An alternative rule to Taylor rule

Philadelphia Fed President, Charles Plosser in a speech reviews rules vs discretion in monetary policy making. He prefers rules but not the Taylor rule which looks at inflation and output gaps.

He says:

Today I would like to discuss how monetary policymakers should approach setting policy in a world in which economic data are measured imprecisely. This is a challenge for policymakers not only in times of crisis but in normal times as well.

I am sure many of you know of the seminal work by John Taylor, in which he showed that monetary policymakers appear to follow a rule in setting interest rates. These rules relate the policy interest rate to the behavior of key macroeconomic variables such as inflation and real activity. As I’ll discuss in a moment, I am in favor of a systematic, rule-based approach to monetary policy, primarily because it limits discretion and improves economic stability by reducing policy uncertainty. But I will argue that choosing the particular form of the rule must be done with great care, because many of the economic variables that could be used in setting policy are in fact poorly measured.

For example, many policymakers focus on measures of economic slack, such as the output gap or the unemployment gap, to provide guidance for policy. Broadly speaking, the output gap refers to the deviation of output from some level deemed optimal, often called “potential output.” Likewise, the unemployment gap is the deviation of unemployment from an unemployment rate that represents “full employment.” But how should we measure “potential output” and “full employment”?

He says calculating potential output or output gap via various statistical techniques is very imprecise.

One approach is to estimate potential output using the trend in actual output. Another approach derives an estimate based on a model of the production function for the economy. However, various studies have shown that such statistical measures of potential output or full employment are very imprecise. Moreover, the most common statistical constructs for these variables often have little in common with their relevant theoretical counterparts. What’s more, different models of the economy can lead to different theoretical concepts for such output gap or unemployment gap variables. So relying on these constructed gap variables in the formulation of policy forces the central bank to operate under a high degree of uncertainty.

The same ideas were discussed by Bernanke and Kohn in their speeches (Taylor responded as well).

He adds there are more issues with output gaps:

Three problems arise when trying to rely on output or employment gaps to guide policy choices in real time. First, theory does not always suggest that desirable policy should be based on an output gap measure at all — it depends on the particular model and the type of economic shocks that are hitting the economy. Second, even in theoretical models in which optimal policy is based on an output gap measure, such measures are inherently unobservable and therefore must be statistically estimated. And third, the most common statistical measures of the output gap do not correspond particularly well to the theoretical measures that are relevant for policy decisions.

He suggests a different kind of rule which looks at inflation deviations from a target and economic growth.

So, if we have problems in measuring output gaps, what type of rule should we use? I believe it makes more sense to use an interest rate rule that responds aggressively to movements in inflation relative to a target and, if it responds to real economic activity, responds to a measure of the change in economic activity itself rather than some deviation from unobserved potential. While measures of the growth rate of output are also subject to data revisions, they are not dependent on an unobservable construct associated with the level of output. Moreover, the measurement errors in growth rates don’t tend to cumulate, which can often happen with mismeasured levels.

My preferred approach also is consistent with the idea that, as economic growth accelerates, the economy’s underlying real rate of interest also rises, signaling the need for tighter monetary policy. This is likely to keep policy ahead of the curve rather than behind it — lowering rates sooner in a cyclical downturn and raising them earlier in a recovery.

He points to examples:

Research has shown that data uncertainties are not just theoretical curiosities. They have caused actual problems when policy has been based on mismeasured gaps, resulting in unnecessary economic instability. A particularly poignant example is the Great Inflation of the 1970s in the U.S. While I do not believe that mismeasurement is the sole reason for the stagflation of that era, I do believe it was a contributing factor. Part of the problem appears to have been caused by basing monetary policy on unemployment gaps. Over much of the 1970s, real-time estimates of the natural rate of unemployment indicated that the economy was operating below its full-employment potential. In fact, the opposite was true. This misperception led to an inflationary bias to policy, as policymakers reacted to the mismeasured unemployment gap.

In contrast, a good case can be made that the Fed seemed to follow more robust rules during the mid to late 1990s, responding aggressively to deviations of inflation from a target and to economic growth — not gaps. By doing so, the Fed averted a large deflation that would have occurred if it had used real-time unemployment or output gaps. Chairman Greenspan’s choice not to base monetary policy on gaps had its precursor under the leadership of William McChesney Martin. During most of Martin’s chairmanship, the Fed raised interest rates early in recoveries, responding to economic growth rather than gaps.

Hmmm. The speech also has interesting references.


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