Ukraine Labor Force Participation Rate

Name: Ukraine Labor Force Participation Rate
Creator: Agentic Investor

Ukraine · Quarterly series · EC-UA-LFPR

Latest, Q4 2021

61.8%

-0.90pp from Q3 2021

Open interactive chartUkraine Labor Force Participation Rate in the app

History through Q4 2021, the forecast path to Q4 2022 (dashed) and its 80% interval (shaded).

Forecast

Forecast for Q4 2022: 61.9%, with an 80% interval of 57.7% to 65.9%.

Forecast path. Intervals are shown where available.
Period	Forecast	80% low	80% high
Q1 2022	61.8%	58.4%	65.3%
Q2 2022	61.9%	57.9%	65.8%
Q3 2022	62.2%	58.9%	65.1%
Q4 2022	61.9%	57.7%	65.9%

Model: Agentic Investor TSFM (foundation model). Forecast generated 2026-11-15.

AI confidence

Weak evidence

The serving forecast made larger errors than the no-change baseline in these tests.

Model: Agentic Investor TSFM (foundation model)

Accuracy vs naive: -11%Trails the no-change baseline over 8 tests (8 tests, 3 won)
Direction: 43%No clear edge over a coin flip (13 of 30 calls right in 8 tests)
Turning points: 11 of 13Anticipated most turns (13 turns in 8 tests, 0 without a turn)

Error vs baseline: 11% higherError ratio 1.11; 1.00 is a tie.
Tests won: 3 / 8Complete rolling backtests; ties count as no win.
Test period: 2014-03-01 to 2021-12-014 observations ahead per test.
80% band coverage: 84%Observed outcomes inside the band across all stored test windows.

Band coverage uses all stored test windows, including model-selection windows when present; it does not determine the confidence label.
Evaluated 2026-11-15 against the cached history through 2021-12-01.
This is an evaluation of the serving model; it does not establish a winner across four model classes.

How this assessment is made

AI confidence describes historical evidence for this forecast, not a probability of being correct. Each backtest fits on data available before its test window. The baseline carries the last value forward. Supported evidence requires at least six complete, non-overlapping tests, an error ratio below 0.90 (rounded to two decimals), and wins in a majority of tests. Ratios from 0.90 to below 1.10 are on par; 1.10 or above is weak evidence. Inconsistent wins produce mixed evidence. For a selected model, only the recent tests excluded from model selection determine this label. These are historical simulations using the available data, not a live trading track record; revisions and foundation-model pretraining can limit how closely they reproduce a past decision. Past performance can change.

Replay past tests

Model comparison

Comparison pendingA new ticker first receives its serving model's forecast and evaluation. An eligible nightly batch can compare both candidates, subject to call budgets and retry limits.

Reading

It is above 10% of the 39 earlier readings since Q1 2012.

Written from the figures by a fixed template; no AI model is involved.

Recent history (24 observations)

The 24 most recent observations, newest first.
Period	Value
Q4 2021	61.8%
Q3 2021	62.7%
Q2 2021	61.7%
Q1 2021	61.4%
Q4 2020	62.1%
Q3 2020	62.3%
Q2 2020	62.5%
Q1 2020	63.7%
Q4 2019	63.4%
Q3 2019	63.5%
Q2 2019	63.2%
Q1 2019	62.8%
Q4 2018	62.6%
Q3 2018	62.6%
Q2 2018	62.4%
Q1 2018	61.9%
Q4 2017	62.0%
Q3 2017	62.2%
Q2 2017	61.9%
Q1 2017	61.4%
Q4 2016	62.2%
Q3 2016	62.3%
Q2 2016	62.1%
Q1 2016	61.7%

Source

Data: public market data feeds.