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Vol. 2, No. 9
SEPTEMBER 2007
EconomicLetter
Insights from the
F e d e r a l R e s e r v e B a n k of D a l l a s
The ‘Great Moderation’ in Output
and Employment Volatility: An Update
by Evan F. Koenig and Nicole Ball
The reduced
Volatility can wreak havoc on economies. Sudden, sharp ups and downs
aggregate volatility
in business activity can make it difficult for consumers to plan their spending,
that began in 1984
workers to feel secure in their jobs and companies to determine their future in-
has continued into
vestments. Because of their impact on expectations and business and consumer
the new millenium.
confidence, swings in the economy can become self-reinforcing. Volatility can
also spill over into real and financial asset markets, where severe price movements can produce seemingly arbitrary redistributions of wealth.
It’s good news, then, that the U.S. economy has become much more
stable. On average, the five recessions from 1959 to 1983 were 47 months apart,
lingered 12 months and were associated with a 2.17 percent peak-to-trough decline in real gross domestic product. By contrast, the 1990 downturn came after
92 months of expansion, lasted eight
months and involved a 1.26 percent
decline in GDP. The 2001 slump ended
a record 120 months of uninterrupted
growth, lasted eight months and entailed a GDP decline of only 0.35
percent. More generally, quarterly
growth in both real GDP and jobs
became markedly less volatile after
1983.1
Explanations for this “Great
Moderation,” as it’s called, include
structural changes in the economy,
improved monetary policy and simple
good luck.
Potentially important structural
changes include the elimination of
ceilings on deposit interest rates,
broader access to credit markets
through financial innovations like
home equity loans, tighter inventory
controls facilitated by technology, and
the globalization of output and labor
markets.
By improved monetary policy,
analysts typically have in mind central bank actions that respond more
quickly and forcefully to emerging
inflation pressures, so that mediumto long-term price expectations remain
contained.
As for good luck, analysts cite
the reduced frequency of economic
shocks comparable to the 1973 Arab
oil embargo and 1979 oil price spike.2
We’ve accumulated eight years of
additional data since completion of the
early work on the Great Moderation,
and the U.S. economy has experienced another recession and recovery.
The new data allow us to examine
whether the moderation has continued
and detect changes in different sectors’
contributions to volatility.
Our results are interesting because of the light they shed on the
debate over the causes of the Great
Moderation, but they’re also useful
in their own right. Breaking volatility down by sector, for example, can
pinpoint which industries and expenditure categories are currently the
most important sources of fluctuations
in GDP and employment. It’s in these
areas that monitoring efforts ought to
be focused.
What we’ve found in studying the
new data is that the reduced aggregate
volatility that began in 1984 has continued into the new millennium. The
economy’s volatility hasn’t, however,
dropped much further.
In the case of GDP growth, most
of the initial volatility decline can be
attributed to greater stability in investment and consumer durables expenditures. Volatility from consumer spending has fallen further in recent years,
but this decline has been completely
offset by increased volatility from
international trade.
In the case of jobs growth, most
of the 1984 volatility decline can
be attributed to manufacturing. The
sector’s volatility contribution has
held steady since then, even though
its employment share has continued
to shrink. Meanwhile, jobs growth
volatility originating in professional
and business services has increased
sharply.
Sector Volatility
How much any sector contributes
to the U.S. economy’s ups and downs
depends on three factors: the sector’s
own volatility, its share of business
activity, and its tendency to move with
or against the overall economy. This
cataloging is analogous to the familiar
notion that any given stock contributes more to a portfolio’s riskiness the
more volatile its returns, the larger its
portfolio share, and the greater the
correlation between its return and
returns on the portfolio’s other stocks.3
We traced various sectors’ contributions to the volatility of quarterly
growth in GDP and jobs over three
periods: the 25 years starting in 1959
and running through 1983, the 12
years from 1984 through 1995 and the
nearly 12 years from 1996 through the
second quarter of 2007. Each of these
intervals includes at least one economic expansion, recession and recovery.
The most recent period is interesting because it was marked by rapid
EconomicLetter
Federal Reserve Bank of Dall as
growth in international trade and
financial flows and the spread of new,
more flexible labor market arrangements. These are the kinds of structural changes that might be expected
to affect the stability of economic
growth. This period was also marked
by large swings in the real price of
oil.4 Insofar as oil price shocks were
responsible for some of the economy’s
pre-1984 instability, we might expect a
return of some of that volatility.
GDP Growth Volatility
We can measure GDP growth’s
volatility by looking at the range within which growth has fallen 95 percent
of the time. Between 1959 and 1983,
for example, annualized GDP growth
averaged 3.6 percent and strayed outside a –5.3 to 12.5 percent range only
5 percent of the time. The margin of
error for GDP growth over this period
was plus or minus 8.9 percentage
points (Chart 1).
Between 1984 and 1995, growth
was 3.2 percent, plus or minus 4.3
points — a margin of error less than
half of what it had been. Finally, from
1996 to 2007, GDP growth averaged
3.1 percent, plus or minus 4.1 points.
By convention, analysts measure
a series’ volatility by its standard deviation, which is one-half the margin of
error. In percentage points, the standard deviations for GDP growth are
4.47 for 1959 – 83, 2.14 for 1984 –95
and 2.04 for 1996 – 2007.
The big decline in GDP growth
volatility occurred during the mid1980s. Since then, it has stayed relatively constant. Sustaining this low volatility over the past 12 years is impressive, however, given the large swings
in oil prices and business investment
during that period. This suggests the
economy’s increased stability is due to
more than good luck.
So, if not purely good luck, then
what? A sector-by-sector breakdown
reveals expenditure categories whose
volatility contributions fell most sharply from 1959 – 83 to 1984 – 95 (Table
1). Inventory investment’s contribution
Chart 1
Sustaining low volatility
GDP Growth Volatility Dropped Off Sharply
in the Mid-1980s
over the past 12 years
is impressive, given
Real GDP growth (percent)
the large swings
20
in oil prices and
15
Volatility bands
business investment
10
during that period.
5
0
Average
–5
–10
’60
’63
’66
’69
’72
’75
’78
’81
’84
’87
’90
’93
’96
’99
’02
’05 ’07
NOTE: Shaded areas denote recessions.
SOURCES: Bureau of Economic Analysis; National Bureau of Economic Research.
declined from 1.82 to 0.69 percentage
points, consumer durables’ from 0.83
to 0.44 points, residential investment’s
from 0.57 to 0.25 points and nonresidential fixed investment’s from 0.71 to
0.42 points.
These results suggest — but don’t
prove — that tighter inventory controls,
consumers’ improved access to credit
and financial deregulation played
important roles in the economy’s
greater stability.
Although the decline in overall
GDP growth volatility has been small
since 1995, some shifts in sector contributions are significant. For example,
consumption’s contribution over the
most recent 12 years is half what it
was over the previous 12. Most of this
decline can be attributed to consumer
durables, but nondurables also show a
drop.
The recent reduction in consumption’s volatility contribution is, however, offset by net exports’ increased
contribution. In 1959 – 83 and 1984 – 95,
the trade sector subtracted about 0.3
percentage points from GDP volatility.
Table 1
Contributions to Volatility in GDP Growth
(Percentage points)
1959 – 83
1984 – 95
1996 – 2007
1.42
.83
.39
.20
3.10
.71
.57
1.82
.22
–.26
4.47
.82
.44
.24
.14
1.36
.42
.25
.69
.24
–.28
2.14
.41
.12
.18
.11
1.34
.51
.17
.66
.17
.12
2.04
Consumption
Durables
Nondurables
Services
Investment
Nonresidential fixed
Residential
Inventory
Government
Net exports
Total
NOTES: The total is the standard deviation of GDP growth. 2007 data are through the second quarter.
Numbers may not add up due to rounding.
SOURCE: Bureau of Economic Analysis.
Federal Reserve Bank of Dall as
EconomicLetter
Chart 2
Investment, Consumer Spending on Durables Key
to Post-1983 GDP Stability
For each period, the black horizontal line represents the contribution of investment (A) or consumer spending on durables (B) to GDP growth volatility. To
a close approximation, the line’s height is the product of the heights of the
three bars.
A. Investment Expenditures
Fraction of 1959 – 83 value
1.4
1.2
Share of GDP
Sector volatility (percentage points)
Correlation with GDP growth
GDP growth volatility contribution (percentage points)
3.10
1
.8
.6
1.36
1.34
.4
1959–1983
1984–1995
1996–2007
.2
0
.162
× 22.6 × .85 ≈ 3.10
.151 × 14.2
× .64 ≈ 1.36
.164 × 11.4 × .73 ≈ 1.34
B. Durable Goods Spending
Fraction of 1959 – 83 value
1.4
1.2
Share of GDP
Sector volatility (percentage points)
Correlation with GDP growth
GDP growth volatility contribution (percentage points)
.83
1
.8
.6
.44
.4
.2
0
1959–1983
.084
1984–1995
× 15.0 × .66 ≈ .83
1996–2007
.083 × 12.1 × .44 ≈
.44
.085
× 9.4
× .15 ≈ .12
SOURCE: Bureau of Economic Analysis.
EconomicLetter
.12
Federal Reserve Bank of Dall as
This reflects net exports’ historical tendency to act as an automatic stabilizer,
rising when the U.S. economy is weak
and falling when it’s strong. Since
1995, though, the correlation between
quarterly changes in net exports and
GDP has turned slightly positive, and
the category has added 0.1 point to
aggregate volatility.
Let’s take a closer look at investment and consumer durables, which
are primarily responsible for output’s
increased post-1983 stability. Changes
in these sectors’ relative size didn’t
contribute much to the decline in
overall GDP volatility. Most of the
impact came from reductions in their
volatility and their correlation with the
overall economy.
For investment, the standard deviation of sector growth fell from 22.6
to 14.2 to 11.4 percentage points over
the sample periods, and the correlation between sector and GDP growth
declined from 0.85 to 0.64 before
bouncing back up to 0.73 (Chart 2A).
Meanwhile, investment’s share
of GDP held steady at about 0.16 (16
percent). The net result was a sharp
decline in the sector’s contribution to
GDP growth volatility from 1959 – 83
to 1984 – 95 and very little change
from 1984 – 95 to 1996 –2007.
For consumer durables, the standard deviation of sector growth fell
from 15.0 to 12.1 to 9.4 percentage
points, and the correlation between
sector and GDP growth dropped from
0.66 to 0.44 to 0.15.
At the same time, the sector
share held steady at about 0.084 (8.4
percent). Consequently, consumer
durables’ contribution to the volatility
of GDP growth fell substantially from
sample period to sample period, up to
and including 1996 – 2007 (Chart 2B).
Before 1984, the key categories
to watch in tracking GDP fluctuations
were inventory investment, consumer
durables spending and nonresidential
fixed investment. Inventory and nonresidential fixed investment remain
important sources of volatility today,
but consumer durables ranks as an
also-ran. Now tied for third in importance are consumer expenditures on
nondurable goods, residential investment and government expenditures.5
Jobs Growth Volatility
When it comes to overall volatility, jobs growth exhibits a decline
that’s similar to the one we saw for
GDP growth but smaller in magnitude (Chart 3). The margin of error
needed to encompass 95 percent of
jobs growth’s variation narrows from
5.1 percentage points for 1959–83, to
3 points for 1984 – 95, to 2.7 points for
1996 – 2007. The standard deviation of
jobs growth drops from 2.53 to 1.52 to
1.33 points in those periods.
Average annual jobs growth has
declined, too, going from 2.3 percent
in 1959 – 83 to 2.1 percent in 1984 – 95
and 1.4 percent in 1996–2007.
Manufacturing was mainly responsible for the sharp fall in jobs growth
volatility after 1983. Its contribution
dropped from 1.25 percentage points
in 1959 – 83 to 0.32 points in 1984 – 95
and 0.34 in 1996 – 2007 (Table 2).
Construction has caused less volatility
in the past 12 years, but it’s doubtful
this decline will survive the current
slowdown in residential building.
Overall, private services’ contribution to the economy’s volatility hasn’t
changed much. Within services, however, we see a marked tendency for
the volatility from the professional and
business services sector to rise over
the three periods — from 0.13 percentage points to 0.19 points to 0.37
points. The contribution from trade,
transportation and utilities, on the
other hand, has declined.
What’s going on in manufacturing and professional and business
services, the two sectors with the most
notable change in their contributions
to overall volatility?
Part of the story in manufacturing
is foreign competition and productivityenhancing technologies, which have
combined to reduce the sector’s share
of total employment from 25 percent
to 17 percent to 12 percent (Chart 4).
Chart 3
Jobs Growth Volatility Declined Markedly
in the Mid-1980s
Nonfarm jobs growth (percent)
10
8
Volatility bands
6
4
2
0
Average
–2
–4
–6
–8
’60
’63
’66
’69
’72
’75
’78
’81
’84
’87
’90
’93
’96
’99
’02
’05 ’07
NOTE: Shaded areas denote recessions.
SOURCES: Bureau of Labor Statistics; National Bureau of Economic Research.
Table 2
Contributions to Volatility in Jobs Growth
(Percentage points)
Goods
Resources
Construction
Manufacturing
Private services
Trade, transportation and utilities
Information
Financial
Professional and business
Education and health
Leisure
Other
Government
Total
1959 – 83
1984 – 95
1.54
.04
.25
1.25
.88
.40
.10
.04
.13
.07
.12
.03
.11
2.53
.56
.01
.23
.32
.89
.40
.04
.06
.19
.01
.13
.06
.07
1.52
1996 – 2007
NOTES: The total is the standard deviation of jobs growth. 2007 data are through the second quarter.
SOURCE: Bureau of Labor Statistics.
Federal Reserve Bank of Dall as
EconomicLetter
.46
.00
.12
.34
.86
.29
.10
.03
.37
–.03
.08
.01
.01
1.33
Chart 4
Manufacturing Much Less Important As Source
of Jobs Growth Volatility
For each period, the black horizontal line represents manufacturing’s contribution to jobs growth volatility. To a close approximation, the line’s height is the
product of the heights of the three bars.
Fraction of 1959 – 83 value
1.5
1.25
Share of nonfarm jobs
Sector volatility (percentage points)
Correlation with nonfarm jobs growth
Jobs growth volatility contribution (percentage points)
1.25
1
.75
.5
.32
.34
.25
1959–1983
1984–1995
1996–2007
0
.25
× 5.4
× .95 ≈ 1.25
.17
× 2.2
× .86 ≈ .32
.12
× 3.0
× .91 ≈ .34
SOURCE: Bureau of Labor Statistics.
The standard deviation of manufacturing’s volatility growth rate is generally lower now, too. It fell sharply
from 5.4 percentage points in 1959 – 83
to 2.2 points in 1984 – 95, before rising
slightly — to 3 points — over the past
12 years. This lower jobs growth volatility probably reflects the more stable
growth in investment and consumer
goods expenditures we’ve already discussed.
Finally, it’s interesting that the
correlation between total and manufacturing jobs growth has changed
so little over the years, fluctuating
from 0.95 to 0.86 to 0.91. Perhaps
more flexible labor market practices
have offset the weaker links between
investment expenditures and GDP and
between consumer goods expenditures and GDP.
Manufacturing has traditionally
been a source of economic instability,
but volatility from a segment of the
usually stable services sector may be
something of a surprise. Professional
and business services’ increasing contribution to overall volatility has been
driven mainly by two factors: the sector’s growing relative size — its share
of total jobs has gone from 8 to 10 to
over 12 percent — and rising internal
volatility — the standard deviation of
its growth is up from 1.9 to 2.3 to
3.2 percentage points (Chart 5). The
sector’s correlation with aggregate jobs
growth has held fairly steady.
The expansion of professional
and business services has been well
documented. This sector includes
business managers and knowledgebased employees like lawyers, accountants and computer-system designers,
whose jobs are in increasing demand
and relatively difficult to send overseas. The sector’s rising volatility
reflects the high-tech boom and bust
of the late 1990s and early 2000s. The
EconomicLetter
2001 downturn was widely considered
a white-collar recession. Unfortunately,
the detailed subsector data we need
to be able to say more are simply not
available for before 1990.
Factoring in all these changes,
which were the most important sources of jobs growth variation before the
Great Moderation and which are the
most important now? Between 1959
and 1983, manufacturing; trade, transportation and utilities; and construction — in that order — were the main
drivers of aggregate jobs growth fluctuations. Today, the big three are professional and business services; manufacturing; and trade, transportation
and utilities. Given that service-sector
developments increasingly drive the
U.S. economy today, it’s no surprise
that two of the three most important
sectors to monitor fall into the services
category.6
Federal Reserve Bank of Dall as
Summary and Conclusions
GDP and jobs growth became
more stable about 24 years ago. Most
of the decline in output growth volatility is attributable to smaller swings
in investment and consumer durables
purchases, swings that are also less
synchronized with fluctuations in the
overall economy. The reduction in
jobs growth volatility is due almost
entirely to a shrunken and less variable manufacturing sector.
Changes in GDP and jobs growth
volatility since 1984 have been relatively modest. Beneath the surface,
however, sector contributions have
shifted. Consumer spending—especially on durable goods—accounts for an
ever-smaller fraction of short-run variability in GDP growth. On the other
hand, net exports have become less of
a stabilizing influence.
Two decades ago, keeping tabs
on shifts in investment spending and
consumer durables purchases was crucial for understanding swings in GDP
growth. Tracking shifts in investment
spending remains critical, but changes
in household spending on nondurable
goods are now more important than
Quiros, American Economic Review, vol. 90,
December 2000, pp. 1464 – 76; and “The Long
Chart 5
and Large Decline in U.S. Output Volatility,” by
Professional and Business Services More Important
Source of Jobs Growth Volatility
Olivier Blanchard and John Simon, Brookings
Papers on Economic Activity, no. 1, 2001, pp.
135 – 64. (Blanchard and Simon see the 1984
volatility reduction as part of a longer-term trend.)
For each period, the black horizontal line represents the contribution of the
professional and business services sector to jobs growth volatility. To a close
approximation, the line’s height is the product of the heights of the three
bars.
For evidence on jobs growth volatility, see “The
Fraction of 1959 – 83 value
of Governors, International Finance Discussion
Declining Volatility of U.S. Employment: Was
Arthur Burns Right?” by M. V. Cacdac Warnock
and Francis E. Warnock, Federal Reserve Board
3
Share of nonfarm jobs
2.5
Paper no. 677, August 2000.
.37
Inflation has been lower and more stable, too.
Sector volatility (percentage points)
However, we focus on real activity.
Correlation with nonfarm jobs growth
2
Jobs growth volatility contribution (percentage points)
Good summaries of the Great Moderation
literature include “The Great Moderation,”
2
a speech by Federal Reserve Chairman Ben
1.5
S. Bernanke at the meetings of the Eastern
.19
Economic Association, Feb. 20, 2004, and “Has
the Business Cycle Changed? Evidence and
.13
1
Explanations,” by James H. Stock and Mark W.
.5
0
1959–1983
.076
× 1.9
× .92 ≈ .13
1984–1995
.098
Watson, a paper presented at the Federal Reserve
1996–2007
× 2.3 × .88 ≈
.19
.123
× 3.2 × .95
Bank of Kansas City symposium “Monetary
Policy and Uncertainty,” Jackson Hole, Wyo.,
≈ .37
Aug. 28 – 30, 2003. Also, see “On the Causes
of the Increased Stability of the U.S. Economy,”
SOURCE: Bureau of Labor Statistics.
by James A. Kahn, Margaret M. McConnell and
Gabriel Perez-Quiros, Federal Reserve Bank of
New York Economic Policy Review, May 2002,
movements in consumer durables.
Meanwhile, the fraction of jobs growth
volatility attributable to firms in professional and business services has
risen to the point where this sector
has become the largest contributor
to short-run swings in aggregate jobs
growth.
While the underlying causes
of the economy’s increased stability remain the subject of debate, the
stability’s persistence suggests that it’s
unlikely to be entirely the result of
good luck. Improved monetary policy
may well have played a role, but the
timing of the volatility reduction and
its sectoral composition also suggest
other factors have been at work. They
include improved inventory management, changes in the financial system
that have made it easier for households to smooth out their spending
over time, and the elimination of ceil-
ings on bank deposit interest rates,
which has helped reduce the construction sector’s cyclicality.
pp. 183 – 202; “New Economy, New Recession?”
by Evan F. Koenig, Thomas F. Siems and Mark
A. Wynne, Federal Reserve Bank of Dallas
Southwest Economy, March/April 2002, pp.
Koenig is a vice president and senior policy
advisor and Ball an economic analyst in the
Research Department of the Federal Reserve
Bank of Dallas.
11 – 16; and “Has Monetary Policy Become More
Effective?” by Jean Boivin and Marc P. Giannoni,
Review of Economics and Statistics, vol. 88,
August 2006, pp. 445–62.
3
Notes
Suppose that the random variable X is the
weighted sum of n other random variables,
The authors thank Christine Rowlette and
Xi , for i = 1, 2, ...n: X = Σai Xi , where the
Jessica Renier for research assistance.
weights, ai, are fixed. From the definition of
1
the correlation coefficient, ρXX , we know that
Among the earliest articles documenting the
i
reduction in GDP volatility are “Has the U.S.
Cov(X, Xi) = ρXX σX σX , where σX and σX are the
Economy Become More Stable? A Bayesian
standard deviations of X and Xi , respectively.
Approach Based on a Markov-Switching Model
Hence, σ²X = Cov(X, Σai Xi) = Σai Cov(X, Xi)
of the Business Cycle,” by Chang-Jin Kim and
= Σai ρXX σX σX , and σX = Σai ρXX σX . In
Charles Nelson, Review of Economics and
practice, there is often small period-to-period
i
i
i
i
i
i
i
Statistics, vol. 81, November 1999, pp. 608 – 16;
variation in the ai . Consequently, this formula is
“Output Fluctuations in the United States:
only approximately valid.
What Has Changed Since the Early 1980’s?”
4
by Margaret M. McConnell and Gabriel Perez-
change in real oil prices was 36.3 percentage
Federal Reserve Bank of Dall as
The standard deviation of the four-quarter
EconomicLetter
EconomicLetter
investment (0.46) and consumer expenditures on
points over the 24 years from 1960 through
1983, 22.7 points over 1984 – 95 and 32.7 points
nondurable goods (0.46).
over 1996 – 2007. Looking only at the standard
6
deviation of oil price increases (some claim
between sector and aggregate jobs growth puts
increases have a much bigger economic impact
manufacturing in first place over 1959 – 83,
than decreases), the standard deviations are 52.5,
with a correlation of 0.95, followed by the
15.1 and 25.9 points over the three periods.
professional and business services and trade,
5
A ranking based entirely on the correlation
transportation and utilities sectors in a virtual tie,
An alternative ranking, based solely on
correlations between sector and GDP growth, has
with correlations of 0.92 and 0.91, respectively.
consumer durables expenditures, nonresidential
In today’s economy, the tables are turned.
fixed investment and inventory investment in a
Professional and business services and trade,
virtual dead heat over 1959 – 83, with correlations
transportation and utilities both have correlation
of 0.66, 0.65 and 0.64. In today’s economy,
coefficients of 0.95, while manufacturing has
the top-ranking sectors by this criterion are
slipped to third, with a correlation coefficient of
nonresidential investment (0.56), inventory
0.91.
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