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1
•

•

The Economy in Perspective
Taking stock … Although some people worried
that the U.S. economy would stumble at the end of
this year and limp into the next, it appears to be
running in fine form. Income and output actually
accelerated last quarter, despite soaring energy
prices and storm damage along the Gulf Coast. In
November, energy prices receded, and employers
impressively stepped up the pace of hiring. Retail
store traffic is encouraging, with consumers seemingly throwing off their worries as easily as Katrina
uprooted trees. Business confidence has stabilized
as well: Stock prices have risen, and market volatility and credit quality spreads remain low. Many
private-sector economic forecasters expect the U.S.
economy to grow at a moderate pace next year,
with headline inflation numbers falling back toward
the 2% range.
What can we look forward to? The most interesting characteristic of the 2006 economy may prove
to be its maturity. We are now into the fifth year of
an economic expansion, far enough along for many
of the imbalances that accumulated in the last
expansion and recession to have been corrected.
Capacity utilization rates have recovered considerably in most industries, and business spending for
capital equipment has finally strengthened again.
Surveys of business executives indicate that they are
optimistic about orders, sales, and equipment
spending. Employment growth was strong enough
in 2005 to push the unemployment rate down to
5%, which is roughly equal to its long-term average.
As business conditions have matured, so have
financial conditions. Many companies and investors
took significant financial losses when the 1990s
dot-com industry collapsed, but the macro
economy has finally worked out the losses and
moved on. Corporate profits, cash flow, and balance
sheets now look healthy, for the most part, providing a firm foundation for further growth. And,
allaying concerns about housing bubbles in some
parts of the country, rising interest rates have
helped to cool off housing price appreciation.
At the macro level, the pricing of corporate bonds
and equities is not a red flag as far as investors

are concerned. Banking companies, which often extend credit to those who cannot borrow in the capital markets, report stellar loan quality.
The inflation picture also is brightening. Declining
energy prices are relieving the pressure on headline
inflation, and thus far core inflation rates have not
edged up from past energy price increases being
passed through to consumers.* And if productivity
growth continues at a healthy pace, inflation rates
are likely to continue their pattern of moderation.
Monetary policy has apparently succeeded in anchoring longer-term expectations, an important factor in
holding down long-term nominal interest rates.
Although maturity connotes a successful evolution from an uncertain beginning, aging brings its
own problems and sows the seeds of potential
future disruptions. Yes, the dot-com wreckage has
been hauled away, but yellow flags are out for the
motor vehicle industry. How serious will their problems prove to be? What combination of sacrifices
will ultimately be agreed upon by current and
retired employees, investors, and taxpayers
through the obligations of the Pension Benefit
Guarantee Corporation? How will these adjustments affect communities that rely heavily on the
most affected industries? What are the implications
of the adjustments for the future of corporate pensions and health care policies?
Hurricane Katrina demonstrated more than the
fact that low-probability events eventually will come
to pass; the devastation of New Orleans was a product of both the storm and inadequate preparedness. Similarly, what some people call institutional
legacy costs, others describe as the consequences
of a failure to prepare prudently. Private-sector
companies are not alone in grappling with the burden of past assurances that are no longer viable.
Federal, state, and municipal governments are all
confronting problems that were created in the past
when decisionmakers shuttled the costs of their actions into the future. Increasingly, that future is now.
Taking stock of the U.S. economy requires us to
acknowledge that while maturity has its privileges,
it also entails significant responsibilities.

FRB Cleveland • December 2005

*This sentence was revised after this issue of Economic Trends
was printed and before it was posted online.

2
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Inflation and Prices
12-month percent change
4.75 CPI AND CPI EXCLUDING FOOD AND ENERGY
4.50

October Price Statistics
Percent change, last:
a
a
a
1 mo. 3 mo. 12 mo. 5 yr.

2004
avg.

3.75

Consumer prices
All items

4.25
4.00

2.4

8.0

4.3

2.7

3.4

CPI

3.50
3.25

Less food
and energy

3.0

1.8

2.1

2.0

2.2

Medianb

1.9

2.3

2.7

2.3

2.75
2.50
2.25

Producer prices
Finished goods

3.00

8.6 13.2

5.9

2.8

4.4

2.00
CPI excluding
food and energy

1.75

Less food and
energy

–3.0

0.0

1.9

1.1

2.2

1.50
1.25
1.00
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

12-month percent change
4.25 CORE CPI AND TRIMMED-MEAN MEASURES

12-month percent change
6 CORE CPI GOODS AND SERVICES

4.00

5
Three months annualized

CPI core services

3.75

Median CPI b

3.50

3.25
3.00

2.75

2.50

2.25

–1

2.00
1.75

–2

16% trimmed mean b

–3

1.50
1.25

CPI excluding food and energy

1.00

Three months annualized
CPI core goods

–4
–5

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

FRB Cleveland • December 2005

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.

After surging 15.7% (annualized rate)
in September—its largest monthly
rise in more than 25 years, the Consumer Price Index (CPI) rose a relatively modest 2.4% (annualized rate)
in October. Energy prices, which rose
sharply throughout the third quarter,
declined 2.9% (annualized) in October. Growth in the core CPI rose to
3.0% (annualized), higher than its
three- and 12-month growth trends,
whereas the median CPI’s monthly
growth rate was a subdued 1.9%.
Longer-term inflation trends were
mixed. The CPI’s 12-month growth

rate ticked down from 4.7% in September to 4.3% in October, the secondhighest 12-month growth rate since
the early 1990s. The 12-month growth
rates of the core CPI and the median
CPI remained steady at 2.1% and
2.3%, respectively. However, the
16% trimmed-mean CPI’s 12-month
growth rate has accelerated just a bit
since June, reaching 2.5% in October.
Taken as a whole, the data suggest
that there has been a retail inflation
trend in the range of 2.0% to 2.5%
since at least the end of 2004; prices of
both core goods and core services
have been showing some stability.

Meanwhile, household inflation
expectations fell from a 15-year high
of 5.5% in September and October to
4.1% in November. The improved
household inflation sentiment probably reflects the continued decline in
petroleum prices, which fell from
their recent peak of nearly $70 per
barrel in August to about $57 in November. However, even longer-term
inflation expectations—which are less
likely to be influenced by fluctuations
in energy prices—declined 0.5 percentage points to 3.3% in November.
(continued on next page)

3
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Inflation and Prices (cont.)
Dollars per barrel
80 WEST TEXAS INTERMEDIATE CRUDE OIL PRICES

12-month percent change
6.0 HOUSEHOLD INFLATION EXPECTATIONS a

5.5

Future prices

70
5.0

65
60

4.5

Five to 10 years ahead

4.0

50
45

3.5

3.0

35
2.5

30
25

2.0
One year ahead

1.5

15
10

1.0
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

Percent of index
40 DISTRIBUTION OF CHANGES IN CPI
AND CORE COMPONENT PRICES
35

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

Accuracy in Predicting CPI Growth over the
Next 12 Months: Root Mean-squared Errors

One-month annualized percent
change in the CPI
One-month annualized percent
change in the core CPI

16%
trimmedMedian mean
CPI
CPI

Annualized
percent
change, last

CPI

Core
CPI

One month

2.83

2.75

2.35

2.22

Three months

2.20

2.39

2.12

2.01

Six months

1.99

2.32

2.03

1.97

Nine months

1.98

2.36

2.05

2.01

12 months

2.09

2.44

2.13

2.11

5
0
Less than 0

0–1

1–2

2–3
Percent

3–4

4–5

Greater
than 5

FRB Cleveland • December 2005

a. Mean expected change as measured by the University of Michigan’s Survey of Consumers.
SOURCES: U.S. Department of Labor, Bureau of Labor Statistics; Federal Reserve Bank of Cleveland; University of Michigan; and the Wall Street Journal.

Although underlying inflation
patterns seem relatively subdued,
some CPI components are still
subject to pricing pressure. Indeed,
apart from energy, 27% of the CPI’s
components showed annualized
price increases of more than 5% in
October. These price increases were
largely offset, however, by deflation
in roughly 17% of the core CPI’s
components.
This uneven distribution of component price changes across the
consumer’s market basket makes it

difficult to gauge any potential shift
in the growth trend in overall retail
prices. Indeed, even the core inflation measures have been showing
somewhat contradictory patterns in
the monthly data: The CPI excluding
food and energy accelerated, the
trimmed-mean CPI decelerated, and
the median CPI held comparatively
steady. Which of these is likely to
be the most accurate? Although no
single monthly measure of inflation
should be given a great deal of weight,
an examination of these alternative

measures’ forecasting record suggests that the trimmed-mean and
median CPI measures tend to predict future CPI trends more accurately than the more traditional core
statistic. That is, when it comes to
forecasting CPI-measured inflation
over the next 12 months, the oneand three-month annualized percent
changes in the median CPI and 16%
trimmed-mean CPI are more accurate than either the regular CPI or
the CPI excluding food and energy.

4
•

•

Monetary Policy
Percent
8 RESERVE MARKET RATES

Percent
6 REAL FEDERAL FUNDS RATE c,d

Effective federal funds rate a
6

4
Intended federal funds rate b

1
Primary credit rate b
Discount rate b

–1

–2
2000

2001

2002

2003

2004

2005

Percent
5.0 IMPLIED YIELDS ON FEDERAL FUNDS FUTURES
4.8

1988

1990

1992

1994

1996

1998

2002

2004

Percent, daily
100 IMPLIED PROBABILITIES OF ALTERNATIVE TARGET
FEDERAL FUNDS RATES (JANUARY MEETING OUTCOME) f
90

November 2, 2005 e
4.6

2000

4.50%

80
November 25, 2005

4.4

August 10, 2005 e

4.2

60
September 21, 2005 e

4.0
3.8

50
40

July 1, 2005 e

3.6

3.4

3.2

3.0

4.25%

4.75%
4.00%

July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June July Aug.
2005
2006

10/07

10/14

10/21

10/28

11/04
2005

11/11

11/18

11/25

FRB Cleveland • December 2005

a. Weekly average of daily figures.
b. Daily observations.
c. Defined as the effective federal funds rate deflated by the recent annual (that is, trailing) core PCE Chain Price Index.
d. Shaded bars indicate periods of recession.
e. One day after the FOMC meeting.
f. Probabilities are calculated using trading-day closing prices from options on February 2005 federal funds futures that trade on the Chicago Board of Trade.
SOURCES: U.S. Department of Commerce, Bureau of Economic Analysis; Board of Governors of the Federal Reserve System, “Selected Interest Rates,”
Federal Reserve Statistical Releases, H.15; Chicago Board of Trade; and Bloomberg Financial Information Services.

At its November 1 meeting, the
Federal Open Market Committee
(FOMC) raised its federal funds rate
target from 3.75% to 4%, which is still
less than 2 percentage points above
the core inflation rate of personal
consumption expenditures for the
past year. The rate hike was widely
anticipated.
Because the most recent annual
core inflation rate is often viewed as a
proxy for expected future inflation,
the difference between the fed funds

rate and core inflation rate is commonly used to measure the real
(inflation-adjusted) fed funds rate.
However, in light of hurricanerelated inflation concerns, trailing
core inflation might be a questionable
proxy for inflation expectations. Indeed, the inflation expectations
revealed in other, more prospective,
measures—such as those from survey
data or market yields on inflationprotected securities—are currently
higher than recent inflation levels.

Hence, a real fed funds rate based on
trailing inflation may be an overestimate. This would suggest that a
greater degree of policy accommodation remains.
The November policy move was
consistent with the forward-looking
language offered in recent statements.
For more than a year now, the FOMC
policy statement has repeated that
“the Committee believes that policy
accommodation can be removed at a
measured pace.” The fed funds rate
(continued on next page)

5
•

•

Monetary Policy (cont.)
Percent
6.0 IMPLIED YIELDS ON EURODOLLAR FUTURES

Percent, weekly average
5.0 YIELD CURVE b,c

November 2, 2005 a
5.5

November 2, 2005 d

4.8
November 25, 2005

August 12, 2005 d

4.6

November 25, 2005

September 23, 2005 d

4.4

August 9, 2005 a
5.0

4.2
September 21, 2005 a

4.5

4.0
3.8
July 1, 2005 d

3.6
July 1, 2005 a

4.0

3.4
3.2

3.5
2004

3.0
2007

2010

2013

Percent, weekly average
8 SHORT-TERM INTEREST RATES b

10
15
Years to maturity

Percent, weekly average
9 LONG-TERM INTEREST RATES

7
8
Conventional mortgage
6
Three-month Treasury bill
7

20-year Treasury bond b

6
Two-year Treasury note

3
5
2
4

One-year Treasury bill
1

10-year Treasury note b
0
1998

3
1999

2000

2001

2002

2003

2004

2005

1998

1999

2000

2001

2002

2003

2004

2005

FRB Cleveland • December 2005

a. One day after the FOMC meeting.
b. All yields are from constant-maturity series.
c. Average for the week ending on the date shown.
d. First weekly average available after the FOMC meeting.
SOURCE: Board of Governors of the Federal Reserve System, “Selected Interest Rates,” Federal Reserve Statistical Releases, H.15.

has risen in increments of 25 basis
points at each FOMC meeting without
a hint of when a pause might occur.
The minutes of the November
meeting, released with a three-week
lag, seemed to make preparations
for removing the “measured pace”
language. Analysts focused on this
sentence: “Several aspects of the statement language would have to be
changed before long, particularly
those related to the characterization
and outlook for policy.” However,
prices of fed funds futures and

options on those futures suggest that
market participants do not expect
dramatic changes in the language.
Rather, a pause in rate hikes sometime next spring had already been
priced into these instruments.
Implied yields based on the prices
of fed funds futures indicate that the
funds rate is expected to rise to
between 4.5% and 4.75% by April.
Moreover, options on these futures
suggest that rate hikes of 25 basis
points each at the December and January meetings remain very likely.
Thus the release of the minutes

seemed to have only a marginal
effect on when market participants
expected a pause. After the minutes
were released, investors were giving
slightly higher odds that the pause
would be announced at the March
meeting.
Yields on Treasury bonds tended
to fall after the release, but only marginally. On the whole, financial markets seem fairly confident that hurricane-related inflation concerns will
come to pass, and that policy may be
approaching a more neutral setting.

6
•

•

Money and Financial Markets
Percent, daily
12 YIELD SPREADS: CORPORATE BONDS
MINUS THE 10-YEAR TREASURY NOTE c

Percent of total refinancing
100 CASH-OUT REFINANCING OF RESIDENTIAL PROPERTY a

10
80

High yield

At least 5% higher loan amount b
8
60

4
40

BBB
2
Lower loan amount b

20
0

0
1987 1989

1991

1993

1995

1997

1999

2001

2003

2005

Percent, daily
5 10-YEAR REAL INTEREST RATE AND

–2
1998

1999

2000

2001

2002

2003

Index, 1985 = 100
155 CONSUMER ATTITUDES

2004

2005

2006

Index, 1966:IQ = 100
115

TIPS-BASED INFLATION EXPECTATIONS
Corrected 10-year TIPS-derived expected inflation e

Consumer sentiment, University of Michigan f

135

105

10-year TIPS d
3

115

10-year TIPS-derived expected inflation d
1

Consumer confidence, Conference Board
0

55
1998

1999

2000

2001

2002

2003

2004

2005

2006

2000

2002

2003

2004

2005

2006

FRB Cleveland • December 2005

a. Annual data until 1997; quarterly data thereafter.
b. Compared with previous financing.
c. Merrill Lynch AA, BBB, and High Yield Master II indexes, each minus the yield on the 10-year Treasury note.
d. Treasury inflation-protected securities.
e. Ten-year TIPS-derived expected inflation, adjusted for the liquidity premium on the market for the 10-year Treasury note.
f. Data are not seasonally adjusted.
SOURCES: Board of Governors of the Federal Reserve System, “Selected Interest Rates,” Federal Reserve Statistical Releases, H.15; Federal Home Loan
Mortgage Corporation; University of Michigan; the Conference Board; and Bloomberg Financial Information Services.

Despite 12 straight increases in the
federal funds rate, long-term interest
rates remain low by historical standards. For more than three years, the
economy has been expanding at an
average annual rate of 3.5%. Normally, when economies expand at
such a healthy pace, investment
opportunities abound, boosting the
real rate of return on new business
investment. In turn, the high returns
on new capital tend to pull up the
whole yield structure, including longterm real interest rates.

The savings glut in Asia is increasingly viewed as a major damper on the
U.S. interest rate structure. The impact
of low long-term rates is nowhere
more evident than in the housing market. Persistently low mortgage rates
have fueled a boom, raising housing
prices relative to income levels.
High housing prices and low mortgage rates have combined to give
households a substantial source of
financing. More specifically, they have
enabled households to tap their

increased housing equity by refinancing at higher loan amounts. In recent
months, this so-called cash-out refinancing has supplied funds that have
allowed households to spend at a
pace that has exceeded growth in
personal income.
Some analysts are concerned that
a sharp uptick in interest rates would
stop cash-out refinancing, causing
a precipitous drop in consumer
spending, especially if housing prices
fall significantly. This concern has
(continued on next page)

7
•

•

Money and Financial Markets (cont.)
Index, monthly average
2,200 STOCK MARKET INDEXES

Index, monthly average
5,500

2,000

Dollars per share, four-quarter moving average
24 S&P 500, EARNINGS PER SHARE a

5,000

4,500

4,000

3,500

3,000

2,500

2,000

1,500

400

1,000

200

500

2,300
2,200

1,300
1,800

1,200

2,100

1,600

1,100

1,400

1,000
Mar. May

1,200

2,000
1,900
July Sept.
2005

Nov.

Operating
1,000

S&P 500

800
600

NASDAQ

As-reported

0
1990

1992

1994

1996

1998

Index
50 S&P 500 OPTIONS VOLATILITY b

2000

2002

2004

2006

1996

1999

2002

2005

12
10

40
Mar. May July Sept. Nov.
2005

1993

Ratio
50 S&P 500 PRICE/EARNINGS RATIO

18
16
14

1990

35
Average

23.9
25

20
20
15
15

13.3

5
1998

1999

2000

2001

2002

2003

2004

2005

2006

1946 1952

1958

1964

1970

1976

1982

1988

1994

2000

2006

FRB Cleveland • December 2005

a. Dashed lines indicate the forecast as of November 22.
b. CBOE Volatility Index (VIX). Monthly data.
SOURCES: Standard and Poor’s Corporation; Chicago Board Options Exchange; and Bloomberg Financial Information Services.

been heightened by higher energy
prices, which will put additional
stress on household budgets and
balance sheets.
Business balance sheets, on the
other hand, are quite healthy, as
reflected in the stable spreads of corporate bond rates over Treasuries.
Many businesses have ample cash for
investing if they choose to spend it.
With inflation expectations remaining well-contained and consumer
confidence on the rebound, business
investment should continue to be a

major driver of the expansion. Moreover, although consumer spending
might slow, it could continue to be
supported by employment gains.
Increased business spending is
most evident in the energy sector.
More broadly, however, improved
investment prospects seem to have
been supported by a surge in broad
equity indexes in November. Indeed,
stock market fundamentals appear
quite favorable. Chief among these
fundamentals are S&P 500 companies’
earnings, which have been increasing

at a rate of 15% over the past year.
Earnings are expected to decelerate,
but analysts nonetheless project earnings to grow at nearly double-digit
rates over the next year. Despite the
recent run-up in stock prices, the
price–earnings ratio remains well
below its average in recent years.
The strength in equities in November was coupled with a decline in
equity options volatility. The decline
in volatility since October may reflect
some taming of inflation fears.

8
•

•

The Interest Rate Conundrum and the Savings Glut
Percent
10 U.S. REAL LONG-TERM BOND RATE a

Percent of GDP
23 UNITED STATES b

Percent of GDP
2
1

Current account
21

–1

–2

–3

18
Investment

–4

–5

16
Savings

–2

–4
–6
1960

–6

–7

13
1965

1970

1975

1980

1985

1990

1995

Percent of GDP
50 JAPAN b

2000

–8

2005

1970

Percent of GDP
6

1975

1980

1985

1990

1995

Percent of GDP
30 EURO AREA b

2000

Percent of GDP
2
Current account

29
5

Current account

Savings
40

4
Investment

27
26

3
25

–1

23
22

–2
Savings

–1

10
1970

–2

21
20

–3

Investment

19
1975

1980

1985

1990

1995

2000

–4
1970

1975

1980

1985

1990

1995

2000

FRB Cleveland • December 2005

a. Calculated using 10-year Treasury bond rate and 12-month change in CPI less food and energy.
b. IMF staff calculations. Original sources include the OECD Analytical Database; and the World Bank, World Development Indicators.
SOURCES: Federal Reserve Board; Bureau of Labor Statistics; and International Monetary Fund, World Economic Outlook, September 2005, pp. 91–124.

Two of the brightest blips on U.S. policymakers’ radar screens are the low
level of U.S. long-term interest rates
and our large, expanding currentaccount deficit. Global saving and investment patterns go a long way toward explaining both of them.
Real long-term interest rates in the
U.S. and elsewhere around the globe
seem unusually low for the current
state of the business cycle. A recent
International Monetary Fund study of
46 countries (including industrialized,
emerging-market, and oil-producing

nations) suggests that lackluster
global investment helps explain real
interest rates.
Expressed as a percentage of
world GDP, global investment fell
from 23% in 1997 to 21% in 2002. It
recovered to approximately 22% in
2004, according to the latest available
data. The current pace of worldwide
economic recovery and recent declines in the cost of capital seem capable of supporting a higher level of
global investment than we have recently seen.

Among industrialized countries,
most of the investment decline was
concentrated in the euro area and in
Japan, where 15 years of subpar economic growth has taken a toll. On
balance, investment in most other
industrialized countries remained
fairly flat between 2001 and 2004. In
the U.S., however, fixed investment
has recently been rebounding.
Investment in most East Asian
countries fell precipitously after the
Asian financial crisis in the mid-1990s.
A notable exception is China, where
(continued on next page)

9
•

•

The Interest Rate Conundrum and the Savings Glut (cont.)
Percent of GDP
7.0 EMERGING-MARKET AND
OIL-PRODUCING ECONOMIES a
6.5

Percent of GDP
1.00

Percent of GDP
9

0.75
Current account

6.0

Percent of GDP
40 EAST ASIA a
Current account
36

0.50

Investment

5.5

0.25

5.0

4.5

–0.25

Investment
32

–3

–0.50

4.0
Savings

3.5

–0.75

3.0

–1.00

2.5

–1.25

2.0

–1.50
1970

1975

1980

1985

1990

1995

Savings

–9

16
1970

2000

Percent of GDP
36 OIL PRODUCERS a

–6

Percent of GDP
9

1975

1980

1985

1990

1995

Percent of GDP
55 CHINA a

2000

Percent of GDP
6
Current account

Current account
6

–3

–6

–9

32
Investment

Investment

–2

Savings
Savings
16

12
1970

1975

1980

1985

1990

1995

2000

–4

–6
1970

1975

1980

1985

1990

1995

2000

FRB Cleveland • December 2005

a. IMF staff calculations. Original sources include the OECD Analytical Database; and the World Bank, World Development Indicators.
SOURCE: International Monetary Fund, World Economic Outlook, September 2005, pp. 91–124.

investment has risen sharply. Among
oil-producing nations and other
emerging-market nations, investment
has been unimpressive.
In the aggregate, savings must
equal investment; not surprisingly,
global savings have declined as a
share of world GDP. Within any country or region, however, savings can—
and typically do—differ from local
investment. Divergences between
nations’ saving and investment patterns are mirrored in their currentaccount positions. Countries running
current-account surpluses save more

than they invest, whereas countries
experiencing current-account deficits
invest more than they save.
In most countries and regions covered in the IMF study, savings closely
paralleled—but slightly exceeded—
local investment. Consequently, most
countries and regions maintain small
current-account surpluses.
There are, however, striking exceptions. As a consequence of federal
budget deficits and low private savings, overall savings in the U.S. have
fallen sharply since 1997 and remain
well below our level of investment. In
contrast, most East Asian countries

and oil-producing countries maintain
savings substantially in excess of local
investment. Inflows of savings from
these emerging-market economies
account for roughly two-thirds of the
divergence between U.S. investment
and savings. The pattern of their
savings, currently at record levels,
generally reflects many East Asian governments’ wish to acquire foreignexchange reserves as a buffer against
future financial crises and as a consequence of relatively low returns in
investment projects in these emerging economies.

10
•

•

Economic Activity
Percentage points
3 CONTRIBUTION TO PERCENT CHANGE IN REAL GDP c

a,b

Real GDP and Components, 2005:IIIQ
(Preliminary estimate)

Annualized
percent change
Current
Four
quarter
quarters

Change,
billions
of 2000 $

Real GDP
116.9
Personal consumption 75.2
Durables
29.6
Nondurables
14.7
Services
34.9
Business fixed
investment
19.4
Equipment
22.4
Structures
–0.9
Residential investment
7.0
Government spending 15.8
National defense
12.2
Net exports
2.4
Exports
2.2
Imports
–0.2
Change in business
inventories
–14.9

4.3
3.9
10.8
2.6
3.2

3.6
3.8
6.6
4.2
3.0

6.2
8.9
–1.4
4.8
3.2
10.3
__
0.7
0.0

7.8
10.1
1.0
6.6
2.1
3.3
__
6.5
4.5

Business fixed
investment

Last four quarters
2005:IIQ
2005:IIIQ

Personal
consumption
Exports

Government
spending

Residential
investment
Imports

–1

–2
Change in
inventories
–3

Annualized quarterly percent change
4.5 REAL GDP AND BLUE CHIP FORECAST c

Annualized quarterly percent change
6 GDP AND OTHER INDICATORS c
Final estimate
Preliminary estimate

4.0

Blue Chip forecast d

Real GDP
Capacity utilization
Hours of employment
Nonfarm employment
Industrial production

30-year average
3.5

0
3.0
–2

2.5
–4

2.0

–6
IIIQ

IVQ
2004

IIQ

IIIQ
2005

IVQ

IIQ
2006

IIIQ

2005:IIQ

2005:IIIQ

10/05 and 11/05, annualized

FRB Cleveland • December 2005

a. Chain-weighted data in billions of 2000 dollars.
b. Components of real GDP need not add to the total because the total and all components are deflated using independent chain-weighted price indexes.
c. Data are seasonally adjusted and annualized.
d. Blue Chip panel of economists.
SOURCES: U.S. Department of Commerce, Bureau of Economic Analysis; and Blue Chip Economic Indicators, November 10, 2005.

The Commerce Department’s preliminary reading of 2005:IIIQ real GDP
growth was 4.3%, up from the advance
reading of 3.8%. The upward revision
to the preliminary estimate resulted
from upward revisions to residential
fixed investment, nondurable consumption, and business spending on
equipment and software.
Most components’ contributions
to the percent change in real GDP
were similar to their average for the
previous four quarters. However, the
components with the largest contributions did shift from 2005:IIQ
to 2005:IIIQ. Personal consumption

contributed 2.7 percentage points (pp)
to the change in real GDP, compared
to only 2.4 pp in 2005:IIQ; private
inventories subtracted only 0.6 pp
from the change in real GDP, compared to 2.1 pp in 2005:IIQ. Conversely, exports contributed a modest
0.1 pp in the third quarter, after
adding 1.1 pp to the change in real
GDP in 2005:IIQ.
Real GDP growth of 4.3% or higher
has not been achieved since 2004:IQ.
This is significantly higher than the
30-year average of 3.3%. However,
according to the November report,
the Blue Chip panel of economists

predicts that growth will slow to 3.0%
in 2005:IVQ and then remain between
3.1% and 3.5% in 2006.
Although real GDP growth increased in the third quarter, other important indicators of the economy’s
health faltered. Industrial production
and capacity utilization decreased
between 2005:IIQ and 2005:IIIQ, and
data from the first two months of the
fourth quarter suggest that they will
continue to drop. However, monthly
data from both hours of employment
and nonfarm employment currently
indicate that these numbers will
increase in 2005:IVQ.

11
•

•

Temperature and Retail Sales
Annualized growth rate except autos, September/October, percent
30 TEMPERATURE AGAINST OCTOBER RETAIL
SALES GROWTH EXCEPT AUTOS
25

Annualized growth rate, September/October, percent
140 TEMPERATURE AGAINST OCTOBER RETAIL SALES GROWTH
120
100

15
October 2005

60
10
40
5
20
0
0
October 2005

–5

–20

–10

–40

–15

–60
50

53
54
October temperature

Annualized growth rate, September/October, percent
140 TEMPERATURE CHANGE AGAINST OCTOBER
RETAIL SALES GROWTH
120

53
54
October temperature

Annualized growth rate, September/October, percent
30 TEMPERATURE CHANGE AGAINST OCTOBER
RETAIL SALES GROWTH EXCEPT AUTOS
25

100

15
October 2005

60
10
40
5
20
0

0
October 2005

–20

–5
–10

–40
–60

–15
–16

–14

–10
–12
Temperature change, September/October

–8

–6

–16

–14

–10
–12
Temperature change, September/October

–8

–6

FRB Cleveland • December 2005

NOTE: All retail data are seasonally adjusted.
SOURCES: U.S. Department of Commerce, Bureau of the Census; and National Climatic Data Center.

Many retailers credited colder October
weather with improving the month’s
sales. It is easy to think of individual
goods—down-filled jackets and swimsuits, say—whose sales depend on
temperature. It is less obvious that
such a relationship should exist in aggregate economic data, partly because
of “averaging out” over the many
goods sold in the U.S., but principally
because such data are seasonally
adjusted, which removes the obvious
effects of temperature. Nonetheless,
can we see a relationship between
temperatures and retail sales in
aggregate U.S. data?

Retail sales growth from September to October seems unrelated to
average U.S. temperatures in October. (The 120% growth rate recorded
in 2001 was presumably an aftershock of the September 11 attacks.)
A loose relationship between these
variables emerges if we exclude automobiles from retail sales, which may
be warranted in light of automotive
companies’ recent rebates and
special pricing.
But these figures may not get at the
essence of what retailers mean when
they say that colder temperatures

improved retail sales in October.
Perhaps sales took off when the temperature fell sharply between September and October. For total retail
sales, it is difficult to discern a pattern. However, if we again exclude
automobiles, the size of the drop in
temperature seems to be positively
correlated with the rate of growth
in retail sales. At the very least, October’s retail sales growth seems to
have been more closely linked to the
amount of temperature change than
to the average temperature level.

12
•

•

Labor Markets
Change, thousands of workers
400 AVERAGE MONTHLY NONFARM EMPLOYMENT CHANGE

Labor Market Conditions

350

Average monthly change
(thousands of employees, NAICS)

Revised
Preliminary estimate

300
250

100
50
0
–50
–100

29
23
3
9
–6

22
25
–6
1
–7

50
37
11
9
2

154
13
12
45
15
33
22
12

145
11
16
36
11
31
17
16

165
9
13
29
5
36
29
21

2004
183

–76
–7
–67
–48
–19

–42
10
–51
–32
–19

Service providing
30
Retail trade
–10
Financial activitiesa
6
PBSb
–17
Temporary help svcs.
2
Education & health svcs. 40
Leisure and hospitality
12
Government
21

50
–5
7
22
12
30
18
–4

Goods producing
Construction
Manufacturing
Durable goods
Nondurable goods

150

Nov.
2005
215

2003
8

Payroll employment

200

YTD
2005
167

2002
–45

Average for period (percent)

–150

Civilian unemployment
rate

–200
2001 2002 2003 2004

IVQ
2004

IIQ IIIQ
2005

Sept.

5.8

6.0

5.5

5.1

5.0

Oct. Nov.
2005

Percent
65.0 LABOR MARKET INDICATORS

Percent
6.5

Employment-to-population ratio

November Employment Status of Adults Who
Evacuated Their Homes in August because of
Hurricane Katrinac

6.0

64.5

Employment status,
November 2005

5.5

64.0

Civilian noninstitutional
population (thousands)
Civilian labor force
(thousands)

63.5

5.0

Participation rate
(percent)
Employed (thousands)

63.0

4.5

4.0
Civilian unemployment rate
3.5

62.0

November
residence
different than
in August

886

442

443

489

233

256

55.2

52.7

57.7

389

204

185

43.9
100

46.1
29

41.6
71

20.5

12.5

27.8

397

209

188

Employment-population
ratio
Unemployed (thousands)

62.5

Total

November
residence
same as
in August

Unemployment rate
(percent)
Not in labor force
(thousands)

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

FRB Cleveland • December 2005

NOTE: All data are seasonally adjusted unless otherwise noted.
a. Financial activities include the finance, insurance, and real estate sector and the rental and leasing sector.
b. Professional and business services include professional, scientific, and technical services, management of companies and enterprises, administrative and
support, and waste management and remediation services.
c. Not seasonally adjusted. Not fully representative of the total evacuee population. For further information see www.bls.gov/cps.
SOURCE: U.S. Department of Labor, Bureau of Labor Statistics.

Nonfarm payrolls grew by 215,000 in
November, beating consensus expectations by 5,000 jobs. This followed
meager growth in September (17,000)
and October (44,000), which was
attributable to Hurricane Katrina’s
direct and indirect effects.
November’s employment gains
included every major industry. Large
gains occurred in construction
(37,000) and food services (39,000).
Manufacturing payrolls increased by

11,000, the industry’s first back-toback monthly increase in over a year.
Retail and temporary help services
made modest gains over the month.
The national unemployment rate
held at 5.0% in November, after ranging from 4.9% to 5.1% for the previous six months. The employment-topopulation ratio, which has varied
only slightly in the last four months,
was essentially unchanged at 62.8%.
Beginning in October, the household survey included questions

designed to identify Hurricane Katrina evacuees. The survey indicated
that 900,000 persons 16 and older
had been forced out of their homes
by the storm in August; by November, half of them had returned home.
Of the 55.2% of evacuees who were
classified as being in the labor force,
20.5% were unemployed. However,
the unemployment rate among those
who had returned home was 12.5%.

13
•

•

Manufacturing Employment
Percent
30 U.S. EMPLOYMENT SHARE a

Percent
90

Goods-producing industries

Index, 1985 = 100
140 MANUFACTURING EMPLOYMENT
130
Korea

120
Canada

Service-providing industries

110

80
Manufacturing industries

100
Japan

U.S.
75

80
Taiwan

U.K.

70
10
1975 1977 1980

70
1983

1986 1989

1992

1995 1998

2001 2004

1977 1980

1983

1986

1989

1992

1995

1998

2001 2004

Index, U.S. = 100
160 HOURLY COMPENSATION COSTS FOR MANUFACTURING
PRODUCTION WORKERS (U.S. DOLLARS)

Annual percent change
16 MANUFACTURING OUTPUT PER HOUR
14

140

Korea

Japan

European Union

12
120

Taiwan
10

100

6
4

Canada

U.K.

Korea

2
40
0

U.S.
Japan

Canada

–2

Taiwan

U.K.

–4
1978

1981

1984

1987

1990

1993

1996

1999

2002

1977 1980

1983

1986

1989

1992

1995

1998

2001 2004

FRB Cleveland • December 2005

a. Total nonfarm payroll employment.
SOURCE: U.S. Department of Labor, Bureau of Labor Statistics.

Manufacturing’s share of total U.S.
employment has been dropping for
at least 60 years. Since 1975 alone, the
share plummeted from about 22% to
roughly 11% of all nonfarm jobs.
Since 1977, manufacturing employment has dropped roughly 18% in
Japan and a whopping 49% in the
U.K. In contrast, manufacturing employment has risen slightly (about
3%) in Canada, and most dramatically
in Taiwan, where it has jumped nearly
40% in the last 25 years or so. In 2004,
manufacturing employment fell in the

U.S., U.K., Canada, and Japan, but
rose in Korea and Taiwan.
Increased productivity generally
slows employment growth. In 2004,
manufacturing employment posted
its largest declines in the U.S., U.K.,
and Japan, three countries where productivity growth exceeded historical
average annual growth rates. However, higher productivity does not
necessarily correspond to lower manufacturing employment. For example,
although Taiwan has experienced substantial productivity growth since the

mid-1970s, manufacturing employment rose for a decade after the late
1970s and has remained relatively
unchanged since the early 1990s.
Manufacturing employment rose
in the countries that have relatively
low hourly compensation costs. Over
the past 20 years or so, manufacturing
employment has risen in Korea and
Taiwan, where hourly compensation
costs have ranged between 10% and
50% of those for U.S. manufacturing
workers.

14
•

•

Fourth District Employment
Percent
8.5 UNEMPLOYMENT RATES a

UNEMPLOYMENT RATES, SEPTEMBER 2005 b

8.0

U.S. average = 5.1%

7.5
7.0
6.5
6.0
5.5
Lower than U.S. average

U.S.
5.0

About the same as U.S. average
(5.0% to 5.2%)
Higher than U.S. average

4.5
Fourth District b

More than double U.S. average

4.0
3.5
1990

1993

1996

1999

2002

2005

Payroll Employment by Metropolitan Statistical Area
12-month percent change, October 2005
Cleveland Columbus Cincinnati Dayton
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

Toledo Pittsburgh Lexington

U.S.

–0.1
0.4
0.7

0.6
1.1
–0.6

0.9
2.0
0.5

–1.3
–3.1
–3.4

0.5
–1.6
–2.8

–0.1
–3.3
–3.6

0.7
1.3
0.0

1.4
0.9
–0.7

–0.4
–0.2
–1.0
–1.0
0.4

4.5
0.5
–0.6
0.0
0.1

5.5
0.6
–0.5
0.0
–0.5

–1.8
–1.0
–2.4
–3.6
–2.2

1.7
1.1
1.8
–4.2
0.0

–2.9
0.4
–0.5
0.4
1.2

4.7
0.6
0.9
–2.2
–0.9

4.0
1.5
1.0
0.2
2.4

–0.3
1.2
0.6
0.0
–1.5

1.2
3.8
2.1
–0.5
–1.4

2.6
2.3
–1.9
1.4
0.9

0.0
0.5
–2.0
4.0
–1.5

3.7
1.1
1.5
3.9
–1.9

0.5
2.3
1.4
1.3
–2.8

–1.0
0.7
1.6
0.0
1.6

2.7
2.2
1.7
0.2
0.9

September unemployment rate (percent) 5.7

5.3

5.4

6.0

6.7

5.1

4.6

5.1

FRB Cleveland • December 2005

a. Shaded bars represent recessions.
b. Seasonally adjusted using the Census Bureau’s X-11 procedure.
SOURCE: U.S. Department of Labor, Bureau of Labor Statistics.

The Fourth District unemployment
rate rose 0.1 percentage point to 5.8%
in September. Although employment
increased 0.3% over the month, both
the labor force and the number of
unemployed were estimated to have
grown even more (0.4% and 0.6%,
respectively). The U.S. unemployment rate fell from 5.1% in September
to 5.0% in October.
Unemployment rates in the great
majority of the District’s counties
exceeded the 5.1% U.S. average in
September. In 142 counties, unemployment rates exceeded 5.2%; 20

counties had rates that were within
0.1 percentage point of the U.S. average; and only seven counties had unemployment rates of 4.9% or lower.
From August to September, rates in
the District’s major metropolitan
areas were little changed, generally
remaining above the national rate.
Lexington’s unemployment rate rose
0.7% on the month; however, its
September unemployment rate of
4.6% was still well below the nation’s.
In the 12 months ending in October, the Cleveland, Dayton, and Pittsburgh metropolitan areas all lost net

employment. Dayton’s nonfarm employment drop was caused by declines in both goods-producing and
service-providing industries; Cleveland’s nonfarm employment decline
resulted from a contraction in
service-providing industries alone;
and Pittsburgh’s decline was traceable to goods-producing industries.
A bright spot for the District was the
education and health services industry, whose employment increased as
much as 3.8% over the year in
Columbus.

15
•

•

The Cincinnati Metropolitan Area
Index, March 2001 = 100
104 PAYROLL EMPLOYMENT SINCE MARCH 2001 a

PAYROLL EMPLOYMENT, CINCINNATI MSA b
Total nonfarm
Goods-producing

102

Natural resources,
mining, and construction

Manufacturing

Cincinnati MSA b
100

Service-providing

Trade, transportation,
and utilities
U.S.

Information

Financial activities

Professional and business services

Ohio
Education and health services

Leisure/ hospitality

Other services
Government

94
2001

2002

2003

2004

–3

2005

LOCATION QUOTIENTS, 2004

0
3
12-month percent change, October

Selected Demographics, 2004
Cincinnati MSAb,c

Natural resources and mining
Construction

Ohio/U.S.
Cincinnati MSA/U.S. b

Total population
(millions)

Manufacturing

Percent by race
White
Black or AfricanAmerican
Other American

Trade, transportation, and utilities
Information
Financial activities

Percent by age
0–19
20–34
35–64
65 or older

Professional and business services
Education and health services
Leisure and hospitality

Ohio

U.S.

2.1

11.2

285.7

85.3

85.7

77.3

11.7
3.0

12.3
1.9

12.8
9.9

29.4
20.7
38.3
11.7

26.7
19.1
39.9
12.5

27.9
20.3
39.8
12.0

Other services

Percent with
bachelor’s degree
or higher

24.8

23.3

27.0

Government

Median age

35.2

37.5

36.2

FRB Cleveland • December 2005

a. Seasonally adjusted.
b. The Cincinnati–Hamilton metropolitan statistical area consists of Dearborn, Franklin, and Ohio counties in Indiana; Boone, Bracken, Campbell, Gallatin,
Grant, Kenton, and Pendleton counties in Kentucky; and Brown, Butler, Clermont, Hamilton, and Warren counties in Ohio.
c. Calculated by the Federal Reserve Bank of Cleveland.
SOURCES: U.S. Department of Commerce, Bureau of the Census; and U.S. Department of Labor, Bureau of Labor Statistics.

Cincinnati was undoubtedly hurt by
the last recession, but it was affected
less than the U.S. or Ohio, at least
where employment is concerned.
Throughout the recovery, Cincinnati’s employment fell more slowly
than the rest of the U.S. and for fewer
weeks. Moreover, since the last business cycle peak in March 2001, the
city has added about 1% to its nonfarm employment (roughly the same
rate as the U.S. average). Ohio, in
contrast, suffered a 3% loss.

Much of Cincinnati’s recent employment growth has occurred
in goods-producing rather than
service-providing industries. Goodsproducing employment grew 2.0%
during the year, compared to a 0.7%
gain in service-providing employment. Among the big gainers were
natural resources, mining, and construction; professional and business
services; and education and health
services. The leisure and hospitality
industry, however, declined over
the year.

Cincinnati’s industrial mix of employment differs markedly from the
nation’s in several ways: The share of
its employment occupied in natural
resources and mining is nearly triple
that of the U.S. It also has a significantly smaller share of employment
in the construction and information
industries.
As for demographics, Cincinnati
and Ohio have similar shares of minority residents. However, Cincinnati
has a smaller percentage of residents
65 and older, and a larger percentage
with a bachelor’s degree.

16
•

•

Coincident Economic Indexes
Index, March 2001 = 100
110 COINCIDENT ECONOMIC ACTIVITY INDEXES,
FOURTH DISTRICT STATES

Three-month change, percent
2 CHANGE IN COINCIDENT ECONOMIC ACTIVITY
Pennsylvania
INDEXES, FOURTH DISTRICT STATES

West Virginia

105

Ohio
Kentucky
0
Kentucky
West Virginia

100
Pennsylvania
–1
Ohio

–2
2001

2002

2003

2004

2005

2001

2002

2003

2004

2005

COINCIDENT ECONOMIC ACTIVITY INDEXES BY STATE

Three-month percent change, September 2005
Lower than –0.5%
Between –0.5% and –0.1%
No change
Between 0.1% and 0.5%
Higher than 0.5%

FRB Cleveland • December 2005

SOURCE: Federal Reserve Bank of Philadelphia.

Although measures such as the unemployment rate and gross domestic product are significant, they can
leave out important information that
is captured in other economic series.
To round out the picture, the Federal
Reserve Bank of Philadelphia regularly calculates and publishes coincident economic indexes for each
state, incorporating data from several sources (nonfarm employment,
the unemployment rate, average

hours worked in manufacturing, and
wages and salaries).
Although Ohio’s coincident economic index has risen steadily since
mid-2003, it still lags behind the other
Fourth District states. West Virginia
continues to have the highest coincident index of any District state, the
rank it has held since May 2001.
Changes in the indexes over threemonth periods help distinguish
trends from temporary aberrations. In
the three months ending September

2005, West Virginia’s index dropped
sharply, making it one of only three
states to undergo such a decline; the
other two were hurricane-ravaged
Mississippi and Louisiana. The recent
decline in West Virginia’s coincident
index can be attributed primarily to
the state’s rising unemployment rate,
which has resulted from major layoffs
in the steel and manufacturing industries, and to its payroll employment
performance.

17
•

•

FDIC Funds
Percent of insured depsoits
1.50 RESERVES

Number
140 PROBLEM INSTITUTIONS

1.45

BIF
SAIF

1.40

120
BIF
SAIF

Target
100

1.35
1.30

1.25
60

1.20
1.15

1.10
20
1.05
1.00

0
1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Number
12 FAILED INSTITUTIONS

Billions of U.S. dollars
35 ASSETS OF PROBLEM INSTITUTIONS
30

BIF
SAIF

10
BIF
SAIF

25
8
20
6
15
4
10
2

0
1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

FRB Cleveland • December 2005

SOURCE: Federal Deposit Insurance Corporation, Quarterly Banking Profile (various issues).

Insured deposits grew over the past
five years at an average annual rate of
4.99% for members of the FDIC’s
Bank Insurance Fund (BIF) and
4.54% for members of its Saving
Association Insurance Fund (SAIF).
This robust deposit growth has had a
material impact on both funds.
At the end of 2005:IIQ, BIF reserves
stood at 1.26% of insured deposits,
marginally above the reserve target
ratio of 1.25% and well below its peak
level of 139 basis points of reserves for
each dollar of insured deposits at the
end of 1998. SAIF reserves dropped

from 1.34% of insured deposits at the
end of 2004 to 1.32% at the end of
2005:IIQ, continuing the steady decline that started at year-end 2003. Although the SAIF reserve ratio remains
comfortably above the target ratio of
1.25% of insured deposits, it is considerably below its 1999 peak of 144 basis
points. Despite recent declines in reserve ratios, the financial position of
both FDIC funds remains solid. Their
strength results partly from the stability of the banking and thrift industries,
as evidenced by member institutions’
low failure rates and generally robust

balance sheets. Bank failures since
1996 have been miniscule in the number of institutions as well as their total
assets. The three BIF members that
failed in 2004 were small institutions
with total assets of only $151 million.
No BIF or SAIF members failed during
the first half of 2005. If no SAIF members fail in the second half of 2005,
it will mark the fourth year out
of the last nine with no failures and
over 10 years since more than one
SAIF member failed. The rarity of
thrift institutions’ failures over the
past decade contrasts starkly to the
(continued on next page)

18
•

•

FDIC Funds (cont.)
Percent of total assets
1.2 NONPERFORMING ASSETS OF INSURED INSTITUTIONS

Millions of U.S. dollars
3,000 ASSETS OF FAILED INSTITUTIONS

1.0

2,500

BIF
SAIF

BIF
SAIF
2,000

0.8

1,500

0.6

1,000

0.4

500

0.2

0
1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

BIF Assessment-Base Distributiona

SAIF Assessment-Base Distributionb

Assessable Deposits in Billions as of June 30, 2005
Supervisory and Capital Ratings for Second Semiannual
Assessment Period, 2005
Supervisory risk subgroup
Capital group
A
B
C

Well-capitalized

Number of
institutions

7,301

Assessable deposit
base
$4,570

94.0%
98.0%

352
$72

4.5%

1.5% $13

0.6%

Number of
institutions

1,039

93.1%

5.4%

1.0%

0.3%

Assessable deposit
base
$1,190

98.1%

$21

1.7%

0.2%

0.4%

0.1%

0.0%

0.1%

0.0%

Adequately capitalized
Number of
institutions
Assessable deposit
base

Adequately capitalized
50
8

0.6%
0.2%

5
$1

0.1%
0.0%

7
$0

0.1%

Number of
institutions

0.0%

Assessable deposit
base

Undercapitalized
Number of
institutions
Assessable deposit
base

Undercapitalized
0
0

0.0%
0.0%

0
$0

0.0%
0.0%

3
$0

0.0%

Number of
institutions

0.0%

Assessable deposit
base

FRB Cleveland • December 2005

a. Number reflects the number of BIF members; base reflects the BIF-assessable deposits held by both SAIF and BIF members. Institutions are categorized
according to their capitalization and supervisory subgroup rating, which is generally determined by on-site examinations.
b. Number reflects the number of SAIF members; base reflects the SAIF-assessable deposits held by both BIF and SAIF members. Institutions are categorized
according to their capitalization and supervisory subgroup rating, which is generally determined by on-site examinations.
SOURCE: Federal Deposit Insurance Corporation, Quarterly Banking Profile (various issues).

widespread solvency problems that
plagued the industry throughout the
1980s. Not only have the numbers of
bank and thrift failures been low over
the last decade; they also represent a
tiny percent of FDIC-insured institutions in terms of both number of firms
and total assets.
Since the end of 2004, problem institutions (those with substandard examination ratings) have declined
from 69 to 61 for the BIF, while increasing slightly from 11 to 13 for the
SAIF. Moreover, for both FDIC funds,
the change in the number of problem

institutions was matched by a change
in the assets of problem banks and
thrifts. However, the continued low
number of problem institutions and
the small amount of assets they held
suggests that members’ losses will
remain low in the near future. This
conjecture is supported by the low
levels of nonperforming assets as a
percent of total assets on the books of
BIF and SAIF members.
The Federal Deposit Insurance
Corporation Improvement Act of
1991 mandated that FDIC insurance
premiums be adjusted for risk. So for

both funds, the FDIC assigns each
member to one of nine risk groups on
the basis of its most recent examination rating and its level of capitalization. With both funds exceeding their
target reserve ratios, well-capitalized
institutions in supervisory risk group
A pay no premiums by statute.
Currently, 94% of BIF members and
93% of SAIF members are in this
group. Furthermore, these A-group
banks and thrifts account for at least
98% of both BIF’s and SAIF’s assessable deposits.

Full text of Economic Trends (Federal Reserve Bank of Cleveland) : Economic Trends - December 2005

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