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Authorized for public release by the FOMC Secretariat on 01/11/2019
June 7, 2013
Assessing the Recent Decline in the Unemployment Rate
and its Implications for Monetary Policy
Stephanie Aaronson, Bruce Fallick, Charles Fleischman, Robert Tetlow
The unemployment rate in the second quarter of this year is on track to average
¾ percentage point less than what the staff had anticipated in the September 2012 Tealbook.
(Compare the black and red lines in the top left panel of figure 1.) Given the absence of any
material change in our assumptions for the natural rate of unemployment as of the April
Tealbook, the surprise in the unemployment rate has translated into a roughly equivalent
reduction in the gap between the actual and natural unemployment rates (the blue and red lines in
the upper right panel of figure 1), with attendant implications for monetary policy.
However, the continued downside surprises in actual unemployment have led us to revisit
our assumptions for the natural rate and potential output for the June Tealbook projection. In
brief, we now attribute some of the unexpected decline in the unemployment rate to an earlierthan-expected decline in the natural rate of unemployment rather than viewing it all as a
narrowing of the unemployment gap. In particular, we now assume that the natural rate declined
about ¼ percentage point more through the end of 2012 than we had previously assumed, and we
anticipate that it will fall a little more quickly over the remainder of the forecast period, reaching
our unrevised estimate of its long-run level of 5¼ percent by the end of 2015. We have
attributed this more-pronounced downward trajectory in the natural rate to both improvements in
labor-market functioning and some additional permanent withdrawals from the labor force.
The faster decline in the natural rate is only one of the ways in which we could have
modified our supply-side assumptions in order to better explain recent developments in the labor
market, and one purpose of this memo is to explore some plausible alternative explanations and
their implications for monetary policy. We start by describing, in more detail than is possible in
Tealbook Book A, the changes we made to our supply-side assumptions. We then contrast the
adjustments we made in the Tealbook forecast with a pair of alternative explanations for these
recent developments that roughly bracket the range of possible implications for our reading of
slack in the economy. We then use the FRB/US model to illustrate the implications of these
alternative scenarios for monetary policy.

An Okun’s Law Framework
A useful starting point for thinking through the evolution of labor market conditions is Okun’s
law. A simple version of Okun’s law equates the unemployment rate gap, specifically the

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*
difference between the unemployment rate, ut , and the natural rate of unemployment1, ut , to the
*
level of the GDP gap, expressed as the difference between GDP, y t , and potential GDP, yt (both

output variables being measured in natural logarithms), plus an error term,  t :
(1)

ut  ut*   ( yt  yt* )  t

Typically β has been estimated to be about -½, so that when output is below its potential level the
unemployment rate is above the natural rate, and the unemployment rate gap is about half the
size of the output gap.2
Conditional on our assumptions for the natural rate and potential output, the two measures of
slack may deviate, a feature captured by the error term ε. Our understanding of these errors is
*
enhanced by decomposing the output gap as in equation (2) into the gaps in productivity, qt  qt ,

*
and labor input, which is the sum of the gaps in the participation rate, lfpt  lfpt , in the
*
workweek, wwt  wwt , and the negative of the unemployment rate gap. Equation (2) also

includes a residual vt
(2)

yt  yt*  (qt  qt* )  ( wwt  wwt* )  (ut*  ut )  (lfpt  lfpt* )  vt

ee*

As before, the asterisks denote the unobserved structural or trend values of the variables.3 Note
that together the labor force participation rate and (up to a transformation) unemployment rate
gaps form the employment gap, et  et* , to which we will return below. Because labor
productivity is measured for the nonfarm business sector and the unemployment rate and
participation rate are available only for the aggregate economy, the residual, vt , captures the
effects of the sectoral differences, among other things.4
1

When defining the unemployment rate gap, we use the “effective” natural rate, which includes the estimated
effects on the unemployment rate of the extended and emergency benefit programs.
2
The staff’s working version of Okun’s Law model allows for a dynamic relationship between the unemployment
rate gap and the current and lagged values of the GDP gap. The coefficients on the GDP gap terms sum to about
negative ½.
3
As typically specified, the gap accounting includes the employment rate gap, which is the negative of the
unemployment rate gap. To simplify the discussion we specified equation (2) in terms of the negative of the
unemployment rate gap.
4
These differences between the NFB sector and the aggregate economy can be important, as the NFB sector has a
more pronounced cyclical pattern than the other sectors of the economy. The more complete accounting that the
staff uses is an identity where the GDP gap is the sum of the gaps in the components shown as well as the gaps in
the ratios of output and employment in the NFB sector to the total economy. These omitted ratios are represented
here by the residual. Peter Clark (1983) shows that the more complete version of equation (2) that the staff uses
holds because the gaps in each of the components can be represented as a function of the GDP gap and its lags, with

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Over the course of the business cycle, each of these elements moves relative to its trend. An
ordinary Okun’s law equation like equation (1) attempts to embody the typical cyclical
relationship between the unemployment rate gap and the GDP gap in the single coefficient β,
subsuming the usual relationships among the underlying gaps (labor force participation, the work
week, and so forth).5 Unusual movements in any combination of the underlying gaps can result
in a nonzero error in equation (1). (Indeed, even an error of zero may reflect unusual
movements that cancel each other out.) In other words, when movements in GDP and the
unemployment rate appear to be at odds, the explanation may be related to atypical movements
in some combination of the productivity, work week or participation rate gaps or to misestimation of u* or y*.6

Revised Supply-Side Assumptions for the June Tealbook
In our view, the unemployment rate rose more during and immediately following the recession
and fell more quickly during the recovery than could easily be explained by the simple Okun’s
law relationship in equation (1), conditional on reasonably smooth paths for potential output and
the natural rate of unemployment. We judge that firms reacted to the plunge in economic
activity and the accompanying heightened uncertainty by cutting employment more than would
normally have been consistent with the fall in actual production. Moreover, as real GDP began
to recover, firms responded to the increase in demand, to a greater than usual extent, by
increasing productivity rather than by adding workers. However, as the recovery has continued,
we think that firms have brought their workforces and labor productivity back towards more
sustainable levels, causing the unemployment rate to decline by more than could be explained by
the closing of the GDP gap. In the April 2013 Tealbook, we assumed that the unemployment
rate had fallen enough by the end of 2012 so that the unemployment rate gap and the GDP gap
provided consistent signals about slack in the economy.
In accordance with this hypothesis, we assumed a substantially lower level of potential output
(and structural productivity) than would have been necessary to make Okun’s law fit from 2008
through 2012. That is, under our assumptions in the April Tealbook, an unusually large and
persistent Okun’s law error (a positive ε in equation (1)) opened up during the recession (as
indicated by the space between the black and blue lines in the lower left panel of figure 1), which
began to close in late 2010 and was essentially gone by the end of 2012.
cross-equation restrictions on the coefficients on the contemporaneous GDP gap and on the sum of the residuals in
each equation. Note that we assume potential population growth equals actual population growth.
5
Equation (1) has typically provided an adequate representation of the average co-movement of aggregate output and
the unemployment rate, and one that requires fewer assumptions about difficult-to-estimate trends in other
components. However, this has not been the case in recent years, which is why we have placed greater emphasis on
the elements in the gap accounting in equation (2). Nevertheless, we continue to assume that as the effects of the
economic crisis fade, the parsimony of equation (1) will again be a virtue.
6
In addition, there may be many other reasons for an error in equation (1), including measurement errors in GDP or
the unemployment rate, and changes over time in the value of β or in the dynamic structure of the relationships.

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In addition, we assumed that the natural rate of unemployment rose from 5 to 6 percent during
the recession, both because much of the rise in the actual unemployment rate was concentrated
among permanent job losers, and because studies of the Beveridge curve (e.g. Barnichon and
Figura (2011)) pointed to a decline in labor market match efficiency. We have also attributed
some of the increase and subsequent decrease in the unemployment rate to the effects of the
extended and emergency unemployment insurance benefit programs.
However, even conditional on our downward-revised path for potential output, the
unemployment rate fell more in the first quarter of this year than would be suggested by Okun’s
law, and, based on our current projection for real GDP this pattern seems to have continued into
the second quarter. To better account for the decline in the unemployment rate since the middle
of last year, we have made additional revisions to our supply-side assumptions for the June
Tealbook: We now assume that the natural rate of unemployment is on a more pronounced
downward trajectory than we had previously assumed, due both to somewhat greater
improvement in labor market functioning and a slightly steeper pace of decline in the trend labor
force participation rate. These supply-side revisions imply that both the unemployment rate gap
and the GDP gap were a little wider at the end of last year than we had previously assumed and
that less of the recent decline in the unemployment rate reflected a narrowing of labor market
slack.
We have assumed for some time that as the labor market recovered, the natural rate of
unemployment would gradually move down to near its pre-recession level as labor market
functioning improved and some unemployed workers permanently left the labor force. In fact,
we lowered the trajectory of the natural rate of unemployment a bit for the January Tealbook. As
noted above, we have further altered our assumptions and have the decline starting in early 2011
rather than in 2012 (see the lower right panel of figure 1.) As a result of these adjustments, the
unemployment rate gap is ¼ percentage point wider at the end of 2012 than in the April
Tealbook. (Compare the black and blue lines in the top right panel of figure 1.) Moreover, we
now expect the natural rate to reach our estimate of its long-run level of 5¼ percent by the end of
2015, two years earlier than we had projected in the April Tealbook.
The evidence supporting improvement in labor-market functioning is mixed. As shown in the
top left panel of figure 2, estimates of the degree of mismatch across industries and occupations,
such as those constructed by Sahin et al. (2012) and by Lazear and Spletzer (2012), suggest that
labor market functioning has improved considerably. In addition, the amount of permanent job
loss (the top right panel), which has historically been associated with greater difficulty in
matching to a new job, has receded, although it remains somewhat elevated. In contrast, the
Beveridge Curve has not yet shifted back toward its pre-recession locus, and related estimates of
matching efficiency, such as those constructed by Barnichon and Figura (2011), shown in the
middle left panel, suggest that there has been little improvement in the natural rate since late
2010. Despite the ambiguity, we have taken some signal from this evidence that the increase in
structural unemployment induced by the recession has diminished.

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The evidence supporting a steeper decline in the trend labor force participation rate is also
mixed. The labor force participation rate has fallen by more than we were expecting, and the
latest reading is ¼ percentage point below what we were projecting in the September 2012
Tealbook. Although we do not have a precise explanation, it seems possible that some
individuals who are near the end of their planned working years may have accelerated their
retirements and that others have applied for and begun to receive Social Security Disability
Insurance (SSDI) payments. Because such withdrawals are likely to be concentrated among
those who would have the greatest difficult finding acceptable jobs even after a full economic
recovery, their withdrawal would not only lower the trend participation rate but would also lower
the natural rate of unemployment, leaving a larger unemployment rate gap than under current
assumptions. However, rates of exit out of the labor force from unemployment have not been
especially elevated in the demographic groups we would expect to be most likely to accelerate
retirement. As to disability, there has been a large increase in the number of recipients of SSDI
since the recession began. However, most of this appears to be a continuation of the secular
upward trend. (See the middle right panel of figure 2.) While there does appear to have been a
cyclical increase in the number of applicants for disability payments (not shown), given
historical approval rates, this does not imply a large increase in the number of recipients.
Furthermore, while we view recipients of SSDI as contributing to a lower trend participation rate
because few persons leave the SSDI program once they have begun to receive payments, it is
possible that under the current extraordinary circumstances, a greater number than is typical
could return to work once labor demand improves sufficiently.
In any event, we have marked down our estimate of the level of the trend participation rate at the
end of last year by 0.1 percentage point relative to the April Tealbook, accounting for about onethird of the downward revision to the natural rate of unemployment.
We view this revision to our assumed trend for the labor force participation rate as better
balancing the risks in our projection between the possibility that more of the recent decline
reflects trend factors and the possibility that more of the decline reflects an unusual cyclical
response. However, this evidence is by no means conclusive. Below we will explore a scenario
in which cyclical phenomena explain more of the decline in the labor force participation than we
had assumed in the April Tealbook. Several bits of evidence led us away from incorporating that
interpretation into the baseline projection. First, to explain the recent declines in participation as
an unusually large cyclical response in the face of more than two years of rising employment and
a falling unemployment rate would require that the participation rate lag the unemployment rate
by more than has been the case historically.7 Of course, this episode may be different because
7

For example, Erceg and Levin (2013) estimate that the typical lag is considerably shorter, on the order of two
quarters.

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of the extraordinarily long durations of unemployment. However, rates of labor force
withdrawal for the long-term unemployed (shown in the bottom left panel of figure 2) are not
particularly high relative to those with shorter durations of unemployment, suggesting that this is
not the case. Second, broader measures of labor underutilization from the BLS, such as U5
(shown in the bottom right panel of figure 2), which adds to the unemployed those who are
marginally attached to the workforce), do not suggest unusual movements in discouragement.
Third, the staff’s model of labor force participation has, for some time, shown a lower level of,
and steeper decline in, trend labor force participation than was built into the April Tealbook
projection. Note, however, that several other estimates of the trend participation rate suggest a
higher trend than we have assumed. For example, see Aaronson and Brave (2013).
From the perspective of our June Tealbook supply-side assumptions, the unemployment rate gap
remains the best single measure of labor market slack. As noted above, there is much
uncertainty about the trend in the participation rate, and thus the participation rate gap.
Moreover, given the numerous influences on the participation rate, movements in the
participation rate around any trend would be hard to explain. Given that history, we do not view
the movements in the participation rate gap to be to be sufficiently out of line with the
unemployment rate to significantly distort the signal sent by the latter. The employment-topopulation ratio is an alternative measure of slack that takes into account the low level of the
participation rate. However, the employment-to-population ratio is the product of the
unemployment rate and the labor force participation rate, so the interpretation of the
employment-to-population ratio depends upon one’s view of the participation rate.8
We decided against a further downward adjustment to structural productivity and potential
output in the current Tealbook projection, for several reasons. First, our downward adjustment
to potential output as of the April Tealbook was consistent with the average historical effect of
financial crises found in studies, such as Furceri and Mourougane (2012).9 Second, under our
April Tealbook assumptions, the level of productivity was still well above its trend at the end of
last year, even as we assumed that the unemployment rate had moved back into line with the
GDP gap. Given these considerations, steepening the decline in the natural rate of
unemployment seemed the more appealing way to reconcile the evidence as neatly as possible.10
Indeed, the low level of payroll employment relative to its pre-recession level seems more

8

For a general discussion of the unemployment rate as a summary of labor market conditions and a comparison to
alternatives see the memo to the FOMC, “Assessing Conditions in the Labor Market”, December 2012.
9
A financial crisis and deep recession may reduce structural productivity by reducing capital formation and
inhibiting permanent improvements in TFP by making it more difficult to finance the necessary investments and
increasing uncertainty.
10
It is also possible that the natural rate of unemployment didn’t rise as much during the recession as we have
assumed. In this case, the rise in unemployment during the recession was even more cyclically unusual, and the
recent improvement would reflect the greater required normalization.

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consistent with the greater labor market slack that is implied by the lower natural rate of
unemployment that we now assume.

Alternatives to the Baseline Explanation
There are many possible characterizations of the recent behavior of the unemployment rate other
than the one embodied in the staff forecast, which would lead to different assessments of the
amount of slack in the economy and thus have different implications for monetary policy. Here
we highlight two alternatives to the changes we have implemented for the June Tealbook that
serve to illustrate a range of possible implications. In assessing the implications for slack and
monetary policy, we compare these alternatives with the forecast in the April Tealbook.
More of the decline in the labor force participation rate is cyclical: The labor force
participation rate has fallen about 2 percentage points (on a data-consistent basis) since the
business cycle peak. Based on our assumptions in the April Tealbook, we attributed about twothirds of this 2 percentage point decline to the downward trend in participation. However it is
possible that less of the observed decline is attributable to the trend in participation and more
reflects a reaction to the extended period of weak labor demand. (As noted above, under this
explanation the labor force participation rate notably lags the business cycle in the current
episode.) If we are experiencing a greater-than-usual cyclical response in the labor force
participation rate, then to the extent that the potential workers who dropped out are a ready
source of labor that could re-enter when conditions improve sufficiently, the unemployment rate
would provide a misleading signal of the amount of slack in the labor market.11 Moreover,
because we would attribute less of the recent decline in the labor force participation rate to its
trend, we would raise our estimate of trend participation and therefore also our estimate of
potential output. Hence, consistent with equation (2), the output gap would be wider than under
the staff’s current assumptions for trend participation.
Conditional on our other assumptions in the April Tealbook, the unemployment rate gap in this
scenario is smaller than would be expected given the GDP gap (that is, there is a negative Okun’s
law error) because the unemployment rate gap itself understates the amount of slack in the labor
market. Thus, in this scenario the gap in the employment-to-population ratio—which combines
both the unemployment rate gap and the participation rate gap—provides a better sense of labor
under-utilization. Looking ahead, at some point as the economic expansion continues, the
unemployment rate would be buoyed by people moving into the labor force, and should fall less

11

Unlike the changes we have implemented for the June Tealbook, where lower trend participation helped explain
the downward revision to the natural rate of unemployment and the decline in the actual unemployment rate, the
change discussed here is explicitly limited to an explanation for the decline in the actual unemployment rate.

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than would be suggested by movements in the output gap alone, until eventually, the two gaps
come back into their historical alignment.12
The level of structural productivity is lower than we assumed in April: At present, the level
of real GDP is 8½ percent lower than it would have been had GDP grown at the potential rate the
staff projected prior to the financial crisis. We have assumed that much of this lower level of
economic activity represents lower potential GDP, largely reflecting a weaker assessment of
structural productivity in the years since the onset of the crisis. However, while we have
calibrated our downward revision to structural productivity based on past experience, every crisis
is different and our uncertainty around this assumption is high. Thus, it is quite possible that the
current level of structural productivity is even lower than we have assumed. To the extent this is
true, the level of potential output is also lower than we had estimated in the April Tealbook, and
the GDP gap is correspondingly narrower.
Conditional on our other assumptions in the April Tealbook, the unemployment rate gap in this
scenario, which is not directly affected by the change to potential output, would indicate more
slack in the economy than the GDP gap—in other words there would be a positive Okun’s law
error (the ε in equation (1)). In this case, firms would have made less progress in bringing their
workforces back to more sustainable levels than we had assumed in April. Looking ahead, we
would expect the unemployment rate to come down more quickly than would be suggested by
the closing of the GDP gap, as firms increase their labor input, bringing labor productivity down
to a more sustainable level.

Two Illustrative Scenarios
In this section we illustrate the significance for monetary policy of the two alternative
interpretations of the surprises in labor market conditions that we think bracket the range of
possibilities.
Our first scenario assumes that trend rate of labor force participation follows a higher path than
in our baseline, beginning slowly in 2002 and growing to a difference of about 1 percentage
point by the first quarter of 2013; the higher trend participation rate is also assumed to persist
indefinitely. This revisiting of history implies that only about one third of the observed decline
in the participation rate since the fourth quarter of 2007 is associated with a decline in trend
participation, whereas in the baseline nearly two thirds of the observed decline is accounted for
by trend. This results in a participation rate gap in the first quarter of 2013 that is approximately
-1¾ percentage points, instead of -¾ percentage point as in the baseline. As discussed in the
previous section, the relationship of the participation rate to the business cycle is also very

12

In the April Tealbook, we also assumed that the labor force participation rate gap would narrow during the
projection period, but that this represented a “normal” cyclical improvement in participation.

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different in this scenario than in our baseline thinking, with the participation gap notably lagging
the cycle as measured by the unemployment rate gap.
Three implications arise from this alternative interpretation of history. First, the standard
FRB/US model equation describing the evolution of the participation rate will not suffice to
explain this reimagined history. Thus, an alternative model equation is substituted for the
model’s standard equation for labor-force participation to allow the participation rate gap to have
a more pronounced cyclical character than has typically been the case historically, and to allow
the participation rate to lag persistently behind the unemployment rate gap. Second, the atypical
comovement of the participation rate gap relative to the unemployment gap implies that the
unemployment rate, by itself, will not provide an accurate signal of labor market slack. As a
consequence, it may no longer be appropriate to interpret the “maximum employment” half of
Committee’s dual mandate as equivalent to seeking the return of the unemployment rate to the
natural rate.13 When the participation gap is negligible, or when it moves together with the
unemployment gap, the unemployment gap can ably stand in for an overall employment gap in
the design of monetary policy; however, the scenario considered here is one example where this
need not be the case.14 Third, in this alternative interpretation the larger and more cyclically
sensitive participation rate gap leaves more room for monetary policy to ameliorate labor market
conditions than would otherwise be the case.
We consider optimal control simulations under this higher trend participation rate scenario,
under two different objectives for monetary policy: In one instance, we maintain our usual
assumption that the Committee seeks to minimize deviations of the unemployment rate from the
natural rate of unemployment, in addition to the usual penalty on deviation of inflation from its
target and a penalty on the change in the federal funds rate; in the other, we instead assume that
the Committee chooses paths for the funds rate with the deviation of employment from trend
employment in mind as the “maximum employment” leg of its mandate.15 In both cases, we
employ as the baseline the extended April 2013 Tealbook projection and assume that the Federal
Reserve’s balance sheet policies remain at their baseline paths.16
The information assumptions surrounding these simulations are the same as those in the optimal
control exercises reported in Tealbook B: In all instances, we carry out these experiments using
13

This scenario is in the spirit of Erceg and Levin (2013).
To operationalize the insufficiency of the unemployment rate as a summary statistic of resource utilization we also
alter a few other equations of the FRB/US model’s employment sector so as to “break” Okun’s law in the model,
thereby allowing the unemployment gap and output gap to vary over time to a certain degree. In terms of equation
(1), this means that we are allowing  to vary over time.
15
As equation (2) shows, the employment gap is simply (a transformation of) the unemployment gap plus the
participation rate gap. In addition, given the assumptions that actual and potential population growth are identical,
minimizing the employment gap can equivalently be thought of as minimizing the deviation of the employment-topopulation ratio from its trend (or sustainable) ratio. Omitted from consideration here is anything to do with a work
week gap.
16
Note that the baseline used here assumes a higher natural rate of unemployment than in the June Tealbook.
14

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the FRB/US model assuming agents form model consistent expectations, with complete policy
credibility. These are strong assumptions that might overstate the ability of the Committee to
achieve its objectives; that said, the virtue of this framework is that by construction our results do
not depend on any explicit or implicit assumption of ignorance or myopia.17 As a check against
false confidence, we will discuss (but not show) simulation results where policy is governed by
the inertial Taylor rule (with thresholds). Simple rules, like the inertial Taylor rule, are often
advocated for their robustness properties, trading off the precision of optimal control, which
exploits complete knowledge of the model and the baseline, for the breadth and ubiquity of the
arguments that enter simple rules.
Figure 3 shows the optimal control solution for this scenario, along with the corresponding
optimal path for the extended April Tealbook, for comparison.18 Focusing first on results using
the conventional unemployment-based optimal policy, the thick solid (blue) line in the bottomright panel shows that the federal funds rate lifts off from the effective lower bound (ELB) in the
first quarter of 2015, two quarters earlier than in the baseline optimal control results (the thin
solid line). On average, growth in real GDP is stronger than in the baseline, and the
unemployment rate declines more rapidly, despite a more rapid climb in the workforce. And yet,
as the bottom-left panel shows, this more rapid expansion produces inflation that is tangibly
lower, with the result that real interest rates are little different than in the baseline. This
constellation of results arises because the higher participation rate trend, even though it has no
implications, initially, for the unemployment gap, implies a higher level of potential output.
Higher potential, in turn, implies higher target spending levels and thus a greater impetus to
growth going forward; by the same token, the larger output gap puts more downward pressure on
inflation.
The simulation using the employment-based optimal policy is shown by the thick dashed (green)
lines. As the bottom-right panel shows, in this case, the liftoff of the funds rate from the ELB is
prescribed for the fourth quarter of 2016—seven quarters later than under the unemploymentbased optimal policy. Inflation differs little in the early going from the unemployment-based
policy, so that real interest rates are substantially lower. Growth in real GDP soars for a time,
and the unemployment rate, shown in the top-right panel, falls much faster than in either of the
other two scenarios, overshooting the natural rate by significantly more. The unemployment rate
bottoms out at 4½ percent at the end of 2016 after which it approaches the natural rate from
17

The exception to this is the assumption of full credibility the efficacy of which depends on either an established
reputation or a “commitment technology” that binds future generations of the Committee to the promises of the
present one. An exploration of this assumption is, however, beyond the scope of this memo.
18
Because the April Tealbook baseline was constructed, in large part, with the standard model in mind, the standard
model is also used for optimization for the baseline scenario shown here; in particular, optimization is carried out in
the standard way such that the real variable that appears as the objective of optimization is the (discounted)
unemployment rate gap. The optimal policy for the baseline shown in figure 3 and again in figure 4 differs slightly
from what was shown in Part B of the April Tealbook because of small differences in the variables for which
expectations are taken to be model consistent.

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below.19 These unemployment dynamics are intended to propel a more rapid recovery in the
participation rate than would otherwise take place.20 The employment-based optimal policy thus
leads to monetary policy that is “lower for longer,” arguably reaping noteworthy gains in
employment and inflation.21,22
Our second scenario considers a case at the opposite end of the spectrum, in which goods market
slack is notably less than what we have in the baseline. As noted above, the most likely scenario
capturing this possibility entails even larger declines in structural productivity in recent history
than we have built into the baseline, and consequently smaller shortfalls in resource utilization,
all else equal. Specifically, this scenario assumes a (further) reduction in the growth rate of trend
productivity over the period from 2009 to 2012, which leaves the level of structural productivity
at the beginning of this year 1 percent lower than in the baseline. Private agents are assumed to
understand that the reduction in the level of productivity will persist indefinitely and also that the
growth rate going forward is unchanged relative to baseline. The shock introduces a dissonance
between the output and unemployment rate gaps, but does not distort the measurement of labor
market utilization per se. Accordingly, we narrow our focus to the unemployment-based optimal
policy and the standard FRB/US labor market equations that impose Okun’s law.
The results are summarized in figure 4, where the thick solid (blue) lines show the optimal policy
under the alternative scenario, while thin solid lines represent the optimal policy for the extended
Tealbook for April. The scenario is constructed such that the output gap starts out 1 percentage
point narrower than in the baseline. This narrower output gap implies that the unemployment
gap will close earlier than in the baseline. Accordingly, optimal policy is initially tighter, calling
for departure from the ELB one year earlier, in the third quarter of 2014. The higher initial
readings for the nominal funds rate do not last for long, however, as reduced inflation pressures,
anticipated in 2017 and beyond, cause the pace of policy tightening beyond 2016 to slow. This
path for the funds rate results in a more rapid decline in the unemployment rate than in the
baseline, as shown in the top-right panel.23
19

Erceg and Levin (2013) obtain a broadly similar result, although the overshoot of unemployment they produce
appears to be smaller but longer lasting than what we show here.
20
In the baseline, the participation rate gap closes by the end of 2016. By contrast, the participation rate gap in the
unemployment-based optimization scenario does not close until 2021, while under the employment-based optimal
policy the gap closes early in 2018, not a great deal later than in the baseline despite starting from an initial gap that
is nearly 1 percentage point wider.
21
We say the gains are “arguable” because whether the employment-based optimal policy produces actual gains
relative to the unemployment-based optimal policy is a judgment call on the appropriate loss function. The FRB/US
model does not have the structure to make a definitive case on this question.
22
The inertial Taylor rule proves to be too narrow in its consideration of resource utilization when the
unemployment and output gaps do not move as closely together as they do in the baseline. In particular, the inertial
Taylor rule with thresholds (not shown) renders significantly higher unemployment and lower inflation than either
of the trend participation rate scenarios shown in figure 3.
23
When governed by the inertial Taylor rule, the federal funds rate remains at the ELB until 2015:Q2—longer than
is optimal—but climbs faster thereafter. Inflation is lower than optimal, resulting in higher real rates than otherwise,

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This scenario, like the previous one, shows how certain shocks can induce contrary movements
in goods market measures—GDP growth in this case, which is worse than in the baseline—and
labor market measures like the unemployment rate, which is better than in the baseline. It
follows that the extent to which a single summary statistic of resource utilization can adequately
capture that state of demand deficiency will depend on the origins of the shocks that produce
those economic conditions in the first place. The examples considered in this section focused on
supply-side shocks. However, as our discussion of the baseline interpretation of the recent
history makes clear, demand-side shocks can induce an Okun’s law error as well. Since the realtime identification of shocks is, at best, difficult, a broad-based approach to assessing resource
utilization and designing monetary policy would appear to be in order.

References
Aaronson, Daniel and Scott Brave, “Estimating the trend in employment growth”, Chicago Fed
Letter No. 312, Federal Reserve Bank of Chicago, July 2013.
Barnichon, Regis and Andrew Figura. “What Drives Matching Efficiency? A Tale of
Composition and Dispersion.” Federal Reserve Board Finance and Economics Discussion Series
Paper no. 2011-10, 2011.
Clark, Peter K., “Okun’s Law and Potential GNP, manuscript, 1983.
Erceg, Christopher J, and Andrew T. Levin, “Labor Force Participation and Monetary Policy in
the Wake of the Great Recession”, manuscript, April 2013.
Furceri, Davide and Anabelle Mourougane, “The effect of financial crises on potential output:
New empirical evidence from OECD countries”, Journal of Macroeconomics 34(3), September
2012, pp.822-832.
Lazear, Edward P. and James R. Spletzer, “The United States Labor Market: Status Quo or New
Normal?” U.S. Census Bureau, Center for Economic Studies Discussion Paper #12-28,
September 2012.
Levin, Andrew, Volker Wieland and John C. Williams, “The Performance of Forecast-Based
Monetary Policy Rules under Model Uncertainty”, American Economic Review 93(3), June
2003, pp. 622-645.
Şahin, Ayşegül, Joseph Song, Giorgio Topa, and Gianluca Violante. “Measuring Mismatch in
the U.S. Labor Market.” NBER Working Paper no. 18265, 2012.
and consequently, the unemployment rate does not overshoot the natural rate. Similarly, the output gap does not
exceed zero during this decade.

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Figure 1

Okun’s Law
Unemployment Rate

Unemployment Rate Gap
Percent

11

September Tealbook
April Tealbook
Current projection

10

11

10

9

4

4

3

3

2

2

1

1

0

0

8

7

7

6

6

5

5

2004

2006

2008

2010

2012

4

-1

Okun’s Law
Percent

Unemployment rate
April 2013 Simulation starting 1990:Q3

11.0

11.5

10.5

10.0

10.0

9.5

9.5

9.0

9.0

8.5

8.5

8.0

8.0

7.5

7.5

7.0

7.0

6.5

6.5

6.0

6.0

5.5

5.5

5.0

5.0

4.5

4.5
2006

2006

2008

2010

2012

2008

2010

2012

2014

Percent

6.50

-1

4.0

6.50

Current Estimate
April Tealbook

11.0

10.5

2004

2004

Natural Rate of Unemployment

11.5

4.0

5

September Tealbook
April Tealbook
Current projection

9

8

4

Percent

5

6.25

6.25

6.00

6.00

5.75

5.75

5.50

5.50

5.25

5.25

5.00

5.00

4.75

Page 13 of 16

2004

2006

2008

2010

2012

2014

4.75

Authorized for public release by the FOMC Secretariat on 01/11/2019
Figure 2

Indicators of Labor Market Functioning and Discouragement

Industry/Occupation Mismatch
(Contribution to the Unemployment Rate)

Permanent Job Losers

Percentage points

2.4

2.4

Occupation
Industry

2.1

2.1

1.8

1.8

1.5

1.5
Apr.

1.2

1.2

0.9

0.9

0.6

0.6
Mar.

0.3
0.0

2007

2008

2009

2010

2011

2012

0.3
0.0

2013

Percent of unemployment

60
55

55

50

50

45

45

40

40

35

35

30

2007

Barnichon-Figura Estimate of Matching Efficiency
(Contribution to the Unemployment Rate)
Percentage points

2.0

60

2008

2009

2010

2011

2012

2013

30

Social Security Disability Recipients
Percent of population 16 years and over

2.0

4.0

1.5

3.5

3.5

1.0

1.0

3.0

3.0

0.5

0.5

2.5

2.5

0.0

0.0

2.0

2.0

-0.5

-0.5

1.5

1.5

-1.0

1.0
1975

1.5

4.0

Q2

-1.0

2007

2008

2009

2010

2011

2012

2013

1980

1985

1990

1995

2000

2005

2010

1.0

Note: Hollow dot is the average for April and May.

Unemployment Rate

UN Transition Rate, by Unemployment Duration*
Percent

32

1-26 weeks
27-52 weeks
53+ weeks

30
28
26
24

Apr.

22

32
30

11
10

26

9

9

24

8

8

22

7

7

6

6

5

5
4

18

4

16

16

3

2010

2011

2012

*Six-month moving averages of s.a. monthly data.

2013

12

10

28

18
2009

13

11

20

2008

Unemployment Rate (3-month moving average)
U-5* (3-month moving average)

12

20

2007

Percentage points

13

1995
2000
2005
2010
* U-5 measures total unemployed plus all marginally
attached to the labor force, as a percent of the labor force
plus persons marginally attached

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3

Authorized for public release by the FOMC Secretariat on 01/11/2019
Figure 3
___________________________________________________________________________________
Optimal
Control Simulations for Baseline and Alternative Trend Participation Scenario
(Optimization based on unemployment rate or employment rate, as indicated)

Real GDP

Civilian Unemployment Rate

Q4/Q4 Growth
5

9

Baseline (unemployment)
LFPR (unemployment)
LFPR (employment)

8

4
7
3
6

Natural Rate

2

2012

2014

2016

2018

Headline PCE Prices

2020

2012

2014

5

2016

2018

2020

Federal Funds Rate

Q4/Q4 Growth
2.6

5

2.4
4
2.2

Target
2.0

3

1.8
2

1.6
1.4

1
1.2
1.0
2012

2014

2016

2018

2020

0
2012

Page 15 of 16

2014

2016

2018

2020

Authorized for public release by the FOMC Secretariat on 01/11/2019
Figure 4
__________________________________________________________________________________________________
Optimal
Control Simulations for Baseline and for a Shock Reducing Productivity Beginning in History
(Optimization based on unemployment rate)

Real GDP

Civilian Unemployment Rate

Q4/Q4 Growth
4.0

9

Baseline
Productivity
3.5

8

3.0
7
2.5
6
2.0

Natural Rate
2012

2014

2016

2018

Headline PCE Prices

2020

2012

2014

5
2016

2018

2020

Federal Funds Rate

Q4/Q4 Growth
2.6

5

2.4
4

2.2

Target
2.0

3

1.8
2

1.6
1.4

1
1.2
1.0
2012

2014

2016

2018

2020

0
2012

Page 16 of 16

2014

2016

2018

2020