Thailand Labour Costs

Thailand · Quarterly series · EC-TH-LC

Latest, Q2 2026

106.9 pts

+7.7% from Q1 2026

Open interactive chartThailand Labour Costs in the app

110.199.2188.36Q1 2013Q2 2027
History through Q2 2026, the forecast path to Q2 2027 (dashed) and its 80% interval (shaded).

Forecast

Forecast for Q2 2027: 106.7 pts, with an 80% interval of 102.1 pts to 110.1 pts.

Forecast path. Intervals are shown where available.
PeriodForecast80% low80% high
Q3 2026106.3 pts102.4 pts109.2 pts
Q4 202698.3 pts95.0 pts102.7 pts
Q1 202799.7 pts95.6 pts104.2 pts
Q2 2027106.7 pts102.1 pts110.1 pts

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

AI confidence

Supported evidence

The 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
+40%Beats the no-change baseline over 7 tests (7 tests, 6 won)
Direction
70%No clear edge over a coin flip (19 of 27 calls right in 7 tests)
Turning points
7 of 9Anticipated most turns (9 turns in 7 tests, 0 without a turn)
Error vs baseline
40% lowerError ratio 0.60; 1.00 is a tie.
Tests won
6 / 7Complete rolling backtests; ties count as no win.
Test period
2019-09-01 to 2026-06-014 observations ahead per test.
80% band coverage
86%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 87% 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 2026106.9 pts
Q1 202699.2 pts
Q4 202597.4 pts
Q3 2025106.9 pts
Q2 2025105.8 pts
Q1 202599.0 pts
Q4 202498.6 pts
Q3 2024107.3 pts
Q2 2024108.8 pts
Q1 2024100.8 pts
Q4 2023100.6 pts
Q3 2023107.7 pts
Q2 2023107.5 pts
Q1 2023100.9 pts
Q4 2022101.2 pts
Q3 2022106.8 pts
Q2 2022106.8 pts
Q1 202299.1 pts
Q4 202191.0 pts
Q3 202197.4 pts
Q2 202199.9 pts
Q1 202195.2 pts
Q4 202096.0 pts
Q3 2020101.8 pts

Source

Data: public market data feeds.

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