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FRBSF ECONOMIC LeTTer
2014-35

November 24, 2014

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Monetary Policy When the Spyglass Is Smudged
Early Elias, Helen Irvin, and Òscar Jordà
An accurate measure of economic slack is key to properly calibrate monetary policy. Two traditional gauges of slack have
become harder to interpret since the Great Recession: the gap between output and its potential level, and the deviation
of the unemployment rate from its natural rate. As a consequence, conventional policy rules based on these measures of
slack generate wide-ranging policy rate recommendations. This variability highlights one of the challenges policymakers
currently face.

It would be a mistake to characterize the Great Recession as simply a run-of-the-mill economic
downturn, only larger in magnitude. In the post-World War II era the United States experienced both
deep recessions and episodes of financial turmoil, but not since the Great Depression had the U.S.
economy suffered both simultaneously. The degree of economic dislocation has been considerable,
greatly altering the long-term structure of the economy and the outlook.
Economists are still grappling with this new economic order and how to refine their thinking. Not
surprisingly, implementing policy in such an uncertain economic environment has been specially
challenging. This Economic Letter examines how this new environment has made traditional measures of
economic performance harder to interpret. The tool we use to communicate these policy challenges is
the well-known Taylor rule.
This is the first in a two-part series. The second (Bosler, Daly, and Nechio 2014) details mixed signals
from the labor market.
Large revisions to potential output
The deviation of real GDP from its potential level has long been regarded as a standard measure of
economic slack. When the economy grows faster than its potential, the effects are widespread:
Overtime hours increase for workers, capital utilization rates go up for businesses, and inflation
pressures mount for consumers. Not surprisingly, the difference between real GDP and its potential
level, known as the output gap, is closely scrutinized by policymakers. Although potential GDP is not
directly observable, the Congressional Budget Office (CBO) regularly publishes an estimate of its value.

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Federal Reserve Bank San Francisco | Monetary Policy When the Spyglass Is Smudged |

Data on both real GDP and potential GDP go through a number of revisions. Data on real GDP come from
the National Income and Product Accounts (NIPA) published by the Bureau of Economic Analysis. The
NIPA relies on a wide variety of data that differ in quality, coverage, and availability. Initial GDP
estimates rely mostly on smaller-scale surveys, which are available reasonably quickly. Over time,
survey data are replaced with large-scale census data, which are more exhaustive but take longer to
collect.
By contrast, potential GDP estimates are
revised less frequently. Moreover, past
revisions have usually been small so that
even initial estimates about future values
have been reliable. Potential GDP had
moved slowly enough that the CBO
releases yearly updates together with 10year projections. However, the Great
Recession eradicated this stability and has
vividly demonstrated how quickly
estimates of potential GDP can change in
times of economic tumult. Between 2007
and 2014, the CBO revised its projection
of real potential GDP for the first quarter
of 2014 downward by almost 8%. Figure 1
depicts the CBO’s 10-year projections of
potential GDP from 2007, 2010, and 2014
alongside the path of real GDP for context.

Figure 1
Revisions to potential GDP

Sources: BEA and CBO, chained 2009 dollars.

A primer on the Taylor rule
How significant are these revisions of potential GDP, and how do they affect a policymaker’s assessment
of current economic conditions? This is difficult to answer considering only the data in Figure 1. We can
get a more complete picture by examining how revisions to potential GDP affect the policy
recommendations one would derive from a textbook policy rule such as the Taylor (1993) rule. This
benchmark is designed with price and output stability in mind. The rule incorporates two essential
elements to handle inflation’s deviation from its targeted level and output’s deviation from its potential
level. If inflation is at its target and the economy is growing on par with its potential, these two penalty
terms vanish and the policy rate equals the nominal equilibrium rate of interest.
There are numerous modifications to the original rule in Taylor (1993). Taylor (1999), Rudebusch and
Svensson (1999), and Coibion and Gorodnichenko (2005) provide good surveys. These modifications run
the gamut, from using forecasts rather than current values of inflation and output to adding a
smoothing term to capture the incremental way the policy rate is typically adjusted. The version we use
here was discussed in Taylor (1999) and has since gained wide acceptance as a natural benchmark.
According to this version of the rule, the policy rate can be expressed as follows:
Policy rate = 1.25 + (1.5 × Inflation) + Output gap.
We measure inflation using the personal consumption expenditures price index (PCEPI) excluding food
and energy. This measure is commonly referred to as core PCE inflation. Although the Federal Reserve is
ultimately interested in ensuring that headline inflation remains stable, core inflation is significantly less
volatile and therefore offers a more reliable measure (see Bernanke 2007). We measure the output gap
using the percentage difference between real GDP and its potential. The intercept in this rule is based on
an estimate of the natural rate of interest; our conclusions would only be reinforced if we accounted for

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Federal Reserve Bank San Francisco | Monetary Policy When the Spyglass Is Smudged |

the greater uncertainty about the natural rate of interest in the wake of the Great Recession (Leduc and
Rudebusch 2014).
Potential GDP and the Taylor rule
Figure 2 depicts three different policy rate
paths using the 2007, 2010, and 2014
vintages of the CBO’s potential GDP
plotted against the actual target for the
federal funds rate, the U.S. policy rate.
The estimated policy rates track the
federal funds rate and each other fairly
closely until the end of 2008, when the
federal funds rate hits the zero lower
bound and the three alternative policy
paths begin to diverge significantly.

Figure 2
Taylor rules by potential GDP estimates

This divergence comes from the sequential
revisions to potential GDP. Mechanically,
the recommended policy rate increases as
the output gap diminishes. With time and
Sources: BEA, CBO, and authors’ calculations.
more current data, a more accurate
picture of the recession and how it had
affected potential GDP emerged. Notice
that the 2007 and 2010 estimates of the output gap are so large and negative that the benchmark
Taylor rule suggests the policy rate should be negative for most of the period since 2008. Based on the
2007 estimates of potential GDP and the value of actual GDP today, the Taylor rule would recommend a
policy rate of –8.7%. This striking number underscores the importance of the revisions to potential GDP.
From output gap to unemployment gap with Okun’s law
A popular alternative for assessing slack in the economy is to use the unemployment gap, the gap
between the unemployment rate and its natural rate. This alternative gap measure offers two main
advantages for policymakers. First, unemployment data are available monthly as opposed to quarterly
for GDP data. Second, unemployment numbers offer a more direct discussion of the one of the Fed’s
explicit mandates, full employment. It is natural to ask then whether the unemployment gap provides a
cleaner measure of economic slack than the output gap and to determine how these measures are
related.
Okun’s law is a popular rule of thumb that relates changes in the unemployment rate to GDP growth at
an approximate two-to-one ratio. However, underlying this empirical regularity are important economic
mechanisms that justify the result and illuminate the link between the output and unemployment gaps.
For example, when businesses face declining demand, they reduce production using a blend of fewer
hours per worker, reduced staffing levels, decreased capital utilization levels, and changes in
technology. Historically, Okun’s law has been a remarkably stable relationship, but the Great Recession
has muddied the waters, as discussed in Daly, et al. (2014).
Using Okun’s law, the Taylor rule can easily be rewritten to incorporate an unemployment gap in place of
the output gap:
Policy rate = 1.25 + (1.5 × Inflation) – (2 × Unemployment gap).
The unemployment gap is measured as the percentage point difference between the unemployment rate
and the non-accelerating inflation rate of unemployment, or NAIRU. The NAIRU, just like potential GDP,

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Federal Reserve Bank San Francisco | Monetary Policy When the Spyglass Is Smudged |

is not directly measurable. However, the CBO regularly releases estimates of its value. These estimates
are closely linked to those of potential GDP and include several adjustment factors, for example, based
on the potential size of the labor force or potential labor force productivity. The version of the Taylor
rule that uses the unemployment gap is discussed in Rudebusch (2010).
Before 2008, the policy rates
recommended by the output and
unemployment gap versions of the
benchmark Taylor rule remained within a
few fractions of a percentage point of each
other and reasonably close to what the
federal funds rate turned out to be, as
illustrated in Figure 3. Note that we use
the most up-to-date measures of potential
GDP and the NAIRU to abstract from the
variation induced by revisions and focus
exclusively on the different signals
provided by each gap measure.

Figure 3
Two Taylor rules

Policy recommendations diverged
considerably once the Great Recession
was under way. If we ignore the zero
lower bound on nominal interest rates, the
Sources: BEA, CBO, BLS, and authors’ calculations.
unemployment gap version of the Taylor
rule called for policy to be set about 3
percentage points lower than the output
gap version would have suggested throughout 2010. The differences between the two narrowed over
the next few years, and by 2012 they appeared to be as close as in the past.
Recently, however, the unemployment rate has been gradually improving, whereas economic
performance, as measured by real GDP growth, has remained lackluster. As a result the difference in
the suggested policy rates has flipped: the unemployment gap version of the Taylor rule now calls for
policy to be about 2 percentage points higher than the output gap version. Once again, it appears that
Okun’s law and the margins firms use to adjust to the new economic environment have temporarily
diverged from normal. Conflicting signals from labor markets may shed some light on this recent
divergence, an issue that will be explored in the second part of this series (Bosler, Daly, and Nechio
2014).
Conclusion
Determining whether the economy is overheating or underperforming is critical for monetary policy.
Policymakers cannot simply rely on one indicator to make this judgment. This Letter has shown that in
times of economic turmoil it is especially difficult to get a clear read on the economy’s potential, and
different indicators can generate conflicting signals. Our analysis highlights the difficulties of using the
Taylor rule as a practical guide to implementing monetary policy in real time.

Early Elias and Helen Irvin are research associates in the Economic Research Department of the Federal
Reserve Bank of San Francisco.
Òscar Jordà is a senior research advisor in the Economic Research Department of the Federal Reserve
Bank of San Francisco.

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Federal Reserve Bank San Francisco | Monetary Policy When the Spyglass Is Smudged |

References
Bernanke, Ben. 2007. “Semiannual Monetary Policy Report to the Congress.”

July 18.

Bosler, Canyon, Mary C. Daly, and Fernanda Nechio. 2014. “Mixed Signals: Labor Markets and Monetary
Policy.” FRBSF Economic Letter 2014-36 (December 1).
Coibion, Olivier, and Yuriy Gorodnichenko. 2012. “Why Are Target Interest Rate Changes So Persistent?”
American Economic Journal: Macroeconomics 4(4), pp. 126–162.
Daly, Mary, John Fernald, Òscar Jordà, and Fernanda Nechio. 2014. “Interpreting Deviations from Okun’s
Law.” FRBSF Economic Letter 2014-12 (April 21).
Leduc, Sylvain, and Glenn D. Rudebusch. 2014. “Does Slower Growth Imply Lower Interest Rates?”
FRBSF Economic Letter 2014-33 (November 10).
Rudebusch, Glenn D. 2010. “The Fed’s Exit Strategy for Monetary Policy.” FRBSF Economic Letter 201018 (June 14).
Rudebusch, Glenn D. and Lars E.O. Svensson. 1999. “Policy Rules for Inflation Targeting.” In Monetary
Policy Rules, ed. John Taylor. Chicago: University of Chicago Press.
Taylor, John B. 1993. “Discretion versus Policy Rules in Practice.” Carnegie-Rochester Conference Series
on Public Policy 39, pp. 195–214.
Taylor, John B. 1999. “The Robustness and Efficiency of Monetary Policy Rules as Guidelines for Interest
Rate Setting by the European Central Bank.” Journal of Monetary Economics 43(3), pp. 655–679.
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Reserve Bank of San Francisco or of the
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