HomeContributorsFundamental AnalysisWhen the Rear-View Mirror is Foggy, Triangulate

When the Rear-View Mirror is Foggy, Triangulate

Forecasting is hard when even the past does not stand still.

Local markets were heavily focused this week on the June quarter national accounts. Our note (PDF 712KB) on the subject highlighted the key points. Foremost amongst these is that despite strong population growth, private sector demand is stagnant. Household consumption went backwards in the quarter, which was weaker than even we expected. Public demand did all the heavy lifting on growth, as it has done for the past few quarters.

When all the detail is fully combed over, we can still take some overarching lessons. The first is the simple fact that these data are for the June quarter. We are now in the final month of the September quarter. This is the proverbial ‘rear-view mirror’. The data have information value, but much of the focus should be on what they tell us about the near-term outlook and economic behaviour more broadly.

The consumption data are a good illustration of that lesson. As noted, the outcome was weaker than even we expected. This is not because households had boosted their saving. The household saving ratio remained unusually low, at 0.6%. Rather, household incomes were still being squeezed to some extent. While real household disposable income is no longer declining in year-ended terms, it was still down 4.7% since the peak in September quarter 2021. In per capita terms, real incomes are down a whopping 10.3% over this period.

The implications for the future are that any tendency to catch up on consumption as tax cuts boost income will be tempered by some reversion in saving to rates more like those seen in the past. There is no iron law that the saving rate must revert to some centre of gravity, and in any case, it is prone to revisions. However, the arithmetic of compulsory (and rising) superannuation contributions and contractual repayments of principal on mortgages implies that saving rates cannot remain at ultra-low levels forever.

This is especially important given that the Stage 3 tax cuts took effect after the period recorded in the latest national accounts. Most observers (including us) are working on the assumption that the extra income will support a pick-up in consumption growth. Given the latest data, though, especially the renewed drag from tax, it looks as though the risks here are to the downside.

The second lesson is that even the past does not stand still. As highlighted in the team’s note on Wednesday, the latest national accounts included significant revisions to the profile for investment for previous quarters. And the hours worked data – so crucial to estimates of productivity – have been revised significantly, though the revisions have differed in the labour force survey (LFS) versus the national accounts.

The third lesson is to be mindful of noise, shifting seasonality and artefacts of measurement. The productivity data are a case in point. Never mind that productivity growth in the market sector was a not-too-shabby 1.1% over the year. Those minded to catastrophise about Australia’s productivity performance will focus on the quarterly fall, as hours worked was strong in the quarter despite weak GDP growth. Yet average earnings per hour worked was also weak, leaving growth in unit labour costs over the past couple of quarters at a less concerning annualised rate of 3.4% – in line with the outcomes recorded over 2019 when underlying inflation was below the target range. The resolution might be found by recalling the distinction between hours worked and hours paid. One area where seasonal patterns seem to have shifted in a lasting way post-pandemic has been the pattern of leave-taking. We note that June quarter outcomes for growth in hours worked have been systematically stronger than surrounding quarters over the post-pandemic years, even more so for the LFS than the national accounts.

Conventional methods of seasonal adjustment struggle in those situations. Looking at year-ended data smooths out these lingering seasonal issues to some extent, but if seasonal patterns are shifting, some noise remains. If shifting seasonality in leave-taking is indeed the culprit, though, then the noise in hours worked will be largely offset by surprises on average earnings per hour in the opposite direction.

What to do under these circumstances, when even the past is hard to predict?

One helpful approach is to triangulate across multiple data sets. A good example of the value of this approach comes from the large revisions to US payrolls data last month. This was less of a surprise to us than it was to some observers because we had already seen signs of fragility in other US labour market data, including the household survey and other business surveys.

Another helpful triangulation is to use the discrepancies between different data sources as information themselves. Since Australia’s international borders reopened, growth in hours worked in the national accounts has grown faster than the LFS measure. This is because temporary residents are counted in the former but not the latter. (So are defence personnel and the under-15s, but we do not think they are driving the result.)

We can use this fact to help shape our view of the outlook: given that much of the recent strength in population growth appears to be catch-up after the borders reopened, growth rates will eventually ease. And so too will the outsized contribution of additional temporary residents. Growth in national accounts hours worked will therefore likely converge back to its LFS counterpart.

This is yet another reason to believe that Australia is not unique. While there will be bumps along the way – including a drag from the expansion in the care economy – the recent past for productivity need not imply a stagnant future.

Westpac Banking Corporation
Westpac Banking Corporationhttps://www.westpac.com.au/
Past performance is not a reliable indicator of future performance. The forecasts given above are predictive in character. Whilst every effort has been taken to ensure that the assumptions on which the forecasts are based are reasonable, the forecasts may be affected by incorrect assumptions or by known or unknown risks and uncertainties. The results ultimately achieved may differ substantially from these forecasts.

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