Four Shock Doctrines – ActionForex

Four Shock Doctrines - Actionforex F Special110

Shocks make it hard to know where you are. It helps to know that some shocks are policy choices, people can respond to mitigate shocks, and net effects can vary and sometimes linger.

  • Supply shocks complicate the already difficult task of assessing the supply–demand balance underlying monetary policy decisions. If estimates of current slack or trend growth in capacity are inaccurate, so will be the interpretation of the size and impact of a supply shock.
  • Some general principles about shocks are useful for analysis. First, many “supply shocks” are policy shocks within the control of some decisionmaker, and thus specific to that decisionmaker. Second, other people have agency to respond to the shock, usually to mitigate it but occasionally exacerbating it.
  • Third, buffers of inventories or spare capacity absorb supply shocks, making them less visible. Without economic slack, supply shocks might seem more frequent even if they are not.
  • Fourth, temporary shocks can have lasting effects. This is especially relevant for geopolitical policymakers, but recent research suggests central banks need to allow for the possibility that a period of tight policy worsens supply capacity over the longer term.

The RBA’s hawkish tone in recent months stems from its assessment that demand is currently outstripping supply. It is trying to engineer a period of below-trend growth so that demand comes back into line with supply. How far it thinks it needs to go with that slowdown in turn depends on how fast it thinks Australia can grow without hitting capacity constraints. However, this is one of those situations where you do not know exactly where you are, or how fast you can go before hitting the skids. The data are uncertain, supply capacity can only be estimated not directly observed, and you just have to do the best you can with the available data.

This uncertainty matters even more when supply shocks occur. You can only see the movements in quantity and prices, which capture the combined effect of the shock and the trend growth in supply capacity, conditional on the pre-shock starting point. You don’t know how big the shock was, and if your estimates of the trend or the starting point are off, you will mis-attribute some of the resulting moves in price or quantity.

For example, a downbeat view of trend will lead you to attribute less of the weakness in quantity to the shock, and more to underlying supply capacity growth being slow. In this environment it is all too easy to either underestimate spare capacity or to overestimate the sensitivity of prices to shocks of this kind.

Extracting trend from shock and signal from noise is a perennial issue for any forecaster. If supply shocks have become more frequent or larger, though, forecasting becomes even harder. In that situation, it helps to think more deeply about the shocks themselves. There are principles that can help with this, some of which suggest a need to step outside traditional models developed decades ago and incorporate more recent research.

Many shocks are a choice

First, the really big adverse supply shocks of recent years are mostly policy shocks. Russia invading Ukraine was a choice. The US imposing tariffs was a choice, as was attacking Iran. And while the pandemic was caused by a virus, most of the economic impact was driven by policy choices around control measures.

Because they are policy shocks, their size and shape are determined by the costs and constraints they impose on the policymakers who unleash them. Thus Trump blinked when the market fallout from tariffs reached a threshold and tends to stop attacking Iran when oil prices rise high enough. If a policy choice imposes a large cost on the community, it is only because the decisionmakers believe that the alternative is worse (think the casualties of an uncontrolled pandemic, but also the loss of face and power from an invasion-turned-quagmire). In other words, you can stop punching yourself in the face anytime you like, so you will only keep punching if the pain is less than the benefit of looking tough.

Another implication of these being policy shocks is that their nature and frequency often depend on politics and personality. That means changing the personalities changes the shocks. For example, current trade disputes and other fractures in the US–European relationship should not be assumed to continue beyond 2028, though they still could.

Others can respond

Second, other people do not stand still. People can respond to shocks, and they will do so in ways that mitigate the impact on them. This is why second-round thinking is so important, as we have emphasised in a range of contexts.

Most of the time, responses that mitigate the impact on the individual reduce the overall impact as well. Much catastrophising about particular shocks is therefore overdone. However, sometimes people make things worse, as the panic buying of toilet paper in the pandemic and petrol more recently has shown. It is these adverse, compounding feedback loops that policymakers worry about most.

Shocks are perennial, symptoms differ

Third, economic slack is a buffer that absorbs supply shocks and makes them less visible. Supply shocks might not be more frequent, just more obvious. When economies no longer have significant spare capacity, even relatively small supply shocks become more visible in quantities and prices.

Consider a typical supply disruption – a flood or a train derailment affecting a mine, for example. Even if the repairs take a while, it is often the case that the disruption is not evident in economy-wide production or export data. Other facilities had enough spare capacity, or inventories were large enough, to fill the gap. And if there are spare resources in construction and related labour, the repairs are done quickly.

When supply and demand are in balance, though, small supply shocks cannot always be buffered. The inventories and other idle resources just aren’t there to make up the gap. Then you are more likely to see the shock in economy-wide quantities and prices. Thus it is not clear whether we have more supply shocks, or just more visible ones.

As noted last week in a labour market context, for example, extra labour supply when there is already labour market slack means more unemployment, not more employment. At full employment, though, extra labour supply boosts employment (the quantity). Whether it also boosts unemployment depends on how much demand moved at the same time.

Effects can linger beyond the shock

Fourth, temporary shocks can have lasting effects. For example, even if energy prices return to something like pre-war levels over time, every person who bought an EV in response to high petrol prices will dampen demand – and so prices – in a lasting way. Indeed, one of the constraints for the Iranian government in the current conflict is the risk that the rest of the world protects its energy security by permanently decoupling from Middle East oil supply. This is why, as we have noted previously, blocking the Strait of Hormuz is a time-limited source of leverage for Iran. Similarly, one can only disrupt relationships with allies (or customers) for so long until they start finding ways to do without you for good. It has also been known for some time that wars and crises lower output permanently.

These lasting effects are not always the ones people anticipate. Recall how worried people were about the scarring effects of job losses in the pandemic. But while it didn’t happen that time, forecasters need to be alert to the possibility that cyclical developments have lasting path-dependent effects. There is an emerging literature on this possibility, including from central banks (see here and here). According to this work, the full-employment level of employment and productivity could both be dragged down by overly tight policy, and a mildly ‘hot’ economy might actually help more than a weak economy hurts; this is an aspect of “holding onto the employment gains” that has been underplayed in much of the debate. Standard models do not allow for this, and it makes policy decisions even more fraught than widely believed.


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