Lumps, bumps and technology waves
Lumps, bumps and other noise mean top-line data cannot always be taken at face value, but sectoral investment booms like the current one in data centres are consequential.
- This week’s national accounts highlight that top-line data should not be taken at face value. Many outcomes are just the lumps and bumps of special factors, not an underlying trend. Weather events and other abnormal seasonal movements are good examples of these bumps. The combination of bumps we saw this quarter imply that GDP was a reasonable read of the underlying trend, but exports and productivity growth were not.
- Sometimes, though, a special factor is more than just a bump. Sectoral shocks and the investment booms that typically flow from them cannot be simply subsumed into a top-down view of the economy.
- Fundamental investment booms centred on a particular sector, including the mining boom and the current data centre boom, resemble each other in some ways. They contend with other sectors for resources, which can be quite disruptive. They are largely impervious to the level of interest rates, but less so to policy settings and political backlash. And their downswing phase can be just as consequential as the boom phase. For all these reasons, the current boom in data centre construction bears close watching.
The Q1 national accounts released this week highlight two key principles for analysing macroeconomic data. First, never take top-line data, or shifts in those data, at face value. Second, macro aggregates are never just one thing. There is more than one good or service in the economy. Sectoral shocks matter, partly because they spread unevenly across the economy.
On the first principle, we see data fluctuations – mostly in exports but also in domestic transport and wholesale sectors – that have nothing to do with the underlying trend and everything to do with weather.
Cyclones are normal for the Pilbara in the first quarter of the year, but if the resulting disruption is abnormal, seasonal adjustment will not mop it up completely. This year, ports were disrupted but production was not. Mining output was accumulated as inventories instead of flowing overseas, leaving GDP largely unaffected. Exports should bounce back in coming quarters, as port infrastructure has mostly returned to full operation already. It was just a bump.
Another example of a bump that should not be construed as a trend can be seen in the national accounts’ labour market detail. As Westpac Economics’ colleague Pat Bustamante flagged in the preview note, strong hours worked in the quarter, coupled with weak GDP growth, induced a quarterly fall in measured labour productivity. (Cue the usual hand-wringing.) A funny thing happened on the way to the Temple of Productivity Gloom, though: average earnings per hour was also weak, leaving the outcome for unit labour costs reasonably benign.
The bump here relates to the seasonal pattern of leave-taking. Shifts in this pattern affect the relationship between hours worked and hours paid. If a worker on a salary takes less leave than usual for this time of year, their hours worked is higher, but their hours paid do not change. Dividing a fixed salary by a higher number of hours mechanically reduces average earnings per hour. Labour accounts data released today confirm this shift in hours worked versus hours paid. Indeed, in the quarter this effect went beyond the residual season pattern that emerged after the pandemic and is yet to be absorbed by standard adjustment methods.
Both are examples of “bumps” that need to be recognised, and in most cases looked through.
Some special factors are more than just a bump, though. They are also examples of when a purely top-down macro level view fails. Sometimes it is reasonable to treat millions of individual decisions as a single “thing”: “the” level of output, “the” price level, “the” labour market. Other times a purely macro, one-good, “representative agent” lens is misleading. The trick is to know which moment you are in. AI will not help with that judgement.
As we highlighted in the lead-up to this week’s national accounts, Q1 really was the quarter of the data centre in Australia. Around ¾ppts of the growth in the quarter look to be from a big increase in data centre construction and fit-out. While much of this involves imported inputs that do not add to local production (i.e. GDP) in net terms, nearly 40% was local value-add. After all, the buildings and chips do not (yet) build and install themselves.
There is an element of “bump” to this lump of investment, too. Local labour and other resources were expended in the quarter to build something that is not yet itself producing output (GDP). So there is an initial drop in measured labour productivity. Investment does rise, of course, but the build phase is more labour intensive than the output that the data centres produce once online. Short-term productivity pain, longer-term gain – and that is aside from whatever productivity boost the additional computing capacity affords to end users.
In this respect, the current data centre boom is more of a wave than a bump, bearing a considerable resemblance to the mining investment boom of the first decade and a half of the century. In this case, it is a technology wave as well as a sectoral investment boom. Waves cannot be ignored or subsumed into a top-down, homogenised view of the economy. They are fundamental drivers of outcomes for multiple years and must be analysed on their own terms. At the same time, they resemble each other in specific ways.
First, the initial build phase competes with the rest of the economy for resources, especially construction resources, and can feel quite disruptive as resources shift.
Second, a fundamental investment boom in a single sector will be largely impervious to the level of interest rates. To the extent that capacity pressures emerge in the overall economy, it will be other sectors that get squeezed by the monetary policy response. We are already seeing signs of that in household consumption and consumer-facing sectors. Indeed, household consumption is running at around 52% of the nominal economy – almost 5ppts below its pre-pandemic historical average.
Third, policy and politics matter for the shape of a wave. We are already seeing this in the backlash against data centres in the United States. While the build-out here faces challenges of ensuring enough power supply in the right places, so far, we have seen a significant build-out without material backlash or new regulatory roadblocks. Unlike the US, Australia actively tries to portray itself as an attractive destination for investment, given the tyranny of distance and the difference in local market size.
Finally, as the build phase peaks, different challenges will emerge. The downswing of the mining investment boom was an enormous drag on Australia’s economic performance, even when the level of investment was still high. Australia is still in the early stages of the data centre ramp-up, and so it might seem premature to talk about the downswing. But since it takes a lot less time to build an individual data centre than an enormous iron ore or gas project, the ramp-up and unwind could be steeper and shorter this time around.
This is all separate from AI as a technology. At some level, the data centres and the AI services are geographically separable. There are regulatory (e.g. privacy) and network latency reasons for the compute capacity to be near the users, and thus in Australia. This does not quite explain why the scale of the pipeline of projects here seems so large relative to some other non-US countries, however. Some of the outsized contribution stems from Australia’s natural endowments – abundant solar radiation and thus renewable energy. A welcoming regulatory environment and fast-growing domestic IT industry might also be part of the story. Whatever the drivers, the data centre investment boom is an aspect of the current technology wave that bears watching.
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