“Unfortunately, we have as yet devised no method to estimate accurately and readily the natural rate of either interest or unemployment. And the ‘natural’ rate itself will change from time to time.” Milton Friedman, American Economic Association Presidential Address, 1968.

What do you do if, on a dark and foggy night, you are forced to drive on a road with a sheer cliff on one side? Unless you know precisely where the road ends and the cliff begins, you will likely go slowly and keep your foot near the brakes. Driving like a tortoise is not the “first best” solution – fog lights that distinguish the road from the cliff would be better. But, absent proper illumination, going slowly is a safe response to perilous driving conditions. It helps prevent catastrophic, irreversible errors.

Such robust strategies are key to central bankers’ success as well. With only a dim view of the future (or even the present), it is prudent to adjust interest rates gradually as conditions become clear. Monetary policy experts also have long advocated “policy inertia” to prevent big mistakes that can arise from misperceptions of the state of the economy.

What are the key policy drivers subject to such hazardous misperceptions? To see, we can look at the Taylor Rule – a compact guide for setting interest rates. One version of the rule says that the policy rate should be set equal to the (weighted) sum of four things:

1) The equilibrium or “natural” real interest rate,

2) The policymaker’s inflation target,

3) The difference between current inflation and the target (the “inflation gap”),

4) And the difference between the actual and the “natural” rate of unemployment (the “unemployment gap”).

You can think of the “natural” rates of interest and unemployment as the rates that are consistent with price stability. (The original Taylor Rule uses the gap between actual and potential output instead of the deviation from the natural rate of unemployment.)

As Milton Friedman highlighted more than 50 years ago, policymakers do not *know* the “natural” rate of interest or of unemployment (and, as we highlighted last week, they do not know potential GDP either). The true natural rates – which are critical to policy rate decisions – cannot be directly observed. Instead, they must be estimated. And, whenever you estimate something, mistakes are inevitable.

One episode in policy history highlights the risks arising from estimation errors. In the 1970s, Fed policymakers persistently underestimated the natural rate of unemployment (and overestimated the economy’s potential). The result was a policy rate that was too low to prevent a sustained rise of inflation. While the Great Inflation may also have had other causes – like a reluctance to tolerate high levels of unemployment – it eventually took record interest rates and a deep recession to restore price stability and Fed credibility.

In theory, the natural rate of interest is closely linked to the economy’s trend growth rate. The idea is that faster economic growth is associated with a higher real rate of return on investment. In the current episode, evidence that the trend rate of growth has slowed (see last week’s post) has prompted observers to mark down their estimates of the natural rate of interest. FOMC members have been doing precisely that over the past three years – lowering their (implicit) projections of the real federal funds rate in the long run (based on the evolution of the median estimates from the Survey of Economic Projections) from 2¼% to 1¾%.

Some observers argue that the natural rate of interest has fallen much lower. Proponents of the view that we are in the midst of a “secular stagnation” driven by a sustained shortfall of aggregate demand – like former Treasury Secretary Lawrence Summers or Nobel Prize-winner Paul Krugman – have suggested that, consistent with the negative yields on some inflation-adjusted bonds, today’s natural rate could well be below zero.

How does this all matter for Fed policy today? A new report from the U.S. Monetary Policy Forum (USMPF) on our uncertainty about the natural rate of interest makes a renewed case for policy inertia. (Full disclosure: We are members of the USMPF, but are not authors of the latest report. You can find one of the authors’ take on the conclusions of the report here.)

The first key point from the report is that the natural rate of interest varies significantly over time, including prolonged periods when it is high and others when it is low (see chart below). Second, the natural rate is very difficult to predict. In fact, the range of forecast error is so large as to make the projections of little use as a guide for monetary policy.

U.S. ex-ante real policy interest rate as inferred from annual and quarterly data

The third key finding in the report is that, while the link between changes in trend growth and changes in the natural rate may be tight in theory, it is quite loose in practice. Instead, a range of other factors can push the natural rate higher or lower over extended intervals of time. These drivers include financial regulation, trends in inflation, fiscal policy, and asset price bubbles.

In the end, the report suggests that the natural rate currently is in the 1% to 2% range, well above what secular stagnationists believe.

Yet, even that one-percentage point range is sufficiently wide to make policymakers’ lives difficult. What should they do? Our answer, strongly supported by the excellent technical work in the report, is that this uncertainty strengthens the case for policy inertia. When you can’t accurately estimate the natural rate of interest or the natural rate of unemployment or the level of potential GDP, it makes sense to adopt a policy approach that is relatively insensitive to errors in those estimates. (We should note that there are situations in which gradualism is *not* the best way to manage uncertainty. For example, when policymakers are uncertain about the persistence of economic shocks or about the impact of policy on the trade-off between conflicting objectives, the robust policy response may be more aggressive than usual, not less. You can find a discussion of these issues here.)

To see what we mean, consider a Taylor-style policy rule in *changes* rather than *levels*. That is, think about how a policymaker might decide whether to change the policy rate from where it is today rather than figure out its best or optimal level. Looking at the four pieces of the simple Taylor rule – the natural real interest rate, the inflation target, the inflation gap and the unemployment gap – if we subtract today’s level from yesterday’s we are left with only two policy drivers: the change in inflation and the change in the unemployment rate. Unless the natural rates change rapidly, we don’t have to worry about them – our uncertainty becomes much less important.

This formulation – setting the change in the policy interest rate equal to a (weighted) sum of the change in inflation and (minus) the change in the unemployment rate provides substantial inertia to policy. The only reason to change the policy rate is if inflation or unemployment were to change. Otherwise, you stay put – there is policy inertia.

Like driving slowly on a foggy cliff road, such policy inertia is not the “first best” option. To the extent central bankers can estimate the natural rates of interest and unemployment (or the growth rate of potential output) accurately, using those estimates to set policy would be better, further stabilizing the economy. But when, as seems likely now, the uncertainty is high, policy inertia is an attractive and robust strategy.

What does this mean for the Fed? As the USMPF report concludes: “Policymakers who are concerned about natural rate uncertainty may want to adopt a later but steeper path for normalizing the funds rate.” That is, wait until inflation starts rising (and approaches the FOMC’s 2% objective) and the unemployment rate falls to sustainably low levels before starting to increase interest rates.

So, if you are wondering why the FOMC has waited so long to start raising interest rates in a recovery that is nearly six years old – longer than a mechanical application of the Taylor rule would suggest – natural rate uncertainty is a good reason. But, then, you might also anticipate that the FOMC, when it finally starts to hike rates, could go further than observers currently expect. That’s what policymaking without visibility implies.