| Nominal wages, y-o-y % (period average) | 2022 | 2023 | 2024 | 2025 | 2026'E | 2027'F | 2028'F | 2029'F | 2030'F | 2031'F | 2032'F | 2033'F | 2034'F | 2035'F |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| IMF Country Report (July 2026), baseline as of 2026-07 | ||||||||||||||
| IMF Country Report (July 2026), downside as of 2026-07 | ||||||||||||||
| NBU Inflation Report (July 2026) as of 2026-07 | — | — | — | — | — | — | — | |||||||
| KSE Macro Handbook (July 2026) as of 2026-07 | — | — | — | — | — | — | — | — | — | — |
| Population, mln | 2022 | 2023 | 2024 | 2025 | 2026'E | 2027'F | 2028'F | 2029'F | 2030'F | 2031'F | 2032'F | 2033'F | 2034'F | 2035'F |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| IMF WEO (April 2026) as of 2026-04 | — | — | — | — |
| Unemployment rate, % | 2022 | 2023 | 2024 | 2025 | 2026'E | 2027'F | 2028'F | 2029'F | 2030'F | 2031'F | 2032'F | 2033'F | 2034'F | 2035'F |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| IMF Country Report (July 2026), baseline as of 2026-07 | ||||||||||||||
| IMF Country Report (July 2026), downside as of 2026-07 | ||||||||||||||
| EC Economic Forecast (May 2026) as of 2026-05 | — | — | — | — | — | — | — | — | ||||||
| NBU Inflation Report (July 2026) as of 2026-07 | — | — | — | — | — | — | — | — | ||||||
| KSE Macro Handbook (July 2026) as of 2026-07 | — | — | — | — | — | — | ||||||||
| ICU Macro Insight (June 2026) as of 2026-06 | — | — | — | — | — | — | — | — | — |
Every cell is queried by row ID from the data registry. Click a value to see its provenance (publisher, document, vintage, primary source).
“The labor market is expected to stay exceptionally tight until demobilization, when the average unemployment rate is projected to rise from 9.5% in 2027 to 11.1% in 2028, before investment pulls it back down toward ~9% by 2029.”
KSE Institute (Kyiv School of Economics) — Ukraine Macroeconomic Handbook, p.5 · vintage 2026-08 · UA-Q-0048✓ substring-verified
“As the secular population decline resumes, growth will need to be underpinned by productivity gains, continued high investment and export expansion.”
International Monetary Fund — Ukraine: Country Report (EFF programme reviews), p.21 · vintage 2026-07 · UA-Q-0046✓ substring-verified
“A rapid improvement in the security situation will help stabilize the energy sector, reverse negative migration trends, boost domestic and foreign investment, and significantly accelerate economic growth.”
National Bank of Ukraine — Inflation Report, p.6 · vintage 2026-07 · UA-Q-0047✓ substring-verified
“Labour shortages are expected to remain pronounced over the forecast horizon due to slow reintegration, the lasting impact of the war on the workforce, and persistent regional and skills mismatches. As a result, the unemployment rate is set to remain high, albeit on a gradually declining path.”
European Commission — European Economic Forecast, p.183 · vintage 2026-05 · UA-Q-0049✓ substring-verified
Comparison of institutional forecast accuracy by Average error, Mean absolute error (MAE) and Adjusted MAE. Institutions are ranked by Adjusted MAE — the lowest value indicates the strongest predictive power and is highlighted.
| Institution | N | Avg. error (pp) | MAE (pp) | Adj. MAE (pp) | Rank Avg | Rank MAE | Rank Adj. MAE |
|---|---|---|---|---|---|---|---|
| ICUbest · Adj. MAE | 4 | +3.71 | 3.90 | 3.19 | 3 | 1 | 1 |
| KSE | 4 | -1.91 | 4.16 | 6.31 | 1 | 2 | 2 |
| NBU | 21 | -2.68 | 6.92 | 6.67 | 2 | 3 | 3 |
| IMF | 18 | -3.85 | 7.53 | 7.50 | 4 | 4 | 4 |
| Institution | N | Avg. error (pp) | MAE (pp) | Adj. MAE (pp) | Rank Avg | Rank MAE | Rank Adj. MAE |
|---|---|---|---|---|---|---|---|
| ICUbest · Adj. MAE | 15 | -0.69 | 3.92 | 3.59 | 2 | 3 | 1 |
| IMF | 21 | -3.40 | 4.16 | 3.86 | 5 | 4 | 2 |
| NBU | 24 | -2.26 | 4.91 | 3.94 | 4 | 5 | 3 |
| EC | 9 | +1.80 | 2.08 | 4.25 | 3 | 2 | 4 |
| KSE | 4 | +0.42 | 0.94 | 4.71 | 1 | 1 | 5 |
Forecasts made long before the actual data are released are inherently harder than those made shortly before release. The Adjusted MAE therefore takes into account the period of time between the making of each forecast and the release of the actual data, putting institutions that forecast at different horizons on an equal footing. The approach follows Michael K. Andersson, Ted Aranki and André Reslow: “Adjusting for Information Content when Comparing Forecast Performance” (2016) and “Evaluation of the Riksbank’s forecast” (2018).