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Federal Reserve Bank of Cleveland

Economic Trends
August 2007
(Covering July 14, 2007, to August 9, 2007)

In This Issue
Economy in Perspective
Housing Haikus …
Inflation and Prices
June Price Statistics
Money, Financial Markets, and Monetary Policy
A Step Towards Neutral
When Did Inflation Persistence Change?
What Is the Yield Curve Telling Us?
International Markets
The Dollar’s Depreciation and Inflation
Economic Activity and Labor Markets
The Employment Situation
The Advance GDP Report
How Do Americans Spend Their Time?
Regional Activity
The Cleveland Metropolitan Statistical Area
Fourth District Employment Conditions
Banking and Financial Institutions
Foreign Banks in the United States
Business Loan Markets

1

Economic Trends is published by the Research Department of the Federal Reserve Bank of Cleveland.
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ISSN 0748-2922
2

The Economy in Perspective

Housing Haikus...
08.20.07
by Mark S. Sniderman
Global financiers
Can turn houses into gold
Till their own doors close.

Holding cash seems dense
Until margin calls require
Transparent assets.

Whose fault the defaults?
Diversification’s creed:
Spread it all around.


3

Inflation and Prices

June Price Statistics
08.13.07
by Michael F. Bryan and Brent Meyer

June Price Statistics
Percent change, last
1mo.a

3mo.a

6mo.a

12mo.

5yr.a

2006 avg.

All items

2.3

5.2

5.0

2.7

3.0

2.6

Less food and
energy

2.8

2.3

2.3

2.2

2.1

2.6

Medianb

2.5

1.9

2.5

3.0

2.6

3.6

16% trimmed
meanb

2.1

2.3

2.8

2.6

2.3

2.7

Finished
goods

2.8

5.7

6.4

3.2

3.7

1.6

Less food and
energy

3.8

2.0

2.3

1.8

1.5

2.1

Consumer prices

Producer prices

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.

CPI Component Price Change Distributions*
Weighted frequency

The Consumer Price Index (CPI) increased 2.3 percent (annualized rate) in June, moderating significantly from May’s 8.4 percent surge and bringing
the headline number under its 12-month percent
change. The CPI excluding food and energy (core
CPI) increased from 1.8 percent (annualized) in
May to 2.8 percent (annualized) in June. This
marks the first time that the core CPI has been
above the headline number since January 2007.
The same is true for the Producer Price Index (PPI),
as finished goods less food and energy increased 3.8
percent (annualized), while the headline PPI fell
2.8 percent (annualized).
An investigation into the distribution of retail price
changes is also suggestive of a downswing in the
underlying trajectory of inflation. Only 44 percent
of the components included in the overall CPI rose
at a rate exceeding 3 percent in June, compared
with 52 percent on average over the last 12 months.
On the other side of the distribution, 39 percent of
CPI components grew less than 1 percent for the
month. During the 12 previous months, roughly
30 percent of the index’s components grew less
than 1 percent.

45
Average annualized monthly percent change, last 12 months
40

1-month annualized percent change

35
30
25
20
15
10
5
0
<0

0 to 1

1 to 2

2 to 3

3 to 4

4 to 5

>5

*Owner’s equivalent rent is divided into four regional subcomponents (Northeast,
Midwest, South, and West).
Source: U.S. Department of Labor, Bureau of Labor Statistics.

The longer-run trend in inflation, as measured by
the 12-month percent change in the CPI, core
CPI, and the 16% trimmed-mean CPI, remained
between 2¼ percent and 2¾ percent. The median
CPI, which tracks the price movements of the
middle component in the monthly price distribution, continues to decline, but at 3.0 percent (annualized) it is still above its five-year average of 2.6
percent. Inflation in core service prices continued
to stay in the 3 percent to 4 percent range, while
core goods (commodities less food and energy commodities) have been trending down since the third
quarter of 2006 and are now 0.8 percent below last
year’s level.
July’s average household expectations for short-run
inflation held steady at 4.2 percent. Longer-term (5
4

to 10 years out) expectations have been holding just
above the 10-year average of 3.4 percent since April
and stand a 3.6 currently.

CPI, Core CPI, and
Trimmed-Mean CPI Measures
12-month percent change
4.75
4.50
4.25
Median CPI a
4.00
CPI
3.75
3.50
3.25
3.00
2.75
2.50
2.25
2.00
1.75
1.50
Core CPI
1.25
16% trimmed-mean CPI a
1.00
1995
1997
1999
2001
2003
2005

Professional forecasters (Blue Chip Panel of economists) predict that headline inflation will moderate
over the short to medium term. Toward the end of
2008, the Blue Chip forecast has CPI inflation just
north of 2 percent.

2007

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

Core CPI Goods and Core CPI Services
12-month percent change
8.0
7.0
6.0
5.0
4.0
3.0
2.0
1.0
0.0
-1.0
-2.0
-3.0
1-month annualized
-4.0
percent change
-5.0
-6.0
1995
1997
1999

CPI and Forecasts
Annualized quarterly percent change
7.0

1-month annualized
percent change
Core services

6.0

Forecast
Actual

5.0
Top 10 forecast

4.0
3.0
2.0
1.0

Bottom 10 forecast

0.0
-1.0
Core goods

2001

2003

2005

-2.0

2007

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

-3.0
3/06

9/06

3/07

9/07

3/08

9/08

Source: Blue Chip panel of economists, August 10, 2007.

Household Inflation Expectations*
12-month percent change
6.0
5.5

One year ahead

5.0
4.5

Five to 10 years ahead

4.0
3.5
3.0
2.5
2.0
1.5
1.0
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
*Mean expected change as measured by the University of Michigan’s Survey of
Consumers.
Source: University of Michigan.

5

Money, Financial Markets, and Monetary Policy

A Step Toward Neutral
08.08.07
by Charles T. Carlstrom and Bethany Tinlin

Reserve Market Rates
Percent
8
Effective federal funds rate

7

a

6
5
Primary credit rate

4

b

3
2
1

b
Discount rate
0
2000 2001 2002

Intended federal funds rate
2003

2004

2005

2006

b

2007

a. Weekly average of daily figures.
b. Daily observations.
Sources: Board of Governors of the Federal Reserve System, “Selected Interest
Rates,” Federal Reserve Statistical Releases, H.15.

Implied Probabilities of Alternative
Target Federal Funds Rates,
September Meeting Outcome*
Implied probability
1.0

5.25%

0.9
0.8
0.7
0.6
0.5

New home sales, durable goods

4.75%

FOMC meeting

0.4
0.3

4.50%

0.2

5.00%

0.1
0.0
5/04

5/14

5/24

6/03

5.50%

6/13

6/23

7/03

7/13

7/23

*Probabilities are calculated using trading-day closing prices from options on
federal funds futures that trade on the Chicago Board of Trade.
Sources: Chicago Board of Trade; and Bloomberg Financial Services.

8/02

The Federal Open Market Committee kept rates
unchanged at the August 7 meeting; the federal
funds rate has remained at 5.25 percent since July
2006. While the committee did not change rates, it
changed the postmeeting statement to acknowledge
that “Financial markets have been volatile in recent
weeks, credit conditions have become tighter for
some households and businesses, and the housing
correction is ongoing.” Still, the committee maintained that growth is likely to continue at a moderate pace, citing “solid growth in employment and
incomes” and “a robust global economy” in support
of that view.
The committee acknowledged an increase in the
downside risks to growth while maintaining that its
“predominant policy concern remains the risk that
inflation will fail to moderate as expected.” While
the increased discussion of the downside risks to
growth was seen by many as a step toward neutral,
the implied probability of a rate cut in either September or October actually fell slightly following
the meeting. These declines occurred as the probability of no change in both September and October increased.
Judging from the behavior of implied probabilities
of federal funds futures, the market had already
factored in a possible change in the statement language, since in the weeks leading up to the FOMC
meeting, the probability of a rate cut increased.
On July 26 the probability that the fed would cut
rates in September increased 15 percent, sparked by
a particularly disappointing release on new home
sales. June new home sales were down 22 percent
from June 2006 and 6.6 percent from the previous month. Markets now place nearly a 40 percent
probability on the possibility that the Fed will cut
rates by the October meeting.
The volatility of financial markets was mentioned
in the statement, after the S&P 500 fell almost 6
percent in the slightly over two-week period lead6

ing up to the meeting. This decline was primarily
influenced by concerns about subprime failures and
credit-risk repricing. While the market has undeniably been volatile on a daily basis over the past two
weeks, this volatility rapidly disappears when the
market is averaged over even a weekly basis. On a
weekly basis, the current volatility in the S&P 500
is not particularly different from the movement of
the market over the last several years.

Implied Probabilities of Alternative
Target Federal Funds Rates,
October Meeting Outcome*
Implied probability
1.0
5.25%

0.9
0.8
0.7
0.6

New home sales, durable goods

0.5

FOMC meeting

0.4
0.3 4.50%
0.2

5.75%
5.50%

5.00%

0.1
0.0
6/04

6/11

6/18

4.75%

6/25

7/02

7/09

7/16

7/23

7/30

8/06

Probabilities are calculated using trading-day closing prices from options on federal
funds futures that trade on the Chicago Board of Trade.
Sources: Chicago Board of Trade; and Bloomberg Financial Services.

Nevertheless, the market bears watching in light of
the drop over the last couple of weeks. Large drops
in the stock market are correlated with oncoming
recessions. As it now stands, the declines have only
reversed the gains the market had achieved over the
previous two months. However, if these declines
were to continue, concerns about a future recession
may increase.

S&P 500

S&P 500*

Index, daily

Year-over-year percent change
60

1600

50
40

1550

30
20

1500

10
0

1450

-10
1400

-20
-30

1350

-40
-50

1300

1965

March

April

May

June

July

1970

1975 1980

1985

1990

1995

2000

2005

August
*Monthly average of daily data.
Sources: Wall Street Journal; and National Bureau of Economic Research.

Source: Bloomberg Information Services.

S&P 500
Index, weekly average
1600
1500
1400
1300
1200
1100
1000
900
800
700
2000

2001

2002

2003

2004

2005

2006

2007

Source: Bloomberg Information Services.

7

Money, Financial Markets, and Monetary Policy

When Did Inflation Persistence Change?
07.27.07
by Charles T. Carlstrom and Bethany Tinlin

Inflation Persistence Assuming
Constant Long-Term Inflation*
Coefficient
1.4
1.2
1.0
0.8
0.6
0.4

+/- Standard error

0.2
0.0
-0.2
1970 1974 1978 1982 1986 1990 1994 1998 2002 2006
*Inflation is based on core PCE using unfiltered data. The coefficients are calculated using 10-year rolling regressions of inflation on the output gap and 4-quarter
lags of inflation. Inflation persistence is defined as the sum of the 4-quarter lag
coefficients.
Sources: Bureau of Economic Analysis, the Congressional Budget Office, and
authors’ calculations.

Output Gap Coefficient Assuming
Constant Long-Term Inflation*
Coefficient
0.4
+/- Standard error
0.3
0.2
0.1
0.0
-0.1
-0.2
-0.3
1970 1974 1978 1982 1986 1990 1994 1998 2002 2006
*The output gap is defined as the natural log of real gross domestic product less the
natural log of potential gross domestic product, taken from the Congressional Budget
Office. The output gap coefficients are calculated using 10-year rolling regressions of
unfiltered inflation on the output gap and 4-quarter lags of inflation.
Sources: Bureau of Economic Analysis, the Congressional Budget Office, and authors’
calculations.

Policymakers and academics have noticed that the
inflation process in the United States and other
countries has changed markedly. Two formerly
characteristic features of the process have been deviating from their historical norms. First, inflation
persistence—the degree to which current inflation
depends on past inflation—appears to have declined. Second, the relationship between current
inflation and the output gap has also fallen. (The
output gap is the percent by which actual output
deviates from its potential.)
The timing of this decline suggests that something
else may be going on. Before 2000, every percentage point in the previous year’s inflation was associated with almost a 1 percentage point increase in
current inflation. Six quarters later, that number
had fallen to 0.4. This roughly coincides with the
period of time in which the decline in inflation that
had been occurring more or less steadily since the
early 1990s had abated and leveled off.
To the extent that the steady decline in inflation
until 2000 reflected a lowering of the Fed’s implicit
long-run inflation target, the timing of the change
in inflation persistence may be mismeasured. A
sustained decrease in long-term inflation would
artificially increase measured inflation persistence
since it would be picking up the declining trend
in long-term inflation. Thus, the actual decline in
inflation persistence may have occurred much earlier. Survey data also suggest that over this period of
time, professional forecasters were expecting inflation over the next 10 years to fall.
To correct for this effect we need some measure of
long-run inflation. Unfortunately, the Fed’s implicit
long-term inflation target is not directly observable.
We address this problem by smoothing the data.
By smoothing the data, we are left with a measure
of the underlying trend in inflation. This gives us a
reasonable measure of long-term inflation.
By filtering out the high frequency (e.g., quarterly
8

Core PCE
1-quarter percent change annualized
8
7
6
5
4
3
2
1
0
1983

1986

1989

1992

1995

1998

2001

2004

2007

Source: Bureau of Economic Analysis.

Hoey and SPF Inflation Expectations
Percent
10
9
8
7

Hoey

6

and annual movements) we have a relationship
that best captures whether inflation persistence
would be declining in a period where long-term
inflation is constant, as appears to be true during
the current period. We also have a better measure
of how the output gap affects inflation in such an
environment. While the current decline in inflation
persistence is historically unusual, the decline in the
gap-inflation trade-off does not seem unusual. This
coefficient has declined but the decline is modest
and its current value is not low by historical standards. The impact of the output gap on inflation is
currently (and is typically) very small.
Comparing our estimates of inflation persistence
and the inflation-gap relationship for both the raw
inflation data (“constant long-run inflation”) and
where the monetary authority’s implicit long-term
inflation target changes over time (“variable longterm inflation”), we see some interesting differences. The decline in inflation persistence is more
pronounced and has been pushed back to around
1990.

5
4
SPF

3
2
1
0

1978 1981 1984 1987 1990 1993 1996 1999 2002 2005
Sources: Survey of Professional Forecasters and the Hoey Survey.

Core PCE and Trend Inflation

Note that since these are 10-year rolling windows,
any possible change that may have led to the
decline in inflation persistence could conceivably
have occurred anywhere between 1980 and 1990.
Two obvious suspects, both of which occurred in
the early 1980s, come to mind: the sharp decline
in output variability (the so-called “Great Moderation”) and the change in the central bank’s operating procedure. Since 1983 the operating procedure
has de-emphasized monetary targets and reacted
much more aggressively to control inflation than it
did in earlier periods.

1-quarter percent change annualized
12
10
8

Core PCE
Trend (long-term) inflation

a

6
4
2
0
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005
a. Data is detrended using an HP filter, lambda = 1600.
Sources: Bureau of Economic Analysis and the Congressional Budget Office.

9

Inflation Persistence Assuming
Variable Long-Term Inflation*

Output Gap Assuming
Variable Long-Term Inflation*

Coefficient
1.2

Coefficient
0.3

1.0
0.2

0.8
0.6

0.1

0.4
0.2

0.0

0.0
-0.1

-0.2
-0.4

+/- Standard error

+/- Standard error
-0.2

-0.6
-0.8
1970 1974 1978 1982 1986 1990 1994 1998 2002 2006

-0.3
1970 1974 1978 1982 1986 1990 1994 1998 2002 2006

*Variable long-term inflation is based on core PCE using HP-filtered data (lambda =
1600). The coefficients are calculated using 10-year rolling regressions of inflation on
the output gap and 4-quarter lags of inflation. Inflation persistence is defined as the
sum of the 4-quarter lag coefficients.
Sources: Bureau of Economic Analysis, the Congressional Budget Office, and
authors’ calculations.

*The output gap is defined as the natural log of real gross domestic product less the
natural log of potential gross domestic product, taken from the Congressional Budget
Office. The output gap coefficients are calculated using 10-year rolling regressions of
HP-filtered inflation (lambda = 1600) on the output gap and 4-quarter lags of inflation.
Sources: Bureau of Economic Analysis, the Congressional Budget Office, and
authors’ calculations.

Inflation Persistence

Output Gap

Coefficient
1.2

Coefficient
0.30

Constant long-term inflationa

1.0

0.25

0.8

0.20

Output gap using constant long-term inflationa

0.15

0.6

0.10
0.4
0.2

Variable long-term inflationa,b

0.05
0.00

0.0

-0.05

-0.2

-0.10

-0.4
1970 1974 1978 1982 1986 1990 1994 1998 2002 2006

Gap using variable long-term inflationa,b
-0.15
1970 1974 1978 1982 1986 1990 1994 1998 2002 2006

a. Inflation is based on detrended core PCE.
b. Inflation is detrended using the HP filter (lambda = 1600).
Note: The coefficients are calculated using 10-year rolling regressions of inflation on
the output gap and 4-quarter lags of inflation. Inflation persistence is defined as the
sum of the 4-quarter lag coefficients.
Sources: Bureau of Economic Analysis, the Congressional Budget Office, and
authors’ calculations.

a. Inflation is based on the core PCE.
b. Inflation is detrended using the HP filter (lambda =1600).
Note: The output gap is defined as the natural log of real gross domestic product less
the natural log of potential gross domestic product, taken from the Congressional
Budget Office. The output gap coefficients are calculated using 10-year rolling regressions of inflation on the output gap and 4-quarter lags of inflation.
Sources: Bureau of Economic Analysis, the Congressional Budget Office, and authors’
calculations.

10

Money, Financial Markets, and Monetary Policy

What Is the Yield Curve Telling Us?
Yield Spread and Real GDP Growth*
Percent
12
Real GDP growth
(year-to-year percent change)

10
8
6
4
2
0
-2
-4
1953

Yield spread:
10-year Treasury note minus 3-month Treasury bill
1963

1973

1983

1993

2003

*Shaded bars indicate recessions.
Sources: U.S. Department of Commerce, Bureau of Economic Analysis; and
Board of Governors of the Federal Reserve System.

Yield Spread and
Lagged Real GDP Growth
Percent
12
One-year-lagged real GDP growth
(year-to-year percent change)

10
8
6
4
2
0
-2
-4
1953

Yield spread:
10-year Treasury note minus 3-month Treasury bill
1963

1973

1983

1993

2003

Sources: U.S. Department of Commerce, Bureau of Economic Analysis;
and Board of Governors of the Federal Reserve System.

Predicted GDP Growth
and the Yield Spread
Percent
6
5

Real GDP growth
(year-to-year percent change)

4
Predicted
GDP growth

3
2
1
0
Yield spread: 10-year Treasury note
minus the 3-month Treasury bill

-1
-2
3/02

3/03

3/04

3/05

3/06

3/07

3/08

Sources: U.S. Department of Commerce, Bureau of Economic Analysis; the
Board of Governors of the Federal Reserve System; and authors’ calculations.

07.18.07
by Joseph G. Haubrich and Brent Meyer
Since last month, the yield curve has flattened,
with short rates rising and long rates falling. Even
so, long rates remain higher than short rates, and
the movement was not enough to return the curve
to inversion. One reason for noting this is that the
slope of the yield curve has achieved some notoriety
as a simple 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 had been giving a rather pessimistic
view of economic growth for a while, but with the
inversion gone, this view is less pronounced. The
spread has turned positive, with the 10-year rate at
5.10 percent and the 3-month rate at 4.96 percent
(both for the week ending July 13). The spread
stands at 14 basis points, down considerably from
June’s 54 basis points, but still well above May’s
negative 23 basis points. Projecting forward using
past values of the spread and GDP growth suggests
that real GDP will grow at about a 2.3 percent rate
over the next year. This prediction is on the low
side of other forecasts, in part because the quarterly
average spread used here remains negative.
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.
11

Probability of Recession Based on the
Yield Spread*
Percent
100

Looking at that relationship, the expected chance of
a recession in the next year is 24 percent, up from
June’s 15 percent, but still down from May’s value
of 35 percent and April’s 38 percent.

90
80
70
60
50
40

Forecast

Probability
of recession

30
20
10
0
1960

1966

1972

1978

1984

1990

1996

2002

2008

*Estimated using probit model. Shaded bars indicate recessions.
Sources: U.S. Department of Commerce, Bureau of Economic Analysis; Board of
Governors of the Federal Reserve System; and authors’ 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

The Dollar’s Depreciation and Inflation
08.07.07
By Owen F. Humpage and Michael Shenk

Foreign Exchange Indexes

Factors underlying the dollar’s depreciation may be
changing in a manner that could put upward pressure on U.S. prices, should they continue. Nevertheless, dollar depreciations do not cause inflation.
Inflation is a purely home-grown, monetary phenomenon.

Index, February 2002 = 100
110
Other
105
100
95
Broad
90
85
80
Major

75
70
65
2002

2003

2004

2005

2006

Source: Board of Governors of the Federal Reserve System.

2007

Since early February 2002, the U.S. dollar has
depreciated nearly 31 percent on a trade-weighted
basis against the currencies of the major industrialized countries and has also depreciated more than
6 percent on a similar basis against the currencies
of key developing countries. On a real basis—that
is, after controlling for the effects of domestic and
foreign inflation—the dollar has depreciated nearly
26 percent against the major industrialized countries’ currencies and almost 7 percent against the
key developing countries’ currencies.
12

Current Account Deficit*
Billions of U.S. dollars

Percent of GDP
1

100
0

0

–100

–1

–200

–2

–300

–3

–400

–4

–500

–5

–600

–6

–700

–7

–800

–8
–9

–900
1980 1983 1986 1989 1992 1995 1998 2001 2004 2007

*2007 data points are annualized first-quarter data.
Sources: U.S. Department of Commerce, Bureau of Economic Analysis; Haver Analytics.

Net International Investment Position
Billions of U.S. dollars
1500

Percent of GDP
15

1000

10

500

5
0

0
–500

–5

–1,000

–10

–1,500

–15

–2,000

–20

–2,500

–25

–3,000

–30

–3,500

–35

–4,000
1980 1983 1986 1989 1992 1995 1998 2001 2004

–40

Sources: Bureau of Economic Analysis; Haver Analytics.

Key Policy Rates
Percent
7
6

FOMC
Bank of England

5
4
3

European
Central
Bank

2
1

Bank of Japan a

0

2000

2001

2002

2003

2004

2005

2006

2007

a: Daily data until 3/9/2006.
Sources: Board of Governors of the Federal Reserve System, “Selected Interest
Rates,” Federal Reserve Statistical Releases, H.15; The Bank of England; The
Bank of Japan; The European Central Bank; and Bloomberg Financial Information
services.

Economists have always found explaining movements in exchange rates difficult, even in hindsight,
but comparing movements in the dollar with broad
changes in the current-account deficit can provide
some insight. Between early 2002 and late 2005,
the dollar depreciated as the current-account deficit
widened, suggesting that an expansion of U.S.
aggregate demand motivated both events. U.S. economic growth at the time was not obviously faster
than economic growth elsewhere across the globe,
but between mid-2003 and late 2005, U.S. output
converged on, and eventually surpassed, potential
output quicker than was generally the case abroad.
Americans consumed and invested more than they
produced domestically. A small part of the dollar’s
depreciation against the currencies of the major industrialized countries reflected a slightly higher rate
of inflation in the United States than in many other
large industrialized countries. At best, this seems to
explain only about 5 percentage points of the overall depreciation against our large trading partners;
it describes none of the dollar’s depreciation against
the key developing countries.
Last year, however, the situation seemed to change.
The dollar continued to depreciate, but the current-account deficit narrowed from a record 6.8
percent of GDP in the fourth quarter of 2005 to
5.7 percent of GDP in the first quarter of 2007.
This pattern of exchange-rate and current-account
movements, along with myriad anecdotal reports,
tentatively suggests that foreign investors are becoming somewhat reluctant to acquire U.S. financial claims, although they are not outright dumping
dollars.
Many analysts have been anticipating such a
development. The United States has financed its
persistent string of current account deficits by issuing financial claims to the rest of the world. As a
consequence of this process, the world now holds
financial claims amounting to $3.5 trillion against
the United States, or 26 percent of our GDP. (Our
negative net international investment position
measures this.) Economists have long argued that
the stock of outstanding financial claims could not
grow continuously relative GDP (a comparison
which indicates our ability to service and repay
the claims). At some point, they argued, foreigners
13

Exchange Rate and
Relative Import Prices
Index, January 1997 = 100

Index, 2000 = 100
120

130
125

Nominal
broad dollar index

120
115
110

116
112
108
104

Nonpetroleum
import price index a

105

100

100
96
1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
a. Nonpetroleum import price index divided by CPI less food and energy.
Sources: U.S. Department of Labor, Bureau of Labor Statistics; Board of Governors
of the Federal Reserve System.

Exchange Rates and
Relative Export Prices
Index, January 1997 = 100

Index, 2000 = 100

130
125

120

Nominal
broad dollar index

116

120

112

115

108

110

104
Export price index a

105

100

100
96
1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
a. Export price index divided by CPI.
Sources: U.S. Department of Labor, Bureau of Labor Statistics; Board of Governors
of the Federal Reserve System.

would become reluctant to add dollar-denominated
assets to their portfolios. When this point was
reached—and economists did not know when that
might be—the dollar would depreciation and real
interest rates in the United States might also rise to
coax foreigners into holding additional dollar-denominated assets. The broad-based dollar depreciation since late 2005 is certainly consistent with this
story.
The relative thrust of U.S. and foreign monetary
policies may be encouraging international investors
to diversify. Since June 2006, the FOMC has kept
the federal funds target rate at 5.25 percent, while
other key central banks have tightened. Markets
do not expect the Federal Reserve to change policy
anytime soon, but the chances are better than not
that other central banks will move their key policy
rates upward.
A dollar depreciation exerts upward pressure on
U.S. prices through a couple of different channels,
but how a depreciation affects the overall inflation
rate depends on the stance of U.S. monetary policy.
Inflation is, after all, purely a monetary phenomenon. A dollar depreciation lowers the foreign-currency prices of U.S. made goods and services, making our exports more attractive to foreigners. The
resulting increase in foreign demand for U.S.–made
traded goods raises their dollar prices. Similarly,
a dollar depreciation increases the dollar prices of
foreign-made goods and services. Many of these are
consumer goods, and as their prices rise, U.S. consumers look for domestic substitutes, thereby also
putting upward pressure on the prices of domestically produced alternatives. In addition, to the extent that imported goods enter into the production
of domestically made goods and services, the dollar
depreciation will raise the costs of domestic production. The bottom line is that a dollar depreciation
will raise the relative price of all traded goods and
any nontrade substitutes in this country, as well as
domestic goods with a high import component in
their manufacture. But this is not inflationary.
As long as U.S. monetary authorities have not
caused the dollar depreciation because of an excessively easy monetary policy, and as long as U.S.
monetary policymakers do not subsequently ac14

commodate a dollar depreciation with an easier
monetary policy, the price effects of a dollar depreciation will not lead to a general inflation in the
United States . The dollar depreciation from 2002
through 2005 appears to have been a response to
U.S. developments, including the stance of U.S.
monetary policy. Import prices advanced apace
with prices overall, and relative export prices rose
only a bit faster than the consumer price index.
The depreciation over the last year, however, seems
foreign in origin. It has not had a price impact as
of yet, but should it continue, this foreign-sourced
dollar depreciation could complicate the conduct
of monetary policy as it shifts worldwide demand
towards the United States, but it will not cause
inflation. That depends of the FOMC.

Economic Activity and Labor

The Employment Situation
08.07.07
By Yoonsoo Lee and Cara Stepanczuk

Labor Market Conditions
Average monthly change
(thousands of employees, NAICS)
2004

2005

2006

Jan-Jun
2007

July
2007

Payroll employment

172

212

189

144

92

Goods-producing

28

32

9

−14

−12

Construction

26

35

11

−4

−12

Manufacturing

0

−7

−7

−13

−2

Durable goods

8

2

0

−12

3

Nondurable goods

−9

−9

−6

−1

−5

Service-providing

144

180

179

157

104

Retail trade

16

19

−3

10

−1

Financial activitiesa

8

14

16

4

27

PBSb

38

57

42

18

26

Temporary help svcs.
Education and health
svcs.
Leisure and hospitality
Government

11

18

−1

−8

−7

33

36

41

49

39

25

23

38

33

22

14

14

20

24

−28

Average for period (percent)
Civilian unemployment rate

5.5

5.1

4.6

4.5

4.6

a.Financial activities include the finance, insurance, and real estate sector and the
rental and leasing sector.
b. 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: U.S. Department of Labor, Bureau of Labor Statistics.

Nonfarm payrolls grew by 92,000 jobs in July—
slower than expected and below the average monthly increase reported during the first six months of
2007 (144,000). A nominal loss in the goods-producing sector trimmed 12,000 jobs from the total,
while the service-providing sector added 104,000
to it. Changes were more muted in both sectors this
past month than the monthly average in 2007; on
average the goods-producing sector has dropped
13,300 jobs each month this year, and the serviceproviding sector has added an average 149,700.
Although employment growth has been moderating, the labor market remains firm: The monthly
unemployment rate (4.6 percent) is similar to its
average during the first half of 2007, and except for
government, which experienced large employment
declines, most sectors’ employment grew in July at
about the same rates as in recent months.
A drop of 28,000 in government payrolls accounted for some of the weakness in the report; it
was the first loss for the sector since January 2006
(−34,000). More than half of the drop was due to
a decline in local government education. Employment in temporary help services is often used as an
indicator of business confidence and overall de15

Average Monthly
Nonfarm Employment Change
Change, thousands of workers
300
270

Revised
Previous estimate

240
210
180
150
120
90
60
30
0
2004 2005 2006 2007 IIIQ IVQ IQ IIQ May Jun Jul
2006
2007

mand conditions for labor, as businesses can adjust
to new conditions by changing their orders for
temporary workers. While the decline in temporary
help services may be an indication of softening employment, the magnitude of the change is about the
same as in recent months. In contrast, other parts
of the service-providing sector remained solid and
mostly on par with recent months: Education and
health services added 39,000 jobs, financial activities added 27,000, and professional and business
services added 26,000. Financial activity, boosted
by credit intermediation and related activities
(+11,000), experienced its strongest payroll increase
since September 2006.

Source: Department of Labor, Bureau of Labor Statistics.

The loss of goods-producing jobs was held to
12,000 in July. Construction, which lost 12,000
jobs, contributed most of the losses to this sector.
July’s construction payroll reduction also exceeds
the industry’s average monthly payroll change since
the start of 2007 (−4,000). However, the employment losses in this sector remain relatively small
compared to the sharp contraction recently observed in homebuilding activity. Since last August,
employment in construction has declined less than
1 percent. During the same period, total housing starts declined 30.4 percent. If these differing
trends reflect the lagged adjustment of employment
to slowing activity in this sector, overall employment growth in the coming months may decline
further. The loss of manufacturing jobs, which
numbered only 2,000, was well above the manufacturing industry’s average monthly loss of 13,000
jobs so far in 2007.

Economic Activity and Labor

16

The Advance GDP Report
08.06.07
by Tim Dunne and Brent Meyer

Real GDP and Components 2007:IIQ

Annualized percent
change, last:
Change,
billions of 2000$
Real GDP

Quarter

Four
quarters

95.3

3.4

1.8

25.7

1.3

2.9

Durables

5.0

1.6

5.0

Nondurables

−4.8

−0.8

2.4

Services

25.2

2.2

2.7

25.9

8.1

3.4

Personal consumption

Business fixed investment
Equipment

5.9

2.3

0.1

Structures

14.5

22.2

11.5

Residential investment

−12.1

−9.2

−15.9

Government spending

20.9

4.3

2.0

National defense

11.2

9.4

3.0

Net exports

34.2

Exports

21.2

6.4

6.8

Imports

−13.1

−2.6

2.0

Change in business inventories

3.5

Source: Bureau of Economic Analysis.

Annualized quarterly percent change
6
Final estimate
Advance estimate
Blue Chip forecast
5
4
3
2
1
0
IIQ IIIQ IVQ IQ
2006

Looking at the contribution of individual components to the percent change in real GDP, we see
that business fixed investment added 0.8 percent to
real GDP growth, doubling its average contribution of 0.4 percent over the last four quarters. Also,
the free fall in residential fixed investment abated
somewhat, and this component took away only 0.5
percentage point of growth, compared to 0.9 over
the last four quarters. Exports grew in the second
quarter almost as strongly as they had over the past
year, adding 0.7 percentage point; and imports actually fell for the first time since 2003, boosting real
GDP growth by one-half of a percentage point.
Real GDP growth for the second quarter came in
slightly above expectations and its 30-year average
of 3.2 percent. The July 10 Blue Chip forecast had
predicted second-quarter growth of 3.0 percent.
Looking ahead to the next four quarters, expectations are for growth to average 2.8 percent.

Real GDP Growth

IIQ IIIQ IVQ IQ
2005

Real Gross Domestic Product (GDP) grew at a 3.4
percent annual rate in the second quarter of 2007,
according to the advance estimate released by the
Bureau of Economic Analysis (BEA). The acceleration from first quarter’s four-year low (0.6 percent)
reflected strong increases in private nonresidential
investment and exports, a decline in imports, and
some slowing in the recent losses in residential
fixed investment. A decrease in personal consumption expenditures in the second quarter—from 3.7
percent to 1.3 percent—partly offset the gains seen
in the other components. The decrease in personal
consumption expenditures was primarily due to a
drop in demand for durable and nondurable goods,
which fell from 8.8 percent to 1.3 percent and 3.0
percent to −0.8 percent, respectively.

IIQ IIIQ IVQ IQ IIQ
2007
2008

It is important to note that the most recent data
are from the advance estimate and are subject to
further revisions that may significantly change our
current perceptions. Not only does the BEA revise
current data, once a year (usually in July) it also
“benchmarks” historical data to “incorporate newly

Sources: Blue Chip Economic Indicators, July 2007; Bureau of Economic Analysis.

17

available and more comprehensive source data, as
well as improve estimating methodologies.” The
most recent benchmark revised the data back to
2004, considerably changing what we thought we
knew about the economy over the past few years.

Contribution to
Percent Change in Real GDP
Percentage points
4
3
2
1
0
-1

Last four quarters
2007:IQ
2007:IIQ

The estimates were almost exclusively revised down.
In fact, the estimate for the average annualized percent change of real GDP in 2004 was revised down
to 2.7 percent from 3.0 percent. The revisions were
just as striking for personal consumtion expenditures and private fixed investment. Annualized
average growth of personal consumption expenditures dropped to 3.3 percent from 3.6 percent,
and private fixed investment dropped from 3.6 to
3.2 on average. An implication of these downward
revisions in real GDP growth is that productivity
growth may not have been as robust as previously
thought. However, the revisions to the productivity growth series will also depend upon upcoming
revisions that the BLS makes to the payroll series. If
payrolls are also revised downward, then the net effect on the productivity numbers remains uncertain.

Business
fixed
investment
Imports

Change in
inventories
Personal
consumption

Exports

Government
spending

Residential
investment

-2
Source: Bureau of Economic Analysis.

Revisions to Real GDP Growth
Annualized quarterly percent change
6

Benchmarked
Vintage

5
4
3
Economic
Activity and Labor
2

1. ATUS data are collected for all segments of the population 15 and
older for weekdays as well as weekends and holidays. Hence, an average day measures the average time allocation across all persons
and days.

1
0
IQ IIQ IIIQ IVQ IQ IIQ IIIQ IVQ IQ IIQ IIIQ IVQ IQ
2007
2004
2005
2006
Source: Bureau of Economic Analysis.

Revisions to Real
Private Fixed Investment

Revisions to
Real Personal Consumption Expenditures

Annualized quarterly percent change

Annualized quarterly percent change
6

15
Benchmarked
Vintage

10

5
Benchmarked
4

5

3

0

Vintage
2

-5
1
-10
IQ IIQ IIIQ IVQ IQ IIQ IIIQ IVQ IQ IIQ IIIQ IVQ IQ
2007
2004
2006
2005
Source: Bureau of Economic Analysis.

0
IQ IIQ IIIQ IVQ
2004

IQ IIQ IIIQ IVQ IQ IIQ IIIQ IVQ IQ
2007
2006
2005

Source: Bureau of Economic Analysis.

18

How Do Americans Spend Their Time?
07.31.07
by Murat Tasci and Laura Kleinhenz

Time Spent in Primary Activities, 2006*
Sleeping
(8.63 hours)

Working
(3.75 hours)
Other
(2.77 hours)

Caring for others
(0.74 hours)
Eating and drinking
(1.23 hours)
Household activities
(1.79 hours)
Leisure and sports
(5.09 hours)
*Time is a daily average, and a primary activity is an individual's main activity.
Other activities done simultaneously are not included.
Note: Data refer to civilians 16 years and over. All major activity categories
include related travel time.
Source: Bureau of Labor Statistics.

Time Use on Average Work Day
for Employed People Aged 25
to 54 with Children
Working
(8.0 hours)

Other
(2.5 hours)
Eating and drinking
(1.1 hours)
Household activities
(1.0 hour)

Leisure and sports
(2.6 hours)

Sleeping
(7.6 hours)

Note: Data include employed persons ages 25 to 54 who lived in
households with children under 18. Data include nonholiday
weekdays and are annual averages for 2005.
Source: Bureau of Labor Statistics.

The American Time Use Survey (ATUS), which has
been sponsored by the Bureau of Labor Statistics
and conducted by the U.S. Census Bureau since
2003, provides information about how people in
the United States spend their time on an average
day.1 By including valuable information about what
activities people do during the day and how much
time they spend doing each, the survey creates a
larger picture of employment. For instance, on an
average day in 2006, people spent 3.40 hours working. However, only about 45 percent of the entire
population (51 percent of men and 39 percent of
women) worked on an average day. Among the
civilian population, the average daily number of
work hours was 7.59 (8.04 hours for men and 7.04
for women).
Not surprisingly, sleeping was the most time-consuming daily activity for the civilian population as
a whole. Leisure and sports came next, with 5.09
hours; much of their leisure time was spent watching television (about 2.58 hours a day).
It is important to recognize that time allocation
can differ significantly among subgroups within
the civilian population. Consider, for instance, that
the average workday for employed adults aged 25
to 54 with children was eight hours in 2005. This
subgroup used significantly less time for sleeping
(7.6 hours) and leisure (2.6 hours) than the civilian
population as a whole, seemingly to compensate for
the extra hours spent working.
ATUS data also provide information about the timing and location of certain activities. For instance,
we can see how many people work on weekends or
at home. It turns out that in 2003–05, about 32
percent of employed people worked on an average
weekend day. Among those holding more than one
job, 57 percent worked weekends. More interestingly, 18 percent of single-job holders aged 15 and
older worked at home on the average work day. For
multiple-job holders, this proportion is 32 percent.
The proportions working at home are higher for
19

self-employed workers (47 percent) and those with
a bachelor’s degree or higher (33 percent).

Percent of Employed Persons Who Worked
at Home on an Average Workday, 2003–05
Percent
60
Number of jobs
held
50

Class of worker

Education level

40
30
20
10
0

Some
Single-job Multiple-job Self- Wage and Less than High
holders employed salary high school school college
holders
workers workers
diploma diploma
only

Bachelor's
degree or
higher

Note: Data include all employed persons age 25 and over on days they
worked. Data include all days of the week and are an average for 2003–05.
Source: Bureau of Labor Statistics .

Regional Activity

The Cleveland Metropolitan Statistical Area
08.06.07
By Kyle Fee and Bob Sadowski

Location Quotients,
2006 Cleveland MSA / U.S.
Natural resources,
mining, & construction
Manufacturing
Trade, transportation, & utilities
Information
Financial activities
Professional & business services
Education & health services
Leisure & hospitality
Other services
Government

0

0.5

1

1.5

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

Payroll Employment since March 2001
Index, March 2001 = 100
105
U.S.

100
Ohio

The Cleveland metropolitan statistical area (MSA)
is located along the southern shores of Lake Erie.
Counties within the MSA include Cuyahoga,
Geauga, Lake, Lorain, and Medina. Ever since the
turn of the twentieth century, Cleveland has been
recognized as a manufacturing center, and despite
the sector’s downturn, the region retains a high
concentration of manufacturing jobs. In 2006,
Cleveland’s concentration of manufacturing employment was 31 percent higher than the nation as
a whole.
In recent years, the region has built an international
reputation as a major player in the health care
sector. Employment within the sector has grown
rapidly, to the point where health care edged past
manufacturing as Cleveland’s largest sector employer. The region’s employment concentration in
health services and education is about 22 percent
greater than is found nationally. However, the rise
in the number of health care jobs is not characteristic of the overall employment picture.

Cleveland MSA
95

90
2001

Since the employment turnaround began after the
last recession, total nonfarm employment in the
2002

2003

2004

2005

2006

2007

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

20

U.S. has grown over 6 percent. In Cleveland, by
contrast, employment growth has been flat. Decomposing the employment data into manufacturing and nonmanufacturing sectors, we see that the
U.S. outperformed the local area in both categories.
Since the last business cycle peak through 2006, the
U.S. shed 16.6 percent of its manufacturing jobs,
while Cleveland lost 23.4 percent. Likewise, in all
nonmanufacturing sectors, employment in the U.S.
rose 6.6 percent, while in Cleveland it declined 1.4
percent.

Payroll Employment since March 2001
Index, March 2001 = 100
U.S.
Cleveland MSA

Nonmanufacturing

105

95

Manufacturing
85

75
2001

2002

2003

2004

2005

2006

2007

Looking at the components of annual employment growth helps us to pinpoint why Cleveland
is lagging the nation. Manufacturing job loss is the
main culprit, especially for the 2001–2003 period. Further, in 2002, several other sectors played
significant roles in the region’s employment decline:
the financial, information, and business services
sector and retail and wholesale trade. In contrast,
the education, healthcare, leisure, government, and
other services category made a positive contribution
to employment change in each year except 2003. In
fact, this component was the major contributor to
the region’s positive growth—albeit slight—in 2005
and 2006.

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

Components of Employment Growth,
Cleveland MSA
Percent change
4

2

Retail & wholesale trade

Natural resources, mining & construction

Manufacturing

Financial, information & business services
Education, health, leisure, government & other services

Transportation,
warehousing & utilities

U.S.
0

-2

-4
2001

2002

2003

2004

2005

2006

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

Payroll Employment Growth, May 2007
U.S.
Cleveland MSA
Total nonfarm
Goods-producing
Manufacturing
Natural resources, mining, & construction
Service-providing
Trade, transportation, and utilities

Employment trends similar to those observed in
the Cleveland MSA and the United States between
2001 through 2006 continued into 2007. For the
12-month period ending in May, the U.S. reported
higher employment growth than Cleveland in all
industry sectors except natural resources, mining,
and construction. On a year-over-year basis, total
nonfarm employment in the U.S. grew by about
1.5 percent, compared to a 0.5 percent decline in
the region.

Information
Financial activities
Professional and business services
Education and health services
Leisure and hospitality
Other services
Government

-3

-2
-1
0
1
2
3
Year-over-year percent change

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

4

Prior to middle of 2003, the MSA’s unemployment
rate closely tracked the nation’s. However, since the
beginning of 2004, the unemployment rate in the
U.S. has averaged 0.6 percentage point less than is
found regionally.
In addition to Cleveland’s overall decline in employment, the region has also lost population.
Since 1970, the region’s population has declined
almost 9 percent, to 2.1 million. This compares to
7.7 percent growth in Ohio and 47 percent across
the U.S. It should be noted that Cleveland is not
21

unique among MSAs in the Fourth District in this
respect. Many regions in the district have seen their
populations remain flat or decline over the past few
decades.

Unemployment Rate
Percent
9
Cleveland MSA
8
7
6
U.S.
5
4
3
1990

1992

1994

1996

1998

2000

2002

2004

2006

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

Population
Index, 1970 = 100
150
140
U.S.
130
120
110
Ohio
100
90
1970

Cleveland MSA

1980

1990

2000

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

Selected Demographics, 2005

Between 1980 and 2000, per capita personal
income in the Cleveland metro area exceeded that
of aggregate U.S. metro areas by an average of just
over 4 percent. Part of this disparity can be attributed—at least until the recent past—to the large
number of high-paying manufacturing jobs and
Fortune 500 company headquarters in the region.
Beginning in 2001, average per capita income in
U.S. metro areas rose slightly above Cleveland’s and
has continued to do so since. In 2004, per capita
income in Cleveland was $34,078, compared to an
average of $34,688 across all U.S. metro areas.
Looking at some selected demographic statistics, we
see that the Cleveland metro area is almost on par
with the United States in terms of the percentage
of people who hold a bachelor’s degree or a higher
degree—26.6 percent and 27.2 percent, respectively, and it exceeds the state’s share by 3.3 percentage
points. The share of Cleveland’s minority population is equal to that of the United States. However,
the share of black residents in Cleveland exceeds
that of the nation by over 6 percentage points.
Other minority groups are not as well represented
in Cleveland as they are across the nation. Finally,
the median age in Cleveland is slightly higher than
in Ohio or the United States.

Cleveland, OH
MSA

Ohio

U.S.

2.1

11.2

288.4

White

76.9

85.7

74.7

Black

18.8

12.3

12.1

Other

4.3

2.0

13.2

Total population (millions)
Percent by race

Per Capita Personal Income
Thousands of dollars
40

Percent by age

U.S. metropolitan areas

0 to 19

26.9

27.0

27.8

20 to 34

17.5

19.3

20.1

35 to 64

41.8

40.8

40.0

65 or older

13.8

12.8

12.1

Percent with bachelor’s
degree or higher

26.6

23.3

27.2

Median age

39.0

37.6

36.4

30
Cleveland MSA

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

Ohio

20

10
1980

U.S.

1985

. 1990

1995

2000

2005

Source: U.S. Department of Commerce, Bureau of Economic Analysis.

22

Regional Activity

Fourth District Employment Conditions
07.18.07
by Tim Dunne and Kyle Fee

Unemployment Rates*
Percent
8
7

Fourth District a

6
5
United States
4
3
1990

1992

1994

1996

1998

2000

2002

2004

2006

a. Seasonally adjusted using the Census Bureau’s X-11 procedure.
*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.

Unemployment Rates, May 2007*
U.S. unemployment rate = 4.5%

3.5 – 4.5
4.6 – 5.5
5.6 – 6.5
6.6 – 7.5
7.6 – 8.5
8.6 – 13.5
*Data are seasonally adjusted using the Census Bureau’s X-11 procedure.
Source: U.S. Department of Labor, Bureau of Labor Statistics.

May’s employment report showed relatively stable
conditions in the Fourth District’s labor markets.
The district’s unemployment rate remained unchanged at 5.4 percent for the month, which was
a bit higher than the national unemployment rate
of 4.5 percent (also unchanged from April). While
the unemployment rate stayed constant, there were
changes in the number of workers employed, the
number unemployed, and size of the labor force.
Compared to the previous month, the District’s
employment and labor force both increased 0.1
percent; however, this was offset by a 1.3 percent
increase in the number of unemployed people. On
a year-over-year basis, the District’s labor force and
the number of people employed increased 0.8 percent and 0.7 percent, respectively, and the unemployment rate rose slightly (0.1 percent).
Of the 169 counties in the Fourth District, 18 had
an unemployment rate below the national average
and 151 had a higher rate in May. Rural Appalachian counties experienced the highest unemployment rates, with six counties having unemployment
rates above 10 percent. Pennsylvania’s labor market
continued to show the most strength, with the
Pennsylvania counties that are within the Fourth
District registering an unemployment rate of 4.4
percent. The unemployment rates of both Fourth
District Kentucky (5.4 percent) and Ohio (5.7
percent) exceeded the national rate. Unemployment
rates for the District’s major metropolitan areas
ranged from a low of 4.0 in Lexington to a high of
6.2 in Toledo.
Lexington’s employment grew at a rate of 1.9
percent on a year-over-year basis and was the only
major metropolitan area in the District to increase
employment faster than the national average of 1.4
percent. Nonfarm employment dropped in Cleveland (−0.6 percent), Toledo (−0.3 percent), and
Dayton (−1.1 percent) since last May. Employment
in goods-producing industries fell in almost all
District cities as well as nationally (−0.7 percent).
23

Cleveland, Columbus, Cincinnati, and Dayton
all lost goods-producing jobs at more than double
the national rate. Service-providing employment
fared better and increased in four of the seven
major metro areas; Lexington remained at the top
of the Fourth District with a 2.8 percent increase
in service-providing jobs. All major District metro
areas posted job gains in the education and health
services industry. The professional and business
services sector posted job gains in all major District
metro areas except for Cleveland, which contracted
0.5 percent.

Payroll Employment by Metropolitan Statistical Area
12-month percent change, May 2007
Cleveland

Columbus

Cincinnati

Dayton

Toledo

–0.6

0.3

0.3

–1.1

0.3

0.4

1.9

1.4

Goods-producing

–1.8

–1.9

–1.5

–2.8

–0.8

–0.8

0.6

–0.7

Manufacturing

–2.6

–1.4

–1.1

–3.3

–1.6

–1.2

0.0

–1.2

1.2

–2.8

–2.5

–0.7

2.0

0.5

2.4

0.0

Total Nonfarm

Natural resources, mining, construction
Service-providing

Pittsburgh Lexington

U.S.

–0.3

0.6

0.7

–0.7

0.2

0.6

2.3

1.8

Trade, transportation, and utilities

–0.6

0.4

–0.1

–3.3

0.2

–0.3

–1.3

0.9

Information

0.5

–2.6

–2.5

1.0

5.0

–0.9

6.5

1.7

Financial activities

–0.8

–0.8

–1.1

1.0

–0.8

–1.7

2.8

1.0

Professional and business services

–0.5

2.0

0.7

0.2

1.5

1.5

1.3

2.2

Education and health services

0.6

1.6

3.6

0.2

0.4

2.2

1.9

3.0

Leisure and hospitality

0.0

2.4

1.4

0.3

–0.9

0.2

5.6

3.4

Other services

0.7

–1.1

1.2

–0.6

–1.3

–0.7

–1.0

0.9

Government

–1.1

–0.4

–0.6

–1.1

–1.9

0.8

4.9

1.3

5.7

4.8

5.0

6.1

6.2

4.2

4.0

4.5

May unemployment rate
(seasonally adjusted, percent)

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

24

Banking and Financial Institutions

Foreign Banks in the United States
08.06.07
by James Thomson and Cara Stepanczuk

Assets of Domestic and
Foreign Banks in the U.S.*
Billions of dollars
10,000
9,000

Domestic a
Foreign b

Percent of total
40
37

8,000

34

7,000

31

6,000
5,000
4,000

28
Share of
foreign
banks

25
22

3,000

19

2,000

16

1,000

13

0

10
1980 1990 2000 2001 2002 2003 2004 2005 2006 2007

Loans of Domestic and
Foreign Banks in the U.S.*
Billions of dollars
6,000
Domestic a
Foreign b
5,250

Percent of total
27
24
21

4,500
Share of foreign banks
3,750

18

3,000

15

2,250

12

1,500

9

750

6
3

0

Foreign banks are growing competitors of the U.S.
domestic banking industry. The numbers clearly indicate that foreign banks are becoming an increasingly important part of the U.S. banking system.
Assets held by branches and agencies of foreign
banks in the United States have grown substantially
over time, from $800 billion at the end of 1991 to
$2.5 trillion in the first quarter of 2007. Their share
of U.S. banking assets has risen since 2003 to a
historical high of 24.1 percent in the first quarter of
2007, well above the previous peak of 22.6 percent
in 1991.
A similar pattern is apparent in foreign banking
organizations’ market shares of loans and deposits.
Their total loan holdings rose to $885 billion, or
14.9 percent, of all loans at the beginning of 2007,
after having gone through a trough of 10.9 percent
in 2003. The predominant type of asset held in
the U.S. branches of foreign banks is commercial
and industrial loans. Recent trends suggest that
foreign banks remain active in business lending, as
the annual growth rate of business loans (nearly 29
percent) mirrors that of growth in total loans over
the same period (from the end of 2003 through the
first quarter of 2007).

1980 1990 2000 2001 2002 2003 2004 2005 2006 2007

Business Loans of Domestic and
Foreign Banks in the U.S.*
Billions of dollars
6,000
Domestic a
Foreign b
5,000

Percent of total
50

Finally, foreign banking organizations’ 27.6 percent
share of deposits confirms that they are important
competitors in the United States. Moreover, the
growth in deposit share for these organizations suggests that foreign banking companies will remain
important competitors in U.S. financial markets.

45
40
35

4,000

30
3,000

Share of
foreign
banks

2,000

25
20
15
10

1,000

5
0

0
1980 1990 2000 2001 2002 2003 2004 2005 2006 2007

25

Footnotes and Sources

Deposits of Domestic and
Foreign Banks in the U.S.*
Billions of dollars
1,500

Percent of total
40

Domestic a
Foreign b

1,350

35

1,200
30

Share of foreign banks

1,050
900

25

750

20

600

15

450
10
300

*Total claims, including domestically owned commercial banks as
well as foreign banks’ branches and agencies in the 50 states and
the District of Columbia; New York investment companies (through
September 2006); U.S. commercial banks, of which more than 25
percent are owned by foreign banks; and international banking
facilities. The data exclude Edge Act and agreement corporations;
U.S. banks’ offices in Puerto Rico, the U.S. Virgin Islands, and other
affiliated insular areas; and foreign banks’ offices in U.S.-affiliated
insular areas.
a. Excludes commercial banks but includes international banking
facilities as well as banks owned by foreign nonbank entities.
b. Adjusted to exclude net claims on their own foreign offices.
Source: Federal Reserve Board, Structure and Share Data for U.S.
Offices of Foreign Banks.

5

150

0

0
1980 1990 2000 2001 2002 2003 2004 2005 2006 2007

Banking and Financial Institutions

Business Loan Markets
08.06.07
by James Thomson and Cara Stepanczuk

Domestic Banks
Reporting Tighter Credit Standards
Net percent
60
50
Medium and large firms
40
30
20
Small firms
10
0
-10
-20
-30
2000

2001

2002

2003

2004

2005

2006

2007

Source: Senior Loan Officer Opinion Survey on Bank Lending Practices,
Board of Governors of the Federal Reserve System, March 2007.

The April 2007 Senior Loan Officer survey (covering the months of February, March, and April)
revealed a slight increase in credit availability for
businesses. After a slight tightening of standards reported on the previous survey, domestic and foreign
banks reported that their lending standards were little changed for commercial and industrial loans for
borrowers of all sizes in the last three months. More
domestic banks narrowed their lending spreads
(loan rates over the cost of funds), attributing their
decision to more aggressive competition from other
banks and nonbank lenders, and increased liquidity
of business loans in the secondary market. Many
foreign banks, as well as some domestic banks,
also reduced the cost of credit lines and eased loan
covenants.
Demand for commercial and industrial loans continued to weaken over the past three months, and
at a faster rate, than reported in the January survey.
Those institutions that reported weaker demand for
commercial and industrial loans cited as motivation
a decreased financing need for accounts receivable
and competition from other credit sources.
Bank balance sheets have yet to reflect the decline
in businesses’ appetite for bank loans in the face of
stable credit standards. The $35 billion increase in
26

bank and thrift holdings of business loans in the
first quarter of 2006 marks the twelfth consecutive
quarter of increase in the bank and thrift holdings of commercial and industrial loans. The sharp
reversal in the trend of quarterly declines in commercial and industrial loan balances on the books
of FDIC-insured institutions prior to the second
quarter of 2004 is still going strong.

Domestic Banks Reporting
Stronger Demand
Net percent
45
Small firms
30
15
0
-15
Medium and large firms
-30
-45
-60
-75
2000

2001

2002

2003

2004

2005

2006

2007

Source: Senior Loan Officer Opinion Survey on Bank Lending Practices,
Board of Governors of the Federal Reserve System, March 2007.

The utilization rate of business loan commitments
(drawdowns on prearranged credit lines extended
by banks to commercial and industrial borrowers)
held at 36.3 percent of total commitments, potentially indicating the declining importance of bank
credit to commercial borrowers as a result of easier
access to capital markets. However, this trend could
reverse if current problems in housing markets and
subprime mortgages spill over into the corporate
debt market.

Quarterly Change in Commercial and
Industrial Loans

Utilization Rate of Commercial and
Industrial Loan Commitments

Billions of dollars

Percent of loan commitments

50

41

40
40
30
39

20
10

38

0

37

-10
36

-20

35

-30
-40
2001

2002

2003

2004

2005

2006

Source: Federal Deposit Insurance Corporation, Quarterly Banking Profile,
First Quarter 2007.

34
2001

2002

2003

2004

2005

2006

Source: Federal Deposit Insurance Corporation, Quarterly Banking Profile,
First Quarter 2007.

27