Overview

High-profile commitments and ambitious strategies are not enough to ensure that low- and middle-income countries are on track to realize the United Nation's Sustainable Development Goals (SDGs). The annual financing gap for the Global South to achieve the SDGs has grown to over US$4 trillion, more than a 50% increase since pre-pandemic.

To realize Agenda 2030, aid agencies, philanthropies, and partners in the Global South need better data to monitor how official development finance dollars advance the SDGs—and avoid missing the mark.

AidData's groundbreaking report summarizes the results of a novel effort to use AI to tag and analyze nearly 3 million development finance projects from 2010-2021 to understand their contributions to the SDGs at a goal and target level. Our report compares the last six years of the Millennium Development Goals and the first six years of the new SDG era, monitoring how donor priorities have evolved over time.

Our original pilot project relied on manual coding from a team of over 30 student research assistants to develop a target-level SDG financial tracking methodology. With this initial dataset of 104,000 projects, we trained a machine learning algorithm to classify projects, producing a dataset of over 3 million development finance projects coded to the SDGs.

Brook Lautenslager

Deputy Director for Data Analytics and Technology Solutions

Bryan Burgess

Senior Policy Specialist

John Custer

Deputy Director, Communications and Data Analytics

Three highlights from the policy report

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Alex Wooley

Director of Partnerships and Communications

Shock treatment: Estimating COVID-19's displacement on donor financing

What would have SDG funding looked like in 2020 and 2021, if the COVID-19 shock didn't happen?

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.

This chart takes point estimates for what SDG funding would have looked like in 2020 and 2021 in the absence of a global pandemic, based on the average growth rate of funding to each goal in the five years prior to COVID-19 (2015-2019). The arrows then compare actual development finance allocations for each goal in those two years against these point estimates.

In context

Financing Agenda 2030, Figure 4

Revealed priorities: Donor portfolios in the pre- and post-2015 eras

How have donors adjusted financing for the SDGs, in absolute terms and as a share of their portfolios?

For this donor-level analysis, our report draws on AidData's Financing the 2030 Agenda for Sustainable Development Dataset, Version 1.0, which includes project-level details on 3.2 million disbursements from 157 development partners cumulatively worth $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 $2.9 trillion, or 98 percent of the funds tracked in the dataset.

This chart segments donors into one of four categories: 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).

In context

Financing Agenda 2030, Figure 6

Country view: Geography of donor financing for the SDGs and emerging gaps

To what extent does donor financing for the SDGs vary by income level?

Externally-driven development finance is most critical in countries where the ratio of SDG funding needs to GDP is higher. 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 development finance that same year was in part driven by donors stepping in to help meet this shortfall.

Unfortunately, SDG-focused donor financing has continued to move away from the poorest places, even after SDGs were adopted in 2015. In 2010, low-income countries attracted $1.54 for every dollar that lower-middle income countries received in SDG-related ODF. But by 2021, this ratio had dropped by 32 percent, with the poorest countries receiving $1.05 for every dollar that went to lower-middle income countries.

In context

Financing Agenda 2030, Figure 9