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September 2008
(Covering August 15, 2008 to September 11, 2008)

In This Issue
Inﬂation and Prices
July Price Statistics
Money, Financial Markets, and Monetary Policy
What Is the Yield Curve Telling Us?
International Markets
Global Developments in the Economic Outlook
Economic Activity and Labor Markets
Update of the Housing Market
Second-Quarter GDP Preliminary Revision: Onward and Upward?
The Employment Situation August
Do Oil Prices Directly Aﬀect the Stock Market?
Regional Activity
The Columbus Metropolitan Statistical Area
Fourth District Employment Conditions

Inﬂation and Prices

July Price Statistics
8.26.08
by Michael F. Bryan and Brent Meyer

July Price Statistics
Percent change, last
1mo.a

3mo.a

6mo.a

12mo.

5yr.a

2007 avg.

All items

13.4

10.6

6.4

5.6

3.6

4.2

Less food and
energy

4.0

3.5

2.3

2.5

2.3

2.4

Medianb

4.7

3.8

3.1

3.3

2.8

3.1

16% trimmed
meanb

7.2

5.5

4.0

3.6

2.7

2.8

Consumer Price Index

Import Price Index
All commodities

22.7

34.3

30.9

21.7

8.9

3.6

Nonpetroleum
imports
Export Price Index

11.0

9.9

11.4

8.0

3.5

2.1

All commodities

18.5

11.7

12.3

10.2

5.2

21.

a. Annualized.
b. Calculated by the Federal Reserve Bank of Cleveland.
Sources: U.S. Department of Labor, Bureau of Labor Statistics; and Federal Reserve
Bank of Cleveland.

Import and Export Price Indexes
12-month percent change
22
18
14
10

Imports

6
2
-2

Nonpetroleum imports

Exports

-6
-10
1998

2000

2002

2004

2006

2008

Source: Bureau of Labor Statistics.

Federal Reserve Bank of Cleveland, Economic Trends | September 2008

The CPI rose at an annualized rate of 10.3 percent
in July, much higher than expected, as energy and
commodity prices continued to surge. The energy
components of the CPI jumped up 59.2 percent
(annualized rate) and are up 29.2 percent over
the past 12 months. Consequently, the 12-month
growth rate in the CPI stands at 5.6 percent, its
largest increase in 17 years. The core CPI was
also elevated in July, rising 4.0 percent, its largest
monthly jump since November 2001. This followed a 3.9 percent increase in June. Measures
of underlying inﬂation trends computed by the
Federal Reserve Bank of Cleveland—the median
CPI and 16 percent trimmed-mean CPI—rose 4.7
percent and 7.2 percent, respectively. Over the past
three months, the 16 percent trimmed-mean CPI is
up 5.5 percent, while the median CPI has increased
3.8 percent.
Import prices, which have been surging since
March, rose 22.7 percent in July. This is a slight
improvement from the past four months, which
have all seen import price increases in excess of 39
percent. Both petroleum and nonpetroleum prices
contributed to the overall price gain in July, rising
60.4 percent and 11.0 percent, respectively. Export
prices remain elevated as well, rising 18.5 percent
in July after a 13.2 percent increase in June. Over
the past 12 months, export prices are up 10.2
percent, while import prices have jumped up 21.7
percent. Nonpetroleum imports have increased 8.0
percent over that same time period.
An investigation into the distribution of price
changes in the components of the CPI yields some
information about the nature of the price increases.
In July, 60 percent of the components of the CPI
rose at rates exceeding 3.0 percent, while 47 percent rose at rates greater than 5.0 percent, more
than double the 2007 average of 22.4 percent rising
at rate greater than 5.0 percent. On the other side
of the price-change distribution, only 9.2 percent
of the index’s components exhibited price decreases
1

CPI Component Price-Change Distributions

Core goods prices jumped up 5.6 percent in July
(their largest monthly price spike since September 1999), which may indicate that energy and
commodity prices are passing through into goods
production. Core services prices—which are much
more sensitive to wage pressures—were relatively
well-behaved, rising 3.4 percent during the month.

Weighted frequency
50
July 2008
45
2008 year-to-date average
40
2007 average
35
30
25
20
15
10
5
0

0 to 1
1 to 2
2 to 3
3 to 4
Annualized monthly percentage change

in July, compared with 16.5 percent year-to-date,
and an average of 20.7 percent in 2007.

4 to 5

Source: Bureau of Labor Statistics.

Core CPI Goods and Core CPI Services
12-month percent change
8
7
One-month annualized percent change
6
Core services
5
4
3
2
1
0
-1
-2
-3
Core goods
-4
-5
One-month annualized percent change
-6
1998
2000
2002
2004
2006
2008
Sources: U.S. Department of Labor, Bureau of Labor Statistics.

One-year-ahead average inﬂation expectations, as
measured by the University of Michigan’s Survey of
Consumers, fell 0.8 percentage point to 5.5 percent
in August, likely reﬂecting the recent decline in energy and commodity prices from near-term peaks.
Longer-term (5—10 year-ahead) average expectations ticked up to 3.8 percent in August from 3.5
percent in July, holding slightly above their recent
trend.

Household Inflation Expectations
12-month percent change
7.5
7.0
6.5
6.0
5.5
5.0
4.5
One year ahead
4.0
3.5
3.0
Five to ten-years ahead
2.5
2.0
1.5
1.0
1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Note: Mean expected change as measured by the University of Michigan’s
Survey of Consumers.
Source: University of Michigan.

Money, Financial Markets, and Monetary Policy

What Is the Yield Curve Telling Us?
08.26.08
by Joseph G. Haubrich and Kent Cherny
Since last month, the yield curve has ﬂattened
modestly, with both short-term interest rates
increasing and longer rates holding steady. One
reason for noting this is that the slope of the yield
curve has achieved some notoriety as a simple
Federal Reserve Bank of Cleveland, Economic Trends | September 2008

Yield Spread and Real GDP Growth
Percent
12
10

R eal G DP
growth
(year-to-year
a
perc ent
c hange)

8
6
4
2
0

Ten-year minus three-month
yield s pread

-2
-4
1953

1963

1973

1983

1993

2003

Note: Shaded bars represent recessions
Sources: Bureau of Economic Analysis; Federal Reserve Board.

Yield Spread and One-Year Lagged
Real GDP Growth
Percent
12
10

One year lagged real G DP growth
(year-to-year perc ent c hange)

8
6
4
2
0
Ten-year minus three-month
yield s pread

-2
-4
1953

1963

1973

1983

1993

2003

Sources: Bureau of Economic Analysis; Federal Reserve Board.

Yield Spread and Predicted GDP Growth
Percent
6
R eal G DP growth
(year-to-year perc ent c hange)

5
4

P redic ted
G DP growth

3
2
1
0

Ten-year minus three-month
yield s pread

-1
-2
2002

2003

2004

2005

2006

2007

2008

2009

Sources: Bureau of Economic Analysis; Federal Reserve Board.

Federal Reserve Bank of Cleveland, Economic Trends | September 2008

forecaster of economic growth. The rule of thumb
is that an inverted yield curve (short rates above
long rates) indicates a recession in about a year,
and yield curve inversions have preceded each of
the last six recessions (as deﬁned by the NBER).
Very ﬂat yield curves preceded the previous two,
and there have been two notable false positives: an
inversion in late 1966 and a very ﬂat curve in late
1998. More generally, though, a ﬂat curve indicates weak growth, and conversely, a steep curve
indicates strong growth. One measure of slope, the
spread between 10-year bonds and 3-month T-bills,
bears out this relation, particularly when real GDP
growth is lagged a year to line up growth with the
spread that predicts it.
The yield curve slope became somewhat ﬂatter,
with short rates moving up. The spread remains
positive, with the 10-year rate moving up 1 basis
point to 3.91 percent and the 3-month rate moving
up 9 basis points to 1.86 percent (both for the week
ending August 15). Standing at 205 basis points,
the spread is just below the 213 basis points seen
in July and the 218 basis points of June. Projecting
forward using past values of the spread and GDP
growth suggests that real GDP will grow at about a
3.0 percent rate over the next year. This remains on
the high side of other forecasts.
While such an approach predicts when growth is
above or below average, it does not do so well in
predicting the actual number, especially in the case
of recessions. Thus, it is sometimes preferable to
focus on using the yield curve to predict a discrete
event: whether or not the economy is in recession.
Looking at that relationship, the expected chance
of the economy being in a recession next August
stands at 1.3 percent, just above June and July’s 1.1
percent.
The probability of recession is below several recent
estimates, and perhaps seems strange the in the
midst of recent ﬁnancial concerns. But one aspect
of those concerns has been a ﬂight to quality, which
lowers Treasury yields. Also working to steepen the
yield curve are the reductions in both the federal
funds target rate and the discount rate by the Federal Reserve. Furthermore, the forecast is for where
the economy will be next August, not earlier in the
3

year.

Probability of Recession Based on the
Yield Spread

To compare the 1.1 percent to some other probabilities, and learn more about diﬀerent techniques
of predicting recessions, head on over to the Econbrowser blog.

Percent
100
90
P robability of
rec es s ion

80
70

Forecast

60
50
40
30
20
10
0
1960

1966

1972

1978

1984

1990

1996

2002

2008

Note: Estimated using probit model.
Sources: Bureau of Economic Analysis; Federal Reserve Board; author’s calculations.

Of course, it might not be advisable to take this
number quite so literally, for two reasons. First,
this probability is itself subject to error, as is the
case with all statistical estimates. Second, other
researchers have postulated that the underlying
determinants of the yield spread today are materially diﬀerent from the determinants that generated
yield spreads during prior decades. Diﬀerences
could arise from changes in international capital
ﬂows and inﬂation expectations, for example. The
bottom line is that yield curves contain important
information for business cycle analysis, but, like
other indicators, should be interpreted with caution.
For more detail on these and other issues related to
using the yield curve to predict recessions, see the
Commentary “Does the Yield Curve Signal Recession?”

International Markets

Global Developments in the Economic Outlook
09.09.08
by Owen Humpage and Michael Shenk
Sometimes globalization giveth, but sometimes
it taketh away. The dollar’s recent depreciation
and exceptionally strong economic growth abroad
have been a boon to U.S. economic growth, but
that may now be changing. Preliminary estimates
showed a surprisingly strong, 3.3 percent increase
in GDP during the second quarter of 2008, with
almost all of this increase attributable to a combined rise in U.S. exports and decline in imports.
Real gross domestic purchases—spending less
exports—continued to be very weak in the second
quarter, so much so that their recent performance
resembles that during the 2001 recession. U.S.
exports have increased substantially faster than
GDP since mid-2003 and have, therefore, been
a signiﬁcant, sustained source of growth. While
imports are now a higher percentage of GDP than
Federal Reserve Bank of Cleveland, Economic Trends | September 2008

in 2003, they have ﬂattened out over the past three
years. Consequently, our trade deﬁcit has narrowed
substantially.

Real Gross Domestic Product and
Purchases
Percent change, annual rate
8
Gross domestic product
Gross domestic purchases

7
6
5
4
3
2
1
0
-1
-2
2000

2002

2004

2006

2008

Source: Bureau of Economic Analysis.

World GDP Growth
Projections

World
Advanced economies
United States

2006

2007

2008

2009

5.1

5.0

4.1

3.9

3.0

2.7

1.7

1.4

2.9

2.2

1.3

0.8

Euro area

2.8

2.6

1.7

1.2

Japan

2.4

2.1

1.5

United Kingdom

2.9

3.1

1.8

1.7

Canada

3.1

2.7

1.0

1.9

7.9

8.0

6.9

6.7

China

11.6

11.9

9.7

9.8

India

9.8

9.3

8.0

ASEAN-5

5.7

6.3

5.6

5.9

Western Hemisphere

5.5

5.6

4.5

3.6

Emerging and developing economies

Note: GDP growth is measured as a year-over-year percent change.
Source: International Monetary Fund, World Economic Outlook Update July
2008.

Federal Reserve Bank of Cleveland, Economic Trends | September 2008

Explaining the causal relationship between trade
deﬁcits and dollar depreciations is always tricky
because other economic events determine both
variables. Since at least 2005, however, the passive
reluctance of international investors to add dollars to their portfolios seems to have precipitated
the dollar’s depreciation. Since the end of 2005
through March of this year, the dollar depreciated
14 percent on a real, or inﬂation-adjusted, basis
against a broad array of U.S. trading partners. Such
a real depreciation raises the dollar price of foreign
goods, lowers foreign-currency prices of U.S. goods,
and shifts world demand toward U.S. products.
At roughly the same time as this exchange-rateinduced demand shift started, the world began to
exhibit an exceptionally strong streak of economic
growth. Between 2004 and 2007, world output
expanded at a 4.8 percent average annual rate.
While emerging markets, notably China and India,
led the way, nearly every nation on earth shared in
the expansion. Such rapid, widely shared economic
growth seems unprecedented.
Now, however, some of these favorable international factors may be dissipating and signaling slower
economic growth ahead. The dollar seems to have
stabilized since March and, while it certainly could
move lower, the dollar now seems a tad soft on a
purchasing-power-parity basis. More importantly,
however, global economic activity is likely to slow
substantially in the second half of 2008 and return
gradually to a more normal growth rate by late
2009. The International Monetary Fund, for example, expects global growth to slow from 5.0 percent
in 2007 to 4.1 percent this year and 3.9 percent in
2009. Economic growth among the advanced economies is expected to drop from 2.7 percent in 2007
to only 1.7 percent this year and 1.4 percent in
2009, while economic growth among the emerging
and developing economies is expected to slow from
8.0 percent in 2007 to 6.9 percent in 2008 and
6.7 percent in 2009. While many forecasters have
recently revised their forecasts for foreign growth
down, the IMF, which initially had a pessimistic
5

world outlook, has generally revised them up.
Financial turmoil, stemming from U.S. subprime
real estate loans, initiated the global slowdown. Despite some improvements, ﬁnancial strains remain
a serious risk to the economic outlook. As banks
continue to improve their balance sheets by writing
down debts and raising new capital, they will increase the terms and limit the availability of credit.
This will impair economic growth, which will, in
turn, feed back into credit quality. Downturns in
housing prices and construction seem to be spreading among advanced developed countries with little
evidence of bottoming out. Many central banks
have tempered their response to the downside risks
associated with the ﬁnancial turmoil for fear of
igniting inﬂation.

Headline Inflation and Oil Prices
12-month percent change
10

Dollars per barrel
160

140

120

CPI: developing countries

7
6

100

4
3

Oil prices

CPI: industrial countries

2
1

2000

2002

2004

2006

2008

Source: International Monetary Fund, International Financial Statistics; and the Wall
Street Journal

The exceptionally strong economic growth between
2004 and 2007, particularly among emerging and
developing countries, raised commodity prices in
recent years. Although the upward pressures on
commodity prices have recently eased as global
economic activity has softened, higher commodity
prices are unlikely to disappear in the near future.
Spare oil capacity and inventories are limited, and
expanding production and distribution capacity is
costly and time consuming. Although agricultural
production may be more responsive to higher prices
than the oil supply, growing global demand and
higher oil prices will keep pressure on food prices.
Higher commodity prices mean consumers have
less to spend on other goods and services.
In advanced countries, according to the IMF,
core price measures have generally stayed below 2
percent, while upward pressure from oil and other
commodity prices have pushed headline price measures substantially higher. Central banks in most
developed countries have been reluctant to ease
policy in the face of strong price pressures. Emerging and developing countries, however, have been
more accommodative. They have allowed commodity-price pressures to exert a bigger eﬀect on core
prices, which are now rising around 4 percent year
over year, according to the IMF. Inﬂation could
remain a problem in these economies through next
year.

Federal Reserve Bank of Cleveland, Economic Trends | September 2008

Economic Activity

Update of the Housing Market
Existing Single-Family Home Sales
Millions of units
6.5

Thousands of dollars
240

6.0

220

5.5

200

5.0

180
Median sales price

4.5

160

4.0

140

3.5

120

3.0
1995

100
1997

1999

2001

2003

2005

2007

Source: National Association of Realtors.

Inventories of Existing Single-Family
Homes for Sale
Months of supply
12

Millions of units
4
3.7

3.4

3.1

2.8

2.5

2.2

1.9

1.6

1.3
1990

3
1994

1998

2002

2006

Source: National Association of Realtors.

New Single-Family Home Sales
Millions of units
1.4

Thousands of dollars
280

1.3

260

1.2

240

1.1

220

1.0

200

0.9

Median sales price

180

0.8

160

0.7

140

0.6

120

0.5
1995

09.04.08
by Michael Shenk
Over the past two weeks, a lot of data on the housing market has been released, giving us a fairly
comprehensive look at where the market stands
through July. Here’s a brief overview of that data
and the picture it paints of the housing market.
Existing single-family home sales—which comprise
the majority of home sales in the United States—
rose 3.1 percent in July, after falling 3.4 percent in
June. Over the past few months, existing singlefamily home sales have stabilized noticeably. They
have increased in four of the ﬁrst seven months of
2008, compared to a total of just three increases in
2006 and only two in 2007. In fact, so far this year,
sales are up an annualized 2.8 percent.
While these reports on existing single-family home
sales have been refreshing, it’s diﬃcult to say with
any certainty that the market has bottomed out.
Remember, we saw a similar period of apparent
stabilization from July 2006 to February 2007, but
then sales began to decline again in March. Looking at inventories, it’s clear that there is still an
oversupply of homes for sale, which could continue
to put downward pressure on prices and potentially
further slow the pace of sales.
Sales of new single-family homes also increased
in July, rising 2.4 percent following a 2.1 percent
decline in June. Like the existing-homes market,
the market for new single-family homes is showing
some encouraging signs. However, those signs are a
little more tenuous since the trend has not been as
pronounced or as long in duration. Still, over the
past ﬁve months, new single-family home sales have
been essentially ﬂat, a performance that represents
the series’ best ﬁve-month showing since late 2006.
However, the growth rates for the series over longer
periods—6, 9, and 12 months—all remain substantially negative and have shown limited improvement in recent months.

100
1997

1999

2001

2003

2005

2007

Source: Census Bureau.

Federal Reserve Bank of Cleveland, Economic Trends | September 2008

The inventories picture for new homes is a little
more encouraging. New-home builders continued
7

New Single-Family Homes for Sale
Thousands of units
650

Months of supply
12

600

550

500

450

400

350

300

250

4
3

200
1990
1994
Source: Census Bureau.

1998

2002

2006

Single-Family Starts and Permits
Millions of units
1.9

Starts
1.5
1.3
1.1
Permits
0.9
0.7
0.5
2001

2003

2005

2007

All things considered, the housing market’s troubles
continued into July. But for those looking for a
bright spot, some tenuous signs that the market is
getting close to the bottom are emerging. Going
forward, the downside risk is that high inventories
and ﬁnancial troubles will continue to put downward pressure on prices, which could result in
further declines in sales and construction activity.

Home Price Indexes
Percent change, year over year
20
S&P/Case-Shiller

Given the level and direction of inventories, the
data for housing starts shouldn’t be a surprise. The
decline in single-family housing starts has continued in recent months and shows little signs of
bottoming out. The only positive sign is that the
pace of the decline, while still rapid, appears to be
slowing somewhat, as evidenced by improvements
in the 3-, 6-, and 9-month growth rates. However,
at −21.5 percent, −27.0 percent, and −34.9 percent (annualized rates), these rates make clear that
single-family starts are far from turning a corner.
Given the level and direction of inventories, the
data for housing starts shouldn’t be a surprise. The
decline in single-family housing starts has continued in recent months and shows little signs of
bottoming out. The only positive sign is that the
pace of the decline, while still rapid, appears to be
slowing somewhat, as evidenced by improvements
in the 3-, 6-, and 9-month growth rates. However,
at −21.5 percent, −27.0 percent, and −34.9 percent (annualized rates), these rates make clear that
single-family starts are far from turning a corner.

1.7

1995
1997
1999
Source: Census Bureau.

to work oﬀ inventory in July, as the number of
homes on the market fell 5.2 percent, the largest
monthly decline since 1963. However, given the
slow pace of sales, inventories are still elevated,
though they have backed oﬀ of their recent highs
somewhat.

10
5
OFHEO purchase only index
0
-5
-10
-15
-20
1992

1994

1996

1998

2000

2002

2004

2006

2008

Sources: S&P, Fiserv, MacroMarkets LLC, and OFHEO.

Federal Reserve Bank of Cleveland, Economic Trends | September 2008

Economic Activity

Second-Quarter GDP Preliminary Revision: Onward and Upward?
09.05.08
by Brent Meyer

Real GDP and Components 2008:
Second-Quarter Preliminary Estimate
Annualized percent change, last:
Quarterly change
(billions of 2000$)

Quarter

Four quarters

Real GDP

94.3

3.3

2.2

Personal consumption

36.1

1.7

1.4

Durables

-7.9

-2.5

-1.1

Nondurables

24.7

4.2

1.3

Services

15.6

1.3

1.9

Business fixed investment

7.9

2.2

4.2

-8.9

-3.2

0.2

Equipment

10.6

13.6

12.7

Residential investment

Structures

-16.1

-15.8

-22.2

Government spending

19.4

3.9

2.6

National defense

9.4

7.4

5.9

Net exports

85.4

—

Exports

47.3

13.2

11.2

Imports

-38.1

-7.5

-2.0

Private inventories

-49.4

—

Source: Bureau of Labor Statistics.

Contribution to Percent Change in Real GDP
Percentage points
2.5
2008:Q2 advance
2008:Q2 preliminary
2.0
Imports

1.5
1.0
0.5
0.0
-0.5
-1.0

Business
fixed
investment

Change in
inventories

Personal
consumption

Exports
Residential
investment

Government
spending

-1.5
-2.0
-2.5
Source: Bureau of Economic Analysis

Federal Reserve Bank of Cleveland, Economic Trends | September 2008

Real GDP advanced at an annualized rate of 3.3
percent in the second quarter, outpacing its growth
over the past four quarters, according to the preliminary release from the BEA. This is an upward
revision of 1.4 percentage points from the advance
estimate, and an extremely large revision when
compared to the average advance–to–preliminary
revision over the past 20 years of 0.5 percentage
point (this is the absolute average—the average
without regard to sign). If this estimate holds, the
economy will have grown in the second quarter at
a rate in excess of its average over the past 20 years
(not bad for a quarter that, not too long ago, was
expected to post near–zero growth).
The upward revision was, in large part, due to
favorable adjustments to net exports and private
inventories. Exports increased 13.2 percent in the
second quarter, revised up from 9.2 percent. At
the same time, imports (which subtract from GDP
growth) were revised down from a decrease of 6.6
percent to one of 7.5 percent. All told, the revision
to net exports added 3.1 percentage points to real
GDP growth in the second quarter, an additional
0.7 percentage point over the advance estimate. The
sell-oﬀ in private inventories was not as dramatic as
the advance release made it out to be, subtracting
1.4 percentage points from second-quarter growth,
as opposed to a 1.9 percentage-point subtraction.
Consumption growth was also revised up, increasing 1.7 percent in the second quarter (up from 1.5
percent in the ﬁrst quarter), while the investment
picture was largely unchanged from the advance
release.
In contrast to the large contribution to real GDP
growth from net exports in 2008:Q2 (3.1 percentage points), the average contribution to growth
from net exports since 1980 has been −0.2 percentage point. In fact, the last time net exports added
this much to growth was during the second quarter
of 1980.
9

Net Exports Contribution to Percent Change
in Real GDP
Percentage points
5
4
3
2
1
0
-1
-2
Average contribution since 1980
-3
-4
-5
1980
1984
1988
1992
1996

Forecast

2000

2004

2008

Source: Bureau of Economic Analysis.

Real GDP Growth
Annualized quarterly percent change
6
Final estimate
Preliminary estimate
Blue Chip consensus forecast
5

In contrast to the large contribution to real GDP
growth from net exports in 2008:Q2 (3.1 percentage points), the average contribution to growth
from net exports since 1980 has been −0.2 percentage point. In fact, the last time net exports added
this much to growth was during the second quarter
of 1980.
Looking forward, professional forecasters are expecting growth in the second half of the year to be
weak, perhaps reﬂecting the drying up of the ﬁscal
stimulus and the ongoing ﬁnancial uneasiness.
Although they still expect GDP growth to start to
rebound toward its longer-term trend in 2009, 31
of the 50 forecasters on the Blue Chip panel revised
their 2009 growth outlook down from their previous forecast.

Average GDP growth
(1978:Q3-2008:Q2)

4
3
2
1
0
-1

Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

2006

2007

2008

2009

Source: Blue Chip Economic Indicators, July 2008; Bureau of Economic Analysis.

Economic Activity

The Employment Situation
09.09.08
by Yoonsoo Lee and Beth Mowry
Nonfarm payrolls declined by 84,000 in August,
and the unemployment rate rose to 6.1 percent, up
from 5.7 percent in July. Downward revisions to
June and July payroll numbers amounted to 58,000
additional losses for those months. This marks the
eighth consecutive month of employment decline
and the highest rate of unemployment since September 2003. The decline in payrolls and the rise
in the unemployment rate were both larger than
consensus expectations.
Federal Reserve Bank of Cleveland, Economic Trends | September 2008

The diﬀusion index of employment change improved, moving up to 48.9 from 41.4 in July. However, given the overall weakness of the labor report,
the rise in this index implies that employment
losses are more concentrated in certain sectors. Furthermore, a reading below the threshold of 50 still
indicates that more businesses are subtracting jobs
than adding them.

Average Nonfarm Employment Change
Change, thousands of jobs
250

Revised
Previous estimate

200
150
100
50
0

The goods-producing sector shed 57,000 jobs in
August, compared to July’s slightly smaller loss of
48,000. These higher losses come entirely from
manufacturing, as construction losses actually improved over the month, from 20,000 job losses to
just 8,000. While residential construction continued to decline, nonresidential construction added
12,200 jobs in August.

-50
-100
-150

2005 2006 2007 2008 IV
I
II
YTD 2007 2008

III

Jun

Jul

Aug

Source: Bureau of Labor Statistics.

Private Sector Employment Growth
Change, thousands of jobs: 3-month moving average

The manufacturing sector shed 61,000 jobs last
month, contributing a good portion of the 57,000
net jobs lost within goods-producing industries
as a whole. Most of the sector’s declines are explained by losses at durable goods ﬁrms, which
totaled 55,000. In comparison, nondurable goods
ﬁrms lost 6,000 jobs. The greatest losses in nondurables occurred in motor vehicles and parts, which
dropped 39,000 jobs last month compared to July’s
loss of just 400. This is the biggest dip the auto
industry has seen since July 1998. Excluding motor
vehicles and parts, manufacturing lost 22,000 jobs
last month, a smaller loss than July’s loss of 37,700
or June’s of 38,400.

350
300
250
200
150
100
50
0
-50
-100
-150
-200
2003

2004

2005

2006

2007

2008

Source: Bureau of Labor Statistics.

Federal Reserve Bank of Cleveland, Economic Trends | September 2008

With a payroll decline of 27,000, service-providing
industries lost more jobs in August than in July,
despite the government sector’s larger contribution this month of 17,000 jobs. Education and
health services, with 55,000 new jobs, continued
to provide the only strength to service-providing
industries, which lost 27,000 jobs as a whole.
Education added 16,300 jobs, and healthcare and
social assistance tacked on an even more impressive
38,100. All other major service industries shrank
in August, particularly professional and business
services (−53,000) and trade, transportation and
utilities (−35,000). Within trade, transportation
and utilities, wholesale and retail trade suﬀered the
heaviest losses at 38,400. Temporary help services,
considered a leading indicator of overall employ11

ment conditions, had yet another tough month in
August, dropping 36,900 jobs in its worst decline
since November 2001.

Labor Market Conditions
Average monthly change (thousands of employees, NAICS)
2005

2006

2007

YTD 2008

August 2008

Payroll employment

211

175

−76

−84

Goods-producing

−38

−74

−57

−19

−37

−8

Construction
Heavy and civil engineering

−1

−5

−2.0

Residentiala

−5

−20

−27

−18.6

Nonresidentialb

−5

−12.2

Manufacturing

−7

−14

−22

−43

−61

Durable goods

−4

−16

−55

Nondurable goods

−8

−10

−6

−12

−6

Service-providing

179

172

130

−2

−27

Retail trade

−25

−19.9

Financial activitiesc

−9

−6

−3

PBSd

−34

−53

−7

−28

−23.5

Leisure and hospitality

−5

Government

Temporary help services
Education and health services

Local educational services
Civilian unemployment rate

5.1

4.6

5.3

6.1

a. Includes construction of residential buildings and residential specialty trade contractors.
b. Includes construction of nonresidential buildings and nonresidential specialty trade contractors.
c. Financial activities include the finance, insurance, and real estate sector and the rental and leasing sector.
d. PBS is professional business services (professional, scientific, and technical services, management of companies
and enterprises, administrative and support, and waste management and remediation services.
Source: Bureau of Labor Statistics.

Unemployment Rate
Percent
22

Percent
8
7

Ages 16-19

14
Ages 25+
12

2
2000

2002

2004

2006

2008

Notes: Data are seasonally adjusted rates for the civilian population. The shaded
bar indicates a recession.
Source: Bureau of Labor Statistics.

Federal Reserve Bank of Cleveland, Economic Trends | September 2008

The three-month moving average of private sector employment growth remains in the negative
territory it entered back in January, sitting roughly
unchanged from the previous report at −92,000.
These private sector declines, though, have not
yet reached levels as severe as losses during typical
recessions.
As noted earlier, the unemployment rate jumped 40
basis points to 6.1 percent, the highest level it has
been since September 2003. The rate had also experienced large jumps in the spring, particularly April
to May, owing much to teenagers (16 to 19), whose
unemployment rate jumped from 15.4 percent
to 18.7 percent. August’s increase is more worrisome, though, because it is an increase in the adult
12

unemployment rate which accounts for it. The rate
for people 25 years and older increased from 4.4 to
4.9 percent last month, while the rate for teenage
workers fell.

Economic Activity

Do Oil Prices Directly Aﬀect the Stock Market?
09.12.08
by Andrea Pescatori and Beth Mowry

Oil Prices and the S&P 500 Index
Dollars per billions of barrels
200

S&P500 index, 1941–43=10
1,600
1,400

160

1,200

120

1,000

800

600
1997

0
1999

2001

2003

2005

2007

Notes: The oil price is the weekly average domestic spot price of light sweet
crude oil (WTI). The S&P 500 index values are taken from the average
weekly close.
Sources: The Wall Street Journal; S&P.

Market commentators and journalists like to draw
direct lines between the behavior of crude oil prices
and market behavior on a given day, with such
headlines as “Oil Spike Pummels Stock Market”
(Wall Street Journal) or “U.S. Stocks Rally as Oil
Prices Fall”(Financial Times). But does a change
in oil prices aﬀect the overall stock market in any
predictable, meaningful way? Might a hike in crude
foretell a weak day on the Street?
It seems logical to assume that oil prices and stock
market performance might be negatively correlated.
More expensive fuel translates into higher transportation, production, and heating costs, which can
put a drag on corporate earnings. Rising fuel prices
can also stir up concerns about inﬂation and curtail
consumers’ discretionary spending. But it is also
possible to associate expensive crude with a booming economy. Higher prices could reﬂect stronger
business performance and increased demand for
fuel.
Which is it? A look at oil prices and the S&P 500
index suggests neither. Both oil prices and the S&P
500 index have mostly climbed over the past 10
years, but they have frequently moved in opposite
directions. Sometimes they rise and fall together,
but the relationship between oil and stocks does
not appear to be very strong.
The following scatterplot relates the weekly behavior of crude prices with S&P 500 performance
since the beginning of 1998. If a clear negative
relationship between oil prices and the S&P 500
index existed, we would expect to see the points
aligned along somewhat of a downward-sloping
line, indicating poorer stock performance when oil

Federal Reserve Bank of Cleveland, Economic Trends | September 2008

prices pick up. No such relationship is evident, at
least not in the time period sampled. Furthermore,
the correlation between weekly averages of the spot
oil price and the S&P 500 index is a weak and statistically insigniﬁcant −0.021 for the past 10 years
(with a conﬁdence level of 95 percent).

Oil Price and S&P Growth
Series 1
10

S&P growth

-20

-10

10
-5

-10

Oil price growth
Note: The sample period is January 1998–August 2008, and the data are weekly.
Source: Financial Times.

It is possible that a stronger correlation might exist for data at diﬀerent frequencies (daily, weekly,
monthly) or with diﬀerent stock indexes. The S&P
500 index is widely used as a broad market indicator because it contains the stocks of 500 leading
U.S. companies that trade on the two largest U.S.
stock markets, the New York Stock Exchange and
the Nasdaq. We can expand the industries covered
by including other indexes: S&P Financial, S&P
Industrial, Dow Jones Industrial, Dow Jones Transportation, the Nasdaq Composite, and the NYSE
Composite, and we can look at data at all three
frequencies to see if either of these factors aﬀect the
correlation.
It is also possible that the relationship between oil
and the stock market changes over time, say when
oil prices are at a trough versus when they are at
a peak. To investigate this possibility, we designate the 18-month period surrounding December
1998 as an oil price trough (from March 1998 to
September 1999) and the most recent 18-month
period beginning February 2007 as a price peak,
and compare the correlations.
As it turns out, correlations between oil prices and
all of these stock indexes at the daily, weekly, and
monthly levels for the two time periods also reveal
very few relationships of statistical signiﬁcance. Calculations using daily data yielded the most statistically signiﬁcant results, but as you can see from the
table below, these were very small.
The majority of correlations we computed for the
diﬀerent indexes and frequencies of data are relatively small and, in the ﬁrst sample, not signiﬁcant,
with the expection of the Dow Jones Transportation index. (A statistically insigniﬁcant correlation
indicates that a relationship is likely nonexistent.)

Federal Reserve Bank of Cleveland, Economic Trends | September 2008

Correlation Between Oil and Stock Index Growth
(daily)
S&P
500

S&P
Industrial
Index

S&P
Financial
Index

NYSE
Composite

Dow Jones
30 Industrial
Average

NASDAQ

Dow jones
Transportation

1998-1999

13.4

10.6

6.4

5.6

3.6

4.2

2007-2008

4.0

3.5

2.3

2.5

2.3

2.4

Note: Only the highlighted correlations are statistically significant at the 95% confidence level..
Sources: The Wall Street Journal, S&P, Financial Times.

During the oil peak between February 2007 and
August 2008, ﬁve correlations are signiﬁcant at
the 95 percent conﬁdence level. Furthermore, all
correlations for this period (whether statistically
signiﬁcant or not) are negative. Not surprisingly,
the Dow Jones Transportation index is the only
index with signiﬁcant correlations in both samples.
In this case, it seems fair to say that changes in oil
prices have a direct eﬀect on the share prices of
transportation companies. On the other hand, the
Financials index has the highest negative correlation
in the 2007–2008 sample. In principle, the ﬁnancial industry is not directly aﬀected by energy costs,
so this correlation may support the inverted causality argument claimed by some ﬁnancial analysts:
When ﬁnancials are battered by bad news, liquidity ﬂies to “the easier bet” markets like commodity
markets. (This does not necessarily last.)
More generally, the fact that correlations for the
ﬁrst period in the table above change from being
mainly insigniﬁcant to being generally signiﬁcant
(and negative) in the latter period suggests that
the level of oil prices might matter. This is another
reﬂection of the possibility that correlations are
generally not stable over time. For example, the
short-run share of the economy going toward oil is
price elastic, which means that the share increases
when the price of oil does. When oil takes up a
higher share of the economy, like today with respect
the 1990s, it implies that a change in the price of
oil could be more harmful than when oil’s share
was smaller. So, for example, a 1 percent change in
the price of oil today could do more damage than a
1 percent increase in 1999.

Federal Reserve Bank of Cleveland, Economic Trends | September 2008

Regional Activity

The Columbus Metropolitan Statistical Area
09.03.08
by Kyle Fee

Counties of the Columbus MSA

The Columbus Metropolitan Statistical Area (MSA)
is located in the geographic center of Ohio. The
MSA is home to 1.75 million people dispersed
across eight counties (Delaware, Fairﬁeld, Franklin,
Licking, Madison, Morrow, Pickaway, and Union).
Columbus diﬀers from other large Fourth District
MSAs in terms of population growth. Since 1970,
Columbus’s population has grown at a pace equivalent to the nation. In that same period, Cincinnati’s
population grew half as fast, while Pittsburgh’s
declined 15 percent and Cleveland’s declined 10
percent.
Columbus also diﬀers from other Fourth District
MSAs in that the proportion of its workforce employed in manufacturing is lower than the national
average. This diﬀerence in labor allocation may
have helped insulate the MSA from the job losses
that have taken their toll on other Fourth District
MSAs. Columbus’s diverse economy is anchored
by two high-skilled, high-wage service industries:
ﬁnancial activities and professional and business
services. In 2007, the share of workers in each of
these service industries was more than 20 percent
greater in Columbus than in the nation as a whole.

Population Growth
Index, 1970 = 100
150
140
U.S.
130
Cincinnati MSA
120

Columbus MSA

110

Ohio

100

Cleveland MSA

90
Pittsburgh MSA
80
1970

1975

1980

1985

1990

1995

2000

From 2006 to 2007, the MSA’s total nonfarm employment grew faster than the nation’s (1.3 percent
compared to 1.1 percent). Professional and business
services have seen employment growth in excess
of 4 percent, roughly doubling that of the nation’s
in that industry. Manufacturing was less of a drag
on Columbus than on the nation with growth of
−1.3 percent and −1.9 percent, respectively. On the
downside, natural resources, mining, and construction lost employment in Columbus at a rate substantially above the national rate.

2005

Source: U.S. Department of Commerce, Bureau of the Census.

Location Quotients for the Columbus MSA
and the U.S., 2007
Natural resources, mining, and construction
Manufacturing
Trade, transportation, and utilities
Information
Financial activities
Professional and business services
Education and health services
Leisure and hospitality
Other services
Government

0.2

0.4

0.6

0.8

1.2

Note: A location quotient is used to measure the degree to which an industry is
concentrated in a region relative to a reference economy. A quotient greater than
1.0 says that the region, here, the Columbus MSA, has a higher concentration of
an industry’s employment than the reference economy (U.S.).
Source: U.S. Department of Labor, Bureau of Labor Statistics.

Federal Reserve Bank of Cleveland, Economic Trends | September 2008

1.4

Since the last business cycle peak in March 2001,
Columbus added 2.8 percent to its total nonfarm
payroll employment, compared to Ohio’s loss of
3.1 percent and the nation’s gain of 3.9 percent.
Columbus’s employment numbers returned to
16

Payroll Employment Growth, 2006–2007
Columbus MSA
U.S.

Total nonfarm
Goods-producing
Manufacturing
Natural resources, mining, and construction
Service-providing
Trade, transportation, and utilities
Information
Financial activities
Professional and business services
Education and health services
Leisure and hospitality
Other services
Government
-4

-3

-2

-1
0
1
2
Percent change

Source: U.S. Department of Labor, Bureau of Labor Statistics.

Index, March 2001 = 100
106
U.S.
104

Columbus MSA

100

The most consistent drivers of annual employment
growth have been education, health, leisure, government and other services, followed by transportation, warehousing, and utilities. Financial, information, and business services rebounded in 2004 and
have been providing a boost to employment growth
in recent years. Not surprisingly, manufacturing has
been a drag on Columbus’s employment numbers;
on the bright side, the size of manufacturing’s negative impact has decreased each year since 2001.
Until recently, the Columbus MSA had experienced lower levels of unemployment than the
nation. From 1990 through late 2004, Columbus’s
unemployment rate was consistently below the national rate. In the late 1990s, Columbus even had
an unemployment rate below 3 percent. However,
coming out of the last recession, the MSA’s unemployment rates have generally hovered around the
national unemployment rate.

Payroll Employment since March 2001

102

pre–recession levels in late 2005, while the nation’s
returned in early 2005.

Ohio

96
2001

2002

2003

2004

2005

2006

2007

2008

Source: U.S. Department of Labor, Bureau of Labor Statistics.

Components of Employment Growth in the
Columbus MSA
Percent change
3
Natural resources, mining, and construction
2

Financial, information, professional,
and business services
Education, health, leisure, government,
and other services

Transportation, warehousing,
and utilities
Manufacturing
Retail and wholesale trade

U.S.

Unemployment
Percent
8
7

U.S.

5
0

4
-1

Columbus MSA

3
-2
2001

2002

2003

2004

2005

2006

2007

Note: The white bars represent total annual growth for the Columbus MSA. The brown
line is U.S. growth.
Source: U.S. Department of Labor, Bureau of Labor Statistics.

Federal Reserve Bank of Cleveland, Economic Trends | September 2008

2
1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
Source: U.S. Department of Labor, Bureau of Labor Statistics.

Regional Activity

Fourth District Employment Conditions
09.11.08
by Kyle Fee

Unemployment Rates
Percent
8
7
Fourth Districta
6
5
United States

3
1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
a. Seasonally adjusted using the Census Bureau’s X-11 procedure.
Note: Shaded bars represent recessions. Some data reflect revised inputs,
reestimation, and new statewide controls. For more information, see
http://www.bls.gov/lau/launews1.htm.
Source: U.S. Department of Labor, Bureau of Labor Statistics.

County Unemployment Rates
U.S. unemployment rate = 5.7%

4.1% - 5.0%
5.1% - 6.0%
6.1% - 7.0%

The district’s unemployment rate jumped up 0.4
percent to 6.6 percent for the month of July. The
increase in the unemployment rate is attributed to
monthly increases in the number of people unemployed (5.9 percent) along with a decrease in
the number of people employed (−0.5 percent).
The District’s rate was 0.9 percent higher than the
nation’s in July, and it has been consistently higher
since early 2004. Since this time last year, the
Fourth District’s unemployment rate has increased
1.2 percentage points and the nation’s has increased
1.0 percentage point.
Unemployment rates varied considerably across
counties in the Fourth District. Of the 169 counties that make up the District, 29 had an unemployment rate below the national average in July
and 140 had a higher rate. Twelve District counties
reported double-digit unemployment rates, while 6
counties had an unemployment rate below 5.0 percent. Rural Appalachian counties continue to experience higher levels of unemployment, and counties
along the Ohio-Michigan border have begun to see
more elevated rates of unemployment.

7.1% - 8.0%
8.1% - 9.0%
9.1% - 11.7%
Note: Data are seasonally adjusted using the Census Bureau’s X-11 procedure.
Source: U.S. Department of Labor, Bureau of Labor Statistics.

County Unemployment Rates
Percent
12.0
11.0
10.0
9.0

Ohio
Kentucky
Pennsylvania
West Virginia
Median unemployment rate = 7.0%

8.0
7.0
6.0
5.0
4.0
3.0

County

Note: Data are seasonally adjusted using the Census Bureau’s X-11 procedure.
Source: U.S. Department of Labor, Bureau of Labor Statistics.

Federal Reserve Bank of Cleveland, Economic Trends | September 2008

The distribution of unemployment rates among
Fourth District counties ranges from 4.1 percent to
11.8 percent, with the median being 7.0 percent.
Only one of Pennsylvania’s Fourth District counties
lies in the upper half of the distribution, whereas
59 percent of Ohio’s counties and 57 percent of
Kentucky’s District counties are above 7.0 percent.
These county-level statistics are reﬂected in statewide unemployment rates: Ohio’s is at 7.2 percent,
Kentucky’s is 6.7 percent, and Pennsylvania’s is 5.4
percent.
The distribution of monthly changes in unemployment rates shows that the median county unemployment rate increased 0.4 percentage point from
June to July. The rise in county-level unemployment rates was concentrated in Kentucky and Ohio
during this period. In Kentucky, 93 percent of the
18

Change in County Unemployment Rates,
June 2008–July 2008
Percentage points
2.4

Ohio
Kentucky

2.0

counties in the District experienced an increase in
the unemployment rate, as did 86 percent of the
counties in Ohio.

Pennsylvania
West Virginia

1.6
1.2

Median unemployment rate change = 0.4 percentage point

0.8
0.4
0.0
-0.4
-0.8
-1.2
-1.6
-2.0

County

Note: Data are seasonally adjusted using the Census Bureau’s X-11 procedure.
Source: U.S. Department of Labor, Bureau of Labor Statistics.

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Federal Reserve Bank of Cleveland, Economic Trends | September 2008

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