ABS Australia - Industry Statistics (Industry Overview)

ABS Australia's Industry overview is the front door to Australia's official industry statistics, and it indexes three annual release families rather than one flat table. Australian Industry reports financial indicators for selected industries - total operating profit before tax (OPBT) and EBITDA among them - with 2024-25 as the latest reference period. Estimates of Industry Multifactor Productivity covers the sixteen-industry market sector on both hours-worked and quality-adjusted-hours bases. Estimates of Industry Level KLEMS Multifactor Productivity takes the decomposition further, splitting productivity into its capital, labour, energy, materials and services components industry by industry. For anyone positioning Diversified REITs against the wider economy, this is the national-aggregate spine: profit, earnings and productivity for every ANZSIC industry division, rental, hiring and real estate services included.

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The record carries three verified headline rows - one per release family's lead finding, exactly as published:

release          : Australian Industry
reference_period : 2024-25
release_date     : 2026-06-19
headline         : Total selected industries operating profit before tax fell $12.2b (-1.9%)

industry : Mining
metric   : OPBT change
value    : -$32.9b (-19.1%)

industry : Rental, hiring and real estate services
metric   : OPBT change
value    : +$20.2b (+47.6%)

That last row is the one Diversified REITs analysts zoom in on: rental, hiring and real estate services swung $20.2 billion upward in 2024-25 - a 47.6% rise - while Mining gave back $32.9 billion. National aggregates, financial-year basis, industry-keyed. A full sample shows the complete measure set per industry, not just the headline changes.

Six headline measures plus the industry key cover everything the release families publish at summary level. Examples below come straight from published headline figures; where a cell reads -, the value arrives with the sample rather than the summary.

Fields whose definitions sit below summary level - the individual KLEMS component series, the hours-worked versus quality-adjusted-hours variants, growth-cycle tables and per-release commentary - are folded under additional fields on request: ask for them in the sample form and they arrive itemised, defined and exemplified.

Geography - Australia, national aggregates. These releases do not split states or territories; subnational industry detail lives elsewhere in the ABS catalog rather than here.

Temporal - annual financial-year reference periods. Latest: 2024-25 for both Australian Industry and Estimates of Industry Multifactor Productivity, 2023-24 for KLEMS. The three families land on their own schedules across the year, so a single snapshot date catches them at different vintages.

Granularity - one measure set per ANZSIC industry or market-sector industry, sixteen industries per productivity release, national level. Establishment-level and company-level detail sits outside these tables; treat anything below the industry division as a different dataset.

API, files, or your warehouse. Daily, weekly, or hourly.

• Benchmarking industry profitability. OPBT and EBITDA by ANZSIC division turn "how are Australian industries doing" into a number you can rank - and place real-estate-services earnings of +$20.2b (+47.6%) in 2024-25 against Mining's -$32.9b (-19.1%) rather than against vibes.
• Reading the property cycle from national accounts. When rental, hiring and real estate services posts the largest gain of any industry, that belongs next to REIT funds-from-operations and cap-rate work - context in the investors and quants use cases for Diversified REITs.
• Building industry-factor models. Profit levels join cleanly against productivity indices on a shared ANZSIC spine, giving factor models a macro layer that price feeds cannot supply - see data scientists working in Diversified REITs.
• Attribution-grade citation. Journalists and academics cite official national-accounts figures with the financial year attached, which survives peer review better than a scraped aggregator - more in journalists and academics use cases.
• Cross-country comparisons. ANZSIC maps to NAICS and GICS divisions, so Australian profit and productivity benchmarks slot beside US and EU industry statistics with one concordance table.

Market researchers and consultants get the widest win: a citable, industry-complete baseline for Australian market sizing and client decks. Investors and quant researchers use the real-estate-services lines as a macro tell for REIT earnings power, and the sixteen-industry productivity panel for factor tilts. Data scientists and ML engineers join ANZSIC-keyed profit and productivity series into models as slow-moving features that rarely need re-engineering. Journalists, academics and students take the attribution-ready framing: every figure carries its financial year and industry, so citations stay precise. Developers building data products on top of it usually start with the sample to fix schemas early - the developers and builders use cases page shows the pattern.

Notes worth reading alongside this page:

• Diversified REITs data hub - the pooled industry view this record sits inside, alongside fund flows, ticker-level quotes and property-sector peers.
• Best Diversified REITs datasets - where this ranks in the pool and what beats it for depth versus geography.
• The Australian Bureau of Statistics source profile - the publisher's wider catalog, including mining-only companions to this release.
• Business Dynamics Statistics (BDS) - the US mirror image: firm births, deaths, survival and job creation from 1978 onward.
• LEHD Quarterly Workforce Indicators - US quarterly employment and earnings by industry when workforce dynamics matter more than profits.
• BLS Public Data API - NAICS 56 employment series - monthly headcount history back to 1939; pairs with this dataset's profit-and-productivity view of the same economies.
• Tiingo Financial Market Data API - per-ticker prices to sit beside these industry aggregates.
• This dataset vs GSA eLibrary Contract Schedules - the head-to-head sets out where federal-contract data and national-accounts data diverge.
• Get a sample of this dataset - the fastest route to full rows, the extended field list and the KLEMS component series.