An evidence-based reading of fourteen years of UN system financial data. Every figure from primary public sources. Three chapters: funding quality, concentration, and the signals in the data.
UN system revenue grew from $39.6B in 2011 to $68.3B in 2024: +72% nominal, 34 to 48 reporting entities; +69% at constant perimeter (entities reporting in both 2011 and 2024); a real-terms figure in 2024 dollars is not computed in this build (no US GDP deflator or CPI series available offline). Over the same period unrestricted funding (assessed plus core) fell from 44.1% to 28.0% of total revenue; core alone from 10.6% to 7.8%, while earmarked contributions rose from 49.6% to 60.6%.
Core contributions were 7.8% of total revenue in 2024, or 11.4% of voluntary contributions. The rest was assessed (20.2%), earmarked (60.6%) or other revenue.
Source: CEB Financial Statistics 2024 · Core funding $5.3B of $68.3B
Earmarking is a known trade-off: it lets donors target results and report on them, and it limits how far entities can move money between priorities. Volatility is visible too: WFP revenue changed by -37% between 2022 and 2023, after an exceptional 2022.
The United States contributed $14.3B to the UN system in 2024, 30.6% of all government contributions. The second-largest government contributor provided 10.2%. Concentration is measured here, not judged: it describes how much of each entity's government funding comes from a single contributor.
US contributions were 57.9% of UNHCR's government contributions in 2024, 55.2% of IOM's, 52.3% of WFP's and 52.2% of UNAIDS'.
Source: CEB Revenue by Government Donor 2024 · Arithmetic on published data, no inference made
Each signal is a published figure, with its source and years. What it means for policy is left to the reader; the questions below suggest where to start.
These are questions, not answers. Each one connects a figure in this study to a debate already open in the UN system.
The CEB and UNGM publish UN system financing in detail, but across many separate datasets that are rarely read together. Flows puts those public series side by side, so that funding quality, donor concentration and reporting gaps can be discussed on the same evidence.
Method in three lines. 1. Download the published CEB Financial Statistics, CEB HR Statistics and UNGM reports. 2. Compute every headline figure with one script into a single file, flows.json, that stores source, years, formula and limitation. 3. Publish only what the data supports, and show gaps as gaps. Full methodology.