Lithuania Government Revenues
Lithuania · Quarterly series · EC-LT-GR
Latest, Q4 2025
9.17B EUR
+15.2% from Q3 2025
Forecast
Forecast for Q4 2026: 9.79B EUR, with an 80% interval of 8.08B EUR to 11.51B EUR.
| Period | Forecast | 80% low | 80% high |
|---|---|---|---|
| Q1 2026 | 7.99B EUR | 7.86B EUR | 8.13B EUR |
| Q2 2026 | 9.51B EUR | 9.01B EUR | 10.11B EUR |
| Q3 2026 | 8.62B EUR | 7.71B EUR | 9.49B EUR |
| Q4 2026 | 9.79B EUR | 8.08B EUR | 11.51B EUR |
AI confidence
Supported evidenceThe point forecast beat the no-change baseline overall and in a majority of the evaluated tests.
Model: Agentic Investor TSFM (foundation model)
- Accuracy vs naive
- +46%Beats the no-change baseline over 8 tests (8 tests, 7 won)
- Direction
- 88%Beats a coin flip (28 of 32 calls right in 8 tests)
- Turning points
- 24 of 24Anticipated most turns (24 turns in 8 tests, 0 without a turn)
- Error vs baseline
- 46% lowerError ratio 0.54; 1.00 is a tie.
- Tests won
- 7 / 8Complete rolling backtests; ties count as no win.
- Test period
- 2018-03-01 to 2025-12-014 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 2025-12-01.
- 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.
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
That is the highest of the 40 readings since Q1 2016.
Recent history (24 observations)
| Period | Value |
|---|---|
| Q4 2025 | 9.17B EUR |
| Q3 2025 | 7.96B EUR |
| Q2 2025 | 8.85B EUR |
| Q1 2025 | 7.22B EUR |
| Q4 2024 | 8.34B EUR |
| Q3 2024 | 7.33B EUR |
| Q2 2024 | 7.91B EUR |
| Q1 2024 | 6.55B EUR |
| Q4 2023 | 7.61B EUR |
| Q3 2023 | 6.36B EUR |
| Q2 2023 | 7.23B EUR |
| Q1 2023 | 5.95B EUR |
| Q4 2022 | 6.85B EUR |
| Q3 2022 | 5.72B EUR |
| Q2 2022 | 6.24B EUR |
| Q1 2022 | 5.22B EUR |
| Q4 2021 | 5.73B EUR |
| Q3 2021 | 4.94B EUR |
| Q2 2021 | 5.53B EUR |
| Q1 2021 | 4.33B EUR |
| Q4 2020 | 5.01B EUR |
| Q3 2020 | 4.44B EUR |
| Q2 2020 | 4.63B EUR |
| Q1 2020 | 3.98B EUR |
Source
Data: public market data feeds.
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