Perspective · Data

The half-life
of a good year.

Every owner wants to sell on their best year. Every buyer discounts it. We ran the regression on 25 years of ABS data to find out who is right.

47%
Survives one year
3.6
Quarter half-life
1,513
Industry-quarters
2001–2026
Period covered

Less than half of an above-average profit margin is still there twelve months later. That single number reframes the most common argument in a business sale. An owner looks at a standout year and treats it as the new baseline. A buyer looks at the same year and normalises it back toward trend. The ABS data says the buyer is closer to right — and now we can say by how much.

The question

Does a strong year tell you anything about the next one?

Business value is a multiple of sustainable earnings. The word doing the work is sustainable. If an exceptional margin tends to stick, a peak year is a fair basis for a valuation. If it decays, pricing off that year is asking a buyer to pay for something that is already leaving.

This is testable. The Australian Bureau of Statistics has surveyed business sales, wages and gross operating profits every quarter since 2001. That gives a panel of 15 industry divisions across 101 quarters — enough to measure how quickly an unusual margin returns to normal.

Method

What we actually ran

For each industry we computed the quarterly gross operating profit margin, then its deviation from that industry's own long-run average. Regressing each deviation on the same industry's deviation h quarters earlier gives the share that survives:

devi,t = αi + ρ · devi,t−h + εi,t
devi,t = margini,t − mean(margini)
margin = gross operating profit ÷ sales

Industry fixed effects (αi) absorb the fact that mining simply runs at a higher margin than retail. Standard errors are clustered by industry, so correlated shocks inside an industry do not inflate significance. ρ is the answer: the fraction of an unusual margin still present h quarters later.

What ρ is not. This is a persistence measure, not a causal claim. It describes how reliably an exceptional margin repeats — which is exactly the question a buyer is asking — but it does not identify why any individual business is above trend.
Result

It decays fast, then keeps going

0%25%50%75%100%1 year · 47% left1q4q8q12q16q20qQUARTERS LATER
Share of an above-average profit margin still present after h quarters. Shaded band is the 95% confidence interval from industry-clustered standard errors. ABS Business Indicators, 15 industry divisions, 2001Q1–2026Q1.

One quarter on, 81% remains — the near term looks stable, which is precisely why a good quarter feels like a new normal. A year later it is 47%. After four years the coefficient is 0.077 and no longer statistically distinguishable from zero. An exceptional margin does not settle at a new plateau. It reverts completely.

Quarters laterρStd. errorpN
10.8060.033<0.00011,498
20.6450.065<0.00011,483
30.5360.076<0.00011,468
40.4670.075<0.00011,453
60.4060.069<0.00011,423
80.3110.074<0.00011,393
120.1720.0800.03131,333
160.0770.0670.25081,273
200.0520.0700.46331,213

Headline estimate at four quarters: ρ = 0.467 (t = 6.18, p <0.0001, N = 1,453, R² = 0.224). Implied half-life 3.6 quarters.

Robustness

We tried to break it

A single specification is not evidence. The result holds across every cut we ran — dropping fixed effects, removing the mining cycle, excluding the pandemic, and restricting to the recent decade.

SpecificationρStd. errortpN
Baseline · industry fixed effects0.4670.0756.18<0.00011,453
Without fixed effects0.4660.0756.21<0.00011,453
Excluding Mining0.4160.0785.32<0.00011,356
Excluding COVID (2020–21)0.5370.0628.70<0.00011,333
Pre-2020 only0.4130.0775.39<0.00011,078
2015 onwards only0.2910.0863.370.0007615

The recent-decade estimate is the one worth pausing on. Since 2015 persistence has fallen to 0.29 — earnings have become less durable, not more. Whatever a strong year told you a decade ago, it tells you less today.

Because this is a lagged dependent variable with fixed effects, the estimate carries Nickell bias of roughly −1/T. With T = 101 quarters that is about -0.010 — small enough to ignore, and it biases ρ down, so true persistence is marginally higher than reported.
The null result

It is not wages

We began this expecting to write about labour costs. The received wisdom is that wage growth is what is crushing Australian margins. On this data, it is not there.

Δlog(profit) on Δlog(wages): β = -0.151 (se 0.321, p = 0.637) — not significant
Δlog(profit) on Δlog(sales): β = +0.700 (se 0.436, p = 0.109)
N = 1,453 · R² = 0.051

Across 1,453 industry-quarters, year-on-year wage growth does not explain year-on-year profit movements once revenue is controlled for. We tested six specifications — quarterly and annual differences, margin in percentage points and in logs, wage bill and wage share — and none produced a stable, significant wage effect. We are reporting it because a null is a result, and because it points somewhere more useful: at the revenue line.

Where the volatility comes from

Revenue, amplified

-2x-1x+0x+1x+2xMining+1.60xInformation Media and Telecommunications+1.54xManufacturing+1.07xFinancial and Insurance Services+1.07xRental, Hiring and Real Estate Services+0.83xTransport, Postal and Warehousing+0.78xRetail Trade+0.63xProfessional, Scientific and Technical Services+0.63xWholesale Trade+0.59xElectricity, Gas, Water and Waste Services+0.52xConstruction+0.23xAccommodation and Food Services-0.10xArts and Recreation Services-0.57xAdministrative and Support Services-1.74xOther Services-1.88x
Operating leverage: the percentage move in gross operating profit for each 1% move in revenue, estimated per industry with Newey–West standard errors (4 lags). Solid bars are significant at 5%; faded bars are not.

Where the relationship is measurable, profit moves further than revenue — 1.60× in mining, 1.54× in information media, 1.07× in manufacturing. That is operating leverage, and it cuts both ways. It is also the mechanism behind the headline finding: fixed costs turn ordinary revenue variation into amplified earnings variation, which is what then mean-reverts.

Where the coefficient is negative or insignificant — construction, accommodation and food, professional services — margin is being set by something other than volume. In a business sale, that distinction matters more than the multiple being argued over.

Where margins sit now

Current margin against its own 25-year average

0%10%20%30%40%Rental, Hiring and Real Estate Services36.6%-4.4Financial and Insurance Services8.6%-4.1Information Media and Telecommunications19.8%-3.7Arts and Recreation Services13.4%-3.1Accommodation and Food Services8.2%-2.5Electricity, Gas, Water and Waste Services20.6%-1.5Mining44.4%-0.6Construction8.0%-0.5Retail Trade5.7%-0.2Manufacturing9.9%+0.0Wholesale Trade6.5%+0.9Administrative and Support Services7.0%+1.1Transport, Postal and Warehousing20.1%+2.6Professional, Scientific and Technical Services13.1%+3.7Other Services15.8%+4.8
Hollow marker: the industry's average margin, 2001Q1–2026Q1. Solid marker: 2026Q1. Final column is the gap in percentage points. ABS Business Indicators, seasonally adjusted, current prices.

Read this alongside the decay curve rather than on its own. An industry sitting below its long-run average is not necessarily in structural decline — on these estimates, roughly half of that gap closes within a year on its own. The same arithmetic that stops a good year from lasting also stops a bad one.

What it means

For anyone pricing a business

A peak-year valuation is asking the buyer to fund a reversion. If 53% of an above-trend margin is gone within a year, pricing off that year and defending it as the new run-rate is a position the data does not support. Normalisation is not a negotiating tactic. It is the base rate.

Two years of evidence beats one. Persistence at eight quarters is 0.31 and still significant. A margin that has held for two years carries genuine information; one that appeared last quarter carries very little. If you are preparing to sell, the length of the track record is worth more than the height of the peak.

Know which kind of business you own. High operating leverage means your earnings look more exceptional at the top and worse at the bottom than the underlying business actually is. Buyers who understand your industry price that in. Owners who do not will feel lowballed.

And a bad year is not a verdict either. Reversion runs both ways. The owner who sells into a trough for the same reason another sells into a peak — treating one year as permanent — is making the identical error.

Data and reproducibility

Sources

Every number on this page comes from one public dataset, pulled directly from the ABS API. No manual entry, no adjustments.

AgencyAustralian Bureau of Statistics
CollectionBusiness Indicators, Australia (ABS catalogue 5676.0)
DataflowABS:QBIS(1.0.0)
SeriesM1 Sales · M5 Wages · M7 Gross Operating Profits
BasisCurrent price, seasonally adjusted, all business scopes, Australia
Coverage2001Q1 to 2026Q1 · 15 ANZSIC divisions · 1,515 industry-quarters retrieved, 1,513 used (2 dropped for non-positive values before taking logs)
Retrieved2026-08-23
API requesthttps://data.api.abs.gov.au/rest/data/ABS,QBIS,1.0.0/M1+M5+M7.CUR..TOT.20.AUS.Q?startPeriod=1994-Q1&format=csvfilewithlabels
LicenceABS data licensed under Creative Commons Attribution 4.0 International

Method notes

Estimation in Python (pandas, statsmodels). Persistence models are OLS with industry fixed effects and standard errors clustered by industry. Operating leverage is estimated per industry with Newey–West (HAC) standard errors at 4 lags. Observations with non-positive sales, wages or profit are excluded before taking logs. Margin is gross operating profit divided by sales, both current price and seasonally adjusted.

Gross operating profit is an ABS survey construct and is not identical to the EBITDA a buyer would assess in a specific business. The finding here is about the behaviour of margins in aggregate, and is not a substitute for diligence on any single company.

Contains ABS data used under CC BY 4.0. Analysis and interpretation are Balfene's own and do not represent the views of the Australian Bureau of Statistics.

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