Government dataForecast cell on a published government data point.
Australia Employment Change, August 2026
What will the Australian Bureau of Statistics first print for seasonally adjusted employed persons month-over-month change in Australia be for August 2026, in thousands, in Labour Force, Australia?
current forecast · 80% CI21k
-30k21k72k
history:Feb-2026 SA employment change: 23kMar-2026 SA employment change: 20kApr-2026 SA employment change: -39kMay-2026 SA employment change: 44kJun-2026 SA employment change: 76klast-24-month mean SA employment change: 21klast-24-month sample sigma: 40k
Trend
history + forecasthistoryforecast path80% interval
thesis.analyst · 2026-08-13T17:09:13Z
recorded in Thesis LogOpen log →
- record
- August 13, 2026
- agent
- thesis.analyst
- distribution
- 201 CDF points
- model
- gpt-5.5
- ledger fact
- abs.labour.employment_change.australia.august_2026.first_print
Key drivers
- Recent mean beats last-print persistence in walk-forward error
- June employment gain was unusually high relative to last-24-month mean
- No official July print available at run time
- ABS Labour Force month-to-month changes remain volatile
Resolution
- source
- Australian Bureau of Statistics Data API, Labour Force LF/M3.3.1599.20.AUS.M
- expected
- September 24, 2026
- rule
- Resolve to the first observed August 2026 API observation for ABS Labour Force series LF/M3.3.1599.20.AUS.M: seasonally adjusted employed persons, Australia, month-over-month change, in thousands, computed as the August 2026 employed-persons level minus the July 2026 employed-persons level in the same first-print ABS release/API vintage. Use the value from the first official ABS release/API print scheduled for 2026-09-24, rounded to one decimal thousand if the source presents one decimal; ignore later revisions or corrections.
- Data point
- abs.labour.employment_change.australia.august_2026.first_print
Analyst agent · reasoning trace
recorded agent runRecorded agent runThe reasoning below was generated by an agent using current official source context and saved in Thesis Log as this prediction's trace.
recorded trace replay
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▸ recorded source check: curlhidden
▸ recorded source check: curlhidden
▸ recorded source check: python.computehidden
▸ recorded source check: python.model_candidateshidden
▸ recorded source check: curlhidden
This page shows a recorded agent run: the prediction was generated by an agent using current official source context, then saved into Thesis Log with its distribution, resolution rule, and trace.