerging donors (e.g., Estonia, Saudi Arabia), along with established DAC bilaterals (e.g., Canada, Germany, Italy, New Zealand, the United Kingdom), regional multilaterals (e.g., the AfDB, EBRD), among others. A commonality across these donors is a large historical emphasis on humanitarian refugee relief (important, but beyond the scope of the SDGs which deals with longer-term development issues).
Many donors in this cohort referenced the SDGs in sustainability-focused fora or publications, but the agenda does not appear to have been formally mainstreamed within their strategies and operations. The Saudi Vision 2030 does not explicitly reference the SDGs, in part or in whole, but the emphasis on environmental and economic sustainability is aligned with the intent of Agenda 2030 (Kingdom of Saudi Arabia, n.d.). New Zealand conducted a voluntary national review in 2019, but also expressed a commitment to not add further bureaucracy in its aid program (New Zealand MFAT, n.d.). In the case of Canada, other considerations, such as the merger of the Canadian International Development Agency into Global Affairs Canada, may have taken precedence and inadvertently slowed the formal adoption of Agenda 2030. Even though the Canadian government conducted a voluntary national review in 2018, its Federal Implementation Plan for the SDGs was only published in July 2021 (Government of Canada, 2021).
If financial allocations are reflective of donors’ true priorities, then nearly a fifth of donors (15 of 89) appear to be detached from the SDGs agenda. Representing a diverse group of donors, this cohort gave less money to SDG-themed activities in the post-2015 period than prior and this represented a declining share in their overall portfolio relative to non-SDG activities. Some, like the United States, pursued development strategies consciously distinct from the SDGs for much of the post-2015 period. Others, like the International Monetary Fund, have funding consisting of large, non-sector allocable loans. The United Arab Emirates contributes large funds to humanitarian activities, but also restricts its reporting to the CRS to the extent that this methodology likely underestimates its contributions to SDG areas.
Interestingly, some DAC members that rhetorically made the SDGs central to their development policy agendas, most notably Denmark, also appear within this cohort. The Danish Strategy for Development Cooperation and Humanitarian Action, The World 2030, is directly built on the SDGs, yet Danish disbursements to SDG activities declined by US$1.1 billion after 2015, while the same six years saw Denmark channel US$1.4 billion dollars more to non-SDG activities than in the closing years of the MDG era. Donors incorporating Agenda 2030 into their policy frameworks appears to be helpful, but not sufficient, for focusing development assistance on the 17 goals.
The breadth of the SDGs agenda—17 goals and 169 targets—has been both an attraction and detriment of the ambitious development agenda since its inception. This raises a critical question: to what extent do international donors go deep in focusing their attention on a subset of the agenda versus going broad in attempting to bankroll projects across all the goals?
To answer this question, we examined how “evenly” ODF donors distributed their financing across the 17 goals, [13] comparing the end of the MDGs period (2010-2015) as a baseline versus the start of the SDGs period (2016-2021). We also examined whether there are observable differences in donors’ allocation behavior based upon differences in how SDG funding is allocated.
Donors typically fell within one of four categories: agenda boosters (proportional growth in SDG funding broadly distributed across the goals); goal promoters (proportional growth in SDG funding, narrowly distributed); aid specialists (proportional increase in non-SDG funding, while SDG funding is narrowly distributed across the goals); and aid generalists (proportional increase in non-SDG funding, which is while SDG funds are broadly distributed).
Figure 7 visualizes the change in SDG related finances between the two periods and a measure of variance for how evenly this financing is distributed across the goals for both periods. The change in SDG-financing between the periods represented by the percentage of 2010-2021 SDG funding occurring after the goals were adopted. Juxtaposed with this, the measure of variance in donors' respective SDG funding portfolios, indicates whether donors implicitly favored depth (i.e., higher variance between amounts per each goal indicating a sharper focus on a narrow subset of goals) or breadth (i.e., lower variance between amounts per each goal, indicating a broader emphasis on a wider set of goals.)
Just because a donor is doubling down on financing for the SDGs does not mean that they are doing so in exactly the same way. One cohort of donors—including large European bilaterals (e.g., France, Sweden, Norway), multilateral organizations with wider mandates (e.g., AsDB, EU, IADB), as well as Japan and Korea—appeared to use their financing to advance the SDGs agenda writ large. Consistent with public stances that seek to bolster Agenda 2030 on the world stage, such as sponsoring research and roundtables on progress, these donors channeled more of their money to the SDGs overall and distributed this financing broadly across all of the goals.
Comparatively, other big spenders on the SDGs have adopted more of a niche focus on promoting specific goals, crowding in resources and political attention to progress in their preferred sector. This cohort includes specialized multilaterals and vertical funds—from the health-focused efforts of the UNFPA and GAVI to the food security emphasis of the Food and Agriculture Organization and the Climate Investment Funds’ focus on climate resilience and transformational innovation—as well as private foundations such as the Gates Foundation. Rounding out this goal promoter group are emerging donors with smaller aid programs (e.g., Croatia, Hungary, Kuwait). Either by design or necessity, these donors have focused their efforts on advancing specific subsets of the SDGs agenda rather than going broad.
Interestingly, there was also variation in the allocation behavior of donors whose financing was less focused on the SDGs relative to other sectors and issues as a proportion of their overall portfolios. The difference here seems to be in how these donors deployed the smaller share of their budgets oriented to SDG-aligned activities. Some donors operated as aid generalists, spreading their financing for the SDGs across numerous goals. This group includes “mega” bilaterals (e.g., United States, Germany, United Kingdom), large bilaterals (e.g., Australia, United Arab Emirates) and medium bilaterals (e.g., Belgium, Finland, Ireland). It also includes multilaterals like the International Monetary Fund and the World Bank’s IDA and IBRD, and the Global Environment Facility. The remaining donors—including Greece, the Global Fund, UNAIDS, WHO, and WFP—tended to focus on a specific subset of the goals that either reflect explicit priorities within their stated mandates or the desire to deploy modest resources in a focused way to generate the largest impact possible.
Regions and countries are not monolithic in the blend of domestic resources and donor financing they have available to advance progress towards the SDGs. The extent to which domestic resource mobilization (DRM) is viable as a predominant source of funding for the SDGs increases as a country’s gross domestic product (GDP), and thereby the potential tax base, grows. Countries with high SDG financing needs but lower GDPs can realistically only make a limited dent in SDG funding gaps through DRM, and are therefore more reliant on external assistance (Sachs et al 2018, 2019). [14]
This reality raises several critical questions about the geographic distribution of financing for the SDGs which we examine in this section. To what extent does donor financing for the SDGs vary by geography and income-level? How has donor financing for the SDGs changed in relation to the capacity of countries to raise their own revenues (proxied by GDP)? How much progress has been made on the “ODF portion” of estimated SDG funding gaps?
In this section, we leverage the thematic tagging within AidData's Financing the 2030 Agenda for Sustainable Development Dataset, Version 1.0, to take a harder look at where donor financing for the SDGs is going relative to need. We assess differences and similarities in SDG financing by region and country (section 4.1) and examine the widening SDG funding gap for a selection of 59 low- and middle-income countries (section 4.2).
The sustainable development agenda is commonly referred to as the “Global Goals,” but this obscures differences in how donors distribute financing across regions, likely due to a combination of their own priorities and that of their counterparts in low- and middle-income countries. For example, good health and well-being may be the largest goal overall, but this is driven by huge investments in Sub-Saharan Africa (SSA). Elsewhere, donors directed funding to sustainable cities or economic growth. Financing within regions also varies, with larger nations receiving the lion’s share of resources, potentially at the expense of the smallest and most vulnerable countries (Figure 8).
SSA was not only the largest recipient of official development financing overall but also specific to the SDGs. At the individual goal level, donors disbursed more ODF funding to SSA than any other region between 2010 and 2021 for 10 of 17 SDGs: partnerships for the goals (49 percent of SDG17 funding), zero hunger (44 percent of SDG2 funding), good health and well-being (42 percent of SDG3 funding), gender equality (36 of SDG5 funding), and reduced inequalities (32 percent of SDG10 funding). Strikingly, SSA attracted more funding for health (SDG3) than all other geographic regions combined. [15]
Health-focused programming accounted for roughly one-fifth of SSA’s total SDG funding (US$147.1 billion out of US$624 billion), dwarfing other aspects of the agenda. Funding was driven by programs that began in the MDGs era in line with MDG6 to combat HIV/AIDS, malaria, and other diseases: US$54.6 billion related to PEPFAR (the U.S. President’s Emergency Plan for AIDS Relief) and US$30.2 billion from the Global Fund to Fight AIDS, Tuberculosis, and Malaria.
SDG financing in South and Central Asia (SCA) focused on two key themes: sustainable cities (SDG11, US$52.1 billion), along with affordable and clean energy (SDG7, US$50 billion). Likely reflective of the region’s emphasis on urbanization and infrastructure-led development, SCA countries captured roughly a quarter of each ODF dollar spent globally on sustainable cities and energy investments.
Despite novel smart city initiatives from the EU and France, Japan (US$17.8 billion) bankrolled the largest share of SDG11-type investments in the region between 2010 and 2021 (AFD, 2019). Japan has had a long-standing interest in promoting sustainable cities as part of its core strategies to combat pollution and support infrastructure, initially in East Asia and Pacific and then farther afield, since 1997 (MOFA Japan, 1997).
The Asian Development Bank (AsDB) was a major financier of affordable and clean energy projects in the SCA region to the tune of US$16.5 billion between 2010 and 2021. In fact, 21 percent of all AsDB lending was deployed to energy projects between 2009 and 2021, in line with established strategies in place since the MDGs era and reaffirmed in the era of the SDGs (AsDB, 2021). [16]
Countries in the Western Hemisphere received a larger share of total global environmental and climate resilience funding, compared to other regions. [17] However, environment and climate-related goals still trailed many other priorities in the region. SDG financing to the Western Hemisphere was more heavily driven by: economic growth (US$48 billion for SDG8) and peace, justice and strong institutions (US$46 billion for SDG16).
Even within regions there can be noticeable differences and one’s that may raise questions about the extent to which donor SDG financing is directed to areas of greatest need. For example the 16 Small Island Developing States of the Caribbean are at the frontline of climate change risks, and in need of significant investments in resilience (UN, n.d.). Nevertheless, it is the largest states in the region—Mexico (34 percent) and Colombia (12 percent)—that capture the lion’s share of the US$5.8 billion of climate change funds. Just under half a billion (US$479.8 million) was directed to regional funds to be spread across the smaller states of the Caribbean and Central America.
Eleven percent of SDG funding in East Asia and Oceania was oriented towards sustainable cities (US$44.7 billion for SDG11). Notably, the region attracted roughly one-fifth of global funding for this goal. As in SCA, sustainable cities funding was led by Japan (US$13.3 billion) and the AsDB (US$11.1 billion). Due to KOICA’s limited reporting, US$37.9 billion of the funds disbursed by Korean development agencies cannot be attributed to specific SDGs, but likely contributes significant volumes to each of the SDGs including SDG11.
East Asia and Oceania leads all other regions in funding directed to life below water (SDG14), though this only amounted to US$636.9 million dollars (less than 0.2 percent of all funding to the region). As with the Western Hemisphere, this financing was directed to larger nations: the Philippines, Indonesia, and Vietnam accounting for nearly three-quarters of those funds (US$469.3 million). Despite being home to 13 of the 38 Small Island Developing States, East Asia and Oceania trails the Western Hemisphere in climate resilience funding (US$4.9 billion versus US$5.8 billion). This total accounted for only 1.2 percent of all funding to the East Asia and Oceania region.
Funding to Europe & Eurasia was centered on economic growth goals, led by industry, infrastructure and innovation (US$38.7 billion to SDG9) and economic growth (US$32.2 billion to SDG8). EU Institutions directed the largest volume of funds to the region’s progress on industry (US$17.1 billion) and the European Bank for Reconstruction and Development did the same on economic growth (US$12.8 billion). Germany, Europe’s largest bilateral donor, was not as active in the region for these economic growth goals, instead focusing on the social sector (education, zero hunger) and directing its economic growth funding toward other regions.
Externally driven ODF is arguably most critical in countries where the ratio of SDG funding needs to GDP is higher (Sachs et al. 2018, 2019; Kharas and McDonald, 2019). Donors recognize this and have responded when countries in crisis experience a decline in government revenues. As a case in point, when low- and middle-income countries experienced declining domestic revenues in 2020 amid the COVID-19 outbreak, the spike in ODF that same year was in part driven by donors stepping in to help meet this shortfall (OECD, 2022).
Unfortunately, SDG-focused donor financing has continued to move away from the poorest places, even after SDGs were adopted in 2015 (Figure 9). In 2010, low-income countries (LICs) attracted US$1.54 for every US$1 for lower-middle income countries (LMICs) in SDG-related ODF. By 2021, this ratio dropped by 32 percent: US$1.05 to US$1.
Figure 10 visualizes the rise in GDP growth in LICs and LMICs since 2010 (as a proxy of DRM potential), compared with donor SDG financing directed to each country cohort. LICs experienced 49 percent growth in their GDPs on average over the period, compared with only 15 percent growth in donor SDG financing. During the same period, LMICs charted 59 percent growth in their GDPs and even higher growth in donor SDG financing (69 percent). In short, LMICs pulled farther ahead of LICs not only in their DRM potential, but also in attracting more SDG funding from external donors.
It should be noted that these figures only consider ODF as reported to the OECD Creditor Reporting System. Unreported sustainable development finance, such as that from the People’s Republic of China (PRC) or private sector actors, likely understates the total resource envelope of available funding during this period. [18] That said, donors still have a responsibility to align their resourcing with their rhetoric of leaving no one behind. [19]
Prior to the COVID-19 pandemic, Sachs et al. (2018) estimated that LICs and LMICs needed to mobilize additional resources worth 19 and 8 percent of their annual GDPs, respectively, to overcome gaps in available SDG financing. [20] This implies an SDG-funding gap for these 59 countries of US$363 billion per year (in USD 2020). [21] In a follow-up study, Sachs et al. (2019) estimated an even larger total SDG funding gap of US$483 billion (in USD 2020). For a similar cohort of countries, Kheras & McArthur (2019) project the public spending gap at over $700 billion by 2025, including ODF and other forms of financing. [22]
Closing this funding gap will ultimately require a mix of domestic resources, blended finance, global taxes, and public and private development assistance. In the short- and medium-term, however, ODF has outsized importance particularly in countries with more limited DRM potential (due to smaller GDPs) and greater difficulty attracting private sector capital due to creditworthiness. For this reason, we refer to the SDG funding shortfall as the “ODF portion.”
Extending and adapting the GDP-based method from Sachs et al. (2018) study to additional years, [23] reveals a sobering estimate that we are hundreds of billions of dollars off-track in filling the SDG financing hole. Figure 11 visualizes the proportion of donor SDG financing for LICs and LMICs from 2010 to 2021, compared to estimated funding needs. [24] During this period, we estimate that increased donor SDG financing only closed the funding gap by 9 percentage points (from 75 percent unmet need in 2010 to 66 percent in 2021). Over the entire 12-year period, this corresponds to a mere 3 percent per year average increase—even before factoring in COVID-19 related displacements.
There are two important caveats to keep in mind when interpreting these results. First, the “needs estimate” and the “funding gap” do not take into account shifts in trajectory related to COVID-19. [25] Second, previous studies only examine SDG costs after 2015, while we extended this back to 2010 as a baseline. [26] Since SDG costing exercises are rough estimates, taking heuristics that were valid in 2018 and asserting their relevance back to 2010 is arguably one of the least contorted methods to gauge how ODF has (or has not) met the needs of its portion of the SDG financing gap. [27]
Examining actual official development finance allocations between the last five years of the MDGs era versus the first five years of the SDGs era, Agenda 2030 does not appear to be the paradigm-shifting vision donors had hoped for. In several areas, donors stuck to their old playbooks dating back to at least the MDGs era if not before. The broadening of the agenda from the MDGs to the SDGs did not catalyze a commensurate change in the focus of donor spending. Health, governance, and economic growth still capture the lion’s share of aid financing, while inequality and environmental agendas remain under-resourced. Non-SDGs activities still attracted over a quarter of ODF, just as they did before the adoption of the Global Goals in 2015.
The MDGs were criticized for being overly technocratic (OHCHR, 2008), but the SDGs era has yet to see a substantive realignment of aid funding to the countries and sectors that need it the most. Lower-middle income countries are on track to attract more ODF dollars than low-income countries, putting the latter at a greater risk of falling behind in the face of a widening gap between donor spending versus local financing needed to achieve the SDGs. Funding for the goals varies by region, and smaller countries are often sidelined in favor of larger countries. In responding to unpredictable global shocks like COVID-19, donors put longer-term development goals on pause, shifting money from infrastructure and economic growth to immediate needs of health, poverty, and governance.
Yet, there are also areas for optimism. Donor financing pre-2015 was already reasonably well-aligned with the Global Goals and continued in that vein in the first five years of the SDGs era, particularly in the consistent emphasis on global health, protecting international peace, and creating economic opportunity. Donors that mainstreamed Agenda 2030 goals and targets in their development strategies were more likely to align financing with the SDGs. Specialized donors used the language of the SDG Agenda to crowd in more funding for their focus areas, and several emergent (often private sector) donors are positioning themselves in the gaps that the largest funders overlook.
The very existence of the SDGs agenda is itself a remarkable achievement. The global community had the ambition to imagine a broad set of targets to make a better world by 2030. Yet, over halfway into implementation, it is clear that more is required for the development community to scale the challenges ahead. Certainly, increasing the volume of ODF available through urging more donors to realize the OECD’s recommended 0.7 percent of GNI target is a worthy goal (OECD, 2016). Yet, to close the SDGs financing gap, we must not only ask how much aid is provided but also where it goes.
Are donors walking the talk or missing the mark? We hope that this report, along with the supporting methods and data, will help leaders in the Global North and Global South assess the current state of play, identify course corrections, and make informed choices about where to focus future investments to advance the SDGs in both word and deed.
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A1 Appendix 1: Context-setting, Total Disbursements as % of GDP
Though the total volume of finance reported into the OECD CRS database has expanded since 2012, it has remained static as a percentage of GDP. The only major jumps in the past decade were a result of the response to the COVID-19 pandemic, and this appears to be a one time jump rather than sustained improvement.
Year |
Global GDP, USD Millions |
Total OECD Member GDP, USD Millions |
Total ODF Disbursements, USD Millions |
ODF percent of Global GDP |
ODF percent of total OECD GDP |
2010 |
70,410,102 |
46,936,537 |
212,151 |
0.30% |
0.45% |
2011 |
72,740,904 |
47,813,276 |
194,761 |
0.27% |
0.41% |
2012 |
74,711,586 |
48,476,163 |
191,712 |
0.26% |
0.40% |
2013 |
76,809,378 |
49,212,170 |
215,066 |
0.28% |
0.44% |
2014 |
79,182,859 |
50,241,900 |
216,335 |
0.27% |
0.43% |
2015 |
81,620,558 |
51,464,903 |
256,742 |
0.31% |
0.50% |
2016 |
83,907,532 |
52,405,503 |
265,617 |
0.32% |
0.51% |
2017 |
86,747,772 |
53,712,460 |
270,809 |
0.31% |
0.50% |
2018 |
89,597,902 |
54,977,127 |
273,521 |
0.31% |
0.50% |
2019 |
91,919,644 |
55,934,444 |
275,886 |
0.30% |
0.49% |
2020 |
89,055,976 |
53,564,981 |
319,671 |
0.36% |
0.60% |
2021 |
94,283,365 |
56,449,490 |
333,242 |
0.35% |
0.59% |
Note: OECD GDP is calculated from the GDPs of Australia, Austria, Belgium, Canada, Chile, Colombia, Costa Rica, Czechia, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Japan, Republic of Korea, Latvia, Lithuania, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovenia, Spain, Sweden, Switzerland, Turkiye, United Kingdom, and United States. Financial amounts are in constant 2020 USD. Source: Burgess, B., Bengtson, A., and B. Lautenslager. (2023). Financing the 2030 Agenda for Sustainable Development, Version 1.0. Williamsburg, VA. AidData. Accessed at https://aiddata.org/sdg.
A2 Appendix 2: Overview of Finance to the 17 Goals
This table shows the average size of a project linked to each of the 17 goals via average dollar value of disbursement, the total number of projects with activities related to the targets of each goal, and the total financing disbursed by donors to projects linked to each goal between 2010 and 2021.
SDG |
Average Project Disbursement, USD Millions |
Funded Project Count |
Total Disbursement, USD Billions |
1: No Poverty |
0.95 |
118610 |
112.17 |
2: Zero Hunger |
0.91 |
245137 |
222.50 |
3: Good Health and Well-Being |
0.95 |
370633 |
349.09 |
4: Quality Education |
0.54 |
340107 |
184.64 |
5: Gender Equality |
0.23 |
118781 |
27.53 |
6: Clean Water and Sanitation |
1.18 |
96514 |
113.66 |
7: Affordable and Clean Energy |
3.58 |
58675 |
210.11 |
8: Decent Work and Economic Growth |
1.48 |
168919 |
250.23 |
9: Industry, Innovation and Infrastructure |
2.28 |
89322 |
203.38 |
10: Reduced Inequalities |
0.35 |
26478 |
9.23 |
11: Sustainable Cities and Communities |
1.58 |
133360 |
210.59 |
12: Responsible Consumption and Production |
0.56 |
12325 |
6.84 |
13: Climate Action |
0.92 |
24614 |
22.68 |
14: Life Below Water |
0.64 |
3414 |
2.20 |
15: Life on Land |
0.64 |
49930 |
31.98 |
16: Peace, Justice and Strong Institutions |
0.65 |
422695 |
272.60 |
17: Partnerships for the Goals |
1.16 |
49861 |
57.67 |
General Environmental Projects |
0.62 |
32280 |
19.88 |
Non-SDG Projects |
2.11 |
339910 |
718.51 |
Note: “Funded projects” captures only projects that were tagged with a related SDG-target code and received disbursements greater than zero dollars. This may exclude project entries that only recorded commitments. Classifying a project as “Non-SDG” is not to imply that these efforts are not beneficial to local communities but rather that their activity descriptions did not trigger any matches to the SDGs. This could reflect a primary emphasis outside of the SDGs agenda or be a consequence of the project documentation not sufficiently articulating contributions to aspects of the SDGs. Financial amounts are in constant 2020 USD. Source: Burgess, B., Bengtson, A., and B. Lautenslager. (2023). Financing the 2030 Agenda for Sustainable Development, Version 1.0. Williamsburg, VA. AidData. Accessed at https://aiddata.org/sdg .
A3 Appendix 3: Real and Estimated funding to SDGs in 2020 and 2021
This table shows the total funding directed to SDG-related activities for 2020 and 2021. The 2020 estimates were calculated based on the average annual change in funding from 2015-2019. 2021 estimates apply the same average rate of change to the 2020 estimate, simulating a stable trend in funding values. Financial amounts are in constant 2020 USD.
Goal |
2020, Real Disbursements, USD Millions |
2021, Real Disbursements, USD Millions |
2020, Estimated Disbursements, USD Millions |
2021, Estimated Disbursements, USD Millions |
2020, Difference between Estimated and Real Disbursements, USD Millions |
2021, Difference between Estimated and Real Disbursements, USD Millions |
1: No Poverty |
15,262 |
18,338 |
8,788 |
9,034 |
6,474 |
9,304 |
2: Zero Hunger |
26,153 |
22,569 |
23,947 |
25,621 |
2,206 |
-3,051 |
3: Good Health and Well-Being |
49,304 |
47,180 |
27,904 |
28,322 |
21,400 |
18,858 |
4: Quality Education |
17,483 |
17,135 |
18,342 |
19,207 |
-859 |
-2,072 |
5: Gender Equality |
3,351 |
3,401 |
3,867 |
4,415 |
-516 |
-1,015 |
6: Clean Water and Sanitation |
10,301 |
9,558 |
12,282 |
12,734 |
-1,981 |
-3,176 |
7: Affordable and Clean Energy |
18,168 |
17,135 |
23,103 |
24,167 |
-4,935 |
-7,033 |
8: Decent Work and Economic Growth |
30,274 |
32,838 |
31,977 |
34,685 |
-1,703 |
-1,846 |
9: Industry, Innovation and Infrastructure |
19,967 |
17,705 |
18,924 |
19,412 |
1,043 |
-1,707 |
10: Reduced Inequalities |
2,219 |
1,680 |
2,389 |
4,037 |
-170 |
-2,357 |
11: Sustainable Cities and Communities |
20,286 |
19,130 |
21,992 |
22,900 |
-1,706 |
-3,770 |
12: Responsible Consumption and Production |
289 |
258 |
410 |
397 |
-121 |
-140 |
13: Climate Action |
2,469 |
2,942 |
2,328 |
2,494 |
141 |
448 |
14: Life Below Water |
216 |
230 |
257 |
268 |
-41 |
-38 |
15: Life on Land |
3,074 |
3,713 |
2,623 |
2,642 |
451 |
1,071 |
16: Peace, Justice and Strong Institutions |
30,381 |
22,213 |
23,142 |
23,079 |
7,239 |
-866 |
17: Partnerships for the Goals |
4,187 |
3,076 |
3,603 |
3,634 |
584 |
-558 |
Non-SDG Projects |
64,624 |
92,459 |
56,063 |
53,662 |
8,561 |
38,797 |
Source: Burgess, B., Bengtson, A., and B. Lautenslager. (2023). Financing the 2030 Agenda for Sustainable Development, Version 1.0. Williamsburg, VA. AidData. Accessed at https://aiddata.org/sdg .
A4 Appendix 4: Leading Donor to each Goal, MDG and SDG era
This table shows the leading donor to each of the 17 SDGs in the last six years of the MDG era (2010-2015) and the first six years of the SDGs era (2016-2021), in terms of total volume of SDG-related finance during that period. The shift in rank for the leading donor of the SDG era is listed in parenthesis, along with the change in the new leading donor’s goal-specific financing before and after 2015.
Goal |
Leading donor 2010-2015 |
Leading donor 2016-2021, (Previous rank of leading donor, 2010-2015) |
Change in Leading donor 2016-2021’s funding to Goal vs. 2010-2015, USD Millions |
1: No Poverty |
IBRD |
International Development Association, (2) |
+6,338 |
2: Zero Hunger |
United States |
United States, (1) |
+3,304 |
3: Good Health and Well-Being |
United States |
United States, (1) |
+3,745 |
4: Quality Education |
Germany |
Germany, (1) |
+6,325 |
5: Gender Equality |
United States |
United States, (1) |
-744 |
6: Clean Water and Sanitation |
Japan |
IBRD, (3) |
+2,368 |
7: Affordable and Clean Energy |
IBRD |
Asian Development Bank, (2) |
+8,660 |
8: Decent Work and Economic Growth |
IBRD |
IBRD, (1) |
+1,082 |
9: Industry, Innovation and Infrastructure |
EU Institutions |
EU Institutions, (1) |
-600 |
10: Reduced Inequalities |
United States |
EU Institutions, (2) |
+1,356 |
11: Sustainable Cities and Communities |
IBRD |
Japan, (2) |
+9,573 |
12: Responsible Consumption and Production |
IBRD |
IBRD, (1) |
+83 |
13: Climate Action |
France |
Germany, (2) |
+1,209 |
14: Life Below Water |
International Development Association |
Japan, (6) |
+202 |
15: Life on Land |
Germany |
Germany, (1) |
+2,296 |
16: Peace, Justice and Strong Institutions |
United States |
United States, (1) |
-4,984 |
17: Partnerships for the Goals |
France |
France, (1) |
-4,537 |
Note: Pre-2015 funding is calculated using the total amount directed to SDG-related activities over the six years prior to the SDG-era (2010-2015), and Post-2015 funding is calculated using the total amount directed to SDG-related activities over the six years following the adoption of the SDG agenda (2016-2021). Financial amounts are in constant 2020 USD. Source: Burgess, B., Bengtson, A., and B. Lautenslager. (2023). Financing the 2030 Agenda for Sustainable Development, Version 1.0. Williamsburg, VA. AidData. Accessed at https://aiddata.org/sdg .
[1] Note: This definition is inclusive of Official Development Assistance, Other Official Flows, Equity Investment, and Private Development Finance recorded in the OECD CRS database. For full definitions of these terms as applied in the OECD CRS database, see the DAC Glossary of Key Terms. https://www.oecd.org/dac/financing-sustainable-development/development-finance-data/dac-glossary.htm#ODF
[2] Specifically, fastText, scikit-learn, and Keras. For full documentation of those models, see: https://fasttext.cc/ ; https://scikit-learn.org/stable/ ; https://keras.io/ .
[3] For further detail on Goal-level aggregates, see Appendix 2: Overview of Finance to the 17 Goals.
[4] MDG1: Eradicate Extreme Poverty and Hunger, MDG2: Achieve Universal Primary Education, MDG3: Promote Gender Equality and Empower Women, MDG4: Reduce Child Mortality, MDG5: Improve Maternal Health, MDG6: Combat HIV/AIDS, Malaria and Other Diseases, MDG7: Ensure Environmental Sustainability, and MDG8: Global Partnership for Development. Available from: https://www.un.org/millenniumgoals/bkgd.shtml
[5] This increase of US$28 billion in non-SDG funding may in part be tied to the Fall of Kabul. The United States and Germany both redacted much of the data on their projects going to Afghanistan as a precaution to protect in-country partners, and both saw a substantial increase in non-SDG funding directed to “Bilateral, unspecified” recipients from 2020 to 2021 (+2.6 Billion for the USA, +1.7 Billion for Germany). However, there were also huge aggregated disbursements from the New Development Bank and Asian Infrastructure Investment Bank that may have been more directly linked to post-COVID-19 budget support.
[6] Note that this finding, and the high ranking of Partnerships for the Goals (SDG17), diverge from AidData’s earlier finding for ODA from 2000-2013 in Realizing Agenda 2030. https://docs.aiddata.org/ad4/pdfs/Realizing_Agenda_2030.pdf . This likely reflects key changes occurring within the MDG era rather than between eras.
[7] Examining projects that contained any degree of gender or inequality sensitivity may yield a much larger pot of funding to these goals, though we argue that this would also overrepresent the funding actually intended to impact SDG 5 and SDG 10.
[8] The OECD estimates that developing countries suffered a US$689 billion drop in government revenue in 2020 (OECD 2022).
[9] These donors include: Belgium, Cyprus, Denmark, Estonia, Greece, Iceland, IFAD, IMF (Concessional Trust Funds), Ireland, Israel, Italy, Malta, Romania, Saudi Arabia, Taiwan (referred to as Chinese Taipei in the OECD CRS source data), Thailand, UNDP, UNEP, United Arab Emirates.
[10] These donors include: Asian Development Bank, Azerbaijan, Council of Europe Development Bank, Hungary, Islamic Development Bank, Kazakhstan, Korea, Lithuania, Nordic Development Fund, Norway, Portugal, Slovenia, Sweden, Switzerland, Turkiye, UNFPA, UNICEF.
[11] European Commission President von der Leyen wrote the SDGs into the Commissions political guidelines for 2019-2024 (von der Leyen, 2020).
[12] Lithuania conducted voluntary national reviews ( VNRs ) on their internal progress in 2018 and 2023 (UN HLPF, 2018; Ministry of Environment Republic of Lithuania, 2023), as well as producing an SDG-aligned strategy document “Lithuania 2030” (State Progress Council, 2017).
[13] For each goal, this variable takes the absolute difference from a value representing an “ideally” distributed portfolio, then calculates the mean of all values for each donor. The values range from 0.033 for Finland, with a very broad portfolio, to 0.111 for the Montreal Protocol, which had 100% of funds tied to SDG 15, with a median of 0.06176.
[14] This is not to say that higher GDPs always makes for higher domestic revenues, as this is also partly a consequence of a government’s tax policies. However, we would argue that higher GDPs generally improves the potential for countries to boost their DRM through a growing tax base. Conversely, the DRM potential for countries with lower GDPs is necessarily limited.
[15] If we omit the 22 percent of Global Health funds directed to unspecified regions or the world as a whole.
[16] The AsDB’s 2021 Energy Policy policies largely extend its earlier strategies to focus on “energy operations aligned with AsDB’s Strategy 2030 and the global commitments that Strategy 2030 supports, including the SDGs” (AsDB, 2021).
[17] As a case in point: Western Hemisphere countries captured an outsized share of global funding for life on land (SDG15): US$6 billion or 19 percent of all funding for this goal. However, life on land made up only 1 percent of all funding to the region, led by Brazil (US$2 billion), and Mexico and Colombia (US$1.1 billion each).
[18] For further detail on China’s development finance, see Malik et al. (2021), Horigoshi et al. (2022), and https://china.aiddata.org/ .
[19] Biermann et al. argue that the SDGs only have had a rhetorical impact on governance, not a transformational one.
[20] Using World Bank income classifications at the time, this includes 32 LIC countries and 27 LMIC countries. The Sachs et al. (2018) estimates of funding needed is net of domestic budgets, domestic resource capacity, and borrowing capacity.
[21] A 2019 study, Closing the SDG Budget Gap, calculates the financing gap not supplied by domestic resource mobilization at US$173 billion in LICs and US$180 in LMICs in 2018 USD. Inflated to 2020 USD, this equals US$364 billion.
[22] The Kheras & McArthur (2019) study estimated the total annual public spending needs for LICs at US$344 billion and for LMICs at US$583 billion by 2025. Netting out estimated SDG-related funding, which included aid, they arrived at a needs gap of US$150 billion for LICs and US$549 billion for LMICs. In USD 2020 terms, this equates to US$938 billion in total needs and US$708 billion for unmet needs.
[23] By this we mean that for LICs, we took 18 percent of the 2010-2021 average GDP, and for LMICs we took 9 percent of the 2010-2021 average GDP. These 18 percent and 9 percent thresholds are the same as Sachs et al (2018) paper.
[24] Using AidData’s Financing the 2030 Agenda for Sustainable Development dataset, Version 1.0, we filtered for LICs and LMICs to obtain estimates of donor SDG financing for 2010 to 2021 (the numerator). To approximate “needed funds” (the denominator), we averaged GDPs for LICs and LMICs respectively on an annual basis from 2010 to 2021. For LICs, GDP was US$432 billion in 2010 and US$643 billion in 2021, with an average over the period of US$535 billion. Eighteen percent of this is US$102 billion. For LMICs, GDP was US$1.3 trillion in 2010 and US$2 trillion in 2021, with an average over the period of US$1.7 trillion. Nine percent of this is US$132 billion. Together, the total gap used to calculate met versus unmet need is US$234 billion. Met need is all SDG ODF annually for both cohorts divided by $234 billion. All financials are USD 2020.
[25] The costing exercise that we are basing our “proportion of GDP” rule of thumb for LIC and LMIC is from 2018—before the COVID 19 pandemic.
[26] Commonly cited SDG costing exercises such as the 2018 and 2019 Sach et al. studies and the 2019 Kharas and McDonald study take a forward look at SDG costs only after the SDGs adoption. But not all SDG costing exercises are post-2015. For example, the 2014 UNCTAD World Investment Report: https://unctad.org/system/files/official-document/wir2014_en.pdf .
[27] We assume that this 2010 lookback does not reduce need by spreading the cost of the SDGs over a longer time period, since SDG spending consists not only of capital investments but also social transfers, ongoing public goods, and the recurrent operational costs of health and education systems.