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July 2008
(Covering June 13, 2008, to July 10, 2008)

In This Issue
The Economy in Perspective
That Giant Sucking Sound...
Inﬂation and Prices
May Price Statistics
Money, Financial Markets, and Monetary Policy
What is the Yield Curve Telling Us?
Steady on Policy Rate, but Alert to Inﬂationary Pressures
International Markets
Why Hasn’t the U.S. Intervened?
Economic Activity and Labor Markets
Housing Values
Where’s the Spillover From Housing?
First Quarter Real GDP: Final Estimate
The Employment Situation
Just When Did the Labor Market Begin to Soften?
Regional Activity
Fourth District Employment Conditions
Diﬀerences in Educational Attainment across States

That Giant Sucking Sound
07.02.08
by Mark Sniderman
Republics are created by the virtue, public spirit, and intelligence of the citizens. They fall, when the wise are banished from
the public councils, because they dare to be honest, and the proﬂigate are rewarded, because they ﬂatter the people in order
to betray them.
—Joseph Story, Commentaries on the Constitution of the United States, 2d ed., vol. 2, chap. 45, pg. 617 (1851).
Historians may decide that Ross Perot’s greatest contribution to the American political landscape was not his prediction of the job losses NAFTA would cause, but his memorable description of the result he feared. “That giant
sucking sound,” he said, was the noise of U.S. jobs being pulled into Mexico. Since his phrase entered the political
lexicon, it has been used to describe the draining of U.S. jobs into China and India, Mexican jobs into China and
India, and even Western European jobs into Eastern Europe. It would be no surprise if the Chinese began using the
same phrase to describe their country’s loss of jobs to Vietnam.
Perot’s intent was to warn the U.S. public about the pernicious eﬀects he believed NAFTA would cause. His phrase
resonated with the public: Everyone has heard that sucking sound, most often when something is being swept away
(into a vacuum cleaner, say), or siphoned oﬀ (down a bathtub drain). Despite all of the passion NAFTA provoked in
its supporters and detractors, economists are still divided about the agreement’s ultimate consequences for U.S. and
Mexican employment.
Has the phrase outlived its usefulness? I think not: There are plenty more sucking sounds to worry about.
The loudest is the sound of earth’s atmosphere sucking in the greenhouse gases that human inventions are spewing
out. Although opinions diﬀer about the eﬀect of human activity on the global warming trend, few dispute the rise
in greenhouse gas emissions. Controlling these emissions presents an enormous political challenge for heads of state,
who feel that accepting emission limits is tantamount to imposing limits on their citizens’ employment and income
growth. At the same time, we know that failure to ﬁnd a solution could have disastrous consequences for life—human and otherwise—on the planet. So every time you drive a car, ﬂy in a plane, enjoy cooling or warming indoors
air, or consume products manufactured using coal, petroleum, or natural gas, remember to listen for the giant sucking sound of hydrocarbons being inhaled by earth’s atmosphere.
Another worrisome sucking sound is caused by the speed with which we are siphoning oﬀ potable water from our
lakes, rivers, and underground aquifers. Climate change, urbanization, and global population growth are combining to create water shortages in many parts of the world. In the United States, several major metropolitan areas
have undergone serious water shortages in recent years and been forced to impose rationing. Although many people
attribute recent water scarcities to a period of unusually low rainfall, we know that demand for water in arid regions
of the country has been driven up by growing populations and agricultural usage. In many instances, water rights
established by treaties or grants more than a century ago are still in force, leading to conﬂict with present realities.
Unfortunately, there may be little scope for market forces to play a strong role in allocating water for its most beneﬁcial uses, or political institutions to protect ground and surface water from being depleted by overuse, much as some
ﬁshing grounds have been depleted in the absence of sustainable use agreements.
The third vortex—you have probably anticipated this one—is the federal budget deﬁcit. There was a time when
people erroneously believed that ﬁscal rectitude required that the budget be balanced annually. Economists debunked that belief, replacing the one-year balancing interval with something more akin to the business cycle; their
logic was that in times of high unemployment and resource slack, ﬁscal deﬁcits would help stabilize the economy,
Federal Reserve Bank of Cleveland, Economic Trends | July 2008

while in times of low unemployment, surpluses would do the same. The prudent course was to adopt spending and
tax programs that would make for a balanced budget in times of full employment.
In the long term, our current ﬁscal posture is unsustainable. We have become accustomed to thinking that if an
objective is worthwhile, it is worthwhile to subsidize it, increase spending on it, or insure private lenders against
the risk they assume for it. Granted, we have a great many national needs, some of them worthy of being ﬁnanced
through debt rather than current taxes. But our current trajectory must be corrected, and the longer we delay that
correction, the more disruption we invite.
Carbon and water imbalances may be more dire than a ﬁscal mismatch, but a large ﬁscal footprint is not a thing to
be taken lightly. I think Mr. Perot would agree.

Inﬂation and Prices

May Price Statistics
07.02.08
by Michael F. Bryan and Brent Meyer

May Price Statistics
Percent change, last
1mo.a

3mo.a

6mo.a

12mo.

5yr.a

2007 avg.

All items

8.1

4.9

4.0

4.2

3.4

4.2

Less food and
energy

2.5

1.8

2.1

2.3

2.2

2.4

Medianb

2.2

2.7

2.9

3.0

2.7

3.1

16% trimmed
meanb

4.0

3.5

3.1

3.0

2.6

2.8

30.9

35.4

20.1

17.8

8.0

11.5

Nonpetroleum
imports
Export Price Index

6.6

12.9

10.0

6.6

3.3

3.1

All commodities

3.9

9.9

10.4

8.0

4.6

6.1

Consumer Price Index

Import Price Index
All commodities

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

CPI Component Price Change Distributions
Weighted frequency
45
May 2008
40
Average over 12 months prior
35
30
25
20
15
10
5
0
<0

0 to 1
1 to 2
2 to 3
3 to 4
Average over prior 12 months

4 to 5

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

Federal Reserve Bank of Cleveland, Economic Trends | July 2008

The CPI rose 8.1 percent (annualized rate) in May,
pushed up, in part, by a 67.8 percent increase in
energy components. Over the past three months,
the CPI is up 4.9 percent. The CPI excluding food
and energy (core CPI) increased 2.5 percent in
May, rising at a rate above all its longer-term trends
and following a 1.3 percent increase in April. Like
the CPI, import prices have been aﬀected by oil
prices—albeit to a greater extent—as the import
price index for all commodities rose 30.9 percent in
May and 35.4 percent over the past three months.
Unfortunately, it is not just oil prices that are rising.
The nonpetroleum import price index increased 6.6
percent during the month and is up almost 13 percent over the past three months. The export price
index rose 3.9 percent in May, somewhat more
subdued than its longer-term trends.
There was an unusual amount of dispersion
between the median CPI and the 16 percent
trimmed-mean CPI in May, as the 16 percent
trimmed-mean measure rose 4.0 percent, while the
median increased just 2.2 percent. That last time
the trimmed-mean estimators were this far apart
was in October 2001. Looking at the component
distribution reveals that nearly 36 percent of the
CPI’s components rose at rates in excess of 5.0
percent during the month. This, coupled with 38
percent of the index’s components rising at rates
less than 1 percent, shows that 74 percent of the
CPI was out near the tails of the component price
2

Core CPI Goods and Core CPI Services
12-month percent change
8.0
7.0
6.0
5.0
4.0
3.0
2.0
1.0
0.0
-1.0
-2.0
-3.0
-4.0
-5.0
-6.0
1998

One-month annualized
perc ent c hange
C ore s ervic es

C ore goods
One-month annualized perc ent c hange

2000

2002

2004

2006

2008

Sources: U.S. Department of Labor; Bureau of Labor Statistics.

CPI and Forecasts
Annualized quarterly percent change
7.0
6.0
5.0
4.0

Top 10 forecast

Actual

3.0
2.0
1.0

Bottom 10 forecast

0.0
-1.0
-2.0
-3.0
3/06

12/06

9/07

6/08

3/09

12/09

Sources: Blue Chip panel of economists, June 10, 2008.

distribution. The 16 percent trimmed-mean incorporated some of those wild component price
swings, such as a 30.7 percent increase in car and
truck rental prices and a 17.4 percent increase in
the lodging-away-from-home component. On
the other side of the distribution (but excluded
from the 16 percent trimmed-mean), the prices of
jewelry and watches fell 18.9 percent, infant and
toddler apparel decreased 9.8 percent, and medical
care commodities fell 8.5 percent in May. While it
may be tempting to tell a story about budget-constrained consumers substituting away from other
goods in the face of higher relative fuel prices, it
would take more data and careful analysis to prove
that point.
The prices of core services (services excluding
energy services) rose 4.1 percent in May, following a 1.7 percent increase in April. Over the past
12 months, core service prices are up 3.2 percent.
On the other hand, the prices of core goods (goods
excluding food and energy commodities) fell 1.6
during the month and are up only 0.1 percent on a
year-over-year basis.
Looking forward, professional forecasts see headline
consumer prices remaining elevated throughout the
rest of 2008 and falling to 2.4 percent by the end
of 2009. Of the 48 forecasters surveyed, 36 revised
their 2008 inﬂation forecasts upward in June from
their projections in May, and will most likely do so
again, as energy prices have continued to rise.

Money, Financial Markets, and Monetary Policy

What is the Yield Curve Telling Us?
06.18.08
by Joseph G. Haubrich and Kent Cherny
Since last month, the yield curve has taken a parallel upward shift, with both short-term and longterm interest rates rising. One reason for noting
this is that the slope of the yield curve has achieved
some notoriety as a simple forecaster of economic
growth. The rule of thumb is that an inverted yield
curve (short rates above long rates) indicates a
recession in about a year, and yield curve inversions
have preceded each of the last six recessions (as deﬁned by the NBER). Very ﬂat yield curves preceded
Federal Reserve Bank of Cleveland, Economic Trends | July 2008

Yield Spread and Real GDP Growth
Percent
12
10

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

8
6
4
2
0

Ten-year minus three-month
yield s pread

-2
-4
1953

1963

1973

1983

1993

2003

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

Yield Spread and Lagged Real GDP
Growth
Percent
12
10

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

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

-2
-4
1953

1963

1973

1983

1993

2003

Sources: Bureau of Economic Analysis; Federal Reserve Board.

Yield Spread and Predicted GDP Growth
Percent
6
5

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

P redic ted
G DP growth

3
2
1
0

Ten-year minus three-month
yield s pread

-1
-2
2002

2003

2004

2005

2006

2007

2008

Sources: Bureau of Economic Analysis; Federal Reserve Board.

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 Treasury notes
and 3-month Treasury bills, bears out this relation,
particularly when real GDP growth is lagged a year
to line up growth with the spread that predicts it.
The yield curve slope stayed the same, with both
long and short rates edging up. The spread remains
positive, with the 10-year rate moving up 30 basis
points to 4.15 percent and the 3-month rate up
33 basis points to 1.97 percent (both for the week
ending June 13). Standing at 218 basis points, the
spread is just below the 221 basis points seen in
April and May. Projecting forward using past values
of the spread and GDP growth suggests that real
GDP will grow at about a 3.0 percent rate over the
next year. This is on the high side of other forecasts.
While such an approach predicts when growth is
above or below average, it does not do so well in
predicting the actual number, especially in the case
of recessions. Thus, it is sometimes preferable to
focus on using the yield curve to predict a discrete
event: whether or not the economy is in recession.
Looking at that relationship, the expected chance of
the economy being in a recession next June stands
at 1.1 percent, just above May’s 0.9 percent, and
April’s 1 percent.
The probability of recession is below several recent
estimates and perhaps seems strange the in the
midst of recent ﬁnancial concerns. But one aspect
of those concerns has been a ﬂight to quality, which
lowers Treasury yields. Also working to steepen the
yield curve are the reductions in both the federal
funds target rate and the discount rate by the Federal Reserve. Furthermore, the forecast is for where
the economy will be next June, not earlier in the
year.
To compare the 1.1 percent to some other probabilities and learn more about diﬀerent techniques
of predicting recessions, head on over to the Econbrowser blog.
Of course, it might not be advisable to take this

Federal Reserve Bank of Cleveland, Economic Trends | July 2008

Probability of Recession Based on the
Yield Spread
Percent
100
90
P robability of
rec es s ion

80
70

F orec ast

60
50
40
30
20
10
0
1960

1966

1972

1978

1984

1990

1996

2002

2008

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

number quite so literally, for two reasons. First,
this probability is itself subject to error, as is the
case with all statistical estimates. Second, other
researchers have postulated that the underlying
determinants of the yield spread today are materially diﬀerent from the determinants that generated
yield spreads during prior decades. Diﬀerences
could arise from changes in international capital
ﬂows and inﬂation expectations, for example. The
bottom line is that yield curves contain important
information for business cycle analysis, but, like
other indicators, should be interpreted with caution.
For more detail on these and other issues related to
using the yield curve to predict recessions, see the
Commentary “Does the Yield Curve Signal Recession?”

Money, Financial Markets, and Monetary Policy

Steady on Policy Rate, but Alert to Inﬂationary Pressures
06.26.08
by John B. Carlson and Sarah Wakeﬁeld

June Meeting Outcomes
Implied Probability
1.0

Case-Shiller Home Price Index (Apr); Index of Consumer Sentiment (Jun)

0.9
0.8
0.7

2.00%

0.6
0.5
0.4

2.25%

0.3
0.2

1.75%

1.50%

0.1
0.0
04/01 04/11

04/21

05/01

05/11 05/21

05/31

06/10

06/20

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

August Meeting Outcomes
Implied Probability
1.0
0.9

Case-Shiller Home Price Index (Apr); Index of Consumer Sentiment (Jun)

The Federal Open Market Committee (FOMC)
left its target for the federal funds rate unchanged
at 2 percent on June 25. This outcome surprised
few: The market’s assessment of the probability of a
rate change never rose above 25 percent during the
intermeeting period.
Immediately after the April 30 meeting, market
participants expected the FOMC to hold the policy
rate steady at least through the summer. However,
when incoming data failed to conﬁrm that the
economy was in a recession, a rate hike of at least
25 basis points in August emerged as the most
likely prospect. But by mid-June, the no-change
outcome reemerged as the most likely one.

0.8
0.7

Prices for Federal funds futures revealed a similar
story. The highest and steepest trajectory for implied yields occurred in the second week of June,
when stronger-than-expected data on the economy
were released and some Fed oﬃcials expressed concerns about inﬂationary pressures.

2.00%

0.6
0.5
0.4

2.50%

0.3

1.75%

0.2
0.1

2.25%
2.75%

0.0
05/09

05/15

05/21

05/27

05/02

06/08

06/14

06/20

Federal Reserve Bank of Cleveland, Economic Trends | July 2008

In its post-meeting statement, the FOMC noted
that “[t]ight credit conditions, the ongoing credit
5

Implied Yields on Federal Funds Futures
Percent
4.00
June 26, 2008

3.50
June 24, 2008a

3.00
2.50

June 13, 2008

2.00

April 29, 2008a
March 17, 2008a

1.50
1.00
3/08

5/08

7/08

9/08

11/08

1/09

3/09

5/09

7/09

a. One day before FOMC meeting.
Source: Chicago Board of Trade and Bloomberg Financial Services.

Reserve Bank Credit
Dollars (billions)
160
140
120
100

contraction, and the rise in energy prices are likely
to weigh on economic growth over the next few
quarters.” Moreover, “the Committee expects inﬂation to moderate later this year and next year.”

Repurchase agreements

Term Auction Credit

The FOMC’s assessment of risks indicated that
the “substantial easing of monetary policy to date,
combined with ongoing measures to foster market
liquidity, should help to promote moderate growth
over time. Although downside risks to growth
remain, they appear to have diminished somewhat,
and the upside risks to inﬂation and inﬂation expectations have increased.”
The market’s reaction to the June 25 policy announcement has been limited. Initially, equity
prices reacted favorably, adding more than half a
percentage point to an ongoing rally of almost one
percentage point. However, prices then declined
somewhat, ending the day up about 60 basis points
over the previous day’s close. The bond market
showed little reaction to the news. Although the
market continues to expect an upward trajectory to
the policy rate, the FOMC statement led participants to expect rate hikes to come later than sooner.

60
Primary Dealer Credit

40
20

Primary credit
0
12/07

01/08

02/08

03/08

04/08

05/08

06/08

Source: Federal Reserve Board.

3-Month LIBOR Spread
Percent
1.20

The rise in Reserve Bank credit during the intermeeting period was primarily a reﬂection of
the higher amounts auctioned through the Term
Auction Facility (TAF), a key new measure to
foster market liquidity. Primary credit peaked in
late May, driven largely by a rise in the number of
institutions borrowing on net. Primary dealers have
substantially reduced their reliance on the Primary
Dealer Credit Facility.
Although credit terms have tightened for some
businesses and households, concerns about liquidity have lessened substantially. The spread between
the term borrowing rate in the London interbank
market (LIBOR) and the cash market rate (OIS) is
a closely watched indicator of liquidity conditions.
Spreads for both one-month and three-month
borrowing have declined considerably from recent
peaks, although they remain above their pre-crisis
levels.

1.00
0.80
0.60
0.40
0.20
0.00
7/07

9/07

11/07

1/08

3/08

5/08

Notes: Daily observations; LIBOR spread is the three-month LIBOR rate minus
the three-month OIS Rate.
Sources: Bloomberg Financial Services, Financial Times.

Federal Reserve Bank of Cleveland, Economic Trends | July 2008

International Markets

Why Hasn’t the United States Intervened?
07.09.08
by Owen F. Humpage and Michael Shenk

Interventions: German Mark
Billions of U.S. dollars
4

Marks per U.S. dollar
3.4

3.1

2.8

2.5

2.2

-1

1.9

-2

1.6

-3

1.3

U.S. sales of marks
U.S. purchases of marks

1.0
-4
1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995
Source: Board of Governors.

Interventions: Japanese Yen
Billions of U.S. dollars
3

Yen per U.S. dollar
350

300

250

200

-1

150

-2

100

-3

U.S. sales of yen
U.S. purchases of yen

-4
0
1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995
Source: Board of Governors.

Federal Reserve Bank of Cleveland, Economic Trends | July 2008

The dollar’s precipitous fall since February 2002,
particularly against the euro, has renewed interest in foreign-exchange-market intervention, that
is, oﬃcial purchases and sales of foreign exchange
designed to inﬂuence dollar exchange rates. Aside
from a single transaction against the euro and a
single transaction against the yen, the United States
stopped intervening in 1995 for two very good
reasons: First, foreign-exchange-market intervention has the potential to conﬂict with monetary
policy and to create uncertainty about the ultimate
objectives of monetary policy. Second, intervention
has not been very successful.
Technically, foreign-exchange interventions are
very much like open-market operations, and like
the latter, they can conceivably add or drain bank
reserves. To stem a dollar depreciation, for example,
the Federal Reserve Bank of New York might sell
euros or Japanese yen to banks and debit their
reserve accounts in payment. Such an intervention,
if big enough, could indeed slow or reverse a dollar
depreciation by reducing U.S. money growth. So
why not intervene?
Because it isn’t necessary. Or worse, such an intervention is likely to conﬂict with the domestic
objectives of monetary policy. Intervention is
unnecessary if the underlying cause of the dollar’s
depreciation is a rise in U.S. inﬂation. In that case,
standard open-market operations can reduce the
inﬂation rate and prop up the dollar. In all other
cases, attempting to support the dollar through
intervention sales of foreign exchange can conﬂict
with the domestic objectives of monetary policy.
When, for example, inﬂation expectations are
fairly well contained and the FOMC is temporarily
providing liquidity to stave oﬀ a credit collapse and
the associate downside risks to real economic activity, selling foreign exchange to prop up the dollar
will conﬂict with the domestic thrust of policy. The
Federal Reserve does, of course, have a way around
this problem. To avoid conﬂict with the domestic
7

Were U.S. Foreign Exchange
Interventions Succesful?
Total
interventions

Actual
successes

Expected
successes

Standard
deviations

...dollar
depreciation?

502

127

242

...a more
moderate
dollar
depreciation?

502

...either of
these criteria?

502

223

306

...dollar
depreciation?

150

...a moderate
dollar
depreciation?

150

...either of
these criteria?

150

...dollar
depreciation?

469

121

225

...a moderate
dollar
depreciation?

469

...both of
these criteria?

469

211

285

...dollar
depreciation?

...a more
moderate
dollar
depreciation?

...both these
criteria?

Was a U.S. purchase of German
marks associated
with

Was a U.S. purchase of Japanese
yen associated with

Was a U.S. sale
of German marks
association with

Was a U.S. sales
of Japanese yen
associated with

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.

Federal Reserve Bank of Cleveland, Economic Trends | July 2008

objectives of monetary policy, the Federal Reserve
routinely oﬀsets (or sterilizes) any intervention
whose impact on bank reserves conﬂicts with the
FOMC’s federal-funds-rate target. In doing so,
however, the Federal Reserve also prevents intervention from aﬀecting key macroeconomic determinants of exchange rates—interest rates and money
growth.
Sterilized intervention has long been a puzzle
because economists are not quite sure how, or if, it
works. According to the current best guess, central
banks can sometimes convey information through
sterilized intervention to foreign exchange traders
that aids them in price discovery. Information is
costly, and market participants do not continuously
possess the same information about exchange rates.
Large foreign-exchange traders may often have better information than their smaller counterparts because of broader customer bases and wider market
networks. Such information asymmetries can sometimes encourage bandwagon eﬀects, overreaction to
news, and excessive volatility in uncertain exchange
markets. If monetary authorities have better information about fundamentals than private traders,
they may be able to impart this information to
the market through their trades and improve the
market’s functioning. Central banks do have large
information networks, and sometimes they have an
inside track to impending policy changes.
Sounds grand, but do central banks, in fact, routinely have better information than foreign-exchange traders? If they do, then their interventions
should be highly successful at inﬂuencing exchange
rates.
Between March 2, 1973, and December 31,
1998, the United States intervened in the foreignexchange market on 652 days against German
marks and on 563 days against Japanese yen. Most
of these were purchases of foreign exchange. These
interventions were not successful at producing
a same-day dollar depreciation or appreciation;
in fact, market participants generally could have
proﬁted by trading against U.S. monetary authorities. These interventions, however, were successful
at moderating dollar appreciations or depreciations
over the day of the intervention from the previous
8

day. These successful interventions amounted to
only about 20 percent of all transactions—so much
for the routine information story.
The underwhelming success rate, however, was not
the key reason that U.S. monetary authorities gave
up on an active intervention program. As expressed
at their October 3, 1989, meeting, the FOMC
feared that even sterilized intervention ultimately
must create uncertainty about the Federal Reserve’s
commitment to price stability. They determined
that a central bank cannot credibly anchor inﬂation
expectations and attempt to manage exchange rates.

Economic Activity and Labor Markets

Housing Values
06.19.08
by O. Emre Ergungor

Case-Shiller Home Price Index
Index, January 2000 = 100
200

The Case–Shiller Home Price Index continued its
rapid descent in the ﬁrst quarter of 2008. Currently, it stands 14 percent below the peak it hit in
the second quarter of 2006.

180
160

S&P/Case-Shiller U.S. National Home Price Index
140
120
100
80
60
40
1987

1991

1995

1999

2003

2007

Source: S&P, Fiserv, and MacroMarkets LLC.

Index, January 2000 = 100
Case-Shiller Home Price Index
300
280
260
240
220
200
180
160
140
120
100
80
60
40
1987
1991
1995

Miami

Las Vegas

Cleveland
Detroit
1999

2003

2007

Source: S&P, Fiserv, and MacroMarkets LLC.

Federal Reserve Bank of Cleveland, Economic Trends | July 2008

Home prices continued to deteriorate in the Cleveland metropolitan area. According to the Case–
Shiller home price index, home prices are back
to their February 2002 levels. In comparison, the
well–publicized price collapse in the bubble areas
(Miami and Las Vegas, for example) brought those
prices back only to their 2004–2005 levels. In other
words, people who purchased a house in Cleveland
or Detroit in late 2002 would now take a loss if
they tried to sell, but those who bought in Miami
or Las Vegas could still turn a proﬁt.
The Cleveland metro area diﬀers from the bubble
areas not only in terms of the hit it is taking to
housing values but also in terms of which part of its
housing stock is experiencing the losses. Recently,
S&P began dividing the housing stock in most
metro areas into three groups by home value. In
the Cleveland area, for example, a third of housing
stock is valued over $176,307 (depicted as “high”
in the chart below), a third below $111,071 (“low”)
and a third in the middle of these two values
(“middle”). These thresholds will be higher or lower
in other metro areas but in the end, they all capture
the highest, lowest, and the middle third of local
9

Tiered Home Price Index: Cleveland

home values.

Index, January 2000 = 100
140

In the 1987–2005 period, the home price appreciation in the low end of the Cleveland housing
market has been noticeable. Homes that are worth
less than $111,071 appreciated by more than 6 percent per year. Annual appreciation in the high end
of the market was a more modest 4 percent over the
same period (nominal ﬁgures). However, the health
of the market deteriorated dramatically after 2005.
Since September 2005, the low end of Cleveland’s
housing market has experienced 37 percent depreciation, compared to an 11 percent decline in the
high group and a 15 percent decline in the middle
group.

120
100

High (over $176,307)
Middle ($111,071 to $176,307)
Low (under $111,071)

80
60
40
1987

1991

1995

1999

2003

2007

Source: S&P, Fiserv, and MacroMarkets LLC.

Tiered Home Price Index: Las Vegas
Index, January 2000 = 100
260
240
220

Middle ($215,949 to $282,491)

200
180
160

High (over $282,491)

140
120

Similarly, in Miami, low-end housing units lost
22.5 percent of their value in the last year. The
losses are around 23.4 percent for higher value
homes.

100
80
60
40
1987

Low (under $215,949)

1991

1995

1999

While home prices declined much more signiﬁcantly in Miami and Las Vegas compared to Cleveland
(they are down 28 percent in Las Vegas from their
peak in August 2006 and down almost 25 percent
in Miami over the same period), the declines have
been slightly more pronounced in the higher-end
homes. In Las Vegas, low–end housing units lost 23
percent of their value in 18 months. Higher–valued
homes lost drop is 28 percent.

2003

2007

Source: S&P, Fiserv, and MacroMarkets LLC.

Tiered Home Price Index: Miami
Index, January 2000 = 100
360
340
Low (under $240,512)
320
300
280
260
240
Middle ($240,512 to $351,630)
220
200
180
160
140
120
High (over $351,630)
100
80
60
40
1987
1991
1995
1999
2003
2007
Source: S&P, Fiserv, and MacroMarkets LLC.

Federal Reserve Bank of Cleveland, Economic Trends | July 2008

As prices have fallen, so too has homeowners’
equity in their homes. An increase in equity extractions and low–downpayment purchases adds to
the problem. Homeowners’ equity in their homes,
as reported by Mortgage Bankers Association,
dropped to 46.2 percent of the home value, the
lowest level on record.
One negative consequence of declining equity is
an increase in homeowners’ inability to sell their
homes and pay oﬀ their mortgages or reﬁnance
their loans if the payments become too burdensome. As a result, mortgage foreclosures have risen
sharply in recent quarters. While subprime adjustable-rate mortgages (ARM) look like the worst
performers, even the recently originated prime
ﬁxed–rate mortgages (FRM) are performing uncharacteristically poorly, according to Loan Performance Corporation data.
10

Homeowners’ Equity

Foreclosure Starts

Percentage of household real estate
100

Percent
7.0
6.5
6.0
5.5
5.0
ARM subprime
4.5
4.0
3.5
FRM subprime
3.0
2.5
Subprime
2.0
1.5
1.0
FRM prime All loans
Prime
ARM prime
0.5
0.0
1998
2000
2002
2004
2006
2008

90
80
70
60
50
40
1952 1957 1962 1967 1972 1977 1982 1987 1992 1997 2002 2007
Source: Mortgage Bankers Association.

Source: Mortgage Bankers Association

Economic Activity and Labor Markets

Where’s the Spillover from Housing?
Gross Domestic Purchases Exluding
Residential Investment
Percent change, annual rate
8
6
4
2
0
-2
-4
-6
1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
Note: Shaded bars indicate recessions.
Source: Bureau of Economic Analysis.

Export Growth and the Value of the Dollar
12-month percent change
25
20
Exports
15
10
5
0
-5
-10

Nominal Broad Dollar Index

-15
-20
1995

1997

1999

2001

2003

2005

2007

Note: Shaded bar indicates a recession.
Source: Census Bureau; Federal Reserve Board.

Federal Reserve Bank of Cleveland, Economic Trends | July 2008

06.19.08
Michael Shenk
Recently, the argument has been made that outside
of the housing market, the economy is actually doing pretty well. Looking at the GDP numbers, that
argument appears to hold some weight. Once you
take into account the direct impact of large declines
in residential investment (it fell an annualized 25.5
percent in the ﬁrst quarter of 2008), GDP growth
looks pretty good over the past two quarters: According to the preliminary estimate, GDP excluding residential investment increased 2.0 percent in
the ﬁrst quarter of 2008, following a 1.7 percent
gain in the fourth quarter of 2007. While these
numbers may be encouraging, they seem at least a
little peculiar, given what we know about housing
and what we’ve seen in the labor market.
Aside from providing a place to live, homes provide
many services for their owners. They are a means
of forced savings, a storer of wealth, and, in most
cases, a household’s largest asset. With homes so
important to a household’s ﬁnancial situation, how
is it that a serious downturn in housing can have
such a limited eﬀect on the rest of the economy?
One factor that helps to explain the persistence of
GDP growth is the global economy. GDP measures
the value of goods produced in the United States,
11

Gross Domestic Purchases
Percent change, annual rate
8
6
4
2
0
-2
-4
-6
1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
Note: Shaded bars indicate recession.
Source: Bureau of Economic Analysis

GDP Growth Excluding Residential
Investment
Percent change, annual rate
8
6
4
2
0
-2
-4
1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
Note: Shaded bars indicate recessions.
Source: Bureau of Economic Analysis.

Owners’ Equity in Household Real Estate
Percent
100
90
80
70
60
50
40
30
20
10
0
1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
Note: Shaded bars indicate recessions.
Source: Federal Reserve Board

Household Consumer Credit
12-month percent change
20

but not all of these goods are consumed within its
borders. While demand for U.S. goods may have
slowed within the United States, rapid growth in
the global economy has added to it. The increase in
foreign demand has been further boosted by a weak
dollar, which makes goods and services priced in
dollars cheap relative to goods and services priced
in other currencies. The increase in demand from
outside of the U.S. helps to keep production in the
U.S. from falling oﬀ, ultimately boosting our GDP.
We can see this in the relative strength of export
growth.
Meanwhile, to see the strength of domestic demand
by itself, we can look at gross domestic purchases.
This series, which is essentially GDP less net exports, has grown much more slowly than GDP in
the past two quarters, perhaps reﬂecting a negative
wealth eﬀect from the downturn in housing.
After adjusting for the direct impact of the downturn in residential investment, we still see some
slowing in overall domestic purchase growth over
the previous two quarters but not to the extent that
purchases have actually fallen. This slowdown is
likely partially the result of spillover from the housing downturn, but it should also reﬂect the impact
of factors unrelated to housing that are weighing
on consumers, such as rising food and energy costs.
Still, the overall persistence of the series suggests
that the spillover eﬀect from housing has been
relatively small.
One reason we still see no large-scale spillover may
be that households view the downturn as transitory
and just aren’t adjusting their spending signiﬁcantly
This behavior requires, of course, that households
have either enough wealth or available credit to
buﬀer the temporary downturn. For some, this is
certainly an issue, but in general, households still
have a signiﬁcant amount of equity in their homes
to borrow against, and despite the credit crunch,
households’ nonmortgage borrowing appears to be
robust.

-5
1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
Note: Shaded bars indicate recessions.
Source: Federal Reserve Board

Federal Reserve Bank of Cleveland, Economic Trends | July 2008

Economic Activity and Labor Markets

First Quarter Real GDP: Final Estimate
07.07.08
by Brent Meyer

Real GDP and Components 2007:
Fourth-Quarter Advance Estimate
Annualized percent change, last:
Quarterly change
(billions of 2000$)

Quarter

Four quarters

Real GDP

27.9

1.0

2.5

Personal consumption

23.8

1.1

1.9

Durables

-19.0

-6.0

0.5

Nondurables

-1.0

-0.2

0.7

Services

36.5

3.1

2.8

Business fixed investment

1.9

0.5

6.7

Equipment

0.6

0.2

3.5

Structures

1.0

1.3

13.7

Residential investment

-29.3

-24.5

-20.7

Government spending

10.5

2.1

3.0

7.1

5.6

5.8

Net exports

National defense

23.0

—

Exports

19.6

5.5

9.5

Imports

-3.4

-0.7

-0.1

-1.3

—

Change in business
inventories
Source: Bureau of Labor Statistics.

Contribution to Percent Change in Real GDP
Percentage points
1.5

2008:IQ advance
2008:IQ preliminary
2008:IQ final

Personal

1.0 consumption
0.5
0.0
-0.5

Residential
investment
Business
fixed
investment

Government
spending

Change in Exports
inventories
Imports

-1.0
-1.5
Source: Bureau of Economic Analysis

Federal Reserve Bank of Cleveland, Economic Trends | July 2008

Real GDP increased at an annualized rate of 1.0
percent in the ﬁrst quarter of 2008, according to
the ﬁnal estimate released by the BEA. The revision—which is 0.1 percentage point above the preliminary estimate and 0.4 percentage point above
the advance release—was primarily due to upward
adjustments to private investment and exports,
which were mostly oﬀset by a downward adjustment to inventories and an increase in imports
(which enter as a negative in GDP accounting).
Business ﬁxed investment was actually revised up
from a 2.5 percent decrease (annualized rate), according to the advance estimate, to a slight growth
of 0.5 percent in the ﬁnal release. Another encouraging sign was that, with each iteration, residential
investment was revised up (albeit slightly).
An investigation into individual components’
contributions to the percentage change in real GDP
shows us that inventory accumulation added 0.8
percentage point to real GDP growth in the advance report, but that this increase was almost completely revised away. Net exports were undoubtedly
helped by the continued weakness in the dollar,
as the ﬁnal estimate for the ﬁrst quarter had net
exports adding 0.8 percentage point to real GDP
growth, compared to just 0.2 percentage point
in the advance estimate. Since the ﬁrst quarter of
2000, net exports have subtracted 0.2 percentage
point from growth, on average.
While personal consumption limped in at 1.1
percent in the ﬁrst quarter, there is little evidence to
suggest that will be the case in the second quarter.
Real personal income increased 2.1 percent and
4.4 percent during the ﬁrst two months of the
second quarter. While the exact eﬀect may be hard
to measure, it seems that the ﬁscal stimulus rebates
are giving at least a moderate boost to consumption. The rebates are also having a signiﬁcant eﬀect
on personal income. Real personal income jumped
up 19.0 percent in May. However, after subtracting out transfer payments—such as the stimulus
13

checks—real personal income was virtually ﬂat,
falling 0.3 percent at an annualized rate.
Professional forecasters continue to expect below–
trend growth over the next few quarters, before
returning to near–trend growth by the end of 2009.
Of the 48 forecasters surveyed by Blue Chip, 27
revised their 2008 forecast up from last month’s
forecast. On the other hand, nearly half of the forecasters on the Blue Chip panel revised their 2009
GDP forecast down compared with their forecast a
month ago.

Real Personal Income

Real GDP Growth

Annualized percent change
8

Annualized quarterly percent change
6
Final estimate
Blue Chip consensus forecast
5

Real personal income

6
Average GDP growth
(1978Q1-2008Q1)

Annualized percent change
20

15
Real personal consumption

1
1

-1

0
IIQ IIIQ IVQ IQ IIQ IIIQ IVQ IQ IIQ IIIQ IVQ IQ IIQ IIIQ IVQ
2007
2008
2006
2009
Source: Blue Chip Economic Indicators, June 2008; Bureau of Economic Analysis.

-2

-5
07q1

07q2

07q3

07q4

08q1

4/08

5/08

Source: Bureau of Economic Analysis.

Economic Activity and Labor Markets

The Employment Situation
07.08.08
by Yoonsoo Lee and Beth Mowry

Average Nonfarm Employment Change
Change, thousands of jobs
250

Revised
Previous estimate

200
150
100
50
0
-50
-100
2005 2006 2007 2008 III
IV
YTD 2007

I
II
2008

Apr May Jun

Source: Bureau of Labor Statistics.

Federal Reserve Bank of Cleveland, Economic Trends | July 2008

Today’s Employment Report revealed a net decline
of 62,000 jobs in June, in line with expectations
and identical to May’s 62,000 drop (after revision).
Combined downward revisions for April and May
amount to an added loss of 52,000 jobs for those
months. This report brings the sixth consecutive
month of decline, which began in January. Average monthly job losses for the second quarter were
about 64,000, compared to an average of 82,000
in the ﬁrst quarter. The diﬀusion index of employment change improved slightly, edging up from
45.6 in May to 46.9 in June. The reading below 50
indicates that over half of all industries are still cutting back on employment.

The goods-producing sector registered its ﬁfteenthconsecutive month of decline, losing 69,000 jobs in
June and surpassing May’s loss of 54,000. The only
major industry within this sector to add jobs was
natural resources and mining. Service-providing industries narrowly squeezed by with a small gain of
7,000 jobs. Discounting the government’s addition
of 29,000 jobs, however, leaves private services with
a loss of 22,000. Furthermore, May’s 8,000 gain in
services was entirely erased and revised instead to a
loss of 8,000 jobs in today’s report.

Labor Market Conditions and Revisions
Average monthly change (thousands of employees, NAICS)
April
current

Revision to
April

May
Current

Revision
to May

June
2008

Payroll employment

−67

−39

−62

−13

−62

Goods-producing

−109

−9

−54

−69

Construction

−59

−7

−37

−3

−43

Heavy and civil engineering

−9.5

−3

−5

Residentiala

−32

−5

−30

−21

−17.5

−3

−4

−17

Nonresidentialb
Manufacturing

−52

−3

−22

Durable goods

−45

−1

−14

−16

Nondurable goods

−7

−2

−8

−1

−17

−30

−8

−16

−46

−7

−23

−8

Service-providing
Retail trade
Financial

activitiesc

PBSd
Temporary help services
Education and health services

−2

−3

−2

−10

−15

−49

−10

−19

−7

−32

−2

−30

−13

−10

Leisure and hospitality

−3

Government

−4

−2

Local educational services

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

Within the goods-producing sector, construction
shed 43,000 jobs and manufacturing shed 33,000.
Durable and nondurable goods manufacturing
faced similar losses amounting to 16,000 and
17,000 jobs, respectively. Within durable goods,
fabricated metal products (−9,300) and wood products (−5,600) suﬀered the greatest losses. Transportation equipment was one of the few subsectors to
add jobs during the month (7,100). Sectors experiFederal Reserve Bank of Cleveland, Economic Trends | July 2008

encing notable losses within nondurable goods were
printing and related support activities (−5,800) and
textile mills (−3,200).

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

2006

2007

2008 YTD

June 2008

Payroll employment

211

175

−73

−62

Goods-producing

−79

−69

Construction

−19

−42

−43

Heavy and civil engineering

−1

−4.9

Residentiala

−2

−10

−29

−21

Nonresidentialb

−9

−16.6

−7

−14

−22

−39

−33

Manufacturing
Durable goods

−4

−16

−27

−16

Nondurable goods

−8

−10

−6

−12

−17

Service-providing

179

172

130

Retail trade

−27

−7.5

−9

−6

−10

−33

Temporary help svcs.

−7

−26

−30.4

Education and health svcs.

Leisure and hospitality

Government

Local educational svcs.

−0.2

5.1

4.6

5.1

5.5

Financial

activitiesc

PBSd

Average for period (percent)
Civilian unemployment rate

4.6

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

Private Sector Employment Growth
Change, thousands of jobs: three-month moving average
350
300
250
200
150
100
50
0
-50
-100
-150
-200
2003

2004

2005

2006

2007

Source: Bureau of Labor Statistics.

Federal Reserve Bank of Cleveland, Economic Trends | July 2008

2008

The small overall gain in service-providing industries was the result of very mixed performances in
its subsectors. Gaining jobs were education and
health services (29,000) and leisure and hospitality
(24,000). Losing jobs were professional business
services (−51,000), ﬁnancial activities (−10,000),
trade, transportation, and utilities (-9,000), and
information (−4,000). Retail trade lost 7,500 jobs,
an improvement compared to May’s loss of 22,600
and April’s loss of 45,700. Some of the biggest
losses in the professional business service sector
were felt by administrative and support services,
which lost a whopping 70,200 jobs, and temporary
help services, which lost 30,400. Temporary help
16

Unemployment Rate for All Ages
Percent
12

Percent
27

services is often regarded as a leading indicator of
overall employment conditions, so this loss does
not paint an optimistic picture of the labor market
in the near future.

10
Ages 16-19

6
Ages
25+

15
12

2
1980

1984

1988

1992

1996

2000

2004

2008

Note: Seasonally adjusted rates for the civilian population.
Source: Bureau of Labor Statistics.

Average Nonfarm Employment Change
Change, thousands of jobs
250

Revised
Previous estimate

200
150
100
50
0
-50
-100
2005 2006 2007 2008 III
IV
YTD 2007

I
II
2008

Apr May Jun

Source: Bureau of Labor Statistics.

The three-month moving average of private sector
employment growth remains well in negative territory and relatively unchanged from the previous
report at -91,000. The moving average has been
negative since January.
While employment dropped 155,000, 144,000
people left the labor force, leaving the unemployment rate unchanged at 5.5 percent. A sharp increase (0.5 percentage point) in the unemployment
rate in the May report was particularly concerning,
although the series was thought to be noisy with an
unusually high increase in teenage unemployment.
The labor market activity of teenagers around
this time of year is tricky to measure. In May, the
unemployment rate for teenage workers increased
from 15.4 percent to 18.7 percent, as large numbers of young workers entered the labor market
but had yet to ﬁnd jobs. June’s unemployment rate
for teenagers sagged slightly to 18.1 percent but
remains at a very high level. However, 359,000
teenagers left the labor force this month, which is
a large number considering the overall labor force
decline of 144,000. Meanwhile, the unemployment rate for workers aged 25 and older increased
slightly from 4.1 percent to 4.3 percent.

Economic Activity and Labor Markets

Just When Did the Labor Market Begin to Soften?
Data on Job Gains and Losses Suggest It’s Earlier
than Previously Thought
07.08.08
by Yoonsoo Lee and Beth Mowry
While net employment changes are usually tracked
as a major indicator of the growth or decline of
the economy, these numbers mask the underlying
process that begets the net results, a process that
includes employment turnover, job creation, and
job destruction. To track this underlying process,
the Bureau of Labor Statistics launched its Business Employment Dynamics (BED) in 2003. BED
Federal Reserve Bank of Cleveland, Economic Trends | July 2008

is a set of statistics that tracks gross job gains and
losses between periods of net employment reports.
Gross gains represent the sum of all jobs added at
the opening and expanding of establishments, and
gross losses are the sum of all jobs lost at the closing
and contracting of establishments.

Gross Job Gains and Losses
Thousands
9,000
8,500

Gains
Losses

8,000
7,500
7,000
6,500
1992

1997

2007

2002

Note: BED data are seasonally adjusted on a quarterly basis, and represents
private sector jobs.
Source: Bureau of Labor Statistics.

Expansions versus Contractions and Openings
versus Closings
Percent of employment
8
7
Expansions

6
5

Contractions
4
3
Openings

2
1

Closings

0
1992

1997

2002

2007

Source: Bureau of Labor Statistics.

Net Employment Change
Jobs, thousands
1,500
BED data
1,000
CES data
500
0
-500
-1,000
-1,500
1992

1997

2002

2007

a. The CES data shown exclude the government sector for consistency with BED data.
Both cover private nonfarm employment here.
b. These CES data have been made quarterly by summing the net employment change for
each quarter.
Source: Bureau of Labor Statistics.

Federal Reserve Bank of Cleveland, Economic Trends | July 2008

The most recent BED data show gross job gains
totaling 7.25 million in the third quarter of 2007
and gross job losses totaling 7.5 million. Before this
quarter, the diﬀerence in the series, or net employment growth, had not been negative since the
second quarter of 2003, in the period following the
2001 recession now referred to as the jobless recovery. The rate of gross job gains fell to 6.4 percent
from 6.7 percent in the previous quarter, its lowest
since the series began. This decline is mostly explained by existing (or expanding) establishments,
where the rate of gains dropped from 5.5 percent to
5.1 percent. At new establishments, the rate of job
creation actually increased from 1.2 to 1.3 percent. The rate of gross job losses, in the meantime,
increased 0.1 percent to 6.6 percent. Again, existing
(or contracting) establishments were solely responsible for the rate change.
In fact, most gross job gain and loss activity occurs
at existing (expanding or contracting) establishments rather than at new or closing facilities. In the
third quarter of 2007, for example, 80 percent of
all job gains occurred at expanding establishments
and 82 percent of job losses occurred at contracting
establishments. The graph below illustrates this fact
by showing that activity at expanding and contracting establishments constitutes a much larger share
of total employment than that of new or closing
ﬁrms.
In fact, most gross job gain and loss activity occurs
at existing (expanding or contracting) establishments rather than at new or closing facilities. In the
third quarter of 2007, for example, 80 percent of
all job gains occurred at expanding establishments
and 82 percent of job losses occurred at contracting
establishments. The graph below illustrates this fact
by showing that activity at expanding and contracting establishments constitutes a much larger share
of total employment than that of new or closing
ﬁrms.
18

There are a number of diﬀerences between the two
data sets besides their frequency. Business Employment Dynamics is released quarterly with a
lag of about nine months. Not until the May 21
release did we see the numbers for the third quarter of 2007, while the CES Employment Report
is released monthly with just a one-month lag.
Although not as timely as the Employment Report,
BED data are based on the Quarterly Census of
Employment and Wages (QCEW). The QCEW requires all employers subject to state unemployment
insurance laws to submit employment and wage
information, so BED data are based on a virtual
census covering about 98 percent of all nonfarm
employers. The CES Employment Report, on the
other hand, is based on much smaller monthly
sample surveys and is benchmarked to the QCEW
data once a year.

Regional Activity

Fourth District Employment Conditions
07.10.08
by Tim Dunne and Kyle Fee

Unemployment Rates
Percent
8
7

Fourth Districta

6
5
United States
4
3
1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
a. Seasonally adjusted using the Census Bureau’s X-11 procedure.
Notes: Shaded bars represent recessions. Some data reflect revised inputs,
reestimation, and new statewide controls. For more information, see
http://www.bls.gov/lau/launews1.htm.
Source: U.S. Department of Labor, Bureau of Labor Statistics.

The district’s unemployment rate jumped 0.6 percent, to 6.1 percent, for the month of May. The increase can be attributed to monthly increases in the
number of people unemployed (12.4 percent) and
the labor force (0.3 percent), along with a decrease
in the number of people employed (−0.2 percent).
Compared to the national rate, the district’s unemployment rate stood 0.6 percent higher in May
and has been consistently higher since early 2004.
Since the same time last year, the Fourth District
unemployment rate has increased 0.7 percentage
point. The national rate has increased 1.0 percentage point.
There are considerable diﬀerences in unemployment rates across counties in the Fourth District.
Of the 169 counties that make up the Fourth
District, 32 had an unemployment rate below the
national average in April, and 136 had a higher
rate than the national average. Rural Appalachian
counties continue to experience higher levels of
unemployment.
The distribution of unemployment rates among

Federal Reserve Bank of Cleveland, Economic Trends | July 2008

Fourth District counties ranges from 4.5 percent
to 11.3 percent, with a median county unemployment rate equal to 6.5 percent. Only one of Pennsylvania’s Fourth District counties lies in the upper
half of the distribution compared to 65 percent of
Kentucky’s Fourth District counties that lie in the
upper half of the distribution.

County Unemployment Rates
U.S. unemployment rate = 5.5%

The distribution of monthly changes in unemployment rates across counties shows that the median
county’s unemployment rate increased 0.64 percentage point from April to May. The county-level
changes indicate that 98 percent of Ohio counties and 100 percent of Kentucky counties in the
Fourth District experienced an increase in their
unemployment rates. Alternatively, the unemployment rate in about half of the Pennsylvania counties in the Fourth District actually fell or did not
change from April to May. This is consistent with
previous Fourth District employment reports,
which have shown that Fourth District Pennsylvania has a much stronger labor market than Ohio
and Fourth District Kentucky and West Virginia.

4.5% - 5.6%
5.7% - 6.6%
6.7% - 7.6%
7.7% - 8.8%
8.9% - 11.3%
Note: Data are seasonally adjusted using the Census Bureau’s
X-11 procedure.
Source: U.S. Department of Labor, Bureau of Labor Statistics.

County Unemployment Rates
Percent
12.0
11.0
10.0

Percentage points

Ohio
Kentucky
Pennsylvania
West Virginia

9.0
8.0

Change in County Unemployment Rates,
April 2008 to May 2008

Median unemployment rate = 6.5%

7.0
6.0
5.0
4.0
3.0
County
Note: Data are seasonally adjusted using the Census Bureau’s X-11 procedure.
Source: U.S. Department of Labor, Bureau of Labor Statistics.

2.2
2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0
-0.2
-0.4

Ohio
Kentucky
Pennsylvania
West Virginia
Median change in unemployment rate = 0.64 percentage point

County

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

Regional Activity

Diﬀerences in Educational Attainment across States
07.10.08
by Timothy Dunne and Kyle Fee
Human capital is the term economists use to describe the skills and knowledge of a worker or, more
broadly, of the workforce. It is a main determinant
Federal Reserve Bank of Cleveland, Economic Trends | July 2008

Percent of Population with a Four-Year
Degree, 2006
Total U.S. (older than 25) with a four-year degree or higher = 27.0.

16.51% - 22.20%
22.21% - 24.90%
24.91% - 26.92%

2000

2006

26.93% - 30.43%

Mean (percent)

23.8

26.3

30.44% - 37.10%

Variance

18.3

21.7

Sources: Census and American Community Survey.

Percent of Population with an Advanced
Degree, 2006
Total U.S. (older than 25) = 9.9

6.13% - 7.38%

of economic growth for a country or a region. The
relationship between economic growth and human
capital is well established in economics (and is the
subject of the Federal Reserve Bank of Cleveland’s
2005 Annual Report). While human capital is
diﬃcult to measure, economists often use data on
educational attainment as a proxy for the amount
of human capital in a region or country.
In the United States, there are considerable differences in educational attainment across regions
and states. This is especially true when one focuses
on diﬀerences in the share of the adult population
with either four-year or advanced degrees. Currently, states with the lowest educational attainment
levels include West Virginia and Arkansas, where
the shares of the adult population with a four-year
college degree are 16.5 percent and 18.2 percent,
respectively. States with the highest educational
attainment levels (above 35 percent) are in the
Northeast and Mid-Atlantic, with Massachusetts
and Maryland topping the list. In 2006, the most
educated states had roughly twice the proportion of
adults with a college degree compared to the least
educated states.
A similar pattern is apparent when one examines the share of the population with advanced
degrees—a master’s degree or above. About 1 in
10 adults over 25 years old has an advanced degree
in the United States. Northeast and Mid-Atlantic
states generally have high shares of adults with
advanced degrees. Colorado and Washington also
have relatively high shares. States with relatively
low shares are located in the Mid-South and in the
Northern Plains.

7.39% - 8.39%
8.4% - 9.47%
9.48% - 10.90%
10.91% - 15.70%

2000

2006

Mean (percent)

8.4

9.5

Variance

4.2

5.5

Sources: Census and American Community Survey.

Of the Fourth District states, Pennsylvania has the
highest share of adults with four-year college and
advanced degrees, while West Virginia has the lowest. For both four-year and advanced degrees, Ohio
is in the second-lowest quintile of states—ranked
38th for 4-year degrees, and 33rd for advanced degrees. Kentucky is in the lowest quintile in the case
of 4-year degrees and second-lowest quintile in the
case of advanced degrees.
Comparing the data from the 2006 American
Community Survey to the 2000 Decennial Census,
the average state increased the share of its adult

Federal Reserve Bank of Cleveland, Economic Trends | July 2008

Growth in Share of Population with
a Four-Year Degree, 2000 to 2006
Percent
18
16
14
12
10
8
6
4
2
0

WY TX ID NM AZ OH OK AK OR VT TN KS IL MS WV NH MA WI MO MT LA NE PA NV RI KY
CO CT DE LA AK CA UT GA WA NC AL USA MN VA SC MD IN NJ MI ME FL HI NY SD ND

Sources: Census and American Community Survey.

Growth in Share of Population with
an Advanced Degree, 2000-2006
Percent
22
20
18
16
14
12
10
8
6
4
2
0

ID WY TX CA AZ AK NM TN GA DE TN US AL NJ LA MI MA SC PA OR RI NE PA WI NV SD
MS LA OK CT AK WV FL CO IN OH NH ME NY IL UT MO MA WA VT NC MN MD HI MT KY

Sources: Census and American Community Survey.

population with a college degree from 23.8 percent
to 26.3 percent—a 10.5 percent increase—as well
as its share of those with advanced degrees, from
8.4 percent to 9.5 percent—a 13.1 percent rise.
Depending upon the measure of variation used to
describe the spread of the data, the overall acrossstate variation in education rates either held steady
(the coeﬃcient of variation) or rose (the variance).
The diﬀerence between these two measures is that
the coeﬃcient of variation normalizes the variance
by the mean of a variable and thus adjusts for the
rise in the mean between 2000 and 2006. The key
point is that this steady-to-rising variation in the
state education data indicates that diﬀerences in
state educational attainment rates persisted over the
period 2000 to 2006.
Moreover, growth in the share of the adult population with a four-year degree also diﬀered markedly
across states. The growth rate ranged from a low of
4–5 percent for Wyoming and Colorado to a high
of 16 percent for Kentucky and North Dakota. A
closer look at the tails of the distribution for these
growth rates shows that states with both high and
low shares of adults with four-year college degrees
appear at both ends of the distribution. For example, Colorado and Connecticut, states with high
shares of degreed individuals, had relatively low
growth rates, while other highly educated states,
such as New York and Rhode Island, experienced
high growth rates. A similar pattern is found for
states with low educational attainment.
With respect to advanced degrees, the growth rates
ranged from a low of 4 percent to a high of 20
percent. Examining the tails of the distribution, it
is generally the states with low shares of advanced
degree holders that populate both ends of the distribution. Idaho, Mississippi, and Wyoming experienced low growth, while the Dakotas and Kentucky
had the highest growth rates. All these states had
relatively low shares in 2000 and still have low
shares in 2006. States with relatively high shares of
advanced degree holders are also spread across the
distribution, but these states do not appear in the
extreme tails of the growth rate distribution.
Looking at Fourth District states, Kentucky and
Pennsylvania have above-average growth in the

Federal Reserve Bank of Cleveland, Economic Trends | July 2008

share of the population with both four-year and
advanced degrees, while Ohio had below-average
growth in both categories. This is especially true in
the case of four-year college degrees, where Ohio’s
growth rate between 2000 and 2006 was the 11th
lowest among the 50 states. Alternatively, West
Virginia had somewhat higher growth in four-year
degrees than the nation in the period 2000-2006,
but lower growth in advanced degrees. However,
even with this higher-than-average growth rate in
four-year degrees, West Virginia remains the lowest
ranked of the 50 states, with only 1 in 6 adults over
25 having earned a four-year college degree.

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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Federal Reserve Bank of Cleveland, Economic Trends | July 2008

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