FRBSF Economic Letter
2006-32; November 24, 2006
Is a Recession Imminent?
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The sharp slowdown in housing and the inverted yield curve
have led to concerns that the odds of a recession have risen.
For instance, Dow Jones Newswire reported on November 2 that
one model based on the yield curve put the probability of a recession
over the next four quarters at more than 50%. This Letter presents
and discusses various estimates of the probability of recession.
Our review of the evidence suggests two conclusions: First, recessions
appear difficult to predict; second, while the probability of
a recession over the next year may now be somewhat elevated,
it does not appear to be nearly as high as the yield curve suggests.
Indicator models for predicting recessions
One way to predict the likelihood of a recession would involve
simulating a large structural model of the U.S. economy.
But economists disagree about the structure of the economy, so
several have suggested using indicator models instead.
The
indicator
models constructed by James Stock and Mark Watson (SW) are
among the best known. Their work in this area preceded
the 1990-1991
recession and continued through December 2003 (see, for instance,
SW 1989). Their recession index (which estimates the probability
of recession six months hence) and variations thereof are
themselves a function of two indexes for Leading and Coincident
Indicators.
Unfortunately, their real-time performance has not been wholly
satisfactory. The first index failed to predict the 1990-1991
recession, and a variation failed to predict the 2001 recession.
Of course, the SW indicators are not the only ones that failed.
SW (2003) discusses this widespread failure and argues
that it is hard to predict recessions because each is caused
by
a unique
set of factors. For instance, income and consumption data
did not provide much evidence portending a recession in
2001, but
industrial production data did, because the recession was
associated with IT manufacturing. By contrast, in the 1990-1991
recession,
consumption did slow. Thus, "without knowing these shocks
in advance, it is unclear how a forecaster would have decided
in 1999 which of the many promising leading indicators would
perform well over the next few years and which would not" (p.
88).
It should be noted that the SW approach definitely has
had successes; the version used by the Chicago Fed, for
instance,
did a reasonably
good job in real time of signaling a (coincident) slowdown
in activity early in the 2001 recession. What does the
index say
now? As of October 25, the three-month average of the
Chicago Fed's National Activity Index (2006) stood at -0.25.
A
value below zero implies that growth is below trend;
values below
-0.7 are associated with an "…increasing likelihood that
a recession has begun" (p. 2).
Information from the yield curve
 The yield curve is perhaps the best known of all the
indicator models used to predict recessions. We begin
with a model
developed by Wright (2006) that uses information on
the term spread and
the funds rate. As Figure 1 shows, this model has done
a reasonably good job of predicting recessions. Based
on data
for November
8, the model estimates a 47% probability of recession
over the next four quarters. As a reference point,
note that
over 1964:Q1-2005:Q2,
27% of the four-quarter periods after any given quarter
contained a recession; however, over 1984:Q1-2005:Q2,
a period when
output growth was noticeably less volatile than before,
this frequency
falls to only 15%.
There is reason to be skeptical about the current high
estimate of the probability of recession, because the
unusually low
rates at the long end of the yield curve are not well
understood; indeed,
former Fed Chairman Greenspan famously pointed out
that this behavior is a conundrum (2005). Wright attempts
to deal with
these problems by estimating several alternative versions,
but the results are virtually indistinguishable from
the base model.
Hence, the statistical evidence does not clearly indicate
how to incorporate the low long-term yields into the
probability estimates.
 Concern about the behavior of long-term yields could
be allayed by adding other variables to the forecasting
equation.
For
example, Dueker (2005) included real GDP growth and
CPI inflation (in
addition to the spread and the funds rate) and estimated
a vector autoregression to improve the modeling of
the dynamics of the
process. Unlike the SW models, real-time estimates
from the Dueker model made at the end of 2000 placed
the probability
of recession
in mid- to late 2001 above 50%. Figure 2 shows the
business conditions index that underlies this probability;
this
version
is updated
and based on currently available data. When this index
falls below zero (as it did in 2000), the recession
probability rises
above 50%. Although the figure indicates that business
conditions
have deteriorated recently, they remain comparable
to those prevailing around 1995-1996, a period when
the
economy
had slowed but did
not enter a recession. While the model predicts some
further deterioration in business conditions over the
next year,
it does not see much more than a 10% chance of a recessionary
quarter
over this period.
Survey evidence
Surveys, such as the well-known Blue Chip survey and
the Survey of Professional Forecasters, represent
subjective probability
assessments and could incorporate judgmental adjustments
to model forecasts. In November, the Blue Chip survey
asked
a
special
question on the odds of a recession in the next 12
months. The consensus was 24.8%; the average of the
highest ten
responses was 36.5%, and the average of the lowest
ten was 14.8%. Earlier,
the consensus was 25.1% in September and 26.9% in
August.
Although these numbers are well below those from
the yield curve model, they also are not that different
from those
recorded before
the beginning of the last recession in March 2001;
for example, in every month from May to September
2000
and
again in November
2000, the consensus probability of recession varied
from a low of 16% to a high of 23%. Moreover, respondents
found it
hard
to tell if the economy was in a recession in real
time; for instance, when asked whether the economy
had entered
a recession
in June
2001, 93% said no.
The Survey of Professional Forecasters regularly
asks respondents to provide separate estimates of
the probability
that real
GDP growth will be negative in the current quarter
and the subsequent
four quarters. Figure 3 displays data for three of
these five quarters; for example, regarding the forecast
for
2006:Q3, the line labeled "current quarter" shows the mean probability
of negative real GDP growth as estimated in 2006:Q3, and the
line labeled "2 quarters earlier" shows
this probability as estimated in 2006:Q1.
Recently, the probabilities have crept up, with the
third quarter survey results indicating close to
a 10% chance
of recession
in 2006:Q4 and a 19% chance in 2007:Q2. Still, these
levels are around the middle of the range that prevailed
during
the boom
years of the late 1990s (see the line labeled "2 quarters
earlier," for instance). Furthermore, probabilities
from this survey did not give much warning of the
last recession,
as even the current-quarter estimate did not rise
substantially until after the recession had begun.
An assessment
Because the single-equation model based on the yield
curve and the funds rate appears to have performed
better historically
than other models, it makes sense to take its
pessimistic forecast seriously. Yet there also are mitigating
factors to consider.
For example, the ability of the yield curve to
forecast recessions is often attributed to the fact that
the
long-term rate reflects
market expectations about future developments
in
the economy. But in that case, one would expect
professional forecasters
to
have this information as well, leading to survey
probabilities
similar to those from the yield curve. At a minimum,
forecasters should be incorporating information
from the yield curve
into their forecasts.
A more concrete reason to be cautious about this
forecast lies in the recent behavior of long-term
rates, which
argues for
reducing the weight one places upon the term
spread and relying upon other
variables when making forecasts. The Dueker
model provides one way of doing so, and its forecast
(based on data
through August)
is noticeably more optimistic. However, deciding
what to include brings us back to the problem
discussed by Stock
and Watson:
The forecast we get depends on the indicators
we add
to the term spread. In particular, adding data
on the housing
sector
is sure
to lead to more pessimistic forecasts.
That said, our review of the available surveys,
indicators, and model forecasts leads to
estimates of the probability
of recession
that are all lower than the one based on
the term spread and the yield curve. Furthermore,
financial
markets
exhibit little
evidence of distress: the Dow has hit record
highs recently, and various risk spreads
(such as the
rate on corporate
bonds relative to Treasuries) remain at low
levels. Taken together
with our inability to explain the unusually
low level of long-term rates, this suggests
to us
that while
the probability
of recession
might have gone up somewhat in recent months,
it is not yet at worrisome levels.
Finally, not only are recessions hard to
predict, it is even hard to tell that the
economy is
in a recession
once
it has
begun. This is especially true in the low
volatility regime that has
prevailed since the mid-1980s. Here, the
evidence suggests that it may be useful
to supplement
data from the surveys
with data
from indicator models that attempt to measure
the current state of the economy.
John Fernald
Vice President
Bharat Trehan
Research Advisor
References
[URLs accessed November 2006.]
Dueker, Michael. 2005. "Dynamic Forecasts of Qualitative
Variables: A QUAL VAR Model of U.S. Recessions." Journal
of Business and Economic Statistics 23(1), pp. 96-104.
FRB Chicago. 2006. "Chicago Fed National Activity Index."
Greenspan, Alan. 2005. Federal
Reserve Board's Semiannual Monetary Policy Report to the Congress
before the Committee on
Banking,
Housing, and Urban Affairs, U.S. Senate, February 16.
Stock, James, and Mark Watson. 1989. "New Indexes of Coincident
and Leading Economic Indicators." NBER Macroeconomics
Annual 1989.
Stock, James, and Mark Watson. 2003. "How Did Leading
Indicator Forecasts Perform During the 2001 Recession?" FRB
Richmond Economic Quarterly (Summer).
Wright,
Jonathan. 2006. "The Yield Curve and Predicting
Recessions." Federal Reserve Board Finance and
Economics Discussion Series 2006-7 (February).
Opinions expressed in this newsletter
do not necessarily reflect the views of the management
of the Federal Reserve Bank of San Francisco or of the
Board of Governors of the Federal Reserve System. Comments?
Questions? Contact
us via e-mail or write us at:
Research Department
Federal Reserve Bank of San Francisco
P.O. Box 7702
San Francisco, CA 94120
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