The risks of central banks in data dependency

While the Fed should take account of the rate pipeline, the market might not if the incoming data consistently comes through above forecasts.

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In fact, many central banks actually set policy based on data from another country if they follow a currency board system, for instance. But for most, the data are key and, right now, it seems that there is a state of heightened data dependency. The risk is that this leads to an over-tightening of monetary conditions.

As we said earlier, virtually all central banks are data dependent. But this dependency goes up and down. For instance, a year ago when the fed funds target was 0.25% and CPI inflation was 6.5%, there was really very little data dependency at all. The Fed needed to lift rates quickly and aggressively no matter what the incoming data said.

Today, it is the opposite: rates are high and inflation appears to be coming down. Hence the Fed seems to be finessing the end of the tightening cycle and has become very data dependent as a result. Some central banks seem to be at a similar stage to the Fed, like the RBA or BoC, while others, like the ECB still seem to have lots of (monetary tightening) work to do and appear slightly less data dependent than the Fed as a result.

In theory, there’s nothing wrong with data dependency. Indeed, we might be concerned if central banks adjusted policy without any reference to incoming data at all. However, the sort of extreme data dependency that the Fed seems to be advocating could prove dangerous and potentially lead to an overtightening of policy, and hence a possible overtightening of financial conditions globally given the importance of Fed policy and the dollar in the global monetary system.

What are these dangers? Mr. Steve Barrow, Head of Standard Bank G10 Strategy, said the first is that data dependency, as followed by the Fed and others means assessing information over a very wide range of areas. Some of this includes the big data releases, like the CPI and payrolls, but also relates to other official hard data, soft data, and will likely also include information that only the central bank can see, such as feedback from the regional Feds and other more anecdotal information. For the market though, there’s a danger that data dependency just means two numbers: the CPI and payroll report. But what if these reports are not necessarily saying the same thing as the whole breadth of information that the Fed encapsulates in its data-dependency framework? We could find that the market runs off in one direction while the Fed is reticent to follow. This in turn could create market-generated excessive tightening or loosening of policy and our best guess is that it is more likely to be the former as our sense is that the market is more sensitive to data on the CPI and employment that are strong, than numbers that are weak.

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Another issue with data dependency is that incoming data has to be weighed against the degree of monetary tightening that’s already in the pipeline. The longer this pipeline the less data dependent central banks should become. But while the Fed should take account of the rate pipeline, the market might not if the incoming data consistently comes through above forecasts. Another factor is that the Fed and other central banks still need to base policy decisions on their forecasts to some extent, even when they appear to be exclusively in data dependent mode, and particularly if a shock happens, such as a slump in energy prices. Here too the market might not appreciate the role that forecasts could still have to play.

In sum, we do see a risk here that either the Fed overtightens if it becomes obsessively data dependent, or that markets tighten financial conditions too much by assuming rate hikes that are not ultimately delivered.