Thailand Unemployed Persons

Thailand · Quarterly series · EC-TH-UP

Latest, Q2 2026

401,000.0 pts

+2.0% from Q1 2026

Open interactive chartThailand Unemployed Persons in the app

1.744M965.9K188KQ1 1998Q2 2027
History through Q2 2026, the forecast path to Q2 2027 (dashed) and its 80% interval (shaded).

Forecast

Forecast for Q2 2027: 396,105.3 pts, with an 80% interval of 260,959.7 pts to 627,455.1 pts.

Forecast path. Intervals are shown where available.
PeriodForecast80% low80% high
Q3 2026379,696.0 pts294,226.6 pts486,529.9 pts
Q4 2026352,626.5 pts245,045.6 pts500,500.2 pts
Q1 2027390,132.4 pts274,405.8 pts567,693.5 pts
Q2 2027396,105.3 pts260,959.7 pts627,455.1 pts

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
-12%Trails the no-change baseline over 8 tests (8 tests, 4 won)
Direction
59%No clear edge over a coin flip (19 of 32 calls right in 8 tests)
Turning points
7 of 10Anticipated most turns (10 turns in 8 tests, 0 without a turn)
Error vs baseline
12% higherError ratio 1.12; 1.00 is a tie.
Tests won
4 / 8Complete rolling backtests; ties count as no win.
Test period
2018-09-01 to 2026-06-014 observations ahead per test.
80% band coverage
78%Observed outcomes inside the band across all stored test windows.
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 41% of the 39 earlier readings since Q3 2016.

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

Recent history (24 observations)
The 24 most recent observations, newest first.
PeriodValue
Q2 2026401,000.0 pts
Q1 2026393,070.0 pts
Q4 2025280,470.0 pts
Q3 2025310,000.0 pts
Q2 2025365,530.0 pts
Q1 2025357,730.0 pts
Q4 2024358,160.0 pts
Q3 2024413,910.0 pts
Q2 2024429,080.0 pts
Q1 2024407,690.0 pts
Q4 2023329,290.0 pts
Q3 2023401,200.0 pts
Q2 2023429,050.0 pts
Q1 2023421,140.0 pts
Q4 2022462,490.0 pts
Q3 2022491,410.0 pts
Q2 2022546,590.0 pts
Q1 2022610,000.0 pts
Q4 2021631,890.0 pts
Q3 2021871,270.0 pts
Q2 2021731,830.0 pts
Q1 2021758,060.0 pts
Q4 2020727,050.0 pts
Q3 2020737,650.0 pts

Source

Data: public market data feeds.

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