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Federal Reserve Bank of Cleveland

Economic Trends
February 2007
(Covering January 11, 2006 - February 8, 2007)

In This Issue
Economy in Perspective
Worry Is Interest Paid on Trouble before It Falls Due
Inﬂation and Prices
December Price Statistics
Money, Financial Markets, and Monetary Policy
Monetary Policy Stays Put
Monetary Aggregates
What Is the Yield Curve Telling Us?
International Markets
China’s Economy
Japanese Monetary Policy
The Yen Carry Trade
Economic Activity and Labor Markets
Employment during Recovery
The Employment Situation
The Employment Cost Index
Job-to-Job Movers
High-technology Manufacturing
Industrial Production Closes 2006 in Fine Form
Some Say Housing Numbers Encouraging
New Cities Added to Case-Shiller Home Price Indices
Regional Activity
Fourth District Employment Conditions
Ohio’s Automobile Industry
Banking and Financial Institutions
Banking Structure
Business Loan Markets

Economic Trends is published by the Research Department of the Federal Reserve Bank of Cleveland.
Views stated in Economic Trends are those of individuals in the Research Department and not necessarily those of the Federal Reserve Bank of Cleveland or of the Board of Governors of the Federal Reserve System. Materials may be reprinted
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ISSN 0748-2922
2

The Economy in Perspective
02.07.07
by Mark S. Sniderman
Worry is interest paid on trouble before it falls due.
——W.R. Inge (1860–1954), The Observer (London, February 14, 1932)
Although still in the throes of a major housing market correction, the U.S. economy ended 2006 in much better
shape than many analysts had expected. According to the Bureau of Economic Analysis, real GDP expanded at an
annual rate of 3.5 percent in the fourth quarter, and consumption spending clocked in at 4.4 percent. December’s
unemployment rate of 4.5 percent is quite low by historical standards, and the January 2007 employment report revealed that the 2006 economy generated nearly one million more jobs than were originally reported. As if this were
not enough, recent inﬂation data have been encouraging: The core PCE price index advanced at an annualized rate
of only 1.7 percent from September to December.
So why should a central banker be worried? One good reason is that worries are sometimes well founded.
Consider the housing situation. The residential construction slide has been steep, but housing prices have held fairly
steady in most markets. Mortgage applications even picked up in the last few months of the year. Despite these signs
of stabilization, caution is required. Most housing data are seasonally adjusted, and the weather was unusually mild
in many parts of the country earlier this winter. Might we soon discover that some of the strength we see melts with
the snow? Second, many people may be keeping their homes oﬀ the market at this time of stress, a tactic that temporarily restricts supply. If home sales pick up, will they put their houses up for sale, prolonging the time it takes to
normalize inventories? To clear the market, prices might have to adjust more than they already have. And third, how
will market developments aﬀect owners’ willingness and ability to treat their homes as piggy banks?
If further housing retrenchment appears unlikely today, recall how quickly the stock market collapse and the investment spending bust seemed to materialize out of thin air in 2000. Admittedly, housing and equity markets diﬀer in
important ways, not the least of them that people can live in their homes—a fact that in itself could diminish the
speed of adjustment, acting as a circuit breaker against ﬁre sale prices.
Perhaps we have not yet read the last chapter of the housing market mystery. The odds favor a relatively happy ending but, in that genre, a few more bodies are often discovered before the last page is turned.
If housing risks don’t seem too worrisome, consider the inﬂation risk. Although both CPI and PCE inﬂation looked
good in the fourth quarter, November’s 0.0 percent change was what drove the results. To judge from a broad array
of inﬂation estimators, the underlying CPI inﬂation trend seems to be in the range of 2 percent to 2-1/2 percent.
Core goods prices have been ﬂat lately, a sign that rising service prices are carrying the inﬂation impulse. Core service
prices, which comprise about half of the CPI, have been increasing at a 3.7 percent rate over the last 12 months.
To increase the diﬃculty of interpreting trend inﬂation, the distribution of the component price changes has been
unusually bimodal for the past year. For example, on an expenditure-weighted basis, the prices of most CPI components in December either declined or rose at rates greater than 3 percent. Hardly any prices increased at the arithmetic average rate.
Movements in inﬂation rates over short periods of time, even a year or two, are heavily inﬂuenced by the process
through which price shocks aﬀect individual markets. Over time, however, inﬂation conforms to the rate of money
3

growth set by the Federal Reserve as well as by the process that governs inﬂation expectations. Surprisingly little is
known about the mechanism for transmitting monetary impulses through the structure of relative prices. We might
expect inﬂationary episodes to vary according to diﬀerences in labor, product, and ﬁnancial markets at various points
in time, as well as on diﬀerences in people’s beliefs about future inﬂation.
At the end of its last meeting, the FOMC issued a statement announcing its decision to maintain the federal funds
target at 5-1/4 percent, along with a brief description of its rationale. The statement concluded by reiterating a point
the FOMC has been making since last June, namely, that some inﬂation risks remain. Inﬂation has not worsened
since then, an outcome that was still in doubt at the time, but it has not convincingly improved either. Worries exist
in two directions—that the rate will edge back up, and that the rate will fail to edge down.
But let’s put these concerns in perspective. What about the prospects of inﬂation becoming unacceptably high? Fortunately, very few are worried about that!

Inﬂation and Prices

December Price Statistics
01.31.07
By Michael Bryan and Linsey Molloy

December Price Statistics
Percent change, last
5yr.a

2005
avg.

1mo.a

3mo.a

6mo.a

12mo.

All items

6.7

0.2

0.5

2.5

2.7

Less food and energy

2.3

1.4

2.0

2.6

2.0

2.6

Medianb

3.5

3.4

3.6

3.7

2.7

3.7

16% trimmed meanb

2.8

1.6

2.2

2.6

2.2

2.7

11.8

5.1

0.1

1.2

3.2

1.9

2.3

1.3

2.0

1.2

2.2

Consumer prices

Producer prices
Finished goods
Less food and energy

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.

Retail price growth in December suggests that the
inﬂation trend remains steady at around 2 to 2-1/2
percent. The Consumer Price Index (CPI) picked
up for the ﬁrst time in three months during December, rising 6.7 percent (annualized). Energy
prices, which declined in each of the proceeding
three months, jumped about 72 percent during the
month. The CPI excluding food and energy prices,
commonly known as the Core CPI, rose at a solid
2.3 percent annualized rate, near its 6-month and
12-month averages. Meanwhile, the median CPI
and the 16% trimmed-mean CPI rose 3.5 and 2.8
percent, respectively, also in the neighborhood of
their recent trends.
Underlying the longer-term patterns in the retail
price measures has been a widening gap between
the prices of services, which have been advancing
strongly, and goods prices, which have been ﬂat (or
declining). Core services, which account for over
half of the overall CPI, have risen about 3.7 percent
over the past 12 months—up about 3/4 percentage
point from the average of the previous several years.
However, core goods prices, which account for a bit
over one-ﬁfth of the overall index, were essentially
unchanged over the past 12 months, roughly a 1/2
4

CPI, Core CPI, and
Trimmed-mean CPI Measures

percentage point lower than the average growth
between 2004 and 2005.

12-month percent change

Indeed, the CPI in 2006 exhibited a rather unusual
distribution of component price changes. Over
20 percent of the items in the index, on average,
posted increases that were relatively modest (20
percent actually declined), while prices for over 55
percent of the items, on average, rose at a relatively
elevated rate in excess of 3 percent. It is not particularly strange that price changes in the consumer
market basket would show some extreme variation,
but it is unusual that so few (roughly 7 percent last
year) would show an increase in the neighborhood
of what is considered “average”—between 2 and 3
percent.

4.75
4.50
4.25
4.00
3.75
3.50
3.25
3.00
2.75
2.50
2.25
2.00
1.75
1.50
1.25
1.00
1995

Median CPI

CPI

16% trimmed-mean CPI
1997

1999

C ore C P I

2001

2003

2005

2007

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

Core Goods and Core Services
12-month percent change
9
8
7
6
C ore s ervic es
5
4
3
2
1
0
-1
-2
-3
-4
1-month
-5
annualized percent change
-6
1995
1997
1999

1-month annualized
perc ent c hange

In time, we would expect to see more concordance
in the price data about where they are headed, and
economists are projecting that the growth rate of
the CPI will settle in at a pace a little lower than
what we saw in 2006. At this point, however, the
price data are not showing a very consistent reading
on where the inﬂation momentum is headed.

C ore goods
2001

2003

2005

2007

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

Average of the CPI Component Monthly
Price-Change Distributions, 2006
Weighted frequency
50
45
40
35
30
25
20
15
10
5
0
<0

0 to 1

1 to 2
2 to 3
3 to 4
4 to 5
Annualized monthly percent change

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

Money, Financial Markets, and Monetary Policy

Monetary Policy Stays Put
02.07.07

Reserve Market Rates

By Guillaume Rocheteau

Percent
8
7

Effective federal funds rate

6
5
Primary credit rate b
4
3
2
1

Discount rate b

Intended federal funds rate b

0
2000

2001

2002

2003

2004

2005

2006

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.

Real Federal Funds Rate*
Percent

On January 31, 2006, the Federal Open Market
Committee voted to leave the federal funds target
rate at 5.25 percent for the ﬁfth consecutive time.
The primary credit rate has also been maintained
at 6.25 percent. In its press release, the Committee
explained that its decision to maintain the status
quo was based on the fact that “readings on core
inﬂation have improved modestly in recent months,
and inﬂation pressures seem likely to moderate over
time.” But it also noted that “some inﬂation risks
remain” due to “ﬁrmer economic growth” and a
“high level of resource utilization.” The next meeting is scheduled for March 21.
The real federal funds rate--deﬁned as the eﬀective
federal funds rate less core inﬂation in personal
consumption expenditures (PCE)--remains stable
at 2.96 percent. Since January 2004, it has gained
3.61 percentage points.

6.0

The monetary authorities’ decision to leave their
key interest rate unchanged hardly came as a surprise. At the close of business on January 30, the
Chicago Board of Trade’s federal funds rate futures
revealed that investors were assigning a 98 percent chance to the possibility that the Committee
would leave the target rate unchanged, and a mere
2 percent probability that the Committee would
decrease the rate by 25 basis points, from 5-1/4
percent to 5 percent.

5.0
4.0
3.0
2.0
1.0
0.0
-1.0
-2.0
2000

2001

2002

2003

2004

2005

2006

*Defined as the effective federal funds rate deflated by the core PCE.
Shaded bars represent periods of recession.
Source: 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; Federal Reserve Bank of Philadelphia; and Bloomberg Financial Information Services.

Implied Probabilities of Alternative Target
Federal Funds Rates January Meeting
Outcome*
Implied probability
1.0
0.9
5.25%
0.8
0.7
0.6
0.5
0.4
5.50%
0.3
0.2
5.00%

0.1
0.0
09/22

10/06

10/20

11/03

11/17

12/01

12/15

12/29

01/12

01/26

*Probabilities are calculated using trading-day closing prices from options
on January 2007 federal funds futures that trade on the Chicago Board of
Trade.
Source: Chicago Board of Trade; and Bloomberg Financial Services.

Implied Probabilities of Alternative
Target Federal Funds Rates March
Meeting Outcome*
Implied probability
1.0
4.75%
0.9
5.00%
5.25%
0.8
5.50%
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.0
11/15

12/1

2/1

*Probabilities are calculated using trading-day closing prices from options on January
2007 federal funds futures that trade on the Chicago Board of Trade.
Sources: Chicago Board of Trade; and Bloomberg Financial Services.

Since the end of 2006, investors in federal funds
futures have revised their estimates of the likelihood of monetary policy softening in the very
near future considerably. In mid-November 2006,
they viewed a rate cut by March 2007 as almost as
probable as a rate hike or no change. By the beginning of December, the probability of a cut (to 5
percent or 4.75 percent) had climbed to more than
50 percent, thanks to steady inﬂation numbers and
some signs of slowing economic activity (such as
GDP growth). Since then, new data have been released indicating both inﬂation risks and sustained
economic activity, and at its latest meeting, the
Federal Open Market Committee reaﬃrmed that
“the extent and timing of any additional ﬁrming
that may be needed to address [inﬂation] risks will
depend on the evolution of the outlook for both
inﬂation and economic growth.” As a consequence,
the probability of a federal funds rate target at 5
percent or below has fallen dramatically, and investors now view a federal funds rate at 5.25 percent
the most likely event, with a probability above 90
percent.
Similarly, at the beginning of January 2007, the
probability of an interest rate cut to 4.75 percent
or 5 percent by June 2007 was close to 50 percent.
Within a month, this probability had fallen below
20 percent. Currently, investors in federal funds futures believe that interest rates will stay unchanged
until the middle of the year, with a probability of
close to 2/3.
As the Committee emphasized in its press release,
“the evolution of the outlook for both inﬂation
and economic growth” are considered when determining the target federal funds rate. The Federal
Reserve monitors price level indices such as the personal consumption expenditure (PCE) deﬂator and
the consumer price index (CPI), and it tightens its
policy when inﬂation risks build up. For instance,
the sequence of 17 rate hikes after June 2004 followed increases in the core PCE and core CPI of
0.7 and 0.8 percentage points, respectively, in the
ﬁrst half of 2004. Since August 2006, core PCE
inﬂation has decreased from 2.44 percent to 2.22
7

Implied Probabilities of Alternative Target
Federal Funds Rates June Meeting
Outcome*
Implied probability
0.8
4.75%
5.00%
0.7
5.25%
5.50%
0.6
0.5
0.4
0.3
0.2
0.1
0.0
1/9

2/1

* Probabilities are calculated using trading-day closing prices from options on January
2007 federal funds futures that trade on the Chicago Board of Trade.
Sources: Chicago Board of Trade; and Bloomberg Financial Services.

Fed Funds Rate and Employment
Percent
7

Millions, seasonally adjusted
140

6
Effective federal funds rate

138

The Committee also considers its objective to
promote eﬀectively maximum employment when
determining the stance of monetary policy. The increase in interest rates since the second half of 2004
has accompanied the steady tightening of the labor
market. Since the beginning of 2004, the economy
has posted large employment gains, approximately
188 thousand workers per month on average. During the same period, the unemployment rate fell
from 5.7 percent to 4.6 percent, indicating a high
utilization of input factors. Despite higher interest rates, economic activity remains strong. From
November 2006 to January 2006, employment
increased from 136.9 million to 137.3 million, and
real GDP grew at 3.5 percent (in annualized terms)
over the last quarter of 2006. The economy has
added an average of 171 thousand jobs per month
since November.

136

4
Employment

134

132

130

128

0
2001

percent, and core CPI inﬂation has decreased from
about 2.83 percent to 2.61 percent. The expectation that these core inﬂation rates would continue
to fall to some acceptable levels warranted a pause
in the policy of interest rate hikes in 2006.

126
2002

2003

2004

2005

2006

2007

a. Monthly average of daily figures.
b. Total nonfarm payroll employment.
Sources: Board of Governors of the Federal Reserve System, “Selected Interest Rates,”
Federal Reserve Statistical Releases, H.15; and the U.S. Department of Labor, Bureau
of Labor Statistics.

Federal Funds Rates and PCE Inflation

Fed Funds Rate and Unemployment

Percent
3.5

Percent
7

3.0
Core CPI

2.5
Core PCE

2.0

b
Unemployment Rate

1.5

Effective federal funds rate
1.0
0.5
Effective Fed Funds Rate

0.0
2001

2002

2003

2004

2005

2006

2007

a. Monthly average of daily figures.
b. PCE is Personal Consumption Expenditures; core PCE is less food and energy;
monthly observations; year-over-year percent change.
c. CPI less food and energy; monthly observations; year-over-year percent change.
Sources: Board of Governors of the Federal Reserve System, “Selected Interest
Rates,” Federal Reserve Statistical Releases, H.15; and the U.S. Department of
Commerce, Bureau of Economic Analysis.

2001

2002

2003

2004

2005

2006

a. Monthly average of daily figures.
b. Civilians over 16 years of age; seasonally adjusted.
Sources: Board of Governors of the Federal Reserve System, “Selected Interest Rates,” Federal Reserve Statistical Releases, H.15;
and the U.S. Department of Labor, Bureau of Labor Statistics.

Money, Financial Markets, and Monetary Policy

Monetary Aggregates
01.02.07
By Guillaume Rocheteau
According to Milton Friedman’s famous aphorism,
“inﬂation is always and everywhere a monetary
phenomenon.” A look at the data on inﬂation and
the growth of the money supply across countries
suggests that the two are indeed very closely related: The correlation between inﬂation and average M2 growth in 132 countries over the period
1960–2000 is close to one (0.86), suggesting that
prices move almost proportionally with the stock of
money. And yet the Federal Reserve stopped reporting the broadest monetary aggregate, M3, last year,
and the time has long since past that it reported
growth rate targets for money aggregates.

Money Growth and Inflation*
Inflation
100
90
80
70
60
50
40
30
20
10
0
0

60
Money growth

100

*This chart has been adapted from George T. McCandless and
Warren E. Weber, “Some Monetary Facts,” Federal Reserve Bank of
Minneapolis, Quarterly Review, vol. 19 (1995), pp. 2-11.
Source: International Monetary Fund, “International Financial Statistics,” December 2006.

Irving Fisher formulated the notion of the almostproportional relationship between money and
prices as the equation of exchange. Loosely speaking, the equation states that the amount of money
in the economy multiplied the number of times
that money changes hands in a given period (this
number is referred to as the velocity of money)
must be equal to the value of the transactions con9

ducted in the same period. Fisher’s equation is true
by construction; it doesn’t tell you much until you
make additional assumptions. If we assume velocity
and the volume of transactions are roughly constant
over some period of time, for instance, the equation
says the relationship between money and prices will
be proportional.

U.S. Money Demand
M1/GDP
0.6
0.5
1900–1959

0.4
0.3

1960–1982
0.2
1983–2000

0.1
0.0
0

5
10
Interest rate, commercial paper

Sources: Robert Lucas. 2000. “Inflation and Welfare,” Econometrica,
vol. 68, pp. 247–74; and Ben Craig, and Guillaume Rocheteau. 2006.
“Inflation and Welfare: A Search Approach,” Federal Reserve Bank of
Cleveland, Policy Discussion Paper, no. 12.

Velocity of M1* in the United States
over the Last Century
GDP/M1*
16
14
12
10
8
6
Trend velocity
4
2

Velocity M1*

0
1892

1906

1920

1934

1948

1962

1976

1990

2004

Source: Miquel Faig and Belen Jerez, “Precautionary Balances and
the Velocity of Circulation of Money,” Journal of Money, Credit, and
Banking (forthcoming, 2006).

Economists used to assume that velocity was, in
fact, fairly constant over time, or that it varied with
other factors in predictable ways. The evidence we
have now suggests this used to be the case but is
no longer. If we look at one measure of the money
supply, M1* (which is M1 minus the value of
currency circulating abroad and is used because a
sizable fraction of U.S. currency is held abroad), we
see that its velocity of circulation (nominal GDP
divided by M1*) has changed over the past century.
Until 1960, velocity varied around a constant mean
of less than 4, but thereafter it has increased signiﬁcantly. If velocity is variable and unpredictable, the
relationship between money and prices is diﬃcult
to characterize, and monetary aggregates can’t help
policymakers track inﬂation.
Nominal interest rates can aﬀect velocity. To see
how, think about the ﬂip side of velocity. Flipping
over the measure of velocity we looked at above, we
get the supply of money over nominal GDP, which
is a measure of money demand (that is, money
balances held by individuals). Theories of money
demand predict that demand declines with the opportunity cost of money, measured by the nominal
interest rate of commercial paper, because a higher
opportunity cost of holding money induces people
to economize on their money balances relative
to spending. Over the twentieth century, in fact,
the relationship between interest rates and money
demand has been negative in the United States.
Unfortunately, the relationship does not appear to
be stable over time. The demand for money balances was higher in the 60s and 70s than it was in the
80s and 90s, and in the ﬁrst half of the twentieth
century it was higher still. Furthermore, since the
beginning of the 80s, money demand has become
less sensitive to changes in the interest rate. (Graphically, it has ﬂattened out.) Because interest rates
don’t aﬀect money demand (or its inverse, velocity)
in a predictable way over time, measures of money
10

Composition of the Money Supply
Percent, monthly data (seasonally adjusted)
100
90

Non-M2 components of M3

80
70
60
Non-M1 components of M2

50
40
30
20
10

0
1959 1964 1969 1974 1979 1984 1989 1994 1999 2004
Source: Federal Reserve Bank of St. Louis, “Monetary Aggregates,”
FRED database.

Composition of the Monetary
Aggregates
Percent of M3
100
90

Large time deposits

can be misleading as sources of information about
future prices.
One explanation for why the relationship between
money demand and interest rates might have
changed is that the assets included in M1 (currency
and checkable deposits) no longer capture households’ transactions balances accurately. Deregulation and ﬁnancial innovation have led to new
ﬁnancial products (such as money market deposit
accounts and money market mutual funds) that
are not included in M1 but can readily be transformed into means of payments. As such, they are
close substitutes to the assets in M1. For instance,
the fact that individuals can transfer funds from
non-interest bearing checking accounts to savings accounts at a high frequency has reduced the
relevance of M1. The lesser importance of M1 is
reﬂected in its declining share in M3. The share
of checkable deposits in M3 has declined steadily
over time while the share of money funds has been
increasing.

80
70

Small time deposits
Institutional money funds

60
50

Savings deposits

Retail money funds

30
20
10

Currency component of M1

Total checkable deposits

0
1959 1964 1969 1974 1979 1984 1989 1994 1999 2004
Source: Federal Reserve Bank of St. Louis, “Monetary Aggregates,”
FRED database.

Is the velocity of circulation of other monetary
aggregates more stable than the velocity of M1?
In fact, the velocities of M2 and M3 have gone
through substantial swings, too. While the velocity of M2 appeared to be fairly stable until the end
of the 80s, it increased sharply from the beginning of the 90s until 1997 and fell abruptly in the
subsequent ﬁve years. The velocity of M3 declined
steadily until the mid 80s, increased from 1987
to 1995, and fell again from 1995 to 2003. These
movements cannot be explained by changes in
nominal interest rates only. Again, deregulation and
ﬁnancial innovation that make portfolio readjustments among monetary assets easier have played a
role.
The instability of velocity notwithstanding, can
the changes in the rate of growth of money supply
help predict the future changes in the inﬂation rate?
Changes in money growth rates predict fairly well
changes in the inﬂation rate that occur two years
later—until the end of the 70s. Since then, ample
movements in the money supply do not appear
to predict accurately either the magnitude or the
direction of future changes in the inﬂation rate. As

a result, monetary aggregates cannot be used alone
to predict or control inﬂation.

Rate of Growth of M2 and Prices
Percent change, yearly averages
14

But as Chairman Ben Bernanke indicated on
November 10, 2006: “although a heavy reliance
on monetary aggregates as a guide to policy would
seem unwise in the U.S. context, money growth
may still contain important information about
future economy developments. Attention to money
growth is thus sensible as part of the eclectic modeling and forecasting framework used by the U.S.
central bank.”

12
M2
10
8
6
4
2
Core CPI lagged two years back
0
1957

1963

1969

1975

1981

1987

1993

1999

2005

Sources: Federal Reserve Bank of St. Louis, “Monetary Aggregates,”
FRED database; and the Bureau of Labor Statistics.

Rate of Growth of M3 and Prices
Percent change, yearly averages

Velocity of Circulation of M2 and M3
Ratio, quarterly data (seasonally adjusted)
2.2

16
M3
14

2.0
12

GDP/M2
1.8

10
8

1.6

6
1.4
4

GDP/M3
Core CPI lagged two years back

1.2

1.0

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005
Source: Miquel Faig and Belen Jerez, “Precautionary Balances and
the Velocity of Circulation of Money,” Journal of Money, Credit, and
Banking (forthcoming, 2006).

1959 1964 1969 1974 1979 1984 1989 1994 1999 2004
Source: Federal Reserve Bank of St. Louis, “Monetary Aggregates,”
FRED database; and the Bureau of Economic Analysis.

Rate of Growth of M1 and Prices
Percent change, yearly averages
16
14
Core CPI
lagged two years back

10
8
6
4
2
0
-2
-4
-6
1958 1963 1968 1973 1978 1983 1988 1993 1998 2003
Sources: Federal Reserve Bank of St. Louis, “Monetary Aggregates,”
FRED database; and the Bureau of Labor Statistics.

Money, Financial Markets, and Monetary Policy

What Is the Yield Curve Telling Us?
01.16.07
by Joseph G. Haubrich and Brent Meyer

Yield Spread and Real GDP Growth
Percent
12
R eal G DP growth
(year-to-year perc ent c hange)

10
8
6
4
2
0
-2

10-year – 3-month yield spread
-4
1953 1958 1963 1968 1973 1978 1983 1988 1993 1998 2003
*Shaded areas represent recessions.
Sources: Department of Commerce, Bureau of Economic Analysis;
Board of Governors of the Federal Reserve System.

Yield Spread and
Lagged Real GDP Growth
Percent
12
10

One year lagged real GDP growth
(year-to-year percent change)

8
6
4
2
0
-2
Yield spread: 10-year Treasury – 3-month Treasury yield
-4
1953 1958 1963 1968 1973 1978 1983 1988 1993 1998 2003

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

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.
Lately, the yield curve has some forecasters worried. One reason for concern is that the spread is
currently negative: with 10-year rate at 4.66 percentand the 3-month rate at 5.05 percent(both for
the week ending January 5), the spread stands at
a negative 39 basis points, and indeed has been in
the negative range since August. Projecting forward
using past values of the spread and GDP growth
suggests that real GDP will grow at about a 1.6
percentrate over the next year.
While such an approach predicts when growth is
above or below average, it does not do so well in
predicting the actual number, especially in the case
of recessions. Thus, it is sometimes preferable to
focus on using the yield curve to predict a discrete
event: whether or not the economy is in recession.
Looking at that relationship, the expected chance of
a recession in the next year is 43 percent.
UPDATE (02.01.07): 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
13

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.

Probability of Recession
Based on Yield Spread*
Percent
100
90

Probability of
recession

80
70
60

Forecast

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?”

40
30
20
10
0
60

*Estimated using probit model.
Sources: Department of Commerce, Bureau of Economic Analysis;
and Board of Governors of the Federal Reserve System.

Yield Spread and Predicted GDP Growth
Percent
6
5

R eal G DP growth
(year-to-year percent change)

4
3
P redic ted
G DP growth

2
1
0
-1

Yield s pread: 10-year Treasury – 3-month Treasury

-2
Dec-01

Dec-02

Dec-03

Dec-04

Dec-05

Dec-06

Dec-07

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

International Markets

China’s Economy
02.02.07
by Owen F. Humpage and Michael Shenk

Real GDP Growth*
Percent change
16
14
12
10
8
6
4
2
0
1979 1982 1985 1988 1991 1994 1997 2000 2003 2006
*2006 preliminary National Bureau of Statistics.
Source: National Bureau of Statistics of China; Haver Analytics.

Consumer Price Inflation
Percent change, year over year
12
10
8
6
4
2
0
-2
-4
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006
Source: National Bureau of Statistics of China; Haver Analytics

Sterilization of Reserve Flow

China’s economy expanded 10.7 percent in 2006,
its fastest rate of growth in eleven years, due to
strong exports and investment spending. The pace
was somewhat faster than most observers had anticipated and occurred despite Chinese attempts to
cool the economy through selective credit controls.
Chinese planners apparently view the current rate
of economic growth as too fast and destined to run
up against capacity constraints—notable in electricity generation. Economists anticipate slower growth
this year, around 9-1/2 percent, but a year ago,
economists issued the same prediction for 2006.
Despite the rapid economic growth and concerns
about building price pressures, inﬂation in China
has remained fairly subdued. Last year, consumer
prices advanced only about 1.6 percent on average.
One thing that might help limit inﬂationary pressures in China is allowing the renminbi to appreciate faster against the dollar. Under its peg and
subsequent limited ﬂoat, China has accumulated a
huge portfolio of foreign exchange, mostly dollars.
All else constant, China’s monetary base should
keep pace with its reserve accumulation, but the
Peoples Bank of China has oﬀset (sterilized) roughly one-half of the impact since early 2001 by selling
bonds to the market. This cannot continue indeﬁnitely. Greater exchange rate ﬂexibility would help
limit China’s reserve accumulation.

Trillions of yuan
2
1.8
1.6

Four-quarter change in foreign exchange reserves a
Four-quarter change in monetary base a

1.4
1.2
1
0.8
0.6
0.4
0.2
0
1995

1997

1999

2001

2003

2005

a: 2006 data is for the third quarter.
Source: International Monetary Fund, International Financial Statistics.

International Markets

Japanese Monetary Policy
01.31.07
By Owen F. Humpage

Japanese Overnight Call-Money Rate
Percent
4.5

The Bank of Japan left its operating target, the uncollateralized overnight call rate, unchanged at 0.25
percent in January. Observers expect that the bank’s
next move will be upward. The timing of any move
remains uncertain and depends on the outlook for
economic activity and prices.

4
3.5
3
2.5
2
1.5
1
0.5
0
-0.5
1992

1994

1996

1998

2000

2002

2004

2006

Source: Bloomberg Financial Information Services.

Consumer Price Inflation, Japan
Percent change, year over year
5
4

CPI

3
2
CPI less fresh foods
1
0
-1
-2
1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
Sources: Bank of Japan, Ministry of Internal Affairs and
Communications; and Haver Analytics.

The Japanese economy, which grew at a modest
pace over the last couple of years, slowed in 2007:
IIIQ as consumer spending dropped precipitously.
Most economists expect its growth to continue at
approximately 2 percent this year. That rate seems
slightly faster than Japan’s potential for economic
growth, implying persistent, yet very moderate,
upward price pressure. The inﬂation rate probably
will not exceed 0.5 percent on a year-over-year basis
in 2007. The Bank of Japan maintains an informal
inﬂation target of 0 percent to 2 percent for core
inﬂation. An inﬂation rate of 0.5 percent, however,
would leave the real overnight call rate negative.
On March 9, 2006, the Bank of Japan announced
an end to its quantitative easing policy. Under that
operating procedure, the Bank of Japan set a target
for current account balances—essentially, non-interest-bearing reserve deposits that ﬁnancial institutions maintain at the Bank of Japan. Between 2004
and 2006, the procedure left substantial amounts
of excess reserves in the Japanese ﬁnancial system.
These reserves have since dissipated, allowing Japanese short rates room to rise somewhat.

Average of the CPI Component Monthly
Price-Change Distributions, 2006
Weighted frequency
50
45

Reserve Balances
Trillions of yen
40
Current account target range
35
30

Current account
balances

25
20

Excess reserve balances

3/2001

5
0

3/2002

3/2003

3/2004

3/2005

3/2006

Source: Bank of Japan, Ministry of Internal Affairs and Communication.
<0

0 to 1

1 to 2
2 to 3
3 to 4
4 to 5
Annualized monthly percent change

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

International Markets

The Yen Carry Trade
01.31.07
By Owen F. Humpage

Japanese Yen vs. Australian Dollar
Yen per Australian dollar
100
95

Percent
7
6.5

Interest rate differential a

5.5

Spot exchange rate

4.5
4

3.5

2.5

50
1999

2000

2001

2002

2003

2004

2005

2006

a: Australian 3-month interbank rate minus Japanese 3-month
interbank rate.
Source: Bloomberg Financial Information Services

2
2007

The yen carry trade carries on. International investors borrow yen at extremely low Japanese interest
rates and invest (carry) the funds in higher yielding,
foreign-currency assets for a proﬁt. The Australian dollar, the New Zealand dollar, and the U.K.
pound are frequent target currencies for the yen
carry trade. Carry-trade investors typically remain
exposed to foreign-exchange risk. Consequently,
many observers fear that if the Bank of Japan raises
interest rates, the carry trade might unwind rapidly
with repercussions in global currency markets.
Persistent carry-trade proﬁts seem an economic
anomaly. Suppose, for example, that an investor
borrows Japanese yen at a low interest rate for three
months and places it in a higher-yielding Australian three-month instrument. All else constant, this
arbitrage should bid up Japanese interest rates and
bid down Australian interest rates until the proﬁt
opportunity disappears. The process, however, is
even more complicated. Arbitrage also alters two
exchange rates—the spot Japanese yen-Australian
dollar rate and the rate three months hence. The
spot yen will depreciate as investors convert their
borrowed yen to dollars, and yen will appreciate
17

Japanese Yen vs. British Pound
Percent
6.5

Yen per British pound
240
230
Interest rate differential

220

5.5

210

200

4.5

190

180

3.5
3

170
Spot exchange rate

2.5

160
150
1999

2000

2001

2002

2003

2004

2005

2006

2
2007

a. British pound 3-month interbank rate minus Japanes 3-month interbank
rate.
Source: Bloomberg Financial Information Services

three months hence as investors go back into yen to
repay their loans. Arbitrage will wipe out any proﬁt,
and any persistent interest-rate diﬀerential will be
lost in currency conversions. Or so theory suggests.
But other things are not necessarily constant. Empirically, this pattern has not happened, as Federal
Reserve Bank of San Francisco economist Michele
Cavallo points out. The currencies of countries with
low interest rates have tended to depreciate, or to
not appreciate suﬃciently to oﬀset arbitrage opportunities. This fuels the carry trade and also the
fear that a Japanese interest-rate hike might rapidly
reverse the yen carry trade.

Japanese Yen vs. New Zealand Dollar
Yen per New Zealand dollar
90

Percent
8
7.5

80
Spot exchange rate

6.5

5.5

Interest rate differential a

4.5

4
3.5

0
1999

2000

2001

2002

2003

2004

2005

2006

2007

a. New Zealand 3-month interbank rate minus Japanese 3-month
interbank rate.
Source: Bloomberg Financial Information Services.

Economic Activity and Labor Markets

Employment during the Recovery
02.07.07
By Peter Rupert and Cara Stepanczuk
As business cycles go from expansions to recessions,
employment and production mirror their trends,
increasing during expansions and decreasing during
recessions at roughly the same rates.

Business Cycle Pattern:
Nonfarm Employment
Percent change from previous peak
9.5
8.0

Average range

6.5
Average change

5.0

2001-2007
revised

3.5
2.0

2001-2007
unrevised

0.5
-1.0
-2.5
0

10 15 20 25 30 35 40 45 50 55 60 65 70

In contrast, employment during the recovery has
been far from normal. It got oﬀ to a good start at
the peak of the expansion, and was still ahead of
the curve at the trough in 2001. After 15 months,
though, employment failed to pick up as fast as
it should have. Because it stayed relatively ﬂat for
an extended period of time, employment took 45
months to regain its pre-recession level.

Months from previous peak
Source: U.S. Department of Labor, Bureau of Labor Statistics.

Business Cycle Pattern: Real GDP
Percent change from previous peak
24
20
16
12

Average range

Average change

4
2001-2007
0
-4
0

In terms of production growth, the current expansion (2001–07) has been fairly typical. Measured
by GDP, the trough of the business cycle was not as
deep as normal; in fact, it barely scraped the upper
bound of the average range. The recovery phase
for 2001–07 is within the average range, but falls
below average growth after eight months.

Quarters from previous peak
Source: U.S. Department of Labor, Bureau of Labor Statistics.

The glaring diﬀerence between nonfarm employment for 2001–07 and the average employment
growth after a recession cannot be explained by
an atypical recession or recovery; real GDP stayed
within normal bounds throughout the cycle. Nor
can it be explained by the unusually large benchmark revisions in nonfarm employment for April
2005 through March 2006 (seasonally adjusted
from 2002 onward) from the BLS; even the upwardly revised data show employment far below ordinary levels. Thus, the current expansion remains a
“jobless recovery.”

Economic Activity and Labor Markets

The Employment Situation
02.05.07

Average Monthly Nonfarm
Employment Change

By Peter Rupert and Cara Stepanczuk
Nonfarm payrolls increased by 110,000 net jobs in
January, down from December and about 40,000
lower than expected—a muted start to the year.
However, 2006 ended with a bang: November
and December payrolls were revised upward a net
103,000 jobs, raising the fourth quarter’s average
monthly increase to 170,000.

Change, thousands of workers
300
270

Revised
Previous estimate

240
210
180
150
120
90
60
30
0
2003 2004 2005 2006 IQ

IIQ

IIIQ IVQ Nov Dec Jan

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

Labor Market Conditions
Average monthly change
(thousands of employees, NAICS)
Jan.-Dec.
2006

2004

Payroll employment

172

212

187

111

Goods-producing

–42

Construction

Manufacturing

–51

–7

–16

Durable goods

–32

–1

–28

Nondurable goods

–19

–9

–6

Service-providing

144

180

178

104

Retail trade

–4

PBS**

Temporary help svcs.

–1

5.7

Education and health
svcs.

Leisure and hospitality

Government

–4

Financial activities*

2005

Jan.
2007

2003

Average for period (percent)
Civilian unemployment rate

6.0

5.5

5.1

4.6

*Financial activities include the finance, insurance, and real estate sector and
the rental and leasing sector.

** 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.

Service-providing industries continue to contribute
the most jobs (104,000 in January), but have lost a
lot of steam since the 2006:IVQ average contribution of 205,000 jobs. Education and health services
grew the most over the month, adding 31,000 net
jobs. Professional and business services grew by
25,000, and leisure and hospitality grew by 23,000.
Construction’s 22,000 payroll increase helped
goods-producing industries post their ﬁrst net
monthly gain since August 2006. However, weakness in motor vehicles and parts; computers and
electronics; furniture; and textiles caused a net loss
of 16,000 manufacturing jobs.
The employment situation was dramatically altered
by the BLS’s annual benchmark revision from April
2005 to March 2006 (seasonally adjusted data were
revised from 2002 onward). Whereas the average
revision over the prior 10-year period was +/–0.2
percent, this year’s was 0.6 percent, which translated into an increase of 752,000 jobs.
Although no sector changed signiﬁcantly more
than others, there were a few notable industries.
Professional and business services posted the largest upward revision, up 230,000 jobs (1.3 percent
growth). Construction also changed for the better,
reporting a net gain of 189,000 jobs (2.6 percent
growth). Trade, transportation, and utilities pitched
in another 158,000 jobs (0.6 percent growth).
However, the revisions showed that the manufacturing sector did worse than previously thought,
losing an additional 21,000 jobs (–0.1 percent

Percent Differences between
Nonfarm Benchmarks
Percent
0.7
0.6
0.5
0.4
0.3

Average percent difference

0.2
0.1
0.0
-0.1
-0.2

Average percent difference

-0.3
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006
Source: U.S. Department of Labor, Bureau of Labor Statistics.

Highest and Lowest
March 2006 Revisions
Jobs, thousands
250

growth). The information industry did not weather
the storm of revisions, either; it lost 15,000 (–0.5
percent growth).
The BLS has oﬀered several reasons for the extreme
revisions. Employment estimates for September–
October 2006 (post–Hurricane Katrina) allowed
more error than usual. Only part of the error was
associated with the model-based estimation process
for employment in new establishments, the typical
source of annual revisions. Most of the employment revisions resulted from an “accumulation” of
smaller sources of error, according to the BLS.
The household survey was also adjusted for population controls, but the update applies only to 2007
data. Even with the adjustment, the unemployment
rate, labor force participation rate, and employment-to-population ratio were essentially unchanged in January.

200
150
100
50
0
-50
Construction

PBS

TTU

Manufacturing Information

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

Economic Activity and Labor Markets

Employment Cost Index
02.02.07
by Tim Dunne and Brent Meyer

ECI: Civilian Workers
Year-over-year percent change
8
Benefits

7
6
5

Compensation

4
3
Wages and salary

2
1

0
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006
Source: U.S. Department of Commerce, Bureau of Labor Statistics.

ECI: Compensation
Year-over-year percent change
6
5

Private industry workers

3
2

State and local
government workers

1
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006
Source: U.S. Department of Commerce, Bureau of Labor Statistics.

ECI: Private vs. Government
Year-over-year percent change
8
Private industry workers: benefits
7
6
5

Private industry
workers: wages
and salary

The Employment Cost Index (ECI), which measures the changes in employers’ wage, salary, and
beneﬁt costs, closed out 2006 showing moderate
growth. For the entire year, total compensation rose
3.3 percent, wages and salaries rose 3.2 percent,
and beneﬁts rose 3.6 percent. Wages and salaries increased slightly more than they did in 2005, while
beneﬁts increased less. Indeed, beneﬁts rose less in
2006 than in any year since 1999.
The past two years have witnessed some divergence
in employment costs for workers in the private and
public sectors. Compensation costs for state and
local government workers grew at an average rate of
4.1 percent in the past two years, whereas private
sector employment costs increased only 3.0 percent.
Employment cost patterns are diﬀerent in the private and public sectors mainly because beneﬁt costs
are increasing less in the private sector. Unlike salary and wage growth, beneﬁts growth across the two
sectors has not tracked closely over time. In the last
three years, the growth in beneﬁt costs for private
sector workers has fallen substantially; however,
the fall in public sector beneﬁt costs since 2004 has
been considerably more muted, and currently, the
growth of public sector beneﬁt costs exceeds private
sector growth by two percentage points.
ECI growth also varies across U.S. regions. From
2004 to 2006, the Midwest experienced, on average, the lowest growth in employment costs in the
nation while the Northeast had the highest.

4
3
2
1

Government workers: benefits

Government workers:
wages and salary

0
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006
Source: U.S. Department of Commerce, Bureau of Labor Statistics.

Employment Cost Index*:
Compensation by Census Region
Annualized percent change
6
2004
2005
5
2006
4
3
2
1
0

Northeast

South

Midwest

West

-1
-2
*Private workers
Source: U.S. Department of Commerce, Bureau of Labor Statistics.

Economic Activity and Labor Markets

High-Technology Manufacturing
01.24.07
By Tim Dunne and Brent Meyer

Industrial Production:
High-Technology Manufacturing

Industrial production of high-technology goods
grew rapidly in 2006. High-tech manufacturing
industries expanded at a 27.3 percent rate during
the year, compared to manufacturing’s overall rate
of 3.0 percent for the industrial sector.

Index (SA, 2002=100)
250
225
200
175

High-technology

150
125

Total

100
75
50
25
1998

2000

Source: Federal Reserve Board.

2002

2004

2006

The High-technology Index measures production
in three information-technology manufacturing industries and computers, communications
equipment, and semiconductors. Recent growth
in semiconductor production easily outpaced that
of computers and communication equipment.
Semiconductors grew at an average annual rate of
35.3 percent in 2005–2006, while computers and
communications equipment expanded at roughly
half that rate.
The prices of high-technology goods continue to
decline. The particularly steep fall in computer
prices is partly a reﬂection of the fact that this price
series controls for quality changes in a wide range
of computer products, whereas the semiconductor
and communications equipment indices contain
fewer quality adjustments. Recent studies (here and
here) suggest that the published price indices for
semiconductor and communications equipment
23

Industrial Production: High-Technology
Producer Price Indexes

shown in the graph understate real price declines.
Nonetheless, it is clear that consumers continue to
beneﬁt from falling prices in all these industries.

Index (SA, 2002=100)
150
140
Computers and peripheral equipment

130
120
110
100
90

Communications equipment
Semiconductors and
related equipment

80
70
60
50
1998

2000

2002

2004

2006

Although high-technology production advanced
markedly in these industries over the last several
years, employment did not. Between 2001 and
2004, these industries shed more than 460,000
workers, a 36.6 percent decline. In the last two
years, employment has stabilized but at a signiﬁcantly lower level than in 2000. Employment
growth in 2005 and 2006 amounted to a net gain
of only 10,000 workers, with the increase occurring
entirely in semiconductors

Source: Department of Labor, Bureau of Labor Statistics.

Industrial Production:
High-Technology Manufacturing Industries
Index (SA, 2002=100)
300
275
250
225
200
175
150
125
100
75
50
25
0
1998

Semiconductors and related equipment

Communications equipment

Computers and peripheral equipment

2000

2002

2004

2006

Source: Federal Reserve Board.

Industrial Production:
High-Technology Employment
Thousands (SA)
Thousands (SA)
800
400
375
700
350
Semiconductors and related
600
325
equipment (right axis)
300
500
275
Computers and peripheral 400
250
equipment
225
300
200
Communications equipment
175
200
150
100
125
100
0
1998
2000
2002
2004
2006
Source: Department of Labor, Bureau of Labor Statistics.

Economic Activity and Labor Markets

Job-to-Job Movers
Contributions to Monthly Employment
Transitions by Age (percent)
Percent
30

Separations (EE+EN+EU) a
Employer-to-employer

Accessions
(EE+NE+UE) b

Employment share

20
15
10
5
0
16-19

20-24

25-35

35-44

45-54

55-64

65 and
over

Age group
a. Total separations consist of three flows: EE Employer-to-employer;
EN Employment-to-not in the labor force; EU Employment-to-unemployment.
b. Total accessions consist of three flows: EE Employer-to-employer;
NE not in the labor force-to-employment; UE Unemployment-to-employment.
Source: Bruce Fallick and Charles Fleischman. "Employer-to-Employer
Flows in the U.S. Labor Market: The Complete Picture of Gross Worker
Flows." Finance and Economics Discussion Series 2004-34. Washington,
D.C.: Board of Governors of the Federal Reserve System, 2004.

Employment Transitions by
Demographic Characteristics
Separations
(EE+EU+EN)

Accessions
(EE+UE+NE)

Female

7.0

2.5

7.1

Male

6.3

2.7

6.2

Nonwhite

7.7

2.6

7.8

White

6.4

2.6

6.5

<High school

12.0

3.4

12.5

High school
diploma

6.6

2.6

6.5

Some college

6.4

2.7

6.5

College degree

4.6

2.3

4.6

>College

3.9

2.0

3.9

Characteristic

01.24.07
By Murat Tasci and Laura Kleinhenz
In a given month, a person’s status relative to the
labor market can fall in one of three categories:
employed (E), unemployed (U) or not in the labor
force (N). The extent of the movement among
these categories provides valuable information
about how well labor markets are functioning. For
instance, though a higher ﬂow from U to E or N
to E implies a larger increase in employment, it
may be the case that not all employed workers have
the jobs that would suit them best. They, and the
national economy overall, might beneﬁt from a
reallocation of workers across existing jobs. Such
reallocations might be achieved eﬃciently through
employer-to-employer (EE) transitions, which
would not force the worker to go through a spell of
unemployment.
A recent study by Bruce Fallick and Charles Fleischman of the Federal Reserve Board documents
in detail the number and characteristics of people
ﬂowing between and within diﬀerent categories of
labor market status. The researchers estimate that
in a given month, 2.6 percent of workers change
their employers without a spell of unemployment.
This employer-to-employer ﬂow of workers, which
constitutes 40 percent of all employer separations,
accounts for more than 3 million job movers each
month.

Gender

Race

Education

Labor market ﬂows also vary by age group. Workers
aged 16 to 19 experience 15.6 percent of all separations and 16.7 percent of all ﬂows into employment (which are sometimes called “accessions”).
These contributions increase with workers’ ages
until their mid-30s. Employer-to-employer ﬂows
follow a similar pattern. Because inexperienced
young workers tend to look for better job matches
early in their careers, the combined contribution
of the two youngest groups to EE ﬂows is almost
double these groups’ employment share.

Gross Flows among Labor Market States
State in first
month

State in second month
(as a percent of state in first month, monthly)
Same
employer

New
employer

Unemployed

Not in the
labor force

93.4

2.6

1.3

2.7

Unemployed

28.3

48.4

23.3

Not in the labor
force

4.8

2.4

92.8

Employed

Source: Bruce Fallick and Charles Fleischman. “Employer-to-Employer
Flows in the U.S. Labor Market: The Complete Picture of Gross Worker
Flows.” Finance and Economics Discussion Series 2004-34. Washington:
Board of Governors of the Federal Reserve System, 2004.

Employer-to-employer ﬂows also change with
demographic characteristics. EE transitions are
responsible for 35 percent of the separations experienced by women and 35 percent of their accessions.
But a greater share of men’s separations and accessions come from EE transitions--44 percent and
42 percent, respectively. Although total ﬂows into
and out of employment are signiﬁcantly higher for
nonwhites, the share of EE ﬂows does not vary with
race. Even though EE ﬂows decrease with education level, the share of EE ﬂows within total separations and accessions rises with education.

Economic Activity and Labor Markets

Some Say Housing Numbers Encouraging
Housing Starts and Permits
Millions of units, annual rate
2.4

2.2

2.0
Permits
1.8
Starts
1.6

1.4
2000

2001

2002

2003

2004

2005

2006

2007

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

Single-Family
Housing Starts and Permits
2.0 Millions of units, annual rate
1.8
1.6
Starts
1.4

01.23.07
By Ed Nosal and Michael Shenk
The housing permits series, which is less volatile
than the housing starts series, tracks housing starts
fairly closely. Both of these series—for single-family units as well as total units—reported sustained
growth from late 2000 until the summer of 2005.
After that, and continuing until recently, all of
these series declined substantially. In 2006, permits
for both single- and multi-unit structures showed
no increase until December, and recent housing
starts have not declined from their October numbers.
Most of the post-war recessions have been characterized by substantial declines in starts and permits.
The most recent recession (2001) is a notable exception, in which starts and permits did not diﬀer
substantially from those observed the previous year.
The recent numbers do not necessarily imply that
the housing-market slide is over; however, many
analysts believe that recent numbers are encouraging and that the housing market may cease to be a
drag on economic activity by the end of 2007:IIQ.

1.2
Permits
1.0
2000

2001

2002

2003

2004

2005

2006

2007

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

Single-Family
Housing Starts and Permits*
Millions of units, annual rate
2.5
2.3
2.1

Starts

1.9
1.7
1.5
1.3
Permits

1.1
0.9

Although residential investment has recently been
rather weak, the other components of GDP have
been relatively robust. To see this, we compare
GDP growth with the same growth rate excluding
residential investment. Note that for 2005:IQ, the
growth rate for residential construction exceeded
that of economic activity overall, whereas for 2006:
IQ, it lagged the overall growth rate. General
economic activity excluding residential construction registered a solid growth rate of 3.2 percent in
2006:IIIQ

0.7
0.5
1959 1964 1969 1974 1979 1984 1989 1994 1999 2004
*Gray bars indicate recessions.
Source: U.S. Department of Commerce, Bureau of the Census.

Real GDP Growth Excluding
Residential Investment
Annualized quarterly percent change
6
5

Real GDP
Real GDP excluding residential
investment

4
3
2
1
0
IQ

IIQ

IIIQ

IVQ

2005

IIQ
2006

IIIQ

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

Economic Activity and Labor Markets

Industrial Production Closes 2006 in Fine Form
Industrial Production, 2006
Annualized monthly percentage change
12
10
8
6
4
2
0
-2
-4
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

01.23.07
By Ed Nosal and Michael Shenk
During the ﬁrst eight months of 2006, annualized
growth rates for industrial production were, on
average, quite strong. During that period, growth
rates were never negative and reached annualized
highs in excess of 11 percent. The general view
was that in the latter part of the third quarter and
the ﬁrst part of the fourth, economic activity was
beginning to soften; industrial production posted
three consecutive months of negative growth. Many
economic indicators subsequently have suggested

Source: Board of Governors of the Federal Reserve System.

that economic activity is ﬁrming; consistent with
this view, industrial production ended the year on a
strong note.

Industrial Production
Percent change, annually
6
Total Index
5
Total excluding motor vehicles and parts
Excluding energy
4

From the perspective of its recent history, industrial production showed strong growth in 2006,
approaching its rates for 2000. Over the last three
years, production of motor vehicles, as well as parts
and energy-related goods, pulled down the overall
index.

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

2001

2002

2003

2004

2005

2006

Source: Board of Governors of the Federal Reserve System.

Economic Activity and Labor Markets

New Cities Added to Case-Shiller Home Price Indices
01.22.07
By David E. Altig and Brent Meyer

Case Shiller Home Price Indices
Year-over-year percent change
30
25
20
15
Composite 10
10
Composite 20

5
0
-5
-10
1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

Source: Standard&Poor’s S&P Case-Shiller Home Price Indices, Fiserv, MacroMarkets.

One of the more closely watched indicators of
residential housing activity is the Standard & Poor’s
S&P Case-Shiller index, which tracks housing
prices in select markets across the country. Until
recently, individual-market and composite indices
(measuring the average across markets) were restricted to the areas represented by 10 cities -- Boston, Chicago, Denver, Las Vegas, Los Angeles,
Miami, New York, San Diego, San Francisco, and
Washington, D.C. Last month an expanded index
was introduced that includes 10 more metropolitan areas -- Atlanta, Charlotte, Cleveland, Dallas,
Detroit, Minneapolis, Phoenix, Portland, Seattle,
and Tampa.
Although the broader 20-market price index did
not quite reach the heights of the 10-market index
over the 2002-2004 “boom” period, the fall-oﬀ in
the growth rate in prices has been just as dramatic:
The experiences of the markets in the original set of
10 cities have been relatively similar over the past
ﬁve years -- very robust housing-price growth early
on followed by a sharp decline, commencing sometime during the past year to year-and-a-half:
28

Case Shiller Home Price Indices
Year-over-year percent change
60
50
40
Miami
30

San Diego

Another set, which includes the Cleveland metropolitan area, did not experience the really rapid
(better than 5 percent per year) acceleration in
property values seen elsewhere -- though that has
not made these areas immune from the recent slowdown in the pace of price appreciation:

Composite 10

20
Washington

10
0

San Francisco
-10

New York

-20
1988

1990

1992

1994

1996

1998

2000

The experience in the markets added to the make
the composite 20 index has been more diverse.
Several of the cities chosen had experiences similar to those in the composite 10 -- and, given the
regions represented by the “hot 10,” their locations
are probably not surprising:

2002

2004

2006

Source: Standard&Poor’s S&P Case-Shiller Home Price Indices, Fiserv, MacroMarkets.

Case Shiller Home Price Indices
Year-over-year percent change

60
50

Then there is the “none of the above” category:
Among the markets recently added to the CaseShiller calculations, the behavior of house prices in
the Minneapolis and Charlotte metro areas have
been somewhat unique, with the pace of price appreciation over the past ﬁve years falling steadily in
the former and rising steadily in the latter.

Phoenix

40
30
Portland

Seattle

Tampa

10
0
-10
-20
1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

Source: Standard&Poor’s S&P Case-Shiller Home Price Indices, Fiserv, MacroMarkets.

Case Shiller Home Price Indices

Case Shiller Home Price Indices
Year-over-year percent change
25

Year-over-year percent change
25

Minneapolis
15

15
10

Cleveland

Detroit

10
Charlotte
5

5
Atlanta

0
Dallas

-5

-10

-10
1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

Source: Standard&Poor’s S&P Case-Shiller Home Price Indices, Fiserv, MacroMarkets.

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

Source: Standard&Poor’s S&P Case-Shiller Home Price Indices, Fiserv, MacroMarkets.

Regional Activity

Fourth District Employment Conditions
02.05.07
by Christian Miller and Paul Bauer

Unemployment Rates*
Percent
8

United States

5
Fourth District a
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.
Sources: U.S. Department of Labor, Bureau of Labor Statistics; Kentucky Office
of Employment and Training, Workforce Kentucky; Ohio Department of Job and
Family Services, Bureau of Labor Market Information; Pennsylvania Department
of Labor and Industry, Center for Workforce Information and Analysis; and West
Virginia Bureau of Employment Programs, Workforce West Virginia.

Unemployment Rates, December 2006*
U.S. unemployment rate = 4.5%

Lower than U.S. average
About the same as U.S.
average (4.4% to 4.6%)
Above U.S. average
More than double U.S.
average

* Data are seasonally adjusted using the Census Bureau’s X-11 procedure.
Sources: U.S. Department of Labor, Bureau of Labor Statistics; Kentucky
Office of Employment and Training, Workforce Kentucky; Ohio Department of
Job and Family Services, Bureau of Labor Market Information; Pennsylvania
Department of Labor and Industry, Center for Workforce Information and
Analysis; and West Virginia Bureau of Employment Programs, Workforce
West Virginia.

The Fourth District unemployment rate was up in
December, rising to 5.4 percent from 5.2 percent in
November. Though the number of employed persons was up slightly over the month (0.15 percent),
larger increases in the labor force (0.3 percent) and
the number of unemployed persons (4.2 percent)
led to the higher unemployment rate. Nonetheless, over the last year the District’s employment
outlook has improved. Since December 2005, the
unemployment rate has fallen from 5.7 percent,
the number of unemployed persons is 3.9 percent
lower, and employment is up 1.3 percent. Nationally, the unemployment rate was 4.5 percent in
December 2006, and the January 2007 rate inched
up to 4.6 percent.
In December, 146 counties in the Fourth District
reported unemployment rates above the national
rate of 4.5 percent, with the remaining 23 counties
around or below that level. The median unemployment rate for the 169 counties in the District
was 5.75 percent (that is, half of the counties had
rates above 5.75 percent and half had rates below). While rates remained high in comparison
with the U.S. average, unemployment rates fell in
71 counties from November to December. About
three-fourths of counties had lower unemployment
rates in December 2005 compared to a year earlier.
Delaware County, Ohio, registered the District’s
lowest unemployment rate at 3.5 percent; the
District’s highest rate was 12.6 percent in Jackson
County, Kentucky.
Though payroll employment fell in Cleveland and
Dayton over the past 12 months, it increased in
Columbus, Cincinnati, Toledo, Pittsburgh, and
Lexington. Goods-producing industries weighed
down employment gains in the service-providing sector in the major metro areas of the Fourth
District. This pattern was mirrored in the national
data, where manufacturing continued to trend
downward, but several service-providing sectors made strong gains. Employment growth was
30

strongest in Cincinnati, growing by 1.2 percent
year-over-year. The largest percentage gain in
employment for Cincinnati came from the professional and business services sector, which grew at
4 percent and also generated the largest gain in the
number of employed persons (in Cincinnati and
the District), with 6,200 jobs added.

Payroll Employment by Metropolitan
Statistical Area
12-month percent change, December 2006
Cleveland

Total nonfarm

-0.2

Goods-producing
Manufacturing
Natural resources, mining, and
construction

Columbus

Cincinnati

Dayton

Toledo

Pittsburgh

Lexington

0.7

1.2

-0.5

0.6

0.5

-1.5

0.0

-0.8

-1.6

0.0

-2.3

0.4

0.2

-1.5

-0.9

-1.8

-2.1

0.2

-3.6

-1.1

-0.6

-1.7

1.7

1.5

0.0

-0.7

0.2

4.7

1.5

0.1

0.8

1.6

-0.2

0.7

0.9

1.3

1.6

Trade, transportation, and
utilities

0.1

-0.1

1.2

-2.6

0.6

-0.3

1.2

0.6

Information

-1.0

-0.5

-2.6

-0.9

0.0

-2.7

-2.2

0.2

Financial activities

-0.4

-0.5

0.2

-1.1

3.7

0.9

-2.8

1.9

Professional and business
services

0.7

1.0

4.0

0.9

-2.0

1.0

1.9

2.3

Education and health services

1.3

3.4

2.6

0.2

1.6

2.1

0.3

2.7

Leisure and hospitality

0.6

1.3

1.7

0.8

2.8

2.6

3.2

2.9

Other services

0.0

1.0

1.2

2.4

0.0

-1.0

0.0

0.6

Government

-1.8

0.4

-0.6

0.3

0.0

1.4

2.3

1.3

5.5

4.8

5.1

6.0

6.2

4.5

4.0

4.5

Service-providing

December unemployment rate
(percent)

1.1

U.S.

1.4

SOURCES: U.S. Department of Labor, Bureau of Labor Statistics; Kentucky Office of Employment and Training, Workforce Kentucky;
Ohio Department of Job and Family Services, Bureau of Labor Market Information; Pennsylvania Department of Labor and Industry,
Center for Workforce Information and Analysis; and West Virginia Bureau of Employment Programs, Workforce West Virginia

Regional Activity

Ohio’s Automobile Industry
02.01.07
By Yoonsoo Lee and Brian Rudick

Motor Vehicle Parts
Manufacturing Employment*
Index, Jan 1990 = 100
140
United States
130
120
110

Ohio

Ford Motor Company’s $12.6 billion loss in 2006,
coming on the heels of General Motor’s $10.6 billion loss in 2005, leaves little doubt that the domestic automobile industry is indeed going through
hard times. Part of the problem is their vehicle mix,
but foreign manufacturers’ advantages in labor costs
and currency values are also factors.

100
90
1990

1993

1996

1999

2002

2005

*Note: Seasonally adjusted by the Federal Reserve Bank of Cleveland.
Source: U.S. Department of Labor, Bureau of Labor Statistics.

Ohio Automotive Assembly Plants
DaimlerChrysler
Employees: 3,302
Production: 317,099
Ford
Employees: 2,730
Production: 230,132
GM
Employees: 7,283
Production: 301,159
Honda
Employees: 7,900
Production: 647,179
Source: Ward’s Auto; and manufacturers’ Web sites.

With seven ﬁnal assembly plants and nearly 400
tier 1 suppliers, Ohio is at the heart of the industry,
ranking second only to Michigan in terms of employment in the motor vehicle industry. Ohio employs more than 150,000 in transportation equipment manufacturing (NAICS 336) ; the industry’s
share of total employment is more than double that
of the U.S.
What do domestic auto producers’ struggles mean
for Ohio? To examine this, we’ll look at parts and
ﬁnal assembly manufacturers.
Parts Manufacturers
About two-thirds of all employment in transportation equipment manufacturing is in parts. Ohio’s
400 tier-1 suppliers specialize in metal stamping
(22 percent of U.S. employment in the industry),
air conditioning (20 percent of U.S. employment),
and brakes systems (18 percent of U.S. employment).
During the 1990s, parts suppliers experienced unprecedented growth, as original equipment manufacturers (such as GM, Ford, Toyota, etc.) looked
to streamline activities and buy parts from standalone suppliers rather than build them in-house.
Recently, however, lower production from the Big
Three, increased commodity prices, and heightened
foreign competition have put pressure on parts
suppliers. Locally, suppliers such as Delphi (12,441
jobs in Ohio) and Dana (1,801 jobs in the state)
have felt the impact and are currently in Chapter
11 bankruptcy. Delphi plans to close six out of
eight Ohio plants.
32

Employment in Transportation Equipment Manufacturing, 2005*
Ohio
Title

NAICS

Transportation equipment manufacturing

Level

U.S.

% of 336

Level

% of 336

Location
quotient
(OH/U.S.)

336

150,895

100.0

1,769,833

100.0

2.1

Motor vehicle manufacturing

3361

29,702

19.7

249,055

14.1

2.9

Motor vehicle body and trailer manufacturing

3362

8,373

5.5

169,845

9.6

1.2

Motor vehicle parts manufacturing

3363

94,671

62.7

679,143

38.4

3.4

Aerospace product and parts manufacturing

3364

14,889

9.9

453,136

25.6

0.8

Railroad rolling stock manufacturing

3365

389

0.3

27,254

1.5

0.3

Ship and boat building

3366

816

0.5

151,907

8.6

0.1

Other transportation equipment manufacturing

3369

2,054

1.4

39,495

2.2

1.3

*Note: The location quotient is the simple ratio of an industry’s share of employment between two locations.
Source: U.S. Department of Labor, Bureau of Labor Statistics.

Ohio Automotive Assembly Plants
Plant

Currently
producing

Recently
produced

Employees

Avon Lake

Ford Econoline

Ford Escape,
Mercury Mariner,
Mercury Villager,
Nissan Quest

2,730

East Liberty

Honda Civic Sedan/GX, Honda
Element, Honda
CR-V

Honda Accord

2,500

Lorain*

None

Ford Econoline

Lordstown

Chevrolet Cobalt,
Pontiac Pursuit,
Pontiac G4

Cheverolet
Cavalier, Pontiac
Sunfire

4,233

Marysville

Honda Accord,
Acura RDX,
Acura TL

Acura CL

5,300

Moraine

Buick Rainier,
Chevrolet
TrailBlazer, GMC
Envoy, Isuzu
Ascender, Saab
9-7X

Oldsmobile
Bravada

3,050

Toledo
(Parkway)**

None

Jeep Wrangler/
Unlimited, Jeep
Cherokee

Toledo North Dodge Nitro,
Jeep Liberty
Toledo
South***

(Supplier Park)
Jeep Wrangler/
Unlimited

2,969
333

*Plant closed in December 2005 and production moved to Avon Lake.

**Plant closed in June 2006 and production moved to Toledo South.
***Plant opened and production started in August 2006.

Nevertheless, the future of parts suppliers in Ohio
may be less bleak than it seems. Many parts suppliers are tied to the fate of nearby assembly plants,
and Ohio’s assembly plants look to be well positioned (more on that later). In addition, Ohio’s
proximity to plants near its borders, such as Toyota’s Georgetown, Ky, plant, enables parts suppliers
to open up in Ohio and deliver their products just
outside its borders. Indeed, Ohio’s proximity to the
I-65/I-75 automotive corridor makes it a prime
location for auto parts suppliers, as documented in
a Chicago Fed Study.
Final Assembly Plants
Ohio is home to seven ﬁnal assembly plants. Like
parts manufacturing, employment in motor vehicle
manufacturing has fallen signiﬁcantly over the
past several years—28 percent in Ohio since 2000.
However, some of this decline has resulted from
productivity increases. In fact, total motor vehicle
production in Ohio has declined only modestly
over this time.
The state has certainly felt the eﬀects of domestic
manufacturers’ restructurings. In 2005, Ford consolidated its Lorain and Avon Lake plants; it also
plans to close its Maumee stamping plant and its
Batavia transmission plant. In addition, some shifts
at area assemblers, such as Moraine’s third shift,
have recently been eliminated.

Sources: Ward’s Auto, manufacturers’ Web sites.

Ohio Motor Vehicle Production
Plant

2002

2003

2005

2006

46,240

26,891

19,581

42,949

27,061

179,293

East
Liberty

236,029

222,742

231,844

190,731

205,300

237,926

Lorain

149,210

189,530

178,308

201,319

203,071

Lordstown

323,841

348,400

334,817

230,042

301,159

278,101

Marysville

456,348

421,975

445,544

432,972

441,879

446,946

Moraine

258,072

325,436

352,585

320,850

299,020

229,126

Toledo
(Parkway)

122,862

76,608

84,486

97,701

96,381

45,737

Toledo
North

146,485

225,714

237,712

224,067

220,718

209,594

40,050

Avon Lake

2001

Toledo South
(Supplier
Park)
Ohio total

2004

1,739,087 1,837,296 1,884,877 1,740,631 1,794,589 1,666,773

Source: Ward’s Auto.

Nonetheless, Ohio’s ﬁnal assembly plants seem well
positioned because of recent investments and their
portfolio of models produced. In December 2006,
Ford announced that it will invest $60 million in
its Avon Lake plant so it can continue producing
Econolines. In addition, GM invested more than
$500 million several years ago in its Lordstown
plant to get ready for the Cobalt, which will be
produced through 2009. And although it closed its
Toledo Parkway plant, DaimlerChrysler opened the
new Toledo Supplier Park nearby. Moreover, Ohio
plants produce some of the most popular cars in
America, including the Accord, Cobalt, Econoline,
Liberty, and Trailblazer.
We should note that model changeovers can have
a signiﬁcant eﬀect on production at the plant level.
However, the state’s overall motor vehicle production has been surprisingly steady over the last six
years, during which Honda was Ohio’s biggest
producer, followed by GM, DaimlerChrysler, and
Ford.
For greater detail on Ohio’s motor vehicle industry,
see the Ohio Department of Development’s full
report.

Banks and Financial Institutions

Banking Structure
01.24.07
By James Thomson and Cara Stepanczuk

Commercial Bank Offices
Number, thousands
100
Banks
90
80

Branches
Offices

70
60
50

Passage of the 1994 Reigle–Neal Act, which regulates interstate banking, has spurred the consolidation of depository institutions. The number of
FDIC-insured commercial banks fell from 9,972
at the end of 1995 to 7,451 at the end of the third
quarter of 2006, a decline of more than 25 percent. The total number of banking oﬃces, however,
increased nearly 23 percent over that period, from
65,711 to 80,809.

40
30
20
10
0
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006
Source: Federal Deposit Insurance Corporation, Quarterly Banking Profile,
Third Quarter 2006.

From 1995 through the end of September 2006 the
number of FDIC-insured savings associations fell
by more than 36 percent, from 2,030 in 1995 to
1,293. The number of savings associations’ oﬃces
also declined, but less sharply than the number of
institutions (less than 15 percent, from 15,461 in
1995 to 13,220 at the end of the 3rd quarter of
34

2006). Over the same period, the total number
of FDIC-insured depository institutions’ oﬃces
increased almost 16 percent from 81,172 at the
end to 1995 to 94,029 through the 3rd quarter of
2006. This count does not include other channels
for delivering banking services, such as automated
teller machines, telephone banking, and online
banking. Hence, the reduction in the number of insured depository institutions has not decreased the
availability of bank services for most consumers.

Savings Association Offices
Number, thousands
20
Savings and loans

Branches

Offices

14
12
10
8
6
4
2
0
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006
Source: Federal Deposit Insurance Corporation, Quarterly Banking Profile,
Third Quarter 2006.

The eﬀects of the banking industry’s interstate consolidation are evident: All but ﬁve states now report
that more than 15 percent of depository institutions’ branches are part of an out-of-state bank or
savings association. And in over half the states, 30
percent or more of all branches are oﬃces of out-ofstate depository institutions.

Interstate Branches as a
Percent of Total Offices*
Greater than 30%
Between 15% and 30%
Less than 15%
WA
OR

WI
IA

PA
IL IN OH
WV VA
KS
MO
KY
NC
TN
OK AR
SC
MS AL GA
LA
TX

NB
UT

WY
NV

NH
VT
ME

MA
RI
CT
NJ
DE
MD

AK
HI

*Figures reflect percent of branches owned by out-of-state commercial banks
and savings institutions.
Source: Federal Deposit Insurance Corporation, Quarterly Banking Profile,
Third Quarter 2006.

Banks and Financial Institutions

Business Loan Markets
Respondent Banks
Reporting Tighter Credit Standards
Net percent
60
50

Medium and large firms

40
30
20
Small firms
10
0
-10
-20
-30
Jan-00 Oct-00 Jul-01 Apr-02 Jan-03 Oct-03 Jul-04 Apr-05 Jan-06 Oct-06

Sources: Senior Loan Officer Opinion Survey on Bank Lending Practices,
Board of Governors of the Federal Reserve System, October 2006.

Respondent Banks
Reporting Stronger Demand
Net percent
50

0
Small firms

Medium and large firms

-25

-50

-75
Jan-00 Oct-00 Jul-01 Apr-02 Jan-03 Oct-03 Jul-04 Apr-05 Jan-06 Oct-06
Sources: Senior Loan Officer Opinion Survey on Bank Lending Practices,
Board of Governors of the Federal Reserve System, October 2006.

01.17.07
By James Thomson and Cara Stepanczuk
For most of the past year the survey of senior loan
oﬃcers showed that credit availability for businesses continued to improve. For the October 2006
survey (covering the months of August, September
and October), banks reported that their lending
standards were unchanged for commercial and
industrial loans for borrowers of all sizes. Survey
respondents indicate that they’ve have been narrowing their lending spreads and reducing the cost of
credit lines. They attribute their decisions to increased competition (from other banks and as well
as other sources of business credit), greater liquidity
of business loans resulting from a deeper secondary
market, and a reduction in loan defaults.
The maintenance of lending standards reported in
the October survey coupled with some narrowing
of credit spreads has come in the face of somewhat
weaker loan demand, which resulted largely from
businesses’ decreased need for external ﬁnancing of
inventories and accounts receivable.
The continued relaxation of bank lending standards
and marginally weaker loan demand reported in the
most recent survey has yet to be reﬂected on bank
balance sheets. The $24 billion rise in bank and
thrift holdings of business loans in 2006:III marked
it as the tenth consecutive quarter of increased bank
and thrift holdings of commercial and industrial
loans. This recent string of increases represents a
strong reversal in the trend of quarterly declines
in commercial and industrial loan balances on the
books of FDIC-insured institutions before 2005:II.
It is interesting that the rise increase in booked
credits coincides with a steady rate of utilization
rate for business loan commitments (credit lines
extended by banks to commercial and industrial
borrowers). This is another piece of evidence suggesting that business credit is readily available.

Quarterly Change in Commercial
and Industrial Loans
Billions of dollars
50
40
30
20
10
0
-10
-20
-30
-40
Sep-01

Jun-02

Mar-03

Dec-03

Sep-04

Jun-05

Mar-06

Sources: Federal Deposit Insurance Corporation, Quarterly Banking Profile,
Third Quarter, 2006.

Utilization Rate of Commercial
and Industrial Loan Commitments
Percent of loan commitments
41
40
39
38
37
36
35
34
Sep-01

Jun-02

Mar-03

Dec-03

Sep-04

Jun-05

Mar-06

Sources: Federal Deposit Insurance Corporation, Quarterly Banking Profile,
Third Quarter, 2006.

Full text of Economic Trends (Federal Reserve Bank of Cleveland) : Economic Trends - February 2007

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