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September 2004

M

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T

H

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Y

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A

B

O

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REVIEW

Bureau of Labor Statistics

U.S. D ep artm en t o f L abor

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Federal Reserve Bank of St. Louis

Diurnal job injuries

Unions in Mexico

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Wages and benefits

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U.S. Department of Labor
Elaine L. Chao, Secretary
Bureau of Labor Statistics
Kathleen P. Utgoff, Commissioner
The Monthly Labor Review ( usps 987-800) is published
monthly by the Bureau of Labor Statistics of the U.S.
Department of Labor. The Review welcomes articles on the
labor force, labor-m anagem ent relations, business
conditions, industry productivity, com pensation,
occupational safety and health, demographic trends, and
other economic developments. Papers should be factual
and analytical, not polemical in tone. Potential articles, as
well as communications on editorial matters, should be
submitted to:
Editor-in-Chief
Monthly Labor Review
Bureau of Labor Statistics
Washington, dc 20212
Telephone: (202) 691-5900
E-mail: mlr@bls.gov
Inquiries on subscriptions and circulation, including address
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MONTHLY LABOR

REVIEW_______________________
Volume 127, Number 9
September 2004

U.S. import and export prices in 2003

3

Prices for both imports and exports rose over the year,
with the export price index posting its largest gain since 1995

Melissa E. Schwartz

Declining union density in Mexico, 1984-2000

10

About three-fourths of the decline in Mexico’s labor unions
has been accounted for by structural and institutional changes

David Fairris and Edward Levine

The diurnal pattern of on-the-job injuries

18

Data indicate that the injury hazard is substantially higher
late at night than during regular daytime work hours

Kenneth N. Fortson

Accounting for wages and benefits using the ECI

26

Workers at the bottom part of the wage distribution exhibit
a stronger correlation between benefits and wages than those at the top

Jonathan A. Schwabish

Reports
Employment in the information sector in March 2004
Post-recession trends in nonfarm employment and related indicators

42
49

Departments
Labor month in review
Report from the regions
Précis
Visual essay
Book review
Current labor statistics

2
42
48
49
57
59

Editor-in-Chief: Deborah P. Klein • Executive Editor: Richard M. Devens • Managing Editor: Anna Huffman Hill • Editors: Brian
I. Baker, Kristy S. Christiansen, Richard Hamilton, Leslie Brown Joyner • Book Reviews: Richard Hamilton • Design and Layout:
Catherine D. Bowman, Edith W. Peters • Contributor: Gary Martin


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Labor in Month Review

The Septem ber Review
Our lead article welcomes back an annual
review of international prices for imports
and exports to the United States. Melissa
E. Schw artz finds that im port price
increases abated in 2003 compared with
2002, while the rate of increase in export
prices rose substantially. Price increases
for petroleum and related products were
much less sharp than in the previous year,
but those for other imports accelerated
somewhat. On the export side, price
increases were larger for both agricultural
and nonagricultural items.
D avid Fairris and Edw ard Levine
analyze the decline in unionization in
the M exican workforce. They find that
dem ographic and econom ic factors
such as in d u stry , o c c u p a tio n , and
worker characteristics account for a
relatively small part o f that decline,
w h ile in s titu tio n a l and s tru c tu ra l
changes account for much more.
Kenneth N. Fortson examines the
d iu rn a l, or in tra d a y , p a tte rn o f
occupational injuries. Using injuries
d a ta fro m th e T exas W o rk e rs ’
C o m p e n s a tio n C o m m issio n and
w orking tim e data from the Current
Population Survey, Fortson concludes
that injuries are much more prevalent at
night, even after accounting for worker
ch a ra c teristic s, broad ind u stry and
occupational classification, and length
of time at work.
Jonathan A. Schw abish uses data
from the Employment Cost Index as the
b a sis o f an a n a ly s is o f p o ss ib le
c o rre la tio n s b e tw e e n w ag es and
benefits. Among workers in the lower
10 p e rc e n t o f e a rn in g s , he fin d s
s ig n ific a n t n e g a tiv e re la tio n s h ip s
between wages and benefits such as life
insurance and pension plans in several
specifications o f a regression equation.
Gerald Perrins contributes the first in
what we plan as a series of “Reports
from the Regions.” Perrins, the regional
economist in the Bureau’s Philadelphia
office, reports on employment trends in
the information sector.
2

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David Langdon, Rachel Krantz, and
M ichael Strople provide a visual essay
on post-recession trends in employment
and related economic indicators. The
visual essay format is another relatively
new feature of the Review.

More than 10 jobs before 40
Persons bom from 1957 to 1964 held an
average of 10.2 jobs from ages 18 to 38.
These younger baby-boomers held an
average of 4.4 jobs while ages 18 to 22.
The average fell to 3.3 jobs while ages
23 to 27, to 2.6 jobs while ages 28 to 32,
and to 2.5 jobs from ages 33 to 38. (Jobs
that span more than one age group were
counted once in each age group, so the
overall average number of jobs held is
less than the sum of the number o f jobs
across the age groups.)
On average, men held 10.4 jobs and
women 9.9 jobs from age 18 to 38. Men
held 4.5 jobs from ages 18 to 22, but only
2.5 jo b s from ages 33 to 38. The
reduction in the number of jobs held in
successive age groups was similar for
wom en. For m ore inform ation, see
“Number of Jobs Held, Labor Market
Activity, and Earnings Growth Among
Younger Baby Boomers: Recent Results
From a Longitudinal Survey,” news
release u s d l 04-1678.

Summer youth labor force
The labor force participation rate for
y o u th — th e p ro p o rtio n o f the
population age 16 to 24 working or
looking for work— was 67.2 percent in
July 2004, about the same as in July
2003. These were the lowest rates for
July since 1966. The proportion of 16to 24-year-olds enrolled in school in
July has grown over the last decade—
from 16.3 percent in 1994 to 28.9 percent
in 2004— and labor force participation
rates for students are typically lower
than for nonstudents. Only about half
of the youth enrolled in school were in
the labor force in July, compared with
about th ree-fourths of those not in

September 2004

school. Find out more in “Employment
and U nem ploym ent Among Youth—
Summer 2004,” news release USDL 041590. (The data in this report are not
seasonally adjusted.)

Veterans’ unem ploym ent in
August 2003
T he u n em p lo y m e n t ra te s o f m ale
veterans ages 25 to 34 (4.7 percent) and
ages 35 to 44 (3.8 percent) were lower
than the rates of their nonveteran peers
(6.3 and 4.8 percent, respectively) in
August 2003. Among men 45 to 54 years,
however, veterans had a higher jobless
rate than nonveterans (5.4 versus 3.6
percent).
Female veterans ages 25 to 34 had a
relatively high unemployment rate of 8.2
percent, but the rate was much lower for
those ages 35 to 44 (3.4 percent). Among
female nonveterans in these age groups,
unemployment rates did not differ nearly
as much— 6.2 percent for those 25 to 34
years and 5.2 percent for those 35 to 44
years. Female veterans ages 45 to 54 had
a jo b le ss rate o f 5.4 p ercen t, little
d iffe re n t from th e ir n o n v e te ra n
contemporaries.
The survey of veterans was conducted
for the Bureau of Labor Statistics by the
U .S. C ensus B ureau as a special
supplement to the August 2003 Current
Population Survey. The 2003 supplement
was co-sponsored by the U.S. Department
o f V eterans A ffairs and the U.S.
D epartm ent of L ab o r’s Veterans Em ­
ployment and Training Service. These
supplements have been conducted every
two years since 1985. To learn more, see
“Em ploym ent Situation of Veterans:
August 2003,” USDL 04-1378._________

Re view chief retires
Deborah P. Klein, Editor-in C hief of

Monthly Labor Review and Bureau of
Labor Statistics Associate Commissioner
for Publications and Special Studies,
retired last month after 38 years of service
to the Bureau.
[]

Import and Export Prices, 2003

U.S. import and export
prices in 2003
Prices for imports and exports rose during 2003,
with price increases for petroleum and petroleum products
leading import prices; the overall export price index
posted its largest gain since 1995
Melissa E. Schwartz

Melissa Schwartz is a
senior economist in
the Division of
International Prices,
Bureau of Labor
Statistics, Washington,
DC.


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n 2003, overall U.S. import and export prices
increased for the second consecutive year.1
Prices for imports rose 2.4 percent, following a
4.2-percent rise in 2002, while export prices gained
2.2 percent, up from a 1.0-percent rise in 2002.
During 2001-03, U.S. economic indicators for
prices suggested a marked slowdown in inflationary
pressures, and in May of 2003, the Federal Reserve
Board expressed concern over the possibility of an
“unwelcome substantial fall” in inflation.2 Never­
theless, prices for agricultural and petroleum
products—traditionally volatile price components—
strengthened along with prices for other raw
materials during 2003 to bring about overall gains
for the year. However, the increases in prices for
these two commodity areas, along with the depre­
ciation of the U.S. dollar against many major
foreign currencies, did not appear to have a signi­
ficant impact on prices for imported finished goods.
Prices for imported petroleum and petroleum
products led to the overall growth in import prices,
but the 12.8-percent increase in the petroleum index
was up far less than the sharp increase of 56.9
percent in 2002. The increase in the index for all
imports excluding petroleum accelerated in 2003,
rising 1.2 percent, compared with a modest 0.3percent advance the previous year, as nearly all
major categories of imports recorded price increas­
es in 2003. The U.S. dollar’s depreciation against
many major currencies appeared to have a small
impact on the 2003 increases in prices for imported
finished goods.
Agricultural and nonagricultural export prices
both increased in 2003 by larger amounts than in

I

2002, triggering the largest gain in the overall
export price index since 1995. Over the past year,
agricultural export prices jumped 13.4 percent,
while nonagricultural commodities prices, led
primarily by increases in prices for raw materials,
were up 1.3 percent. Both components marked
their largest December-to-December increase in
the index since 1995. Automotive and consumer
goods prices also increased in 2003, while the
index for the capital-goods component posted its
eighth consecutive annual decline. (See table 1.)

Other price measures
The Bureau of Labor Statistics produces various
price indexes that measure different aspects of
inflation in product markets: import and export
price indexes, which measure the change in the
prices of imports and exports of nonmilitary goods
exchanged between the United States and the rest
of the world; the Consumer Price Index, which
measures inflation as experienced by consumers in
their day-to-day living; and the Producer Price
Indexes, which are a family of indexes that measure
changes in the selling prices received by domestic
producers of goods and services at various stages
of processing. The Consumer Price Index for All
Urban Consumers (CPI-U) rose 1.9 percent in 2003,
a slowdown from its 2.4-percent advance in 2002.
The core CPI-U, which excludes energy and food
prices, increased 1.1 percent in 2003, less than the
1.9-percent rise in 2002 and the 2.7-percent
increase in 2001. Smaller increases in prices for
shelter costs, motor vehicle insurance, and medical

Monthly Labor Review

September 2004

3

Import and Export Prices, 2003

Table 1.

End

U.S. import and export price indexes, annual percent changes for selected categories of goods, 1994-2003

Relative
im portance,
N ovem ber
20032

D escription

P ercen t c h a n g e for 12 m onths e n d e d in D e c e m b e r —

1994

1995

1996

100.000

5.2

2.6

89.171
87.650
4.144

3.8

2.4

14.7

-2.7

-1.3

1.3

-3.1

-.3

26.501

12.9

6.1

9.1

-10.4

-17.1

15.670

9.0

6.4

-2.4

-1.7

1997

1998

1999

20 00

2001

20 02

1.5

-5.2

-6.4

7.0

3.2

-9.1

4.2

2.4

-1.8

-2.8

-3.3

.0

1.3
-4.0

-4.5
_
-4.7

.3
.0
5.9

1.2
1.0
3.0

33.7

13.8

-24.6

21.9

9.5

-6.7

5.1

11.2

-14.6

5.8

7.2

_

_

_

_

3.6

6.3

27.1

-41.9

53.7

13.2

20 03

Im ports

All commodities..............
All imports, excluding
petroleum ..............................
All imports, excluding fuels......
Foods, feeds, and beverages ..

0
1

Industrial supplies and
materials.............................
Industrial supplies and
materials, excluding
petroleum..........................
Industrial supplies and
materials, excluding fu e ls.

10

Fuels and lubricants.....

-

14.149

-

-

-

12.353

16.9

5.7

Petroleum and
petroleum products ..

10.831

20.3

2

Capital goods........................

28.371

1.0

3

Automotive vehicles, parts,
and engines........................
Consumer goods, excluding
automotives........................

17.170

100

4

-

-

-

-

-

-

-

34.4

-23.8

-36.5

114.7

6.0

33.7

-25.5

-40.8

137.2

17.6

-39.5

56.9

12.8

1.1

-3.8

-7.4

-5.0

-3.3

-2.1

-2.7

-2.4

-1.1

3.0

2.3

.0

.5

.0

.7

.7

-.2

.5

.9

23.794

1.1

1.8

-.7

-.9

-1.3

-.4

-1.2

-.8

-.7

.1

100.000
8.540
91.459

3.9
-.2
4.4

3.3
17.3
1.7

-1.1
-6.9
-.4

-1.2
-2.9
-1.0

-3.4
-9.3
-2.7

.5
-6.8
1.2

1.1
3.1
.9

-2.5
-1.8
-2.5

1.0
8.0
.4

2.2
13.4
1.3

Exports

All commodities...........
Agricultural commodities.........
Nonagricultural commodities....
0

Foods, feeds, and beverages..

7.741

-2.7

19.9

-6.5

-3.3

-8.3

-5.7

1.7

-.5

7.9

12.6

1

Industrial supplies and materials
Nonagricultural industrial...........
supplies and materials.........

23.504

15.6

1.5

-2.3

-1.4

-7.1

5.3

3.6

-8.6

5.0

6.8

22.111

15.0

1.6

-2.2

-1.3

-6.9

6.3

3.3

-8.4

4.8

6.3

2

Capital goods............................

46.308

-1.1

1.8

.1

-1.6

-1.8

-1.1

.3

-.8

-1.3

-.6

3

Automotive vehicles, parts,
and engines..........................

10.870

1.5

1.6

.4

.8

.5

1.0

.5

.4

.8

.5

4

Consumer goods, excluding....
automotives...........................

11.538

.5

1.6

1.4

.8

-.8

.6

-.4

.2

-.6

.6

1Bureau of Economic Analysis category.
2 Relative importance figures are based on 2000 trade values.
N ote : Dash indicates data not available.

care, coupled with declines in prices for cigarettes and used cars,
contributed to the increase in 2003.
The Producer Price Index (ppi) for finished goods increased
4.0 percent in 2003, following a 1.2-percent rise in 2002.
Excluding food and energy prices, the PPI for finished goods
was up 1.0 percent, and the ppi for intermediate materials was
up 2.1 percent, in 2003. Prices for crude nonfood materials less
energy increased 20.8 percent over the year. (See chart 1.)

4

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September 2004

Import price trends
Energy.

Following a 56.9-percent spike in 2002, the index
for petroleum and related products rose 12.8 percent in 2003,
driven largely by a 12.0-percent increase in crude-oil prices.
Tight world crude-oil supplies and geopolitical uncertainties in
2002 carried into 2003. In January, crude-oil prices rose sharply
due to a shortage of imports from Venezuela, which faced a

Chart 1.

Changes in the CPI, PPI, and import and export price indexes, 1999-2003

12-month
percent change

1999

12-month
percent change

2000

2000

2001

2001

work stoppage at its State-owned oil company Petróleos de
Venezuela from late 2002 into the early part of 2003. Venezuela
ranks as the world’s fifth-largest oil supplier and fourth as a
supplier of crude oil to the United States. As a result of the work
stoppage, U.S. refineries conserved existing crude inventories
by reducing inputs into refinery production, thereby drawing
down the inventories, which remained extremely low through
February. Furthermore, strong seasonal demand, combined with
Middle East supply disruptions and cuts in production levels from
the Organization of Petroleum Exporting Countries (OPEC),
pushed petroleum and related products prices higher in 2003. At
the same time, natural-gas prices spiked 93.0 percent in the first
3 m onths o f the year. Tight oil m arkets and bitterly cold
temperatures early in the year sent demand for natural gas
soaring, and by April, storage was more than 45 percent below
the 5-year average.
By March, Venezuelan oil imports resumed, causing crudeoil prices to drop slightly. Then, in April, the U.S. advance in
Iraq and an abundance of crude imports— a record average of
10.6 million barrels per day— led crude-oil prices to plummet
15.5 percent. Inventories in the United States subsequently
increased by more than 12 million barrels, but remained at least
40 million barrels below 5-year averages. Similarly, prices for
petroleum products and natural gas dropped due to a slackening
oil market and moderating temperatures. By summer, however,


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2002

2002

2003

2003

seasonal travel demand pushed up gasoline prices, while demand
for cooling increased natural-gas prices. Meanwhile, a 7-percent
production cut announced by OPEC, coupled with a temporary
decline in crude exports out of Iraq, kept crude-oil markets tight.
Gasoline prices pushed higher in the summer due to a pipeline
rupture in Arizona and a shutdown of three Midwest refineries as
a result of the August power blackout. By fall, declines in demand
allowed both natural-gas and crude-oil inventories to build back
up somewhat; however, an announcement by OPEC that it would
cut exports by a further 900,000 barrels of crude oil per day
effective November 1 affected energy spot markets, and crude
prices of imports rose 8.7 percent over the last quarter of 2003.
Thus, despite the sharp increase during the first quarter,
natural-gas prices fell 38.4 percent throughout the remainder
of 2003, to finish up 18.8 percent overall over the year.

Nonjuel industrial supplies and materials.

This component—
which excludes petroleum, natural gas, coal, and nuclear and
electrical energy— made up nearly 14 percent of the U.S. import
price index for all commodities.3 The price index for nonfuel
industrial supplies and materials finished up 6.3 percent for the
year, compared with a 3.6-percent increase the previous year.
Prices for every subcomponent of nonfuel industrial supplies
and materials advanced in 2003, with chemicals and unfinished
metals prices having the largest impact. In the chemicals area,

Monthly Labor Review

September 2004

5

Import and Export Prices, 2003

which was up 4.5 percent for the year, fertilizers, insecticides,
and pesticides prices, along with plastics prices, were the major
contributors. Higher energy prices increased feedstock costs,
which in turn pushed chemicals prices up. Unfinished metals
also increased for the second consecutive year, by 8.4 percent,
following an 11.4-percent rise in 2002. Gold and silver prices
increased over the year due to speculative fund buying, as
investors saw these m etals as a safe alternative to other
financial assets. Furthermore, favorable economic news, such
as improvements in GDP growth and a declining unemployment
rate, in the latter part of the year helped push up spot prices for
platinum and other base metals, such as copper, nickel, and
aluminum, reflecting hopes for a pickup in future demand for
these p ro d u ctio n inputs. In add itio n , an ex p ansion in
manufacturing in Asia, particularly in China, helped boost
demand for metal inputs, thereby creating upward pressure on
world prices.4Indeed, China’s demand for platinum in the jewelry
sector was instrumental in sending platinum prices to 23-year
highs.
Higher base-metal prices affected prices for finished metals,
which rose 4.3 percent in 2003 after declining 1.1 percent in
2002. Prices for steelmaking and ferroalloying materials, along
with prices for iron and steel products, increased over the year,
up 19.4 percent and 6.2 percent, respectively. A lthough
inclement weather early in the year, political nervousness
over Iraq and Venezuela, and high energy prices affected the
supply side of the world steel market, international demand
for scrap was heavy, particularly in Asia. Domestically, a
weak dollar and tariffs on imported steel caused the quantity
of imported steel products to decline by more than 40 percent
in 2003.5
Prices for building materials (such as lumber and panels)
also pressed higher in 2003, up 13.7 percent for the year,
following a modest 2.3-percent increase in 2002. Although
demand was off in the first quarter of the year due to the slow
winter season combined with market concerns over affairs in
the M iddle East, purchasing picked up in late spring because
of low mortgage rates and strong housing starts, the latter up
15 percent for the year.6 In August, plywood prices surged
due to a large U.S. Government purchase for rebuilding Iraq
and an increase in demand with Hurricane Isabel’s arrival.7
The price indexes for paper and paper base stocks, for
textile supplies and related materials, and for agricultural
industrial supplies and m aterials all increased in 2003.
Woodpulp prices rose a sharp 16.6 percent, the result of a
first-quarter turnaround in prices due to w eather-related
industry shortages and energy costs. Textile supplies prices
increased 4.0 percent for the year, reflecting higher cotton
and energy prices and a weakened U.S. dollar. Finally, prices
for agricultural industrial supplies and materials increased
4.6 percent in 2003, led by a surge in rubber prices. World
prices for natural rubber increased primarily in the last 4

6

Monthly Labor Review


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September 2004

months of 2003, due to strong demand from tiremakers,
increased market demand from China, and heavy rains in
Southeast Asia that constricted supplies.8

Capital goods. Capital goods represent approximately 28
percent of U.S. imports and include many products, such as
electrical generating equipment; computers, peripherals, and
semiconductors; and transportation equipment, excluding
motor vehicles. The capital-goods category was the only
major import category to decline in 2003, falling 1.1 percent.
This index has declined every year since 1995 and has
trended with the steady decline in prices for com puters,
peripherals, and semiconductors— 55.8 percent over the last
decade. Since the end of the technology boom of the 1990s,
computer and semiconductor sales have slumped along with
sales of telecommunications equipment. Concomitantly, with
rapid innovation keeping manufacturing costs low and the
industry undergoing consolidation, prices have continued to
decline steadily. Semiconductor sales showed a promise of
rebounding in 2003, fueled by strong worldwide demand
(particularly from Asia).9
Prices for capital goods, excluding computers, peripherals,
and semiconductors, increased 1.2 percent in 2003, reversing
the trend over the previous decade. The price index for electrical
generating equipment increased 2.0 percent over the year. This
index, along with prices for nonelectrical machinery, excluding
computers, peripherals, and semiconductors, which rose 0.9
percent over the year, was influenced by exchange-rate effects
and higher costs for raw m aterials. Similarly, prices for
transportation equipment, excluding motor vehicles, increased
1.8 percent in 2003, the result of higher input costs, higher fuel
prices, and the depreciation of the dollar.
Consumer goods. Consumer goods account for approximately
24 percent of U.S. imports. In 2003, consumer goods prices
rose a modest 0.1 percent, the first annual increase since a 1.8percent rise in 1995. Price movements within the consumergoods category were mixed; price increases for manufactured
nondurables and for nonmanufactured consumer goods offset
a decline in prices for manufactured durables. Manufactured
nondurables prices were affected, in general, by raw materials
costs, along with exchange rates, while the decline in prices
for manufactured durables was the result of declines in home
entertainment equipment prices.
Automotive vehicles, parts, and engines.

This component
makes up about 17 percent of U.S. imports, and prices were
up 0.9 percent in 2003, following a 0.5-percent increase in
2002 and a 0.2-percent decline in 2001. All subcategories of
automotives, parts, and engines had price increases in 2003.
Historically, most increases occur in the fall of each year with
the introduction of new models.

As with most other categories of manufactured goods, raw
material costs and the U.S. dollar’s depreciation against many
major currencies put upward pressure on prices for automotive
parts and engines. However, import prices for automobiles did
not increase as much as would be expected on the basis of the
U.S. dollar’s depreciation, indicating that foreign manufacturers
absorbed some of the exchange-rate effects to maintain market
share, particularly in the lower priced models. Prices for
imported parts increased 0.7 percent in 2003, but were still 0.7
percent below 2000 levels. With sales slow and competition, in
general, intense, auto manufacturers continue to pressure their
suppliers to keep parts prices low.

Foods, feeds, and beverages.

The price index for foods, feeds,
and beverages increased 3.0 percent in 2003, following a 5.9percent increase in 2002. Prices for agricultural foods, feeds,
and beverages increased 4.6 percent, while prices for nonagricultural foods posted a decline of 1.7 percent. Beef prices
pressed higher due to a smaller U.S. herd and a shortage of
livestock because of an embargo on Canadian cattle imports.
Vegetables prices also increased in 2003, by 3.4 percent,
countering declines in coffee and fruit prices. The decline in
prices for nonagricultural foods was the result of shrimp
continuing to be in oversupply, while lobster prices fell after
winter 2002-03 highs.

Locality o f Origin price indexes.

Another avenue for analyzing
import price movements— particularly when assessing the
impact of exchange rate fluctuations— is to consider import
prices by country or region of origin. The Bureau produces such
price indexes according to seven major regional categories:
Industrialized Countries, Other Countries, Canada, the European
Union, Latin America, Japan, and the Asian Newly Industrialized
Countries (NIC’s). Within the first five of these localities, the
price indexes are further disaggregated by manufactured and
nonmanufactured goods.
Import prices for the European Union increased 3.4 percent
in 2003, following a 3.6-percent increase in 2002. The U.S.
dollar depreciated significantly against major foreign currencies
in 2003: over the year, the dollar fell against the Euro by 17
percent.10 After rising 6.4 percent in 2002, the price index for
Canadian imports increased 5.2 percent in 2003, a year in which
the U.S. dollar fell against the Canadian dollar by 16 percent.
Also in 2003, prices for imports from Japan edged up 0.1
percent, following a decline of 2.5 percent in 2002. The U.S.
dollar declined against the Japanese yen by 12 percent in 2003.
In general, currency effects have not been fully passed on to
import prices, for a variety of reasons, including worldwide
excess capacity preventing prices from rising; foreign exporters
holding their prices steady to maintain market shares; and an
increasingly integrated and com petitive global economy
weakening com panies’ power to pass on higher costs to
customers.11


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In contrast, the Asian n ic ’s price index fell 0.4 percent in 2003
after declining by 2.7 percent in 2002 and 5.5 percent in 2001.
Prices for finished goods—particularly capital goods— were the
primary contributors to the downward trend in this index.
Furthermore, the Asian nic’s price index is unaffected by currency
fluctuations, because the respective currencies are either pegged
to the U.S. dollar or managed within a specified range.
Energy prices also affected the Locality of Origin price indexes,
including the index for Latin American imports, which rose 3.7
percent in 2003. Prices for nonmanufactured imports from Latin
America rose 10.6 percent over the year. Oil and gas imports
from Canada and the European Union totaled nearly $30 billion
in year-2000 weights, and the respective 8.7-percent and 14.1percent increases in those commodities’ (non-manufactured
imports) prices reflect higher energy prices.

Services.

The Bureau publishes a set of services price indexes,
primarily transportation related. The U.S. import price index
for air passenger fares, which measures fares paid to foreign
carriers by U.S. residents for international travel, declined 0.2
percent in 2003 after rising 1.4 percent in 2002. The price index
for import air freight, which measures changes in rates paid for
the transportation of freight from foreign countries to the United
States on foreign air carriers, increased 7.5 percent in 2003.
Unlike the index’s 11.8-percent gain in 2002— the result of the
West Coast port shutdowns— the 2003 increase parallels the U.S.
dollar’s depreciation and demand-driven increases in shipment
volumes.
Inbound ocean liner rates picked up in 2003, increasing 26.3
percent over the year. The majority of the increase occurred
worldwide, concomitantly with contract renegotiations in the
second quarter. The renegotiations came about out of attempts
to compensate for unanticipated industry growth and high
demand that began in 2002, particularly from China, the United
States, and Europe.12Inbound crude-oil tanker freight rates also
increased in 2003, by 16.8 percent. Prices surged in the first
quarter due to diminished tanker availability. Thereafter, a
reversal in tanker freight rates was followed in late fall by a
resumption of rate increases, driven by seasonal stockpiling and
weather-related transit problems.

Export price trends
Agricultural goods.

Prices for foods, feeds, and beverages
rose 12.6 percent in 2003, following an 8.0-percent increase in
2002. Substantial increases in soybean and m eat prices
contributed to the rise in the overall foods, feeds, and beverages
index. Soybean harvest shortages due to hot, dry weather in
South America and Europe led to diminished world supplies,
and significant demand from China and Europe pushed soybean
prices higher. Meat supplies, particularly beef, have been tight
due to the ban on imports of live cattle from Canada. Moreover,
Monthly Labor Review

September 2004

7

Import and Export Prices, 2003

concerns about avian flu in Asia led to a widespread slaughter of
chickens on that continent.
Agricultural industrial supplies and materials increased 15.3
percent in 2003, following a 9.2-percent rise in 2002. Prices for
cotton and tallow were the primary contributors to the 2003
increase. Also, China’s demand for cotton imports has grown by
nearly 600 percent in the last year.13Meanwhile, world stocks of
cotton were low in 2003, and the combined result of this, together
with China’s rising demand, was an increase in cotton prices.
Prices for tallow, which is an animal fat and a substitute for
soybean and other oils, followed increases in soybean oil prices.
Relatively low slaughter counts resulting from the Canadian cattle
embargo added to the upward pressure on tallow prices.14

Nonagricultural industrial supplies and materials.

The
category of nonagricultural industrial supplies and materials
accounts for about 22 percent of U.S. exports and includes goods
such as energy, metals, paper, chemicals, industrial textiles,
rubber, and building materials. The price index for this category
rose 6.3 percent in 2003, up from a 4.8-percent increase in 2002.
Prices for chemicals and metals were the major contributors to
the annual increase; prices for fuels and building supplies
increased in 2003 for reasons similar to their import counterparts.
Export prices for steel, woodpulp, and synthetic rubber
increased substantially in 2003. Rising energy prices and heavy
demand from Asia— China in particular— caused ferrous scrap
prices to soar. The export woodpulp industry similarly benefited
from Chinese demand, offsetting the economic downturn of the
domestic pulp and paper sector since the most recent U.S.
recession. In addition, prices for synthetic rubber, a substitute for
natural rubber, followed the upward movement of world prices
for that commodity.

Capital goods. On the export side, capital goods represent
approximately 46 percent of the volume of U.S. trade. As with
the import side, prices for capital goods for export declined in
2003. The 0.6-percent drop followed declines of 0.8 percent
and 1.3 percent in 2001 and 2002, respectively. Prices for
computers, peripherals, and semiconductors, down 4.3 percent
over the past year and 47.7 percent over the past decade, are
the primary m over of capital-goods prices. Import and export
prices for com puters and sem iconductors have behaved
similarly, the result of a competitive industry and declining
manufacturing costs. Also contributing to the annual decline
in capital-goods prices were telecommunications equipment

prices, which fell 4.3 percent in 2003 and 3.0 percent in 2002.
After finding themselves overinvested in infrastructure at the
end of the technology boom of the 1990s, telecommunications
firms have been forced to restructure debt and cut costs in the
face of strong competition. Consumer demand, however, remains
strong as well.15 The other components of capital goods—
nonelectrical machinery (excluding computers, peripherals, and
semiconductors) and transportation equipment (excluding motor
vehicles)— posted annual increases of 0.4 percent and 3.1
percent, respectively. As with their import counterparts, higher
input costs and foreign currency effects contributed to the
increases.16

Consumer goods. After falling 0.6 percent in 2002, prices for
consumer goods rose 0.6 percent in 2003, as each subcategory
of the consumer goods price index increased. Increases in the
price indexes for household goods, for medicinal, dental, and
pharmaceutical preparatory materials, and for recreational
equipment more than offset modest price declines for apparel
and footwear and for home entertainment equipment.
Automotive vehicles, parts, and engines.

The price index for
exported automotive vehicles, parts, and engines increased 0.5
percent in 2003. Domestic automakers faced higher costs for
raw materials such as steel and rubber. Canada and Mexico are
the largest markets for U.S. cars, trucks, and parts. Although up
slightly in 2003, auto exports to Canada remain somewhat below
2000 levels. The volume of auto exports to Mexico dropped by
more than 10 percent in 2003 and was nearly 18 percent below
2000 levels.17

Services. The price index for export air passenger fares, a
measure of changes in foreign travel fares paid to foreign
carriers by U.S. residents, recorded an increase of 14.7
percent in 2003. During the first half of the year, the airline
industry faced increases in jet fuel costs and a downturn in
demand due to Middle East tensions and the outbreak of
severe acute respiratory syndrome ( s a r s ). In general, sea­
sonal price changes tend to dominate the industry. The price
index for export air freight, a measure of changes in rates
paid for the transportation of freight from the United States
to foreign countries on U.S. carriers, increased 0.2 percent
last year, as adjustments to fuel surcharges led to increased
prices in the early part of the year, followed by small declines
thereafter.
□

Notes
1Annual percent changes are calculated from December to December,
unless otherwise specified. Data are not seasonally adjusted.
2 Federal Open Market Committee Statement, May 6, 2003.
3 The 2003 import and export price indexes are based on trade dollar

8

Monthly Labor Review


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Federal Reserve Bank of St. Louis

September 2004

values for the year 2000. Beginning with the January 2004 import and
export price indexes, the Bureau has been updating its weights on an annual
basis, with, however, a 2-year lag.
4 See “A copper-bottomed boom?” The Economist, Oct. 2, 2003.

5 Fact Sheet (U.S. International Trade Administration, Jan. 27,
2004).
6 New Residential Construction (U.S. Census Bureau, December
2003).
7 nawla Bulletin (North American Wholesale Lumber Association,
Sept. 22, 2003).

8 See “Surging rubber prices put exporters in risky situation” (Thailand
Department of Export Promotion, Nov. 10, 2003); on the Internet at http:
//w w w.thaitrade.com /exportnew ssurging.shtm l.

13 Cotton: World Markets and Trade (U.S. Department of Agriculture,
Foreign Agriculture Service, March 2004). The percent change in
Chinese imports was calculated on the basis of the cotton season from
August 2002 to August 2003.
14 Oil Crops Yearbook (U.S. Department of Agriculture, Economic
Research Service, Oct. 22, 2003).
15 See “Beyond the bubble,” The Economist, Oct. 9, 2003.

11 See “Dollar’s Decline Has Little Impact on Import Prices,” The
Wall Street Journal, Jan. 14, 2004; and “A faded green,” The Economist,
Dec. 6, 2003.

16 Although most transaction prices collected by the Bureau are in U.S.
dollars, some prices are reported in a foreign currency, and those prices
must be converted into U.S. dollars for use in price index calculations.
Currency fluctuations directly affect export prices when foreign-currencybased transactions prices are converted into U.S. dollars. Economic theory
suggests that currency fluctuations should indirectly affect both import and
export prices over time, depending on several factors, such as the magnitude
and duration of the fluctuation, the nature of the industry for which the
particular good is being priced, and the general state of the global economy.

12 See “Shipping prices move into the fast lane,” The Wall Street
Journal, Nov. 6, 2003.

17 Product trade data were obtained from the Foreign Trade Statistics
Division of the U.S. Census Bureau.

9 See “Asia Has Chipmakers Cheering,” Business Week, Dec. 8,
2003.
10 fred (Federal Reserve Economic Data) II, database maintained by
the Federal Reserve Bank of St. Louis.


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Monthly Labor Review

September 2004

9

Union Density in M exico

ms

Declining union density
in Mexico, 1984-2000
Since the mid-1980s, Mexico has witnessed
a significant decline in unionization; changing industry,
occupation, and demographic worker characteristics
account for only about one-fourth of the decline, while structural
and institutional changes account for three-fourths.

David Fairris
and
Edward Levine

David Fairris is a
professor and Edward
Levine is a doctoral
student in the
Department of
Economics at the
University of California,
Riverside. Edward
Levine is currently also
a lecturer at Queens
College, CUNY.
E-mail:
david.fairris@ucr.edu
tedlevine@earthlink.net
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nions have experienced membership
setbacks in a number of countries since
1984. In Mexico, union density has
declined for the labor force as a whole, and also
across a wide spectrum of industries and occu­
pations. Only a small proportion of the decline
is accounted for by changes in industry, occu­
pation, and demographic characteristics. Most
of the decline is attributable to the changing
structural/institutional context within which
unions organize new workers and retain exist­
ing m em bers, which could include, for ex­
ample, changing government policies and in­
creasing employer resistance to unions.
This article examines the union density situ­
ation in Mexico, using individual workers’ re­
sponses to a nationally representative series of
household surveys. This approach allows ac­
tive union rep resen tation to be m easured.
Workers who self-report being union members
are less likely to be a party to protection con­
tracts — that is arrangements in which employ­
ers pay unions a fee (often unbeknownst to
w orkers) for explicitly failing to represent
labor’s interests at the worksite. Labor schol­
ars have argued that protection contracts have
been on the rise in recent years in Mexico.

U

The data
This article derives weighted estimates of the
September 2004

proportion of the labor force affiliated with a
union for various years from 1984 to 2000, both
in the aggregate and by industry, occupation,
and proximity to the border with the United
States. Data are from the National Survey of
Household Income and Expenditures (Encuesta
Nacional de Ingresos y Gastos de los Hogares
— or e n ig h ) — a national sample of households,
stratified by population size of locality, with
sampling weights that make estimates drawn
from the sample nationally representative.1 The
data contain a number of useful worker charac­
teristics, including whether workers are affili­
ated with a union in their principal job, their
monthly pay and average weekly hours worked
at this job, their industry and occupation, edu­
cational level, and demographic characteristics
such as age and gender. To make meaningful
inter-temporal comparisons, this article uses
detailed industry and occupation categories that
are consistent across all years.2
Restricting the sample in a number of ways
ensures the reliability and meaningfulness of the
estimates, and particularly the union/nonunion
comparisons. This study excludes workers un­
der age 16, those who did not work at all in the
month prior to the date the survey was taken,
the self-employed, business owners, and those
working for cooperatives, working for family
businesses, or working without compensation.
Also excluded are workers with more than one

job, because information is available on union status only for
the primary job in 1984 and 1989. Certain sectors (farming,
livestock, forestry, hunting, and fishing) and certain occupa­
tions (domestic servants, vendors with no fixed or stable es­
tablishment, and agricultural occupations) that are tradition­
ally “beyond the pale” of unionization in Mexico are also
excluded; workers in these sectors and occupations are typi­
cally considered part of M exico’s “informal” — that is, un­
regulated — labor force.3

Changing union density
For the “form al” sector labor force as a whole, union density
declined from just over 30 percent in 1984 to just under 20
percent in 2000. (See chart 1.) (If the “informal” sector work­
ers are included, the numbers are 26 percent and 17 percent
respectively.4) The biggest and steadiest decline was a 9-per­
centage-point decline from 1984 to 1994, with an approxi­
mate leveling-off thereafter. The trend is geographically simi­
lar if considering only those states that do not share a border
with the U nited States. The trajectory for the border states is
more variable, beginning at 26 percent in 1984, initially drop­
ping slightly and then spiking to 29 percent (above the na-

tional level of 25 percent) in 1992, and following a similar
pattern as (but declining faster than) the national trajectory
thereafter.5 For most of the period studied, union density
along the border was lower than in the interior, and thus rapid
job growth in this region of the country m ight be expected to
contribute to the aggregate decline in unionization.
Interestingly, unionization generally declined across all
sectors. (See chart 2.) By far the most dramatic is the sharp
and steady decline in union density in the transportation,
mail, shipping, and warehousing sector, a 38-percentagepoint drop over this period. The mining, electricity, water,
and gas transmission industry also experienced a rather sig­
nificant (14-percentage-point) decline in union density early
in the period, between 1984 and 1994, but witnessed a large
spike from 1996 to 1998 and a sharp drop again between
1998 and 2000, arriving at 47-percent union density by the
end of the decade. Union density declined 10 percentage
points in manufacturing, 8 percentage points in the service
sector, and 5 percentage points in the commercial sector.
The construction sector, after a substantial increase to 9-per­
cent union density by 1989, then dropped 7 percentage
points over the 1990s.
By the year 2000, the mining, electricity, water, and gas

Chart 1. Union density in Mexico as a whole, and by proximity to U.S. border, 1984-2000
Percent

Percent


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Monthly Labor Review

September 2004

11

Union Density in Mexico

transmission sector was still, by far, the most unionized sec­
tor, with 47-percent union density, and the commercial and
construction sectors continued to have, by far, the lowest
union density, at merely 3 percent and 2 percent, respectively.
Among the three sectors in the middle, transportation, mail,
shipping, and warehousing went from the top to the bottom
position, and services remained well above (by 10 percent­
age points) manufacturing, but both still with substantial
union densities of 29 percent and 19 percent, respectively.
Education workers (that is, teachers at all levels of instruc­
tion) are by far the m ost highly unionized occupation in
Mexico, with an initial union density o f 73 percent and an 8percentage-point decline in union density between 1984 and
2000. (See chart 3.) Technicians maintained a distant sec­
ond place despite a 21-percentage-point decline. Just be­
neath teachers and technicians is a large cluster of other oc­
cupations, all showing a general declining trend over the pe­
riod, ranging between 19 percent and 35 percent union den­
sity in 1984, and ending between 8 percent and 23 percent
union density in 2000. Again, the general trend among these
two occupations was a period o f steepest decline in the 1980s
and early to mid-1990s, with a tendency to level off or even
recover slightly thereafter, and then sometimes drop slightly

again from 1998 to 2000. An interesting exception is the
case of professionals, who saw a steady rise in union density
from 1984 to 1994, and a steady decline thereafter.
Sample sizes become small, and density estimates there­
fore become less reliable, in the analysis of more detailed
industry categories. However, to give a sense of the overall
tendency of the entire period, table 1 shows the union den­
sity for more detailed industry categories at the beginning
and end of the period. A similar, downward-trending trajec­
tory of union density is seen in almost every case, though not
without notable exceptions.
An in-depth, institutional analysis of each sector would
offer specific insights into the move towards lower unioniza­
tion rates. For example, M exico’s declining unionization in
the transportation, mail, shipping, and warehousing sector
may be partly accounted for by the deregulation of the indus­
try and the tremendous growth of private shipping services,
which typically lack active unions. These changes may not
only have increased the number of nonunion jobs in the sec­
tor, but also simultaneously, by displacement, caused a re­
duction in the absolute numbers or growth of jobs in the more
heavily unionized, public shipping sector. However, the ex­
istence of a secular decline across almost every industrial

Chart 2. Union density by major sector, 1984-2000
Percent

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Percent
80

70

60

50

40

30

20

10

September 2004

Chart 3. Union density in selected occupations, 1984-2000
Percent

Percent

80

75

80

-

p

70

65

-

60

-

55

-

•«

70

• I • • • • • •
Department managers, coordinators, and
supervisors in administrative and service
sectors, administrative workers

$ 9

m

65

60

Technicians
Education workers

55

Merchants, commercial employees, and
sales agents
Personal service providers in fixed
establishments
— Professionals

50

45

75

Direct workers (operators, manual
laborers, and artisans), industrial
• ■ •• •

Assistants and other non-credentialed
workers, artisanal, and industrial

50

-

40

35

30

25

20

15

-

10


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Monthly Labor Review

September 2004

13

Union Density in Mexico

U nion d e n s ity b y d e ta ile d in d u s try c a te a o r v .
1984-98
Ye<ar

Industry c a te g o ry
Mining and petroleum extraction.............
Food products, beverages, and tobacco ..
Textiles, apparel, and leather products.........
Wood and wood products.........
Paper, paper products, and printing..............
Chemical substances, petroleum and coal
derivatives, plastics, and rubber.............
Non-metallic mineral products (excluding
petroleum derivatives).................
Basic metal industry.......................
Metal products, machinery, and equipment
Other manufacturing industries.......

1984

1998

0.50
.35
.28
.12
.19

0.49
.18
.16
.12
.16

.43

.28

.21
.50
.27
.32

.14
.26
.25
.13

.65
.04
.11
.08
.09
.54
.33
.00
.15
.37

.57
.02
.08
.06
.09
.20
.20
.00
.06
.29

.65

.57

Electricity, water, and gas transmission...............
Construction .............................
Wholesale commerce.................
Retail commerce....................
Restaurants and h o te ls................
Transportation and communications...........
Insurance and financial services.....
Real estate leasing and administration........
Other services....................
Public administration, defense, and health....
Education, research, social service doctors, and
civil and religious associations..........

and occupational category suggests that there is an underly­
ing, systemic explanation for the general decline of union­
ization in M exico.6

Accounting for the decline
The decline in union density may be the result of two broad
forces. On the one hand, rates of unionization may change
due to changes in the industrial, occupational, or geographi­
cal composition of jobs in the economy, or to changes in the
education, age, and gender composition of workers in the
labor force (“compositional changes”). Alternatively, the
decline in union density may be the result of systemic institu­
tional changes, such as changing support for unions by gov­
ernm ent actors or a changing desire for, or resistance to,
unions by workers or employers (“institutional changes”).
The success o f the labor movement in Mexico has been
linked historically to its alignm ent with the Institutional
Revolutionary Party, which held power for most of the 20th
century.7 State and federal labor authorities can exert sub­
stantial influence over both the union registration process and
contractual relations between unions and employers. Begin­
ning with the shift in M exico’s development strategy in the
1980s, unions fell into disfavor among influential members
of the Institutional Revolutionary Party. As a consequence,
union organizing and maintenance of membership may well
have become more difficult in the 1980s and 1990s.
The authors have found no direct evidence for decreased
union support among M exican workers during this period.
14 Monthly Labor Review


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September 2004

If the ability of unions to win key contract demands had de­
creased, this might have led to diminished support for unions
among workers; however, in separate analyses, little evidence
was found of changing union relative wage effects over the
period, and only a moderate, but significant, reduction in the
ability of unions to standardize wages and level the wage
structure through collective bargaining.8
The growing prevalence of protection contracts and “ghost
unions” cited by labor scholars in Mexico suggests that, in
recent decades, employers may have become less willing to
deal with workers as an organized force, and more effective
at co-opting the formal structure of unions to avoid having to
deal with organized workers. Thus, there is at least some
evidence to suggest that unions are facing greater difficulty
in organizing new members and perhaps retaining existing
members in recent years.
To begin an exploration of the relative importance of “in­
stitutional changes” versus “compositional changes” in ac­
counting for the decline in union density over this period,
table 2 shows the changes in both union density and em ploy­
ment share by industry, occupation, demographic and human
capital characteristics, and geographical categories. In nearly
every category, union density declined, and typically by large
amounts — between 5 percentage points and 15 percentage
points or more; this suggests that a change in the overall in­
stitutional climate for organizing and retaining union m em ­
bers is likely to be responsible for declining union density.
Further evidence against the importance of compositional
effects is found in a second feature of the results. Holding
union density constant at 1984 levels, the direction of some
of the compositional changes is consistent with a decline in
union density, but the direction of others suggests a rise in
union density. For example, the share of employment in the
highly unionized mining, electricity, water, and gas industry
declined by 2 percentage points, thereby suggesting a de­
cline in overall union density; however, the moderate-uniondensity services sector saw its share of employment rise by 3
percentage points, tending to produce the opposite effect.
Similarly, the shift in employment in favor of border states
would account for some of the decline in union density, as
would, in general, the shift in employment away from the
capital zone, yet the shift in favor of urban areas points to an
increase in union density, as does the shift in favor of female
employment. Thus, while the examination of these descrip­
tive statistics makes clear the importance of the decline of
within-group union density in accounting for the overall de­
cline in union density, the case for “compositional changes”
is weaker, and ultimately inconclusive on the basis of these
descriptive tables.
In separate research, the changing union density over this
period is decomposed into “institutional” and “com posi­
tional” forces following the statistical technique found in

Table 2. I Change in union density and employment share by industry and occupation, demographic and human capital
Change, 1984-98'

1998

1984
Characteristics

Employment
share

Union
density

Employment
share

Union
density

Employment
share

Union
density

0.30

1.00

0.21

1.00

-0.09

0.00

.62
.29
.04
.08

.04
.26
.10
.14

.53
.20
.02
.07

.02
.26
.08
.16

-.08
-.09
-.02
-.02

-.02
.00
-.02
.02

.54
.37

.07
.39

.20
.28

.05
.42

-.33
-.09

-.02
.03

.47
.73
.73
.21
.35
.30
.19

.05
.05
.01
.03
.03
.27
.09

.37
.64
.13
.13
.19
.20
.09

.05
.06
.01
.03
.03
.23
.11

-.10
-.09
-.60
-.09
-.16
-.10
-.10

.00
.00
.00
.00
.00
-.04
.02

.32
.08
.27
.23
.27
.13

.19
.08
.09
.05
.02
.02

.25
.05
.19
.15
.16
.21

.17
.11
.09
.05
.04
.04

-.08
-.03
-.08
-.08
-.11
.08

-.02
.02
-.01
.00
.01
.01

.38
.27

.30
.70

.25
.18

.34
.66

-.12
-.09

.04
-.04

.22
.30
.42
.35
.41
.16
.00

.34
.33
.18
.10
.04
.01
.00

.10
.21
.31
.31
.25
.07
.15

.33
.32
.20
.10
.04
.01
.00

-.12
-.09
-.11
-.03
-.16
-.08
.15

-.02
-.01
.02
.00
.00
.00
.00

.21
.30
.31
.42
.40
.12

.23
.33
.24
.12
.07
.00

.11
.16
.21
.25
.32
.46

.13
.24
.34
.18
.10
.01

-.10
-.15
-.09
-.17
-.08
.34

-.11
-.09
.10
.06
.03
.01

States not bordering the U.S...................................................
States bordering the U.S.........................................................

.31
.26

.81
.19

.21
.21

.80
.20

-.11
-.05

-.01
.01

North-West2 .............................................................................
N orth........................................................................................
North-East...............................................................................
Center-North............................................................................
W est.........................................................................................
Center......................................................................................
Gulf-Center..............................................................................
Pacific-South............................................................................
Yucatan Peninsula..................................................................
Capital Z o n e ............................................................................

.19
.29
.30
.28
.27
.26
.39
.24
.26
.34

.09
.08
.09
.08
.10
.06
.05
.03
.03
.39

.19
.21
.28
.15
.22
.24
.23
.24
.23
.18

.09
.09
.09
.09
.11
.08
.07
.04
.03
.18

.00
-.09
-.02
-.13
-.05
-.01
-.16
.00
-.02
-.16

.01
.01
.00
.01
.02
.02
.02
.01
.01
-.21

Rural (population less than 2 5 0 0)..........................................
Urban (population greater than or equal to 2500).................

.25
.31

.14
.86

.12
.21

.07
.93

-.13
-.10

-.07
.07

In d u s try an d oc cu p atio n

Total..................................................................................
Industry (aggregate)
Mining, electricity, water, and gas transmission.................
Manufacturing.......................................................................
Construction.........................................................................
Commerce............................................................................
Transportation, communication, shipping,
and warehousing.............................................................
Services................................................................................
Occupation
Technicians...........................................................................
Education workers................................................................
Arts, performance, and sports workers...............................
Functionaries and directors.................................................
Supervisors..........................................................................
Direct workers and industrial...............................................
Assistants, artisanal, and industrial....................................
Department managers, supervisors in administrative/
service sectors, and administrative w orkers.................
Merchants, commercial employees, and sales agents......
Personal service providers in fixed establishments...........
Conductors and assistant conductors.................................
Workers in protection, security, and Armed Forces...........
Professionals........................................................................
D e m o g ra p h ic and hum an capital

Sex
Female..................................................................................
M ale......................................................................................
Age (in years)
1 6 -2 5 ....................................................................................
2 6 -3 5 ....................................................................................
36-45 ....................................................................................
46-55 ....................................................................................
5 6 -6 5 ....................................................................................
6 6 -7 5 ....................................................................................
75 and older..........................................................................
Highest level of education completed
N one.....................................................................................
Prim ary.................................................................................
Secondary............................................................................
Preparatory...........................................................................
College..................................................................................
Graduate...............................................................................
G e o g ra p h ic c la s s ific a tio n s

1 Figures for changes do not always equal the difference in reported levels due
to rounding.
2Regional definitions are those used in Fernando Herrera and Javier Melgoza,
“Evolución Reciente de la Afiliación Sindical y la Regulación Laboral en México,”
in Enrique de la Garza and Carlos Salas, eds., La Situación del Trabajo en México,
2003 (Mexico City, Plaza y Valdés, 2003) and are as follows: Ñorth-West: Baja
California Norte, Baja California Sur, Sinaloa, and Sonora; North: Chihuahua,
Coahuila, and Durango; North-East: Nuevo León andTamaulipas; Center-North:


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Aguascalientes, Guanajuato, Querétaro, San Luis Potosí, and Zacatecas; West:
Colima, Jalisco, Michoacán, and Nayarit; Gulf-Center: Veracruz and Tabasco;
Pacific-South: Chiapas, Guerrero, and Oaxaca; Yucatán Peninsula: Campeche,
Quintana Roo, and Yucatán; Capital Region: Federal District (D.F.) and Mexico State.
Due to an ambiguity in coding, it was not possible to classify 12 percent of
employees by region in 1998. Thus, the shares of employment by region do not
sum to 1 for that year. The shares follow a similar pattern when the unclassified
workers are removed from the sample.

Monthly Labor Review

September 2004

15

Union Density in Mexico

Henry S. F arber’s analysis of the decline in union density in
the United States.9 In particular, the 1984 data is used to
estimate a union status probit regression with the following
explanatory covariates: a set of 20 industry and 12 occupa­
tion categorical variables, age, age squared, a gender dummy,
a set o f categorical variables indicating level and type of edu­
cational attainment (including technical school), an indica­
tor for location in a rural or urban zone, and an indicator
variable for whether the person lives with 1 or more family
members who are in a union.
The estimated coefficients from this regression represent
the difficulty or ease that unions experienced in organizing
and retaining union workers in 1984, and thus reflect the in­
stitutional context within which unions operated during the
period. Substituting the individual characteristics, industry,
occupation, and geographical information on workers from
the 1998 data into the 1984 estimated probit regression, union
density in 1998 can be predicted under the counterfactual
assumption that the institutional context for union organiz­
ing remained the same in 1998 as it was in 1984. The differ­
ence between this “counterfactual” union density and the
actual 1984 union density is then interpreted as that part of
changing unionization from 1984 to 1998 accounted for by
com positional changes in the various job and labor force
characteristics.10 The difference between the actual 1998
union density and this counterfactual measure gives the part
of the change from 1984 to 1998 accounted for by institu­
tional changes.11
The results of this exercise are as follows:

Year
1984

1998

Actual union density........ ........ 0.303
Counterfactual union
density using 1984
coefficients..................

0.208
.280

Based on this analysis, of the 9.5-percent decline in union
density in Mexico, the change in industry, occupation, and
dem ographic com position explains only 2.3 percentage
points, while changes in the estimated coefficients of the
model explain 7.2 percentage points. In other words, slightly
less than one-fourth (24 percent) of the decline in union den­
sity is due to changes in job and labor force compositional
characteristics, while just over three-fourths (76 percent) of
it is due to structural and institutional changes in the ability
of unions to organize and retain members.
T rajectories of union density — in the aggregate and by
industry, occupation, and proximity to the border with the
United States — reveal that, in nearly every category, Mexico
has experienced a substantial decline in unionization since
1984. For the formal sector labor force as a whole, the de­
cline is from 30 percent to 20 percent — a fall of about onethird. Moreover, changing industry, occupation, and dem o­
graphic worker characteristics account for only about onefourth of this decline; the remaining three-fourths are ac­
counted for by structural and institutional changes in the abil­
ity of unions to organize and retain workers.
□

Notes
ACKNOWLEDGMENT:

We acknowledge the helpful comments of
Alejandro Covarrubias, Fernando Herrera and Armando Rendon, and the
able research assistance of Gurleen Popli. We thank David Card for sug­
gesting that we conduct this analysis, and the Institute for Labor and Em­
ployment at the University of California for financial support.

1INEGI. Encuesta nacional de ingresos y gastos de los hogares, 1989,
1984. (Aguascalientes, Mexico, Instituto Nacional de Estadísticas,
Geografía e Informática, 1992). ------. Encuesta nacional de ingresos y
gastos de los hogares, 1992, 1994, 1996. (Aguascalientes, Mexico,
Instituto Nacional de Estadísticas, Geografía e Informática, 1998). ------.
Encuesta nacional de ingresos y gastos de los hogares, 1998, 2000.
(Aguascalientes, Mexico, Instituto Nacional de Estadísticas, Geografía e
Informática, 2000).
2 Because of the change between 1998 and 2000 in the industrial clas­
sification system in Mexico (from the Clasificación Mexicana de
Actividades y Productos or c m a p to the Sistema de Clasificación Indus­
trial de América del Norte or s c i a n [ n a i c s in English]), it was not possible
to make the detailed industry categories for 2000 consistent with those of
previous years. Thus, for comparisons between 2000 and previous years,
we rely on more aggregate industry categories.
3 Certain of these exclusions are similar to those used by Fernando
Herrera and Javier Melgoza to construct a sample representing the
“unionizable population of the industrial sector” ( p s s i representing the

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September 2004

name in Spanish). See Fernando Herrera and Javier Melgoza, “Evolución
Reciente de la Afiliación Sindical y la Regulación Laboral en México,” in
Enrique de la Garza and Carlos Salas, eds., La Situación del Trabajo en
México, 2003 (Mexico City, Plaza y Valdés, 2003). However, they further
restrict their p s s i sample to the industrial sector, arguing that the service
sector has enjoyed high and relatively stable union density in Mexico.
(Our estimates below measure the degree of that relative stability.) They
also, usefully, analyze trends in both the economically active population
( p e a ) and the p s s i , raw numbers of unionized workers and union densities,
overall and by gender, age group, region, industry, and occupation, as well
as both raw numbers of unionized workers and union densities for both
the p e a and the p s s i .
4The informal sector is a large percentage of the labor force in Mexico
- some estimates put it at 40 percent or more - but many of these workers
are properly classified as self employed. Focusing, as we do here, on
wage and salary workers, inclusion of the informal sector does not change
the numbers by very much.
5 This spike in border-state union density is curious. However, the
1992 union density for the border states is indeed statistically significantly
greater than that for Mexico as a whole. Nor does it appear to be the result
of any sudden change in the level of employment in the border states, as
employment in the region has risen fairly steadily over the entire period.
6 Herrera and Melgoza, “Evolución Reciente,” analyze the trends in
unionization between 1995 and 2000 in terms of changes in regulation

governing the organization of work, introduction of new technologies, sub­
contracting and casualization of labor. A number of other articles in the
same volume provide useful, institutional analyses of the trends presented
here.
7 See Kevin J. Middlebrook, The Paradox o f Revolution: Labor, The
State, and Authoritarianism in Mexico (Baltimore, The Johns Hopkins
University Press, 1995).
8 See David Fairris and Edward Levine. Forthcoming. “La Disminución
del Poder Sindical en México,” El Trimestre Económico 71 (4), Number
284, Oct.-Dec. 2004 and David Fairris, “Unions and Wage Inequality in
Mexico,” Industrial and Labor Relations Review 56(3), 2003, pp. 481—
97.
9 See Fairris and Levine, forthcoming and Henry S. Farber, “The Re­
cent Decline of Unionization in the United States,” Science, 238(4829),
1987, pp. 915-20.
10 Following Farber, “Decline of Unionization,” we use the term “ac­
counted for” rather than “caused” in this description, because institutional


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and compositional forces are not necessarily independent of one another.
For example, shifts in relative employment across sectors may alter the
ease of organizing within the growing and shrinking sectors, respectively.
Thus, we say that one factor “accounted for” a given share of the decline
in union density only in the conditional sense that union density would
have declined by the corresponding amount given the observed change in
that factor but holding the other factor fixed.
11
Actually, following Farber, “Decline of Unionization,” we compare
three predicted union densities using: (1) the 1984 coefficients and the
1984 worker characteristics, (2) the 1984 coefficients and the 1998 worker
characteristics, and (3) the 1998 coefficients and 1998 worker character­
istics. Because the probit model uses a non-linear functional form, (1)
and (3) do not exactly correspond to the actual 1984 and 1998 union den­
sities. However, in practice they are extremely close, and it is therefore
harmless, and infinitely more intuitive to talk of the difference between
the actual 1984 and 1998 values and the counterfactual 1998 value, than
to talk of differences between predicted 1984 and 1998 values and the
counterfactual 1998 value.

Monthly Labor Review

September 2004

17

Diurnal Job Injuries

mm

The diurnal pattern
of o n -th e-jo b injuries
Data from two sources indicate that the injury hazard
is substantially higher late at night than during regular
daytime work hours; the best explanation for this finding
is that work at night is dangerous even adjusting
for broad industry-occupation composition and worker fatigue

,

Kenneth N. Fortson

Kenneth N, Fortson is a
Ph.D. candidate,
Department of
Economics, Princeton
University, Princeton, n j .
18

hortly after 4:00 a .m. on March 28, 1979,
mechanical equipment at the nuclear power
plant at Three Mile Island, near Harrisburg,
Pennsylvania, malfunctioned. In the course of
responding to the emergency, operators working
the late-night shift made errors that exacerbated
the situation, resulting in the worst accident in
the short history o f U.S. commercial nuclear
power.1 Seven years later and halfway around
the globe, at 1:23 a . m . on A pril 26, 1986,
negligence by night shift workers at the nuclear
reactor in Chernobyl, U.S.S.R., led to an even
more catastrophic nuclear disaster.2
In the popular press, it is often asserted,
without explanation, that workplace injuries are
more common at night.3In the academic literature,
econom ists have largely ignored the diurnal
pattern of on-the-job injuries and, by extension,
the economic ramifications. This article uses data
on w orkers’ compensation claims from Texas to
estimate the empirical distribution of injuries. The
results show that the injury rate is high during
off-hours late at night and low during the regular
nine-to-five shift.
The article also decom poses the factors
causing the observed injury pattern and explores
the possibility that the empirical injury cycle is
merely an artifact of compositional changes in
the age or industry and occupation of workers

S

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September 2004

throughout the day. Late-night workers have
longer shifts as well, so fatigue is examined as a
possible explanation of the injury pattern. Both
of these possibilities, however, are rejected as
the lone explanation of the injury pattern.
Instead, the article argues that there are
inherent physiological implications of late-night
work that make off-hours jobs more hazardous
than daytime jobs. This is an important distinc­
tion because it suggests that, in scheduling work
hours, firms should consider shift time in addition
to factors such as shift length, which is merely
correlated with late-night work and contributes
to a higher injury rate, but is not unique to night
work.

Texas Workers’ Compensation Commission.
The Texas W orkers’ Compensation Commission
provided data on age, time, date, and nature of
injury for workers injured between 1998 and 2002.
Texas was chosen because of the particularly ac­
curate and detailed records of workers’ com pen­
sation injuries maintained by the commission and
because Texas has an industrial composition sim­
ilar to that of the United States as a whole.4 The
5-year time span in the data provides a large
sample size, but is short enough that shifts in the
industrial mix should not be a factor. The sample
is a complete count of all workers who were em-

evening, or night— but did report their starting and ending
times. An adjusted median was used because shift times are
reported as the time of day (on a 24-hour clock) and simply
using the m edian w ould incorrectly estim ate the usual
schedule for each type of shift. For example, using the median
would consider midnight a very late time and 1:00 a .m. a very
early time. Conceptually, however, it is usually more reason­
able to consider 1:00 a .m. 1 hour later than midnight, rather
than 23 hours earlier.
To get around this issue, for each of the three shifts, the
24-hour day was bisected into two 12-hour segments, one
based on the shift starting time and one based on the shift
ending time. Median shift times were then calculated only for
those shifts with a starting time within the first segment and
an ending time within the second, and the 12-hour windows
were iteratively selected so as to maximize the number of
observations used in the calculation for each shift.6
Each of the 12-hour windows was rescaled such that when
the median was calculated, the beginning of the window was
treated as early and the end of the window as late. The median
of the rescaled windows were then used in the study. The
Current Population Survey. Data on work schedules come resulting imputed shift times for those who reported working
from the May 2001 Work Schedules Supplement to the Current a day shift were 8:00 a .m. to 5:00 p.m.; for those who reported
Population Survey (cps). In addition to affording data on such working an evening shift, they were 3:00 p.m. to 11:00 p.m.; and
common factors as age, education, industry, occupation, race, for those who reported working a night shift, they were 9:00
and gender, the 2001 supplement provides data on when each p.m. to 7:00 a .m. For the day and evening shifts, the shift times
w orker’s shift usually began and ended. For respondents who imputed with the use of the adjusted median are identical to
reported that they worked a regular work schedule, shift the modal shift times, and the modal shift times for night shifts
beginning and end times are used to determine whether a are very close to the adjusted median, providing additional
support for the imputations. Exactly 6,849 observations were
worker was at work during each hour of the day.
Workers responding to the supplement report their usual imputed in this manner; consequently, 44,260 of the original
shift in two ways: by citing the usual times they start and end 47,047 observations in the Work Schedules Supplement could
work and by giving categorical descriptions of the hours they be used.7
work. In the latter case, they indicate whether their shift is
best described as a regular daytime schedule, an evening shift, Diurnal injury distribution
a night shift, a rotating shift, a split shift, or an irregular
schedule. O f the 47,047 observations examined from the Work Table 1 reports the share of hours worked in each of the 24
Schedule Supplement, 9,636 lack data on either when the shift time intervals. The share is computed from the Work Sched­
ules Supplement for all workers aged 21 to 69 years and
usually began or when the shift usually ended (or both).
In order to m axim ize the sample size, the categorical separately for each of three age subgroups. All calculations
description o f the shift was used to impute the starting and are weighted with the supplem ent’s sample weights.
Two important features stand out. First, hours of work are
ending times whenever possible. Among those who reported
heavily
concentrated during the day: a full 80 percent of the
the starting and ending times of their shift, there was wide
share
of
hours worked fall between 8:00 a .m. and 5:00 p.m.
variation in actual schedules within the rotating shift category,
Second,
the distribution of hours throughout the day is
as well as within the split shift and irregular shift categories.
However, within the day, evening, and night shift categories, remarkably similar for all three age groups. Only slightly more
the typical starting and ending times were quite consistent. 21- to 39-year-olds work evening shifts than 40- to 49-yearThus, for these three types of schedule, when the individual olds and 50- to 69-year-olds, while the latter two groups work
refused to say or did not know when the shift usually started, marginally more during normal business hours.
The data from the Texas com m ission can be used to
or when the person reported that the starting time varied, his
compute
the share of injuries incurred during each hour-long
or her starting time was coded as the adjusted median starting
interval
for
two distinct categories of injuries: fractures and
tim e o f those who w orked the same type of shift— day,

ployed by a firm carrying w orkers’ compensation insurance
and who were injured during that period. Unlike nearly all
other States, Texas does not require firms to provide workers’
compensation insurance,5 and the sample does not include
those who work for firms that do not carry such insurance;
however, there does not appear to be any compelling reason
to believe that the diurnal injury pattern would be different
am ong firm s opting out o f the w o rk ers’ com pensation
insurance system.
In addition to furnishing data on the time of day the worker
was injured and the w orker’s age at the time of injury, the
commission provided information about the type and severity
of the injury, as well as the body part injured. More than
400,000 injuries are recorded in the commission’s database, of
which the analysis that follows examines the 42,902 severe
fractures or lacerations and the 29,074 severe falls. The primary
advantage of focusing on these injuries is that they are acute
and likely to be reported immediately, whereas back injuries,
for example, are caused by cumulative conditions; hence, the
time they are reported is somewhat arbitrary.


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Monthly Labor Review

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19

Diurnal Job Injuries

Table 1.

Share of hours worked in each hour of the day
A g e g ro u p , ye a rs
H our o f d a y
21 to 39

4 0 to 4 9

0.006
.007
.007
.007
.007
.009
.018
.041
.082
.092
.094
.095

0.007
.007
.007
.007
.007
.009
.017
.039
.079
.090
.092
.093

0.006
.007
.006
.006
.007
.009
.018
.044
.084
.093
.095
.095

0.005
.006
.006
.006
.006
.008
.018
.043
.085
.094
.096
.097

.094
.093
.092
.087
.071
.030
.017
.013
.011
.010
.009
.008

.092
.092
.091
.087
.073
.032
.019
.014
.013
.012
.011
.008

.095
.094
.093
.087
.070
.029
.016
.012
.010
.009
.008
.007

.096
.095
.094
.087
.070
.027
.016
.012
.010
.009
.008
.007

21 to 69

24:01 to 1 :0 0 .........................................
1:01 to 2 :0 0 ...........................................
2:01 to 3 :0 0 ...........................................
3:01 to 4 :0 0 ...........................................
4:01 to 5 :0 0 ...........................................
5:01 to 6 :0 0 ...........................................
6:01 to 7 :0 0 ...........................................
7:01 to 8 :0 0 ...........................................
8:01 to 9 :0 0 ...........................................
9:01 to 10:00 .........................................
10:01 to 11:00.......................................
11:01 to 12:00.......................................
12:01
13:01
14:01
15:01
16:01
17:01
18:01
19:01
20:01
21:01
22:01
23:01

to
to
to
to
to
to
to
to
to
to
to
to

13:00.......................................
14:00.......................................
15:00.......................................
16:00.......................................
17:00.......................................
18:00.......................................
19:00.......................................
20:00 .......................................
2 1 :00.......................................
22:00 .......................................
23:00 .......................................
24:00 .......................................

5 0 to 69

S ource : Author’s calculations from May 2001 Work Schedules Supplement of Current Population Survey. Total sample size is 44,260, including 20,125
aged 21 to 39 years, 12,761 aged 40 to 49 years, and 11,374 aged 50 to 69 years.

laceratio n s, and falls. T hese injury shares can then be
weighted by the share of hours in each interval rby taking the
ratio o f the share of injuries to the share of hours for each age
group a from the Work Schedules Supplement to obtain the
injury ratio:8

\

f

Injury ratioaI

v
Hours at

Injuries^
£ ln ju r ie s a(
V/
/

\

V

EHoursai
í

( 1)

y

The profiles of the three age groups in charts 1 and 2 reveal
little discernible difference in injury rates between older and
younger workers throughout the day, a point taken up in the
next section. There is wider dispersion between the age groups
in the late night and early morning hours, compared with the
normal business hours of 8:00 a . m . to 5:00 p . m ., but the
differences are not systematic, and given the much larger
number of observations used in the calculations for daytime
hours, it is not surprising that there is more “noise” in the wee
hours of the night.

Possible explanations
If there is a constant hazard of being injured, the ratio in
equation (1) should be constant at unity across the day; that
is, an increase in the share of injuries should be offset by a
commensurate increase in the share of hours worked in that
time interval. The results o f this calculation for severe lacera­
tions and fractures are shown in chart 1 and for falls in chart 2.
Both charts demonstrate that the injury rate is far from con­
stant. Indeed, the injury ratio is almost 3 times greater very
early in the m orning than it is at midafternoon. The two
categories o f severe injuries display similar patterns, both
peaking in the 1:01 A.M-to-2:00 a . m . hour and then steadily
declining until 8:00 a .m ., from which point the injury rate stays
low and flat until 5:00 p . m ., before gradually rising again
through the evening hours.

20

Monthly Labor Review


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September 2004

Compositional differences.
In a 1996 study, Daniel S.
H am erm esh found that age is negatively related to the
probability of working late at night.9Young workers also may be
more prone to injuries due to inexperience, which could drive the
results. However, there is little difference in the distribution of
hours across the day for the three age groups in the sample
presented here, as reported in table 1 and noted in the previous
section. Furthermore, as also mentioned in that section, the injury
ratio patterns reported in charts 1 and 2 are quite comparable for
each age group. This finding is notable because it indicates that
the overall injury pattern is not driven purely by compositional
changes in the age of the workforce; that is, the injury pattern is
not simply an artifact of a disproportionately young and inexpe­
rienced workforce working late at night.

Chart 1

Ratio of share of lacerations and fractures to share of hours, by hour worked, all workers
under 70 years
Ratio

Ratio

3.0
2.5

2.0
1.5

1.0
0.5

0.0
to

01:00

to
03:00

to
05:00

to
07:00

to
09:00

to

11:00

to
13:00

to
15:00

to
17:00

to
19:00

to

21:00

to
23:00

Hour worked
SOURCE: Author’s calculations from May 2001 Work Schedules Supplement to Current Population Survey and from
unpublished data from Texas Workers’ Compensation Commission.

Chart 2.

Ratio of share of falls to share of hours, by hour worked, all workers under 70 years

Ratio

Ratio

3.0
- 2.5

-

2.0
1.5

-

1.0

0.5

0.0
to

01:00

to
03:00

to
05:00

to
07:00

to
09:00

to

11:00

to
13:00

to
15:00

to
17:00

to
19:00

to

21:00

to
23:00

Hour worked
SOURCE: Author’s calculations from May 2001 Work Schedules Supplement to Current Population Survey and from
unpublished data from Texas Workers’ Compensation Commission.______________________________________


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Monthly Labor Review

September 2004

21

Diurnal Job Injuries

Still, there are other compositional differences that should
be of concern. For one, the distribution of injuries throughout
the day may be a corollary of the differential distribution of
industries and occupations throughout the day. If, for exam­
ple, more dangerous jobs are also more likely to have night
shifts, then the composition of jobs could alone explain the
dramatic increase in injuries in the hours shortly before and
after midnight. Table 2 reports the broad industry and occu­
pation of employment for those working between 1:01 a . m .
and 2:00 a . m . and also for those working between 1:01 p .m .
and 2:00 p .m . Note that, although the shares of blue-collar and
white-collar workers are comparable in the early morning (35.7
percent and 40.5 percent, respectively), there are fewer than
half as many blue-collar jobs as w hite-collar jobs in the
afternoon (25.9 percent and 64.2 percent, respectively).10
To examine this phenomenon more closely, additional data
on w orkers’ compensation were extracted from the cps March
2001 Annual Demographic Survey. For each broad industryoccupation combination, the percentage of people working
in that category who received w orkers’ compensation pay­
ments in the previous year was calculated. The percentage
was then used as a measure of the injury rate in the category.
Not surprisingly, there was a fair amount of dispersion across
industry-occupation cells: although less than one-half of 1
percent of white-collar workers in the commerce industry
(including trade, finance, and insurance) received income from
w orkers’ compensation insurance, nearly 2 percent of bluecollar manufacturing workers reported that they received
workers’ compensation payments. Table 2 further reveals that,
in addition to being more likely to be injured, blue-collar
manufacturing workers make up 19.7 percent of workers
between 1:01 a . m . and 2:00 a . m ., but only 7.0 percent of
workers between 1:01 p .m . and 2:00 p .m . The reverse is true of
white-collar commerce workers, who represent only 11.6

^

percent of the workers in the early morning, but 18.1 percent
by the afternoon.
To test the hypothesis that these broad industries and
occupations fully explain the distribution of injuries throughout
the day, a weighted average of injuries throughout the day was
created as follows: Let co. be the percentage of workers in each
cell i who received workers’ compensation, according to the
March cps Supplement. Let Su be the percentage of workers at
each hour t of the day who were employed in cell i, according to
the May 2001 Work Schedules Supplement. Then the following
formula computes the share of injuries that is explained purely
by differential industry and occupation injury rates:11

Explained share t

a m.

(2)

i

Chart 3 plots the explained injury share for each hour
against both the actual share of fractures and lacerations in
each hour and the actual share of falls in each hour. For
comparability, the injury shares are normalized to sum to 1
throughout the day. The horizontal line through the middle of
the chart, labeled “Constant injury rate,” represents the
hypothetical flat line that would be observed if the ratio of
injuries to hours worked were constant throughout the day.
The shape of the explained share curve is similar to the shapes
of the actual injury rate curves, dipping below the constant
injury rate during normal daytime hours and increasing above
it during hours late at night and very early in the morning.
Nonetheless, the magnitude of the difference between the
constant injury rate and the explained share is less than half
of the difference between the constant injury rate and the
actual shares. In other words, compositional differences in
industries and occupations throughout the day account for
less than half of the diurnal variation in injury rates.

Occupation and industry composition, 1:01 a .m . to 2:00
------------------------ ,------- — ________________________________
Type of o c c u p a tio n , 1:01

= ^ J C0i S t ,.

to 2:00

a .m .

and 1:01 p.m . to 2:00 p.m .

a m.

Ty pe of o c c u p a tio n , 1:01

p.m .

to 2:00

p.m .

Industry
W hite co lla r

Blue co lla r

Total occupation share...

0.405

0.357

Agriculture, mining,
construction.......................

.008

Manufacturing......................

S ervices

Industry share

W hite co llar

Blue co llar

Services

Industry sh are

0.238

1.000

0.642

0.259

0.099

1.000

.036

.000

.044

.026

.088

.001

.115

.030

.197

.003

.230

.068

.070

.002

.140

Infrastructure......................

.046

.047

.005

.098

.040

.029

.002

.070

Commerce.........................

.116

.050

.059

.225

.181

.035

.020

.236

Services................................

.206

.026

.170

.403

.327

.037

.075

.440

S ource : Author’s calculations from May 2001 Work Schedules Supplement of Current Population Survey.

22 Monthly Labor Review

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September 2004

Chart 3.

Actual share of injuries and share of injuries explained by industrial and occupational
composition, all workers under 70 years
Ratio1

Ratio1

0.08
0.07

0.07
Actual share of fractures and lacerations

Actual share of

0.06
0.05
0.04 'Constant injury rate
0.03

0.02
0.01
24:01
to
01:00

i__________ i_____

02:01
to
03:00

04:01
to
05:00

06:01
to
07:00

I

08:01
to
09:00

I

i_____

12:01
10:01
to
to
13:00
11:00
Hour worked

I

14:01
to
15:00

I

16:01
to
17:00

____ i
_____

I

18:01
to
19:00

20:01
to
21:00

22:01
to
23:00

1Ratio of share of injuries to share of hours.
SOURCE: Author’s calculations from May 2001 Work Schedules Supplement to Current Population Survey and from
unpublished data from Texas Workers’ Compensation Commission.
______________________________ _

Chart 4.

Average cumulative hours by hour worked, all workers under 70 years
Average
cumulative hours

Average
cumulative hours

24:01

02:01

01:00

to
03:00

04:01
to
05:00

06:01
to
07:00

08:01
to
09:00

10:01

12:01

to

to
13:00

11:00

14:01
to
15:00

16:01
to
17:00

18:01
to
19:00

20:01

22:01

to

to
23:00

21:00

Hour worked
SOURCE: Author’s calculations from May 2001 Work Schedules Supplement to Current Population Survey.


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Monthly Labor Review

September 2004

23

Diurnal Job Injuries

Fatigue.

One explanation for the observed diurnal injury
rate pattern could be fatigue. Most of the people working
between 10:01 a . m . and 11:00 a .m . have been at work for only
a couple of hours, while most of those at work between 3:01
a . m . and 4:00 a . m . have been at work for much longer. Further
evidence o f the possibility that fatigue is a factor comes from
the earlier adjusted median schedule calculations, which show
that, for night workers, the typical schedule is 10 hours long,
compared with 9 hours for day workers and 8 hours for eve­
ning workers. Such differences in the duration of work at
each time o f the day can have sizable effects on diurnal injury
rates if workers are sensitive to the amount of time they spend
on the job.
The relevance o f fatigue can be considered by first
calculating the cumulative hours worked as of each hour of
the day by each w o rk er and then tak in g the average
cum ulative hours in each hour o f the day of em ployees
w orking during that hour. C hart 4 displays the average
cumulative hours worked for each hour (among those who
are working). Although both the average duration of the shift
and the injury rate dip during the day and peak at night, the
shape and extrema of the shift duration plot are remarkably
dissimilar to the injury patterns in charts 1 and 2. The patterns
of fractures and lacerations and of falls have wide troughs
bottoming out between 4:01 p .m . and 5:00 p .m . (charts 1 and 2),
while the profile of average cumulative hours has a very
narrow, but deep, trough that reaches its minimum between
8:01 a .m . and 9:00 a .m . (chart 4). As cumulative hours on the
job rise dramatically from 8:00 a . m . to 5:00 p . m ., injury rates
remain low and actually decrease slightly. Given the dis­
similarities between the diurnal injury patterns and the diurnal
fatigue patterns, there is little evidence that fatigue is the
primary factor contributing to the late-night spike in the injury
rate.

Other physiological factors. Up until now, this article has
discussed circumstances that are correlated with working a
late shift, but that are not intrinsic to late shifts. For example,
working in dangerous industries or occupations and working
long hours are relatively more prevalent among workers who
work night shifts than day shifts, but neither of these factors
can, by itself, explain the high nighttime injury rate. However,
Ed C oburn and M artin M oore-Ede argue that there are
inherent characteristics of night activity that affect w orkers’
alertness.12 These characteristics may explain why the injury
pattern has such large variation throughout the day.

A well-developed body of research in the physiology and
neuroscience literature examines biological patterns known
as circadian rhythms. These rhythm s are biochem ically
regulated processes that generate a diurnal variation in the
body’s level of alertness. One recent article, for example,
experimentally assesses the influence of circadian rhythms
on such behavioral functions as short-term memory, reaction
time, and visual vigilance.13 In this study, the researchers
scheduled episodes of sleep in such m anner as to “de­
sy n ch ro n ize” circad ian rhythm s from the d u ratio n o f
w ak efu ln ess, thus in d ep en d en tly id en tify in g the tw o
processes. The authors find that functional impairment peaks
just after the nadir of the circadian cycle, which is observed in
the early m orning h o u rs. A lthough each su b ject w as
evaluated intensively throughout the course of 15 to 24
repetitions of a 20-hour cycle, one limitation of the study is
that it is based entirely on only six subjects. However, several
related studies conducted by many of the same researchers
have found similar effects of the circadian cycle on alertness.
A lthough by no m eans conclusive, these experim ental
studies, coupled with the empirical results presented in the
current article, provide strong evidence that workers are not
optimally alert during night shifts, contributing to hazardous
work conditions for them selves as well as their fellow
employees.

a r e b o t h s u p p ly - s id e a n d d e m a n d - s id e r e a s o n s that
workers might work at night. As Hamermesh notes in his 1996
book, working “unusual” times is a more usual event than we
might expect.14 He finds that women with young children
often choose to work late at night, arguably because o f a lack
of affordable childcare during the day. On the demand side,
firms can increase the productive capacity of plants by sus­
taining night shifts to supplement the day shifts.
However, there is a tradeoff for firms employing night shift
workers. As this article has demonstrated, injuries are much
more prevalent late at night than during normal business
hours. The evidence presented here suggests that this differ­
ence is not simply because of compositional changes in the
age or in the broad industries or occupations of late-night
workers. Nor is it attributable to late-night workers having
been at work longer. The failure of all of these factors to explain
the higher prevalence of injuries on the late-night work shift
leads to the conclusion that there are inherent features of
night work that make it more hazardous than day work. □

T here

Notes
c k n o w l e d g m e n t s : I thank Hank Farber, Jane Garrison, Alan Krueger,
and participants at the Princeton Labor Lunch for many useful
suggestions and discussions. Additional thanks go to Linda McKee of

A

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September 2004

the Texas Workers’ Compensation Commission, who provided much
of the data on which this study is based. I am also indebted to the
Industrial Relations Section at Princeton University and the Fellowship

of Woodrow Wilson Scholars for generous financial support. Naturally,
I absolve all of the aforementioned of responsibility for any remaining
errors of fact or interpretation.
1 President’s Commission on the Accident at Three Mile Island,
Report o f the President’s Commission on the Accident at Three Mile
Island (Washington, d c , U.S. Government Printing Office, 1979).
2 o e c d Nuclear Energy Agency, Chernobyl— Ten Years On (Paris,

Organization for Economic Cooperation and Development, 1995);
on the Internet at www.nea.fr.
3 See, for example, “No More Nine-to-Five,” The Economist, Jan.
10, 1998; and Valerie Marchant, “In the Deep of the Night,” Time,
Nov. 1, 1999.
4 See Current Employment Statistics (Bureau of Labor Statistics,
various years); on the Internet at www.bls.gov.
5 State Workers’ Compensation Laws (U.S. Department of Labor,
January 2004).
6 The particular windows chosen with the use of this procedure are
as follows:
Day shift. Begins between 1:00 a . m . and 1:00 p . m .; ends between
1:00 p . m . and 1:00 a . m .
Evening shift. Begins between 7:00 a . m . and 7:00 p . m .; ends
between 7:00 p .m . and 7:00 a . m .
Night shift. Begins between 12:00 p . m . and 12:00 a . m .; ends
between 12:00 a . m . and 12:00 p . m .
7 In a preliminary analysis, all results in this article were computed
without the imputed schedules and were found to be qualitatively similar
to the results obtained with imputation.
8 Note that this formula is equivalent to taking the number of
injuries per hour and multiplying by a constant that depends only on
the age group. Hence, the informational content of the injury ratio
calculation used in equation (1) is the same as that contained in the
calculation of an injury rate, which is the number of injuries divided by
the number of hours. However, because the numerator and denominator
in the analysis presented here come from two separate sources, the
ratio of injury shares to hour shares was calculated in order to avoid
confusion and to provide a statistic with a more transparent inter­


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pretation. Because of this relationship, the remainder of the article
uses the terms “injury ratio” and “injury rate” interchangeably.
9 Daniel S. Hamermesh, Workdays, Workhours, and Work Schedules
(Kalamazoo, m i , W.E. Upjohn Institute for Employment Research,
1996).
10 In this analysis, executive, professional, administrative, mana­
gerial, technician, and sales occupations are considered white-collar
occupations. Precision production, m achine-operating, m aterialmoving, transportation-handling and cleaning, farming, fishing, and
forestry occupations are deemed blue-collar occupations, and private
household services, protective services, and other services are adjudged
service occupations. Industries are divided into five categories: (1)
agriculture, mining, and construction, which also includes forestry and
fishing; (2) manufacturing, including durable and nondurable goods; (3)
infrastructure, comprising transportation, communications, utilities,
and sanitation services; (4) commerce, consisting of retail and whole­
sale trade, finance, insurance, and real estate; and (5) services, including
household, repair, personal, recreational, medical, social, educational,
and other professional services.
11 This formula is similar to calculations that Robert Shimer and, in a
separate work, Lawrence F. Katz and Alan B. Krueger, used to examine
how compositional differences in age and education in the U.S. workforce
could account for unemployment patterns over the past three decades.
(See Robert Shimer, “Why Is the U.S. Unemployment Rate So Much
Lower?” in Ben Bernanke and Julio Rotemberg (eds.), nber
Macroeconomics Annual 1998 (Cambridge, m a , m it Press, 1998); and
Lawrence F. Katz and Alan B. Krueger, “The High-Pressure U.S. Labor
Market of the 1990s,” Brookings Papers on Economic A ctivity
(Washington, d c , The Brookings Institution, 1999), pp. 1-87.
12 Ed Coburn and Martin Moore-Ede, “Keeping the Night Shift
A lert,” Journal o f Workers’ Compensation, vol. 10, no. 2, winter
2001, pp. 22-35.
13 James K. Wyatt, Angela Ritz-De Cecco, Charles A. Czeisler, and
Derk-Jan Dijk, “Circadian Temperature and Melatonin Rhythms,
Sleep, and Neurobehavioral Function in Humans Living on a 20-h
Day,” American Journal o f Physiology, vol. 277, October 1999, pp.
R 1152-R 1163.
14 Hamermesh, Workdays.

Monthly Labor Review

September 2004

25

A ccounting for w ages
an d benefits using the ECI

Using the data set behind the Employer Cost Index to impute
benefit values on the National Longitudinal Study of Youth
and the Current Population Survey this study finds
that workers at the bottom part of the wage distribution
exhibit a much stronger correlation between benefits
and wages than those at the top

,

Jonathan A.
Schwabish

Jonathan A,
Schwabish is senior
director of Research
and Policy at the
Partnership for New
York City. E-mail:
lschwabish@pfnyc.org,
The views expressed
here are those of the
author and do not
necessarily reflect the
views of the
Partnership for New
York City.

26

ccounting for employee benefits as a
form of real compensation for work has
received much theoretical and empirical
attention. The hedonic theory of compensating
wage differentials, first made popular by Sherwin
Rosen, contends that workers make tradeoffs
between wages and benefits.1 That is, in lieu of
lower wages, workers are compensated by taking
the g reater b en efits offered by em ployers.
Empirical approaches to estimating the tradeoff
however, have generally failed to correspond
with theory. A slew of econometric difficulties
are only the tip o f the iceberg— unobserved
worker and firm heterogeneity, m easurem ent
error, present discounted value issues (especially
for pensions), and group discounts (especially
for health insurance) complicate estimation. In
addition, data sets often lack the necessary
variables to construct and estim ate hedonic
models. There are few data sets that have enough
variables to create such models but even fewer
are n a tio n a lly re p re s e n ta tiv e , c o n ta in in g
employer and fringe benefit characteristics as
well as employee (demographic) information. The
hedonic model competes with what is commonly
known as the “good jobs, bad jobs” story.2 An
observable feature of the labor market, the “good

A

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jobs, bad jobs” story asserts that workers with high
wages also receive high benefits. However, perhaps
within a jo b there are com p en satin g w age
differentials, which would put the hedonic and
“good jo b s, bad jo b s ” m odels in concert.
Subsequently, workers at the bottom end of the
income distribution may be forced to switch jobs in
order to obtain a preferable benefit-wage mix and
those at the top of the distribution may be better
able to change the mix within their current job.
T h is study uses the B u reau o f L a b o r
S tatistics’ survey behind the Em ployer Cost
Index (ECI) to impute the value of fringe benefits
onto the National Longitudinal Survey of Youth
(nlsy) household survey between 1990 and 1998
and fo rm a lly te st the h e d o n ic th e o ry o f
c o m p e n sa tin g w age d iffe re n tia ls . A s an
additional check, this study performs the same
procedure for the same set of years using the
M arch C u rren t P o p u la tio n S u rv ey s (C PS).
Because of concerns relating to endogeneity and
measurement error— a common problem in this
body of research— conclusions are generally
confined to a discussion of the inequality of
benefits and the degree of correlation between
wages and benefits at different points in the
income distribution. Although certain models

point to com pensating differentials for particular groups,
these technical considerations generally lead to a discussion
of correlations as opposed to tradeoffs.
In general, coefficients on health insurance, life insurance,
and pensions are nontrivial and statistically significant. The
sign on the benefit coefficients varies, depending upon the
sam p le and e s tim a tio n m e th o d . P o o lin g th e n l s y
observations and estimating a fixed effects model addresses
the u n o b serv ab le h etero g en eity o f w orkers; how ever,
estimated coefficients are not markedly different than those
from the ordinary least squares model. The CPS permits this
study to have a cro ss-sectio n al approach and enables
broader appeal to the model. The main contribution of the
study is to utilize the bls data in a hedonic framework. The
very nature o f the data permits employee benefits to enter
not simply as dummy variables, as is usually done in the
literature, but to enter as continuous, dollar-valued variables.
The methodology continues to be troubled by endogeneity
concerns but, for the time being, the eci data sheds new light
on nonwage forms of compensation and the distribution of
such compensation.
The study begins by reviewing a selection of previous
work in the wage-benefit literature, with particular focus on
the distribution of employee benefits. It then discusses the
various models used in the empirical work, and is followed by
a discu ssio n o f the d ata itself. Sum m ary resu lts with
decompositions of benefits and wages, and the full model
results conclude the study.

Previous literature
The value of employee benefits is of increasing importance
to researchers and policymakers alike. According to William
W iatrowski, total benefits make up almost 30 percent of all
w orkers’ total compensation from the em ployers’ cost point
of view.3An August 2001 study from the Employee Benefits
Research Institute reports that employee benefits became an
even greater proportion of total compensation, rising from
26.8 percent to 28.9 percent between 1987 and 1994.4 Using
Chamber of Commerce data, Masanori Hashimoto shows that
between 1951 and 1994, employee costs for Social Security
rose by 414 percent; w orkers’ compensation costs increased
by 66 percent; retirement costs by 76 percent; and health
(and medical) insurance costs, 688 percent.5From the existing
literature, it is clear that benefits play an important part of
w orkers’ com pensation and thus the correlation between
wages and benefits will have important consequences for
public policy and distributional issues.
Several studies in the early 1980s attempted to estimate
the value o f benefits.6 A dditional work on hedonic price
theory7 generated mixed results from hedonic models; some
negative coefficients, but not often statistically significant.


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Charles Brown’s review article considers the research on the
tradeoffs workers make between wages and job disamenities,
such as poor working conditions, death rates, noise, heat,
and so forth.8 Brow n’s own empirical work (using the nls
Young M en’s sample for the years 1966-71 and 1973) finds
weak evidence for tradeoffs between wages and jobs that
have the following characteristics:
•
•
•
•

require employees to perform repetitive functions
involve stressful conditions
call for physical strength
contain bad working conditions

Brown postulates several reasons why the hedonic model
may not perform well in practice, including poorly measured job
characteristic variables, omitted variable bias, and that “[l]abor
markets are simply not as competitive as the theory of equalizing
differences assumes.” These issues continue to be challenging
issues for researchers and strides are being continually made
with improvements in methods and data sets.
G iven the difficulties in estim ating hedonic m odels,
research in this area has spilled over into other areas of the
labor market, such as mandated benefits and minimum wages.
For example, Jonathan Gruber and Alan Krueger examine
w orkers’ com pensation and m andated health insurance
programs.9 Arguing that looking at the tradeoff effects within
entire population bias results, Gruber and Krueger select certain
industries (trucking, carpentry, hospitals and plumbing) and
show that employers largely shift the costs of providing workers’
compensation insurance to the worker in the form of lower wages.
U sing variation in m andated m aternity benefits as an
instrumental variable, Jonathan Gruber identifies substantial
shifting in benefit costs to workers.10 Joseph G Altonji and
Christina H. Paxson investigate whether job quitters attempt to
achieve more desirable benefit-wage mixes by accepting different
jobs.11 They find that workers typically demand additional
compensation for jobs that offer “unattractive” hours (that is,
jobs that do not permit workers to change or increase their
hours). These papers are unique in the literature in that they are
generally successful in finding tradeoffs betw een these
mandated benefits and wages by using State variation in benefit
laws as exogenous instruments.
R ec e n t w ork has p aid p a rtic u la r a tte n tio n to the
distribution of benefits and in conjunction with the wage
d is tr ib u tio n .12 B ro o k s P ie rc e show s th a t w ag e and
compensation inequality increased over the 1982-96 period,
with those in the lower tail of the distribution experiencing
the greatest decline.13 Craig A. Olson uses an instrumental
variables approach to estimate the tradeoff between health
benefits and wages for wives who work full-tim e.14 He
contends that, “Husbands working in small firms or in non­
union jobs are less likely to have health insurance through
their jobs, and this increases the probability that their wives

Monthly Labor Review

September 2004

27

Wages and Benefits

have a jo b w ith h ealth in su ra n c e th ro u g h th e ir ow n
em p lo y e rs.” P rob lem s w ith the in stru m en tal variable
approach used in O lson’s study remain: assortative mating
theory and quality of benefits, conditional on firm size and
union status may bias the instrum ents.15
In all, research on the tradeoff between wage and non­
wage compensation has encompassed several different areas
o f the lab o r m arket. R esearch ers have used d ifferen t
estimation methods and different data sets to explore these
tradeoffs with varying degrees of success. Although earlier
studies generally failed to find such tradeoffs, later studies
have taken a different view of the model with more success.16
Focus on distribution of benefits has received new attention
in papers from Brooks Pierce and from William J. Carrington
and o th ers.17 A lthough the results in this article fail to
precisely identify the hedonic effect, the study brings these
different approaches together while taking advantage of a
rich but relatively unused data set.

D ata
This study uses three data sets to estimate the various models
in the next sections.

Employment Cost Index.

Em ployee benefit cost data,
along with wage and salary data, com e from the survey
used by the Bureau o f L abor S tatistics to generate the
quarterly price index for em ployer costs, know n as the ECI.
Q uarterly m icro data are available back to the early 1990s
and co n tain s h ourly d o llar b en efit costs fo r com m on
b e n e fits in clu d in g h ealth , d en tal, and life insurance,
defined benefit and defined contribution pension plan s,18
sick and vacation days, overtim e, bonuses, shift differen­
tials (“other p ay”), and legally required benefits such as
Social Security and w orkers’ com pensation. Em ployers are
asked the cost o f em ployee benefits by occupation within
the firm . Thus, a firm may be asked the cost of health
insurance and days off for, say, m anagers inside the firm.
The survey does not include Federal, private-household,
or self-em ployed w orkers.19
Due to attrition in the ECI and the addition o f new firms to
account for these losses, external employment data from the
b l s Web site were used to create consistent weights within
each data set and to aggregate the quarterly observations to
annual data sets.20 Using these (w eighted) observations,
benefit costs were calculated by averaging more than 72
industry-occupation cells for each year between 1990 and
1998.21 These averages were then merged onto the NLSY and
CPS data sets using the same industry-occupation structure.
In other words, if individual n works in industry-occupation
cell j, then the benefit level imputed to the individual’s record
equals the average (weighted) benefit level from industry-

28

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S e p te m b e r 2004

occupation cell j if the individual receives (or is offered) the
benefit, and zero otherwise. Ultimately, the average costs
calculated in the study are close to published numbers by
BLS.22

Several aspects of the ECI m ade the calculations of
average benefit costs especially troublesome. In particular,
the survey asks for full-time, part-time status not as a function
of actual hours worked, but according to the practice of the
employer (that is, benefit schedules). Thus, there are many
observations for which the observation is categorized as a
full-time worker but worked only 20 hours in the reporting
period. It is therefore difficult to distinguish between actual
full-time and part-time workers within the ECI to calculate
benefits. This m ay be im portant because, as has been
dem onstrated in previous work, part-tim e workers often
receive fewer (if any) benefits, com pared with full-time
w o rk ers.23 F u ll-tim e dum m y v ariab les— based on the
individual data— are included in some specifications to
control for the full-tim e issue. Furtherm ore, the benefit
averages from the ECI include some observations equal to
zero, which could potentially downward bias the benefit-cell
averages. However, the inclusion of these zeros may help
identify the interfirm trade-off of the benefits at the job level.
Additionally, the external weighting scheme may further help
to mitigate this potential bias.

N ational Longitudinal Survey o f Youth.

The NLSY,
beginning in 1979, surveyed individuals between 18 and 25
years old. Initially, more than 12,500 individuals responded
to the survey. This study uses 7 of the recent years of data;
1990-1994,1996, and 1998 (surveys were not conducted in
1995 or 1997). The discussion in the following sections is
re stric te d to the re su lts in 1998, alth o u g h issu es o f
unobserved worker heterogeneity are addressed by using
the panel nature of the n l s y by pooling all 7 years. The
demographic variables in the models are detailed in the next
section; most importantly, from NLSY data one can find
whether certain benefits are made available to workers. Benefit
indicators are available for most years and include health,
life, and dental insurance; sick, vacation and maternity leave;
retirement programs; discounts, profit sharing, and flexible
hours; and other indicators such as parking, training/education
and child care are also available. This study focuses on health
and life insurance, sick and vacation leave, and retirement
because these are also included in the ECI data.24

Current Population Survey. The March CPS is a familiar
data set to labor economists— it surveys approximately 50,000
households every year. The CPS asks several questions
about health insurance and pension coverage, but other
benefits (except some required benefits) are not covered in
the survey. Thus the analysis using the CPS focuses on these

two variables with the same set of demographic variables as
in the NLSY (less actual work experience). The CPS is a large,
cross-sectional data set and thus permits a more thorough
analysis of the correlation between wages and benefits. The
NLSY, however, is restricted both by the number of observa­
tions (although the average number o f observations does
range between 4,000 and 5,000 for the aggregate groups) and
restricted age range of only 9 years.

Measurement concerns.

Matching employer to employee
data is becoming increasingly common and has the potential
to yield large returns to research.25 Linking these data sets
however, introduces new econometric concerns as well. In
the perfect world o f matching employer information directly
to data for their employees, measurement error and issues
related to fixed effects (on several different levels) estimation
are magnified in the matched data set case.26As Robert Elliott
and Robert Sandy argue, workers who are dissatisfied with
their pay may overstate workplace disamenities, and workers
w ho are sa tisfie d w ith th e ir pay m ay u n d e rsta te the
disam enities.27 Such systematic responses to benefit surveys
are shown to unambiguously bias hedonic model estimates
downward. Panel data sets with matched employer-employee
data would help solve some of these problems.
In the m id-1980s, a substantial literature on measurement
error in this area was born. Papers by Greg J. Duncan and
Daniel H. Hill, and Wesley M ellow and Hal Sider compared
se p a ra te su rv e y re s p o n s e s b e tw e e n e m p lo y e e s and
e m p lo y e rs .28 In th e la tte r, the a u th o rs fo u n d th a t
discrepancies for major industry and occupation responses
were minor. Worker responses to number of hours worked
tended to exceed em ployers’ responses by about 4 percent,
while their reports of wages were lower by almost 5 percent.
Duncan and Hill find similar results and use the Panel Study of
Income Dynamics Validation Study to show that answers to
questions about benefits were relatively accurate. Error rates
(percentage of workers whose responses did not match their
employers) on fringe benefits were small: 1 percent on medical
insurance and paid vacation days; 5 percent on dental benefits;
10 percent on life insurance; and 3 percent on pension coverage.
Thus, this measurement error literature provides some evidence
that the imputation procedure used in this study provides results
that are not inconsistent with expected results.29
Given that the econometric issues related to matched data
sets are not yet resolved, the imputation used in this study
raises additional concerns regarding estimation. The e c i ,
n l s y , and CPS data sets do not make up a direct match data
set but instead simply allow the imputation of benefit costs
to in d iv id u a l d e m o g ra p h ic c h a ra c te ris tic s . G en e ra l
m easurem ent issues are thus not the only concern; deter­
m ining the proper m atching procedure and testing for
significance of the estimated coefficients is also important.


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First, the matching procedure may not be appropriate if one
believes industry and occupation groupings do not adequately
reflect employer costs. From the employer, one would expect
benefits to be contingent upon other firms in that industry (and
occupation) just as one would expect wages or any other form
of compensation to be. The confidentiality restrictions placed
on the ECI data also restricts further decomposition, such as by
region, State, or even more specific industry/occupation groups.
Second, the model is estimated from within the household
surveys and one might be concerned about what degrees of
freedom to use in the hypothesis tests. The n l s y and CPS
have about 5,000 and 55,000 observations in the 1998 sample,
and the e c i has approximately 82,000 observations for the
same year. Hence, in the subsequent sections, the household
data sets are used as the yardstick for significance testing.
The sm aller num ber of observations is som ew hat more
re s tric tiv e a lth o u g h w ith th e se la rg e n u m b ers o f
observations, it should make little difference.
There are two other considerations that are important to
the discussion of m easurem ent error and are m entioned
briefly. The first is the difference between employer cost and
employee valuation. The cost of a benefit reported by the
employer may differ from the value placed on the benefit by
the worker. For example, if one individual in a married couple
is capable of working, health insurance may have a greater
value to the individuals than, say, an unmarried worker with
no children. That said, while it is extremely difficult to measure
the value an individual places on a benefit, the e c i data
provides an easily quantifiable measure of benefits, namely
the cost of the benefits to employers.30 Second, the n l s y
asks w hether the respondent was offered a benefit, not
w h eth er the w o rk er actu a lly a c c e p te d the b e n e fit.31
Individuals who receive benefits were clearly offered benefits,
but also realize that individuals who declined offered benefits
still have a compensating differential. These differences are
conceptually interesting and data on offered benefits are
perhaps preferable to received benefits because receipt of
benefits might miss the potential tradeoffs employees could
make between benefits and wages. In that case, one would
not be able to observe workers who refused such benefits
and benefit packages.

Model
Three models are estimated to test the relationship between
benefits and wages. After the imputation of average benefit
values by industry-occupation cell, ordinary least squares,
fixed effects, and quantile regression models are estimated.
First, the ordinary least squares model asks what the average
wage would be for the worker who has high (or low) benefits
in any given industry-occupation com bination. Because
causality is difficult to identify, the ordinary least squares

Monthly Labor Review

September 2004

29

Wages and Benefits

regression results are interpreted in terms of a wage-benefits
correlation arising from across-industry/occupation group
averages. This is carried out using both the n l s y and CPS—
the dependent variable being the logarithm of the (individual)
hourly wage with both wage and benefit data inflated to 1996
CPI-U a d ju ste d d o lla rs .32 A verage b e n e fit v alu es are
interacted with the individual-level dummy variables that
indicate w hether a benefit is offered; thus, the prim ary
variables of interest will be equal to zero if the respondent
received no benefit and a (continuous) dollar value if the
respondent received the benefit. D em ographic controls
include age; the num ber o f children under age 6; actual
experience and its square33; and dummy variables for marital
status, urban status, race (black and Hispanic), firm size by
number of employees (0-24, 25-99, and 100 or more), full­
time status (35 hours or more worked per week), union status,
and education level (high school graduate, some college,
college graduate). Industry-occupation dummies are included
in a second set of regressions; all regressions are weighted
with the individual-level sample weights.34
The second model exploits the panel nature of the n l s y
by pooling the 1990-98 samples and estimating a fixed effects
model for the same groups as in the ordinary least squares,
using the same covariates as previously specified. The fixed
effects regressions identify the partial correlation between
wages and benefits by allowing one to look at changes in
benefits and wages for a given worker. The fixed effects
ap p ro ach a d d resses the u n o b serv ed h e te ro g en eity of
workers in the sample. Concerns remain, however, of firmlevel unobserved characteristics but controlling for these
factors is much more difficult.
Finally, a series of quantile regressions are estimated for
the 10th and 90th percentiles. Quantile regression analysis is
becom ing increasingly popular with the m ain advantage
being that, like the Least Absolute Deviation ( l a d ) estimator,
estimated coefficients are not overly sensitive to outlier data
points. Quantile regressions are very different from ordinary
least squares regression and is best explained by analogy:
regular ordinary least squares summarizes how the mean
value of the dependent variable varies with some X regressor,
whereas quantile regressions summarize how some quantiles
(that is, median or 10th percentile) of the dependent variable
vary with some X regressor. The extreme quantile regressions
and the ordinary least squares results would differ if wage
dispersion were very different in high-benefit cells than in
low-benefit cells.35
Several studies have recognized that benefit variables,
when measured as dummy variables indicating the existence
of the benefit, are endogenous when included in an ordinary
least squares framework. (See “Previous literature” section.)
Olson notes that in an ordinary least squares model, the
dummy variable for health insurance “is biased, and the

30

Monthly Labor Review


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September 2004

positive sign suggests that unobserved factors affecting
wages that are correlated with [the variable] more than offset
the trade-off between wages and health insurance predicted
by the theory.”36 This potential endogeneity is not eliminated
by using the ECl data, although the variable of interest is no
longer a latent variable and is instead a continuous dollar
value. In addition, the fixed effects model from the n l s y
addresses some of these concerns. In light of these issues,
arguing causality based on these results may be difficult;
however, the negative coefficients in some regressions at
least suggest a compensating differential. Combining the e c i
data with the n l s y and CPS allows for a unique look at the
correlations between wages and benefits that may help our
understanding of the issues relating to w orkers’ com pensa­
tion. The main contribution is to take advantage of the
underutilized ECI data set to explore these correlations and
tradeoffs and to generate dollar-valued benefit variables
rather than simple indicator variables. As will be seen later in
the article, however, the models ultim ately produce few
negative coefficients on the benefit variables.

Subgroups.

Each of the models is estimated for different
subgroups of the population. The first subgroup of interest
consists of individuals at the extreme ends of the income
distribution— the 10th and 90th percentiles— based on the
individual level hourly wage rates. As shown by Pierce, workers
at the lower end of the distribution take a larger percentage of
their total compensation in terms of wages than those at the
higher ends of the distribution.37 (See sections, “Summary
results” and “Model results.”) Hence, one might also expect
workers at different points in the distribution to correlate wages
and benefits differently. And, as will be seen in the following
sections, the payoff from such exploration will be significant.
Selection into these different com ponents of the wage
distribution however, may be an issue of concern. To address
this, a series of quantile regressions (discussed earlier) are
estimated with some success. A separate look at these groups
m ay also have im p o rtan t conseq u en ces for policy
considerations of distribution and inequality.
Estimates were also generated for several other sub-groups,
but due to space constraints and the fact that the results did not
shed further light on the topic, those figures are not reported
here.38 The additional subgroups include, men and women;
workers earning at least 25 cents above the minimum wage;
workers earning at least 50 cents above minimum wage39; and
four “at-risk” groups including single mothers, low education
youths, single fathers, and working-age black women.

Summary results
As reported by Craig Copeland, the number of employers
sponsoring pension plans grew by more than 5 percentage

points between 1992 and 2000, and the number of employees
participating in a plan grew from 47 percent to 52 percent
over the same period.40 Health insurance continues to be a
highly valued form o f compensation to workers in the United
States. In 2001, 60 percent o f those polled in an Employee
B e n e fits R e se a rc h In s titu te /M a tth e w G re e n w a ld &
Associates poll said health insurance was the most important
benefit, followed by 23 percent saying retirement plans were
the most important.41
Summary statistics of interest for the NLSY and the CPS
1998 samples used here (following imputation) are detailed in
table 1, along with breakdowns by subgroups of interest,
namely the 10th, 50th, and 90th wage percentiles. Summary
statistics for other years are not dramatically different and,
along with full regression results, can be obtained from the
author. The summary statistics in table 1 illustrate some of
the differences between the two data sets. CPS respondents
earn about 50 cents less per hour and are a couple of years
older than their n l s y counterparts.42 Individuals in the NLSY
are also much more likely to live in an urban area and belong
to a union, although somewhat less likely to work full-time

Table 1.

(defined as 35 hours or more per week). In terms of benefit
variables, the n l s y contains a much richer set of variables
although most are not included in the regression analysis.
The benefit indicator variables show that n l s y respondents
are somewhat more likely to be offered health insurance or
pension plans, with other benefit variables included simply
for reader interest.43
Table 2 breaks down the mean dollar values of the various
benefit variables (following imputation) into the 10th, 50th, and
9 0 th p e rc e n tile s along w ith p e rc e n ta g e s o f the to tal
compensation. The patterns are as expected— people at the
upper part of the distribution typically earn more in benefits,
sometimes more than double workers at the 10th percentile.
Health insurance and Social Security account for the biggest
parts of the total benefit package, w hereas some of the
unem ploym ent-type insurance benefits, such as supple­
mental and long-term disability, account for the smallest parts
of total benefit compensation.
The variation in the distribution of benefits is interesting
in its own right. For example, take the primary variables of
interest (in table 2)— health and life insurance, and pension

Summary statistics of the Current Population Survey and the National Longitudinal Survey of Youth, 1998
1998 CPS

1998 NLSY

V ariab le

Hourly wage (dollars)....................................
Log(hourly wage) ..........................................
Age.................................................................
Black(0,1) .....................................................
Hispanic(0,1).................................................
High school graduate(0,1) ............................
Somecollege(0,1).........................................
College graduate(0,1)...................................
Married(0,1)...................................................
Previously married(0,1)................................
Number of children........................................
Urban(0,1).....................................................
Union(0,1) .....................................................
Full-time1.........................................................
Actual experienced.........................................
Benefit variables
Health insurance(0,1).................................
Pension(0,1)................................................
Life insurance(0,1)......................................
Dental insurance(0,1) .................................
Maternity coverage(0,1) .............................
Flex-time(0,1)..............................................
Profit sharing(0,1).......................................
Child care(0,1)............................................
Number of sick days...................................
Number of vacation d a y s...........................
Total number of days3..................................

N u m b e r of
observations

M ean

S tandard
de viation

55,439
55,439
55,439
55,439
55,439
55,439
55,439
55,439
55,439
55,439
55,439
55,439
11,497
55,439

15.509
2.470
38.945
.118
.098
.324
.289
.280
.589
.153
.237
.246
.148
.853

6.517
.753
11.521
.323
.298
.468
.453
.449
.492
.360
.555
.431
.355
.354

4,735
4,735
4,735
4,735
4,735
4,735
4,735
4,735
4,735
4,735
4,735
4,735
4,584
4,735
4,735

16.068
2.567
36.983
.135
.057
.436
.227
.268
.661
.180
.224
.645
.164
.750
705.106

6.453
.610
2.309
.342
.232
.496
.419
.443
.473
.384
.478
.479
.370
.433
207.625

55,439
55,439

0.606
.631

0.489
.483

4,735
4,735
4,735
4,716
4,479
4,731
4,694
4,651
4,479
4,602
4,735

0.812
.708
.704
.678
.690
.544
.292
.073
23.620
13.748
47.032

0.391
.455
.457
.467
.463
.498
.455
.259
63.124
29.888
78.793

' Full-time defined as greater than or equal to 35 hours worked per
3k-

N u m b e r of
observations

M ean

S tan dard
d e viatio n

3 Includes sick and vacation days off. See text, endnote 24.
N ote : Statistics are weighted using the cps or nlsy individual weights.

2Total number of weeks worked. See text, endnote 32.


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Monthly Labor Review

September 2004

31

Wages and Benefits

Table 2.

Average benefit values, total and 10th, 50th, 90th percentiles, Current Population Survey and National
Longitudinal Survey of Youth, 1998

P ane l A — CPS s a m p le

V ariab le

S um ..............................
Vacations...........................
Holidays.............................
Sick leave..........................
Other paid leave...............
Shift differential................
Nonproduction bonus........
Severance p a y ..................
Supplemental
unemployment.................
Life insurance....................
Health insurance...............
Sickness and accident
insurance.......................
Defined be n efit..................
Defined contribution..........
Social Security..................
Medicare............................
Federal unemployment
insurance........................
State unemployment
insurance........................
Workers’ compensation.....
Long-term disability..........

Total

M e an

10th p e rc e n tile

P ercen t'

Value

P ercen t'

Value

P ercen t'

Value

P ercen t'

6.088
.751
.518
.215
.073
.067
.289
.027

100.00
12.34
8.50
3.53
1.21
1.11
4.75
.45

2.197
.257
.189
.037
.016
.001
.045
.001

100.00
11.69
8.59
1.70
.73
.05
2.03
.04

5.340
.625
.460
.175
.052
.035
.213
.019

100.00
11.71
8.62
3.28
.98
.65
3.99
.35

11.085
1.518
.985
.395
.154
.207
.579
.071

100.00
13.70
8.89
3.56
1.39
1.87
5.22
.64

.009
.054
1.225

.15
.88
20.12

.000
.013
.520

.00
.58
23.68

.000
.047
1.377

.00
.87
25.79

.014
.106
1.916

.13
.96
17.28

.037
.500
.340
1.006
.254

.61
8.21
5.59
16.53
4.18

.013
.089
.086
.533
.126

.59
4.07
3.93
24.25
5.74

.028
.405
.258
.883
.209

.52
7.58
4.82
16.54
3.92

.080
.926
.726
1.530
.410

.72
8.35
6.55
13.80
3.70

.027

.44

.023

1.04

.027

.51

.035

.31

.095
.350
.029

1.57
5.75
.48

.079
.127
.005

3.57
5.79
.21

.086
.267
.024

1.61
5.00
.44

.123
.642
.050

1.11
5.79
.45

Total

P ane l B — NLSY s a m p le

10th p e rc e n tile

V a ria b le

M ean

P ercen t'

S um ............................
Vacations.........................
Holidays...........................
Sick leave........................
Other paid leave.............
Shift differential..............
Nonproduction bonus......
Severance p a y ................
Supplemental
unemployment...............
Life insurance.................
Health insurance.............
Sickness and accident
insurance......................
Defined be n efit...............
Defined contribution........
Social Security...............
Medicare..........................
Federal unemployment
insurance.....................
State unemployment
insurance......................
Workers’ compensation....
Long-term disability........

6.234
.764
.527
.215
.074
.066
.297
.028

100.00
12.26
8.45
3.45
1.18
1.06
4.77
.45

2.226
.257
.189
.053
.018
.001
.040
.001

100.00
11.54
8.47
2.36
0.79
0.04
1.81
.04

.009
.057
1.250

.15
.92
20.06

.000
.013
.525

.037
.513
.349
1.024
.259

.59
8.22
5.60
16.42
4.15

.026
.098
.379
.030

Value

Value

5.317
.625
.460
.154
.050
.036
.205
.019

100.00
11.76
8.65
2.90
.93
.67
3.86
.35

11.109
1.518
.985
.395
.151
.207
.579
.071

100.00
13.67
8.87
3.55
1.36
1.86
5.21
.64

.00
.57
23.57

.000
.047
1.377

.00
.88
25.90

.022
.106
1.916

.20
.96
17.24

.013
.089
.086
.533
.126

.59
4.02
3.88
23.93
5.66

.025
.410
.240
.883
.209

.48
7.71
4.52
16.61
3.94

.080
.926
.726
1.530
.410

.72
8.33
6.54
13.77
3.69

.42

.023

1.02

.027

.50

.035

.31

1.58
6.08
.47

.079
.127
.005

3.53
5.71
0.22

.087
.267
.024

1.64
5.02
.45

.124
.660
.050

1.12
5.94
.45

2Called “pensions and retirements” by bls prior to June 1995.
3 Called “savings and thrift” by

32

Monthly Labor Review

bls

prior to June 1995.

September 2004

P ercen t'

90th p e rc e n tile

50th p e rc e n tile

P ercen t'

1Percent of total benefits.


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90 th p e rc e n tile

50th p e rc e n tile

Value

P ercen t'

N ote : Statistics are weighted using the cps or nlsy individual weights.
Life insurance, health insurance, defined benefit and defined contribution
are primary variables of interest.

benefits (broken dow n into defined benefit and defined
contribution plans). Health insurance clearly makes up the
largest portion of total benefit compensation and is more
important to those at the 10th and 50th percentiles than those
at the upper tail of the distribution. Life insurance makes up
less than 1 percent of benefit compensation, but is increasing
through the distribution from roughly 0.5 percent for the 10th
percentile to 1.01 percent for the 90th percentile. Pension
benefits follow a similar pattern— those at the high end of the
distribution take nearly 10 times as much in pension benefits
(around 90 cents per hour) than do those at the 10th percentile
(around 9 cents per hour).
To further explore the differences in compensation across
the distribution, chart 1 pictures the breakdowns in total
com pensation (for 1998) across the 10th, 50th, and 90th
percentiles using the n ls y data set. As is clear from the chart,
individuals whose earnings place them in the lower 10th
percentile o f the wage distribution take a higher percentage
of their total compensation in the form of insurance (8 percent,
including health, life, and other insurance) and leave (8
percent). Those in the upper part of the distribution however,
take m ore in w ages (72 percent versus 65 percent, not
pictured) and less in required benefits (including Social

Security), insurance, and leave. The differences between the
percentiles are m uch less for total pay (including shift
differential, nonproduction bonus, severance pay, and
supplemental unemployment) and total pensions (including
defined benefit and defined contribution). For the former,
workers at the bottom part of the distribution take 3.5 percent
of total compensation in the form of total pay, compared with
those in the 90th percentile who take 3.3 percent. The
differences are similar for pensions; 3.7 percent versus 3.5
percent. Visually, the differences in total compensation across
the wage distribution are striking and, as will be shown in the
fo llo w in g sectio n s, estim atin g the co rre la tio n s in an
econometric model also produces different estimates across
the distribution.

Model results
The most simple of the models used in this study is a standard
ordinary least squares and is presented first. A fixed-effects
model is estimated using the 7-year sample of the NLSY from
1990 to 1998. Finally, quantile regressions were estimated on
both the CPS and n ls y to gain a better sense of what is
happening within the 10th and 90th percentiles. Each model is

Chart 1. Benefits as a percentage of total compensation, National Longitudinal Survey of Youth, 1998
Percent of total
compensation

Percent of total
compensation

N ote : Hourly wage not illustrated.


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33

Wages and Benefits

discussed in turn with some coefficient estimates converted
to elasticities in order to better understand the magnitude of
the regression results.

Ordinary least squares. Six ordinary least squares models
are estimated for each year using the CPS and 12 ordinary
least squares regressions are estimated using the NLSY—
absence o f the num ber o f days o ff variable in the CPS
accounts for the discrepancy. The base m odel, as noted
earlier, includes 12 covariates plus the variables of interest
nam ely, h ealth and life in su ran ce co v erag e, pen sio n
coverage, and num ber o f days off (sick plus vacation).
Additional controls include union status, full-time status, and
firm size dummy variables. Each benefit variable is included
separately and then together— industry and occupation
dummies are included in an analogous set of regressions.
The hedonic theory implies that there should be a negative
co efficient on the variables o f interest although in the
sections that follow, positive (and statistically significant)
coefficients will be the norm. These results demonstrate the
degree of correlation between wages and benefits and how
that correlation differs w ithin the distribution although
negative coefficients, at the minimum, suggest a compen­
sating differential.
Tables 3 and 4 present the coefficients on the benefit
variables from the 1998 ordinary least squares model results
for the base models for all respondents and those below the
10th percentile and above the 90th percentile— the regressions
are repeated with industry and occupation dummies and are
found in the neighboring column. Panel A of tables 3 and 4
contains estimates from the whole sample and the estimated
coefficients are, given the previous com pensating wage
differential literature, not surprising. In the regressions that
do not include industry and occupation dummy variables,
the coefficients are uniformly positive and are statistically
sig n ifican t. For health insu ran ce, the co efficien ts are
consistent betw een specifications and data sets, ranging
between 0.11 and 0.22; life insurance (for the n l sy ) is a bit
higher with coefficients ranging between 0.24 and 0.50.
Estimates for pensions differ slightly between the two data
sets with nlsy point estimates ranging between 0.07 and
0.12 and coefficients from the CPS barely higher, between 0.09
and 0.14. All enter statistically significantly and the model fit
(measured by the R2) is fairly strong, ranging between 0.33
and 0.44. In the columns that include industry and occupation
dummies, coefficients are uniformly smaller but o f the same
sign and significance.44
As expected— based on the previous literature— the
regression coefficients on fringe benefit variables enter
p o sitiv ely in the basic m odel. T his is not com pletely
surprising because we might expect that jobs with good pay
would be accompanied by good benefits. The estimates in

34

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September 2004

the base models for the entire population are indicative of
this phenomenon with positive coefficients ranging roughly
between 0.10 and 0.20 for health insurance implying nontrivial
elasticities slightly larger than 0.16 for both data sets. Pension
coefficients from both data sets imply a slightly smaller
elasticity of around 0.08. Due to the endogeneity and
measurement concerns noted earlier, conclusions regarding
causality are difficult to make, although they are suggestive.
On the other hand, the estimates do shed light on the degree
of correlation between wages and benefits and suggest that
health and life insurance are more strongly correlated with
wages than pensions, a conclusion confirmed by the survey
re su lts found by the E m p lo y m en t B e n e fit R esearch
Institute.45
The p o sitiv e co efficien ts gen erated on the b en efit
variables are primarily indicative of an identification problem.
Thus, although the “good jobs, bad jo b s” story is not
surprising (for example, CEO’s have higher pay and better
benefits than, say, janitors), the positive estimates in the
tables imply that holding constant the set of covariates and
industry/occupation dummies does not accurately hold job
type constant. Note however, that workers in “good jobs”
may be able to change the mix of their benefit package (for
example, cafeteria-type plans) but workers in “bad jobs” may
have to physically switch jobs to gain their preferred levels
of wages and benefits.46 Hence, identification of the tradeoff
within job is not established but the correlation between
wages and benefits is established.
E x h ib it 1 (page 37) illu s tra te s the c o m p e n sa tin g
differentials theory diagrammatically with benefits on the
horizontal axis and wages on the vertical axis. The isocost
lines of two firms are pictured and w orkers’ indifference
curves are drawn tangent at different points to the firm ’s
locus. For each firm, worker A prefers higher wages and fewer
benefits, compared with workers B and C. If firms choose to
offer wage-benefit packages so that line I is constructed, this
will be the coefficient identified by the regressions in the top
panels of tables 3 and 4. Similarly, if the higher wage firms
offer relatively higher (lower) wages and fewer (more) benefits
to their lower wage counterparts, the estimation will identify line
II (III). The “hedonic line” is what these models aim to identify
because the negative slope implies a tradeoff between wages
and benefits. The implication of positive estimates from the
model, therefore, is lack of within job identification. By
segmenting the wage distribution into percentiles and focusing
on the bottom and top deciles, we may be better able to detect
those effects.
The top panels of tables 3 and 4 provide evidence for the
issues discussed earlier, however, the results in the lower
panels suggest otherwise. The estimates in panel B use the
same models for those above the 90th percentile point in the
income distribution.47 The coefficients are negative and

Table 3.

Regression results of benefits from the National Longitudinal Surrey of Youth via ordinary least squares model,
1998
Equation

P an e l A ■
w h o le sa m p le

(2)

(3)

0.151
(.014)**
.501
(.106)**
0.120
(.013)**

0.142
(.016)**
0.244
(.113)*
0.087
(.013)**

2.061
(.146)**
4,735
.37

2.301
(.147)**
4,735
.40

0.149
(.014)**
.502
(.106)**
.117
(.013)**
.000
(.000)**
2.045
(.146)**
4,735
.37

(1)
Health
insurance......
Life insurance..
Pension...........
Total days o ff...
Constant.........
Observations ...
R-squared.......

(4)
0.140
(.016)**
0.248
(.113)*
.084
(.013)**
.000
(.000)**
2.287
(.147)“
4,735
.40

(5)

(6)

(7)

(8)

0.139
(.014)**
0.539
(.102)**
.111
(.013)**
.000
(.000)**
2.053
(.143)**
4,584
.39

0.124
(.016)**
.306
(.108)**
.069
(.013)**
.000
(.000)**
2.325
(.143)**
4,584
.43

0.116
(.014)**
.521
(.101)**
.113
(.012)**
.000
(.000)**
1.930
(.142)**
4,584
.40

0.101
(.016)**
.279
(.107)**
.071
(.013)**
.000
(.000)**
2.206
(.143)**
4,584
.44

(10)

(9)
0.110
(.015)**
.519
(.101)**
.112
(.012)**
0.000
(.000)**
1.917
(.142)**
4,584
.40

0.090
(.016)**
.274
(.107)*
.066
(.013)**
.000
(.000)**
2.184
(.143)**
4,584
.44

P ane l B — 90 th
p e rc e n tile

(1)
Health
insurance......
Life insurance..
Pension...........

(2)

(3)

-0.097
(.04803)*
-.279
(.206)
.033
(.029)

-0.069
(.057)
-.394
(.242)
.029
(.031)

3.295
(.538)**
474
0.04

3.352
(.568)**
474
0.08

Total days off...
Constant.........
Observations ...
R-squared .......

(4)

-0.101
(.047)*
-.263
(.205)
.028
(.029)
.000
(.000)**
3.195
(.535)**
474
0.05

(5)

-0.072
(.057)
-.361
(.240)
.027
(.031)
.000
(.000)**
3.264
(.565)**
474
0.09

(6)

-0.057
(.045)
-.208
(.196)
.017
(.028)
.000
(.000)*
3.092
(.491)**
478
0.06

(7)

-0.038
(0.056)
-0.279
(0.227)
0.007
(0.030)
0.000
(0.000)*
3.206
(0.516)**
478
0.10

(8)

-0.063
(.045)
-.221
(.196)
.016
(.028)
.000
(.000)*
3.018
(.493)**
478
.06

(10)

(9)

-0.044
(.056)
-.300
(.227)
.006
(.030)
.000
(.000)*
3.106
(.519)**
478
.11

-0.049
(.047)
-.216
(.196)
.017
(.028)
.000
(.000)*
3.022
(.494)**
478
.07

-0.033
(.056)
-.293
(.227)
.007
(.030)
.000
(.000)*
3.115
(.519)**
478
.11

P anel C — 10th
p e rc e n tile

(1)
Health
insurance......
Life insurance..
Pension...........

(2)

(3)

-0.070
(.069)
-2.270
(.876)**
0.385
(.122)**

-0.046
(.074)
-1.918
(.930)*
.343
(.126)**

1.087
(.440)*
476
.09

Observations ...
R-squared.......

No

Industry/
occupation
dummies........
Additional
covariates.....

(5)

(7)

(8)

(10)

(9)

.845
(.484)
476
.14

-0.047
(.074)
-1.912
(.933)*
.342
(.127)**
.000
(.000)
.846
(.484)
476
.14

-0.102
(.068)
-2.353
(.856)**
.390
(.120)**
-.000
(.000)
1.161
(.444)**
464
.10

-0.085
(.073)
-2.015
(.909)*
.340
(.124)**
-.000
(.000)
.916
(.482)
464
.14

-0.131
(.069)
-2.317
(.854)**
.402
(.120)**
-.000
(.000)
1.080
(.445)*
464
.10

-0.119
(.074)
-1.980
(.905)*
.349
(.124)**
-.000
(.000)
.840
(.481)
464
.15

-0.154
(.071)*
-2.218
(.855)**
.384
(.120)**
-.000
(.000)
1.080
(.444)*
464
0.11

-0.143
(.076)
-1.889
(.905)*
.328
(.124)**
-.000
(.000)
.872
(.481)
464
.16

Yes

No

Yes

No

Yes

No

Yes

No

Yes

Union(0,1)

Union(0,1)

Union(0,1)
-ull-time(0,1)
Firm size

N ote : Standard set of covariates include age; number of children
under age 6; and indicator variables for black, Hispanic, high school
graduate, some college, college graduate, married, previously married,

statistically significant with life insurance entering the largest
in magnitude. The coefficient on health insurance in the n lsy
is significantly smaller than its counterpart for the whole


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(6)

-0.068
(.070)
-2.278
(.877)**
.389
(.123)**
-.000
(.000)
1.080
(.441)*
476
.09

Total days o ff...
Constant.........

(4)

Union(0,1)
Union(0,1)
Union(0,1)
Full-time(0,1) : ull-time(0,1) Full-time(0,1
Firm size
Firm size
Firm size

urban residence, and actual experience. Data set— nlsy ; Year: 1998;
dependent variable: log (hourly wage). Standard errors in parentheses; *
significant at 5 percent; ** significant at 1 percent.

population (table 3, panel A) and is only statistically
significant in the model without additional covariates. The
same holds true for the CPS sample in which the magnitude of

Monthly Labor Review

September 2004

35

Wages and Benefits

Table 4.

Regression results for Current Population Survey via ordinary least squares model, 1998
Equation

P anel A — w h o le s a m p le

(2)

(3)

0.199
(.004)**
.109
(.005)**
1.784
(.019)**
55,439
.32

0.202
(.008)**
.132
(.009)**
1.481
(.027)**
11,497
.32

(2)

(3)

-0.058
(.011)**
-.037
(.010)**
3.749
(.065)**
5,547
.04

-0.028
(.022)
-.012
(.019)
3.768
(.137)**
1,090
.04

(2)

(3)

(1)
Health insurance..........................
Pension........................................
Constant......................................
Observations...............................
R-squared....................................

0.228
(.004)**
.145
(.004)**
1.463
(.013)**
55,439
.30

(4)
0.168
(.009)**
.089
(.009)**
1.848
(.039)**
11,497
.35

(5)

(6)

0.175
(.008)**
.130
(.009)**
1.346
(.029)**
11,497
.33

0.148
(.009)**
.088
(.009)**
1.724
(.041)**
11,497
.36

(5)

(6)

(7)
0.172
(.009)**
.128
(.009)**
1.331
(.030)**
11,497
.33

(8)
0.142
(.009)**
.080
(.010)**
1.708
(.041)**
11,497
.36

P an e l B — 90 th p e rc e n tile

(1)
Health insurance..........................
Pension........................................
Constant......................................
Observations...............................
R-squared....................................

-0.054
(.010)**
-.020
(.009)*
3.714
(.056)**
5,547
.02

(4)
-0.011
(.024)
-.010
(.022)
3.637
(.158)**
1,090
.07

-0.020
(.022)
-.012
(.019)
3.818
(.139)**
1,090
.04

-0.005
(0.024)
-0.009
(0.022)
3.679
(0.162)**
1090
0.07

(7)
-0.012
(0.022)
-0.003
(0.020)
3.857
(0.140)**
1090
0.05

(8)
0.001
(0.025)
-0.001
(0.022)
3.711
(0.162)**
1090
0.07

P an e l C — 10th p e rc e n tile

(1)

(4)

(5)

(6)

(7)

(8)

Health insurance..........................

0.056
(.021)*

0.075
(.022)**

0.006
(.039)

-0.011
(-041)

-0.003
(.040)

-0.020
(.042)

-0.002
(.040)

-0.017
(.042)

Pension........................................

-.028
(.028)
1.166
(.035)**
5,549
.02

.024
(.029)
.707
(.071)**
5,549
.04

.029
(.054)
1.122
(.070)**
935
0.03

.026
(.055)
.959
(.153)**
935
.08

.028
(.054)
1.096
(.072)**
935
.03

.027
(.055)
.919
(.156)**
935
.08

.024
(.055)
1.105
(.079)**
935
.03

.027
(.057)
.936
(.157)**
935
.08

No

Yes

No
Union(0,1)

Yes
Union(0,1)

Constant......................................
Observations...............................
R-squared....................................
Industry/occupation dumm ies....
Additional covariates..................

N o t e : Standard set of covariates include age; number of children under
age 6; and indicator variables for black, Hispanic, high school graduate,
some college, college graduate, married, previously married, and urban

the health insurance coefficient is smaller than for the whole
sample and the analogous result in the NLSY.

The estimates for the pension variable are somewhat more
muddled. In the n l s y sample, pension coverage remains
positive in panel B and is smaller than the analogous results
in panel A; the estim ates are not statistically significant
however. For the CPS, the coefficient on pensions is negative,
between -0.002 and -0.04, and statistically significant in the
first two columns. The overall fit is markedly worse in the
subgroup (R2 around 0.05 for both samples) and the number
of observations drops significantly in the n l s y , from around
4,700 in panel A to fewer than 500 observations in panel B.
The results for respondents at the upper end of the
distribution suggest that wealthier individuals trade higher
wages for less health and life insurance benefits. Intuitively,

36

Monthly Labor Review


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Federal Reserve Bank of St. Louis

September 2004

No
Yes
No
Yes
Union(0,1)
Union(0,1)
Union(0,1)
Union(0,1)
Full-time(0,1) Full-time(0,1) Full-time(0,1) Full-time(0,1)
Firm size
Firm size

residence. Data set— cps ; Year: 1998; Dependent variable: log (hourly wage).
Standard errors in parentheses; * significant at 5 percent; “ significant at
1 percent.

because individuals at the higher end of the distribution are
better able to purchase insurance in the private market, the
offset of health and life insurance is logical. The estimates
also show that the correlation betw een w ages and life
insurance (and pensions) is much higher for workers at the
low end of the distribution. When additional covariates are
included in the regression (table 3, columns (6)-(10)), the
same results also hold for health insurance. The results for
pensions conflict each other between data sets in tables 3
and 4— estim ates from other m odels (fixed effects and
quantile regressions) are examined in the following sections
and tend to be more in concert.48
Analogous to the sample for those at the upper end of the
distribution, panel C estim ates the m odel at the other
extrem e— those at and below the 10th percentile of the

Ultimately, the results for the bottom of the distribution
are consistent in magnitude but are mixed in terms of statistical
significance and sign. Estimates from the CPS imply that
people at the bottom of the distribution correlate higher
benefits with higher wages and people at the other end of the
distribution correlate lower benefits with higher wages. The
n l s y implies a negative correlation between wages and
health and life insurance (though health insurance enters
insignificantly) for workers at the lower end of the wage
d istrib u tio n but those w orkers also ex h ib it a positive
correlation between wages and pensions. The differences
not only raise interesting conceptual and distributional issues
but also issues of estimation. The possibility of unobserved
worker heterogeneity is one concern with these models. In
the next section, the analysis is extended by estimating a
fixed effects model, exploiting the panel nature of the n l s y .

Fixed effects.

distribution. The results are strikingly different from those at
the 90th percentile. In the n l s y specification, the health
insurance coefficient is negative for specifications both with
and without industry-occupation dummies but is statistically
insignificant. In the CPS, which may be somewhat more reliable
g iv e n th e n u m b e r o f o b s e rv a tio n s (5 ,5 0 0 and 935
observations com pared to about 470 observations), the
coefficient on health insurance is positive and statistically
significant in the first three columns, between 0.007 and 0.08.
The coefficient on health insurance is negative in the other
five columns but of smaller magnitude and does not satisfy
statistical significance tests. Regardless of the data set, the
coefficient on health insurance is distinctly smaller in this
sample than when all workers are included.
Again, the coefficient on the pension variable differs
depending on the data set. In the n l s y , the coefficient on
pensions is much larger than for the entire sample— between
0.34 and 0.41— and is statistically significant in all 10 columns.
In the CPS however, the estimate on pensions is positive in
nine of the ten regressions but is not statistically distinguish­
able from zero in any of the runs. Here also, the coefficients
are smaller than their counterparts in panel A, different from
the NLSY-based estimates. Also notice however, that there
are more missing observations when unions, full-time status,
and firm size are added to the CPS than in the n l s y . This may
account for some of the differences across the columns in
table 4.


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The ordinary least squares models, estimated
earlier, neglect some important behavior of workers in the
labor market. Specifically, ordinary least squares ignores the
effects of unobserved heterogeneity among workers and
thus in this section, a fixed effects model is estimated using
the NLSY sample from 1990-98. (See table 5.)49
The entire sample from 1990-98 is pooled, resulting in around
30,000 observations. The coefficients on the variables of interest
are similar in sign and statistical significance to the ordinary
least squares results in table 3, but are smaller in magnitude.
Again, the coefficients are all positive and regressions that
include industry and occupation dummies result in slightly
smaller coefficients on the variables of interest.
When the sample is segmented and the model is estimated
for the 10th and 90th percentiles, the resulting estimates are
not consistently statistically significant and the sign on
h ealth and life in su ran ce is n eg ativ e in m o st o f the
specifications. For the lower end of the distribution, life
insurance enters negatively and is statistically significant in
regressions that include the additional covariates. Pensions
enter positively and are statistically significant in the other
half; the regressions without the additional covariate set.
For the 90th percentile, the model fit is poor with almost no
coefficients entering statistically significantly, although the
sign matches those for the 10thpercentile. Overall, accounting
for unobserved worker heterogeneity does not help identify
the hedonic effect but does reinforce the results found in the
previous tables, although the magnitude is much smaller.

Quantile regressions. It is apparent from the results in the
first three tables that the relationship between wages and
benefits are contingent upon the selected sample. Estimates
for workers at the top of the earnings distribution suggest a
tendency for workers to forego higher wages in lieu of more
pension benefits, whereas workers at the bottom of the

Monthly Labor Review

September 2004

37

Wages and Benefits

1 Regression results for NLSY via fixed effects
Equation
P anel A -W h o le sa m p le

(1)
Health insurance................
Life insurance.....................
Pension...............................

(2)

0.049
(.005)**
(.208)
(.072)**
(.050)
(.006)**

0.044
(.006)**
(.190)
(.076)*
(.050)
(.006)**

(2.206)
(.085)**
32,015
.05

(2.283)
(.087)**
32,015
0.05

Total days o ff.....................
Constant.............................
Observations.....................
R-squared ...........................

(3)
0.055
(.005)**
(-210)
(.072)**
(.050)
(.006)**
(.000)
(.000)
(2.192)
(.086)**
32,015
0.05

(4)
0.044
(.006)**
(.193)
(.076)*
(.050)
(.006)**
(.000)
(.000)
(2.268)
(.088)**
32,015
0.05

(5)
0.033
(.009)**
(.197)
(.091)*
(.046)
(.008)**
(.000)
(.000)
(2.473)
(.157)**
14,134
0.05

(6)
0.014
(-.010)
(.139)
(-.094)
(.042)
(.009)**
(.000)
(.000)
(2.567)
(.160)**
14,134
0.06

(7)
0.033
(.009)**
(.174)
(-.091)
(.046)
(.008)**
(.000)
(.000)
(2.408)
(.158)**
14,134
0.05

(8)
0.014
(-.010)
(.114)
(-.094)
(.041)
(.009)**
(.000)
(.000)
(2.504)
(.161)**
14,134
0.06

0)

(10)

0.031
(0.009)**
.172
(-.091)
.046
(.008)**
.000
.000
2.393
(.159)**
14,134
0.05

0.013
(-0.010)
.114
(-.095)
.041
(.009)**
.000
.000
2.492
(.161)**
14,134
0.06

(9)

(10)

P ane l B - 90 th p e rc e n tile

(1)
Health insurance................
Life insurance....................
Pension...............................

(2)

-0.028
(.023)
-0.011
(-177)
.035
(.016)*

-0.037
(.026)
-.063
(.194)
.033
(-017)

3.058
(.478)**
3,213
.05

3.130
(.490)**
3,213
.06

Total days o ff......................
Constant.............................
Observations......................
R-squared...........................

(3)
-0.028
(.023)
-.012
(.177)
.035
(.016)*
-.000
(.000)
3.063
(.479)**
3,213
.05

(4)
-0.037
(.026)
-.065
(.193)
.033
(.017)
-.000
(.000)
3.133
(.490)**
3,213
.06

(5)
0.079
(.060)
-.006
(.344)
.038
(.033)
-.000
(.000)
.888
(1.267)
1,414
.04

(6)
0.050
(.069)
-.089
(.375)
.020
(.035)
-.000
(.000)
1.124
(1.297)
1,414
.05

(7)
0.094
(.060)
-.069
(-344)
.035
(.033)
-.000
(.000)
.591
(1.270)
1,414
.05

(8)
0.067
(.070)
-.126
(.375)
.020
(.035)
-.000
(.000)
.827
(1.303)
1,414
.06

0.096
(.060)
-.064
(.345)
.036
(.033)
.000
.000
.078
(1.277)
1,414
.05

0.073
(.070)
-.109
(.375)
.020
(.035)
-.000
(.000)
1.040
(1.311)
1,414
.06

P an e l C - 10th p e rc e n tile

(2)

(1)
Health insurance................
Life insurance....................
Pension...............................

-0.007
(.024)
-.696
(-617)
.207
(.046)**

-0.024
(.025)
-.835
(.624)
.197
(.048)**

1.124
(.239)**
3,203
.02

Observations.....................
R-squared...........................

No

Industry/occupation...........
dummies
Additional covariates.........

(4)

1.314
(.263)**
3,203
.04

-0.026
(.025)
-.810
(.625)
.197
(.048)**
.000
(.000)
1.277
(.266)**
3,203
.04

Yes

No

Yes

Total days o ff.....................
Constant.............................

(3)
-0.007
(.024)
-.675
(.618)
.206
(.046)**
.000
(.000)
1.094
(.242)**
3,203
.02

Standard set of covariates include age; number of children under 6; and
indicator variables for black, hispanic, high school graduate, some college,
college graduate, married, previously married, urban residence and actual

distribution take jobs that have benefits in addition to their
regular w ages. In this section, quantile regressions are
performed on the 10th and 90thpercentiles in order to fit median
regression analysis on the two parts of the distribution. (The

38

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(5)
0.012
(.035)
-2.699
(.847)**
.039
(.070)
.000
(.000)
1.539
(.461)**
1,440
.06

(6)
-0.012
(.035)
-2.287
(.842)**
-.041
(-074)
.000
(.000)
1.239
(.499)*
1,440
.16

No
Yes
Union(0,1) Union(0,1)

(7)
0.013
(.035)
-2.679
(.850)**
.040
(.070)
.000
(.000)
1.545
(.462)**
1,440
.06

(8)
-0.011
(.035)
-2.272
(.845)**
-.040
(-074)
.000
(.000)
1.239
(.500)*
1,440
.16

(9)
0.009
(.035)
-2.674
(.854)**
.043
(.070)
.000
(.000)
1.534
(.464)**
1440
.06

(10)
-0.013
(.035)
-2.265
(.849)**
-.037
(.075)
.000
(.000)
1.232
(.501)*
1440
.16

No
Yes
No
Yes
Union(0,1)
Union(0,1)
Union(0,1)
Union(0,1)
Full-time(0,1) Full-time(0,1) Full-time(0,1) Full-time(0,1)
Firm size
Firm size

experience (weeks) . Data set: nlsy ; years: 1990-98; Dependesnt variable:
log (hourly wage). Standard errors in parentheses; * significant at 5 percent;
** significant at 1 percent.

results from the quantile regression model are available upon
request to the author.)
The co efficien ts from the q u antile reg ressio n s are
uniformly positive and generally statistically significant. In

the CPS, workers at the 10th percentile respond more strongly
to health insurance in terms of wages than those at the 90th
percentile.50 The coefficient estimates for workers below the
10thpercentile range between 0.20 and 0.29 while the estimates
for the 90th percentile are consistently smaller, between 0.09
and 0.11. The coefficients on pensions dem onstrate the
differences between the two parts of the distribution: For
workers below the 10th percentile, the estimate on pensions
range between 0.08 and 0.14, larger than the estimates for the
90thpercentile, which are between 0.07 and 0.12. Thus, workers
at the bottom part of the distribution respond more strongly
to wage changes than do those at the top of the distribution.
In the n l s y , the estimates on health insurance are uniformly
larger for the 10th percentile than the 90th percentile, mirroring
the results from the CPS data set. For pensions however, the
estim ates for the 10th percentile are larger than their 90th
percentile counterparts about half of the time. This suggests
that workers at the low end of the distribution respond more
strongly in term s of wages for health insurance but that
workers at the high end o f the distribution may respond more
strongly with respect to pensions.
In summary, the results from the quantile regressions
generally confirm the ordinary least squares estimates. The
effect of health insurance is larger for the bottom tenth of the
distrib u tio n in both data sets but the effect o f pension
benefits is somewhat mixed. The evidence in this section
continues to be indicative of the “good jobs, bad jobs” story*
although the use of the quantile regression method was useful
to gain insight into the different relationships betw een
different parts of the wage distribution.
As previously noted, results for additional subgroups
including men and women; those above the minimum wage
plus 25 cents and plus 50 cents; and several “at-risk” groups,
are omitted from the current analysis. The issues specific to
these groups are important for two reasons. First, different
groups may respond differently to work incentives. For
example, do women have less (more) benefits and do they
pay more (less) implicitly because of how pay packages work?
S eco n d , lo w -w ag e g ro u p s m ay re v e a l an in te re stin g
relationship between wages and benefits because their wages
are bounded below by the minimum wage. In results not
reported, an instrumental variable model was estimated by
using State-level minimum wages.51 Separating the worker
po p u latio n into subgroups p rovides an opportunity to

explore different instruments and to track different behaviors
and is a viable area for future work.

Conclusion
Compensating wage differentials are an important aspect of
the labor market, yet empirical estimation of these differentials
lags behind theory. To date, no researcher has convincingly
estimated a hedonic model although many have produced
mixed results. The estimates in this article point more to
correlations between wages and benefits than to tradeoffs.
The analysis did accomplish two main tasks. First, the data
employed in the analysis are seldom used by researchers due
to confidentiality restrictions. And second, the estim ates
suggest com pensating differentials for subgroups o f the
population, namely the (weakly) 10th and 90th percentiles but
tell a stronger story about the positive correlation between
wages and benefits and how they differ at various points in
the wage distribution.
The estimates imply that individuals at the top of the wage
distribution sometimes earn more than three times as much in
certain benefits than those at the bottom of the distribution.
Workers above the 90th percentile take slightly more of their
compensation in the form of wages than do people below the
10th percentile. Workers at the top of the distribution also
take (proportionately) less in insurance and required benefits
but roughly the same in pension benefits than do workers at
the lower tail of the wage distribution.
In all, the implications of this study are threefold. First, the
detailed data from the eci did generate improvements of point
estimates in that statistical significance was achieved in most
models. Second, the two different household-level data sets,
for the most part, confirmed one another; another check for
consistency. And third, point estimates were generally larger
for workers at the low end of the wage distribution although
estimates for workers above the 90th percentile suggest a
compensating differential for health insurance and wages.
The im plications of the distribution of benefits on the
(gross) wage distribution are important for policy and labor
m arket considerations. D istributional issues as they relate
to nonwage form s of com pensation are recently receiving
m ore attention and should continue to be explored as
better benefit data and better access to such data becom e
available.
□

Notes
A cknow ledgem ent:
This article was written while the author was a
graduate student at Syracuse University. The author would especially like
to thank Brooks Pierce and John Ruser for help using the Bureau of Labor
Statistics e c i data. He also thanks William Horrace, Thomas Kniesner,
Jeff Kubik, Solomon Polachek, and Timothy Smeeding for helpful
comments and suggestions. This research was conducted by having access


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to restricted b l s data on-site at b l s . The views expressed here are those of
the author and do not necessarily reflect the views of b l s .
1
Sherwin Rosen, “Hedonic Prices and Implicit Markets: Product
D ifferentiation in Pure C om petition,” The Journal o f P olitical
Economy, January 1974, pp. 34-55.

Monthly Labor Review

September 2004

39

Wages and Benefits

2 Gary W. Loveman, and Chris Tilly, “Good Jobs or Bad Jobs:
What Does the Evidence Say?” New England Economic Review,
(January/February, 1988), pp. 46-65.
3 William Wiatrowski, “The National Compensation Survey:
Compensation Statistics for the 21st Century,” Compensation and
Working Conditions (Bureau of Labor Statistics, Winter 2000), pp. 5 14.
4 Employee Benefit Research Institute, “Compensation Costs in
Private Industry March 1987 to March 2001,” Facts from ebri, August
2001, on the Internet at: http://www.ebri.org/facts/0801fact.htm,
5 Masanori Hashimoto, “Fringe Benefits and Employment,” in W.
T. Alpert and S. A. Woodbury, eds., Employee Benefits and labor
markets in Canada and the United States (W.E. Upjohn Institute for
Employment Research, Kalamazoo, Michigan, 2000), pp. 229-62.
6 B. K. A trostic, “C om m ent,” in J. E. T riplett, ed., The
Measurement o f Labor Cost, n b e r Studies in Income and Wealth, vol.
48 (Chicago, University of Chicago Press, 1981), pp. 389-94; Arleen
Leibowitz, “Fringe Benefits in Employee Compensation,” in J.E.
Triplett, ed., The Measurement o f Labor Cost, n b e r Studies in Income
and Wealth, vol. 48 (Chicago, University of Chicago Press, 1981),
pp. 371-89; and Timothy Smeeding, “The Size Distribution of Wage
and Nonwage Compensation: Employer Cost versus Employee Value,”
in J. E. Triplett, ed., The Measurement o f Labor Cost, n b e r Studies in
Income and Wealth, vol. 48 (Chicago, University of Chicago Press,
1981), pp. 237-86.
7 For example, see Stephen Woodbury, “Substitution between Wage
and Nonwage Benefits,” The American Economic Review, March 1983,
pp. 166-82 and Edward Montgomery, Kathryn Shaw, and Mary Ellen
Benedict, “Pensions and Wages: An Hedonic Price Theory Approach,”
International Economic Review, vol. 33 no. 1, 1992, pp. 111-28.
8 Charles Brown, “Equalizing Differences in the Labor Market,”
The Quarterly Journal o f Economics, February 1980, pp. 113-34.
9 Jonathan Gruber, and Alan B. Krueger, “The Incidence Mandated
Employer-Provided Insurance: Lessons from Workers Compensation
Insurance,” in D. Bradford, ed., Tax Policy and the Economy, vol. 5
(Cambridge, m a , m i t Press, 1991), pp. 111-44.

in the United States,” Industrial and Labor Relations Review, July
2002, pp. 610-27.
16 The earlier studies are: Arleen Leibowitz, “Fringe Benefits in
Employee Compensation, 1981;” B. K. Atrostic, “Alternative pay
measures and labor market differentials,” bls Working Paper 127
(Bureau of Labor Statistics, 1983); Woodbury, “Substitution between
Wage and Nonwage Benefits, 1983;” and Brown, “Equalizing
Differences in the Labor Market, 1980.” The later studies are: Gruber,
“The Incidence of Mandated Maternity Benefits,” 1994; Gruber, and
Krueger, “The Incidence Mandated Employer-Provided Insurance,
1991; and Altonji, and Paxson, “Labor Supply Preferences,” 1988.
17 Pierce, “Compensation Inequality,” 2001; Pierce, “Com­
pensation Inequality,” 1999; and William J. Carrington, Kristin
McCue, and Brooks Pierce, “N ondiscrim ination Rules and the
Distribution of Fringe Benefits,” Journal o f Labor Economics, 2002,
vol. 20 no. 2, part 2, pp. S5-S33.
18 The b l s staff pointed out that the distinction between defined
benefit and defined contribution plans in the e c i survey is sometimes
vague and thus calculating average values by categories may be
erroneous. Thus, for the regressions in this study, the pension variable
refers to all pension plans including defined benefit and defined
contribution plans.
19 For more on the details of the e c i data set, see John W. Ruser,
“The Employment Cost Index: What is it?” Monthly Labor Review,
September 2001, pp. 3-20.
20 Bureau of Labor Statistics. “National Employment, Hours, and
Earnings from the Current Employment Statistics Survey,” Standard
Industrial Classification code based, on the Internet at: http://
www.bls.gov/ces (extracted July 2002). Additionally, the b l s uses
certain imputation procedures to address sample attrition over time.
A set of these imputed values was dropped from the sample used in
this study. The author would especially like to thanks Brooks Pierce
for calling attention to both of these issues.
The construction of the consistent weights modifies the industry
weights in the e c i :
A
w . x Employment
ww =
v V -----------_
<7

10 Jonathan Gruber, “The Incidence of Mandated Maternity Benefits,”
American Economic Review, vol. 84 no. 3, 1994, pp. 622-41.
11 Joseph G. Altonji, and Christina H. Paxson, “Labor Supply
Preferences, Hours Constraints, and Hours-wage Trade-offs,” Journal
o f Labor Economics, April 1988, pp. 254-76.
12 Brooks Pierce, “Compensation Inequality,” Quarterly Journal of
Economics, November 2001, pp. 1493-1525; Pierce Brooks,
“Compensation Inequality,” Bureau o f Labor Statistics Working Paper
323 (Bureau of Labor Statistics, June 1999); and Craig A. Olson, “Do
Workers Accept Lower Wages in Exchange for Health Benefits?” Journal
o f Labor Economics, vol. 20, no. 2 (part 2), 2002, pp. S91-S114.
13 Pierce “Compensation Inequality,” 2001; Pierce, “Compensa­
tion Inequality,” 1999.

*

where w = industry weight in the e c i ; q = quarter; i = industry; y = year; and
Employmenty. = external employment count in industry i in year y.
21 Due to the confidentiality of the e c i data set, industry and
occupation cell sizes were restricted based on the number of
observations in each. In addition, because some agriculture and
governm ent employees are not included in the e c i , they were
eliminated from the n l s y and c p s samples. This leaves nine occupation
categories (executive, adm inistrative and m anagerial; sales;
adm inistrative support; precision production, craft and repair;
machine operators, assemblers and inspectors; transportation and
material moving; handlers, equipment cleaners, helpers, and laborers;
service except private household; and professional, technical and
specialty) and seven industry categories (mining; construction;
manufacturing; transportation; wholesale and retail trade; finances,
insurance and real estate; and services and public administration).

14 Olson, “Do Workers Accept Lower Wages in Exchange for
Health Benefits?” 2002. Olson also estimates the same models using
data from the April 1993 Consumer Price Index Fringe Benefit
Supplement and again finds negative, though statistically insignificant,
coefficients in the range of -0.290 to -0.030.

22 Bureau of Labor Statistics “Employer Costs for Employee
Compensation: Historical Listing, 1986-2001,” on the Internet at:
ftp://ftp.bls.gov/pub/special.requests/ocwc/ect/ECECHIST.PDF
(September, 2001).

15 See also, Thomas C. Buchmueller, John DiNardo, and Robert G.
Valletta, “Union Effects on Health Insurance Provision and Coverage

23 Smeeding, “The Size D istribution of Wage and Nonwage
Compensation,” 1981.

40

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September 2004

24 The n l s y does not ask whether a respondent has leave or not;
instead it asks how many days are provided to the respondent. In this
study, the author chose to use the total number of days off from the
n l s y (vacation plus sick) rather than use the imputed dollar values
from the e c i because actual days off is probably a better measure. The
total number of days off variable was top-coded at 260 because that is
the greatest number of days an individual working five days a week, 52
weeks a year could use. The difference between using the n l s y days-off
variable and the e c i dollar variable was not very significant.
25 Daniel S. Hammermesh, “LEEping into the future of labor
economics: the research potential of linking employer and employee
data,” Labour Economics, March 1999, pp. 25-42.
26 John M. Abowd, and Francis Kramarz, “Econometric analyses of
linked employer-employee data,” Labour Economics, March, 1999,
pp. 53-76.
27 Robert F. Elliott and Robert Sandy, “Adam Smith may have been
right after all: A new approach to the analysis of compensating
differentials,” Economics Letters, April 1998, pp. 127-31.
28 Greg J. Duncan and Daniel H. Hill, “An Investigation of the
Extent and Consequences of Measurement Error in Labor-economic
Survey Data,” Journal o f Labor Economics, October 1985, pp. 50832; and Wesley Mellow and Hal Sider, “Accuracy of Response in Labor
M arket Surveys: Evidence and Im plications,” Journal o f Labor
Economics, October 1983, pp. 331-44.
For an early look at some of these issues, see also R. Smith, and R.
Ehrenberg, “Estimating Wage-Fringe Trade-Offs: Some Data Pro­
blems,” in J.E. Triplett, ed., The Measurement o f Labor Cost, vol. 48
(Chicago, University of Chicago Press, n b e r Studies in Income and
Wealth, 1981), pp. 347-70.
29 For a comprehensive review of this literature, see John Bound,
Charles Brown, and Nancy Mathiowetz, “Measurement Error in Survey
Data,” in James J. Heckman and Edward Learner eds., Handbook of
Econometrics, Volume 5 (Amsterdam, North-Holland, 2001), pp.
3707-45.
30 For an extended discussion, see Smeeding, “The Size Distribution
of Wage and Nonwage Compensation,” 1981.
31 The health insurance question in the C PS is slightly different than
the question in the n l s y ; it asks whether the respondent was covered
by a health plan provided by their employer. This implies that
individuals answer having already accepted (or rejected) health
insurance offers. The questions for pensions however, are similar in
the two household samples.
32 The estimates use the hourly wage reported in the n l s y and c p s ,
not the e c i . This approach is preferred because the focus is on the
tradeoffs made by workers, not employers.
33 Actual experience is only included in the n l s y sample and is
calculated by summing the number of weeks worked for each year of
the survey from 1979 to the year of interest. If, in any given year, a
respondent was a student and the data for the number of weeks is
missing, weeks worked are then set equal to zero in that year. Additional
missing data are then dropped from the sample. Values for 1995 (and
1997) are set equal to the average of 1994 and 1996 (and 1996 and
1998) .

eci

34 Estimates reported use the n l s y and c p s sample weights; using the
sample weights makes little difference on the results in most models.

35 Moshe Buchnisky, “Recent Advances in Quantile
RegressionModels: A Practical Guideline for Empirical Research,” The


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Journal o f Human Resources, Winter 1998, pp. 88-126; and Roger
Koenker, and Kevin F. Hallock, “Quantile Regression,” Journal o f
Economic Perspectives, Fall 2001, pp. 143-56. The author thanks
the b l s reviewer for making this analogy.
36 Olson, “Do Workers Accept Lower Wages?” 2002.
37 Pierce, “Compensation Inequality,” 1999.
38 See the dissertation by Jonathan A. Schwabish, “Three Essays in
Inequality,” unpublished doctoral dissertation, Syracuse University,
Syracuse, New York, 2003 for an explanation of the results for these
groups.
39 As discussed in the literature section, the studies by Gruber “The
Incidence of Mandated Maternity Benefits,” 1994 and Gruber and
Krueger, “The Incidence Mandated Employer-Provided Insurance,”
1991 use variation in State mandated benefit coverage as instruments
to correct for endogeneity introduced by their benefit variables. The
current study performed similar exercises with the c p s data using
variation in State minimum wages as instruments for the wage. The
instruments proved to be weak however, and thus are not reported.
40 Craig Copeland, “Pension Plan Participation Continued to Rise
in 2000— What N ext?” ebri Notes (Employee Benefit Research
Institute, March 2002), pp. 4-7.
41 Rachel Christensen, “Value of Benefits Constant in a Changing
Word: Findings from the 2001 e b r i / m g a Value of Benefits Survey,” ebri
Notes (Employee Benefit Research Institute, March 2002), pp. 1-3.
42 Note that the mean age in the n l s y will differ by approximately
1 year in each survey year because of the panel nature. The c p s , by
contrast, will basically have the same mean age in each survey. Thus,
the comparison in 1998 is the closest in terms of ages.
43 As mentioned earlier in the endnote section, the estimates use
the hourly wage reported in the n l s y and c p s , not the e c I . This
approach is preferred because the focus is on the tradeoffs made by
workers, not employers.
44 In regressions where the benefit variables enter individually,
coefficients are markedly larger in magnitude—they are not reported
in this study because the more comprehensive models are more
informative and perform just as well.
45 Christensen, “Value of Benefits,” 2002.
46 Loveman and Tilly, “Good Jobs or Bad Jobs,” 1988, pp. 46-65.
47 Note that the percentile points in the remaining tables were
calculated in the household surveys, not from the e c i data.
48 Recall that the n l s y has a compressed age distribution, whereas
the c p s includes persons 18 to 64 years of age. This may account for
some of these differences.
49 A fixed effects model solely on the e c i data was also considered.
However, sample attrition issues within the e c i as well as con­
fidentiality issues led this to be too difficult a task.
50 Tables containing the results for the 10lh and 90th percentiles for
both data sets are available upon request to the author and can be
found in Schwabish, “Three Essays in Inequality,” 2003.
51 The results from the instrumental variables model are not a main
focus of this study for several reasons, including mixed sign and lack of
statistical significance on the instrumental variable (the State minimum
wage); poor overall fit; and mixed results in the second stage.

Monthly Labor Review

September 2004

41

Report from the Regions

Employment in the
information sector
in March 2004
Gerald Perrins
mployment in the information sec­
tor stood at 3,158,000 in the United
States in March 2004, 1.7 percent less

E

Gerald Perrins is the regional economist in
the Philadelphia Regional Office, Bureau of
Labor Statistics, Philadelphia, Pennsylvania.
E-mail: Perrins.Gerald@bls.gov

Chart 1

than the year befo re.1 N ationw ide,
56,000 jobs were lost over this 12-month
period, continuing a trend of over-theyear declines that began in September
2001. (See chart 1.) Since the start of the
most recent recession in March 2001,
this industry sector has lost 555,000 jobs
or approximately 1 out of every 7 posi­
tions. N early three-fo u rth s of the
monthly over-the-year losses in infor­
mation since March 2001 occurred in the
telecommunications (-276,300) and pub­
lishing (-127,300) industries. (Use of not
seasonally adjusted data does not allow
for over-the-m onth comparisons; ac-

cordingly, monthly analysis was based
on the over-the-year change.)

Information employment
by State
Among the 14 States in the Nation in
which information-sector employment
exceeded 75,000,11 reported over-theyear job decreases in March 2004, two
(Georgia and North Carolina) were es­
sen tially unchanged, and only one
(W ashington) recorded an increase.2
The largest over-the-year employment
declines were in California (-16,800),

Employment in the information sector, over-the-year net change, 1999-2004

Employment change
(In thousands)

Employment change
(in thousands)

300

300

200

200

100

100

■100

-100

-200

-200

-3 0 0 Ld------ 1------ 1------ 1------ L
1999
2000

42

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J_____L

J_____L

2001

September 2004

2002

J_____L

2003

-3 0 0
2004

■ Employment change in the information sector, March 2003-04, United States and selected States,
not seasonally aajusrea
[Numbers in thousands]
A re a

M a rc h
2003

January
2004

M a rc h
20043

February
2 0 04

C h a n g e s from M a rc h
2003 to M a rc h 2004
Net

United States................................

Percent

3,214.0

3,151.0

’3,155.0

3,158.0

-56.0

-1.7

93.0
102.8
278.1
124.3

88.6
99.1
270.3
121.1

88.4
99.7
273.6
120.9

88.0
100.8
276.2
121.7

-5.0
-2.0
-1.9
-2.6

-5.4
-1.9
-0.7
-2.1

173.0
127.3
75.8
237.5
101.5

171.1
126.8
74.7
228.5
101.1

171.6
127.3
75.6
229.1
100.3

170.1
126.5
75.1
230.4
100.4

-2.9
-0.8
-0.7
-7.1
-1.1

-1.7
-0.6
-0.9
-3.0
-1.1

135.2
97.7

131.7
95.6

131.2
95.0

131.4
95.1

-3.8
-2.6

-2.8
-2.7

481.0
85.7
91.5

466.2
82.7
92.7

466.7
83.3
93.4

464.2
82.7
93.8

-16.8
-3.0
2.3

-3.5
-3.5
2.5

N o rth east

Massachusetts..........................
New Jersey...............................
New York...................................
Pennsylvania............................
S ou th

Florida........................................
Georgia......................................
North Carolina...........................
Texas .........................................
Virginia.......................................
M id w est

Illinois........................................
O hio...........................................
W est

California...................................
Colorado....................................
Washington ...............................

NOTE: States selected had information-sector employment levels
exceeding 75,000 in September 2003.

1 Data for the United States are preliminary.
2Data are preliminary.

1 Employment change in selected industries in the information sector over the March 2003-04 perioci,
United States and selected states
[Preliminary data, not seasonally adjusted]

A re a

United States................................

M o tio n p ic tu re
a n d sound
re c o rd in g

In te rn e t
s e rv ic e
p ro v id e rs '

B ro a d c a s tin g ,
except
In te rn e t

Total

Publishing,
except
In te rn e t

-56,000

-20,900

9,000

6,500

-43,900

-7,800

-5,000
-2,000
-1,900
-2,600

-2,200
-700
500
-1,100

900
-

300
-

-1,600
-1,400
-3,700
-900

-500
-800
-700

-2,900
-800
-700
-7,100
-1,100

600
^100
-1,500
-

-

-500
-

-1,900
800
-1,200
-6,100
-2,700

-1,400
0
-300
-600
-

-3,800
-2,600

-1,200
-700

-100
-

-300
-

-1,800
-1,700

-200
-

-16,800
-3,000
2,300

-5,200
-900
-

-3,100
—

700
0

-8,300
-2,300
-100

-1,300
-

N o rth east

Massachusetts..........................
New Jersey...............................
New York...................................
Pennsylvania............................
S ou th

Florida........................................
Georgia......................................
North Carolina...........................
Texas .........................................
Virginia.......................................
M id w es t

Illinois........................................
O hio...........................................
W est

California...................................
Colorado....................................
Washington...............................

’ Data for Internet service providers, Web search portals, and data processing services are included in this category.


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

NOTE: Data for Internet publishing and broadcasting and other information
services are available for the United States as a whole but are omitted from
this table. Dash indicates data not available.

Monthly Labor Review

September 2004

43

Report from the Regions

followed by Texas (-7,100), and M as­
sachusetts (-5 ,0 0 0 ). (See table 1.)
These three States employed 1 out of
every 4 workers in this industry. The
largest over-the-year percentage de­
clines in employment occurred in M as­
sachusetts (-5 .4 percent), followed by
Colorado and California (-3.5 percent
each), and Texas (-3 .0 percent).
The only State to post an over-theyear employment increase in the informa­
tion sector was W ashington, which
added 2,300 jobs between March 2003
and 2004, a gain of 2.5 percent. This was
the third consecutive month that the
State had more information jobs than a
year earlier. Until these recent advances,
Washington had registered over-the-year
job declines in every month since July
2001. In the other 13 States, over-theyear job declines in the information sec-

tor have continued for lengthy periods,
ranging from 30 to 36 consecutive
months.
Among States with employment de­
clines in the information industry, the
teleco m m unications subsector was
typically the hardest hit, with particu­
larly heavy losses in California (-8,300),
Texas (-6,100), and New York (-3,700).
(See table 2.) Employment declines were
also w idespread in the p u b lish in g
subsector, with five States (California,
M assachusetts, Texas, Illinois, and
Pennsylvania) recording declines of
more than 1,000 jobs since last March.
Other subsectors were highly concen­
trated; Florida and California, which
have a large concentration of Internet
service providers jobs, bore the brunt
of this industry’s losses— down 1,400
and 1,300 jobs, respectively. The de-

clines in these two States accounted for
more than one-third of the over-the-year
job losses in the Internet service pro­
viders industry nationwide. Despite the
loss of 3,100 motion picture and sound
recording jobs in California, this indus­
try gained 9,000 jobs nationwide be­
tween March 2003 and 2004. Broad­
casting was the only other information
industry sector to add jobs over the
year nationwide, up 6,500.
Employment in the information sec­
tor is not regionally concentrated, with
those States with job counts exceeding
75,000 located in all four geographic re­
gions of the country.3 (See map.) Like­
wise, over-the-year em ploym ent de­
clines in this industry extended to all
regions of the country over the last 2
years. (See tables 3,4, and 5 for changes
during 2002,2003, and 2004.)

Employment changes over the July-December 2002 period, United States and selected States
■ not seasonally adjusted

^

[N u m b e rs in t h o u s a n d s ]

O v e r-th e -y e a r n e t c h a n g e

O v e r -th e -y e a r p e rc e n t c h a n g e

A re a a n d region

United States........

July

Aug.

Sept.

-239.0

-228.0

-237.0

-209.0

-206.0

-12.1
-14.7
-34.1
-8.2

-11.7
-12.5
-29.7
-7.5

-11.1
-16.9
-29.5
-6.9

-9.2
-19.9
-26.6
-6.9

-11.4
-12.0
-2.8
-21.8
-14.3

-10.9
-11.8
-3.3
-22.0
-13.6

-9.9
-12.1
-2.3
-22.1
-14.0

-11.4
-5.5

-11.4
-5.5

-52.6
-14.9
-5.4

-43.8
-14.5
-5.1

O c t.

Nov.

D ec.

July

Aug.

Sept.

-230.0

-6.6

-6.3

-6.6

-8.7
-19.2
-27.5
-6.8

-7.8
-19.7
-26.9
-7.0

-10.8
-11.7
-10.5
-6.0

-10.6
-10.1
-9.2
-5.5

-8.6
-10.9
-1.9
-21.0
-12.2

-8.0
-13.3
-2.4
-20.9
-10.5

-8.1
-13.0
-1.0
-19.3
-10.2

-6.1
-8.4
-3.4
-8.1
-12.0

-11.9
-5.3

-10.4
-5.9

-11.1
-5.3

-12.1
-5.4

—47.6
-13.9
-3.9

-36.1
-12.9
-3.0

-27.6
-12.3
-2.7

-43.1
-11.9
-3.4

O c t.

Nov.

D ec.

-5.9

-5.8

-6.5

-10.3
-13.4
-9.3
-5.2

-8.7
-16.0
-8.4
-5.2

-8.3
-15.3
-8.6
-5.1

-7.4
-15.7
-8.5
-5.3

-5.8
-8.3
-4.0
-8.2
-11.5

-5.3
-8.5
-2.9
-8.3
-12.0

-4.7
-7.7
-2.4
-7.9
-10.7

-4.4
-9.4
-3.0
-7.9
-9.3

—4.4
-9.2
-1.3
-7.4
-9.0

-7.3
-5.1

-7.4
-5.2

-7.8
-5.1

-6.9
-5.7

-7.4
-5.1

-8.0
-5.2

-9.8
-14.0
-5.4

-8.2
-13.7
-5.1

-9.0
-13.4
-4.0

-6.9
-12.6
-3.1

-5.3
-12.1
-2.8

-8.2
-11.8
-3.5

Northeast

Massachusetts....
New Jersey..........
New York..............
Pennsylvania.......
South

Flordia...................
Georgia................
North Carolina.....
Texas ....................
Virginia..................
Midwest

Illinois...................
O hio......................
West

California..............
Colorado...............
Washington..........

44

Monthly Labor Review


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Federal Reserve Bank of St. Louis

September 2004

Table 4. Employment changes over the January-December 2003 period, United States and selected States,
not seasonally adjusted

[N u m b e rs in t h o u s a n d s ]

O v e r-th e y e a r n e t c h a n g e
A re a a n d reg io n

United States..........

Nov.

D ec.

-181.0

-160.0

-113.0

-7.0
-7.6
-16.1
-3.5

-6.8
—3.5
-14.8
-3.5

-7.0
-4.5
-15.0
-3.6

-7.3
—3.5
-12.3
-3.7

-5.1
-4.7
-2.7
-11.7
-3.3

-2.8
-4.6
-1.4
-11.8
-2.6

-1.9
-3.9
-1.6
-11.5
-1.6

-3.5
-1.8
-1.7
-11.7
-1.8

-3.4
-1.4
-2.7
-11.6
-1.3

-8.6
-3.1

-8.7
-3.1

-7.3
-3.2

-7.0
-2.5

-6.3
-3.0

-6.0
-2.8

-23.0
-6.9
-1.5

-19.5
-6.6
-.8

-20.2
-6.0
-.7

-23.2
-4.9
-.8

-23.2
-5.1
-1.0

-14.7
-4.4
-.1

M ay

Jun.

July

Aug.

S ept.

O c t.

-223.0

-217.0

-210.0

-194.0

-197.0

-165.0

-9.5
-17.5
-20.9
-6.4

-8.4
-14.2
-23.5
-5.5

-8.2
-14.3
-22.1
-5.7

-7.3
-13.1
-26.4
-4 .9

-8.3
-8.7
-19.3
-4.2

-7.7
-8.0
-14.6
-3.6

-3.4
-19.7
-8.6

-8.0
-5.5
-3.3
-18.4
-7.8

-7.8
-6.2
-3.8
-17.7
-7.3

-8.7
-6.5
-4.8
-16.1
-6.9

-8.2
-6.8
-4.5
-15.9
-6.6

-7.7
-5.7
-3.9
-15.2
-5.5

-5.9
-5.8
-3.3
-12.0
-3.3

-12.1
-5.3

-11.5
-4.8

-12.4
-4.5

-12.1
-4.3

-11.7
-3.6

-10.9
-3.8

-30.3
-11.6
-2.0

-24.8
-10.9
-1.9

-38.8
-10.5
-2.0

-30.6
-10.2
-2.1

-27.3
-9.2
-1.6

-35.3
-8.7
-1.8

Jan.

Feb.

M ar.

Apr.

-233.0

-237.0

-234.0

-9.8
-18.2
-22.4
-6.3

-9.6
-17.9
-22.3
-6.5

-8.8

Northeast

Massachusetts.....
New Jersey...........
New Y o rk...............
Pennsylvania.........
South

Flordia....................
G eorgia.................
North Carolina.......
Texas .....................
Virginia...................

-4 .7

Midwest

Illinois.....................
Ohio........................
W est

California...............
Colorado................
Washington...........

O v e r-th e y e a r p e rc e n t c h a n g e

United States..........

-6.7

-6.9

-6.8

-6.5

-6.4

-6.1

-5.7

-5.8

-5.0

-5.4

-4.8

-3.4

-9.5
-15.0
-7.5
-4.8

-9.3
-14.9
-7.4
-5.0

-9.3
-14.5
-7.0
-4.9

-8.4
-12.2
-7.9
-4.3

-8.2
-12.3
-7.2

-7.3
-11.3
-8.7
-3.8

-8.3
-7.8
-6.6
-3.3

-7.8
-7.2
-5.0
-2.8

-7.2
-6.9
-5.6
-2.8

-7.0
-3.3
-5.1
-2.8

-7.2
-4.2
-5.1
-2.9

-7.5
-3.3
—4.2
-2.9

—4.9
-3.5
-4.3
-7.6
-7.8

-4.4
-4.1
-4.2
-7.2
-7.1

-4.3
-4.6
-4.8
-6.9
-6.7

-4.9
-4.9
-6.1
-6.4
-6.4

-4.6
-5.1
-5.7
-6.3
-6.1

-4 .3

-4.3
-4.9
-6.0
-5.1

-3.3
-4.4
-4.2
-4.8
-3.1

-2.9
-3.6
-3.5
-3.2

-1.6
-3.5
-1.8
-4.8
-2.5

-1.1
-3.0
-2.1
-4.7
-1.6

-2.0
-1.4
-2.2
-4.8
-1.7

-1.9
-1.1
—3.5
-4.8
-1.3

-8.1
-5.1

-7.8
-4.7

-8.4
-4.4

-8.2
-4.2

-7.9
-3.5

-7.4
-3.7

-6.0
-3.1

-6.1
-3.1

-5.2
-3.2

-5.0
-2.5

—4.5
-3.0

-4.3
-2.8

-5.9
-11.8
-2.1

-4.9
-11.2
-2.0

-7.5
-10.9
-2.1

-6.1
-10.7
-2.3

-5.4
-9.8
-1.7

-7.0
-9.3
-1.9

-4.7
-7.5
-1.6

-4.0
-7.3
-.9

—4.2
-6.7
-.8

-4.8
-5.5
-.9

-4.7
-5.7
-1.1

-3.1
-5.0
-.1

Northeast

Massachusetts.....
New Jersey...........
New Y o rk...............
Pennsylvania.........

-4 .4

South

Flordia...................
Georgia..................
North Carolina.......
Texas .....................
Virginia...................

-4.1

Midwest

Illinois.....................
Ohio........................
West

California...............
Colorado................
Washington...........


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Federal Reserve Bank of St. Louis

Monthly Labor Review

September 2004

45

Report from the Regions

Table 5. Employment changes over the January-March 2004 period, United States and selected States
not seasonally adjusted

[N u m b e rs in th o u s a n d s ]

O v e r-th e y e a r n e t c h a n g e

A re a a n d regio n

United States..............................

O v e r-th e y e a r p e rc e n t c h a n g e

January

February

M a rc h 1

-98.0

-66.0

-56.0

-5.1
-3.7
-6.7
-3.0

-4.7
-2.7
-7.4
-2.6

-.6
-3.5
-1.5
-10.1
-.2

January

February

M arci

-3.0

-2.0

-1.7

-5.0
-2.0
-1.9
-2.6

-5.4
-3.6
-2.4
-2.4

-5.0
-2.6
-2.6
-2.1

-5 4
-1 9
- 7
-2.1

-1.0
-2.1
-.5
-8.8
-1.3

-2.9
-.8
-.7
-7.1
-1.1

-.3
-2.7
-2.0
-4.2
-.2

-.6
-1.6
-.7
-3.7
-1.3

-1 7
- 6
-3.0
-1.1

-4.7
-2.6

-5.1
-2.7

-3.8
-2.6

-3.4
-2.6

-3.7
-2.8

-2.8
-2.7

-13.6
-3.8

-19.8
-2.8
1.4

-16.8
-3.0
2.3

-2.8
-4.4

-4.1
-3.3
1.5

-3.5
-3.5
2.5

Northeast

Massachusetts.........................
New Jersey................................
New York.....................................
Pennsylvania............................
South

Flordia........................................
G eorgia......................................
North Carolina...........................
Texas..........................................
Virginia.......................................

- 9

Midwest

Illinois.........................................
Ohio ...........................................
West

California....................................
Colorado.....................................
Washington................................

.5

.5

1 Data are preliminary.
Note : February data for the United States are also preliminary.

Information industry employment, 2003 annual average

46

Monthly Labor Review


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Federal Reserve Bank of St. Louis

September 2004

Notes
1 The nonfarm payroll series for States
and metropolitan areas produced from the
Current Employment Statistics (CES) pro­
gram are based on the 2002 North Ameri­
can Industry Classification System (NAICS).
NAICS is the product of a cooperative effort
on the part of the statistical agencies of the
United States, Canada, and Mexico. NAICS
uses a production-oriented approach to cat­
egorize economic units. Units with similar
production processes are classified in the
same industry. See http://www.bls.gov/sae/
saewhatis.htm for an overview of NAICS


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Federal Reserve Bank of St. Louis

classification. All State nonfarm payroll
employment estimates have a NAICS-based
history extending back to January 1990,
except for total nonfarm employment esti­
mates which have retained their beginning
date.
This report contains data for the Infor­
mation sector (NAICS sector code 51), which
includes software publishing, and both These
nonfarm payroll data series reflect March
2003 benchmark levels, the completion of
the conversion of the CES survey sample
from a quota-based basis to a probabilitybased basis, and a modification of the sea­
sonal adjustment process.
2 State estimation procedures are designed

to produce accurate data for each individual
state. BLS independently develops a national
employment series; State estimates are not
forced to sum to national totals. Because each
State series is subject to larger sampling and
nonsampling errors than the national series,
summing them cumulates individual State-level
errors and can cause significant distortions at
an aggregate level. Due to these statistical limi­
tations, BLS does not compile a “sum-ofstates” employment series, and cautions users
that such a series is subject to a relatively large
and volatile error structure.
3
There are four geographic regions in the
United States as defined by the U.S. Census
Bureau: Northeast, South, Midwest, and West.

Monthly Labor Review

September 2004

47

Self-em ploym ent
around The world

rosy view” of what it’s like to run one’s
own business.
The study finds that self-employed
workers are more satisfied with their
jobs and pay than those who work for
others. In addition, entrepreneurs tend
to enjoy their work more than employees
and spend less time commuting. On the
other hand, the self-em ployed work
many more hours than employees, often
find their work stressful and exhausting,
spend less time than they would like
with their families, and find it difficult to
devote tim e to nonw ork activ ities.
These findings support the au th o r’s
contention that self-employment is not
for everyone. Although many people
would like the benefits of owning their
own business, they would not be willing
to accept the costs of self-employment.

In countries around the world, many
people think that owning o n e’s own
business is a more desirable form of
em ployment than working for others. A
recent study by Dartmouth economist
David G Blanchflower, however, argues
that self-em ploym ent may not be for
everyone. Self-em ployed persons are
highly m otivated, driven individuals,
who face considerable risks and often
pay a high price for owning their own
business; a price most people are not
willing to pay.
Blanchflow er presents data for 70
d iffe re n t co u n tries, but focuses on
comparisons between the United States
and Europe. The study finds that in all
countries, larger proportions of workers
Goods output versus
say they w ould p refer to w ork for
m anufacturing
them selves than actually do. In the
production
United States, for example, 71 percent
of the respondents to a survey covering
“A curious phenomenon of the 2001
19 97-98 in dicated that they w ould
recession was the sharp divergence
prefer to work for themselves, but only
between two arguably similar economic
about 7 percent actually w ere selfindicators,” opens Charles Steindel in
employed at the time. Similar disparities ' C urrent Issues in Econom ics and
exist in Europe and the other countries,
Finance from the New York Federal
even when the proportion preferring
Reserve Bank. He goes on to analyze
self-employment is relatively small. At
the divergent patterns of the Federal
the same time, the proportion prefering
R e se rv e B o a rd ’s ow n fig u re s on
self-em ploym ent varied considerably
m anufacturing production and goods
by country— from 27 percent in Norway
output as measured by the Bureau of
to 80 percent in Poland.
Economic Analysis.
Such findings present a paradox for
M a n u fa c tu rin g p ro d u c tio n , a
economists, because economic theory
com ponent of the broader industrial
suggests that as the labor market moves
production index, declined by about 6-%
toward equilibrium, the demand for selfpercent from June 2000 through December
em p lo y m en t w ill m eet the supply.
2001. Over the next year and a half, there
Instead, it appears that in both Europe
was very little growth in the index and it
and th e U n ite d S ta te s , th e re are
wasn’t until the middle of 2003 that the
num erous “frustrated entrepreneurs.”
series began to recover more strongly. In
This suggests that while many workers
contrast, goods output, a component of
may be drawn to the idea of working for
the gross domestic product accounts,
them selv es, they face co n sid erab le
suffered only a mild decline in the recent
constraints— personal and economic—
recession and displayed what Steindel
against their becoming self-employed.
ch aracterizes as “ sustained grow th
They may also have an “unrealistically
afterward.”

48

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Federal Reserve Bank of St. Louis

September 2004

Steindel found that there was an
u n d erly in g d e fin itio n a l d iffe re n c e
between the two series that would be a
key to understanding the difference in
trends. The measure of goods output
included the output of service sector
firms that were involved in bringing the
goods to market. This helps explain the
long-term divergence of goods output
and manufacturing production in terms
of the role of services in the sale of
goods. First, because imported goods
typically require more services to bring
to market, the growing significance of
imports and the fact that the U.S. service
component of their sale is included in
the goods output measure tends to raise
goods output relative to manufacturing
production. Second, there is evidence
that the service component of all goods
output— domestic as well as import—
has risen over time.
In the cyclical time frame, however, a
somewhat different dynamic is at work.
In most recessions and recovery cycles,
capital goods production and sales are
more volatile than consumer-oriented
output and sales. Such was very much
the case in the 2001 recession: capital
goods spending fell 8.4 percent from the
first to last quarters of 2001 w hile
consumer spending actually increased.
Given the differential in the service
content o f these sales categ o ries—
co n su m er goods in co rp o rate m ore
service content than capital goods— it
fo llo w s th a t g o o d s o u tp u t, w hich
includes post-factory services would
tra c e a d iffe re n t c o u rse th an
m a n u fa c tu rin g p ro d u c tio n , w hich
excludes post-factory services.
Steindel concludes that where some
h av e seen the c u rre n t d iv e rg e n c e
between these two measures during the
2001 re c e s s io n as u n u su a l, w h at
actually was different was the relatively
close tracking between the two series
in 1990-91. That recession was marked
by an a ty p ic a lly la rg e sw in g in
consumer spending relative to capital
goods spending.
□

A visual essay:
Post-recession trends
in nonfarm employment
and related economic indicators
D a v i d L a n g d o n , R a c h e l K r a n t z , a n d M i c h a e l S tr o p le

•

Real GDP

•

Corporate profits

•

Unemployment Insurance (UI) claims

•

The help-wanted index

•

Manpower Inc.'s employment outlook survey

•

Consumer confidence (appraisal of current employment conditions)

•

Federal income tax withholdings

David Langdon is a supervisory economist and Michael Strople is an economist in the Division of Current
Employment Statistics, Bureau of Labor Statistics. Rachel Krantz is an economist in the Division of Labor
Force Statistics, Bureau of Labor Statistics.
E-mail:
Langdon.David@bls.gov
Strople.Michael@bls.gov
Krantz.Rachel@bls.gov


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Federal Reserve Bank of St. Louis

Monthly Labor Review

September 2004

49

A Visual Essay

he econom y entered a recovery in Novem ber 2001 follow ing an 8-month recession, but the labormarket recovery began much later. Gross dom estic product ( g d p ) and corporate profits had surged
before payroll employm ent reached its August 2003 trough. Em ployment edged up by about 60,000
a month during the remainder o f the year. Gains averaged about 225,000 a month during the first
months o f 2004 before slow ing in the summer. The post-recession disconnect between overall econom ic
growth and the labor market was unusual. The follow ing analysis review s this apparent inconsistency,
and also identifies a number o f other broad labor-market indicators that paralleled the lagged recovery in
payroll em ploym ent. Em ploym ent data used in this essay are from the Current Em ploym ent Statistics
( ces ) survey, a m onthly survey o f about 160,000 businesses and government agencies, which represent
approximately 400,000 individual worksites. For more information on the ces , see bls H a n d b o o k o f

T

M e th o d s ,

chapter

2, on

the Internet at

http://www.bls.gov/ces
Real gdp

During and following the recessions o f the
early 1980s, the employment trend gener­
ally coincided with the trend in real g d p . In
contrast, sustained employment growth
lagged g d p growth by four quarters after the
1990-91 recession and by eight quarters af­
ter the 2001 recession. Overall, the down­
turn in employment associated with the 2001
recession was more prolonged than those as­
sociated with the recessions of the 1980s and
1990-91. (The National Bureau of Eco­
nomic Research, the official arbiter of re­
cessions, has designated these periods as re­
cessions: January-July 1980, July 1981-No­
vember 1982, July 1990-March 1991, and
March-November 2001.)

1.

Percent change in real gross domestic product and quarterly change in
total nonfarm employment, seasonally adjusted

Quarterly
employment change
(in thousands)

GDP annualized
percent change

15

10

The 1990-91 and 2001 recessions were
milder in terms of contracting g d p than those
of the early 1980s. During the 1981-82 re­
cession, employment contracted by 3 per­
cent, compared with a mild 1 percent during
the other three recessions since 1979.

--5

-10

SOURCES: Bureau of Economic Analysis and BLS.

50

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September 2004

5

Corporate profits
Historically, private employment and real
corporate profits behave similarly at the
end o f a recession. Both reach a trough as
the rec e ssio n ends and then recover
quickly. At the end o f the 1990-91 reces­
sion, both profits and employment contin­
ued to move in parallel, but were lagged in
their recovery. The parallels broke down
with the 2001 recession.

2.

After-tax profits in constant (2000) dollars and quarterly averages of
total private employment, seasonally adjusted
Corporate profits
(in billions)
$ 1,200

Employment
(in thousands)
120,000

110,000
1,000
100,000
90.000

Leading into the 2001 recession, growth of
corporate profits stalled and then exhibited
a relatively sharp and deep decline. Em­
ployment declined as well during the re­
cession, but not as drastically as corporate
profits. Since reaching a trough in the third
quarter of 2001, corporate profits have in­
creased by 56 percent. Employment, on the
other hand, rem ained e sse n tia lly un­
changed until late 2003. Rising productiv­
ity explains, at least in part, the divergence
in profits and employment.

800

80.000
mploymentl

70.000

600

60.000
400

Profits

50.000
40.000

200

30.000
20.000

I ■ ,L

1948 52

56

60

64

68

72

76

80

I
84

I 1 I
88 92

I____ L
96 2000 04

NOTE: Corporate profits were deflated using the Implicit price deflator for GDP, 2000 100. Shaded areas denote recessions.
SOURCES: Bureau of Economic Analysis and BLS.

Corporate profits declined substantially
from the first to fourth quarter o f 2001 and
then recovered quickly. A large part of this
swing is tied to the financial situation of
three industry groups: information technol­
ogy (iT)-related manufacturing, information
industries, and transportation, (n-related
manufacturers produce information tech­
nology products. They are classified in
computers and electronic products manu­
facturing [naics 334].) iT-related manufac­
turing and information industries felt the
impact of the bursting technology bubble,
whereas transportation was affected in part
by the aftermath of the September 11th ter­
rorist attacks. Corporate profits excluding
those industries were much less volatile and
much more in keeping with prior reces­
sions.


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3.

Total domestic pre-tax profits and total excluding computer and elec­
tronic products, information, and transportation and warehousing
Billions

Billions

$750

$750

700

Domestic corporate profits,
excluding selected industries

700 -

650 -

650

600 -

600

550

550 Domestic corporate profits with in­
ventory valuation adjustment

500

500 -

450

II
2001

III

IV

II
2002

III

IV

II
2003

III

IV

I

450

2004

SOURCES: Bureau of Economic Analysis and authors' calculations.

Monthly Labor Review

September 2004

51

A Visual Essay

Corporate profits
The difficult financial situation in com ­
puter and electronic products, information,
and transportation and warehousing re­
sulted in cost-cutting initiatives that in­
cluded numerous layoffs. As a percentage
o f private employment, these three indus­
tries accounted for approximately 9 percent
o f employment in the first quarter o f 2001 ;
however, they accounted for approximately
41 percent o f declines in private industry
employment through the third quarter of
2003.

4.

Quarterly employment changes in total private industries and total
private excluding selected industries, seasonally adjusted

Thousands

Thousands

1,000

1,000

800

800

600

600

400

400

200

200

0

0

EPLH^I

-200

-2 0 0

-400

-400

-600

□ Total private
I I Total private excluding
selected industries'

-800
-

1,000

-

1,200

II
2001

III

IV

I

II

III

2002

IV

I

II
2003

III

IV

I

-600
-800
-

1,000

-

1,200

II

2004

' Excludes computers and electronic products, information, and transportation and
warehousing.
SOURCES: BLS and authors' calculations.

The third quarter of 1997 showed a distinct
increase in labor costs per unit of real gross
value added, which coincided with falling
profits; this trend continued until the third
quarter of 2001. (These measures are pro­
duced by the Bureau of Economic Analysis.)
Over this timeframe, labor costs increased by
7 cents, while profits declined by 5 cents per
unit of value added. The rising labor costs co­
incided with strong private employment
growth, an average of 447,000 jobs a quarter.
This apparent tradeoff reversed itself in the
fourth quarter of 2001. Unit profits began to
increase, and unit labor costs decreased.
From the third quarter of 2001 to the third
quarter of 2003, profits per unit increased by
3 cents, while unit labor costs decreased by
2 cents. Private employment averaged de­
clines of 288,000 per quarter over the same
timeframe. This drop in unit labor costs is
unusual, but is a way for firms to return to
profit when their pricing power is weak.
Price per unit of value added was flat be­
tween 2001 and 2003, so in order to increase
profits, businesses cut costs, including the re­
duction of labor costs through layoffs.

52

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5. After-tax profits and labor costs per unit of real gross value added of
nonfinancial domestic corporate business, seasonally adjusted
Labor
costs

Profits

NOTE: Profits are after taxes, inventory valuation adjustment, and capital consumption adjust­
ment. The series are deflated such that the price of one unit of gross value added in 2000 equals $1.
SOURCE: Bureau of Economic Analysis.

September 2004

Unemployment Insurance (ui) claims
Initial ui claims and the over-the-month
change o f total nonfarm employment mea­
sure the flow o f workers. The former mea­
sures the flow o f laid-off workers claiming
unemployment insurance compensation for
the first week following a layoff. The latter
measures the net flow of jobs onto payrolls.
Not surprisingly, these flows are negatively
correlated.
After the 2001 recession, initial ui claims
hovered around 400,000 monthly, a some­
what lower level than during prior reces­
sions. Claims did not fall and remain be­
low 400,000 until the fourth quarter of
2003, coinciding with the return to growth
in total nonfarm employment.

Monthly average of initial UI claims and monthly changes in total non­
farm employment, seasonally adjusted

6.

Over-the-month
employment changes
(in thousands)

Number of
claims, inverse
sca'e
1 U U .U U U

750
Total nonfarm over-the-month change

200,000

/

500

250

300.000

0

400.000

-2 5 0

500.000

600.000

-5 0 0
Initial claims
i

-7 5 0
1980

82

84

l____

86

88

i

l

l

I

I

90

92

94

96

98

I_____L

2000

02

700.000
04

NOTE: The August and September 1983 over-the-month changes, -300,000 and +1.1 million,
reflect a strike of 640,000 workers and their subsequent return.
SOURCES: DOL Employment and Training Administration and BLS.

The labor market’s post-recovery stagna­
tion is particularly evident in the continu­
ing claims series. Like total nonfarm em­
ployment, continuing claims have tended
to reach a turning point at the end o f a re­
cession, with employment then rising and
claim s declining. The pattern changed
somewhat in the 1990-91 recession, as the
drop in claims stalled between m id-1991
and m id-1992.

7.

Monthly average of continuing UI claims and total nonfarm employment,
seasonally adjusted

Number o f
claims

Employment (in
thousands)

140,000

120,000

At the end o f the 2001 recession, continu­
ing claims reached 3.67 million, a plateau
that extended through m id-2003. They
did not decline steadily until September
2003, follow ing the August trough in to­
tal nonfarm employment.


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100,000

80,000

60,000

NOTE: Shaded areas denote recessions.
SOURCES: DOL Employment and Training Administration and BLS.

Monthly Labor Review

September 2004

53

A Visual Essay

The help-wanted index
The help-wanted index measures monthly
help-wanted advertising volume in 51 ma­
jor newspapers across the United States.
During the recessions o f 1980, 1981-82,
and 1990-91, a downturn in help-wanted
advertising corresponded with job losses;
conversely, an upturn in help-wanted ad­
vertising coincided with job gains. News­
paper job advertising began its most recent
decline in 2000 and remained weak through
2003. Nonfarm payroll employment fell
from early 2001 until late 2003.
Interestingly, the magnitude o f decline in
help-wanted advertising around the 2001
recession was more severe than the declines
o f the early 1980s and 1990s. In recent
years, Internet-based job postings have be­
come a popular method for employers to
advertise job openings; some employers
may substitute w eb-based postings for
newspaper advertising. The shape o f the
help-wanted index indicates that newspa­
per job advertising notched up in early
2004, after showing little change in 2003.
This small uptick coincided with strong
gains in total nonfarm employment.

Manpower Inc.'s net employment outlook
measures the difference between the percent
o f employers expecting to add jobs and
those expecting to shed them. Curiously, in
only one quarter since 1977 were there more
firms planning to decrease their staffing lev­
els than firms planning to increase them.

8.

The help-wanted index and monthly changes in total nonfarm employ­
ment, seasonally adjusted

Over-the-month
employment changes
(in thousands)

-6 0 0 U --------1--------1--------1------1--------- 1------1------- 1-------- 1------- 1----------1--------1--------1__ 0
1980 82
84
86
88
90
92
94
96
98 2000 02
04
NOTE: The August and September 1983 over-the-month changes, -300,000 and +1.1 million,
reflect a strike of 640,000 workers and their subsequent return.
SOURCES: The Conference Board and BLS.

Manpower Inc. employment outlook survey
9.

Net employment outlook and quarterly changes in total nonfarm
employment, seasonally adjusted

Quarterly employment

Trends in the net employment outlook cor­
relate highly with quarterly changes in to­
tal nonfarm employment. A one-quarter lag
in the employment outlook shows an even
higher correlation. Not surprisingly, em­
ployers may develop their outlook for the
upcoming quarter by looking at the one that
has just ended.
Like total nonfarm em ploym ent, Man­
power Inc.'s employment outlook behaved
unusually after the 2001 recession. A l­
though the outlook brightened somewhat
in 2002, corresponding with relatively
smaller declines in nonfarm employment,
it dimmed again in 2003. At the end o f the
year and into early 2004, the outlook
showed greater improvement, and total
nonfarm employment began to recover.

54

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Helpwanted
index

SOURCE:

September 2004

Manpower Inc. and BLS.

Net employment outlook

Consumer confidence (appraisal of current employment conditions)
As part of the Conference Board’s monthly
survey of Consumer confidence, respon­
dents evaluate current employment condi­
tions, judging jobs as either “plentiful,”
“not so plentiful,” or “hard to get.” Focus­
ing just on those who see “plenty” of jobs,
it is clear that the most recent economic re­
covery was not accompanied by an imme­
diate improvement in the labor market. The
proportion of respondents finding jobs
plentiful recovered somewhat at the end of
the 2001 recession, only to decline again
during 2002 and through most of 2003.
During the final months of 2003, it began
to rise, coinciding with the first months of
steady, though slow, growth in total non­
farm employment. It is worth remember­
ing that b l s data may condition the public’s
perception of labor market conditions, es­
pecially in the case of people who are not
actively looking, or know anyone actively
looking, for work.

10.

’’Jobs plentiful" and monthly changes in total nonfarm employment,
seasonally adjusted

Over-the-month employment
change (in thousands)

Percent
60

50

40

30

-

20

-

10

NOTE: The August and September 1983 over-the-month changes, -300,000 and +1.1 million,
reflect a strike of 640,000 workers and their subsequent return.
SOURCE:

A broader measure of consumer confidence
in the labor market would take into account
all people, not just those who see "plenty"
of jobs. Such a measure—a pseudo-diffu­
sion index—can be calculated by weight­
ing the proportion of people who respond
“plentiful” as 100, “not so plentiful” as 50,
and “hard to get” as 0, and summing the
results. This index highlights the growing
lag between the end of recessions and the
related labor market recovery. In 1982,
consumers noted a 1-month lag. After the
1990-91 recession came an 11-month lag,
followed by a somewhat fitful recovery;
consumers did not identify sustained labor
market improvement until mid-1992. The
lag following the 2001 recession was 22
months, as the diffusion index bottomed out
in September 2003. This pattern parallels
that seen in c e s data; employment hit a low
in August 2003.


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11.

Conference Board and BLS.

Net appraisal of current employment conditions and monthly changes
in total nonfarm employment, seasonally adjusted
Diffusion
index

Over-the-month employment
change (in thousands)

80

70

60

50

40

30

20
NOTE: The August and September 1983 over-the-month changes, -300,000 and +1.1 million,
reflect a strike of 640,000 workers and their subsequent return.
SOURCE: Conference Board, BLS, and authors' calculations.

Monthly Labor Review

September 2004

55

A Visual Essay

Income tax withholdings
Federal income tax withholdings and non­
farm employment had similar trends during
the last two recessions. Both employment
and withholdings peaked as the recessions
began and reached low points after the re­
cessions had ended. After the 1990-91 re­
cession, there were no substantive job gains
until the second quarter o f 1992, coincident
w ith a return to growth in incom e tax
withholdings. There are not yet sufficient
data to compare turning points in withhold­
ings and employment for the period after the
2001 recession, although both data series
declined through the third quarter o f 2003
and have since regained some of their re­
cession-related losses. Income tax cuts en­
acted in 2001 and 2003 are also a factor in
the recent decline in withholdings.

12.

Federal income tax withholdings and quarterly total nonfarm employ­
ment, seasonally adjusted
Tax with­
holdings (in
billions)
---------1$900

Employment (in
thousands)
140,000

130,000

800
Nonfarm
employment

120,000

700

1
110,000

600
Income tax
withholdings

100,000

500

-

1

90,000
1988

90

92

94

96

98

2000

02

04

400

NOTE: Quarterly withholdings data are not available for years prior to 1988. Federal personal
income tax withholdings were deflated using BEA's price index for Federal consumption expendi­
tures and gross investment (2000 = 100). Shaded areas denote recessions.
SOURCES:

5Ó

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Bureau of Economic Analysis, BLS, and authors' calculations.

Book Review

Parenthood and employment
Families that Work: Policies for Rec­
onciling Parenthood and Employ­
ment. By Janet C. Gomick and Marcia
K. Meyers. New York, Russell Sage
Foundation, 2003, 392 pp., $39.95/
hardcover; $28/softcover.
“American families are struggling with
a shared dilem m a: if everyone is at
the w orkplace, who will care for the
children?”
That is how Janet C. G ornick and
M arcia K. M eyers begin their sum ­
m ing up, and that dilem m a— created
by the decline o f the m ale-breadw in­
ner m odel o f fam ily organization and
the steady rise in the labor force par­
ticipation of women, particularly moth­
ers of young children— is the central
issue that they address in their com ­
prehensive work.
The question is not unique to the
U nited States. The same thing has oc­
curred, to varying degrees, through­
out the advanced in d u strial w orld.
B ecause o f the w idespread nature of
the phenom enon, a variety o f trails
have been blazed by a number of coun­
tries in reconciling the em ploym ent of
mothers with family life.
M ost o f the em pirical analysis in
this book is cross-national. G ornick
and M eyers compare 11 countries with
the U nited States, organized into three
fairly hom ogeneous groups: the four
Nordic countries of Denmark, Finland,
Norway, and Sweden; five other coun­
tries in Northern Continental Europe—
Belgium , France, Germ any, L uxem ­
bourg, and the N etherlands; and two
m ainly E nglish-speaking countries—
the U n ite d K in g d o m and C an ad a.
Countries in the groups vary widely
in their fam ily policies. Those of the
Nordic countries are the m ost gener­
ous and egalitarian. The Continental
countries, while liberal in their welfare
m easures, are m ore conservative with
respect to traditional gender roles and
a d h e re n c e to m a rk e t p r in c ip le s .


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C anada, and to a lesser extent the
U nited Kingdom , m ost resem bles the
United States in that m arket principles
remain dominant and family assistance
is heavily needs-based.
The authors begin with a variety of
w ell-docum ented indicators of family
w ell-being. Among the indicators are
m easures of the rate of family poverty,
incidence of low birth weight, m ortal­
ity rates am ong infants and young
c h ild re n , teenage p reg n an cies and
abortions, and eighth-grade achieve­
m ent test scores in science and m ath­
em atics. With the exception of math
achievem ent, where the U.K. eighth
graders do worse, the U nited States is
at the bottom in all the m easures, usu­
ally follow ed by the other Englishspeaking countries.
Even though the N ordic countries
have the highest em ploym ent rate of
m others— though not in total paren­
tal tim e spent at work, which is great­
est in the U nited States— they fare
best in m ost of these measures of fam ­
ily w ell-being. That should not be a
surprise, suggest the authors, because
they have also been the most success­
ful in creating “dual-earner-dual-carer
societies” with their “fam ily-friendly”
labor and childcare policies.
Only a passing nod is given to the
possibility that other factors such as
dem o g rap hic ch a ra c teristic s, labor
m arket structures, and cultural factors
may also be important in explaining the
different outcomes. If family friendli­
ness of policies, as they m easure it, is
so crucial, then why does the U nited
States, on the bottom of their scale,
continue to have a higher fertility rate
than the E uropean countries? Few
social outcomes could be more directly
related to the family friendliness of the
social environm ent than the choice to
have a child.
The authors are unabashed advo­
cates of European-style family policies
for the United States, a fact that might
color their interpretation of the data.
In a chapter addressing objections to

adopting E uropean fam ily policies,
they suggest that great increases in
non-m arital childbearing in Europe,
ad m itted ly fa c ilita te d by g enerous
social program s there, are not porten­
tous for the U nited S tates because
“the m ajority of unm arried parents in
most European countries are in stable,
cohabiting relationships.” T hat may
be tru e, b u t the fact re m a in s th a t
single-parent households, strictly de­
fined, are very m uch on the rise in
Europe. W hen 55 percent of all live
births are to unm arried women, as was
the case in Sweden in 2000, there is
more than enough room for m any of
those births to be to wom en w ithout
partners or to w om en in less-thanstable relationships. Sw eden’s single­
parent households make up 23 percent
of all households with children. E u­
ropean proportions of single-parent
households rem ain low er than in the
U nited States, but the differential is
closing. (See Gary Martin and Vladimir
Kats, “Fam ilies and work in transition
in 12 countries, 1980-200
Monthly
Labor Review, Septem ber 2003, tables
4 and 6.)
This study is perhaps m ost valu­
able for its extensive up-to-date tabu­
lations, by country, of fam ily-related
practices and policies. The tabula­
tions are draw n from an im pressive
array o f national and in tern atio n al
sources. Readers learn that paid mate r n ity /p a r e n ta l le a v e in E u ro p e
ranges from 14 weeks in G erm any to
52 weeks in Sweden, and that replace­
m ent of m ost or all wages is com m on­
place. In the U nited States, only five
States have any form of paid m ater­
nity leave at all. All of the European
countries have maximum weekly hours
of work, ranging from 39 to 48. The
U nited States and C anada have no
such restriction. In every one of the
European countries a m inim um num ­
ber of vacation days are prescribed by
law. These m inim um s range from 20
to 25. The U nited States has no policy
of required vacations, and the aver-

Monthly Labor Review

September 2004

57

Book Reviews

age num ber in practice is m uch less
than 20. Early childhood education
and care is provided by the govern­
ment in all o f the Continental European
countries, and providers of the service
are generally well paid and standards
are high. In the U nited States, such
services are generally private and ex­
pensive; the providers are relatively

poorly paid; and standards are highly
variable.
M ore than a book of advocacy, this
is a prodigious work of scholarship in
a grow ing and important interdiscipli­
nary field. O f the 413 references, 198
are to works published in 2000 or later,
9 o f which are forthcom ing. With the
breakup of the Soviet Union, the study

of com parative economic system s has
been on the decline. Studies such as
these, which compare different aspects
o f m ainly free-m ark et eco n o m ies,
could breathe new life into the field.
— Gary Martin
Office of Productivity and Technology,
Bureau of Labor Statistics

Where are you publishing your research?
The Monthly Labor Review will consider for publication studies of the labor force,
labor-management relations, business conditions, industry productivity, compensa­
tion, occupational safety and health, demographic trends, and other economic
developments. Papers should be factual and analytical, not polemical in tone.
We prefer (but do not require) submission in the form of an electronic file in
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Potential articles should be mailed to: Editor-in-Chief, Monthly Labor Review,
Bureau of Labor Statistics, Washington, DC 20212, or by e-mail to mlr@bls.gov

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September 2004

Current Labor Statistics

Notes on labor statistics .................. 6o

Labor compensation and collective
bargaining data

Comparative indicators

30.
31.
32.
33.

1. Labor market indicators.........................................................
2. Annual and quarterly percent changes in
compensation, prices, andproductivity..........................
3. Alternative measures of wages and
compensation changes........................................................

73
74
74

Employment Cost Index, compensation................................
Employment Cost Index, wages and salaries......................
Employment Cost Index, benefits, private industry........
Employment Cost Index, private nonfarm workers,
by bargaining status, region, and area s i z e ......................
34. Participants in benefit plans, medium and large firm s......
35. Participants in benefits plans, small firms
and government....................................................................
36. Work stoppages involving 1,000 workers or m o r e...........

102
104
105
106
107
108
109

Labor force data
4. Employment status o f the population,
seasonally adjusted.............................................................
5. Selected employment indicators,
seasonally adjusted.............................................................
6. Selected unemployment indicators,
seasonally adjusted.............................................................
7. Duration of unemployment,
seasonally adjusted.............................................................
8. Unemployed persons by reason for unemployment,
seasonally adjusted.............................................................
9. Unemployment rates by sex and age,
seasonally adjusted.............................................................
10. Unemployment rates by States,
seasonally adjusted.............................................................
11. Employment of workers by States,
seasonally adjusted.............................................................
12. Employment o f workers by industry,
seasonally adjusted.............................................................
13. Average weekly hours by industry,
seasonally adjusted.............................................................
14. Average hourly earnings by industry,
seasonally adjusted..............................................................
15. Average hourly earnings by industry...................................
16. Average weekly earnings by industry..................................
17. Diffusion indexes o f employment change,
seasonally adjusted.............................................................
18. Job openings levels and rates, by industry and regions,
seasonally adjusted...............................................................
19. Hires levels and rates by industry and region,
seasonally adjusted................................................................
20. Separations levels and rates by industry and region,
seasonally adjusted................................................................
21. Quits levels and rates by industry and region,
seasonally adjusted................................................................
22. Quarterly Census of Employment and Wages.
10 largest counties...............................................................
23. Quarterly Census o f Employment and Wages,by State ..
24. Annual data: Quarterly Census of Employment
and Wages, by ow nership.................................................
25. Annual data: Quarterly Census of Employment and Wages,
establishment size and employment, by supersector ...
26. Annual data: Quarterly Census o f Employment and
Wages, by metropolitan area.............................................
27. Annual data: Employment status o f the population........
28. Annual data: Employment levels by industry...................
29. Annual data: Average hours and earnings level,
by industry...........................................................................


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Price data
75
76
77
77
78
78
79
79
80
83
84
85
86
87
88
88

37. Consumer Price Index: U.S. city average, by expenditure
category and commodity and service groups.................
38. Consumer Price Index: U.S. city average and
local data, all item s..............................................................
39. Annual data: Consumer Price Index, all items
and major groups.................................................................
40. Producer Price Indexes by stage o f processing..................
41. Producer Price Indexes for the net output o f major
industry groups....................................................................
42. Annual data: Producer Price Indexes
by stage o f processing........................................................
43. U.S. export price indexes by Standard International
Trade Classification............................................................
44. U.S. import price indexes by Standard International
Trade Classification............................................................
45. U.S. export price indexes by end-use category..................
46. U.S. import price indexes by end-use category.................
47. U.S. international price indexes for selected
categories o f services...........................................................

110
113
114
115
116
117
118
119
120
121
121

Productivity data
48. Indexes of productivity, hourly compensation,
and unit costs, data seasonally adjusted.........................
49. Annual indexes o f multifactor productivity........................
50. Annual indexes o f productivity, hourly compensation,
unit costs, and p rices.........................................................
51. Annual indexes of output per hour for select
industries...............................................................................

122
123
124
125

89
89
90
92
93
94
95
100
100
101

International comparisons data
52. Unemployment rates in nine countries,
data seasonally adjusted..................................................... 128
53. Annual data: Employment status o f the civilian
working-age population, 10 countries............................... 129
54. Annual indexes o f productivity and related measures,
12 countries.......................................................................... 130

Injury and Illness data
55. Annual data: Occupational injury and illness
incidence rates........................................................................ 131
56. Fatal occupational injuries by event or exposure............... 133

Monthly Labor Review September 2004

59

Notes on Current Labor Statistics

This section of the R e v ie w presents the prin­
cipal statistical series collected and calcu­
lated by the Bureau o f Labor Statistics:
series on labor force; employment; unem­
ployment; labor compensation; consumer,
producer, and international prices; produc­
tivity; international comparisons; and injury
and illness statistics. In the notes that fol­
low, the data in each group o f tables are
briefly described; key definitions are given;
notes on the data are set forth; and sources
o f additional information are cited.

General notes
The following notes apply to several tables
in this section:
Seasonal adjustm ent. Certain monthly
and quarterly data are adjusted to eliminate
the effect on the data of such factors as cli­
m atic co n d itio n s, industry production
schedules, opening and closing o f schools,
holiday buying periods, and vacation prac­
tices, which might prevent short-term evalu­
ation of the statistical series. Tables contain­
ing data that have been adjusted are identi­
fied as “seasonally adjusted.” (All other
data are not seasonally adjusted.) Seasonal
effects are estimated on the basis o f current
and past experiences. When new seasonal
factors are computed each year, revisions
may affect seasonally adjusted data for sev­
eral preceding years.
Seasonally adjusted data appear in tables
1-14, 17-21, 48, and 52. Seasonally ad­
justed labor force data in tables 1 and 4 -9
were revised in the February 2004 issue o f
the R e v ie w . Seasonally adjusted establish­
ment survey data shown in tables 1, 12-14,
and 17 were revised in the March 2004 R e ­
view . A brief explanation o f the seasonal
adjustment methodology appears in “Notes
on the data.”
R evisions in the productivity data in
table 54 are usually introduced in the Sep­
tember issue. Seasonally adjusted indexes
and percent changes from month-to-month
and quarter-to-quarter are published for nu­
merous Consumer and Producer Price In­
dex series. However, seasonally adjusted in­
dexes are not published for the U.S. aver­
age All-Items CPI. Only seasonally adjusted
percent changes are available for this series.
A djustm ents for price changes. Some
data— such as the “real” earnings shown in
table 1A— are adjusted to eliminate the ef­
fect o f changes in price. These adjustments
are made by dividing current-dollar values
by the Consumer Price Index or the appro­
priate component of the index, then multi­
plying by 100. For example, given a current
hourly wage rate o f $3 and a current price

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index number o f 150, where 1982 = 100,
the hourly rate expressed in 1982 dollars is
$2 ($3/150 x 100 = $2). The $2 (or any other
resulting values) are described as “real,”
“constant,” or “ 1982” dollars.

tional comparisons data, see In te rn a tio n a l
C o m p a r is o n s o f U n e m p lo y m e n t, Bulletin
1979.
Detailed data on the occupational injury
and illness series are published in O c c u p a ­

Sources of information

tio n a l In ju rie s a n d Illn e s s e s in th e U n ite d
S ta tes, b y In d u stry, a bls annual bulletin.
Finally, the M o n th ly L a b o r R e v ie w car­

Data that supplement the tables in this sec­
tion are published by the Bureau in a vari­
ety o f sources. Definitions of each series and
notes on the data are contained in later sec­
tions o f these Notes describing each set of
data. For detailed descriptions o f each data
series, see b l s H a n d b o o k o f M e th o d s, Bul­
letin 2490. Users also may wish to consult
M a jo r P ro g ra m s o f th e B u reau o f L a b o r S ta ­
tis tic s , Report 919. News releases provide

the latest statistical information published
by the Bureau; the major recurring releases
are published according to the schedule ap­
pearing on the back cover o f this issue.
More information about labor force, em­
ployment, and unemployment data and the
household and establishment surveys under­
lying the data are available in the Bureau’s
m onthly publication, E m p lo y m e n t a n d
E a rn in g s. Historical unadjusted and season­
ally adjusted data from the household sur­
vey are available on the Internet:
http ://www.b!s.gov/cpsi/
Historically comparable unadjusted and sea­
sonally adjusted data from the establishment
survey also are available on the Internet:
http ://w ww.bls.gov/ces/
Additional information on labor force data
for areas below the national level are pro­
vided in the BLS annual report, G e o g r a p h ic
P ro file o f E m p lo y m e n t a n d U n em p lo ym e n t.

For a comprehensive discussion o f the
Employment Cost Index, see E m p lo y m e n t
C o s t In d ex e s a n d L e v e ls, 1 9 7 5 - 9 5 , BLS Bul­
letin 2466. The most recent data from the
Employee Benefits Survey appear in the fol­
lowing Bureau o f Labor Statistics bulletins:
E m p lo y e e B e n e fits in M e d iu m a n d L a rg e
F irm s; E m p lo y e e B e n e fits in S m a ll P r iv a te
E s ta b lis h m e n ts; and E m p lo y e e B e n e fits in
S ta te a n d L o c a l G o v ern m e n ts.

More detailed data on consumer and pro­
ducer prices are published in the monthly
periodicals, T h e c p i D e ta ile d R e p o r t and
P r o d u c e r P r ic e In d ex es. For an overview of
the 1998 revision o f the CPI, see the Decem­
ber 1996 issue of the M o n th ly L a b o r R e ­
v ie w . Additional data on international prices
appear in monthly news releases.
Listings o f industries for which produc­
tivity indexes are available may be found
on the Internet:
http ://w w w.bls.gov/lpc/
For additional information on interna­

September 2004

ries analytical articles on annual and longer
term developments in labor force, employ­
ment, and unemployment; employee com­
pensation and collective bargaining; prices;
productivity; international comparisons;
and injury and illness data.

Symbols
n.e.c. = not elsewhere classified,
n.e.s. = not elsewhere specified.
p = preliminary. To increase the time­
liness o f some series, preliminary
figures are issued based on repre­
sentative but incomplete returns.
r = revised. Generally, this revision
reflects the availability o f later
data, but also may reflect other
adjustments.

C om parative Indicators
(Tables 1-3)
Comparative indicators tables provide an
overview and comparison o f major bls sta­
tistical series. Consequently, although many
o f the included series are available monthly,
all measures in these comparative tables are
presented quarterly and annually.
Labor m arket indicators include em­
ployment measures from two major surveys
and information on rates o f change in com ­
pensation provided by the Employm ent
Cost Index (ECi) program. The labor force
participation rate, the employment-popula­
tion ratio, and unemployment rates for ma­
jor demographic groups based on the Cur­
rent Population (“household”) Survey are
presented, while measures o f employment
and average weekly hours by major indus­
try sector are given using nonfarm payroll
data. The Employment Cost Index (compen­
sation), by major sector and by bargaining
status, is chosen from a variety o f bls
compensation and wage measures because
it provides a comprehensive measure o f
employer costs for hiring labor, not just
outlays for wages, and it is not affected
by em ployment shifts among occupations
and industries.
Data on ch a n g e s in c o m p en sa tio n ,
prices, and productivity are presented in

table 2. Measures o f rates o f change of com­
pensation and wages from the Employment
Cost Index program are provided for all ci­
vilian nonfarm workers (excluding Federal
and household workers) and for all private
nonfarm workers. Measures o f changes in
consumer prices for all urban consumers;
producer prices by stage o f processing; over­
all prices by stage o f processing; and over­
all export and import price indexes are
given. Measures o f productivity (output per
hour o f all persons) are provided for major
sectors.
A ltern a tiv e m easu res o f w age and
com pensation rates o f change, which re­
flect the overall trend in labor costs, are sum­
marized in table 3. Differences in concepts
and scope, related to the specific purposes
of the series, contribute to the variation in
changes among the individual measures.

Notes on the data
Definitions o f each series and notes on the
data are contained in later sections o f these
notes describing each set of data.

Employment and
Unemploym ent Data
(Tables 1; 4-29)

Household survey data

not work during the survey week, but were
available for work except for temporary ill­
ness and had looked for jobs within the pre­
ceding 4 weeks. Persons who did not look
for work because they were on layoff are also
counted among the unemployed. The unem­
ploym ent rate represents the number unem­
ployed as a percent of the civilian labor force.
The civilian labor force consists o f all
employed or unemployed persons in the ci­
vilian noninstitutional population. Persons
not in the labor force are those not classi­
fied as employed or unemployed. This group
includes discouraged workers, defined as
persons who want and are available for a
job and who have looked for work some­
time in the past 12 months (or since the end
o f their last job if they held one within the
past 12 months), but are not currently look­
ing, because they believe there are no jobs
available or there are none for which they
would qualify. The civilian n o n in stitu ­
tional population comprises all persons 16
years o f age and older who are not inmates
o f penal or mental institutions, sanitariums,
or homes for the aged, infirm, or needy. The
civilian labor force p articipation rate is
the proportion o f the c iv ilia n n o n in ­
stitutional population that is in the labor
force. The employment-population ratio is
employment as a percent o f the civilian
noninstitutional population.

Notes on the data

Description of the series
Employment data in this section are ob­
tained from the Current Population Survey,
a program o f personal interviews conducted
monthly by the Bureau of the Census for the
Bureau of Labor Statistics. The sample con­
sists of about 60,000 households selected to
represent the U.S. population 16 years of
age and older. Households are interviewed
on a rotating basis, so that three-fourths of
the sample is the same for any 2 consecu­
tive months.

Definitions
E m ployed persons include (1) all those
who worked for pay any time during the
week which includes the 12th day o f the
month or who worked unpaid for 15 hours
or more in a family-operated enterprise and
(2) those who were temporarily absent from
their regular jobs because o f illness, vaca­
tion, industrial dispute, or similar reasons.
A person working at more than one job is
counted only in the job at which he or she
worked the greatest number o f hours.
Unem ployed persons are those who did


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From time to time, and especially after a de­
cennial census, adjustments are made in the
Current Population Survey figures to cor­
rect for estim a tin g errors during the
intercensal years. These adjustments affect
the comparability o f historical data. A de­
scription o f these adjustments and their ef­
fect on the various data series appears in the
Explanatory N otes o f E m p lo y m e n t a n d
E a rn in g s. For a discussion of changes in­
troduced in January 2003, see “Revisions
to the Current Population Survey Effective
in January 2003” in the February 2003 is­
sue of E m p lo y m en t a n d E a rn in g s (available
on the bls Web site at: http://www.bls.gov/
cps/rvcps03.pdf).
Effective in January 2003, bls began us­
ing the X-12 arima seasonal adjustment pro­
gram to seasonally adjust national labor force
data. This program replaced the X-n arima
program which had been used since January
1980. See “Revision of Seasonally Adjusted
Labor Force Series in 2003,” in the Feb­
ruary 200 3 issu e o f E m p lo y m e n t a n d
E a r n in g s (available on the BLS Web site
at http:www .bls.gov/cps/cpsrs.pdf) for a
discussion of the introduction o f the use of

x - 12 arima for seasonal adjustment of the

labor force data and the effects that it had
on the data.
At the beginning o f each calendar year,
historical seasonally adjusted data usually
are revised, and projected seasonal adjust­
ment factors are calculated for use during
the January-June period. The historical sea­
sonally adjusted data usually are revised for
only the most recent 5 years. In July, new
seasonal adjustment factors, which incorpo­
rate the experience through June, are pro­
duced for the July-December period, but no
revisions are made in the historical data.
For additional information on na­
tional household survey data, contact the
Division of Labor Force Statistics: (202)
691-6378.

Establishment survey data
Description of the series
Employment, hours, and earnings data in
this section are com piled from payroll
records reported monthly on a voluntary ba­
sis to the Bureau o f Labor Statistics and its
co o p era tin g State a g e n c ie s by about
160.000 businesses and government agen­
c ie s , w h ich rep resen t ap p roxim ately
400.000 individual worksites and represent
all industries except agriculture. The active
CES sample covers approximately one-third
o f all nonfarm payroll workers. Industries
are classified in accordance with the 2002
North American Industry Classification Sys­
tem. In most industries, the sampling prob­
abilities are based on the size o f the estab­
lishment; m ost large establishm ents are
therefore in the sample. (An establishment
is not necessarily a firm; it may be a branch
plant, for example, or warehouse.) Self-em­
ployed persons and others not on a regular
civilian payroll are outside the scope o f the
survey because they are excluded from estab­
lishment records. This largely accounts for
the difference in employment figures between
the household and establishment surveys.

Definitions
An esta b lish m e n t is an econom ic unit
which produces goods or services (such as
a factory or store) at a single location and is
engaged in one type o f economic activity.
Em ployed persons are all persons who
received pay (including holiday and sick
pay) for any part o f the payroll period in­
cluding the 12th day o f the month. Persons
holding more than one job (about 5 percent
of all persons in the labor force) are counted

Monthly Labor Review September 2004

61

Current Labor Statistics

in each establishment which reports them.
Production w orkers in the goods-producing industries cover em p loyees, up
through the level of working supervisors,
who engage directly in the manufacture or
construction of the establishment’s product.
In private service-providing industries, data
are collected for nonsupervisory workers,
which include most employees except those
in executive, managerial, and supervisory
positions. Those workers mentioned in
tables 11-16 include production workers in
manufacturing and natural resources and
mining; construction workers in construc­
tion; and nonsupervisory workers in all pri­
vate service-providing industries. Produc­
tion and nonsupervisory workers account
for about four-fifths of the total employment
on private nonagricultural payrolls.
E arnings are the payments production
or nonsupervisory workers receive during
the survey period, including premium pay
for overtime or late-shift work but exclud­
ing irregular bonuses and other special
payments. R eal earnings are earnings ad­
justed to reflect the effects o f changes in
consumer prices. The deflator for this se­
ries is derived from the Consumer Price In­
dex for Urban Wage Earners and Clerical
Workers (CPI-W).
H ours represent the average weekly
hours o f production or nonsupervisory
workers for which pay was received, and are
different from standard or scheduled hours.
Overtim e hours represent the portion of av­
erage weekly hours which was in excess of
regular hours and for which overtime pre­
miums were paid.
The D iffusion Index represents the per­
cent of industries in which employment was
rising over the indicated period, plus onehalf o f the industries with unchanged em­
ployment; 50 percent indicates an equal bal­
ance between industries with increasing and
decreasing employment. In line with Bureau
practice, data for the 1-, 3-, and 6-month
spans are seasonally adjusted, while those
for the 12-month span are unadjusted. Table
17 provides an index on private nonfarm
employment based on 278 industries, and a
manufacturing index based on 84 industries.
These indexes are useful for measuring the
dispersion o f economic gains or losses and
are also economic indicators.

Notes on the data
Establishment survey data are annually ad­
justed to comprehensive counts of employ­
ment (called “benchmarks”). The March
2003 benchmark was introduced in Febru­
ary 2004 with the release o f data for Janu­
ary 2004, published in the March 2004 is­

62

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sue of the R e view . With the release in June
2003, CES completed a conversion from the
Standard Industrial Classification (SIC) sys­
tem to the North American Industry Classi­
fication System (n a ic s ) and completed the
transition from its original quota sample de­
sign to a probability-based sample design.
The industry-coding update included recon­
struction o f historical estimates in order to
preserve time series for data users. Nor­
mally 5 years o f seasonally adjusted data are
revised with each benchmark revision.
However, with this release, the entire new
time series history for all CES data series
were re-seasonally adjusted due to the NAICS
conversion, which resulted in the revision
o f all ces time series.
Also in June 2003, the ces program in­
troduced concurrent seasonal adjustment for
the national establishment data. Under this
methodology, the first preliminary estimates
for the current reference month and the re­
vised estimates for the 2 prior months will
be updated with concurrent factors with
each new release o f data. Concurrent sea­
sonal adjustment incorporates all available
data, including first preliminary estimates
for the most current month, in the adjustment
process. For additional information on all of
the changes introduced in June 2003, see the
June 2003 issue o f E m ploym en t a n d E arn in gs
and “Recent changes in the national Current
Employment Statistics survey,” M on th ly L a ­
b o r R eview , June 2003, pp. 3-13.
Revisions in State data (table 11) oc­
curred with the publication o f January 2003
data. For information on the revisions for
the State data, see the March and May 2003
issues o f E m p lo y m e n t a n d E a rn in g s, and
“Recent changes in the State and Metropoli­
tan Area CES survey,” M o n th ly L a b o r R e ­
v ie w , June 2003, pp. 14—19.
Beginning in June 1996, the bls uses the
X-12-a r im a methodology to seasonally ad­
just establishment survey data. This proce­
dure, developed by the Bureau of the Cen­
sus, controls for the effect o f varying sur­
vey intervals (also known as the 4- versus
5-week effect), thereby providing improved
measurement o f over-the-month changes
and underlying economic trends. Revisions
o f data, usually for the most recent 5-year
period, are made once a year coincident with
the benchmark revisions.
In the establishment survey, estimates for
the most recent 2 months are based on in­
complete returns and are published as pre­
liminary in the tables (12-17 in the R e view ).
When all returns have been received, the es­
timates are revised and published as “final”
(prior to any benchmark revisions) in the

September 2004

third month of their appearance. Thus, D e­
cember data are published as preliminary in
January and February and as final in March.
For the same reasons, quarterly establish­
ment data (table 1) are preliminary for the
first 2 months o f publication and final in the
third month. Fourth-quarter data are pub­
lished as preliminary in January and Febru­
ary and as final in March.
F o r a d d it io n a l in fo r m a t io n on estab­
lishment survey data, contact the Division
o f Current Employment Statistics: (202)
691-6555.

Unemployment data by
State
Description of the series
Data presented in this section are obtained
from the Local Area Unemployment Statis­
tics (LAUS) program, which is conducted in
cooperation with State employment security
agencies.
Monthly estimates o f the labor force,
employment, and unemployment for States
and sub-State areas are a key indicator of
local economic conditions, and form the ba­
sis for determining the eligibility o f an area
for benefits under Federal economic assis­
tance programs such as the Job Training
Partnership Act. Seasonally adjusted unem­
ployment rates are presented in table 10.
Insofar as possible, the concepts and defi­
nitions underlying these data are those
used in the national estim ates obtained
from the CPS.

Notes on the data
Data refer to State o f residence. Monthly
data for all States and the District o f Co­
lumbia are derived using standardized pro­
cedures established by BLS. Once a year,
estimates are revised to new population con­
trols, usually with publication o f January
estimates, and benchmarked to annual aver­
age cps levels.
F or a d d itio n a l in fo r m a tio n on data in
this series, call (202) 691-6392 (table 10)
o r (202) 691-6559 (table 11).

Quarterly Census of
Employment and Wages
Description of the series
Employment, wage, and establishment data
in this section are derived from the quar­
terly tax reports submitted to State em ­
ployment security agencies by private and
State and local government employers sub-

ject to State unemployment insurance (ui)
laws and from Federal, agencies subject
to the Unemploym ent Compensation for
Federal Em ployees ( u c f e ) program. Each
quarter, State agencies edit and process the
data and send the information to the Bu­
reau o f Labor Statistics.
The Quarterly Census of Employment
and Wages (QCEW) data, also referred as e s 202 data, are the most complete enumeration
of employment and wage information by in­
dustry at the national, State, metropolitan
area, and county levels. They have broad eco­
nomic significance in evaluating labor mar­
ket trends and major industry developments.

Definitions
In general, the Quarterly Census of Employ­
ment and Wages monthly employment data
represent the number of covered workers
who worked during, or received pay for, the
pay period that included the 12th day o f the
month. Covered private industry em ploy­
ment includes most corporate officials, ex­
ecutives, supervisory personnel, profession­
als, clerical workers, wage earners, piece
workers, and part-time workers. It excludes
proprietors, the unincorporated self-em ­
ployed, unpaid family members, and certain
farm and domestic workers. Certain types
o f nonprofit employers, such as religious or­
ganizations, are given a choice o f coverage
or exclusion in a number o f States. Workers
in these organizations are, therefore, re­
ported to a limited degree.
Persons on paid sick leave, paid holiday,
paid vacation, and the like, are included. Per­
sons on the payroll o f more than one firm
during the period are counted by each uisubject employer if they meet the employ­
ment definition noted earlier. The employ­
ment count excludes workers who earned no
wages during the entire applicable pay pe­
riod because of work stoppages, temporary
layoffs, illness, or unpaid vacations.
Federal em ploym ent data are based on
reports o f monthly employment and quar­
terly wages submitted each quarter to State
agencies for all Federal installations with
employees covered by the Unemployment
Compensation for Federal Employees ( ucfe )
program, except for certain national secu­
rity agencies, which are omitted for security
reasons. Employment for all Federal agen­
cies for any given month is based on the
number o f persons who worked during or
received pay for the pay period that included
the 12th o f the month.
An establishm ent is an economic unit,
such as a farm, mine, factory, or store, that
produces goods or provides services. It is


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typically at a single physical location and
engaged in one, or predominantly one, type
of economic activity for which a single in­
dustrial classification may be applied. Oc­
casionally, a single physical location encom­
passes two or more distinct and significant
activities. Each activity should be reported
as a separate establishm ent if separate
records are kept and the various activi­
ties are classified under different n a ic s
industries.
Most employers have only one establish­
ment; thus, the establishment is the predomi­
nant reporting unit or statistical entity for
reporting employment and wages data. Most
employers, including State and local govern­
ments who operate more than one establish­
ment in a State, file a Multiple Worksite Re­
port each quarter, in addition to their quar­
terly ui report. The Multiple Worksite Re­
port is used to collect separate employment
and wage data for each of the employer’s
establishments, which are not detailed on the
ui report. Some very small multi-establish­
ment em ployers do not file a M ultiple
Worksite Report. When the total employ­
ment in an employer’s secondary establish­
ments (all establishments other than the larg­
est) is 10 or fewer, the employer generally
will file a consolidated report for all estab­
lishments. Also, some employers either can­
not or will not report at the establishment
level and thus aggregate establishments into
one consolidated unit, or possibly several
units, though not at the establishment level.
For the Federal Government, the report­
ing unit is the installation: a single loca­
tion at which a department, agency, or other
government body has civilian employees.
Federal agencies follow slightly different cri­
teria than do private employers when break­
ing down their reports by installation. They
are permitted to combine as a single state­
wide unit: 1) all installations with 10 or fewer
workers, and 2) all installations that have a
combined total in the State o f fewer than 50
workers. Also, when there are fewer than 25
workers in all secondary installations in a
State, the secondary installations may be
combined and reported with the major in­
stallation. Last, if a Federal agency has fewer
than five employees in a State, the agency
headquarters office (regional office, district
office) serving each State may consolidate
the employment and wages data for that State
with the data reported to the State in which
the headquarters is located. As a result of
these reporting rules, the number o f report­
ing units is always larger than the number
o f employers (or government agencies) but
smaller than the number o f actual establish­
ments (or installations).

Data reported for the first quarter are
tabulated into size categories ranging from
worksites of very small size to those with
1,000 employees or more. The size category
is determined by the establishment’s March
employment level. It is important to note that
each establishment of a multi-establishment
firm is tabulated separately into the appro­
priate size category. The total employment
level of the reporting multi-establishment
firm is not used in the size tabulation.
Covered employers in most States report
total wages paid during the calendar quar­
ter, regardless of when the services were per­
formed. A few State laws, however, specify
that wages be reported for, or based on the
period during which services are performed
rather than the period during which com ­
pensation is paid. Under most State laws or
regulations, wages include bonuses, stock
options, the cash value o f meals and lodg­
ing, tips and other gratuities, and, in some
States, employer contributions to certain de­
ferred compensation plans such as 401(k)
plans.
Covered employer contributions for oldage, survivors, and disability insurance
( oasdi ), health insurance, unemployment in­
surance, workers’ compensation, and private
pension and welfare funds are not reported
as wages. Employee contributions for the
same purposes, however, as well as money
withheld for income taxes, union dues, and
so forth, are reported even though they are
deducted from the worker’s gross pay.
Wages o f covered Federal workers rep­
resent the gross amount of all payrolls for
all pay periods ending within the quarter.
This includes cash allowances, the cash
equivalent o f any type of remuneration, sev­
erance pay, withholding taxes, and retire­
ment deductions. Federal employee remu­
neration generally covers the same types of
services as for workers in private industry.
Average annual w age per employee for
any given industry are computed by divid­
ing total annual wages by annual average em­
ployment. A further division by 52 yields
average weekly wages per employee. Annual
pay data only approximate annual earnings
because an individual may not be employed
by the same employer all year or may work
for more than one employer at a time.
Average weekly or annual w age is af­
fected by the ratio o f full-time to part-time
workers as well as the number of individu­
als in high-paying and low-paying occupa­
tions. When average pay levels between
States and industries are compared, these
factors should be taken into consideration.
For example, industries characterized by
high proportions o f part-time workers will

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63

Current Labor Statistics

show average wage levels appreciably less
than the weekly pay levels o f regular full­
time employees in these industries. The op­
posite effect characterizes industries with
low proportions o f part-time workers, or in­
dustries that typically schedule heavy week­
end and overtime work. Average wage data
also may be influenced by work stoppages,
labor turnover rates, retroactive payments,
seasonal factors, bonus payments, and so on.

Notes on the data
Beginning with the release o f data for 2001,
publications presenting data from the Cov­
ered Employment and Wages program have
switched to the 2002 version o f the North
American Industry Classification System
(NAics) as the basis for the assignment and
tabulation o f economic data by industry.
NAICS is the product of a cooperative effort
on the part o f the statistical agencies o f the
United States, Canada, and Mexico. Due to
difference in n a ics and Standard Industrial
Classification (SIC) structures, industry data
for 2001 is not comparable to the SIC-based
data for earlier years.
Effective January 2001, the program be­
gan assigning Indian Tribal Councils and re­
lated establishments to local government
ownership. This BLS action was in response
to a change in Federal law dealing with the
way Indian Tribes are treated under the Fed­
eral Unemployment Tax Act. This law re­
quires federally recognized Indian Tribes to
be treated similarly to State and local gov­
ernments. In the past, the Covered Employ­
ment and Wage (CEW) program coded Indian
Tribal Councils and related establishments
in the private sector. As a result o f the new
law, CEW data reflects significant shifts in
employment and wages between the private
sector and local government from 2000 to
2001. Data also reflect industry changes.
Those accounts previously assigned to civic
and social organizations were assigned to
tribal governments. There were no required
industry changes for related establishments
owned by these Tribal Councils. These tribal
business establishments continued to be
coded according to the economic activity o f
that entity.
To insure the highest possible quality
o f data, State employment security agen­
cies verify with employers and update, if
necessary, the industry, location, and own­
ership classification o f all establishments
on a 3-year cycle. Changes in establish­
ment classification codes resulting from the
verification process are introduced with the
data reported for the first quarter o f the year.

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Changes resulting from improved employer
reporting also are introduced in the first
quarter. For these reasons, some data, es­
pecially at more detailed geographic lev­
els, may not be strictly comparable with
earlier years.
County definitions are assigned accord­
ing to Federal Information Processing Stan­
dards Publications as issued by the National
Institute o f Standards and Technology. Ar­
eas shown as counties include those desig­
nated as independent cities in some juris­
dictions and, in Alaska, those areas desig­
nated by the Census Bureau where counties
have not been created. County data also are
presented for the New England States for
comparative purposes, even though town­
ships are the more common designation used
in New England (and New Jersey).
The Office of Management and Budget
(o m b ) defines metropolitan areas for use in
Federal statistical activities and updates
these definitions as needed. Data in this table
use metropolitan area criteria established by
o m b in definitions issued June 30, 1999
(o m b Bulletin No. 99-04). These definitions
reflect information obtained from the 1990
Decennial Census and the 1998 U.S. Cen­
sus Bureau population estimate. A complete
list o f metropolitan area definitions is avail­
able from the National Technical Informa­
tion Service ( n t is ), Document Sales, 5205
Port Royal Road, Springfield, Va. 22161,
telephone 1-800-553-6847.
o m b defines metropolitan areas in terms
o f entire counties, except in the six New
England States where they are defined in
terms of cities and towns. New England data
in this table, however, are based on a county
concept defined by OMB as New England
County Metropolitan Areas ( n e c m a ) be­
cause county-level data are the most detailed
available from the Quarterly Census o f Em­
ployment and Wages. The necm a is a countybased alternative to the city- and town-based
metropolitan areas in New England. The
NECMA for a Metropolitan Statistical Area
( m sa ) include: (1) the county containing the
first-named city in that m sa title (this county
may include the first-named cities o f other
m s a , and (2) each additional county having
at least half its population in the m sa in
which first-named cities are in the county
identified in step 1. The n ec m a is officially
defined areas that are meant to be used by
statistical programs that cannot use the regu­
lar metropolitan area definitions in New
England.
F or a d d itio n a l in fo r m ation on the
covered employment and wage data, contact
the Division o f Administrative Statistics and
Labor Turnover at (202) 691-6567.

September 2004

Job Openings and Labor
Turnover Survey
Description of the series
Data for the Job Openings and Labor Turn­
over Survey (jo lts ) are collected and com­
piled from a sample o f 16,000 business es­
tablishments. Each month, data are collected
for total employment, job openings, hires,
quits, layoffs and discharges, and other sepa­
rations. The jolts program covers all private
nonfarm establishments such as factories,
offices, and stores, as well as Federal, State,
and local government entities in the 50 States
and the District o f Columbia. The jo lts
sample design is a random sample drawn from
a universe of more than eight million estab­
lishments compiled as part o f the operations
of the Quarterly Census o f Employment and
Wages, or q c e w , program. This program in­
cludes all employers subject to State unem­
ployment insurance (ui) laws and Federal
agencies subject to Unemployment Compen­
sation for Federal Employees ( u c f e ).
The sampling frame is stratified by owner­
ship, region, industry sector, and size class.
Large firms fall into the sample with virtual
certainty. JOLTS total employment estimates are
controlled to the employment estimates of the
Current Employment Statistics (c e s ) survey.
A ratio o f ces to jolts employment is used to
adjust the levels for all other jolts data ele­
ments. Rates then are computed from the ad­
justed levels.
The monthly jolts data series begin with
December 2000. Not seasonally adjusted data
on job openings, hires, total separations, quits,
layoffs and discharges, and other separations
levels and rates are available for the total non­
farm sector, 16 private industry divisions and
2 government divisions based on the North
American Industry Classification System
( n aics ), and four geographic regions. Season­
ally adjusted data on job openings, hires, total
separations, and quits levels and rates are avail­
able for the total nonfarm sector, selected in­
dustry sectors, and four geographic regions.

Definitions
Establishments submit job openings infor­
mation for the last business day o f the refer­
ence month. A job opening requires that (1)
a specific position exists and there is work
available for that position; and (2) work
could start within 30 days regardless of
whether a suitable candidate is found; and
(3) the employer is actively recruiting from
outside the establishment to fill the position.
Included are full-time, part-time, permanent,

short-term, and seasonal openings. Active
recruiting means that the establishment is
taking steps to fill a position by advertising
in newspapers or on the Internet, posting
help-wanted signs, accepting applications,
or using other similar methods.
Jobs to be filled only by internal transfers,
promotions, demotions, or recall from lay­
offs are excluded. Also excluded are jobs with
start dates more than 30 days in the future,
jobs for which employees have been hired
but have not yet reported for work, and jobs
to be filled by employees of temporary help
agencies, employee leasing companies, out­
side contractors, or consultants. The job
openings rate is computed by dividing the
number of job openings by the sum o f em­
ployment and job openings, and multiplying
that quotient by 100.
Hires are the total number o f additions to
the payroll occurring at any time during the
reference month, including both new and re­
hired employees and full-time and part-time,
permanent, short-term and seasonal em ­
ployees, employees recalled to the location
after a layoff lasting more than 7 days, oncall or intermittent employees who returned
to work after having been formally separated,
and transfers from other locations. The hires
count does not include transfers or promo­
tions within the reporting site, employees
returning from strike, employees o f tempo­
rary help agencies or employee leasing com­
panies, outside contractors, or consultants.
The hires rate is computed by dividing the
number of hires by employment, and multi­
plying that quotient by 100.
Separations are the total number of termi­
nations of employment occurring at any time
during the reference month, and are reported
by type of separation— quits, layoffs and dis­
charges, and other separations. Quits are vol­
untary separations by employees (except for
retirements, which are reported as other separa­
tions). Layoffs and discharges are involuntary
separations initiated by the employer and in­
clude layoffs with no intent to rehire, formal
layoffs lasting or expected to last more than 7
days, discharges resulting from mergers,
downsizing, or closings, firings or other dis­
charges for cause, terminations of permanent
or short-term employees, and terminations of
seasonal employees. Other separations include
retirements, transfers to other locations, deaths,
and separations due to disability. Separations
do not include transfers within the same loca­
tion or employees on strike.
The separations rate is computed by di­
viding the number o f separations by employ­
ment, and multiplying that quotient by 100.
The quits, layoffs and discharges, and other
separations rates are computed similarly,


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able. When the stable seasonal filter is no
longer needed, other program features also
may be introduced, such as outlier adjustment
and extended diagnostic testing. Additionally,
Notes on the data
it is expected that more series, such as lay­
offs and discharges and additional industries,
may be seasonally adjusted when more data
The JOLTS data series on job openings, hires,
and separations are relatively new. The full
are available.
sample is divided into panels, with one panel
jolts hires and separations estimates can­
enrolled each month. A full complement of
not be used to exactly explain net changes in
panels for the original data series based on
payroll employment. Some reasons why it is
the 1987 Standard Industrial Classification
problematic to compare changes in payroll
(Sic) system was not completely enrolled in
employment with jolts hires and separations,
the survey until January 2002. The supple­
especially on a monthly basis, are: (1) the
mental panels o f establishments needed to
reference period for payroll employment is
the pay period including the 12th o f the
create n a ics estimates were not completely
enrolled until May 2003. The data collected
month, while the reference period for hires
up until those points are from less than a and separations is the calendar month; and
full sample. Therefore, estimates from ear­
(2) payroll employment can vary from month
lier months should be used with caution, as
to month simply because part-time and onfewer sampled units were reporting data at call workers may not always work during the
pay period that includes the 12th o f the
that time.
In March 2002, bls procedures for col­
month. Additionally, research has found that
lecting hires and separations data were revised
some reporters systematically underreport
to address possible underreporting. As a re­
separations relative to hires due to a num­
sult, jolts hires and separations estimates for
ber of factors, including the nature o f their
months prior to March 2002 may not be com­
payroll systems and practices. The shortfall
appears to be about 2 percent or less over a
parable with estimates for March 2002 and
later.
12-month period.
F or a d d itio n a l in fo r m ation on the Job
The Federal Government reorganization
Openings and Labor Turnover Survey, con­
that involved transferring approximately
180,000 employees to the new Department tact the Division of Administrative Statistics
and Labor Turnover at (202) 961-5870.
o f Homeland Security is not reflected in the
jolts hires and separations estimates for the
Federal Government. The Office o f Person­
nel Management’s record shows these trans­
Com pensation and
fers were completed in March 2003. The
inclusion of transfers in the jolts definitions
W age Data
o f hires and separations is intended to cover
(Tables 1-3; 30-36)
ongoing movements of workers between es­
tablishments. The Department of Homeland
Compensation and waged data are gathered
Security reorganization was a massive one­
by the Bureau from business establishments,
time event, and the inclusion o f these inter­
State and local governments, labor unions,
governmental transfers would distort the
collective bargaining agreements on file
Federal Government time series.
with the Bureau, and secondary sources.
Data users should note that seasonal ad­
justment of the jolts series is conducted with
Employment Cost Index
fewer data observations than is customary.
The historical data, therefore, may be sub­
ject to larger than normal revisions. Because
Description of the series
the seasonal patterns in economic data series
The E m ploym ent C ost Index (ECI) is a
typically emerge over time, the standard use
quarterly measure o f the rate of change in
o f moving averages as seasonal filters to cap­
compensation per hour worked and includes
ture these effects requires longer series than
wages, salaries, and employer costs of em­
are currently available. As a result, the stable
ployee benefits. It uses a fixed market
seasonal filter option is used in the seasonal
basket o f labor— similar in concept to the
adjustment of the jolts data. When calculat­
Consumer Price Index’s fixed market bas­
ing seasonal factors, this filter takes an aver­
ket o f goods and services— to measure
age for each calendar month after detrending
change over time in employer costs of em­
the series. The stable seasonal filter assumes
ploying labor.
that the seasonal factors are fixed; a neces­
Statistical series on total compensation
sary assumption until sufficient data are avail­

dividing the number by employment and
multiplying by 100.

Monthly Labor Review September 2004

65

Current Labor Statistics

costs, on wages and salaries, and on ben­
efit costs are available for private nonfarm
workers excluding proprietors, the self-em­
ployed, and household workers. The total
compensation costs and wages and salaries
series are also available for State and local
government workers and for the civilian
nonfarm economy, which consists of pri­
vate industry and State and local govern­
ment workers combined. Federal workers
are excluded.
The Employment Cost Index probability
sample consists o f about 4,400 private non­
farm establishments providing about 23,000
occupational observations and 1,000 State
and local government establishments pro­
viding 6,000 occupational observations se­
lected to represent total employment in each
sector. On average, each reporting unit pro­
vides wage and compensation information
on five well-specified occupations. Data are
collected each quarter for the pay period in­
cluding the 12th day o f March, June, Sep­
tember, and December.
Beginning with June 1986 data, fixed
employment weights from the 1980 Census
o f Population are used each quarter to
calculate the civilian and private indexes
and the index for State and local govern­
ments. (Prior to June 1986, the employment
weights are from the 1970 Census of Popu­
lation.) These fixed weights, also used to
derive all o f the industry and occupation
series indexes, ensure that changes in these
indexes reflect only changes in compensa­
tion, not employment shifts among indus­
tries or occupations with different levels of
wages and compensation. For the bargain­
ing status, region, and metropolitan/nonmetropolitan area series, however, employ­
ment data by industry and occupation are
not available from the census. Instead, the
1980 employment weights are reallocated
within these series each quarter based on the
current sample. Therefore, these indexes are
not strictly comparable to those for the ag­
gregate, industry, and occupation series.

Definitions
Total com pensation costs include wages,
salaries, and the employer’s costs for em­
ployee benefits.
W ages and salaries consist of earnings
before payroll deductions, including pro­
duction bonuses, incentive earnings, com­
missions, and cost-of-living adjustments.
Benefits include the cost to employers
for paid leave, supplemental pay (includ­
ing nonproduction bonuses), insurance, retire­
ment and savings plans, and legally required

66

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benefits (such as Social Security, workers’
compensation, and unemployment insurance).
Excluded from wages and salaries and
employee benefits are such items as pay­
ment-in-kind, free room and board, and tips.

Notes on the data
The Employment Cost Index for changes in
wages and salaries in the private nonfarm
economy was published beginning in 1975.
Changes in total compensation cost— wages
and salaries and benefits combined— were
published beginning in 1980. The series of
changes in wages and salaries and for total
compensation in the State and local govern­
ment sector and in the civilian nonfarm
economy (excluding Federal em ployees)
were published beginning in 1981. Histori­
cal indexes (June 1981=100) are available
on the Internet:
http ://ww w .bls.gov/ect/
F o r a d d it io n a l in f o r m a t io n on the
Employment Cost Index, contact the Office
o f Compensation Levels and Trends: (202)
691-6199.

Employee Benefits Survey
Description of the series
Em ployee benefits data are obtained from
the Employee Benefits Survey, an annual
survey of the incidence and provisions of
selected benefits provided by employers.
The survey collects data from a sample of
approximately 9,000 private sector and State
and local government establishments. The
data are presented as a percentage o f em­
ployees who participate in a certain benefit,
or as an average benefit provision (for ex­
ample, the average number of paid holidays
provided to employees per year). Selected
data from the survey are presented in table
34 for medium and large private establish­
ments and in table 35 for small private estab­
lishments and State and local government.
The survey covers paid leave benefits
such as holidays and vacations, and personal,
funeral, jury duty, military, family, and sick
leave; short-term disability, long-term dis­
ability, and life insurance; medical, dental,
and vision care plans; defined benefit and
defined contribution plans; flexible benefits
plans; reimbursement accounts; and unpaid
family leave.
A lso, data are tabulated on the in ci­
dence o f several other benefits, such as
severance pay, child-care assistance, w ell­
ness programs, and em ployee assistance
programs.

September 2004

Definitions
Employer-provided benefits are benefits
that are financed either wholly or partly by
the employer. They may be sponsored by a
union or other third party, as long as there is
some employer financing. However, some
benefits that are fully paid for by the em­
ployee also are included. For example, long­
term care insurance and postretirement life
insurance paid entirely by the employee are
included because the guarantee o f insurabil­
ity and availability at group premium rates
are considered a benefit.
Participants are workers who are cov­
ered by a benefit, whether or not they use
that benefit. If the benefit plan is financed
wholly by employers and requires em ploy­
ees to complete a minimum length o f ser­
vice for eligibility, the workers are consid­
ered participants whether or not they have
met the requirement. If workers are re­
quired to contribute towards the cost o f a
plan, they are considered participants only
if they elect the plan and agree to make the
required contributions.
D efined benefit pension plans use pre­
determined formulas to calculate a retire­
ment benefit (if any), and obligate the em­
ployer to provide those benefits. Benefits
are generally based on salary, years o f ser­
vice, or both.
Defined contribution plans generally
specify the level o f employer and employee
contributions to a plan, but not the formula
for determining eventual benefits. Instead,
individual accounts are set up for partici­
pants, and benefits are based on amounts
credited to these accounts.
Tax-deferred savings plans are a type
of defined contribution plan that allow par­
ticipants to contribute a portion o f their sal­
ary to an employer-sponsored plan and de­
fer income taxes until withdrawal.
Flexible benefit plans allow employees
to choose among several benefits, such as
life insurance, medical care, and vacation
days, and among several levels o f coverage
within a given benefit.

Notes on the data
Surveys o f employees in medium and large
establishments conducted over the 1979—
86 period included establishments that em ­
ployed at least 50, 100, or 250 workers,
depending on the industry (most service
industries were excluded). The survey con­
ducted in 1987 covered only State and lo ­
cal governments with 50 or more employ-

ees. The surveys conducted in 1988 and
1989 included medium and large establish­
ments with 100 workers or more in private
industries. All surveys conducted over the
1979-89 period excluded establishments
in Alaska and Hawaii, as w ell as part-time
em ployees.
Beginning in 1990, surveys o f State and
local governments and small private estab­
lishments were conducted in even-num ­
bered years, and surveys o f medium and
large establishments were conducted in oddnumbered years. The small establishment
survey includes all private nonfarm estab­
lishments with few er than 100 workers,
while the State and local government sur­
vey includes all governments, regardless of
the number o f workers. All three surveys in­
clude fu ll- and part-tim e workers, and
workers in all 50 States and the District o f
Columbia.
F o r a d d it io n a l in f o r m a t io n on the
Employee Benefits Survey, contact the Of­
fice o f Compensation Levels and Trends on
the Internet:
http://ww w.bls.gov/ebs/

Notes on the data
This series is not comparable with the one
terminated in 1981 that covered strikes in­
volving six workers or more.
F or a d d itio n a l in fo r m ation on work
stoppages data, contact the Office o f Com­
pensation and Working Conditions: (202)
691-6282, or the Internet:
http:/w ww.bls.gov/cba/

Price Data
(Tables 2; 37-47)
Price data are gathered by the Bureau
o f Labor Statistics from retail and pri­
mary markets in the United States. Price in­
dexes are given in relation to a base period—
December 2003 = 100 for many Producer
Price Indexes (unless otherwise noted), 198284 = 100 for many Consumer Price Indexes
(unless otherwise noted), and 1990 = 100 for
International Price Indexes.

Consumer Price Indexes

Work stoppages

Description of the series

Description of the series

The Consumer Price Index (CPI) is a mea­
sure o f the average change in the prices paid
by urban consumers for a fixed market bas­
ket o f goods and services. The CPI is calcu­
lated monthly for two population groups,
one consisting only o f urban households
whose primary source of income is derived
from the employment of wage earners and
clerical workers, and the other consisting of
all urban households. The wage earner in­
dex (CPi-W) is a continuation o f the historic
index that was introduced well over a halfcentury ago for use in wage negotiations.
As new uses were developed for the CPI in
recent years, the need for a broader and more
representative index became apparent. The
all-urban consumer index (CPi-U), introduced
in 1978, is representative o f the 1993-95
buying habits o f about 87 percent of the noninstitutional population of the United States
at that time, compared with 32 percent rep­
resented in the CPi-w. In addition to wage
earners and clerical workers, the CPI-U cov­
ers professional, managerial, and technical
workers, the self-em ployed, short-term
workers, the unemployed, retirees, and oth­
ers not in the labor force.
The CPI is based on prices o f food, cloth­
ing, shelter, fuel, drugs, transportation fares,
doctors’ and dentists’ fees, and other goods
and services that people buy for day-to-day
living. The quantity and quality o f these
items are kept essentially unchanged be­

Data on work stoppages measure the num­
ber and duration o f major strikes or lock­
outs (involving 1,000 workers or more) oc­
curring during the month (or year), the num­
ber o f workers involved, and the amount of
work time lost because of stoppage. These
data are presented in table 36.
Data are largely from a variety of pub­
lished sources and cover only establish­
ments directly involved in a stoppage. They
do not measure the indirect or secondary
effect o f stoppages on other establishments
whose employees are idle owing to material
shortages or lack o f service.

Definitions
N um ber o f stoppages: The number o f
strikes and lockouts involving 1,000 work­
ers or more and lasting a full shift or longer.
W orkers involved: The number o f
workers directly involved in the stoppage.
N um ber o f days idle: The aggregate
number o f workdays lost by workers in­
volved in the stoppages.
Days of idleness as a percent o f estimated
working time: Aggregate workdays lost as a
percent of the aggregate number o f standard
workdays in the period multiplied by total em­
ployment in the period.


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tween major revisions so that only price
changes will be measured. All taxes directly
associated with the purchase and use o f
items are included in the index.
Data collected from more than 23,000 re­
tail establishments and 5,800 housing units
in 87 urban areas across the country are used
to develop the “U.S. city average.” Separate
estimates for 14 major urban centers are pre­
sented in table 38. The areas listed are as in­
dicated in footnote 1 to the table. The area
indexes measure only the average change in
prices for each area since the base period,
and do not indicate differences in the level
of prices among cities.

Notes on the data
In January 1983, the Bureau changed the
way in which homeownership costs are
meaured for the CPi-U. A rental equivalence
method replaced the asset-price approach to
homeownership costs for that series. In
January 1985, the same change was made in
the CPi-w. The central purpose o f the change
was to separate shelter costs from the invest­
ment component o f homeownership so that
the index would reflect only the cost o f shel­
ter services provided by owner-occupied
homes. An updated CPI-U and CPi-w were
introduced with release o f the January 1987
and January 1998 data.
F o r a d d it io n a l in fo r m a t io n , contact
the Division o f Prices and Price Indexes:
(202) 691-7000.

Producer Price Indexes
Description of the series
Producer Price Indexes (P P i) measure av­
erage changes in prices received by domes­
tic producers o f commodities in all stages
o f processing. The sample used for calcu­
lating these indexes currently contains about
3,200 commodities and about 80,000 quo­
tations per month, selected to represent the
movement of prices o f all commodities pro­
duced in the manufacturing; agriculture, for­
estry, and fishing; mining; and gas and elec­
tricity and public utilities sectors. The stageof-processing structure o f p p i organizes
products by class of buyer and degree of fab­
rication (that is, finished goods, intermedi­
ate goods, and crude materials). The tradi­
tional com m odity structure o f p pi orga­
nizes products by similarity o f end use or
material com position. The industry and
product structure o f ppi organizes data in
accordance with the 2002 North American In­
dustry Classification System and product
codes developed by the U.S. Census Bureau.

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To the extent possible, prices used in cal­
culating Producer Price Indexes apply to the
first significant commercial transaction in
the United States from the production or
central marketing point. Price data are gen­
erally collected monthly, primarily by mail
questionnaire. Most prices are obtained di­
rectly from producing companies on a vol­
untary and confidential basis. Prices gener­
ally are reported for the Tuesday of the week
containing the 13th day o f the month.
Since January 1992, price changes for
the various commodities have been averaged
together with implicit quantity weights rep­
resenting their importance in the total net
selling value o f all commodities as o f 1987.
The detailed data are aggregated to obtain
indexes for stage-of-processing groupings,
commodity groupings, durability-of-product groupings, and a number o f special com­
posite groups. All Producer Price Index data
are subject to revision 4 months after origi­
nal publication.
For additional information, contact
the Division o f Industrial Prices and Price
Indexes: (202) 691-7705.

International Price Indexes
Description of the series
The International Price Program produces
monthly and quarterly export and import
price indexes for nonmilitary goods and ser­
vices traded between the United States and
the rest o f the world. The export price in­
dex provides a measure o f price change
for all products sold by U.S. residents to
foreign buyers. (“Residents” is defined as
in the national incom e accounts; it in­
cludes corporations, businesses, and indi­
viduals, but does not require the organi­
zations to be U.S. owned nor the individu­
als to have U .S. citizenship.) The import
price index provides a measure o f price
change for goods purchased from other
countries by U .S. residents.
The product universe for both the import
and export indexes includes raw materials,
agricultural products, semifinished manu­
factures, and finished manufactures, includ­
ing both capital and consumer goods. Price
data for these items are collected primarily
by mail questionnaire. In nearly all cases,
the data are collected directly from the ex­
porter or importer, although in a few cases,
prices are obtained from other sources.
To the extent possible, the data gathered
refer to prices at the U.S. border for exports
and at either the foreign border or the U.S.
border for imports. For nearly all prod­
ucts, the prices refer to transactions com ­

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pleted during the first week o f the month.
Survey respondents are asked to indicate
all discounts, allowances, and rebates ap­
plicable to the reported prices, so that the
price used in the calculation o f the indexes
is the actual price for which the product
was bought or sold.
In addition to general indexes of prices for
U.S. exports and imports, indexes are also
published for detailed product categories of
exports and imports. These categories are de­
fined according to the five-digit level of detail
for the Bureau of Economic Analysis End-use
Classification, the three-digit level for the Stan­
dard International Trade Classification (SITC),
and the four-digit level of detail for the Har­
monized System. Aggregate import indexes by
country or region of origin are also available.

put to real input. As such, they encompass a
family o f measures which include single­
factor input measures, such as output per
hour, output per unit o f labor input, or out­
put per unit of capital input, as well as mea­
sures o f multifactor productivity (output per
unit of combined labor and capital inputs).
The Bureau indexes show the change in out­
put relative to changes in the various inputs.
The measures cover the business, nonfarm
business, manufacturing, and nonfinancial
corporate sectors.
Corresponding indexes o f hourly com ­
pensation, unit labor costs, unit nonlabor
payments, and prices are also provided.

bls publishes indexes for selected cat­
egories of internationally traded services,
calculated on an international basis and on
a balance-of-payments basis.

Output per hour o f all persons (labor pro­
ductivity) is the quantity of goods and ser­
vices produced per hour of labor input. Out­
put per unit o f capital services (capital pro­
ductivity) is the quantity o f goods and ser­
vices produced per unit o f capital services
input. M ultifactor productivity is the quan­
tity of goods and services produced per com­
bined inputs. For private business and pri­
vate nonfarm business, inputs include labor
and capital units. For manufacturing, inputs
include labor, capital, energy, nonenergy ma­
terials, and purchased business services.
Compensation per hour is total compen­
sation divided by hours at work. Total com­
pensation equals the wages and salaries of
employees plus employers’ contributions for
social insurance and private benefit plans,
plus an estimate o f these payments for the
self-employed (except for nonfinancial cor­
porations in which there are no self-em ­
ployed). Real com pensation per hour is
com pensation per hour deflated by the
change in the Consumer Price Index for All
Urban Consumers.
U nit labor costs are the labor compen­
sation costs expended in the production
o f a unit o f output and are derived by divid­
ing compensation by output. Unit nonlabor
p aym en ts include profits, depreciation,
interest, and indirect taxes per unit o f out­
put. They are computed by subtracting
compensation o f all persons from currentdollar value o f output and dividing by out­
put.
U nit nonlabor costs contain all the
components of unit nonlabor payments ex­
cept unit profits.
U nit profits include corporate profits
with inventory valuation and capital con­
sumption adjustments per unit o f output.
Hours o f all persons are the total hours
at work o f payroll workers, self-employed
persons, and unpaid family workers.

Notes on the data
The export and import price indexes are
weighted indexes of the Laspeyres type. The
trade weights currently used to compute
both indexes relate to 2000.
Because a price index depends on the
same items being priced from period to pe­
riod, it is necessary to recognize when a
product’s specifications or terms o f transac­
tion have been modified. For this reason, the
Bureau’s questionnaire requests detailed de­
scriptions o f the physical and functional
characteristics o f the products being priced,
as well as information on the number of units
bought or sold, discounts, credit terms, pack­
aging, class of buyer or seller, and so forth.
When there are changes in either the specifi­
cations or terms of transaction of a product,
the dollar value of each change is deleted from
the total price change to obtain the “pure”
change. Once this value is determined, a link­
ing procedure is employed which allows for
the continued repricing of the item.
For additional information, contact
the Division o f International Prices: (202)
691-7155.

Productivity Data
(Tables 2; 48-51)

Business and major sectors
Description of the series
The productivity measures relate real out­

September 2004

Definitions

Labor inputs are hours o f all persons ad­
justed for the effects of changes in the edu­
cation and experience of the labor force.
Capital services are the flow o f services
from the capital stock used in production. It
is developed from measures o f the net stock
o f physical assets— equipment, structures,
land, and inventories— weighted by rental
prices for each type o f asset.
Com bined units o f labor and capital
inputs are derived by combining changes in
labor and capital input with weights which
represent each component’s share of total
cost. Combined units of labor, capital, energy,
materials, and purchased business services are
similarly derived by combining changes in
each input with weights that represent each
input’s share of total costs. The indexes for
each input and for combined units are based
on changing weights which are averages of the
shares in the current and preceding year (the
Tomquist index-number formula).

Notes on the data
B usiness sector output is an annuallyweighted index constructed by excluding
from real gross domestic product (GDP) the
following outputs: general government, non­
profit institutions, paid employees of private
households, and the rental value o f owneroccupied dwellings. Nonfarm business also
excludes farming. Private business and pri­
vate nonfarm business further exclude gov­
ernment enterprises. The measures are sup­
plied by the U.S. Department of Commerce’s
Bureau o f Economic Analysis. Annual esti­
mates o f manufacturing sectoral output are
produced by the Bureau o f Labor Statistics.
Quarterly manufacturing output indexes
from the Federal Reserve Board are adjusted
to these annual output measures by the b l s .
Compensation data are developed from data
o f the Bureau o f Economic Analysis and the
Bureau of Labor Statistics. Hours data are
developed from data of the Bureau of Labor
Statistics.
The productivity and associated cost
measures in tables 48-51 describe the rela­
tionship between output in real terms and
the labor and capital inputs involved in its
production. They show the changes from pe­
riod to period in the amount o f goods and
services produced per unit o f input.
Although these measures relate output to
hours and capital services, they do not mea­
sure the contributions o f labor, capital, or
any other specific factor o f production.
Rather, they reflect the joint effect of many
influences, including changes in technol­
ogy; shifts in the composition o f the labor


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force; capital investment; level of output;
changes in the utilization o f capacity, en­
ergy, material, and research and develop­
ment; the organization of production; mana­
gerial skill; and characteristics and efforts
of the work force.
F o r a d d it io n a l in fo r m a t io n on this
productivity series, contact the Division of
Productivity Research: (202) 691-5606.

ducing that output. Com bined inputs in­
clude capital, labor, and intermediate pur­
chases. The measure o f capital input rep­
resents the flow o f services from the capital
stock used in production. It is developed
from measures o f the net stock of physical
assets— equipment, structures, land, and in­
ventories. The measure o f interm ediate
purchases is a combination of purchased
materials, services, fuels, and electricity.

Industry productivity
measures

Notes on the data

Description of the series
The bls industry productivity indexes mea­
sure the relationship between output and
inputs for selected industries and industry
groups, and thus reflect trends in industry
efficiency over time. Industry measures in­
clude labor productivity, multifactor pro­
ductivity, com pensation, and unit labor
costs.
The industry measures differ in meth­
odology and data sources from the produc­
tivity measures for the major sectors be­
cause the industry measures are developed
independently o f the National Income and
Product Accounts framework used for the
major sector measures.

Definitions
Output per hour is derived by dividing an
index of industry output by an index o f la­
bor input. For most industries, output in­
dexes are derived from data on the value of
industry output adjusted for price change.
For the remaining industries, output indexes
are derived from data on the physical quan­
tity o f production.
The labor input series is based on the
hours o f all workers or, in the case of some
transportation industries, on the number of
employees. For most industries, the series
consists of the hours o f all employees. For
some trade and services industries, the se­
ries also includes the hours of partners, pro­
prietors, and unpaid family workers.
U nit labor costs represent the labor
compensation costs per unit o f output pro­
duced, and are derived by dividing an index
of labor compensation by an index of out­
put. Labor com pensation includes payroll
as well as supplemental payments, includ­
ing both legally required expenditures and
payments for voluntary programs.
M ultifactor productivity is derived by
dividing an index o f industry output by an
index of combined inputs consumed in pro­

The industry measures are compiled from
data produced by the Bureau o f Labor Sta­
tistics and the Census Bureau, with addi­
tional data supplied by other government
agen cies, trade association s, and other
sources.
FOR ADDITIONAL INFORMATION On this se­
ries, contact the Division o f Industry Pro­
ductivity Studies: (202) 691-5618.

International Comparisons
(Tables 52-54)

Labor force and
unemployment
Description of the series
Tables 52 and 53 present comparative meas­
ures o f the labor force, employment, and
unemployment approximating U .S. con­
cepts for the United States, Canada, Austra­
lia, Japan, and six European countries. The
labor force statistics published by other indus­
trial countries are not, in most cases, compa­
rable to U.S. concepts. Therefore, the Bureau
adjusts the figures for selected countries, for
all known major definitional differences, to the
extent that data to prepare adjustments are
available. Although precise comparability may
not be achieved, these adjusted figures pro­
vide a better basis for international compari­
sons than the figures regularly published by
each country. For further information on ad­
justments and com parability issues, see
Constance Sorrentino, “International unem­
ployment rates: how comparable are they?”
M on th ly L a b o r R eview , June 2000, pp. 3-20
(available on the bls Web site at http://
w w w .bls.gov/opub/m lr/2000/06/
artlfiill.pdf).

Definitions
For the principal U.S. definitions o f the la­
bor force, employment, and unemployment,
see the Notes section on Employment and

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Current Labor Statistics

Unem ploym ent Data: Household survey
data.

Notes on the data

p assive jobseekers as unem ployed. An
adjustment is made to exclude them in Canada,
but not in the European countries where the
phenomenon is less prevalent. Persons waiting
to start a new job are counted among the
unemployed for all other countries, whether
or not they were actively seeking work.
The figures for one or more recent years
for France, Germany, and the Netherlands are
calculated using adjustment factors based on
labor force surveys for earlier years and are
considered preliminary. The recent year
measures for these countries are therefore
subject to revision whenever more current
labor force surveys become available.
There are breaks in series for the United
States (1994,1997,1998,1999,2000,2003),
Australia (2001), and Germany (1999).
For the United States, beginning in 1994,
data are not strictly comparable for prior years
because o f the introduction o f a major
redesign o f the labor force survey question­
naire and co llectio n m ethodology. The
redesign effect has been estimated to increase
the overall unem ploym ent rate by 0.1
percentage point. Other breaks noted relate
to changes in population controls that had
virtually no effect on unemployment rates.
For a description o f all the changes in the
U.S. labor force survey over time and their
impact, see Historical Comparability in the
“Household Data” section o f the bls publi­
cation E m p lo y m en t a n d E a rn in g s (available
on the bls Web site at http://www.bls.gov/

The foreign country data are adjusted as
closely as possible to U.S. concepts, with the
exception of lower age limits and the treatment
o f layoffs. These adjustments include, but are
not limited to: including older persons in the
labor force by imposing no upper age limit,
adding unem ployed students to the
unemployed, excluding the military and family
workers working fewer than 15 hours from the
employed, and excluding persons engaged in
passive job search from the unemployed.
Data for the United States relate to the
population 16 years o f age and older. The U.S.
concept o f the working age population has
no upper age limit. The adjusted to U.S.
concepts statistics have been adapted, insofar
as possible, to the age at which compulsory
schooling ends in each country, and the
Sw edish statistics have been adjusted to
include persons older than the Swedish upper
age limit of 64 years. The adjusted statistics
presented here relate to the population 16
years o f age and older in France, Sweden,
and the United Kingdom; 15 years of age and
older in Australia, Japan, Germany, Italy, and
the Netherlands. An exception to this rule is
that the Canadian statistics are adjusted to
cover the population 16 years o f age and
older, whereas the age at which compulsory
schooling ends remains at 15 years. In the labor cps/eetech_methods.pdf).
force participation rates and employmentFor Australia, the 2001 break reflects the
population ratios, the denominator is the
introduction in April 2001 o f a redesigned
civilian noninstitutionalized working age
labor force survey that allowed for a closer
population, except that the institutionalized
application o f International Labor Office
working age population is included in Japan
guidelines for the definitions o f labor force
and Germany.
statistics. The Australian Bureau o f Statistics
In the United States, the unemployed
revised their data so there is no break in the
include persons who are not employed and
employment series. However, the reclassi­
who were actively seeking work during the
fication o f persons who had not actively
reference period, as well as persons on layoff.
looked for work because they were waiting to
Persons waiting to start a new job who were
begin a new job from “not in the labor force”
actively seeking work during the reference
to “unemployed” could only be incorporated
period are counted as unemployed under U.S.
for April 2001 forward. This reclassification
concepts; if they were not actively seeking
diverges from the U.S. definition where
work, they are not counted in the labor force.
persons waiting to start a new job but not
In some countries, persons on layoff are
actively seeking work are not counted in the
classified as employed due to their strong job
labor force. The impact of the reclassification
attachment. No adjustment is made for the
was an increase in the unemployment rate by
countries that classify those on layoff as
0.1 percentage point in 2001.
employed. In the United States, as in Australia
For Germany, the 1999 break reflects the
and Japan, passive job seekers are not in the
incorporation o f an improved method o f data
labor force; job search must be active, such
calculation and a change in coverage to
as placing or answering advertisements,
persons living in private households only.
contacting employers directly,or registering
For further qualifications and historical
with an employment agency (simply reading
data, see C o m p a ra tiv e C ivilia n L a b o r F o rc e
ads is not enough to qualify as active search).
S ta tistics, Ten C o u n tries, on the bls Web site
Canada and the European countries classify
at http ://www.bls.gov/fls/flslforc.pdf

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September 2004

For additional information on this
series, contact the D ivision o f Foreign
L abor S tatistics: (2 0 2 ) 6 9 1 -5 6 5 4 or
flshelp@ bls.gov

Manufacturing productivity
and labor costs
Description of the series
Table 54 presents comparative indexes o f
manufacturing labor productivity (output per
hour), output, total hours, compensation per
hour, and unit labor costs for the United States,
Canada, Japan, and nine European countries.
These measures are trend comparisons— that
is, series that measure changes over time—
rather than level comparisons. There are greater
technical problems in comparing the levels of
manufacturing output among countries.
bls constructs the comparative indexes
from three basic aggregate measures— out­
put, total labor hours, and total compensa­
tion. The hours and compensation measures
refer to all employed persons (wage and sal­
ary earners plus self-employed persons and
unpaid family workers) in the United States,
Canada, Japan, France, Germany, Norway,
and Sweden, and to all employees (wage and
salary earners) in the other countries.

Definitions
Output, in general, refers to value added in
manufacturing from the national accounts
o f each country. However, the output se­
ries for Japan prior to 1970 is an index of
industrial production, and the national ac­
counts measures for the United Kingdom
are essentially identical to their indexes of
industrial production.
The 1977-97 output data for the United
States are the gross product originating
(value added) measures prepared by the
Bureau of Economic Analysis o f the U.S.
Department o f Commerce. Comparable
manufacturing output data currently are not
available prior to 1977.
U.S. gross product originating is a chaintype annual-weighted series. (For more in­
formation on the U.S. measure, see Robert
E. Yuskavage, “Improved Estimates o f Gross
Product by Industry, 1959-94,” S u rv e y o f
C u r re n t B u s in e ss, August 1996, pp. 133—
55.) The Japanese value added series is based
upon one set o f fixed price weights for the
years 1970 through 1997. Output series for
the other foreign economies also employ
fixed price weights, but the weights are up­
dated periodically (for example, every 5 or 10
years).

To preserve the comparability o f the U.S.
measures with those for other economies,
BLS uses gross product originating in manu­
facturing for the United States for these com­
parative measures. The gross product origi­
nating series differs from the manufactur­
ing output series that bls publishes in its
news releases on quarterly measures o f U.S.
productivity and costs (and that underlies the
measures that appear in tables 48 and 50 in
this section). The quarterly measures are on
a “sectoral output” basis, rather than a valueadded basis. Sectoral output is gross output
less intrasector transactions.
Total labor hours refers to hours worked
in all countries. The measures are devel­
oped from statistics of manufacturing em­
ployment and average hours. The series used
for France (from 1970 forward), Norway,
and Sweden are official series published with
the national accounts. Where official total
hours series are not available, the measures
are developed by BLS using employment fig­
ures published with the national accounts,
or other comprehensive employment series,
and estimates of annual hours worked. For
Germany, BLS uses estimates o f average
hours worked developed by a research in­
stitute connected to the Ministry of Labor
for use with the national accounts employ­
ment figures. For the other countries, BLS
constructs its own estimates o f average
hours.
An hours series is not available for Den­
mark after 1993; therefore, the BLS mea­
sure o f labor input for Denmark ends in
1993.
Total com pensation (labor cost) in­
cludes all payments in cash or in-kind made
directly to employees plus employer expen­
ditures for legally required insurance pro­
grams and contractual and private benefit
plans. The measures are from the national
accounts of each country, except those for
Belgium, which are developed by BLS using
statistics on employment, average hours, and
hourly compensation. For Canada, France,
and Sweden, compensation is increased to
account for other significant taxes on pay­
roll or employment. For the United King­
dom, compensation is reduced between 1967
and 1991 to account for employment-related
subsidies. Self-employed workers are in­
cluded in the all-employed-persons measures
by assuming that their hourly compensation
is equal to the average for wage and salary
employees.

Notes on the data
In general, the measures relate to total manu­
facturing as defined by the International


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Standard Industrial Classification. However,
the measures for France (for all years) and
Italy (beginning in 1970) refer to mining and
manufacturing less energy-related products,
and the measures for Denmark include min­
ing and exclude manufacturing handicrafts
from 1960 to 1966.
The measures for recent years may be
based on current indicators o f manufactur­
ing output (such as industrial production in­
dexes), employment, average hours, and
hourly compensation until national accounts
and other statistics used for the long-term
measures become available.
For additional information on this se­
ries, contact the Division of Foreign Labor
Statistics: (202) 691-5654.

O ccupational Injury
and Illness Data
(Tables 55-56)

Survey of Occupational
Injuries and Illnesses
Description of the series
The Survey of Occupational Injuries and Ill­
nesses collects data from employers about
their workers’ job-related nonfatal injuries and
illnesses. The information that employers pro­
vide is based on records that they maintain un­
der the Occupational Safety and Health Act of
1970. Self-employed individuals, farms with
fewer than 11 employees, employers regulated
by other Federal safety and health laws, and
Federal, State, and local government agencies
are excluded from the survey.
The survey is a Federal-State coopera­
tive program with an independent sample
selected for each participating State. A strati­
fied random sample with a Neyman alloca­
tion is selected to represent all private in­
dustries in the State. The survey is stratified
by Standard Industrial Classification and
size o f employment.

Definitions
Under the Occupational Safety and Health
Act, employers maintain records of nonfa­
tal work-related injuries and illnesses that
involve one or more o f the following: loss
o f consciousness, restriction of work or mo­
tion, transfer to another job, or medical
treatment other than first aid.

O ccupational injury is any injury such
as a cut, fracture, sprain, or amputation that
results from a work-related event or a
single, instantaneous exposure in the work
environment.
Occupational illness is an abnormal con­
dition or disorder, other than one resulting
from an occupational injury, caused by ex­
posure to factors associated with employ­
ment. It includes acute and chronic illnesses
or disease which may be caused by inhala­
tion, absorption, ingestion, or direct contact.
Lost workday injuries and illnesses are
cases that involve days away from work, or
days o f restricted work activity, or both.
Lost w orkdays include the number of
workdays (consecutive or not) on which the
employee was either away from work or at
work in some restricted capacity, or both, be­
cause of an occupational injury or illness. BLS
measures o f the number and incidence rate
of lost workdays were discontinued begin­
ning with the 1993 survey. The number of
days away from work or days o f restricted
work activity does not include the day of in­
jury or onset of illness or any days on which
the employee would not have worked, such
as a Federal holiday, even though able to
work.
Incid en ce rates are computed as the
number o f injuries and/or illnesses or lost
work days per 100 full-time workers.

Notes on the data
The definitions o f occupational injuries and
illnesses are from R e c o r d k e e p in g G u id e ­
lin e s f o r O c c u p a tio n a l I n ju r ie s a n d I l l ­
n e ss e s (U.S. Department of Labor, Bureau

o f Labor Statistics, September 1986).
Estimates are made for industries and em­
ployment size classes for total recordable
cases, lost workday cases, days away from
work cases, and nonfatal cases without lost
workdays. These data also are shown sepa­
rately for injuries. Illness data are available for
seven categories: occupational skin diseases
or disorders, dust diseases o f the lungs, respi­
ratory conditions due to toxic agents, poison­
ing (systemic effects of toxic agents), disor­
ders due to physical agents (other than toxic
materials), disorders associated with repeated
trauma, and all other occupational illnesses.
The survey continues to measure the num­
ber of new work-related illness cases which
are recognized, diagnosed, and reported dur­
ing the year. Some conditions, for example,
long-term latent illnesses caused by exposure
to carcinogens, often are difficult to relate to
the workplace and are not adequately recog­
nized and reported. These long-term latent ill-

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Current Labor Statistics

nesses are believed to be understated in the
survey’s illness measure. In contrast, the over­
whelming majority o f the reported new ill­
nesses are those which are easier to directly
relate to workplace activity (for example, con­
tact dermatitis and carpal tunnel syndrome).
Most o f the estimates are in the form o f
incidence rates, defined as the number of in­
juries and illnesses per 100 equivalent full­
time workers. For this purpose, 200,000 em­
ployee hours represent 100 employee years
(2,000 hours per employee). Full detail on
the available measures is presented in the an­
nual bulletin, O c c u p a tio n a l In ju ries a n d Ill­
n e sses: C o u n ts, R a tes, a n d C h a ra c te ristic s.

Comparable data for more than 40 States
and territories are available from the BLS Of­
fice o f Safety, Health and Working Condi­
tions. Many of these States publish data on
State and local government employees in ad­
dition to private industry data.
Mining and railroad data are furnished to
BLS by the Mine Safety and Health Adminis­
tration and the Federal Railroad Administra­
tion. Data from these organizations are in­
cluded in both the national and State data pub­
lished annually.
With the 1992 survey, bls began publish­
ing details on serious, nonfatal incidents re­
sulting in days away from work. Included are
some major characteristics of the injured and
ill workers, such as occupation, age, gender,
race, and length o f service, as well as the cir­
cumstances of their injuries and illnesses (na­
ture of the disabling condition, part o f body
affected, event and exposure, and the source
directly producing the condition). In general,
these data are available nationwide for detailed

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industries and for individual States at more
aggregated industry levels.
For additional information on occupa­
tional injuries and illnesses, contact the Of­
fice o f Occupational Safety, Health and
Working Conditions at (202) 691-6180, or
access the Internet at:
http://ww w.bls.gov/iif/

Census of Fatal
Occupational Injuries
The Census o f Fatal Occupational Injuries
compiles a complete roster o f fatal job-re­
lated injuries, including detailed data about
the fatally injured workers and the fatal
events. The program collects and cross
checks fatality information from multiple
sources, including death certificates, State
and Federal workers’ compensation reports,
Occupational Safety and Health Administra­
tion and Mine Safety and Health Adminis­
tration records, medical examiner and au­
topsy reports, media accounts, State motor
vehicle fatality records, and follow-up ques­
tionnaires to employers.
In addition to private w age and salary
workers, the self-em ployed, fam ily mem­
bers, and Federal, State, and local g o v ­
ernment workers are covered by the pro­
gram. To be included in the fatality cen ­
sus, the decedent must have been em ­
ployed (that is working for pay, com pen­
sation, or profit) at the time o f the event,
en g a g ed in a le g a l work a c tiv ity , or
present at the site o f the incident as a re­
quirement o f his or her job.

September 2004

Definition
A fatal work injury is any intentional or un­
intentional wound or damage to the body re­
sulting in death from acute exposure to energy,
such as heat or electricity, or kinetic energy
from a crash, or from the absence of such es­
sentials as heat or oxygen caused by a specific
event or incident or series of events within a
single workday or shift. Fatalities that occur
during a person’s commute to or from work
are excluded from the census, as well as workrelated illn esses, which can be difficult
to identify due to long latency periods.

Notes on the data
Twenty-eight data elements are collected,
coded, and tabulated in the fatality program,
including information about the fatally in­
jured worker, the fatal incident, and the ma­
chinery or equipment involved. Summary
worker demographic data and event charac­
teristics are included in a national news re­
lease that is available about 8 months after
the end of the reference year. The Census of
Fatal Occupational Injuries was initiated in
1992 as a joint Federal-State effort. Most
States issue summary information at the
time o f the national news release.
For additional information on the
Census of Fatal Occupational Injuries con­
tact the bls Office o f Safety, Health, and
Working Conditions at (202) 691-6175, or
the Internet at:
http://www.bls.gov/iif/

1.

Labor market indicators
2002

III

II

2004

2003

2002

2003

1

IV

III

II

IV

II

I

Employment data
E m ploym ent s t a t u s of th e civilian noninstitutional
population (h o u s e h o ld s u rv e y ):1
L ab o r fo rc e p artic ip a tio n r a te ....................................................................

6 6 .6

6 6 .2

6 6 .7

6 6 .6

6 6 .5

6 6 .3

6 6 .4

6 6 .2

66.1

6 6 .0

6 5 .9

E m plo y m en t-p o p u latio n ra tio .....................................................................

6 2 .7

6 2 .3

6 2 .8

6 2 .8

6 2 .5

6 2 .4

6 2 .3

62.1

6 2 .3

6 2 .2

6 2 .2

U n e m p lo y m en t r a te .......................................................................................

5 .8

6.0

5 .9

5 .8

5 .9

5 .8

6.1

6.1

5 .9

5 .6

5 .6

M en ...................................................................................................................

5 .9

6 .3

6 .0

5 .9

6.1

6.1

6 .5

6 .4

6.1

5 .7

5 .7

12.8

13.4

12.8

13.1

12.5

12.6

14.0

13.8

13.1

12.5

1 2 .9

4 .7

5 .0

4 .8

4 .7

4 .9

5 .0

5 .2

5.1

4 .9

4 .5

4 .5

5 .6

5 .7

5 .7

5 .6

5 .7

5 .5

5 .7

5 .8

5 .6

5 .6

5 .4

11.1

11.4

11.2

10.9

11.4

11.2

11.8

11 .5

10.9

11.1

10.9

4 .6

4 .6

4 .8

4 .6

4 .6

4 .5

4 .6

4 .7

4 .6

4 .5

4 .4

W o m e n ............................................................................................................

E m ploym ent, n o n fa rm (payroll d a ta ), in th o u s a n d s :1
T otal n o n fa rm ...................................................................................................

130,341

129,932

1 3 0 ,389

1 3 0,287

1 3 0 ,2 4 8

1 3 0 ,0 4 7

1 2 9 ,8 7 8

1 2 9 ,8 2 0

1 3 0 ,0 0 2

1 3 0 ,3 6 7

1 3 1 ,1 4 8

T otal p riv a te .......................................................................................

1 0 8 ,8 2 8

1 0 8 ,356

1 0 8 ,895

1 0 8,736

1 0 8 ,6 5 4

1 0 8 ,4 2 8

1 0 8 ,3 0 9

1 0 8 ,2 6 0

1 0 8 ,4 5 3

1 0 8 ,8 2 7

1 0 9 ,5 9 6

G o o d s -p ro d u c in g .....................................................................................

2 2 ,5 5 7

2 1 ,8 1 7

2 2 ,6 3 8

2 2 ,4 6 6

2 2 ,2 5 2

2 2 ,0 2 5

2 1 ,8 4 8

2 1 ,7 1 8

2 1 ,6 7 6

2 1 ,7 1 9

2 1 ,8 6 3

M an u factu rin g ........................................................................................

1 5,259

14 ,5 2 4

1 5 ,3 4 7

1 5,197

1 4,979

1 4,775

1 4,570

1 4,410

14 ,3 4 0

1 4 ,3 2 6

1 4 ,3 7 7

S e rv ice -p ro v id in g .....................................................................................

1 0 7,789

1 0 8,115

107,751

107,821

1 0 7 ,9 9 5

1 0 8 ,0 2 2

1 0 8,030

1 0 8 ,1 0 2

1 0 8 ,3 2 6

1 0 8 ,6 4 8

1 0 9 ,2 8 5

A v e ra g e h ours:
3 3 .9

33 .7

3 3 .9

3 3 .9

3 3 .8

3 3 .8

3 3 .7

3 3 .6

3 3 .7

3 3 .8

3 3 .7

M an u factu rin g .............................................................................................

4 0 .5

4 0 .4

4 0 .6

4 0 .4

4 0 .4

4 0 .4

4 0 .2

4 0 .2

4 0 .6

4 1 .0

4 0 .9

O v e rtim e ...................................................................................................

4 .2

4 .2

4 .3

4 .3

4 .2

4 .2

4.1

4.1

4 .4

4 .6

4 .6

All w o rk e rs (excluding farm , h o u s e h o ld a n d F e d e ra l w o rk ers).....

3 .4

3 .8

.9

.9

.6

1.4

.8

1.1

.5

1.4

.9

P riv ate industry w o rk e rs ...........................................................................

3 .2

4 .0

1.1

.6

.4

1.7

.8

1.0

.4

1.5

.9

G o o d s -p r o d u d n g 3 ..................................................................................

3 .7

4 .0

.9

.6

.9

1.8

.9

.7

.5

2 .3

.9

3.1

4 .0

1.2

.6

.2

1.5

.8

1.1

.5

1.1

1.0

4.1

3 .3

.4

2 .2

.9

.7

.4

1.7

.5

.7

.4

Employment Cost Index2
P e rc e n t c h a n g e in th e ECI, c o m p e n sa tio n :

S erv ice -p ro v id in g 3..................................................................................
S ta te a n d local g o v e rn m e n t w o rk ers
W o rk ers by b arg ain in g s ta tu s (private industry):
U nion....................................................................................................................

4 .2

4 .6

1.0

1.2

.9

1.6

1.2

1.0

.7

2 .8

1 .5

N o n u n io n ............................................................................................................

3 .2

3 .9

1.1

.5

.4

1.6

.8

1.0

.4

1.3

.8

1 Q u a rterly d a t a s e a s o n a lly a d ju s te d .

NOTE:

2 A nnual c h a n g e s a r e D e c e m b e r-to -D e c e m b e r c h a n g e s . Q u a rterly c h a n g e s a r e ca lcu lated

controls. N onfarm d a t a reflect t h e co n v e rsio n to th e 2 0 0 2 v ersio n of th e N orth A m erican

u sin g t h e la s t m onth of e a c h q u arte r.
3

G o o d s-p ro d u c in g in d u strie s in clu d e m ining, co n stru c tio n , a n d m anufacturing. S e rv ic e ­

B eginning in J a n u a ry 2 0 0 3 , h o u s e h o ld su rv e y d a ta reflect re v is e d population

Industry C lassification S y s te m (NAICS), re placing t h e S ta n d a rd Industrial C lassification (SIC)
s y s te m . NAiCS-based d a t a by industry a r e no t c o m p a ra b le w ith s i c - b a s e d d a ta .

providing in d u strie s in clu d e all o th e r private s e c to r industries.


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Federal Reserve Bank of St. Louis

Monthly Labor Review

September 2004

73

Current Labor Statistics: Comparative Indicators

2.

Annual and quarterly percent changes in compensation, prices, and productivity
Selected m easures

2002

2002

2003
II

2003

III

IV

I

II

2004
III

IV

1

II

Compensation data1,2
E m p lo y m e n t C o s t In d e x — c o m p e n s a tio n (w a g e s ,
s a la r ie s , b e n e fits ):
C ivilian n o n fa rm ...........................................
P riv a te n o n fa rm .................................................

3 .4

3 .8

0 .9

0 .9

0 .6

1 .4

0 .8

1.1

0 .5

1 .4

0 .9

3 .2

4 .0

1.1

.6

.4

1 .7

.8

1 .0

.4

1 .5

.9

2 .9

2 .9

.8

.7

.4

1.0

.6

.9

.3

.6

.6

2 .7

3 .0

1.0

.4

.3

1.1

.7

.8

.4

.7

.7

2 .3

2 .3

.5

.6

-.1

1 .8

- .3

- .2

-.2

1 .2

1.2

E m p lo y m e n t C o s t In d e x — w a g e s a n d s a la r ie s :
C ivilian n o n fa rm .............................................
P riv a te n o n fa rm ................................................

Price data1
C o n s u m e r P ric e In d e x (All U rb a n C o n s u m e r s ) : All Ite m s .......
P r o d u c e r P ric e In d ex :
F in is h e d g o o d s .......................................
F in is h e d c o n s u m e r g o o d s ..........................
C a p ita l e q u i p m e n t ..........................................
In te r m e d ia te m a te r ia ls , s u p p lie s , a n d c o m p o n e n ts ........
C r u d e m a t e r ia l s ...................................................

3 .2

3 .2

.2

.2

-.1

3 .7

- .8

.3

.0

1 .2

1 .2

4 .2

4 .2

.4

.0

-.3

2 .4

1 .8

.3

.0

1 .5

1 .4

.4

.4

- .3

- .7

.6

.6

- .6

- .1

.0

.6

5

4 .6

4 .6

1.1

1.1

.1

6 .5

- 2 .1

- .1

.0

2 5

a i)

2 5 .2

2 5 .2

37.1

1 .9

6 .5

2 8 .0

-1 0 .6

3 .4

1 4 .4

6 .0

7 .6

Productivity data3
O u tp u t p e r h o u r of all p e r s o n s :
B u s in e s s s e c t o r ..................................................

4 .3

4 .5

1 .7

4 .8

1.2

3 .9

7 .6

8 .5

2 .4

3 .9

N o n fa rm b u s i n e s s s e c t o r ............................

1 .5

4 .4

4 .4

1.1

4 .5

1 .6

3 .7

6 .7

9 .0

3.1

3 .7

2 .5

N o n fin a n c ia l c o r a o r a t io n s 4 .......................

4 .4

5 .4

4 .9

4.1

3 .4

3 .2

9.1

9 .4

5 .0

.2

1 .4

A nnual

changes

are

D e c e m b e r - to - D e c e m b e r

c a lc u la te d u s in g t h e la s t m o n th of e a c h q u a r te r.

ch an g es.

Q u a rte rly

changes

are

C o m p e n s a tio n a n d p ric e d a t a a r e n o t

s e a s o n a l l y a d j u s t e d , a n d t h e p ric e d a t a a r e n o t c o m p o u n d e d .

b y c o m p a rin g a n n u a l a v e r a g e s .

Q u a rte rly p e r c e n t c h a n g e s re fle c t a n n u a l r a t e s o f c h a n g e in q u a r te rly i n d e x e s .
T h e d a t a a r e s e a s o n a l l y a d ju s te d .

2 E x c lu d e s F e d e r a l a n d p riv a te h o u s e h o ld w o rk e rs .

3.

3 A n n u a l r a te s of c h a n g e a r e c o m p u te d

4

O u tp u t p e r h o u r of all e m p lo y e e s .

Alternative measures of wage and compensation changes
Q uarterly change
C om ponents

2003

Four quarters ending—
2004

2003

IV

2004
IV

A v e r a g e h o u rly c o m p e n s a t io n : 1
All p e r s o n s , b u s i n e s s s e c t o r ...........................................................................

4 .0

All p e r s o n s , n o n fa rm b u s i n e s s s e c t o r ........................................................

4 .2

E m p lo y m e n t C o s t In d e x — c o m p e n s a tio n :
C ivilian n o n fa rm 2 ....................................................................................................
P riv a te n o n f a r m ..................................................................................................
U n io n .....................................................................................................................
N o n u n io n .............................................................................................................
S ta t e a n d lo c a l g o v e r n m e n t s .......................................................................

3 .7

3 .9

3 .5

4 .0

5 .0

6.0

3 .3

3 .5

4.1

3 .4

E m p lo y m e n t C o s t In d e x — w a g e s a n d s a la r ie s :
C ivilian n o n fa rm 2 ...................................................................................................
P riv a te n o n f a r m ..................................................................................................
U n io n .....................................................................................................................
N o n u n io n .............................................................................................................
S ta t e a n d lo ca l g o v e r n m e n t s ......................................................................
1 S e a s o n a ll y a d ju s te d . " Q u a rte rly a v e r a g e " is p e r c e n t c h a n g e from a q u a r te r a g o , a t a n a n n u a l ra te .
2 E x c lu d e s F e d e r a l a n d h o u s e h o ld w o rk e rs .

74

Monthly Labor Review


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Federal Reserve Bank of St. Louis

September 2004

2 .9

2 .9

2 .5

3 .0

2.6

2.6

3 .0
2 .4

3.1

3.1

2 .5

2 .3

2.1

1 .9

2 .9

4.

Employment status of the population, by sex, age, race, and Hispanic origin, monthly data seasonally adjusted

[Numbers in thousands]
2002

2004

2003

Annual average
2003

July

Aug.

Sept.

Oct.

Nov.

Dec.

Jan.

Feb.

Mar.

Apr.

May

June

July

2 2 1 ,1 6 8

2 2 1 ,2 5 2

2 2 1 ,5 0 7

2 2 1 ,7 7 9

2 2 2 ,0 3 9

2 2 2 ,2 7 9

2 2 2 ,5 0 9

222,161

2 2 2 ,3 5 7

2 2 2 ,5 5 0

2 2 2 ,7 5 7

2 2 2 ,9 6 7

2 2 3 ,1 9 6

2 2 3 ,4 2 2

1 4 6 ,5 1 0
66 .2
1 3 7 ,7 3 6

1 4 6 ,6 5 2

1 4 6 ,6 2 2
66 .2
1 3 7 ,6 9 3

1 4 6 ,6 1 0
66.1
1 3 7 ,6 4 4

1 4 6 ,8 9 2
66 .2
1 3 8 ,0 9 5

1 4 7,187

1 4 6,878
6 6 .0
1 3 8 ,4 7 9

1 4 6 ,8 6 3

146,471

1 4 6 ,6 5 0

146,741

1 4 6 ,9 7 4

1 4 7 ,2 7 9

66.1
1 3 8 ,5 6 6

6 5 .9
138,301

65 .9
1 3 8 ,2 9 8

6 5 .9
1 3 8 ,5 7 6

6 5 .9
1 3 8 ,7 7 2

6 6 .0
139,031

1 4 7 ,8 5 6
66 .2
1 3 9 ,6 6 0

TOTAL
Civilian noninstitutional
p o p u la tio n 1............................... 2 1 7 ,5 7 0
Civilian lab o r fo r c e ................. 1 4 4 ,8 6 3
66 .6
P articip atio n r a te ..........
E m p lo y ed ............................ 1 3 6 ,4 8 5

6 6 .3
1 3 7 ,6 0 4

6 6 .2
1 3 8 ,5 3 3

E m p lo y m e n t-p o p ulation ratio2................
U n e m p lo y e d .......................

6 2 .7

62 .3

6 2 .2

6 2 .2

62.1

6 2 .2

62 .3

6 2 .2

6 2 .4

62 .2

62.1

62 .2

6 2 .2

6 2 .3

6 2 .5

8 ,3 7 8

8 ,7 7 4

9 ,0 4 8

8 ,9 2 9

8 ,9 6 6

8 ,7 9 7

8 ,6 5 3

8 ,2 9 7

8 ,1 7 0

8 ,2 0 3

8 ,2 4 8

8 ,1 9 6

5.8
7 2 ,7 0 7

6 .0
7 4 ,6 5 8

6 .2
7 4 ,6 0 0

6.1
7 4 ,8 8 4

6.1
7 5 ,1 6 8

6.0
7 5 ,1 4 7

5.9
7 5 ,0 9 3

75,631

5 .6
7 5 ,2 9 8

5 .6
7 5 ,8 8 6

8 ,3 5 2
5.7

8 ,1 6 4

U n e m p lo y m en t ra te ....
Not in th e lab o r f o r c e .........

8 ,3 9 8
5 .7

7 5 ,9 0 0

5.6
7 6 ,0 1 6

5 .6
7 5 ,9 9 3

5 .6
7 5 ,9 1 6

5 .5
7 5 ,5 6 5

9 6 ,4 3 9

9 8 ,2 7 2

9 8 ,3 0 4

9 8 ,4 3 4

9 8 ,5 6 8

9 8 ,6 9 6

9 8 ,8 1 4

9 8 ,9 2 7

9 8 ,8 6 6

9 8 ,9 6 6

9 9 ,0 6 5

9 9 ,1 7 0

9 9 ,2 7 9

9 9 ,3 9 6

9 9 ,5 1 2

7 3 ,6 3 0
7 6 .3
6 9 ,7 3 4

7 4 ,6 2 3
75 .9

7 4 ,6 6 0
75 .9

7 4 ,6 8 2

7 4 ,9 0 5
7 6 .0

7 4 ,9 4 2

7 5 ,0 4 4

75,171

7 4 ,7 9 7

74,871

75 .6
7 0 ,9 6 9

7 5 ,3 7 2
7 5 .8

7 0 ,2 6 9

7 6 .0
7 1 ,3 2 9

7 5 ,0 4 8
7 5 .6
7 1 ,1 6 2

7 5 ,5 7 7

7 5 .9

7 5 ,0 1 8
75 .7

7 0 ,4 1 5

7 5 ,1 8 8
76.1
7 0 ,9 6 4

Men, 20 years and over
Civilian noninstitutional
p o p u la tio n 1...............................
Civilian lab o r fo r c e .................
P articipation r a te ..........
E m p lo y ed ............................
E m p lo y m e n t-p o p -

7 5 .9
7 0 ,3 2 4

7 0 ,5 9 6

7 5 .9
7 0 ,7 2 6

7 1 ,0 9 9

7 1 ,1 2 8

7 5 .5
7 1 ,1 1 8

7 1 ,5 7 0

7 5 .9
7 1 ,8 4 7

ulation ratio2................

72 .3

71 .7

7 1 .5

7 1 .4

71 .6

71 .7

71.8

71 .9

72.1

71.7

7 1 .8

71 .7

7 1 .7

7 2 .0

7 2 .2

U n e m p lo y e d .......................
U n e m p lo y m en t ra te ....
Not in t h e lab o r fo r c e ..........

3 ,8 9 6

4 ,2 0 9

4,391

4 ,3 5 8

4 ,3 0 9

4 ,2 1 6

4 ,2 2 4

3 ,9 4 5

3,8 4 2

3 ,8 2 8

3 ,7 5 3

3 ,7 3 0

5 .6
2 3 ,6 4 9

5 .9
2 3 ,6 4 4

5 .8
23,751

5.8
2 3 ,6 6 3

5.6
2 3 ,7 5 4

5 .6
2 3 ,6 2 0

5 .3
2 3 ,8 8 2

5.1
2 3 ,6 9 4

5.1
2 4 ,1 6 8

5.0
2 4 ,2 9 9

3 ,8 8 6
5.2
24,231

3 ,8 0 2

5 .3
2 2 ,8 0 9

3 ,8 9 0
5 .2
2 4 ,0 4 7

5.0
2 4 ,0 2 3

4 .9
2 3 ,9 3 5

1 0 5 ,1 3 6

1 0 6 ,8 0 0

1 0 6 ,8 3 9

1 0 6 ,9 5 7

1 0 7 ,0 8 0

1 0 7 ,1 9 7

1 0 7 ,3 0 3

1 0 7 ,4 0 4

107,131

1 0 7 ,2 1 6

1 0 7 ,2 9 9

1 0 7 ,3 8 9

1 0 7 ,4 8 3

1 0 7 ,5 8 6

1 0 7 ,6 8 7

6 3 ,6 4 8
6 0 .5

6 4 ,7 1 6

6 4 ,8 3 6

6 4 ,6 0 8

6 4 ,8 9 9

6 4 ,9 1 7

6 4 ,7 8 5

6 4 ,8 1 3

6 4 ,8 9 3

6 5 ,1 2 2

61,521

6 1 ,2 6 0

6 1 ,4 5 6

60 .3
6 1 ,3 7 3

60 .3
61,571

6 0 .3
61,721

6 0 .5

6 1 ,4 7 9

6 0 .5
6 1 ,5 9 7

6 0 .3

6 1 ,4 0 2

6 0 .5
6 1 ,5 2 4

60 .3

6 0 ,4 2 0

6 0 .3
61,191

6 4 ,5 1 5
6 0 .2

6 4 ,6 8 7

6 0 .6
6 1 ,4 6 7

6 4 ,8 4 6
6 0 .4

6 4 ,6 2 9

60 .6

6 4 ,8 3 5
6 0 .7

6 1 ,6 2 9

6 1 ,9 1 8

Women, 20 years and over
Civilian noninstitutional
p o p u la tio n 1...............................
Civilian lab o r fo r c e ................
P articipation r a te ..........
E m p lo y m e n t-p o p U n e m p lo y e d .......................
U n e m p lo y m en t ra te ....
Not in th e lab o r fo r c e .........

5 7 .5

5 7 .5

5 7 .5

5 7 .5

57.1

57 .4

57 .4

57 .3

57 .2

5 7 .3

5 7 .2

57 .3

5 7 .4

5 7 .3

5 7 .5

3 ,2 2 8
5.1
4 1 ,4 8 8

3 ,3 1 4
5.1

3 ,3 6 9
5 .2
42,121

3 ,4 1 7

3 ,3 2 0
5.1
4 2 ,3 8 7

3,3 2 6
5.1
4 2 ,5 5 8

3 ,2 5 5
5 .0
4 2 ,6 1 7

3 ,1 7 2
4.9
4 2 ,5 8 7

5.1
4 2 ,6 1 3

3 ,2 1 5
5 .0
4 2 ,6 0 4

3 ,0 9 2
4 .8

3 ,2 6 4

5 .3
4 2 ,4 7 2

3 ,3 7 5
5 .2
4 2 ,2 9 9

3 ,3 1 4

4 2 ,6 7 0

5 .0
4 2 ,6 9 3

3 ,2 0 4
4 .9

4 2 ,0 8 3

3 ,3 5 6
5 .2
4 2 ,0 0 4

4 2 ,5 6 5

15 ,9 9 4

1 6,096

1 6,109

16 ,1 1 6

16,131

1 6,145

1 6 ,162

1 6,178

1 6 ,1 6 4

1 6 ,1 7 5

1 6,186

1 6 ,1 9 8

1 6 ,2 0 5

1 6 ,2 1 4

1 6,222

7 ,5 8 5
4 7 .4
6 ,3 3 2

7 ,1 7 0

7 ,1 5 7

7 ,1 0 4

7 ,0 9 7

7,051

7 ,0 8 2

6,9 8 7

7,1 7 7

7 ,0 4 5

6 ,9 4 5

7 ,0 8 5

7 ,1 1 3

7 ,0 1 4

7 ,1 5 7

4 4 .5
5 ,9 1 9

4 4 .4
5 ,8 5 6

44.1
5 ,9 0 2

4 4 .0
5 ,8 5 7

4 3 .7
5 ,8 4 6

43 .8
5 ,9 7 2

43 .2
5 ,8 5 9

4 4 .4
5 ,9 7 7

43 .6
5 ,8 7 5

4 2 .9
5 ,7 9 7

43 .7
5 ,8 8 8

4 3 .9
5 ,8 8 8

4 3 .3
5 ,8 3 2

44.1
5 ,8 9 6

Both sexes, 16 to 19 years
Civilian noninstitutional
p o p u la tio n 1...............................

E m p lo y m e n t-p o p U n e m p lo y e d .......................
U n e m p lo y m en t ra te ...

39 .6

3 6 .8

3 6 .4

3 6 .6

3 6 .3

36 .2

3 7 .0

36 .2

3 7 .0

3 6 .3

35 .8

3 6 .3

3 6 .3

3 6 .0

36 .3

1,253

1,251
17.5
8 ,9 2 6

1,301
18.2
8 ,9 5 2

1,202

1 ,2 4 0

16.1
9,191

1,200
16.7
8 ,9 8 7

1,170
16.6
9 ,1 3 0

1,148
16.5
9 ,2 4 0

1,197
16.9
9 ,1 1 3

1 ,2 2 5
17.2
9 ,0 9 2

1,181
16.8
9 ,2 0 0

1,262

17.5
9 ,0 3 4

1,109
15.7

1,128

16.9
9 ,0 1 2

1 ,2 0 5
17.1
9 ,0 9 4

16.5
8 ,4 0 9

9 ,0 8 0

17.6
9 ,0 6 5

White3
Civilian noninstitutional
p o p u la tio n 1.............................

1 7 9 ,7 8 3

1 8 1 ,2 9 2

181,341

1 8 1 ,5 1 2

1 8 1 ,6 9 6

181,871

1 8 2,032

1 8 2 ,1 8 5

1 8 1 ,8 7 9

182,001

182,001

1 8 2 ,2 5 2

1 8 2 ,3 8 4

182,531

1 8 2 ,6 7 6

1 2 0 ,5 4 6
6 6 .5
1 1 4 ,2 3 5

1 2 0 ,6 4 5
6 6 .5
1 1 4 ,0 8 6

1 2 0 ,6 5 8
6 6 .5
1 1 4 ,1 5 6

120,411
6 6 .3
1 1 4 ,0 1 5

1 2 0 ,7 3 6
66 .4
1 1 4 ,5 3 5

121,041

P articip atio n r a te ..........

1 2 0 ,1 5 0
66 .8
1 1 4 ,0 1 3

120,751
6 6 .3
1 1 4 ,6 7 8

1 2 0 ,7 2 3
6 6 .4
1 1 4 ,7 6 5

1 2 0 ,5 4 0
6 6 .2
1 1 4 ,6 0 2

1 2 0 ,5 4 2
6 6 .2
1 1 4 ,4 3 3

1 2 0 ,6 7 5
66 .2
1 1 4 ,7 1 2

1 2 0 ,9 8 4
6 6 .3
1 1 4 ,9 7 6

1 2 1 ,1 8 0
6 6 .4
1 1 5 ,1 5 2

1 2 1 ,4 2 8
6 6 .5
1 1 5 ,6 2 3

6 6 .5
1 1 4 ,7 8 3

E m p lo y m e n t-p o p ulation ratio2................

6 3 .4

6 3 .0

6 2 .9

6 2 .9

6 2 .8

6 3 .0

63.1

6 2 .9

63.1

63 .0

62 .8

6 2 .9

6 3 .0

63.1

63 .3

U n e m p lo y m en t ra te ...
N ot in t h e lab o r f o r c e .........

6,1 3 7
5.1
5 9 ,6 3 3

6,311
5 .2
6 0 ,7 4 6

6 ,5 5 9
5 .4

6 ,3 9 7
5.3
6 1 ,2 8 5

6 ,2 0 0
5.1
6 1 ,1 3 5

6 ,2 5 8
5 .2
60,991

6 ,0 7 3
5 .0
6 1 ,4 3 4

5 ,9 5 8
4 .9
6 1 ,1 5 6

5 ,9 3 8
4.9

6 0 ,6 9 6

6 ,5 0 2
5.4
6 0 ,8 5 4

6 1 ,4 6 0

6 ,1 0 9
5.1
6 1 ,5 7 9

5 ,9 6 3
4 .9
6 1 ,5 7 7

6 ,0 0 8
5 .0
6 1 ,4 0 0

6 ,0 2 8
5 .0
61,351

5 ,8 0 5
4 .8
6 1 ,2 4 8

2 5 ,5 7 8

2 5 ,6 8 6

2 5 ,7 0 2

2 5 ,7 4 2

2 5 ,7 8 4

2 5 ,8 2 5

2 5 ,8 6 0

2 5 ,8 9 4

2 5 ,8 6 7

2 5 ,9 0 0

2 5 ,9 3 2

2 5 ,9 6 7

2 6 ,0 0 2

2 6 ,0 4 0

2 6 ,0 7 8

1 6 ,5 6 5
64 .8

1 6,526

1 6 ,5 6 3
6 4 .4

1 6 ,5 8 5
64 .4

1 6 6 ,6 7 7

1 6,589
64 .2

1 6 ,5 2 4

1 6 ,3 6 5
6 3 .2
1 4 ,679

1 6,602

1 6 ,404

1 6 ,5 9 5

6 4 .2

6 3 .3
1 4,804

64.0
1 4,909

1 6 ,4 8 5
6 3 .5
1 4,878

1 6 ,4 4 2
6 3 .2

1 6 ,5 0 6
6 3 .4

1 6 ,7 5 5
64 .3

1 4 ,8 1 8

1 4 ,8 3 3

1 4,926

Black or African American3
Civilian noninstitutional

1 4 ,8 7 2

64 .3
1 4,739

1 4,727

14,771

6 4 .7
1 4,826

14,696

6 3 .9
1 4,812

1 4,886

E m p lo y m e n t-p o p 58.1

57 .4

5 7 .3

5 7 .4

5 7 .5

5 6 .9

57 .3

5 6 .7

5 7 .5

57 .2

57 .2

57 .3

5 7 .0

5 7 .0

5 7 .2

1,787

U n e m p lo y m en t ra te ...

1,6 9 3
10.2

1,851
11.1
9 ,1 0 7

1,712
10.4

9 ,2 3 6

9 ,3 3 6

1,686
10.3
9,5 2 9

1,736
1 0 .5

9 ,0 1 3

1,813
10.9
9 ,1 2 7

1,893
11.4

Not in th e lab o r fo rc e ........

1,836
11.1
9 ,1 3 9

1,600
9 .8
9 ,4 9 5

1,686
10.2
9 ,3 3 7

1,607
9 .7
9 ,4 8 2

1,624
9 .9
9 ,5 6 0

1,673
10.1
9 ,5 3 4

1,829
10.9
9 ,3 2 3

10.8
9,161

9 ,2 6 5

S e e fo o tn o te s a t e n d of ta b le .


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

Monthly Labor Review

September 2004

75

Current Labor Statistics:

Labor Force Data

4. Continued—Employment status of the population, by sex, age, race, and Hispanic origin, monthly data seasonally adjusted
[Numbers in thousands]
Annual average

Employment status

2003

2004

2002

2003

July

Aug.

Sept.

Oct.

Nov.

Dec.

Jan.

Feb.

Mar.

Apr.

May

June

July

DODulation1..............................
Civilian lab o r fo r c e ................

2 5 ,9 6 3

27,551

2 7 ,5 9 7

2 7,701

27,791

2 7 ,8 7 9

2 7 ,9 6 8

18,811

P articip atio n r a te ..........
E m p lo y ed ............................

1 8 ,6 9 3

1 9,010

1 9 ,0 6 4

69.1

6 8 .3
1 7,372

1 9 ,3 1 3

2 8 ,0 5 9
1 9 ,3 0 4

2 8 150

1 8 ,843

2 8 ,1 1 6
19 ,0 3 5

2 7 ,7 0 5

18 ,7 7 0

2 7 ,9 1 3
1 8,940

2 7 ,6 1 9

1 8,813

2 7 ,8 0 8
1 8,877

2 8 ,0 1 6

1 7 ,943

6 8 .0
1 7 ,2 4 7

6 8 .0
173 83

67 .9

68 .3
1 7,709

6 7 .7

6 8 .4

6 8 .4

69.1

68 8

19 4 5 0
69 1

1 7 ,7 8 4

68.1
17,441

6 7 .5

1 7,456

6 7 .9
1 7,556

1 7 ,3 0 3

1 7 ,5 9 6

1 7 ,693

1 7 ,9 5 8

1 8 ,0 1 9

1 8 ,1 1 8

6 2 .5

6 2 .8

6 2 .8

6 2 .9

63 .2

63 .3

6 3 .2

1,353

63.1
1,441
7 .7
8 ,7 3 8

1,460
7 .8

1,421
7 .5
8,931

1,383
7.3
8 ,9 7 4

1,416
7 .4

1 ,3 7 0
7.3
8 ,8 0 7

64 2
1 285

1 ,3 3 2

7 .4

8,891

1,250
6 .6
9 ,0 8 2

6 3 .5
1,371

64 .2

1,523
8.1
8 ,8 2 8

6 3 .3
1,4 1 4

7 .5
8 ,0 2 0

6 2 .5
1,389
7 .4
9 ,0 1 2

8,781

7 .2
8 ,8 1 5

Hispanic or Latino
ethnicity
Civilian noninstitutional

1 6 ,590

1 9 ,1 2 5

E m p lo y m e n t-p o p ulation ratio2...............
U n e m p lo y e d .......................

63 .9

U n e m p lo y m en t ra te ....
Not in th e lab o r fo rc e ............

8 ,8 5 8

1,3 5 5
7 .0
8 ,6 5 4

6 7
8 ,7 5 5

8 ,7 0 0

T h e p o p u latio n fig u re s a r e no t s e a s o n a lly a d ju s te d .
NOTE: E s tim a te s for th e a b o v e ra c e g ro u p s (w hite a n d blac k o r A frican A m erican) d o no t sum
2 Civilian em p lo y m en t a s a p e rc e n t of th e civilian noninstitutional p o pulation.

to to ta ls b e c a u s e d a t a a r e no t p re s e n te d for all ra c e s . In addition, p e r s o n s w h o s e ethnicity is

3 B eginning in 2 0 0 3 , p e r s o n s w ho s e le c te d th is ra c e g ro u p only; p e r s o n s w ho s e le c te d

identified a s H ispanic o r Latino m ay b e of an y ra c e a n d , th e re fo re , a r e c la ssifie d by ethnicity a s

m o re th a n o n e r a c e g ro u p a r e not in clu d ed . Prior to 2 0 0 3 , p e r s o n s w h o re p o rte d m o re

well a s by ra c e . B eginning in J a n u a ry 2 0 0 3 , d a ta reflect re v is e d popu latio n c o n tro ls u s e d in th e
h o u s e h o ld su rv e y .

th a n o n e r a c e w e re in clu d ed in th e g ro u p th e y identified a s th e m ain ra c e .

5.

S e le c te d e m p lo y m e n t in dicators, m o n th ly d a ta s e a s o n a lly a d ju s te d

[In t h o u s a n d s ] ________________

Selected categories

Annual average
2002
2003

2003

2004

July

Aug.

Sept.

Oct.

Nov.

137,693

137,644

64,431

64,155

138,095
73,643
64,452

138,533
73,915
64,618

44,566

44,684

45,152

45,431

34,684

34,612

34,993

35,076

35,034

Dec.

Jan.

Feb.

Mar.

Apr.

May

June

July

138,566
74,343
64,223

138,301
73,901
64,400

138,298
74,006
64,292

138,576
74,053
64,523

138,772
74,035
64,737

139,031
74,476
64,555

139,660
74,822
64,838

45,490

45,128

45,043

44,735

44,723

44,938

44,935

34,585

34,502

34,256

34,339

34,522

34,461

34,599

Characteristic
Em ployed, 16 y e a rs an d over..

136,845
72,903
63,582

137,736
73,332
64,404

137,604
73,149
64,455

44,116

44,653

44,747

34,155

34,695

34,648

4,213

4,701

4,661

4,896

4,800

4,880

4,788

4,714

4,437

4,733

4,574

4,665

4,513

4,490

2,788

3,118

3,113

3,063

3,185

3,030

3,226

3,205

2,996

2,865

3,011

2,819

2,853

2,803

2,660

1,124

1,279

1,296

1,201

1,334

1,356

1,350

1,295

1,380

1,347

1,427

1,439

1,467

1,404

1,500

18,843

19,014

19,089

19,482

19,021

18,935

19,110

18,561

18,905

18,900

19,006

19,000

19,621

19,531

19,741

4,119

4,596

4,568

4,404

4,794

4,690

4,782

4,727

4,613

4,328

4,622

4,471

4,605

4,442

4,400

2,726

3,052

3,071

2,989

3,127

2,964

3,153

3,144

2,911

2,778

2,927

2,756

2,812

2,762

2,605

1,114

1,264

1,273

1,191

1,335

1,349

1,353

1,279

1,399

1,340

1,414

1,431

1,476

1,387

1,496

18,487

18,658

18,651

19,016

18,633

18,628

18,752

18,367

18,636

18,691

18,693

18,664

19,220

19,072

19,290

138,479
74,085
64,394

M arried m en, s p o u s e
M arried w om en, s p o u s e

Persons at work part time1
All industries:
P art tim e for econom ic
S lack work or b u sin ess
Could only find part-tim e
P art tim e for noneconom ic
N onagricultural industries:
P art tim e for econom ic
S lack work or b u sin ess
Could only find part-tim e
P art tim e for noneconom ic

Excludes p e rs o n s "with a job but not a t work" during th e survey period for such re a s o n s a s vacation, illness, or industrial disputes.
NOTE:

76

Beginning in J an u a ry 2003, d a ta reflect revised population controls u se d in th e household survey.

Monthly Labor Review


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

September 2004

6. Selected unemployment indicators, monthly data seasonally adjusted
[Unemployment rates]____________________________________
2004

2003

Annual average
Selected categories
2002

Sept.

Aug.

July

2003

Oct.

Nov.

Dec.

Jan.

Feb.

Mar.

Apr.

May

June

July

Characteristic
T o ta l, 1 6 y e a r s a n d o ld e r ...................................

5 .8

6 .0

6 .2

6.1

6.1

6 .0

5 .9

5 .7

5 .6

5 .6

5 .7

5 .6

5 .6

5 .6

5 .5

19 y e a r s ..........................

1 6 .5

1 7 .5

1 8 .2

1 6 .9

1 7 .5

17.1

1 5 .7

16.1

1 6 .7

1 6 .6

1 6 .5

1 6 .9

1 7 .2

1 6 .8

1 7 .6

M en , 2 0 y e a r s a n d o ld e r...............................

5 .3

5 .6

5 .9

5 .8

5 .8

5 .6

5 .6

5 .3

5 .3

5.1

5 .2

5 .0

5 .2

5 .0

4 .9

W o m e n , 2 0 y e a r s a n d o ld e r ........................

5.1

5.1

5 .2

5 .2

5 .3

5 .2

5.1

5.1

5 .0

4 .9

5.1

5 .0

4 .8

5 .0

4 .9

B o th s e x e s , 1 6 to

W h ite , to ta l1........................................................

5.1

5 .2

5 .4

5 .4

5 .3

5.1

5 .2

5 .0

4 .9

4 .9

5.1

4 .9

5 .0

5 .0

4 .8

1 4 .5

1 5 .2

1 5 .7

15.1

15.1

1 4 .3

1 4 .3

1 4 .8

14.1

1 5 .2

1 4 .8

1 5 .7

1 5 .7

1 4 .8

1 4 .9

M e n , 16 to 19 y e a r s ..............................

1 5 .9

17.1

1 7 .9

1 6 .5

1 7 .6

1 5 .9

1 6 .8

1 6 .3

1 4 .0

1 5 .5

1 6 .2

1 7 .9

1 8 .6

1 6 .4

1 5 .5

W o m e n , 1 6 to 1 9 y e a r s .......................

13.1

1 3 .3

1 3 .3

1 3 .7

1 2 .6

1 2 .6

1 1 .5

13.1

1 4 .2

1 4 .9

1 3 .3

1 3 .3

1 2 .7

1 3 .2

1 4 .3

M en , 2 0 y e a r s a n d o l d e r ........................

4 .7

5 .0

5 .3

5 .3

5 .0

4 .9

5 .0

4 .7

4 .5

4 .5

4 .7

4 .5

4 .7

4 .5

4 .3

W o m e n , 2 0 y e a r s a n d o ld e r.................

4 .4

4 .4

4 .4

4 .4

4 .5

4 .4

4 .4

4 .3

4 .4

4 .2

4 .4

4 .2

4.1

4 .4

4 .2

B la ck o r A frican A m e ric a n , to ta l1.............

1 0 .2

1 0 .8

11.1

1 0 .9

11.1

1 1 .4

1 0 .4

1 0 .3

1 0 .5

9 .8

1 0 .2

9 .7

9 .9

10.1

1 0 .9

2 9 .8

3 3 .0

35.1

2 9 .8

3 2 .7

3 7 .3

2 8 .9

2 7 .3

3 2 .5

25 .1

2 9 .4

2 8 .3

3 2 .5

3 2 .6

3 7 .0

M en , 1 6 to 1 9 y e a r s ..............................

3 1 .3

3 6 .0

37.1

2 7 .8

3 4 .2

4 0 .9

3 2 .5

2 8 .4

42.1

2 9 .6

3 6 .6

3 0 .9

3 0 .3

3 3 .9

3 7 .8

W o m e n , 1 6 to 19 y e a r s .......................

2 8 .3

3 0 .3

3 3 .4

3 1 .5

3 1 .4

3 3 .2

2 5 .7

2 6 .5

2 5 .8

2 1 .9

2 2 .8

26.1

34.1

3 1 .4

3 6 .3

M en , 2 0 y e a r s a n d o ld e r ........................

9 .5

1 0 .3

1 0 .3

1 0 .5

1 1 .0

1 0 .5

10.1

9 .3

9 .6

9 .4

9 .2

9 .3

9 .3

9 .3

1 0 .3

W o m e n , 2 0 y e a r s a n d o ld e r ..................

8 .8

9 .2

9 .6

9 .7

9 .2

9 .8

9.1

9 .7

9.1

8 .8

9 .3

8 .7

8 .4

8 .9

9.1

H is p a n ic o r L a tin o e th n ic ity ........................

7 .5

7 .7

8.1

7 .8

7 .5

7 .3

7 .4

6 .6

7 .3

7 .4

7 .4

7 .2

7 .0

6 .7

6 .8

M a rrie d m e n , s p o u s e p r e s e n t ...................

3 .6

3 .8

3 .9

3 .9

3 .8

3 .8

3 .7

3 .3

3 .3

3 .4

3 .2

3.1

3.1

3 .2

3 .2

M a rrie d w o m e n , s p o u s e p r e s e n t ............

3 .7

3 .7

3 .9

3 .9

3 .9

3 .8

3 .8

3 .9

3 .7

3 .6

3 .7

3 .7

3 .3

3 .7

3 .5

5 .9

6.1

6 .3

6 .2

6 .2

6.1

6.1

5 .8

5 .7

5 .6

5 .8

5 .6

5 .7

5 .6

5 .6

5 .2

5 .5

5 .5

5 .3

5 .7

5 .5

5.1

5 .3

5 .4

5 .2

5 .4

5 .3

5 .2

5 .5

5 .2

L e s s t h a n a hig h s c h o o l d ip lo m a ...................

8 .4

8 .8

8 .8

9 .3

8 .7

8 .8

8 .5

8.1

8 .8

8 .5

8 .8

8 .7

8 .8

8 .8

8 .3

H igh s c h o o l g r a d u a t e s , n o c o lle g e 3.............

5 .3

5 .5

5 .5

5 .4

5 .4

5 .5

5 .4

5 .5

4 .9

5 .0

5 .3

5 .2

5 .0

5.1

5.1

S o m e c o lle g e o r a s s o c i a t e d e g r e e ...............

4 .5

4 .8

5 .0

4 .7

4 .8

4 .8

4 .8

4 .5

4 .5

4 .4

4 .7

4.1

4 .0

4 .2

4 .2

B a c h e lo r 's d e g r e e a n d h ig h e r4.......................

2 .9

3.1

3.1

3.1

3 .2

3.1

3.1

3 .0

2 .9

2 .9

2 .9

2 .9

2 .9

2 .7

2 .7

P a rt-tim e w o r k e r s ...........................................

Educational attainment2

'

3 In c lu d e s hig h s c h o o l d ip lo m a o r e q u iv a le n t.

B e g in n in g in 2 0 0 3 , p e r s o n s w h o s e l e c t e d th is r a c e g ro u p only; p e r s o n s w h o

4 In c lu d e s p e r s o n s w ith b a c h e lo r 's , m a s t e r 's , p ro f e s s io n a l, a n d d o c to ra l d e g r e e s .

s e l e c t e d m o re t h a n o n e r a c e g ro u p a r e n o t in c lu d e d . P rio r to 2 0 0 3 , p e r s o n s w h o
re p o r te d m o re t h a n o n e r a c e w e r e in c lu d e d in th e g ro u p th e y id en tified a s t h e
m a in r a c e .

NOTE: B eg in n in g in J a n u a r y 2 0 0 3 , d a t a re fle c t r e v is e d p o p u la tio n c o n tro ls u s e d in t h e

2 D a ta re f e r to p e r s o n s 2 5 y e a r s a n d o ld e r.

h o u s e h o ld s u rv e y .

7. Duration of unemployment, monthly data seasonally adjusted
[Numbers in thousands]
Weeks of
unemployment

M edian d u ra tio n , in w e e k s .................

2002

2003

2004

2003

Annual average
July

Aug.

Sept.

Oct.

Nov.

Dec.

Jan.

Feb.

Mar.

Apr.

May

June

July

2 ,8 9 3

2 ,7 8 5

2 ,7 3 5

2 ,7 4 9

2 ,7 3 3

2 ,6 2 2

2 ,6 2 7

2 ,6 1 2

2 ,4 6 8

2 ,5 8 9

2 ,7 9 2

2 ,7 0 7

2 ,6 8 8

2 ,8 0 5

2 ,5 8 0

2 ,6 1 2

2 ,6 9 8

2 ,6 3 0

2 ,7 3 6

2 ,5 8 5

2 ,5 5 6

2 ,4 5 0

2 ,3 9 4

2 ,4 1 2

2 ,4 1 4

2 ,3 6 9

2 ,3 7 6

2 ,4 0 5

2 ,4 7 6

2 ,9 0 4

3 ,3 7 8

3 ,5 5 9

3,561

3,511

3 ,4 7 8

3 ,4 8 4

3 ,4 0 3

3 ,3 6 5

3 ,2 7 4

3 ,3 2 0

2 ,9 6 9

3 ,0 7 7

3 ,0 6 5

2 ,8 7 8

1,369

1,442

1,598

1,561

1,438

1,460

1,448

1,5 1 3

1 ,4 6 7

1 ,4 0 3

1,332

1,170

1,288

1,306

1,211

1,535

1,936

1,961

2,001

2 ,0 7 3

2 ,0 1 8

2 ,0 3 6

1,890

1,898

1,871

1,9 8 8

1,800

1,789

1,759

1,667

16.6

19.2

19.3

19.2

19.6

19.4

20 .0

19.6

19.8

2 0 .3

20.1

19 .7

2 0 .0

19.9

18.6

9.1

10.1

10.1

10.0

10.1

10.3

10.4

10.4

10.7

1 0 .3

10.3

9 .5

10.0

10.8

8.9

2 ,7 3 9

N o t e : B eginning in J a n u a ry 2 0 0 3 , d a ta reflect re v is e d popu latio n c o n tro ls u s e d in th e h o u s e h o ld su rvey.


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Federal Reserve Bank of St. Louis

Monthly Labor Review

September 2004

77

Current Labor Statistics:

Labor Force Data

8. Unemployed persons by reason for unemployment, monthly data seasonally adjusted
[Numbers in thousands]
Reason for
unemployment
J o b lo s e rs 1.................................

Annual average
2002

2003

2003

2004

July

Aug.

Sept.

Oct.

Nov.

Dec.

Jan.

Feb.

Mar.

Apr.

May

June

July

4 ,9 4 7
1,173
3 ,7 7 4

4 ,9 3 9
1,092
3 ,8 4 7

4 ,9 4 7

4 ,8 7 7
1,097

4 ,7 1 9
1,055
3 ,6 6 4

4 ,6 1 8
1,060

4 ,3 8 2

4 ,3 2 3
1,064
3 ,2 5 8
827

4 ,6 0 7

4 ,3 9 9
994

4,211

4 ,0 9 9

4,181
1 ,0 6 5
3 ,1 1 6
895

4 ,6 0 7
1 ,1 2 4

4 ,8 3 8
1,121

3 ,4 8 3
866
2 ,3 6 8

3 ,7 1 7
818
2 ,4 7 7

798
2 ,5 2 2

536

641

661

J o b l o s e r s 1...................

5 5 .0

55.1

5 5 .4

5 5 .4

55 .6

5 5 .2

5 4 .2

54.6

5 2 .3

5 2 .4

O n te m p o ra ry layoff..........................
Not on te m p o ra ry layoff..................
J o b le a v e r s ..............................................

13.4

13.1
4 2 .3
8 .9

1 2 .5
43.1
9 .4

12.1
42.1

12.5
4 2 .0

12.9

12.2

39 .8

42 .0

4 1 .6

10.7

10.0

30 .0

2 9 .4

7 .3

8.1

8.2

9.8
2 8 .5
7 .4

10.1

2 8 .3
6 .4

9 .3
2 8 .0

12.3
4 0 .0
9.6

R e e n tr a n ts ..............................................
N ew e n tr a n ts .......................................

12.3
4 3 .2
8 .9
2 8 .4

12.4

4 1 .6
10.3

12.8
4 2 .4

O n te m p o ra ry layoff..........................
Not on te m p o ra ry layoff..................
J o b le a v e r s .............................................
R e e n tr a n ts .............................................
N ew e n tr a n ts ......................................

1,110
3 ,8 3 7

790

836

2 ,5 3 0
650

2 ,4 3 6
684

3 ,7 8 0
789
2 ,5 1 8
653

931

3 ,5 5 8
783

1,028
3 ,3 5 3
804

2 ,4 4 0
619

2 ,3 6 6
694

2 ,5 0 9
681

2 ,4 2 4
676

1,040
3 ,5 6 7
836
2 ,4 2 4
627

3 ,4 0 5
822
2 ,3 1 4

926
3 ,2 8 6
846
2 ,4 3 8

1,011
3 ,0 8 8
902
2 ,4 3 5
636

2 ,3 3 0

645

713

53 .8

5 1 .3

5 0 .8

12.1

11.3
4 0 .0
10.3
2 9 .7

12.5

13 .2

3 8 .3

3 8 .5

680

Percent of unemployed

9 .3
2 8 .2

4 2 .8
8 .9

7.3

2 8 .2
7 .4

3.2

3.3

3 .4

3 .4

3 .4

3 .3

3.2

3.1

.6
1.6
.4

.6
1.7
.4

.5
1.7
.5

.5
1.7
.4

.6
1.7

.5
1.7
.4

.6
1.7
.4

1.6
.5

2 7 .4
7 .7

2 8 .5
7 .4

2 8 .0
7.1

8 .2

54 .2

2 8 .3
7 .9

8 .7

5 1 .7

11.2

11.1

3 0 .2
7 .9

2 8 .8
8 .4

2.8
.6

2.8

1.7

1.6

-A .

— Ë.

Percent of civilian
labor force
J o b l o s e r s 1.........................
J o b le a v e r s ...............................................
R e e n tr a n ts ...............................................
N ew e n tr a n ts ......................................

.5

.5

1 In c lu d e s p e r s o n s w h o co m p le te d te m p o ra ry jo b s .

.6

N O TE: B eginning in J a n u a ry 2 0 0 3 , d a ta reflect re v is e d pop u latio n co n tro ls u s e d in th e h o u s e h o ld su rv e y .

9. Unemployment rates by sex and age, monthly data seasonally adjusted
[Civilian workers]
Sex and age

Annual average
2002

T otal, 16 y e a rs a n d o ld e r.....................
16 to 2 4 y e a r s .....................................
16 to 19 y e a r s .................................
16 to 17 y e a r s .............................
18 to 19 y e a r s .............................
2 0 to 2 4 y e a r s .................................

5 .8
12.0
16.5
18.8
15.1
9 .7

2 5 y e a rs a n d o ld e r............................
2 5 to 5 4 y e a r s .............................
5 5 y e a rs a n d o ld e r.....................

4 .6
4 .8
3 .8

M en, 16 y e a rs a n d o ld e r...................
16 to 2 4 y e a r s ..................................
16 to 19 y e a r s ...............................
16 to 17 y e a r s ...........................
18 to 19 y e a r s ...........................
2 0 to 2 4 y e a r s ...............................

5 .9
12.8
18.1
21.1
16.4
10.2
4 .7

2003
6 .0
12.4
17 .5
19.1
16.4
10.0
4 .8
5 .0
4.1

6 .2
12.9
18.2
2 0 .3
16.8
10.4
5 .0
5.1
4 .2

6 .3
13.4

6.6
14.4

19.3
2 0 .7
18.4

2 0 .4
2 2 .3
19.0
11.6
5 .2

5 5 y e a rs a n d o ld e r..................

4 .8
4.1

10.6
5 .0
5 .2
4 .4

W o m e n , 16 y e a rs a n d o ld e r.............
16 to 2 4 y e a r s ...................................

5 .6
11.1

5 .7
11.4

16 to 19 y e a r s ...............................
16 to 17 y e a r s ...........................
18 tO 19 y e a r s ...........................
2 0 to 2 4 y e a r s ...............................
2 5 y e a rs a n d o ld e r..........................
2 5 to 5 4 y e a r s ...........................

14.9
16.6
13.8
9.1
4 .6
4 .8

15.6
17.5
14.2

5 5 y e a rs a n d o l d e r '.................

3 .6

2 5 y e a rs a n d o ld e r..........................
2 5 to 5 4 y e a r s ...........................

2003
July

5.3
4 .6
5 .7

Aug.

Sept.

6.1
12.4
16.9
18.8
15.7

6.1
12.8
17.5
19.3
16.2

10.2
5 .0
5.1
4.1

10.6
4 .9
5.1
4 .0

6 .4

6 .4

12.9
17.6
2 0 .6
15.6
10.7
5 .2
5.4
4 .4

14.1
19.6
22.1
18.2
11.7
5.0
5 .2
4 .2

5 .8
11.8

5.8
11.4

16.2
17.0
15.8
9 .7
4 .7

15.2
16.5
14.1

4 .8

15.9
18.3
14.5
9 .0
4.7
4 .9

4 .8

9 .5
4 .7
4 .9

3 .7

4 .2

4 .5

3 .8

9 .3
4 .6

11.3

2004

Oct.

Nov.

6 .0
12.3
17.1
2 0 .2
15.2
10.1
4.9
5.1
3.8

5 .9
12.1
15.7
17 .5
14.7
10.4

6.2
13.2
18.7
2 0 .4
17.9

6 .2
13.4

4 .8
5.0
3 .9

Monthly Labor Review

September 2004

9.6
4 .7
4 .9
3 .9

5 .6
12.0
16.7
18.2
15.7
9 .8
4 .5
4 .7
3 .7

Feb.
5 .6
11.8
16.6
17.6
15.7
9 .5
4 .5
4 .7
3 .8

May

June

14 .5
9.6
4 .6
4 .9
3 .8

4 .5
4 .6
3 .8

5.8
12.6

5.7

5 .8

5 .6

12.8

13.0
19.1
2 3 .3
16.6

12.8
18.1
2 2 .8
15.8
10.4
4 .4
4 .4

11.8
16 .5
19.4

10.5
4 .5
4 .7
3 .6

10.0
4 .5
4 .7
3 .7

5 .5
10.7

5 .6
10.7

5.6
11.3

5 .5
11.2

15.4
20.1
12.5
9.3
4 .7
4 .9

13.0
16.6
11.1
9 .6
4 .6

14.7
18.2
12.2
8 .8
4 .6

16.0
15.9
15.6
8 .9
4 .4

4 .8

5 .0

15.9
17.1
15.2
8 .9
4 .6
4 .8

4 .5

16.9
13.0
8 .9
4 .6
4 .9

3 .4

3 .5

3 .5

4.1

3 .9

3 .5

11.3

1 7 .5
19.3
16.2

Apr.
5 .6
11.6
16.9
2 0 .2
14.7
9 .2

4 .7
4 .9
4 .0

5.7

5.7
12.2
17.2
19.4
15.7

5 .7

5 .0
5 .2
4.1

10.8
5.0
5 .2
4 .0

5 .7
12.7

Mar.

18.3
18.3
18.1
11.2

No t e : B eginning in J a n u a r y 2 0 0 3 , d a ta reflect re v is e d popu latio n c o n tro ls u s e d in t h e h o u s e h o ld survey.

78

5.7
11.7
16.1
18.3
14.7

Jan.

5.8
12.6
17.4
18.4
16.9
10.4

1 D a ta a r e no t s e a s o n a lly a d ju s te d .


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

Dec.

18.3
2 2 .3
15.8
10.1
4 .6
4 .8
3.8
5 .6
10.8
14.7

19.1
2 3 .4
16.5
10.0
4 .4
4 .5
3 .9
5 .4

5 .6
12.1
17.2
2 1 .6
14.7
9 .7
4 .4
4 .5
3 .9

10.3
4 .6
4 .7
4.1

10.3

5 .3
11.1

14.5
17.3
12.6

15.3
20.1
12.7

8.3
4 .6
4 .7
3 .3

5 .6
12.0
16.8
20 .6
14.3
9 .8
4 .5
4 .5
3 .9

4 .3
5 .6

July
5 .5
12.0
17.6
2 0 .2
16.1
9 .3
4 .4
4 .6
3 .7
5 .5
12.2
17.7
2 1 .2
15.7
9 .7
4 .4
4 .5
3 .8

11.2

5 .6
11.7

9 .0
4 .2
4 .4

15.6
18.7
12.6
9 .0
4 .5
4 .7

17.5
19.4
1 6 .5
8 .8
4 .5
4 .7

3 .3

3 .8

3 .8


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

10. Unemployment rates by State, seasonally adjusted
State

June

May

June

2003

2004p

2004p

A la b a m a ....................................................................

State

June

May

June

2003

2004p

2004p

5 .9

5 .9

5 .8

5.1

5 .2

8 .0

7 .3

7 .3

4 .8

4 .7

4 .8

5 .8

5.1

4 .7

4.1

3 .7

3 .3

6 .2

5 .8

5 .7

5 .5

4.1

4 .2

6 .8

6 .3

6 .3

4 .2

4 .0

3 .9

6.1

4 .9

4 .9

5 .9

4 .9

4 .7

5 .5

4 .6

4 .6

6 .7

5 .4

5 .4

4 .3

3 .8

3 .8

6 .3

5 .8

6 .2

7.1

7 .5

7.1

6 .6

5 .3

5 .5

5 .3

4 .6

4 .8

3 .9

3 .2

3.1

4 .8

3 .9

4 .0

6 .2

5 .6

5 .8

4 .4

3 .0

3.1

6 .0

4 .4

4 .9

5 .5

4 .5

5 .0

8 .7

6 .6

6 .4

5 .9

5 .6

5.1

5 .6

5 .0

5 .2

4 .8

5 .4

5 .6

5 .8

4 .5

4 .3

4 .3

7 .0

6 .3

6 .6

5 .6

4 .7

4 .7

3 .6

3 .4

3 .4

6 .3

5 .4

5 .5

5 .9

4 .8

5 .3

6 .9

6.1

6 .0

5 .0

4.1

4.1

M issouri

U ta h ............................................................................

6 .8

6 .9

6 .8

5 .9

4 .5
5 .7

5 .6

4 .6

4 .6
3 .4

4 .5

3 .9

3 .9

4 .6

3 .5

5 .8

5 .2

5 .3

4.1

3 .5

3 .5

7 .3

6 .6

6 .5

7 .7

6.1

6.1

5 .0

4 .3

4 .4

6 .3

5 .2

5 .3

6 .8

5 .6

5 .4
W y o m in g ...................................................................

5 .6

5.1

5 .0

5 .6

5.1

5 .0

p = p re lim in a ry

11. Employment of workers on nonfarm payrolls by State, seasonally adjusted
[In thousands]
State

June

May

June

2003

2004p

2004p

State

June

May

June

2003

2004p

2004p

A la b a m a .......................

2 ,1 4 8 ,1 8 2

2 ,1 5 9 ,1 2 5

2 ,1 5 6 ,9 8 9

M is s o u ri.......................................................

3 ,0 2 6 ,7 2 4

3 ,0 1 6 ,5 1 8

3 ,0 2 2 ,7 7 6

A la s k a ...........................

3 3 1 ,2 1 7

3 4 4 ,5 3 7

3 4 4 ,0 8 8

M o n ta n a .....................................................

4 7 5 ,5 4 3

4 7 7 ,5 2 1

4 8 1 ,3 0 7

A riz o n a ..........................

2 ,6 8 9 ,8 5 9

2 ,7 5 3 ,0 0 9

2 ,7 5 0 ,9 8 7

N e b r a s k a ....................................................

9 7 5 ,6 3 9

9 8 8 .1 8 2

9 8 6 ,4 4 8

A r k a n s a s ......................

1 ,2 6 0 ,8 3 7

1 ,3 1 9 ,9 4 7

1 ,3 1 5 ,1 9 3

N e v a d a ........................................................

1 ,1 4 0 ,3 3 6

1 ,1 7 8 ,2 9 1

1 ,1 8 3 ,7 6 9

C a lifo rn ia ......................

1 7 ,4 6 2 ,7 1 7

1 7 ,6 1 8 ,1 7 7

1 7 ,6 5 8 ,5 8 7

N e w H a m p s h ir e ......................................

7 1 8 ,6 0 3

7 2 6 ,8 8 8

7 2 8 ,9 9 0

4 ,3 6 9 ,9 2 3

4 ,4 0 3 ,6 2 2

4 ,4 0 1 ,9 9 3

C o lo r a d o ......................

2 ,4 7 9 ,5 3 3

2 ,5 1 6 ,1 9 2

2 ,5 1 8 ,7 6 7

C o n n e c tic u t................

1 ,8 0 3 ,0 9 1

1 ,7 9 7 ,6 5 1

1 ,7 9 2 ,7 5 7

N e w M e x ic o ..............................................

8 9 8 ,3 2 0

9 0 5 ,4 9 2

9 0 6 ,3 7 0

D e la w a r e ......................

4 1 6 ,8 1 0

4 2 5 ,2 1 0

4 2 7 ,0 5 4

N e w Y ork ...................................................

9 ,3 0 8 ,8 7 8

9 ,2 6 7 ,1 8 2

9 ,3 0 8 ,2 6 8

2 9 8 ,6 3 2

N e w J e r s e y ...............................................

D istrict of C o lu m b ia .

3 0 3 ,7 3 7

2 9 9 ,7 8 6

N o rth C a ro lin a .........................................

4 ,2 2 7 ,5 9 6

4 ,1 9 6 ,4 9 6

4 ,1 9 7 ,3 1 7

F lo rid a ...........................

8 ,1 5 4 ,2 8 9

8 ,3 4 0 ,8 0 6

8 ,6 8 1 ,4 8 0 N o rth D a k o ta ..............................................

3 4 6 ,1 7 3

3 4 9 ,5 7 7

3 4 9 ,7 9 9

G e o r g i a ........................

4 ,4 1 4 ,4 7 7

4 ,4 0 6 ,9 8 5

4 ,4 1 3 ,1 7 0

O h io ..............................................................

5 ,9 2 0 ,6 0 6

5 ,8 4 3 ,8 3 9

5 ,8 5 0 ,4 7 9

H a w a ii...........................

6 1 7 ,0 5 7

6 2 9 ,8 7 6

6 2 9 ,4 0 4

O k la h o m a ...................................................

1 ,7 0 1 ,8 5 0

1 ,6 9 4 ,3 9 1

1 ,7 0 9 ,8 6 4

Id a h o ..............................

6 9 3 ,0 0 4

7 0 1 ,0 7 0

7 0 5 ,9 1 1

O r e g o n .........................................................

1 ,8 7 0 ,3 1 8

1 ,8 8 3 ,0 9 8

1 ,8 4 9 ,2 4 3

Illinois............................

6 ,3 2 5 ,4 8 6

6 ,3 9 2 ,7 2 4

6 ,3 4 2 ,4 1 2

P e n n s y lv a n ia ............................................

6 ,1 6 4 ,8 2 8

6 ,2 5 3 ,8 0 2

6 ,2 3 8 ,8 1 6

In d ia n a ..........................

3 ,1 8 9 ,4 3 3

3 ,1 6 7 ,4 3 2

3 ,1 7 7 ,9 7 3

R h o d e Is la n d ............................................

5 7 5 ,1 8 7

5 6 8 ,8 6 3

5 6 9 ,1 8 4

Io w a ...............................

1 ,6 1 1 ,7 4 9

1 ,6 3 1 ,7 1 1

1 ,6 2 3 ,0 6 4

S o u th C a ro lin a .........................................

2 ,0 0 4 ,5 8 5

2 ,0 5 1 ,0 5 7

2 ,0 6 4 ,9 2 6

K a n s a s ..........................

1 ,4 3 6 ,6 4 4

1 ,4 6 3 ,8 3 6

1 ,4 6 4 ,7 4 0

4 2 4 ,6 7 7

4 2 4 ,2 0 4

4 2 4 ,5 9 7

K e n tu c k y ......................

1 ,9 5 7 ,6 9 7

1 ,6 8 7 ,9 9 1

1 ,9 8 6 ,3 7 6

T e n n e s s e e .................................................

2 ,9 0 5 ,3 7 2

2 ,9 3 0 ,5 4 8

2 ,9 2 1 ,0 2 2

L o u is ia n a .....................

2 ,0 3 8 ,3 4 8

2 ,0 2 4 ,3 3 6

2 ,0 3 1 ,8 1 8

T e x a s ...........................................................

1 0 ,9 0 5 ,7 5 5

1 0 ,9 5 6 ,1 8 1

1 0 ,9 3 3 ,5 2 3

M a in e ........................... .

6 9 1 ,2 8 5

7 0 0 ,8 2 3

6 9 9 ,9 0 0

U ta h ..............................................................

1 ,1 8 1 ,8 3 9

1 ,2 0 6 ,3 5 0

1 ,2 0 5 ,9 6 3

M a ry la n d ......................

2 ,9 0 3 ,6 3 6

2 ,9 5 4 ,3 7 6

2 ,9 4 5 ,6 5 4

V e rm o n t......................................................

3 5 0 ,9 4 2

M a s s a c h u s e t t s .........

3 ,4 1 5 ,4 7 2

3 ,4 0 8 ,5 3 9

3 ,4 0 9 ,1 6 7

V irg in ia........................................................
W a s h in g to n ...............................................

3 ,7 7 0 ,3 8 6

3 ,8 4 6 ,2 6 0

3 ,8 4 7 ,8 0 2

3 ,1 3 1 ,5 5 2

3 ,2 0 4 ,4 3 7

3 ,2 1 6 ,2 8 3

3 5 2 ,3 0 6

3 5 3 ,4 3 7

M ic h ig a n ......................

5 ,0 4 8 ,2 8 2

5 ,0 6 5 ,9 2 5

5 ,0 3 8 ,2 1 1

M in n e s o ta ...................

2 ,9 2 2 ,0 3 1

2 ,9 5 1 ,3 6 9

2 ,9 5 2 ,7 7 3

W e s t V irg in ia............................................

7 8 9 ,5 2 9

7 9 5 ,5 0 9

7 9 8 ,9 5 0

M is s is s ip p i..................

1 ,3 1 8 ,8 8 0

1 ,3 1 7 ,1 1 8

1 ,3 1 6 ,6 8 3

W is c o n s in ..................................................

3 ,0 8 1 ,1 3 1

3 ,1 1 5 ,6 0 2

3 ,1 1 6 ,9 9 7

W y o m in g ....................................................

2 7 8 ,3 1 5

2 7 8 ,1 8 6

2 7 8 ,9 7 9

p = p re lim in ary .
N o t e : S o m e d a t a in th is ta b le m a y differ from d a t a p u b lis h e d e l s e w h e r e b e c a u s e o f t h e c o n tin u a l u p d a tin g o f t h e d a t a b a s e .

Monthly Labor Review

September 2004

79

Current Labor Statistics:

Labor Force Data

12. Employment of workers on nonfarm payrolls by industry, monthly data seasonally adjusted
[In thousands]___________
Industry

Annual average
2002

TOTAL NONFARM...........
TOTAL PRIVATE.................
GOODS-PRODUCING...............
Natural resources and
mining................................

July

Aug.

Sept.

2004
Oct.

Nov.

Dec.

Jan.

Feb.

Mar.

Apr.

May

Junep

July11

130,341

129,931

1 2 9 ,8 1 4

1 2 9 ,7 8 9

1 2 9 ,8 5 6

1 2 9 ,9 4 4

1 3 0 ,0 2 7

1 3 0 ,0 3 5

1 3 0,194

1 3 0 ,2 7 7

1 3 0 ,6 3 0

1 3 0 ,954

1 3 1 ,1 6 2

1 3 1 ,2 4 0

1 3 1 ,2 7 2

1 0 8 ,8 2 8

1 0 8,356

1 0 8 ,3 8 4

1 0 8 ,4 8 3

108,491

1 0 8 ,6 6 7

1 0 8 ,7 3 8

1 0 9 ,0 7 7

1 0 9 ,382

1 0 9 ,6 1 8

109,711

1 0 9 ,7 4 3

2 1 ,8 1 7

1 0 8 ,2 0 9
2 1 ,7 1 2

1 0 8 ,3 1 7

2 2 ,5 5 7

1 0 8 ,2 5 3
2 1 ,7 4 4

2 1 ,6 9 7

2 1 ,6 7 4

2 1 ,6 8 6

2 1 ,6 6 8

2 1 ,6 9 6

2 1 ,6 8 4

2 1 ,7 7 8

2 1 ,8 2 2

2 1 ,8 9 4

2 1 ,8 9 6

2 1 ,9 1 4

571
6 8 .2
5 0 2 .7

569
6 7 .5
5 0 1 .8

571

570
65.1
505.1

64 .2
508.1

581
6 5 .9
5 1 4 .9

585
6 6 .7
5 1 8 .5

589

6 7 .6
5 0 3 .4

570
65 .9
5 0 4 .3

572

6 8 .5
5 0 2 .3

6 5 .6
5 2 3 .2

589
6 4 .4
524.1

593
64.1

123.9

124.6

126.9

128.9

130.0

131.0

132.3

131.8

5 2 8 .4
131.7
2 1 1 .7

583
70.4

L o gging .........................................
M ining.................................................

2003

2003

5 1 2 .2
121.£

571

568
6 7 .4

569
67 .9
5 0 1 .5
124.1

122.9

123.5

12 3 .2

5 0 0 .8
123.6

M inina, e x c e p t oil a n d a a s 1....
C oal m in in q ..................................
S u p p o rt activities for m in in g ...

2 1 0 .6

2 0 2 .7

2 0 4 .3

2 0 3 .6

2 0 1 .6

202.1

2 0 2 .4

2 0 2 .0

2 0 0 .0

2 0 0 .6

2 0 2 .8

2 0 5 .2

2 0 7 .8

2 0 9 .0

7 4 .4
179.8

70 .4
176.8

7 1 .6
174.9

7 0 .7
1 7 5 .0

69 .2
175.6

6 9 .6
175.3

6 9 .5
177.1

6 9 .8
177.7

69.6
178.2

7 0 .2
178.6

7 0 .6
182.1

Construction........................

71.8
182.3

72 9
183.1

73 Q
18 3 .3

1 8 5 .0

6 ,7 1 6

6 ,7 2 2

6,721

6 ,7 3 9

6 ,7 5 4

6 ,7 5 4

6,771

6 ,7 7 4

6 ,8 1 2

6,791

6 ,8 5 3

6 ,8 7 2

6 ,9 0 9

6 ,9 1 2

6 ,9 1 6

1,5 7 0 .0

1,6 2 2 .9

Oil a n d g a s e x tra c tio n ...............

C o n stru ctio n of b u ild in q s..........

1,5 7 4 .8

H e av y a n d civil e n g in e e rin g ...
S p ecia lity t r a d e c o n tra c to rs .....

9 3 0 .6
4 ,2 1 0 .4

Manufacturing......................

15,259

4 ,2 3 5 .5
1 4 ,5 2 5

P ro d u ctio n w o rk e rs ...............

10 ,7 6 6

1 0,200

Durable goods....................

9,483

8 ,9 7 0

1 ,5 7 5 .9
91 0 .7

1,5 6 6 .4

1,5 7 7 .7

1,5 7 9 .4

1,5 8 3 .9

1,5 9 0 .9

1,6 0 7 .6

9 1 5 .2

9 1 8 .8

9 2 8 .0

1 ,6 0 9 .8
9 2 4 .7

14,351

4 ,2 6 8 .6
1 4,344

4 ,2 6 8 .4
1 4 ,3 2 4

4 ,2 9 0 .2
1 4 ,3 1 4

9 2 4 .0
4 ,2 7 6 .5
14,321

9 2 6 .8

4 ,2 6 0 .9
1 4 ,3 7 5

9 1 0 .8
4 ,2 6 3 .7

1,585.1
9 2 0 .7

1 ,5 9 3 .3

9 1 3 .9
4 ,2 5 5 .5
1 4 ,4 0 4

4 ,3 1 8 .9
1 4 ,3 4 4

1 0,136
8 ,9 0 8

1 0 ,1 0 4

1 0 ,0 7 7

10 ,0 4 8
8 ,8 7 4

1 0 ,0 3 5

1 0 ,0 3 8

8 ,8 6 7

1 0 ,0 5 8
8 ,8 5 4

1 0 ,0 4 4

8 ,8 8 6

8 ,8 6 8

8 ,8 6 9

8 ,8 8 2

6 ,1 0 4
5 3 2 .4

6 ,0 6 6
5 3 3 .4

6 ,0 7 9
53 6 .6

6,081

6 ,0 8 8
5 3 8 .4

9 1 0 .6
4,244.1
1 4 ,4 5 2

P ro d u ctio n w o rk e rs ................

6 ,5 2 9

6 ,1 5 7

W o o d p ro d u c ts ..............................
N onm etallic m ineral p ro d u c ts
P rim ary m e ta ls .............................

5 5 4 .9
5 1 6 .0
5 0 9 .4
1 ,5 4 8 .5
1 ,2 2 9 .5

536.1
4 9 2 .6
4 7 6 .7
1,4 7 8 .4
1 ,1 5 3 .5

7 6 0 .8
472.1
1,4 6 8 .4
1,1 4 5 .5

6 ,0 9 9
5 2 8 .9
4 9 0 .2
4 7 0 .6
1 ,4 6 5 .6
1,1 4 0 .8

4 6 6 .3
1,461.1
1 ,1 3 9 .4

4 8 6 .6
4 6 3 .4
1,4 6 1 .3
1,1 3 7 .0

6 ,0 8 9
5 3 6 .3
4 8 9 .7
464.1
1,468.1
1 ,1 4 2 .5

1 ,5 0 7 .2

1,3 6 0 .9

1,348.7

1,3 4 3 .8

1,3 3 9 .2

1 ,3 3 2 .8

2 2 5 .7

2 2 4 .0

2 2 2 .5

C o m m u n ic a tio n s e q u ip m e n t..
S e m ic o n d u c to rs a n d
ele ctro n ic c o m p o n e n ts .........
E lectronic in s tr u m e n ts ............

2 5 0 .0
185.8

157.0

155.8

15 5 .0

2 2 1 .9
154.1

2 1 9 .3
1 5 3 .9

5 2 4 .5
4 5 0 .0

4 6 1 .8

4 5 7 .9
4 2 4 .7

4 5 6 .2
4 2 5 .2

4 5 3 .3
4 2 5 .5

E lectrical e q u ip m e n t a n d
a p p lia n c e s ....................................
T ra n s p o rta tio n e q u ip m e n t........

4 9 6 .5
1,8 2 8 .9

F u rn itu re a n d re la te d
p ro d u c ts ........................................
M is c e lla n e o u s m a n u fa ctu rin g

F a b ric a te d m etal p ro d u c ts ........
M a c h in e ry .......................................

6 ,0 7 7
5 3 1 .8
488

1,625.1
9 2 1 .9

1 ,6 2 7 .9

4 ,3 3 7 .3
1 4 ,3 6 5

9 2 4 .3
4 ,3 6 2 .2
1 4,396

4 ,3 6 5 .0
1 4 ,3 9 5

4 ,3 6 5 .2
1 4 ,4 0 5

1 0 ,058

1 0 ,0 8 5

1 0,123

1 0 ,1 2 4

8 ,8 8 9

8 ,9 2 4

8 ,9 4 6

8 ,9 5 3

1 0 ,1 4 2
8 ,9 5 7

6,101
5 3 9 .7
4 9 3 .2

6 ,1 2 6

6 ,1 5 2

6 ,1 5 9

6 ,1 6 6

543
5 0 1 .4

5 4 4 .2
5 0 3 .3

4 6 4 .0
1 ,4 9 4 .5
1 ,1 5 3 .3

5 4 3 .8
5 0 2 .3
4 6 5 .7
1 ,4 9 6 .6
1 ,1 5 6 .8

4 6 6 .8
1 ,5 0 0 .0
1 ,1 6 2 .0

4 8 7 .5
4 6 4 .6
1 ,4 7 1 .2
1,1 4 0 .4

5 3 6 .3
4 9 2 .7
4 3 2 .2
1 ,4 7 1 .8
1,138.7

4 9 0 .5
4 6 2 .2
1 ,4 7 6 .6
1 ,1 4 1 .2

4 6 2 .0
1 ,4 7 8 .5
1,145.1

540
4 9 7 .8
4 6 2 .5
1 ,4 8 6 .7
1 ,1 5 2 .0

1 ,3 3 4 .4

1.3 3 2 .2

1,3 3 3 .2

1,3 3 3 .9

1 ,3 3 8 .0

1,3 3 9 .7

1 ,3 4 5 .8

1 ,3 4 5 .8

1 ,3 5 2 .4

219.1
154.4

2 1 7 .8

2 1 9 .4

153.0

154.8

2 1 9 .0
154.8

2 1 8 .6
155.0

218.1
155.1

2 1 8 .8
1 5 5 .9

2 1 7 .2
157.1

2 1 7 .4
158.8

4 4 9 .4
425.1

4 5 1 .2
4 2 5 .2

4 5 1 .3
4 2 5 .3

4 5 0 .2
4 2 3 .7

4 5 1 .4

452.1
4 2 6 .8

4 5 3 .4

4 2 3 .3

4 2 7 .5

4 5 5 .8
430.1

4 5 8 .0
430.1

4 6 0 .0
4 3 2 .5

4 5 1 .2

4 4 6 .5
1,7 6 8 .8

4 4 7 .3
1,7 6 4 .4

4 4 8 .3
1 ,7 6 1 .0

1 ,7 4 0 .5

C o m p u te r a n d e le ctro n ic
p ro d u c ts 1.....................................
C o m p u te r a n d p erip h e ra l
e q u ip m e n t...................................

4 2 9 .3

9 2 2 .4

4 5 9 .9

4 5 7 .7

4 5 3 .8

452.1

1 ,7 6 6 .5

1,7 6 5 .6

4 5 0 .9
1,7 6 6 .5

1 ,7 6 2 .7

4 4 9 .8
1,7 6 0 .6

4 4 6 .8

1,759.8

4 5 0 .8
1 ,7 6 5 .5

4 4 8 .6

1,7 7 5 .4

1 ,7 6 6 .5

1,769.1

68 8 .3

5 7 3 .5
6 6 2 .8

5 7 2 .6
6 6 0 .2

568.1
6 5 7 .9

5 6 8 .0
6 5 5 .9

5 6 8 .2
6 5 5 .2

56 8 .9
6 5 2 .7

5 6 9 .3
6 5 1 .9

5 7 1 .3
6 5 2 .0

5 7 1 .2
6 5 3 .0

6 5 3 .0

5 7 6 .5
6 5 3 .0

5 7 7 .6
6 5 4 .4

5 7 8 .6
6 5 3 .9

5 8 3 .5
6 5 4 .9

5 ,7 7 5
4 ,2 3 9

5 ,5 5 5
4 ,0 4 3

5 ,5 4 4
4 ,0 3 2

5 ,5 1 8
4 ,0 0 5

5 ,5 0 8
4 ,0 0 0

5 ,4 9 7
3,9 9 2

5 ,4 7 0
3 ,9 5 9

5 ,4 5 6

5 ,4 3 9
3 ,9 5 0

5 ,4 4 5
3 ,9 5 7

3 ,9 5 9

5 ,4 5 0
3,971

5 ,4 4 2

3 ,9 6 5

5 ,4 4 5
3 ,9 5 4

5,441

P ro d u ctio n w o rk e rs .................

3 ,9 6 5

5 ,4 4 8
3 ,9 7 6

F o o d m a n u fa c tu rin g ................... .

1 ,5 2 5 .7

1 ,5 1 8 .7

1,522.1

1 ,5 2 3 .8

1,5 2 6 .0

1,5 2 8 .2

1,5 0 8 .3

1,5 0 6 .3

1,5 0 0 .7

1 ,5 0 2 .4

1 ,5 0 4 .5

1 ,5 0 2 .7

1 ,5 0 7 .0

1 ,5 0 5 .3

1 ,5 0 9 .0

B e v e r a g e s a n d to b a c c o
p ro d u c ts .........................................
T extile m ills.....................................

2 0 7 .4
2 9 0 .9

T extile p ro d u c t m ills.....................
A p p a re l.............................................

194.6
3 5 9 .7

2 0 1 .0
2 4 7 .0
172.6
2 9 9 .7
4 3 .7

195.9
2 3 7 .3
176.6
297.1

197.2
237.1
179.7
2 9 4 .3

198.2
235.1
179.4
188.4

4 4 .3
5 1 0 .3

4 4 .6
5 0 9 .8

4 4 .8
5 0 8 .0

44 .8
5 0 8 .8

197.8
2 3 5 .8
180.1
2 9 2 .7
4 4 .6
5 0 7 .0

1 9 7 .5
236.1
1 8 1 .4
2 9 0 .8

5 1 3 .3

198.3
245.1
175.2
2 9 7 .7
44.1
5 1 1 .7

197.7
2 3 9 .2
176.9
296.1

4 4 .3
515.1

2 0 0 .2
2 5 0 .2
1 7 3 .7
2 9 9 .8
4 4 .2
5 1 3 .8 '

198.3
2 4 1 .0
174.3
2 9 7 .7

5 0 .2
54 6 .6

2 0 0 .7
2 5 6 .9
178.7
3 0 7 .5
4 4 .9
51 6 .3

2 0 1 .0
2 5 1 .8
1 7 0 .7
3 0 4 .0

L e a th e r a n d allied p ro d u c ts .....
P a p e r a n d p a p e r p ro d u c ts ........
Printing a n d re la te d su p p o rt
a c tiv ities.........................................

2 0 0 .6
2 6 0 .3
,7 9 .8
3 1 2 .7
45 .2
5 1 9 .0

45.1
508.1

4 5 .0
5 0 6 .3

198.1
2 3 6 .3
1 7 8 .6
2 8 7 .6
4 5 .8
5 0 9 .2

6 7 8 .8
11 3 .8
9 0 5 .4

6 7 6 .2
112.9
9 0 2 .7

6 7 3 .3
112.6
899.1

673.1
11 2 .0
8 9 7 .6

670.1
112.4
8 9 5 .9

6 6 7 .6
114.3
8 9 3 .7

6 6 5 .0
112.9

6 6 4 .4
113.1
8 9 4 .9

6 6 3 .6
112.6
8 9 6 .4

6 6 5 .9
113.1
8 9 5 .0

667.1
113.6
8 9 4 .4

604.1

Nondurable goods...............

7 0 6 .6
118.1

5 7 3 .4

4 4 9 .2

P etro leu m a n d c o a l p ro d u c ts ...
C h e m ic a ls ........................................

9 2 7 .5

6 8 0 .0
114.6
7.9

681.1
114.6
9 0 8 .2

P la s tic s a n d ru b b e r p ro d u c ts ..

8 4 8 .0

8 1 5 .9

813.1

8 0 8 .8

8 0 8 .4

8 0 6 .3

8 0 6 .5

8 0 5 .8

8 0 4 .8

8 0 3 .9

8 0 6 .3

8 0 7 .5

8 1 0 .2

8 0 9 .6

8 1 2 .3

SERVICE-PROVIDING..............
PRIVATE SERVICEPROVIDING........................
Trade, transportation,
and utilities.........................
Wholesale trade..................

1 0 7 ,7 8 4

1 0 8 ,1 1 4

1 0 8 ,0 7 0

1 0 8 ,0 7 7

1 0 8 ,1 5 9

1 0 8 ,2 7 0

108,341

1 0 8 ,3 6 7

1 0 8 ,4 9 8

1 0 8 ,5 9 3

1 0 8 ,8 5 2

1 0 9 ,1 3 2

1 0 9 ,2 6 8

1 0 9 ,3 4 4

1 0 9 ,3 5 8

86,271

8 6 ,5 3 8

8 6 ,5 0 9

8 2 ,4 9 7

6 6 ,6 2 0

8 6 ,7 1 0

8 6 ,7 9 7

8 6 ,8 2 3

86,971

8 7 ,0 5 4

8 7 ,2 9 9

8 7 ,5 6 0

8 7 ,7 2 4

8 7 ,8 1 5

8 7 ,8 2 9

25,261
5 ,5 9 2 .7

2 5 ,3 1 2
5 ,6 1 1 .4
2 ,9 5 4 .9
1,9 9 3 .7

25,331
5 ,6 1 2 .2
2 ,9 5 3 .8

2 5 ,4 1 5
5 ,6 2 3 .5
2 ,9 6 3 .4

2 5 ,4 7 7
5 ,6 3 6 .7
2 ,9 6 9 .7

2 5 ,5 0 2
5 ,6 3 8 .5
2 ,9 7 5 .4

1 ,9 9 7 .2

1 ,9 9 3 .0

2 5 ,4 9 7

2 5 ,2 7 5

2 5 ,2 2 5

2 5 ,2 7 2

5 ,5 9 6 .8
2 ,9 4 2 .5
2 ,0 0 1 .6

2 5 ,2 2 5
5 ,5 8 9 .0
2 ,9 3 6 .2
1,9 9 7 .9

2 5 ,2 5 2

5 ,6 5 2 .3
3 ,0 0 7 .9

5,585.1
2,932.1
1 ,9 9 5 .9

5 ,5 8 1 .6
2 ,9 3 2 .0
1,9 9 2 .4

2 ,9 4 3 .9
1,9 8 9 .2

25,211
5 ,5 9 8 .4
2 ,9 4 5 .8
1,9 9 1 .8

8 9 4 .7

665.1
1 1 3 .0
8 9 3 .2

N o n d u ra b le g o o d s .....................
E lectronic m a rk e ts a n d
a g e n ts a n d b ro k e rs ..................

2 ,0 1 5 .0

5 ,6 0 5 .0
2 ,9 4 9 .2
2,002.1

1 ,9 9 4 .5

1 ,9 9 5 .3

2 5 ,4 4 8
5 ,6 3 2 .5
2 ,9 6 7 .5
1,9 9 6 .3

6 2 9 .4

6 5 4 .3

6 5 2 .7

6 5 1 .9

6657.1

6 5 7 .2

6 5 9 .6

66 0 .8

6 6 2 .8

6 6 3 .9

6 6 4 .8

6 6 8 .7

6 6 9 .8

670.1

Retail trade.........................

6 7 1 .4

15,025.1

1 4 ,9 1 1 .5

1 4 ,8 9 6 .5

14 ,9 1 1 .6

1 4 ,9 2 6 .8

14,948.1

1 4 ,9 2 1 .7

1 4 ,8 7 6 .0

1 4 ,9 4 4 .8

1 4 ,9 6 3 .0

15 ,0 1 3 .0

15,037.1

1 5 ,0 4 7 .6

1 5 ,0 5 4 .7

1 5 ,0 3 5 .6

1 ,8 7 9 .4
1,2 5 2 .8

1 ,8 8 3 .5
1,255.1

1,883.7
1,2 5 6 .9

1 ,8 8 3 .5
1,2 5 7 .0

1,889.8
1,2 5 9 .7

1,889.7
1,2 5 9 .6

1,8 9 2 .9
1,2 5 8 .9

1,8 9 3 .7
1 ,2 5 9 .5

1,8 9 5 .4
1,2 6 1 .3

1,9 0 0 .9
1,2 6 2 .9

1,9 0 6 .9
1 ,2 6 3 .9

1 ,9 1 0 .9
1,2 6 4 .7

1 ,9 1 1 .4
1 ,2 6 3 .6

1,9 0 8 .7
1 ,2 6 2 .5

1,9 0 8 .2
1 ,2 6 0 .9

5 3 8 .7

5 4 2 .9

540.1

5 3 8 .0

5 3 9 .7

5 4 0 .2

5 4 4 .8

5 4 7 .2

5 4 6 .4

5 4 4 .5

5 4 4 .8

5 4 4 .5

5 4 5 .7

5 4 6 .2

5 4 8 .0

52 5 .3

5 1 1 .9

5 0 7 .2

5 0 7 .4

5 0 6 .7

5 0 6 .5

5 1 2 .8

5 1 1 .9

5 0 9 .3

5 0 8 .2

5 1 1 .7

514.1

5 1 2 .6

5 1 2 .3

5 1 1 .2

D u rab le g o o d s ..............................

2 5,491
5 ,6 4 6 .6
2 ,9 8 5 .9
1 ,9 8 9 .3

M otor v e h ic le s a n d p a rts
d e a l e r s 1.......................................
A utom obile d e a le r s ...................
F u rn itu re a n d h o m e
fu rn ish in g s s t o r e s .......................
E lec tro n ics a n d a p p lia n c e
s t o r e s ..............................................
S e e n o te s a t e n d of ta b le .

80

Monthly Labor Review


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

September 2004

12.

Continued—Employment of workers on nonfarm payrolls by Industry, monthly data seasonally adjusted

[In thousands]
Industry

2004

2003

Annual average

Feb.

Mar.

Apr.

May

1,221.4

1,231.4

2 ,8 2 6 .3

2 ,8 3 1 .3

1,243.5
2 ,8 3 8 .9

1,247.3
2 ,8 3 9 .9

1,248.7
2 ,8 4 5 .3

1,2 4 4 .9
2 ,8 4 1 .0

1,243.5
2 ,8 3 6 .0

871.8

958.2
873.0

95 7 .9
87 2 .4

957.1
87 1 .6

9 5 7 .2
8 7 0 .3

95 5 .2
8 6 7 .7

1,311.3

1,321.8

1,328.0

1,335.5

1,347.1

1,3 4 7 .9

63 6 .8

63 6 .5
2 ,8 2 4 .4

63 5 .8
2 ,8 3 1 .0
16.7
927.9

636.1
2 ,8 3 0 .5
1,610.9
9 2 5 .7

6 3 4 .3
2 8 3 0 .9
1,613.2
9 2 4 .2

42 9 .8

42 7 .4

6 3 5 .6
2 8 3 6 .8
1,614.7
9 2 6 .5
428.1

4 2 2 6 .0
5 1 4 .9

4 2 2 5 .6
5 1 4 .6
2 1 7 .7
52.2

2002

2003

July

Aug.

Sept.

Oct.

Nov.

Dec.

Jan.

1,1 7 6 .5
2 ,8 8 1 .6

1,191.1
2 ,8 4 0 .9

1,188.3
2 ,8 3 5 .6

1,194.7
2 ,8 3 3 .6

1,203.4
2 ,8 2 9 .4

1,204.0
2 ,8 3 8 .7

1,210.0
2 ,8 2 1 .4

1,209.5
2 ,8 1 3 .9

9 3 8 .8
8 9 5 .9

943.1
87 9 .9

941.4
87 7 .9

941.0
88 1 .4

943.1
877.9

9 4 8 .3
8 7 3 .8

951.6
875.2

95 2 .6
871.1

954.1
875..1

1,312.5

1,296.7

1,294.0

1,294.8

1,295.6

1,302.6

1,297.1

1,301.0

1,304.3

6 6 1 .3
2 ,8 1 2 .0
1,684.0
9 5 9 .5
4 4 3 .7

6 4 5 .0
2 ,8 1 5 .2
1,618.8
934.1

644.1
2 ,8 2 0 .4
1,613.7

6 4 2 .5
2 ,8 3 4 .9
1,622.3
9 3 1 .9
4 2 7 .9

64 2 .8
2 ,8 3 9 .9
1,623.7
93 1 .7
42 6 .8

642.0
2 ,8 4 2 .9
1,623.5
93 3 .5
4 2 5 .9

6 4 1 .6
2 ,8 2 6 .4
1,612.6
930.9
4 1 7 .3

633.2
2,7 9 3 .4

63 5 .9
2 ,8 2 2 .7
1,603.4
92 9 .6

4 ,2 2 3 .6
5 6 3 .5
2 1 7 .8
5 2 .6

4 ,1 7 6 .7
5 2 7 .3
2 1 5 .4

4 ,1 5 3 .6
5 1 3 .8
216.1
53.1

4 ,1 4 8 .4
512.4

1,329.6

4 ,1 6 2 .9
506.1
2 1 5 .2
52 .5
1,329.3

4,1 6 8 .0
511.5
2 1 5 .5
50.9
1,335.7

4,1 5 7 .0
5 1 2 .9
2 1 5 .5
50.0
1,338.7

4 ,1 7 5 .9
510.2
21 5 .4
5 0 .6

1,324.3

4,1 6 0 .8
511.8
2 1 5 .6
51.5
1,328.7

Junep

Julyp

Building m aterial a n d g a rd e n
supply s to r e s ...............................
F ood a n d b e v e ra g e s to r e s ........
H ealth a n d p e rs o n a l c a re
s t o r e s .............................................
G a so lin e s ta tio n s .........................
Clothing a n d clothing
a c c e s s o r ie s s t o r e s ...................
S p o rtin g g o o d s, hobby,
book, a n d m u sic s t o r e s ...........
G e n era l m e rc h a n d is e s t o r e s l .
D e p artm en t s t o r e s ....................
M iscellan e o u s s to re re ta ile rs...
N o n sto re re ta ile rs ........................

Transportation and
warehousing.....................
Air tra n s p o rta tio n .........................
Rail tra n s p o rta tio n .......................
W a ter tra n s p o rta tio n ...................
T ruck tra n s p o rta tio n ...................
T ransit a n d g ro u n d p a s s e n g e r
tra n s p o rta tio n ..............................
P ipeline tra n s p o rta tio n ...............

4 2 7 .5

1,339.3

5 2 .5
1,328.0

934.0
4 2 9 .8

2 1 3 .8
52.9

1,601.3
924.4
424.1

42 4 .3

954.9

2 ,8 2 2 .5
1,602.7
92 4 .6
42 4 .8

1,604.9
92 6 .9
42 7 .4

4 2 8 .5

1,343.6

4 ,1 7 5 .8
511.6
215.7
48 .8
1,344.1

4 ,1 9 7 .0
512.9
21 6 .0
49 .2
1,346.4

4 ,1 9 6 .5
5 1 3 .3
2 1 6 .3
5 0 .6
1,352.2

4 ,2 0 9 .9
5 1 4 .7
2 1 6 .4
51.1
1,353.9

2 1 7 .3
52.0
1,3 5 8 .6

1,358.6

3 8 0 .8
41 .7

3 8 0 .3
40 .0

3 7 2 .8
40.1

3 7 1 .2
39.5

380.7
39.3

389.2
39.0

385.7
38.7

3 8 5 .0
38.8

3 8 2 .3
3 8 .3

380.1
38.2

3 8 0 .5
38.1

3 7 2 .3
38.1

3 8 1 .5
38 .3

38 2 .9
38.3

3 7 9 .0
38.4

S c e n ic a n d sig h tse e in g
tra n s p o rta tio n ..............................

2 5 .6

28 .0

29.1

28 .9

28 .9

29 .0

28 .7

2 9 .4

2 8 .7

2 9 .7

3 1 .4

31.1

30 .6

30.0

29 .4

S u p p o rt activities for
tra n s p o rta tio n ..............................
C o u riers a n d m e s s e n g e r s .......
W a reh o u sin g a n d s to ra g e

5 2 4 .7
5 6 0 .9
5 1 6 .7

5 1 6 .3
5 6 6 .6
5 2 2 .3

513.4
5 6 9 .5
521.4

512.2
566.7
521.2

515.4
566.5
522.4

514.3
565.0
5 2 2 .6

512.4
564.7
524.2

511.6
559.0
516.1

514.1
566.9
525.8

515.5
567.7
524.4

5 1 8 .5
572.1
531.9

519.1
570.9
532.6

51 9 .5
57 2 .8
531.1

5 1 9 .9
5 7 7 .3
5 3 4 .8

5 1 9 .8
577.0
538.9

Utilities...............................

5 9 6 .2

5 8 0 .8

578.1

5 7 8 .8

578.9

579.2

578.9

57 9 .3

580.2

580.0

581.2

582.1

5 8 2 .3

5 8 2 .3

5 8 2 .9

3 ,3 9 5

3 ,1 9 8

3 ,1 8 8

3 ,1 7 4

3,175

3 ,1 6 6

3,172

3,1 7 5

3,1 6 3

3,169

3,1 6 9

3,1 7 3

3 ,1 7 7

3 ,1 7 5

3,170

964.1

9 2 6 .4

9 2 2 .7

922.0

9 1 9 .3

918.0

918.4

917.4

914.0

915.1

91 5 .3

91 6 .3

91 6 .2

917.1

9 1 5 .4

3 8 7 .9
334.1

376.1
32 7 .0

376.6
32 6 .5

369.9
32 5 .5

375.4

373.4

382.7
327.0

379.7
329.7

38 2 .7
33 1 .8

381.2
333.0

33 3 .3

3 9 0 .8
3 3 5 .4

3 8 7 .6
3 3 5 .8

3 8 5 .4

326.0

385.2
3 2 9 .5

38 5 .7

3 2 7 .6

33 .7

30 .0
1,082.6

30.1
1,075.3

30.0
1,071.3

30.1
1,069.4

29.9
1,065.2

30.4
1,062.2

30.4

1,1 8 6 .5

1,061.2

30.8
1,061.3

31.9
1,058.2

31.9
1,055.0

32.5
1,051.9

32 .5
1,047.3

3 3 .5
1,045.5

1,043.8

4 4 1 .0
47 .3

4 0 7 .5
48.1

40 9 .5

40 7 .6
47 .8

4 0 5 .4

47 .3

4 8 .0

4 0 4 .8
4 8 .3

4 0 2 .6
48 .2

402.6
48.2

400.1
47 .8

401.1
48.0

40 3 .7
48 .6

40 4 .0
49.6

405.1
49 .6

406.1
4 9 .7

4 0 5 .9
4 9 .6

Financial activities.................

7,8 4 7

7,9 9 5
5,9 3 6 .8

7,996
5,9 3 6 .8

8,004
5,9 4 5 .6

7,990
5,9 3 0 .2

7,985
5,9 2 2 .7

7,981
5 ,9 1 6 .5

7,981
5,917.1

7,989
5,9 2 4 .7

8,003
5,933.0

8 ,0 1 5
5 ,9 4 7 .7

8 ,0 3 6

8 ,0 1 3

5 ,8 1 7 .3

7,9 7 4
5 ,9 2 0 .5

8 ,0 2 9

F in a n c e a n d in s u ra n c e .................
M onetary a u th o rities—
ce n tral b a n k .................................

5,9 4 6 .0

5 ,9 5 4 .5

5 ,9 2 9 .3

23 .4

2 2 .7

22 .7

22 .6

22 .6

2 2 .5

2 2 .5

22 .5

22 .4

22 .4

22 .3

22 .3

2 1 .8

21 .8

21 .4

re la te d a c tiv itie s '.....................
D epository credit

2 ,6 8 6 .0

2 ,7 8 5 .6

2 ,8 0 2 .6

2 ,8 0 6 .0

2,808.1

2,8 0 1 .0

2 ,7 9 0 .3

2 ,7 8 3 .3

2 ,7 8 5 .3

2 ,7 8 7 .2

2 ,7 9 3 .8

2,802.1

2 ,8 0 0 .8

2,8 0 4 .2

2 ,7 8 8 .4

in te rm e d ia tio n '........................
C om m ercial b a n k in g .............
S ecu rities, com m odity
c o n tra c ts , in v e s tm e n ts ............
In s u ra n c e ca rrie rs a n d
re la te d ac tiv ities........................
F u n d s, tru s ts , a n d o th er

1,733.0

1,752.1

1,755.1

1,756.0

1,757.9

1,760.1

1,758.1

1,757.1

1,758.7

1,762.6

1,762.8

1,765.0

1,765.2

1,767.8

1,764.1

1,278.1

1,281.1

1,283.2

1,283.9

1,283.6

1,284.4

1,280.5

1,278.9

1,280.4

1,283.5

1,284.1

1,285.0

1,284.2

1,284.9

1,281.3

7 8 9 .4

7 6 4 .4

7 6 0 .4

7 5 8 .7

761.7

762.0

769.1

771.9

773.8

778.2

780.8

781.0

78 2 .8

786.1

781.7

2 ,2 3 3 .2

2,266.1

2 ,2 6 9 .7

2 ,2 6 8 .7

2 ,2 7 1 .9

2 ,2 6 4 .7

2,2 6 1 .2

2,258.1

2 ,2 5 5 .8

2 ,2 5 7 .4

2,257.1

2 ,2 5 9 .5

2 ,2 6 2 .7

2 ,2 6 4 .7

2 ,2 5 9 .7

85.4

81 .7

81.4

80.8

8 1 .3

80.0

79.6

80.7

79.8

79.5

79.0

78.8

77.9

77.7

78.1

2 .0 2 9 .8
1.352.9
649.1

2 ,0 5 3 .6
1,384.4

2 ,0 5 8 .8

2,0 5 7 .9
1,388.8

2,0 6 0 .2

2,0 6 2 .7

2 ,0 6 4 .0
1,395.7

2 ,0 6 3 .6
1,397.7

639.0

63 8 .3

636.0

1,405.8
634.1

2 ,0 7 1 .6
1,409.2
6 3 3 .2

2,083.1
1,418.7
635.4

2 ,0 8 1 .9
1,416.9
636.1

2,0 8 3 .4
1,418.4

6 3 9 .8

2 ,0 6 4 .5
1,400.2
634.2

2 ,0 6 9 .5

1,390.6
639.9

1,394.5

64 0 .8

2 ,0 5 7 .8
1,385.3
643.9

27.6

2 8 .4

2 8 .6

2 8 .8

2 9 .3

2 9 .7

29 .2

30.0

2 9 .9

30.1

2 9 .6

2 9 .2

2 9 .0

28 .9

2 8 .5

1 5,976

15,999

16,021

15,998

16,051

16,070

16,114

16,159

16,172

16,196

16,237

16,363

16,432

16,451

16,493

6,624.1
1,140.4

6 ,6 4 7 .9
1,142.9

6,6 6 9 .3
1,140.5

6 ,6 5 7 .9
1,138.7

6,658.1
1,139.2

6 ,6 7 9 .8
1,138.4

6,7 0 1 .4
1,141.9

6,708.1
1,143.3

6 ,7 3 1 .8
1,147.0

6 ,7 4 2 .4

80 1 .5

810.6

8 2 6 .6

815.2

813.3

81 2 .8

81 8 .5

8 0 6 .3

8 0 7 .9

809.0

1,233.9

1,235.2

1,230.9

1,240.0

1,246.4

1,254.1

1,258.3

1,262.4

1,264.3

P ublishing in d u stries, e x c ep t
In tern et..........................................
M otion picture a n d so u n d
reco rd in g in d u s trie s..................
B ro ad c astin g , ex c e p t Internet..
Internet publishing an d
b ro a d c a s tin g ...............................
T e le c o m m u n ic a tio n s..................
IS P s, s e a rc h p o rtals, an d
d a ta p ro c e s s in g .........................
O th er inform ation s e r v ic e s .......

3 3 6 .8
3 3 .4

C redit interm ediation an d

R eal e s ta te a n d rental
R eal e s t a t e ....................................
R en tal a n d lea sin g s e r v ic e s ....
L e s s o rs of nonfinancial
intangible a s s e t s ......................

1,386.6
643.4

6 3 6 .5

Professional and business
P ro fe ssio n a l a n d technical
Legal s e r v ic e s ............................
A ccounting a n d book k eep in g
s e r v ic e s ......................................
A rchitectural a n d en g in e erin g
s e r v ic e s .....................................

6 ,6 7 5 .6
1,115.3

6 ,6 2 3 .5
1,136.8

6 ,5 8 5 .7
1,135.0

6,578.1
1,133.8

6 ,6 0 6 .3
1,136.6

8 3 7 .3

8 1 5 .6

800.7

800.7

802.5

1,246.1

1,228.0

1,224.6

1,222.0

1,230.1

1,230.9

1,149.2

S e e n o te s at e n d of ta b le .


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

Monthly Labor Review

September 2004

81

Current Labor Statistics:

Labor Force Data

12. Continued—Employment of workers on nonfarm payrolls by industry, monthly data seasonally adjusted
[In thousands]

______________

Industry

Annual average

2003

2004

2002

2003

July

Aug

Sept.

Oct.

Nov.

Dec.

Jan.

Feb.

Mar.

Apr.

May

1,152.8

1,108.3

1,100.7

1,094.5

1,103.3

1,107.0

1,105.7

1,105.7

1,104.6

1,0 9 9 .8

1,103.5

1,103.5

1,110.1

734.4

747.3

742.5

744.2

7 4 9 .3

7 5 5 .6

760.6

764.0

765.4

767.9

77 4 .0

780.9

7 8 5 .9

791.4

7 9 1 .0

1,705.4

1,675.5

1,680.3

1,671.4

1,671.7

1,669.1

1,671.6

1,670.2

1,675.1

1,675.6

1,676.6

1,679.7

1,683.3

1,686.7

1,690.6

7 ,5 9 5 .2

7 ,6 9 8 .3

7 ,7 5 4 .7

7,748.1

7,773.1

7,7 7 6 .3

7,7 9 4 .5

7,8 1 9 .2

7,8 3 8 .5

7,8 6 2 .4

7,880.1

7,9 8 2 .3

8,040.1

8 ,0 3 2 .3

8 ,0 5 9 .8

s e r v ic e s 1....................................

7,2 7 6 .8

73 ,7 6 4 .0

7,4 2 6 .5

7,4 2 7 .0

7,4 5 1 .6

7,4 5 6 .0

7,4 7 3 .7

7,4 9 6 .3

7,5 1 7 .5

7 ,5 3 9 .6

7 ,5 5 6 .8

7,657.0

7,7 1 5 .6

7,7 0 5 .8

7,733.1

E m ploym ent s e r v ic e s '..........

3,2 4 6 .5

3,3 3 6 .2

3 ,3 6 9 .6

3,366.2

3,389.1

3,402.0

3,4 2 7 .6

3 ,4 6 1 .3

3,4 7 3 .8

3 ,4 9 3 .8

3,4 9 2 .3

3 ,5 5 3 .7

3 ,5 9 1 .5

3 ,5 6 6 .3

3 ,5 9 3 .3

2 ,1 9 3 .7
75 6 .6

2 ,2 4 3 .2
74 7 .4

2 ,2 4 8 .8
744.2

2 ,2 6 2 .3
748.7

2,2 8 7 .2
753.2

2 ,2 9 1 .7
753.2

2,3 1 9 .4
746.7

2,3 5 5 .3
745.1

2,3 4 4 .3
739.0

2 ,3 7 0 .4
739.8

2 ,3 8 0 .3
74 6 .0

2 ,4 2 3 .8
74 8 .6

2 ,4 5 1 .7
751.2

2 ,4 4 1 .2
7 5 5 .7

2,446.1
75 4 .8

1,606.1

1,631.7

1,643.8

1,648.4

1,645.2

1,639.6

1,639.4

1,635.9

1,637.1

1,639.5

1,646.2

1,674.5

1,686.0

1,694.3

1,6 9 2 .5

318.3

321.9

328.2

321.1

32 1 .5

32 0 .3

320.8

32 2 .9

321

322.8

32 3 .3

325.3

32 4 .5

326 .5

3 2 6 .7

16,199
2 ,6 4 2 .8

16,577
2 ,6 8 8 .5

16,568
2 ,6 7 6 .4

16,591
2 ,6 7 3 .9

16,672
2,689.1

16,678
2 ,7 0 7 .7

16,705
2,723.1

16,731
2,7 2 8 .0

16,746
2 ,7 2 9 .3

1 6 ,764
2 ,7 2 7 .4

16,813
2 ,7 3 6 .0

16,854
2 ,7 4 0 .8

16,871
2,731.1

16,891
2 ,7 2 7 .5

16,911
2 ,7 2 7 .3

1 3,555.7

13,888.0

1 3 ,891.3

1 3 ,916.8

1 3 ,933.3

13,970.0

1 3 ,981.5

14,003.2

14,017.1

14,036.8

14,077.1

14,113.1

14,140.1

14,163.1

1 4,183.3

4,6 3 3 .2
1,967.8
41 3 .0
6 7 9 .8

4 ,7 7 6 .0
2 ,0 0 3 .8
423.1
727.1

4 ,7 8 3 .4
2 ,0 0 4 .6
4 2 2 .8
732.0

4 ,7 9 1 .9
2,007.1
4 2 3 .5
733.7

4 ,7 9 2 .8
2 ,0 0 8 .2
4 2 2 .9
732.8

4 ,8 1 2 .8
2 ,0 1 8 .5
4 2 3 .3
737.7

4,8 1 8 .7
2 ,0 2 3 .3
4 2 6 .4
735.7

4 ,8 3 1 .0
2 ,0 3 0 .0
425.0
7 3 9 .9

4 ,8 4 0 .3
2 ,0 3 2 .3
4 2 7 .8
740.2

4 ,8 5 5 .3
2 ,0 3 4 .4
431.1
7 4 1 .5

4 ,8 6 8 .0
2 ,0 4 3 .5
4 3 0 .3
7 4 3 .8

4 ,8 8 3 .6
2,046.1
43 2 .2
748.4

4 ,8 9 6 .8
2 ,0 4 9 .6
435.1
751.7

4 ,9 0 7 .7
2 ,0 5 2 .4
4 3 6 .2
756.1

4 ,9 2 2 .3
2,054.1
44 0 .5
76 1 .4

4 ,1 5 9 .6

4 ,2 5 2 .5

4 ,2 4 7 .4

4,2 6 0 .2

4 ,2 6 4 .4

4 ,2 6 8 .9

4,278.1

4,2 8 3 .9

4 ,2 8 7 .8

4,284.1

4,2 9 8 .0

4,305.1

4 ,3 1 5 .4

4 ,3 1 9 .7

4 ,3 2 3 .8

2 ,7 4 3 .3
1,573.2
2 ,0 1 9 .7

2 ,7 8 4 .3
1,582.8
2 ,0 7 5 .2

2 ,7 8 4 .2

2 ,7 8 7 .7

2,792.1

2 ,8 0 2 .8

2 ,8 0 6 .3

2 ,8 0 8 .4

1,581.7
2 ,0 9 5 .3

1,580.3
2 ,0 9 6 .9

2,791.1
1,578.7
2 ,1 0 6 .3

2 ,7 9 8 .4

1,585.2
2,094.1

2 ,7 9 2 .8
1,584.1
2 ,0 9 1 .9

2,7 9 3 .0

1,580.5
2,0 8 0 .0

2 ,7 8 9 .3
1,583.1
2 ,0 8 6 .8

2 ,7 9 4 .2

1,582.8
2 ,0 7 6 .3

1,582.1
2 ,1 1 2 .7

1,584.0
2 ,1 2 1 .6

1,585.3
2 ,1 2 1 .6

1,586.2
2 ,1 2 7 .3

2 ,8 1 1 .6
1,587.2
2 ,1 2 5 .6

744.1
11,986

760.5
12,128

761.1
12,118

76 4 .5
12,117

76 5 .8
12,126

77 1 .6
12,147

766.3
12,178

770
12,192

766.3
12,218

772.2
12,229

773.7
12,271

777.6
1 2,303

777.1
12,331

7 8 4 .7
12,341

791.9
1 2 ,339

1,782.6

1,801.0

1,797.7

1,795.0

1.794.4

1,796.9

1,799.4

1,795.2

1,801.4

1,796.7

1,798.7

1,791.1

1,793.1

1,790.2

1,785.4

363.7

370.2

366.2

3 6 6 .7

372.0

3 6 9 .6

3 7 1 .7

368.8

369.4

3 6 6 .5

3 6 4 .6

36 1 .4

3 5 8 .8

359.1

354.1

114.2

113.3

113.1

113.4

113.7

114.2

114.6

115.6

115.0

116.4

1,315.1

1,318.7

1,316.1

1,314.9

1 0 ,511.8 1 0 5 ,837.9

1 0,550.4

10 ,5 5 3 .6

C o m p u te r s y s te m s d esig n
a n d re la te d s e r v ic e s ..............
M a n a g e m e n t a n d technical
consulting s e r v ic e s .................
M a n a g e m e n t of c o m p a n ie s
a n d e n te rp ris e s ...........................
A dm inistrative a n d w a s te
s e r v ic e s ...........................................

Junep

July1’

1,118.6

1,122.8

A dm inistrative a n d s u p p o rt

T em p o rary h elp s e r v ic e s ....
B u s in e s s s u p p o rt s e r v ic e s ....
S e rv ic e s to buildings
a n d dw ellings...........................
W a s te m a n a g e m e n t an d
re m e d iatio n s e r v ic e s ...............

Educational and health
services.............................
E ducational s e r v ic e s .....................
H ealth c a re a n d social
a s s i s t a n c e .......................................
A m bulatory h ealth c a re
s e r v ic e s '....................................
O ffices of p h y s ic ia n s ...............
O u tp atien t c a r e c e n te r s ..........
H om e h ealth c a re s e r v ic e s ....
H o sp itals........................................
N ursing a n d residential
c a re facilities1............................
N ursing c a r e facilities...............
S ocial a s s i s t a n c e '........................
Child d ay c a r e s e r v ic e s ..........

Leisure and hospitality..........
Arts, en te rtain m en t,
a n d re c re a tio n ...............................
P erform ing a r ts a n d
s p e c ta to r s p o rts .........................
M u seu m s, historical site s,
z o o s , a n d p a r k s .........................
A m u sem en ts, gam bling, an d
re c re a tio n .....................................

114.0

114.1

114.6

114.5

113.4

1,305.0

1,316.6

1,316.9

1,313.8

1,309.0

1,313.1

1,314.4

1,313.3

1,318.6

1,316.5

1,319.9

A c co m m o d atio n s an d
food s e r v ic e s .................................

1 0 ,203.2

10,324.4

1 0,319.9

1 0,321.8

1 0,331.7

10,350.4

10,378.9

10,396.3

10,416.5

1 0 ,432.3

1 0 ,742.0

1,778.6

1,765.2

1,762.5

1,755.0

1,739.1

1,733.7

1,751.7

1,763.0

1,752.1

1,754.4

1,753.4

1,758.5

1,758.5

1,763.1

1,7 5 8 .5

8,4 2 4 .6
5,372
1,246.9
1,257.2

8,5 5 9 .2
5,393
1,236.2
1,258.2

8 ,5 5 7 .4
5,394
1,238.7
1,258.8

8,5 6 6 .8
5 ,3 9 6
1,242.4
1,257.3

8 ,5 9 2 .6
5,390
1,240.4
1,252.7

8,6 1 6 .7
5 ,3 8 7
1,237.6
1,254.6

8,6 2 7 .2
5,382
1,234.4
1,254.1

8 ,6 3 3 .3
5,374
1,228.5
1,250.2

8,6 6 4 .4
5,379
1,233.5
1,251.2

8 ,6 7 7 .9
5,376
1,230.5
1,247.6

8,7 1 8 .6
5,391
1,239.4
1,255.9

8,7 5 3 .3
5 ,4 0 4
1,238.2
1,260.5

8 ,7 7 9 .4
5 ,4 0 7
1,237.7
1,265.5

8 ,7 8 7 .3
5,419
1,235.4
1,269.1

8,795.1
5,4 1 2
1,235.1
1,265.1

2 ,8 6 7 .8

2,8 9 8 .0

2 ,8 9 6 .3

2 ,8 9 5 .9

2 ,8 9 6 .5

2,8 9 5 .2

2 ,8 9 3 .9

2,8 9 5 .7

2 ,8 9 4 .5

2 ,8 9 8 .3

2,8 9 5 .2

2 ,9 0 4 .8

2 ,9 0 3 .7

2 ,9 1 4 .3

2 ,9 1 2 .2

21 ,5 1 3
2,7 6 7

21 ,5 7 5
2,7 5 6

21,561
2,7 5 8

21 ,5 8 0
2,7 5 0

2 1 ,5 3 9
2 ,7 4 7

21 ,5 6 0
2 ,7 3 6

21 ,5 4 4
2,7 2 3

21 ,5 4 4
2,7 2 0

21 ,5 2 7
2,7 1 5

2 1 ,5 3 9
2,7 1 6

2 1 ,5 5 3
2 ,7 1 0

2 1 ,5 7 2
2 ,7 2 7

2 1 ,5 4 4
2 ,7 1 2

2 1 ,5 2 9
2 ,7 1 5

2 1 ,5 2 9
2 ,7 1 0

1,923.8
842.4

1,947.0
809.1
5,017
2 ,2 6 6 .4
2 ,7 5 0 .7
13,802
7,699.1
6,1 0 4 .0

1,947.8
810.2

1,942.2

1,942.1

1,932.9

1,924.9

789.1

787.3

1 3,773
7,6 7 3 .9
6,0 9 9 .3

13,793
7,6 8 7 .0
6 ,1 0 5 .9

5,0 2 3
2 ,2 8 2 .5
2 ,7 4 0 .0
13,798
7,6 8 4 .5
6,113.1

5,027
2 ,2 8 5 .7
2 ,7 4 0 .9
13,797
7,687.1
6,1 0 9 .7

5,018
2 ,2 7 9 .6
2 ,7 3 8 .4
1 3,805

5 ,0 2 3
2,2 8 3 .2
2 ,7 3 9 .7
13,820
7,704.7
6,1 1 4 .8

5,0 1 9
2 ,2 7 8 .3
2 ,7 4 0 .6
13,826
7 ,7 1 0 .9
6,1 1 5 .4

7 8 6 .5
5 ,0 0 4
2 ,2 6 1 .4
2 ,7 4 2 .8
13,828
7 ,7 1 0 .2
6 ,1 1 7 .9

1,928.9
78 5 .7

1,923.7

798.1

1,923.8
791.7

1,925.7

80 3 .3
5,031
2,2 9 0 .4
2,7 4 0 .4

1,921.5
793.1
5,007

1,939.5

80 4 .8
5,019
2 ,2 7 8 .8
2,7 4 0 .4

1,928.9
791.4

1,921.1

808.0
4,9 9 7
2 ,2 5 8 .7
2,7 3 8 .2
13,833
7,7 4 2 .4

4 ,9 9 8
2,255.1
2,7 4 3 .2
13,816
7 ,7 0 4 .7
6 ,1 1 1 .2

4,9 9 8
2 ,2 5 5 .2
2 ,7 4 2 .4
13,821

A c c o m m o d atio n s.........................
F ood s e rv ic e s a n d drinking
p la c e s ............................................

Other services......................
R ep air a n d m a in te n a n c e ..........
P e rs o n a l a n d laundry se rv ic e s
M em b ersh ip a s s o c ia tio n s an d
o rg a n iz a tio n s ..............................

Government..........................
F e d e r a l...............................................
F e d e ra l, e x c e p t U .S. P ostal
S e rv ic e ...........................................
U.S. P o sta l S e rv ic e ......................
S ta t e ..................................................
E d u ca tio n ......................................
O th er S ta te g o v e rn m e n t.........
L ocal..................................................
E d u ca tio n ......................................
O th er local g o v e rn m e n t..........

5,0 2 9
2 ,2 4 2 .8
2 ,7 8 6 .3
13,718
7,6 5 4 .4
6,0 6 3 .2

4,990
2 ,2 4 9 .0
2 ,7 4 0 .8
13,813
7,7 2 1 .2
6 ,0 9 1 .5

6,090.1

1 In c lu d e s o th e r Industries not show n s e p a ra te ly .
K
’
p - prelim inary.
NOTE: D ata reflect th e co n v e rsio n to th e 2 0 0 2 version of th e North A m erican industry

82

Monthly Labor Review


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

September 2004

2,2 6 8 .0
2 ,7 3 8 .9
13,805
7,6 9 2 .2
6,1 1 2 .7

7 ,6 9 4 .3
6 ,1 1 0 .8

7 8 6 .5

7 ,7 0 7 .6
6,113.1

„
C lassification S y ste m (NAics), replacing th e S ta n d a rd Industrial C lassification (SIC) sy stem .
N A lcs-based d a ta by Industry a r e not c o m p a ra b le with s ic - b a s e d d a ta . S e e "N otes on th e
d a ta - for a description of th e m ost re cen t b e n c h m a rk revision, prelim inary.

13.

Average weekly hours of production or nonsupervisory workers1on private nonfarm payrolls, by industry, monthly
data seasonally adjusted
Industry

2002

2003

2004

2003

Annual average
July

Aug.

Sept.

Oct.

Nov.

Dec.

Jan.

Feb.

Mar.

Apr.

May

Junep July15

TOTAL PRIVATE..................................

3 3 .9

3 3 .7

3 3 .6

3 3 .6

3 3 .6

3 3 .7

3 3 .8

3 3 .6

3 3 .8

3 3 .8

3 3 .8

3 3 .7

3 3 .8

3 3 .6

3 3 .7

GOODS-PRODUCING...............................

3 9 .9

3 9 .8

3 9 .6

3 9 .7

3 9 .8

3 9 .9

40.1

3 9 .9

4 0 .2

4 0 .3

4 0 .2

4 0 .0

4 0 .3

4 0 .0

4 0 .2
4 4 .2

Natural resources and mining..............

4 3 .2

4 3 .6

4 3 .3

4 3 .6

4 3 .6

4 3 .7

4 3 .9

4 3 .6

4 4 .5

44 .1

4 4 .2

4 4 .3

4 4 .2

44 .1

Construction..........................................

3 8 .4

3 8 .4

3 8 .3

3 8 .5

3 8 .4

3 8 .4

3 8 .5

38.1

3 8 .5

3 8 .5

3 8 .6

3 8 .2

3 8 .3

38.1

3 8 .4

Manufacturing........................................

4 0 .5

4 0 .4

40.1

4 0 .2

4 0 .4

4 0 .5

4 0 .8

4 0 .6

4 1 .0

4 1 .0

4 0 .9

4 0 .7

41 .1

4 0 .8

4 0 .9

O v e rtim e h o u r s ...........................................

O v e rtim e h o u r s ...........................................

P rim a ry m e t a l s ...............................................

4 .2

4 .2

4.1

4.1

4 .2

4 .3

4 .5

4 .5

4 .5

4 .6

4 .6

4 .5

4 .6

4 .6

4 .6

4 0 .8

4 0 .8

4 0 .5

4 0 .5

4 0 .8

4 0 .9

4 1 .3

4 1 .2

4 1 .5

4 1 .5

4 1 .4

4 1 .2

4 1 .6

4 1 .2

4 1 .4

4 .2

4 .3

4.1

4 .2

4 .3

4 .4

4 .7

4 .7

4 .7

4 .8

4 .8

4 .7

4 .8

4 .7

4 .7

3 9 .9

4 0 .4

4 0 .7

4 0 .4

4 0 .4

4 0 .6

4 1 .2

4 1 .0

4 0 .9

41.1

4 1 .0

4 1 .0

4 1 .4

4 0 .5

4 0 .9

4 2 .0

4 2 .2

4 1 .8

42.1

4 1 .9

42.1

4 2 .4

4 2 .3

4 2 .5

4 2 .5

4 2 .9

4 2 .3

4 2 .0

4 1 .8

42.1

4 2 .4

4 2 .3

4 1 .7

4 1 .9

4 2 .2

4 2 .3

4 2 .7

4 2 .7

43.1

4 3 .0

4 3 .2

43.1

4 3 .4

4 3 .4

4 3 .3

4 0 .6

4 0 .7

4 0 .5

4 0 .5

4 0 .7

4 0 .8

4 0 .9

4 0 .8

4 1 .2

4 1 .2

41.1

4 1 .0

4 1 .3

4 1 .0

4 1 .3

4 0 .5

4 0 .8

4 0 .4

4 0 .7

4 1 .0

4 0 .9

41.1

41.1

4 1 .8

4 1 .8

4 1 .7

4 1 .6

4 2 .3

4 2 .0

4 2 .3

C o m p u te r a n d e le c tro n ic p r o d u c ts .......

3 9 .7

4 0 .4

4 0 .5

4 1 .0

4 0 .6

4 0 .7

4 0 .7

4 0 .4

4 0 .8

4 1 .2

4 0 .7

4 0 .5

4 0 .8

4 0 .5

4 1 .2

E le c tric a l e q u ip m e n t a n d a p p l i a n c e s ..

40.1

4 0 .6

4 0 .5

4 0 .6

4 0 .6

4 0 .9

4 0 .8

4 0 .7

41.1

4 0 .7

4 0 .8

4 0 .8

4 1 .6

4 0 .8

4 0 .9

T r a n s p o r ta tio n e q u i p m e n t ........................

4 2 .5

4 1 .9

4 1 .3

4 0 .7

4 2 .0

4 1 .9

4 2 .7

4 2 .7

4 2 .8

4 2 .9

4 2 .8

4 2 .4

4 2 .8

4 2 .3

4 2 .5

F u rn itu r e a n d r e la te d p r o d u c ts ..............

3 9 .2

3 8 .9

3 8 .9

39.1

39.1

39.1

3 9 .9

3 9 .7

3 9 .7

3 9 .4

3 9 .6

3 9 .5

4 0 .0

3 9 .7

3 9 .4

M is c e lla n e o u s m a n u fa c tu rin g ................

3 8 .6

3 8 .4

3 8 .3

38.1

3 8 .3

3 8 .3

3 8 .9

3 8 .5

3 9 .0

3 8 .7

3 8 .7

3 8 .3

3 8 .9

3 8 .4

3 8 .7

40.1

3 9 .8

3 9 .4

3 9 .6

3 9 .8

3 9 .9

40.1

3 9 .9

4 0 .2

4 0 .3

40.1

4 0 .0

4 0 .3

40 .1

4 0 .0

4 .3
3 9 .4

4 .3

4 .3

4 .4

4 .4

4 .4

3 9 .3

39.1

3 9 .6

3 9 .4

39.1

F a b r i c a t e d m e ta l p r o d u c ts .......................

O v e rtim e h o u r s ...........................................

4 .2

4.1

4 .0

3 .6

4.1

4.1

4 .3

4 .2

4 .3

F o o d m a n u fa c tu rin g ....................................

3 9 .6

3 9 .3

39.1

3 9 .2

3 9 .3

3 9 .3

3 9 .2

39.1

3 9 .5

B e v e r a g e a n d to b a c c o p r o d u c ts ...........
T e x tile p ro d u c t m ills...................................

P a p e r a n d p a p e r p r o d u c ts .......................

3 9 .4

39.1

3 8 .4

3 8 .8

39.1

3 8 .8

3 9 .9

39.1

3 9 .6

4 0 .3

3 9 .4

3 9 .6

3 9 .2

3 8 .7

3 8 .7

4 0 .6

39.1

3 7 .7

3 8 .7

3 9 .0

39.1

4 0 .0

3 9 .7

4 0 .0

4 0 .0

4 0 .2

3 9 .5

4 0 .3

4 0 .3

4 0 .7

3 9 .2

3 9 .6

3 9 .8

4 0 .0

4 0 .7

4 0 .4

4 0 .0

3 9 .8

3 9 .4

3 9 .9

3 8 .8

3 8 .3

3 8 .8

3 8 .9

3 8 .8

3 6 .7

3 5 .6

3 4 .6

3 4 .8

35.1

3 5 .8

3 6 .2

3 5 .8

3 5 .7

3 6 .2

3 6 .3

3 5 .9

36.1

3 5 .9

3 5 .9

3 7 .5

3 9 .3

3 9 .7

3 8 .9

3 8 .4

3 8 .9

3 9 .3

4 0 .3

3 9 .8

3 9 .5

3 9 .4

39.1

3 8 .4

3 8 .2

3 7 .9

4 1 .8

42.1

4 1 .2

4 1 .2

4 1 .2

4 1 .5

41 ..9

4 1 .8

4 1 .9

4 2 .0

4 1 .8

4 1 .9

4 2 .6

4 2 .0

4 2 .2

P rin tin g a n d re la te d s u p p o r t
a c tiv itie s ..........................................................

3 8 .4

3 8 .2

3 8 .0

3 8 .0

3 8 .2

3 8 .5

3 8 .4

3 8 .2

3 8 .6

3 8 .6

3 8 .4

3 8 .4

3 8 .6

3 8 .5

3 8 .7

P e tro le u m a n d c o a l p r o d u c ts ..................

4 3 .0

4 4 .0

4 4 .4

4 4 .2

4 4 .9

4 5 .6

4 4 .2

4 3 .8

44.1

4 3 .7

4 3 .9

4 5 .0

4 4 .9

4 4 .8

C h e m i c a l s ........................................................

4 2 .3

4 4 .5
4 2 .4

4 2 .0

4 2 .3

4 2 .2

4 2 .0

4 2 .7

4 2 .5

4 2 .9

4 3 .2

4 3 .0

4 3 .0

4 2 .9

4 2 .5

4 2 .8

P la s tic s a n d r u b b e r p r o d u c ts ..................

4 0 .6

4 0 .4

40.1

4 0 .3

4 0 .5

4 0 .6

4 0 .7

4 0 .4

4 0 .8

4 0 .9

4 0 .9

4 0 .7

4 0 .9

4 0 .8

4 0 .5

3 2 .5

3 2 .4

3 2 .2

3 2 .3

3 2 .3

3 2 .3

3 2 .4

3 2 .2

3 2 .4

3 2 .4

3 2 .4

3 2 .3

3 2 .4

3 2 .3

3 2 .4

PRIVATE SERVICEPROVIDING........................................
Trade, transportation, and
utilities.................................................

3 3 .6

3 3 .5

3 3 .4

3 3 .5

3 3 .5

3 3 .6

3 3 .6

3 3 .5

3 3 .6

3 3 .7

3 3 .6

3 3 .5

3 3 .5

3 3 .4

3 3 .5

3 8 .0

3 7 .8

3 7 .8

3 7 .9

3 7 .8

3 8 .0

3 8 .0

3 7 .8

3 7 .9

3 8 .0

3 8 .0

3 8 .0

3 7 .8

3 7 .6

3 7 .9
3 0 .7

3 0 .9

3 0 .9

3 0 .7

3 0 .9

3 0 .9

3 0 .9

3 0 .9

3 0 .8

3 1 .0

3 0 .9

3 0 .8

3 0 .7

3 0 .7

3 0 .6

T r a n s p o r ta tio n a n d w a r e h o u s i n g ...........

3 6 .8

3 6 .9

3 6 .9

3 6 .9

3 6 .9

37.1

3 7 .0

3 6 .7

3 6 .9

3 7 .2

3 6 .9

3 6 .9

3 7 .3

3 6 .9

37.1

U tilities..................................................................

4 0 .9

41.1

4 1 .0

4 1 .0

4 0 .4

4 1 .0

4 1 .4

4 0 .8

4 0 .8

4 1 .0

4 1 .2

4 1 .2

4 1 .3

41.1

4 0 .8

Information.............................................

3 6 .5

3 6 .2

3 6 .3

3 6 .2

36.1

36.1

3 6 .3

3 6 .2

3 6 .2

3 6 .3

3 6 .3

3 6 .3

3 6 .4

3 6 .5

3 6 .3

3 5 .6

3 5 .5

3 5 .5

3 5 .5

3 5 .4

3 5 .5

3 5 .5

3 5 .3

3 5 .7

3 5 .5

3 5 .5

3 5 .6

3 5 .8

3 5 .4

3 5 .5

3 4 .2

34.1

34.1

3 3 .9

3 3 .9

3 4 .0

34.1

3 3 .8

34.1

3 4 .2

34.1

34.1

3 4 .2

3 4 .0

34.1

3 2 .4

3 2 .3

3 2 .3

3 2 .4

3 2 .3

3 2 .3

3 2 .4

3 2 .4

3 2 .4

3 2 .4

3 2 .4

3 2 .4

3 2 .5

3 2 .3

3 2 .5

2 5 .8

2 5 .6

2 5 .4

2 5 .5

2 5 .5

2 5 .6

2 5 .7

2 5 .6

2 5 .7

2 5 .8

2 5 .7

2 5 .7

2 5 .7

2 5 .7

2 5 .6

3 2 .0

3 1 .4

3 1 .3

3 1 .3

3 1 .2

3 1 .3

3 1 .2

3 1 .0

31.1

31.1

3 1 .2

31.1

3 1 .2

3 1 .0

31.1

' D a ta r e la te to p r o d u c tio n w o r k e rs in n a tu ra l r e s o u r c e s a n d m ining a n d m a n u ­

NOTE:

D a ta re fle c t t h e c o n v e rs io n to th e 2 0 0 2 v e r s io n o f t h e N o rth A m e ric a n

fa c tu rin g , c o n s tru c tio n w o r k e rs in c o n s tru c tio n , a n d n o n s u p e r v is o r y w o r k e rs in t h e

In d u s try C la s s ific a tio n S y s te m (NAICS), re p la c in g th e S ta n d a r d in d u s tria l C la s s ific a tio n

Professional and business
Education and health services............
Other services.........................................

s e r v ic e -p r o v id in g in d u s tr ie s .

(SIC) s y s te m .

N A ic s -b a s e d d a t a b y in d u s try a r e n o t c o m p a r a b l e w ith s i c - b a s e d d a t a .

S e e " N o te s o n th e d a ta " for a d e s c rip tio n o f t h e m o s t r e c e n t b e n c h m a r k re v is io n .
p = p re lim in a ry .


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Federal Reserve Bank of St. Louis

Monthly Labor Review

September 2004

83

Current Labor Statistics:

Labor Force Data

14. Average hourly earnings of production or nonsupervisory workers’ on private nonfarm payrolls, by industry,
monthly data seasonally adjusted
Annual average

Industry

2003

2004

2002

2003

July

Aug.

Sept.

Oct.

Nov.

Dec.

Jan.

Feb.

Mar.

Apr.

May

Junep

JulyP

C u rre n t d o lla rs....................................

$ 1 4 .9 5

$ 1 5 .3 5

$ 1 5 .4 0

$15.41

$15.41

$ 1 5 .4 3

$ 1 5 .4 6

$ 1 5 .4 5

$ 1 5 .4 9

$ 1 5 .5 2

$ 1 5 .5 5

$ 1 5 .5 9

$ 1 5 .6 3

$ 1 5 .6 5

$ 1 5 .7 0

C o n s ta n t (1982) d o lla rs....................

8 .2 4

8 .2 7

8.31

8.2 8

8.2 5

8.28

8.23

8.3 0

8 .2 7

8 .2 7

8 .2 4

8.2 5

8.21

8.2 0

8 .2 3

16.33

16.80

16.81

16.86

16.91

16.90

16.94

16.97

17.00

17.06

17.08

17.13

17.13

17.16

17.18

17.19

17.58

17.57

17.62

17.66

17.72

17.79

17.91

17.95

18.01

18.10

18.08

18.10

18.24

18.21

18.52

18.95

15.97

19.01

19.05

19.06

19.06

19.04

19.11

19.18

19.17

19.20

19.20

19.20

19.22

TOTAL PRIVATE

GOODS-PRODUCING.......................
Natural resources and mining..........
Construction.................................
Manufacturing................................

15.29

15.74

15.73

15.79

15.84

15.83

15.89

15.93

15.94

15.99

16.01

16.08

16.08

16.13

16.14

14.54

14.96

14.96

15.02

15.06

15.03

15.06

15.09

15.11

15.14

15.16

15.24

15.23

15.27

15.28

D urable g o o d s .............................................

16.02

16.46

1f>.43

16.50

16.57

16.54

16.58

16.64

16.63

16.68

16.69

16.75

16.75

16.78

16.78

N o n d u rab le g o o d s .....................................

14.15

14.63

14.65

14.68

14.70

14.72

14.79

14.81

14.85

14.89

14.93

15.00

15.02

15.08

15.10

PRIVATE SERVICEPROVIDING...................................

14.56

14.96

15.02

15.02

15.01

15.03

15.06

15.05

15.08

15.10

15.13

15.17

15.23

15.25

15.30

E xcluding o v e rtim e ..............................

Trade,transportation, and
utilities......................................

14.02

14.34

14.39

14.40

14.38

14.41

14.44

14.41

14.45

14.49

14.50

14.57

14.61

14.64

14.69

W h o le sa le tr a d e ..........................................

16.98

17.36

17.40

17.43

17.44

17.47

17.47

17.46

17.53

17.54

17.54

17.60

17.63

17.68

17.72
12.12

R etail tr a d e ..................................................

11.67

11.90

11.94

1 1 .9 5

11.94

11.95

11.97

11.95

11.95

11.98

11.99

12.01

12.06

12.09

T ra n sp o rtatio n an d w a re h o u s in g .........

15.76

16.25

16.36

16.33

16.31

16.32

16.35

16.33

16.46

16.52

16.53

16.71

16.75

16.80

16.86

Utilities............................................................

2 3 .9 6

2 4 .7 6

2 4 .8 0

2 4 .9 9

2 4 .9 6

2 5 .1 7

25 .3 6

2 5 .1 3

25 .3 2

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

2 5 .3 5

2 5 .3 8

2 5 .6 7

2 5 .4 6

2 5 .4 2

2 5 .5 3

2 0 .2 0

21.01

2 1 .1 8

2 1 .2 2

21.21

21.21

2 1 .1 0

2 0 .9 9

2 1 .1 5

2 1 .2 4

2 1 .2 5

2 1 .2 9

21 .4 2

2 1 .3 0

2 1 .3 8

16.17

17.13

17.41

17.39

17.27

17.29

17.30

17.30

17.35

17.32

17.41

17.46

17.49

17.49

17.55

16.81

17.20

17.20

17.20

17.19

17.25

17.29

17.25

17.24

17.25

17.27

17.29

17.36

17.41

1 7 .4 4

15.21

15.64

15.64

15.69

15.70

15.73

15.77

15.81

15.87

15.90

15.96

16.17

15.99

16.06

16.12

8 .5 8

8.7 6

8.7 8

8 .7 7

8.78

8 .7 8

8.82

8 .8 4

8.8 5

8.8 6

8.8 7

8 .8 6

8 .8 6

8 .8 4

8.8 8

13.72

13.84

13.82

13.82

13.81

13.80

13.81

13.80

13.84

13.84

13.87

13.84

13.85

13.86

13.87

1 D a ta re la te to p roduction w o rk ers in n atu ra l re s o u rc e s a n d m ining a n d m a n u fa c ­

NOTE:

turing, co n stru c tio n w o rk ers in c o n stru c tio n , a n d n o n su p erv iso ry w o rk e rs in th e
serv ic e-p ro v id in g industries,

C lassification S y s te m (NAICS), re p la cin g th e S ta n d a rd Industrial C lassification (SIC) s y s te m ,

p = prelim inary.

84

Monthly Labor Review


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

D a ta

reflect th e co n v e rsio n to th e 2 0 0 2 v ersio n of th e

n a ic s

b a s e d d a ta by industry a r e not c o m p a ra b le with S IC -b a s e d d a ta . S e e "N o tes on th e d a ta " for a
d escription of th e m o st re c e n t b e n c h m a rk revision.

September 2004

N orth A m erican industry

15. Average hourly earnings of production or nonsupervisory workers' on private nonfarm payrolls, by industry
2004

2003

A nnual average
Industry
2002

2003

July

Aug

Sept.

Oct.

Nov.

Dec.

Jan.

Feb.

Mar.

Apr.

May

Ju nep

July15
$ 1 5 .5 9

TOTAL PRIVATE...........................

$ 1 4 .9 5

$ 1 5 .3 5

$ 1 5 .2 9

$ 1 5 .3 1

$ 1 5 .4 4

$ 1 5 .4 2

$ 1 5 .5 2

$ 1 5 .4 8

$ 1 5 .5 6

$ 1 5 .6 0

$ 1 5 .5 5

$ 1 5 .5 9

$ 1 5 .6 3

$ 1 5 .5 7

S e a s o n a ll y a d j u s t e d ...........................

1 5 .1 8

1 5 .4 7

1 5 .4 0

15.41

15.41

15.41

1 5 .4 3

1 5 .4 5

1 5 .4 9

1 5 .5 2

1 5 .5 5

1 5 .5 9

1 5 .6 3

1 5 .6 5

1 5 .7 0

1 6 .9 8

1 7 .0 3

1 6 .9 4

1 6 .9 5

1 7 .0 0

1 7 .0 9

1 7 .1 0

1 7 .1 4

1 7 .1 9

GOODS-PRODUCING..........................
Natural resources and mining...........

1 6 .3 3

1 6 .8

1 6 .8 5

1 6 .9 2

17.01

1 6 .9 5

1 7 .1 9

1 7 .5 8

1 7 .5 3

1 7 .5 2

1 7 .6 9

1 7 .6 9

1 7 .1 5

1 7 .9 7

1 8 .0 0

1 8 .0 5

1 8 .1 7

1 8 .1 4

1 8 .0 6

1 8 .1 8

1 8 .1 5

Construction....................................
Manufacturing..................................

1 8 .5 2

1 8 .9 5

1 9 .0 0

1 9 .0 8

1 9 .1 9

1 9 .1 3

1 9 .0 8

1 9 .1 9

19.01

1 9 .0 7

1 9 .0 7

1 9 .1 5

1 9 .1 5

1 9 .1 3

1 9 .2 4

1 5 .2 9

1 5 .7 4

1 5 .6 8

1 5 .7 6

1 5 .8 7

15.81

1 5 .9 2

1 6 .0 5

1 5 .9 8

1 5 .9 9

16.01

1 6 .0 7

1 6 .0 5

1 6 .0 9

1 6 .0 5

D u r a b le g o o d s ................................................

1 6 .0 2

1 6 .4 6

1 6 .3 2

1 6 .4 8

1 6 .6 2

1 6 .5 5

1 6 .6 4

1 6 .7 8

1 6 .6 6

1 6 .6 8

1 6 .6 9

1 6 .7 2

16.71

1 6 .7 6

1 6 .6 3

W o o d p r o d u c t s ...........................................

1 2 .3 3

12.71

12.81

1 2 .7 7

1 2 .8 3

1 2 .8 2

1 2 .9 5

1 2 .9 3

1 2 .9 0

12.91

1 2 .9 3

1 3 .0 0

1 3 .0 3

1 2 .9 9

1 3 .0 2

N o n m e ta llic m in e ra l p r o d u c t s .............

1 5 .4 0

1 5 .7 7

1 5 .8 3

15.81

1 5 .8 4

1 5 .9 5

1 5 .9 9

1 5 .9 8

1 6 .0 3

1 6 .0 0

1 6 .0 2

1 6 .1 9

1 6 .1 8

1 6 .2 4

1 6 .3 4

P rim a ry m e t a l s ...........................................

1 7 .6 8

1 8 .1 3

1 8 .2 6

1 8 .1 3

1 8 .3 0

1 8 .2 5

1 8 .3 2

1 8 .3 9

1 8 .3 9

1 8 .3 6

1 8 .3 3

1 8 .5 2

1 8 .4 8

18.51

18.61

F a b r ic a te d m e ta l p r o d u c t s ...................

1 4 .6 8

15.01

1 5 .0 0

1 5 .0 4

1 5 .0 9

1 5 .0 3

1 5 .0 6

1 5 .2 3

1 5 .2 0

1 5 .1 8

1 5 .2 5

15.21

1 5 .2 0

1 5 .2 4

M a c h in e r y ....................................................

1 5 .9 2

1 6 .3 0

1 6 .3 6

1 6 .3 2

1 6 .4 0

1 6 .3 5

1 6 .4 9

1 6 .6 2

1 6 .5 3

1 6 .5 0

1 6 .4 9

1 6 .5 3

1 6 .5 3

1 6 .5 6

1 6 .6 4

C o m p u te r a n d e le c tro n ic p ro d u c ts ...

1 6 .2 0

1 6 .6 8

1 6 .7 9

16.81

1 6 .7 7

1 6 .7 7

1 6 .7 8

1 6 .8 5

16.81

1 6 .9 2

1 5 .2 9

1 6 .9 3

17.01

17.11

1 7 .2 2

17.41

1 4 .8 3

1 4 .8 9

14.91
2 0 .8 0

E le c tric a l e q u ip m e n t a n d a p p lia n c e s

1 3 .9 8

1 4 .3 5

14.31

1 4 .4 5

1 4 .4 9

1 4 .3 7

1 4 .5 4

1 4 .6 8

1 4 .5 0

1 4 .5 8

1 4 .6 8

1 4 .8 0

T r a n s p o r ta tio n e q u i p m e n t ....................

2 0 .6 4

2 1 .2 5

2 0 .7 6

2 1 .2 9

2 1 .5 6

2 1 .3 5

2 1 .4 8

2 1 .7 4

2 1 .3 8

2 1 .3 7

2 1 .3 4

2 1 .3 6

2 1 .2 9

2 1 .3 8

F u rn itu r e a n d r e la te d p r o d u c t s ...........

12.61

1 2 .9 8

1 2 .9 7

1 3 .0 4

1 3 .1 0

13.01

1 3 .0 8

1 3 .0 8

1 2 .9 5

1 2 .9 2

1 2 .9 6

1 3 .0 9

1 3 .0 4

13.11

1 3 .1 6

12.91

1 3 .3 0

1 3 .2 6

1 3 .2 7

1 3 .4 2

1 3 .4 7

1 3 .5 3

1 3 .6 0

1 3 .6 8

1 3 .7 5

1 3 .7 8

1 3 .7 0

1 3 .7 6

1 3 .8 3

14.01

N o n d u r a b le g o o d s ........................................

1 4 .1 5

1 4 .6 3

14.71

1 4 .6 5

1 4 .7 3

1 4 .6 7

1 4 .8 0

1 4 .8 8

1 4 .8 9

1 4 .8 8

1 4 .9 0

15.01

1 4 .9 8

1 5 .0 3

1 5 .1 3

F o o d m a n u f a c t u r i n g ................................

1 2 .5 5

1 2 .8 0

1 2 .8 4

1 2 .8 0

1 2 .9 0

1 2 .7 7

12.91

1 2 .9 5

12.91

1 2 .8 7

1 2 .8 9

1 2 .9 6

1 2 .9 4

1 3 .0 0

16.11

B e v e r a g e s a n d to b a c c o p r o d u c ts ....

1 7 .7 3

1 7 .9 6

1 7 .8 6

1 7 .7 5

1 7 .7 3

1 8 .0 5

1 8 .6 4

1 8 .5 8

1 8 .8 8

1 8 .7 6

1 9 .1 3

1 9 .6 0

1 9 .5 5

1 9 .3 5

1 9 .4 8

T e x tile m i ll s ..................................................

1 1 .7 3

1 2 .0 0

1 1 .9 7

1 1 .9 5

1 2 .0 7

1 2 .0 2

1 2 .0 8

12.21

12.11

1 2 .1 3

1 2 .0 9

1 2 .2 3

1 2 .0 8

1 2 .1 3

1 2 .0 0

T e x tile p ro d u c t m i ll s ................................

1 0 .9 6

1 1 .2 4

1 1 .2 8

1 1 .4 6

1 1 .4 7

1 1 .3 7

1 1 .3 5

1 1 .4 4

1 1 .4 5

1 1 .4 0

1 1 .3 7

1 1 .3 3

1 1 .3 0

1 1 .3 0

1 1 .3 3

9 .1 0

9 .5 6

9 .6 8

9 .7 5

9 .7 7

9 .6 9

9.71

9 .8 0

9 .7 4

9 .5 8

9 .6 0

9.71

9 .5 5

9 .6 0

9 .6 6

1 1 .0 0

1 1 .6 7

1 1 .5 2

1 1 .6 7

1 1 .6 3

1 1 .8 3

1 1 .8 7

1 1 .9 0

1 1 .9 4

1 1 .7 6

1 1 .6 4

1 1 .6 5

1 1 .4 9

1 1 .5 9

1 1 .6 6

P a p e r a n d p a p e r p r o d u c t s ...................

1 6 .8 5

1 7 .3 2

1 7 .4 5

1 7 .3 3

17.41

1 7 .4 4

1 7 .5 8

1 7 .6 0

1 7 .6 3

1 7 .5 5

1 7 .5 9

1 7 .8 4

1 7 .8 8

1 7 .8 6

1 7 .9 0

P rin tin g a n d r e la te d s u p p o r t activities

1 4 .9 3

1 5 .3 7

1 5 .3 9

1 5 .3 6

1 5 .4 6

15.41

1 5 .4 8

1 5 .5 6

1 5 .5 3

1 5 .5 7

15.61

1 5 .5 4

15.51

1 5 .5 6

1 5 .7 2

2 3 .0 4

2 3 .6 4

2 3 .1 4

2 2 .9 6

2 3 .4 5

2 3 .6 3

2 4 .0 0

2 4 .0 6

2 4 .1 3

2 4 .3 2

2 4 .8 2

2 4 .4 8

2 4 .4 1

2 4 .2 4

2 4 .3 1

1 7 .9 7

1 8 .5 2

18.51

1 8 .6 0

1 8 .6 6

1 8 .6 6

1 8 .7 7

1 8 .7 9

1 8 .8 3

1 8 .8 5

1 8 .8 7

1 9 .0 2

1 9 .0 5

1 9 .1 7

1 9 .2 3

1 3 .5 5

1 4 .1 8

1 4 .3 8

1 4 .2 7

1 4 .3 0

1 4 .1 9

1 4 .2 7

1 4 .4 7

1 4 .4 3

1 4 .4 5

1 4 .4 5

1 4 .5 8

1 4 .5 5

1 4 .5 8

1 4 .7 0

1 4 .5 6

1 4 .9 6

1 4 .8 7

1 4 .8 8

1 5 .0 0

15.01

1 5 .1 3

1 5 .0 7

1 5 .1 9

1 5 .2 4

1 5 .1 6

1 5 .2 0

1 5 .2 4

1 5 .1 4

1 5 .1 5

C h e m i c a l s .....................................................

PRIVATE SERVICEPROVIDING.....................................
Trade, transportation, and
utilities...........................................

1 4 .0 2

1 4 .3 4

1 4 .3 2

1 4 .3 2

1 4 .4 2

1 4 .3 8

1 4 .4 4

14.31

1 4 .5 0

1 4 .5 8

1 4 .5 3

1 4 .6 4

1 4 .6 4

14.61

1 4 .6 2

W h o le s a le t r a d e ..........................................

1 6 .9 8

1 7 .3 6

1 7 .3 3

1 7 .3 5

17.41

1 7 .4 2

1 7 .5 6

1 7 .4 6

1 7 .5 6

1 7 .6 0

1 7 .4 7

1 7 .6 0

1 7 .6 7

1 7 .5 8

1 7 .6 6
1 2 .0 6

R etail t r a d e .....................................................

1 1 .6 7

1 1 .9 0

1 1 .8 9

1 1 .8 9

1 1 .9 9

11.91

1 1 .9 2

1 1 .8 7

1 1 .9 8

1 2 .0 4

1 2 .0 3

1 2 .0 8

1 2 .0 8

1 2 .0 8

T r a n s p o r ta tio n a n d w a r e h o u s i n g ........

1 5 .7 6

1 6 .2 5

1 6 .3 5

1 6 .3 3

16.31

16.31

1 6 .4 0

1 6 .3 3

1 6 .4 6

1 6 .5 8

16.51

1 6 .7 3

1 6 .7 2

1 6 .7 9

1 6 .8 8

U tilitie s ..............................................................

2 3 .9 6

2 4 .7 6

2 4 .6 4

24 .8 1

2 5 .1 5

2 5 .2 3

2 5 .5 0

2 5 .2 6

2 5 .3 8

2 5 .2 9

2 5 .3 6

2 5 .6 9

2 5 .5 3

2 5 .3 0

2 5 .4 0

Information..................................

2 0 .2 0

21 .0 1

2 1 .0 1

2 1 .1 1

2 1 .3 5

2 1 .2 5

2 1 .2 8

2 1 .1 0

21 .2 1

2 1 .2 8

2 1 .1 7

2 1 .2 4

2 1 .4 1

2 1 .1 7

2 1 .2 5

Financial activities...........................

1 6 .1 7

1 7 .1 3

1 7 .2 9

1 7 .3 4

1 7 .2 7

1 7 .2 5

1 7 .4 2

1 7 .2 6

1 7 .3 5

1 7 .4 7

1 7 .3 7

1 7 .4 5

1 7 .6 2

1 7 .3 7

1 7 .4 3

16.81

1 7 .2 0

1 7 .0 7

1 7 .0 0

17.11

1 7 .1 3

17.41

1 7 .2 9

1 7 .3 8

1 7 .4 7

1 7 .2 8

1 7 .2 6

1 7 .4 5

1 7 .2 9

17.31

1 6 .1 4

Professional and business
services.........................................
Education and health
services........................................

15.21

1 5 .6 4

1 5 .6 2

1 5 .6 8

15.71

1 5 .7 3

1 5 .7 9

1 5 .8 6

1 5 .9 4

1 5 .9 5

1 5 .9 4

1 5 .9 9

1 6 .0 0

1 6 .0 6

Leisure and hospitality...................

8 .5 8

8 .7 6

8 .6 8

8 .6 8

8 .7 8

8 .7 8

8 .8 3

8 .9 4

8 .8 9

8 .9 2

8 .8 9

8 .8 4

8 .8 5

8 .7 8

8 .8 0

Other services.................................

1 3 .7 2

1 3 .8 4

1 3 .7 2

1 3 .7 5

1 3 .8 2

1 3 .7 8

1 3 .8 5

1 3 .8 8

1 3 .8 9

1 3 .9 0

1 3 .8 5

1 3 .8 7

1 3 .9 0

13.81

1 3 .7 7

and

m in in g

1

D a ta

r e la t e

to

p r o d u c tio n

w o r k e rs

in

n a tu ra l

re so u rc e s

and

N O T E : D a ta re fle c t th e c o n v e rs io n to th e 2 0 0 2 v e r s io n o f th e N o rth A m e ric a n In d u s try

m a n u fa c tu rin g , c o n s tru c tio n w o r k e rs in c o n s tru c tio n , a n d n o n s u p e r v is o r y w o r k e rs In

C la s s ific a tio n S y s te m

t h e s e rv ic e -p r o v id in g in d u s tr ie s .

s y s te m .


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

In d u strial C la s s ific a tio n

(SIC)

N A iC S -based d a t a by In d u stry a r e n o t c o m p a r a b l e w ith S ic - b a s e d d a t a .

(NAICS), re p la c in g th e

S ta n d a r d

See

" N o te s o n t h e d a t a ” fo r a d e s c rip tio n o f t h e m o s t r e c e n t b e n c h m a r k re v is io n .

Monthly Labor Review

September 2004

85

Current Labor Statistics:

Labor Force Data

16. Average weekly earnings of production or nonsupervisory workers1on private nonfarm payrolls, by industry
Industry

Annual average

2003

2004

2002

2003

July

Aug.

Sept.

Oct.

Nov.

Dec.

Jan.

Feb.

Mar.

Apr.

May

Junep

Julyp

$ 5 0 6 .0 7

$ 5 1 7 .3 6

$519.01
51 7 .7 8

$ 5 1 9 .6 5
5 19.99

5 22.55

$ 5 2 0 .1 3
5 19.12

$ 5 1 8 .1 5
5 23.56

$ 5 2 7 .2 8
52 4 .5 8

$ 5 2 0 .9 3
52 5 .5 9

$ 5 2 2 .2 7
5 2 5 .3 8

$ 5 3 1 .4 2
5 2 8 .2 9

$524.71
5 2 5 .8 4

$ 5 2 6 .9 4

“

$ 5 2 0 .3 3
5 17.78

$ 5 2 7 .6 8

“

$ 5 1 5 .2 7
51 7 .4 4

651.61

6 6 9 .2 3

66 5 .5 8

67 8 .4 9

6 85.50

68 1 .3 9

6 84.29

6 82.90

674.21

674.61

6 81.70

67 8 .4 7

6 9 0 .8 4

6 9 0 .7 4

6 8 7 .6 0

7 4 1 .9 7

7 6 6 .8 3

7 5 7 .3 0

7 72.63

7 80.13

7 78.36

7 84.55

7 81.70

7 84.80

7 8 6 .9 8

7 97.66

79 4 .5 3

7 9 8 .2 5

8 1 4 .4 6

8 0 9 .4 9

7 1 1 .8 2

727.11

7 41.00

7 5 3 .6 6

7 5 2 .2 5

7 4 4 .1 6

7 3 0 .7 6

7 14.34

7 12.88

711.31

7 3 2 .2 9

72 1 .9 6

741.11

7 3 8 .4 2

754.21

6 1 8 .7 5

6 3 6 .0 7

6 2 0 .9 3

6 3 3 .5 5

6 47.50

6 4 3 .4 7

6 55.90

6 62.87

6 50.39

6 5 2 .3 9

653.21

6 5 2 .4 4

65 9 .6 6

6 5 9 .6 9

6 4 6 .8 2

D urable g o o d s ..................................

6 5 2 .9 7

6 7 1 .5 3

6 5 1 .1 7

6 6 9 .0 9

6 84.74

680.21

6 92.22

7 03.08

6 8 8 .0 6

6 8 8 .8 8

6 9 0 .9 7

6 87.19

6 95.14

6 9 5 .5 4

6 7 6 .8 4

W ood p r o d u c ts .............................
N onm etallic m ineral pro d u c ts...
Prim ary m e ta ls ...............................

4 9 2 .0 0
646.91
7 4 9.32

5 2 1 .3 7
6 6 6 .4 4
7 5 0 .4 9

5 19.74

5 37.43
6 8 1 .1 7
7 8 5 .9 3
6 2 1.98
6 8 2.69

6 3 5 .0 9
6 9 6.38

5 17.29
6 6 3 .6 4
7 9 6 .2 9
6 2 6.24
6 8 9.30

5 2 4 .9 6
6 80.85
790.02

5 9 8.50
6 5 1 .1 3

6 7 5 .0 9
754.21
6 0 9.12
6 6 0.96

5 25.62
6 7 9 .4 7
7 7 1 .9 8
6 1 6 .2 3
6 6 7.08

5 2 1 .5 6
6 6 4 .0 0
7 8 7 .6 4

5 9 6 .3 8
6 4 5 .5 5

5 2 6 .0 3
6 7 6 .3 7
7 7 7 .7 5
6 1 7 .1 8
6 7 2.40

5 3 1.42
6 6 9 .5 6
7 9 9 .9 7

F ab rica ted m etal p ro d u c ts .........
M ac h in e ry ........................................

5 1 3.92
665.11
7 6 7 .6 3
6 1 0 .3 3
6 6 4 .7 9

6 2 3.90
6 9 1 .3 5

6 2 5 .2 5
6 9 0 .9 3

5 3 0 .4 0
6 8 4 .8 4
8 00.06
6 2 0 .2 7
9 8 7 .6 5

54 4 .6 5
684.41
8 0 3 .8 8
6 2 7 .7 6
7 0 0 .8 7

5 3 3 .8 9
69 0 .2 0
80 8 .8 9
6 2 7 .8 9
6 9 8 .8 3

5 3 2 .5 2
6 9 2 .8 2
7 8 5 .3 4
6 2 3 .8 3
6 9 0 .5 6

6 4 2 .8 7

TOTAL PRIVATE.................
S e a s o n a lly a d ju s te d ..........

GOODS-PRODUCING...............
Natural resources
and mining..........................
Construction........................
Manufacturing......................

5 2 9 .0 9

C o m p u te r a n d electronic
p ro d u c ts .........................................
Electrical e q u ip m en t an d
a p p lia n c e s ......................................
T ra n sp o rtatio n e q u ip m e n t.........
F urniture a n d re la ted
p ro d u c ts ..........................................

6 7 4 .6 8

6 69.92

6 8 5 .8 5

6 8 4 .2 2

6 8 4.22

693.01

695.91

680.81

695.41

6 9 0.74

6 8 3.80

6 9 4 .6 7

6 9 9 .1 3

70 6 .8 5

5 60.24
8 7 7 .8 7

5 8 2 .6 8
8 9 0 .3 2

568.11
8 2 4 .1 7

5 8 2 .3 4
8 7 0 .7 6

5 8 8.29
9 1 8 .4 6

5 9 2 .0 4
9 0 5 .2 4

6 0 1 .9 6
9 2 5 .7 9

6 1 6 .5 6
9 50.04

5 94.50
9 1 5 .0 6

5 9 1 .9 5
9 1 6 .7 7

596.01
9 1 7 .6 2

5 9 9.40
9 0 5 .6 6

6 1 3 .9 6
9 1 5 .4 7

6 1 1 .9 8
9 1 2 .9 3

6 0 0 .8 7
8 4 4 .4 8

494.01

5 0 5 .2 3

5 0 4 .5 3

5 13.78

5 1 8 .7 6

5 0 8 .6 9

5 23.20

5 28.43

5 10.23

5 0 5 .1 7

5 10.62

5 1 7 .0 6

5 1 7 .6 9

5 2 1 .7 8

51 5 .8 7

M iscellan e o u s
m an u fa ctu rin g ..............................

4 9 9 .1 3

5 1 0 .6 9

5 0 1 .2 3

5 0 5 .5 9

5 15.33

5 15.90

5 3 0 .3 8

5 33.12

5 3 2 .1 5

5 33.50

5 34.66

524.71

5 3 5 .2 6

5 3 1 .0 7

5 3 3 .7 8

N o n d u rab le g o o d s ..........................

5 66.84

5 8 2 .6 5

5 7 5 .1 6

581.61

5 93.62

5 8 8 .2 7

6 00.88

6 02.64

594.11

5 95.20

5 9 6 .0 0

5 95.90

6 0 2.20

604.21

60 0 .6 6

F o o d m a n u fa ctu rin g .....................
B e v e ra g e s a n d to b a c c o
p ro d u c ts .........................................
T extile m ills.....................................
T extile pro d u c t m ills.....................
A p p a rel..............................................
L ea th e r a n d allied p ro d u c ts .......
P a p e r a n d p a p e r p ro d u c ts .........

496.91

502.61

49 9 .4 8

5 0 6 .8 8

5 1 7 .2 9

5 0 5 .6 9

515.11

5 14.12

5 0 4 .7 8

4 9 9 .3 6

49 8 .8 4

4 9 7 .6 6

5 1 1 .1 3

5 1 2 .2 0

5 1 1 .2 9

69 8 .3 9
4 7 6 .5 2
429.01
3 3 3 .6 6
4 1 2 .9 9
7 05.62

70 2 .7 5
4 6 9 .4 7
4 4 5 .0 8
3 4 0 .2 2
4 5 8 .2 6
719.21

69 2 .9 7
4 40.50
4 4 6 .6 9
3 32.02
4 4 9 .2 8
713.71

69 4 .0 3
46 2 .4 7
45 9 .5 5
3 39.30
4 5 1 .6 3
7 10.53

7 07.43
47 5 .5 6
46 7 .9 8
34 1 .9 5
4 4 5 .4 3
7 26.00

7 07.56
46 9 .9 8
458.21
34 8 .8 4
4 6 2 .5 5
7 27.25

7 51.19
4 85.62
45 6 .2 7
35 6 .3 6
4 6 5 .3 0
7 43.63

7 22.76
49 0 .8 4

7 37.27
486.41
4 50.30
34 5 .8 4
4 6 4 .5 2
7 31.84

74 4 .1 6
49 0 .8 5
4 4 1 .1 6
3 50.40
4 6 4 .4 4
7 31.74

7 8 0 .0 8
484.31
4 3 5 .0 7
3 4 7 .7 6
46 0 .1 8
745.71

7 7 4 .1 8
4 8 6 .8 2
4 3 6 .1 8
3 4 6 .6 7
4 4 1 .2 2
7 5 6 .3 2

7 5 8 .5 2

7 5 7 .7 7

4 6 4 .4 6
3 52.80
4 8 5 .5 2
7 51.52

7 28.77
485.61
4 47.70
3 43.82
4 7 1 .6 3
7 38.70

4 9 0 .0 5
4 4 5 .2 2
3 4 8 .4 8
4 4 3 .9 0
7 4 8 .3 3

4 8 1 .2 0
4 3 5 .0 7
3 4 3 .9 0
4 3 1 .4 2
7 4 6 .4 3

Printing a n d re la ted
su p p o rt ac tiv ities.........................
P etro leu m a n d coal
p ro d u c ts ..........................................
C h e m ic a ls ........................................

5 7 3 .0 5

5 87.42

5 7 8 .6 6

5 85.22

5 9 9 .8 5

597.91

6 03.72

6 0 2 .1 7

5 9 3 .2 5

5 9 7 .8 9

6 0 0 .9 9

59 3 .6 3

5 9 4 .0 3

5 9 4 .3 9

6 0 2 .0 8

9 9 0 .8 8
7 5 9 .5 3

1 ,052.97
7 8 4 .5 6

1 ,022.79
7 71.87

1 ,007.94
7 84.92

1 ,045.87
7 9 3 .0 5

1 ,068.08
7 8 5 .5 9

1,099.20
8 08.99

1 ,061.05
8 0 6 .0 9

1,068.96
8 04.04

1,074.94
816.21

1,079.67
811.41

1 ,062.43
81 4 .0 6

1 ,091.13
81 5 .3 4

1 ,098.07
8 1 8 .5 6

1 ,123.12
8 1 3 .4 3

P la s tic s a n d ru b b e r
p ro d u c ts ..........................................

5 4 9 .8 5

5 7 2 .2 3

5 66.57

5 7 2 .2 3

5 83.44

5 78.95

5 86.50

5 96.16

5 85.86

5 88.12

5 8 9 .5 6

5 94.86

59 5 .1 0

5 9 9 .2 4

5 8 3 .5 9

PRIVATE SERVICE­
PROVIDING...........................

4 7 2 .8 8

4 8 4 .0 0

4 8 1 .7 9

4 8 5 .0 9

4 8 3 .0 0

4 8 4 .8 2

4 9 3 .2 4

4 8 5 .2 5

4 8 4 .5 6

4 9 6 .8 2

4 8 6 .6 4

4 8 7 .9 2

4 9 6 .8 2

4 8 9 .0 2

4 9 2 .3 8

Trade, transportation,
and utilities.........................

4 7 1 .2 7

4 8 1 .1 0

4 8 4 .0 2

4 8 5 .4 5

4 8 5 .9 5

4 8 3 .1 7

4 8 6 .6 3

4 8 0.82

4 7 7 .0 5

4 8 8 .4 3

4 8 2 .4 0

4 8 6 .0 5

4 9 3 ..3 7

48 9 .4 4

4 9 4 .1 6

W h o le sa le t r a d e ...............................

6 4 4 .3 8

6 5 7 .1 2

6 5 3.34

6 5 9.30

6 5 8.10

6 6 1 .9 6

6 7 6.06

6 5 9 .9 9

6 5 6.74

6 7 0 .5 6

6 5 8.62

6 6 5 .2 8

R etail tr a d e .........................................

6 7 4 .9 9

661.01

6 6 7 .5 5

360.81

3 6 7 .2 8

3 7 3 .3 5

3 7 3 .3 5

3 7 1 .6 9

3 6 6 .8 3

3 6 5.94

3 6 7.97

3 6 1.80

3 6 8.42

365.71

3 6 7 .2 3

3 7 2 .0 6

37 3 .2 7

3 7 7 .4 8

T ra n sp o rtatio n an d

86

w a re h o u s in g ....................................

5 7 9 .7 5

5 9 7 .7 9

6 0 3 .3 2

604.21

6 0 6.73

6 0 3.47

6 1 5 .0 0

6 0 2 .5 8

5 9 7.50

6 1 3 .4 6

6 0 4 .2 7

6 1 0 .6 5

6 27.00

62 1 .2 3

6 2 7 .9 4

Utilities.................................................

9 7 9 .0 9

1 ,016.94

1,007.78

1,017.21

1 ,026.12

1 ,039.48

1 ,068.45

1 ,028.08

1,032.97

1,039.42

1 ,039.76

1,0 5 3 .2 9

1,0 5 4 .3 9

1,0 4 4 .8 9

1,0 2 6 .1 6

Information...........................

7 38.17

7 61.13

7 6 2 .6 6

7 68.40

7 70.74

7 6 9 .2 5

7 83.10

761.71

7 6 3 .5 6

7 76.72

7 60.00

7 6 4 .6 4

7 7 7 .1 8

7 7 4 .8 2

7 7 1 .3 8

Financial activities.................

575.51

6 0 8 .8 7

6 1 0 .3 4

6 13.84

6 0 7 .9 0

6 08.93

6 2 8 .8 6

6 0 7 .5 5

6 1 2 .1 0

6 3 0 .6 7

6 11.42

6 1 5 .9 9

6 3 7 .8 4

6 11.4 2

61 5 .2 8

Professional and
business services.................

5 74.66

5 8 6 .6 8

5 8 0 .3 8

5 7 9 .7 0

5 7 8 .3 2

580.71

5 9 7 .1 6

5 8 2 .6 7

5 8 3 .9 7

6 02.72

5 87.52

5 8 8 .5 7

6 0 3 .7 7

5 8 9 .5 9

5 9 0 .2 7

Education and
health services....................

49 2 .7 4

5 0 5 .7 6

5 0 4 .5 3

5 0 8 .0 3

5 0 5 .8 6

506.51

5 1 6 .3 3

5 1 2 .2 8

5 14.86

5 19.97

51 3 .2 7

5 1 6 .4 8

5 2 1 .6 0

5 1 8 .7 4

5 2 4 .5 5

Leisure and hospitality...........

22 1 .2 6

22 4 .3 5

2 2 6 .5 5

2 2 8 .2 8

2 2 2 .1 3

2 2 3 .8 9

22 6 .0 5

22 5 .2 9

22 1 .3 6

23 0 .1 4

2 25.80

224.81

2 2 9 .2 2

2 2 7 .4 0

2 3 1 .4 4

Other services.......................

43 9 .7 6

4 3 4 .4 9

430.81

4 3 3 .1 3

43 1 .1 8

431.31

43 4 .8 9

43 0 .2 8

42 9 .2 0

43 3 .6 8

42 8 .7 3

42 8 .5 8

4 3 5 .0 7

428.11

4 2 9 .6 2

1 D a ta re la te to production w o rk ers in natural re s o u rc e s a n d mining a n d m anufacturing,

Industry C lassification S y ste m ( n a ic s ), replacing th e S ta n d a rd Industrial C la s s if ic a tio n

co n stru c tio n w o rk ers in co nstruction, a n d n o n su p erv iso ry w o rk ers in th e serv ic e­
providing industries.

s y s te m . N A ics-based d a ta by industry a r e not c o m p a ra b le with s ic - b a s e d d a ta . S e e "N o tes on
th e data " for a description of th e m o st re c e n t b e n c h m a rk revision.

NOTE:

D ash in d icate s d a ta not available,

D a ta reflect th e co n v e rsio n to th e 2 0 0 2 version of th e North A m erican

Monthly Labor Review

https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

September 2004

p = prelim inary.

(sic)


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

17. Diffusion indexes of employment change, seasonally adjusted
[In percent]________________________________________________________
Tim espan and year

Jan.

Feb.

Mar.

Apr.

May

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

Private nonfarm payrolls, 278 industries
O v e r 1-m o n th s p a n :
2 0 0 0 ............................................................

6 1 .9

6 2 .9

6 3 .3

5 9 .5

4 6 .9

6 1 .7

63.1

5 2 .5

5 1 .5

5 3 .4

5 6 .8

5 3 .8

2 0 0 1 ............................................................

5 2 .2

4 7 .8

5 0 .4

3 4 .4

4 1 .4

3 9 .2

37.1

3 8 .8

3 8 .3

3 2 .4

3 6 .7

3 4 .9

2 0 0 2 ............................................................

40.1

35.1

4 1 .0

4 1 .5

4 1 .7

4 7 .8

44.1

44.1

4 2 .8

3 9 .0

3 8 .7

3 4 .5

2 0 0 3 ............................................................

4 1 .2

35.1

38.1

4 1 .4

4 2 .8

40.1

4 0 .5

3 9 .7

4 9 .3

4 6 .0

51.1

49.1

2 0 0 4 ............................................................

5 2 .3

56.1

6 8 .7

6 7 .6

6 3 .8

60.1

4 9 .5

2 0 0 0 ............................................................

6 9 .2

6 6 .2

6 7 .8

6 8 .3

60.1

58.1

5 6 .3

6 1 .5

5 6 .5

5 3 .2

5 2 .9

5 6 .8

2 0 0 1 ............................................................

5 2 .7

5 0 .4

5 0 .4

4 3 .5

3 8 .8

3 4 .9

3 6 .2

3 7 .9

3 4 .7

3 5 .3

3 0 .8

3 2 .0

O v e r 3 -m o n th s p a n :

2 0 0 2 ............................................................

3 4 .0

3 7 .4

35.1

3 6 .2

3 6 .7

3 9 .4

3 9 .9

4 0 .8

3 8 .7

37.1

3 4 .4

3 4 .7

2 0 0 3 ............................................................

3 6 .5

3 2 .6

3 6 .3

35.1

4 0 .5

4 2 .6

3 7 .4

3 5 .4

40 .1

4 5 .5

5 0 .5

51.1

2 0 0 4 ............................................................

5 4 .0

5 5 .2

6 2 .8

7 0 .0

7 4 .5

69.1

6 1 .0

O v e r 6 -m o n th s p a n :
2 0 0 0 ............................................................

6 7 .3

69.1

7 5 .2

7 2 .5

6 7 .4

6 7 .8

6 6 .7

6 0 .8

5 9 .0

5 5 .0

5 9 .7

5 4 .0

2 0 0 1 ............................................................

5 1 .8

5 0 .0

5 1 .8

4 7 .3

4 3 .5

4 1 .5

38.1

3 5 .4

3 2 .2

33.1

3 1 .5

31.1

2 0 0 2 ............................................................

2 9 .5

3 0 .0

31.1

31.1

3 1 .7

37.1

3 7 .2

3 9 .0

3 4 .7

3 6 .5

3 5 .3

3 3 .3

2 0 0 3 ............................................................

3 3 .6

31.1

3 1 .7

3 1 .7

3 3 .5

3 7 .8

3 6 .2

3 6 .5

4 0 .5

3 9 .4

4 2 .6

4 1 .7

2 0 0 4 ............................................................

4 8 .9

54.1

5 9 .6

6 4 .7

6 7 .8

6 8 .9

6 8 .7

62.1

O v e r 12 -m o n th s p a n :
2 0 0 0 ............................................................

7 0 .9

6 9 .2

7 3 .2

7 1 .0

6 9 .8

7 1 .0

7 0 .0

7 0 .3

7 0 .3

6 5 .6

6 3 .8

2 0 0 1 ............................................................

5 9 .5

5 9 .5

5 3 .4

4 9 .3

4 8 .6

4 5 .0

4 3 .3

4 3 .9

3 9 .9

3 7 .8

37.1

3 4 .9

2 0 0 2 ............................................................

3 3 .6

3 1 .7

3 0 .2

3 0 .4

3 0 .2

29.1

3 2 .0

3 1 .3

3 0 .0

2 9 .5

3 2 .9

3 4 .7

2 0 0 3 ............................................................

3 4 .5

3 1 .5

3 2 .9

3 3 .5

3 6 .2

3 4 .4

3 4 .7

33.1

3 7 .6

3 7 .4

33.1

3 5 .4

2 0 0 4 ............................................................

3 7 .8

4 3 .2

4 7 .3

5 0 .7

5 4 .9

60.1

6 2 .8

Manufacturing payrolls, 84 industries
O v e r 1-m o n th s p a n :
2 0 0 0 ............................................................

4 8 .2

5 8 .3

5 0 .0

5 0 .0

41.1

57.1

6 0 .7

2 8 .6

2 5 .0

35.1

3 9 .9

41.1

2 0 0 1 ............................................................

2 2 .6

2 2 .0

2 1 .4

16.1

1 5 .5

2 3 .2

1 3 .7

1 4 .3

1 9 .0

1 7 .9

1 4 .9

10.1

2 0 0 2 ............................................................

2 1 .4

1 8 .5

2 3 .8

35.1

2 9 .8

3 2 .7

4 0 .5

2 8 .0

3 1 .0

1 1 .9

1 5 .5

1 7 .9

2 0 0 3 ............................................................

2 6 .2

1 5 .5

2 2 .6

1 3 .7

2 6 .2

2 5 .0

2 8 .0

2 6 .2

2 7 .4

2 8 .6

5 1 .2

4 5 .8

2 0 0 4 ............................................................

4 2 .9

5 5 .4

60.1

66.1

6 4 .9

5 1 .2

5 4 .2

2 0 0 0 ............................................................

5 3 .6

5 3 .6

5 6 .0

5 4 .8

4 4 .0

4 4 .0

5 1 .2

4 7 .6

3 2 .7

2 5 .0

2 3 .2

3 8 .7

2 0 0 1 ............................................................

3 5 .7

2 1 .4

16.1

1 4 .3

13.1

1 3 .7

1 1 .9

8 .9

8 .3

13.1

8 .9

10.1

2 0 0 2 ............................................................

9 .5

10.1

1 1 .3

1 7 .9

1 7 .3

1 9 .0

2 8 .0

2 2 .0

2 3 .8

1 5 .5

6 .5

4 .8

2 0 0 3 ............................................................

1 3 .7

13.1

1 6 .7

10.1

13.1

1 4 .9

16.1

16.1

16.1

2 4 .4

2 7 .4

4 1 .7

2 0 0 4 ............................................................

4 8 .8

5 1 .8

5 9 .5

66.1

7 1 .4

6 5 .5

60.1

O v e r 3 -m o n th s p a n :

O v e r 6 -m o n th s p a n :
2 0 0 0 ............................................................

4 4 .0

5 2 .4

5 5 .4

5 7 .7

4 7 .6

5 1 .8

5 6 .0

4 5 .2

3 9 .3

3 4 .5

32.1

2 7 .4

2 0 0 1 ............................................................

2 2 .0

2 3 .8

2 2 .0

2 0 .8

1 4 .3

1 3 .7

1 4 .3

10.1

1 0 .7

5 .4

7.1

4 .8

2 0 0 2 ............................................................

6 .5

8 .9

7 .7

8 .3

7 .7

1 4 .3

1 4 .9

1 0 .7

1 2 .5

10.1

8 .9

8 .9

2 0 0 3 ............................................................

1 1 .3

9 .5

6 .0

7.1

8 .9

13.1

8 .9

13.1

13.1

1 6 .7

1 9 .0

1 9 .6

2 0 0 4 ............................................................

2 8 .6

3 6 .9

4 6 .4

5 6 .5

6 1 .3

6 1 .9

6 6 .7

O v e r 1 2 -m o n th s p a n :
2 0 0 0 ............................................................

4 1 .7

3 9 .3

4 7 .0

5 0 .0

4 6 .4

5 2 .4

5 1 .8

4 9 .4

4 6 .4

4 0 .5

35.1

3 3 .3

2 0 0 1 ............................................................

2 9 .8

32.1

2 0 .8

1 9 .0

13.1

1 2 .5

1 0 .7

1 1 .9

1 1 .9

10.1

8 .3

6 .0

2 0 0 2 ............................................................

7.1

6 .0

6 .0

6 .5

7.1

3 .6

4 .8

6 .0

4 .8

7.1

4 .8

8 .3

2 0 0 3 ............................................................

1 0 .7

6 .0

6 .5

5 .4

8 .3

9 .5

9 .5

9 .5

1 0 .7

1 1 .9

9 .5

1 1 .3

2 0 0 4 ............................................................

9 .5

1 9 .0

1 6 .7

2 6 .2

2 9 .8

3 8 .7

5 0 .0

N o t e : F ig u r e s a r e t h e p e r c e n t o f in d u s tr ie s w ith e m p lo y m e n t

S e e th e "D efinitions" in th is s e c tio n . S e e " N o te s o n t h e d a ta " fo r

in c r e a s in g p lu s o n e - h a lf of t h e in d u s tr ie s w ith u n c h a n g e d

a d e s c rip tio n of th e m o s t r e c e n t b e n c h m a r k re v is io n .

e m p lo y m e n t, w h e r e 5 0 p e r c e n t in d ic a te s a n e q u a l b a l a n c e
b e tw e e n

in d u s tr ie s

w ith

in c r e a s in g

and

d e c re a s in g

D a ta

fo r

th e

tw o

m o st

re cen t

m o n th s

are

p re lim in a ry .

e m p lo y m e n t.

Monthly Labor Review

September 2004

87

Current Labor Statistics:

Labor Force Data

18. Job openings levels and rates by industry and region, seasonally adjusted
Levels (in thousands)1
Industry and region

Rates

2004
Jan.

T o ta l2..................................................................................

Feb.

Mar.

2004

Apr.

May

June

Jan.

Julyp

2 ,8 6 8

2 ,9 0 6

3 ,0 7 9

3 ,1 3 5

3 ,1 0 5

3 ,0 2 2

T o ta l p riv a te 2...........................................................

2 ,5 1 8

2 ,5 3 4

2 ,7 4 0

2 ,7 7 8

2 ,7 4 6

2 ,6 4 0 2 8

C o n s tr u c tio n .....................................................

106

99

113

105

108

94

85

M a n u f a c tu rin g ..................................................

233

226

232

251

244

247

230

T r a d e , tr a n s p o r ta tio n , a n d u tilities..........

430

458

524

531

521

503

571

1 .7

P ro fe s s io n a l a n d b u s i n e s s s e r v ic e s ....

501

491

502

518

530

494

529

3 .0

E d u c a tio n a n d h e a lth s e r v i c e s ................

549

551

559

576

542

496

513

3 .2

Feb.

Mar.

Apr.

May

June

JulyP

3 ,1 9 0

2 .2

2 .2

2 .3

2 .3

2 .3

2 .3

2 .4

36

2 .3

2 .3

2 .5

2 .5

2 .4

2 .3

2 .5

1 .5

1 .4

1 .6

1 .5

1 .5

1 .3

1 .2

1 .6

1 .6

1 .6

1 .7

1 .7

1 .7

1 .6

1 .8

2 .0

2 .0

2 .0

1 .9

2 .2

2 .9

3 .0

3.1

3.1

2 .9

3.1

3 .2

3 .2

3 .3

3.1

2 .9

2 .9

Industry

L e is u re a n d h o s p ita lity ................................

368

383

370

376

391

421

457

2 .9

3 .0

2 .9

3 .0

3.1

3 .3

3 .5

G o v e r n m e n t .............................................................

350

364

353

354

360

380

353

1 .6

1 .7

1 .6

1 .6

1 .6

1 ..7

1 .6

Region5

'

N o r th e a s t ...........................................................

476

500

569

560

526

546

530

1 .9

2 .0

2 .2

2 .2

2 .0

2.1

2.1

S o u t h ...................................................................

1 ,1 3 2

1 ,1 1 2

1 ,1 7 6

1,191

1 ,1 6 4

1 ,1 6 4

1 ,2 3 6

2 .4

2 .4

2 .5

2 .5

2 .5

2 .4

2 .6

M id w e s t...............................................................

679

680

663

692

688

631

655

2 .2

2 .2

2.1

2 .2

2 .2

2 .0

2.1

W e s t ......................................................................

586

632

655

694

765

677

725

2 .0

2 .2

2 .2

2 .4

2 .6

2 .3

2 .5

D etail will n o t n e c e s s a r ily a d d to to ta ls b e c a u s e of t h e in d e p e n d e n t s e a s o n a l

W est

Midwest:

V irginia;

Illinois,

In d ia n a ,

Io w a,

K ansas,

a d ju s t m e n t o f t h e v a r io u s s e r ie s .

M isso u ri, N e b r a s k a , N o rth D a k o ta , O h io , S o u th D a k o ta , W is c o n s in ;

2

C alifo rn ia, C o lo r a d o ,

I n c lu d e s n a tu ra l r e s o u r c e s a n d m in in g , in fo rm a tio n , fin a n c ia l a c tiv itie s , a n d o th e r

N ew

Y ork,

R hode

M o n ta n a ,

N evada,

N ew

A riz o n a,

M ex ico , O r e g o n , U tah ,

N O T E : T h e jo b o p e n in g s lev e l is t h e n u m b e r o f jo b o p e n i n g s o n th e l a s t b u s i n e s s d a y of

C o n n e c tic u t, M a in e , M a s s a c h u s e t t s , N e w H a m p s h ire , N e w J e r s e y ,

P e n n s y lv a n ia ,

Id a h o ,

M in n e s o ta ,

W a s h in g to n , W y o m in g .

s e r v ic e s , n o t s h o w n s e p a r a t e ly .

3 Northeast:

H a w aii,

M ich ig an ,

West: A la s k a ,

Is la n d , V e rm o n t;

South:

t h e m o n th ; t h e jo b o p e n in g s r a te is t h e n u m b e r of jo b o p e n i n g s o n th e l a s t b u s i n e s s d a y of

A la b a m a , A r k a n s a s ,

D e la w a r e , D istrict o f C o lu m b ia , F lo rid a , G e o rg ia , K e n tu c k y , L o u is ia n a , M ary la n d ,

t h e m o n th a s a p e r c e n t of to ta l e m p lo y m e n t p lu s jo b o p e n in g s .

M is s is s ip p i, N o rth C a ro lin a , O k la h o m a , S o u th C a ro lin a , T e n n e s s e e , T e x a s , V irginia,

p = p re lim in ary .

19. Hires levels and rates by industry and region, seasonally adjusted
Levels (in thousands)1
Industry and region

Rates

2004
Jan.

T o ta l2..................................................................................

Feb.

Mar.

2004
Apr.

May

June

Julyp

Jan.

Feb.

Mar.

Apr.

May

June

July"

4 ,1 0 6

4 ,1 0 3

4 ,6 0 3

4 ,3 9 8

4 ,2 0 6

4 ,4 3 3

4 ,2 3 3

T o ta l p riv a te 2...........................................................

3 ,8 0 0

3 ,7 7 2

4 ,2 5 6

4 ,0 9 0

3 ,9 3 8

4 ,1 1 0

3 ,9 3 6

3 .5

3 .5

3 .9

3 .7

3 .6

3 .7

3 .6

C o n s tr u c tio n .....................................................

358

382

437

421

406

436

351

5 .3

5 .6

6 .4

6.1

5 .9

6 .3

5.1
2 .4

3 .2

3 .2

3 .5

3 .4

3 .2

3 .4

3 .2

Industry

M a n u f a c tu rin g ..................................................

349

355

361

354

336

370

349

2 .4

2 .5

2 .5

2 .5

2 .3

2 .6

T r a d e , tr a n s p o r ta tio n , a n d u tilities..........

957

945

1 ,0 0 9

1 ,0 3 2

938

945

939

3 .8

3 .7

4 .0

4.1

3 .7

3 .7

3 .7

P ro fe s s io n a l a n d b u s i n e s s s e r v ic e s ....

708

529

713

609

631

692

621

4 .4

3 .3

4 .4

3 .7

3 .8

4 .2

3 .8

E d u c a tio n a n d h e a lth s e r v ic e s ................

416

447

444

460

451

428

435

2 .5

2 .7

2 .6

2 .7

2 .7

2 .5

2 .6

L e is u re a n d h o s p ita lity ................................

715

766

810

766

739

749

771

5 .9

6 .3

6 .6

6 .2

6 .0

6.1

6 .2

G o v e r n m e n t .............................................................

295

323

343

300

272

328

301

1 .4

1 .5

1 .6

1 .4

1 .3

1 .5

1 .4

3 .0

Region3
N o r th e a s t ...........................................................

722

689

744

810

708

703

760

2 .9

2 .8

3 .0

3 .2

2 .8

2 .8

1 ,5 8 5

1 ,6 0 8

1,781

1 ,5 8 2

1 ,6 0 6

1 ,7 0 9

1 ,6 2 8

3 .4

3 .5

3 .9

3 .4

3 .5

3 .7

3 .5

M id w e s t..............................................................

921

953

1 ,0 4 0

991

956

1 ,0 0 9

914

3 .0

3.1

3 .4

3 .2

3.1

3 .2

2 .9

W e s t .....................................................................

883

876

1 ,0 2 9

1 ,0 9 3

951

1 ,0 2 3

844

3.1

3.1

3 .6

3 .8

3 .3

3 .6

2 .9

Midwest:

Illinois,

S o u t h .....................................................................

1

D etail will n o t n e c e s s a r ily a d d to to ta ls b e c a u s e of t h e i n d e p e n d e n t s e a s o n a l

In d ia n a ,

Iow a,

K ansas,

M ich ig an ,

M in n e s o ta ,

West:

M isso u ri,

a d j u s t m e n t o f t h e v a r io u s s e r ie s .

N e b r a s k a , N orth D a k o ta , O h io , S o u th D a k o ta , W is c o n s in ;

2 In c lu d e s n a tu ra l r e s o u r c e s a n d m in in g , in fo rm a tio n , fin an c ial a c tiv itie s , a n d o th e r

C alifo rn ia , C o lo r a d o , H aw aii, Id a h o , M o n ta n a , N e v a d a , N e w M ex ico , O r e g o n , U tah ,

s e r v ic e s , n o t s h o w n s e p a r a t e ly .

W a s h in g to n , W y o m in g .

3 Northeast:

A la s k a , A riz o n a,

C o n n e c tic u t, M a in e , M a s s a c h u s e t t s , N e w H a m p s h ire , N e w J e r s e y , N ew

Y ork, P e n n s y lv a n ia , R h o d e Is la n d , V e rm o n t;
D istrict of C o lu m b ia , F lo rid a , G e o rg ia ,

South:

K e n tu c k y ,

A la b a m a , A r k a n s a s , D e la w a r e ,

L o u is ia n a ,

M a ry la n d ,

M ississip p i,

N o rth C a ro lin a , O k la h o m a , S o u th C a ro lin a , T e n n e s s e e , T e x a s , V irginia, W e s t V irginia;

Monthly Labor Review
Digitized for 88
FRASER
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

September 2004

N O T E : T h e h ire s level is th e n u m b e r o f h ire s d u rin g t h e e n tire m o n th ; th e h ire s r a te
is t h e n u m b e r of h ire s d u rin g t h e e n tire m o n th a s a p e r c e n t o f to ta l e m p lo y m e n t.
p = p re lim in ary .

20. Total separations levels and rates by industry and region, seasonally adjusted
Rates

Levels (in thousands)1
Industry and region

2004

2004
Jan.

T o ta l2..................................................................................

Mar.

Feb.

Apr.

May

June

Jan.

Julyp

3 .2

3.1

3 .0

Apr

Mar.

Feb.

May

3.1

3.1

June

Julyp

3.1

3.1

3 ,9 6 8

4 ,0 7 3

4 ,1 3 4

4 ,0 8 8

4 ,0 4 0

4 ,0 6 9

4 ,0 1 1

T o ta l p riv a te 2...........................................................

3 ,7 1 6

3 ,8 0 7

3 ,8 6 8

3 ,8 4 3

3 ,7 6 1

3 ,7 8 9

3 ,7 2 5

3 .4

3 .5

3 .5

3 .5

3 .4

3 .5

3 .4

C o n s tr u c tio n .....................................................

436

400

392

391

367

382

380

6 .4

5 .9

5 .7

5 .7

5 .3

5 .5

5 .5
2 .5

Industry

M a n u f a c tu rin g ..................................................

323

355

377

353

377

343

365

2 .3

2 .5

2 .6

2 .5

2 .6

2 .4

T r a d e , tr a n s p o r ta tio n , a n d u tilities.........

936

899

978

1 ,0 1 3

917

927

939

3 .7

3 .5

3 .8

4 .0

3 .6

3 .6

3 .7

P ro fe s s io n a l a n d b u s i n e s s s e r v ic e s ....

572

590

597

606

556

607

576

3 .5

3 .6

3 .7

3 .7

3 .4

3 .7

3 .5

E d u c a tio n a n d h e a lth s e r v i c e s ................

389

388

382

386

379

362

368

2 .3

2 .3

2 .3

2 .3

2 .2

2.1

2 .2

709

727

715

679

696

734

680

5 .8

5 .9

5 .8

5 .5

5 .6

5 .9

5 .5

258

268

284

245

268

270

273

1 .2

1 .2

1 .3

1.1

1 .2

1 .3

1 .3

2 .8

G o v e r n m e n t .............................................................

Region3
N o r th e a s t ............................................................

712

688

666

716

648

704

699

2 .9

2 .8

2 .7

2 .9

2 .6

2 .8

S o u th ....................................................................

1 ,5 0 5

1 ,4 9 9

1 ,6 1 2

1 ,5 2 4

1 ,5 0 4

1 ,5 3 3

1 ,5 0 5

3 .3

3 .3

3 .5

3 .3

3 .2

3 .3

3 .2

903

929

938

877

833

853

904

2 .9

3 .0

3 .0

2 .8

2 .7

2 .7

2 .9

896

941

1 ,0 0 3

959

1 ,0 0 8

979

915

3 .2

3 .3

3 .5

3 .4

3 .5

3 .4

3 .2

W e s t .....................................................................

1 D etail will n o t n e c e s s a r ily a d d to to ta ls b e c a u s e o f t h e i n d e p e n d e n t s e a s o n a l a d ju s tm e n t

Midwest:

o f t h e v a r io u s s e r ie s .

N orth

2

In c lu d e s n a tu ra l r e s o u r c e s a n d

m in in g , in fo rm a tio n , fin a n c ia l a c tiv itie s , a n d

o th e r

Iow a,

K a n s a s , M ich ig an , M in n e s o ta , M isso u ri, N e b ra s k i

D a k o ta , W is c o n s in ;

West:

A la s k a , A riz o n a , C alifornii

C o lo r a d o , H aw aii, Id a h o , M o n ta n a , N e v a d a , N e w M ex ico , O r e g o n , U ta h , W a s h in g to r
W y o m in g .

s e r v ic e s , n o t s h o w n s e p a r a t e ly .

3 Northeast:

Illinois, In d ia n a ,

D a k o ta , O h io , S o u th

C o n n e c tic u t, M a in e , M a s s a c h u s e t t s , N e w H a m p s h ire , N e w J e r s e y , N ew

Y ork, P e n n s y lv a n ia ,

R hode

Is la n d , V e rm o n t;

D istrict of C o lu m b ia , F lo rid a ,

G e o rg ia ,

South:

K e n tu c k y ,

A la b a m a , A r k a n s a s ,

L o u is ia n a ,

M ary la n d ,

D e la w a r e ,
M ississip p i,

N o rth C a ro lin a , O k la h o m a , S o u th C a ro lin a , T e n n e s s e e , T e x a s , V irginia, W e s t V irginia;

N O T E : T h e to ta l s e p a r a t i o n s lev e l is t h e n u m b e r o f to tal s e p a r a t i o n s d u rin g t h e e n tir
m o n th ; t h e to tal s e p a r a t i o n s r a te is th e n u m b e r of to ta l s e p a r a t i o n s d u rin g th e e n tir
m o n th a s a p e r c e n t of to tal e m p lo y m e n t.
p = p re lim in ary .

21. Quits levels and rates by industry and region, seasonally adjusted
Rates

Levels (in thousands)1
Industry and region

2004

2004
Jan.

T o ta l2..................................................................................

Feb.

Mar.

Apr.

May

June

Jan.

Julyp

2 ,1 1 8

2 ,1 7 8

2 ,2 7 1

2 ,2 7 8

2 ,1 7 3

2 ,2 8 4

2 ,2 3 5

2 ,0 0 2

2 ,0 5 1

2 ,1 4 4

2 ,1 5 1

2 ,0 2 6

2 ,1 6 2

2 ,1 1 3

148

133

154

149

144

156

123

Apr.

Mar.

Feb.

May

1 .7

June

1 .7

Julyp

1 .7

1 .7

1 .7

1 .7

1 .8

1 .9

2 .0

2 .0

1 .9

2 .0

1 .9

2 .2

2 .0

2 .3

2 .2

2.1

2 .3

1 .8

1 .6

industry
T o ta l p riv a te 2...........................................................

M a n u f a c tu rin g ..................................................

165

169

176

189

171

171

180

1 .2

1 .2

1 .2

1 .3

1 .2

1 .2

1 .3

T r a d e , tr a n s p o r ta tio n , a n d u tilities........

530

493

530

563

525

536

547

2.1

1 .9

2.1

2 .2

2.1

2.1

2.1

P ro fe s s io n a l a n d b u s i n e s s s e r v i c e s ....

261

302

309

323

259

322

306

1.6

1.9

1 .9

2 .0

1 .6

2 .0

1 .9

E d u c a tio n a n d h e a lth s e r v ic e s ................

237

234

252

245

223

225

264

1 .4

1 .4

1 .5

1 .5

1 .3

1 .3

1 .6

428

447

465

429

455

480

430

3 .5

3 .7

3 .8

3 .5

3 .7

3 .9

3 .5

116

126

129

129

129

123

123

.5

.6

.6

.6

.6

.6

.6

G o v e r n m e n t ................................... .........................

Region3
288

319

314

390

318

334

347

1 .2

1 .3

1 .3

1 .6

1 .3

1 .3

1 .4

852

867

957

888

857

910

869

1 .9

1 .9

2.1

1.9

1 .8

2 .0

1 .9

M id w e s t..............................................................

513

455

474

479

479

485

501

1.7

1 .5

1 .5

1 .5

1 .5

1 .6

1 .6

W e s t .....................................................................

475

520

565

524

521

573

508

1 .7

1 .8

2 .0

1 .8

1 .8

2 .0

1 .8

Io w a,

K ansas,

S o u t h ...................................................................

1 D etail will n o t n e c e s s a r ily a d d to t o ta ls b e c a u s e o f t h e i n d e p e n d e n t s e a s o n a l a d ju s tm e n t

Midwest:

o f t h e v a r io u s s e r ie s .

N e b r a s k a , N o rth D a k o ta , O h io , S o u th D a k o ta , W is c o n s in ;

2

I n c lu d e s n a tu ra l r e s o u r c e s a n d

m in in g , in fo rm a tio n , fin an c ial a c tiv itie s , a n d o th e r

Y ork,

In d ia n a ,

M ich ig an ,

M in n e s o ta ,

West:

M isso u ri,

A la s k a , A riz o n a,

C alifo rn ia , C o lo r a d o , H aw aii, Id a h o , M o n ta n a , N e v a d a , N e w M ex ico , O r e g o n , U tah ,
W a s h in g to n , W y o m in g .

s e r v ic e s , n o t s h o w n s e p a r a t e ly .

3 Northeast:

Illinois,

C o n n e c tic u t, M ain e, M a s s a c h u s e t t s , N e w H a m p s h ire , N e w J e r s e y , N ew

P e n n s y lv a n ia ,

R hode

D istrict o f C o lu m b ia , F lo rid a ,

Is la n d , V e rm o n t;
G e o rg ia ,

South:

K e n tu c k y ,

A la b a m a , A r k a n s a s ,

L o u is ia n a ,

M a ry la n d ,

N o rth C a ro lin a , O k la h o m a , S o u th C a ro lin a , T e n n e s s e e , T e x a s , V irginia,


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

D e la w a re ,
M ississip p i,

W e s t V irginia;

N O T E : T h e q u its level is t h e n u m b e r o f q u its d u rin g th e e n tir e m o n th ; t h e q u its r a te
is t h e n u m b e r of q u its d u rin g t h e e n tire m o n th a s a p e r c e n t o f to tal e m p lo y m e n t.
p = p re lim in ary .

Monthly Labor Review

September 2004

89

Current Labor Statistics:

22.

Labor Force Data

Quarterly Census of Employment and Wages: 10 largest counties, fourth quarter 2003.
Establishments,
fourth quarter
2003
(thousands)

County by NAICS supersector

Average weekly wage1

Percent change,
December
2002-032

Fourth
quarter
2003

Percent change,
fourth quarter
2002-032

U nited S ta t e s 3 ...................................................
P rivate industry .................................
N atural re s o u rc e s a n d m ining ......................................
C o n stru ctio n ........................................................
M anufacturing .........................................
T ra d e , tra n sp o rta tio n , a n d u tilitie s ...............................
Inform ation ......................................
F inancial a c t iv i t i e s ................................................
P ro fe s sio n a l a n d b u s in e s s s e r v i c e s ...........................
E d u ca tio n a n d h e a lth s e rv ic e s .....................................
L eisu re a n d hospitality ....................................................
O th e r s e rv ic e s ..........................................
G o v e rn m en t ............................................................

8,314.1
8 ,0 4 8 .7
123.7
8 0 4 .9
3 7 6 .8
1,853.6
145.2
767.0
1,329.4
732.2
66 9 .9
1,080.6
2 6 5 .3

1 2 9 ,3 4 1 .5
108,215.1
1,5 5 7 .8
6 ,6 8 9 .5
14 ,3 0 7 .8
2 5 ,9 5 7 .3
3 ,1 6 5 .9
7 ,8 7 4 .7
16 ,1 1 3 .2
15 ,9 7 4 .0
12 ,0 4 2 .8
4,274.1
2 1 ,1 2 6 .3

.0
.1
1.2
-4.2
-.3
-4.0
1.2
.6
2.1
1.7
-.1
-.2

$767
769
703
837
943
665
1,139
1,1 3 8
945
731
335
494
757

2 .4

L os A n g e le s, CA ....................................................
P rivate ind ustry .........................................
N atural re s o u rc e s a n d m ining ......................................
C o n s tr u c tio n ........................................................
M anufacturing ....................................
T ra d e , tra n sp o rta tio n , a n d u tilitie s ..............................
Inform ation .................................................
F inancial a c t iv i t i e s .......................................
P ro fe ssio n a l a n d b u s in e s s s e r v i c e s ...........................
E d u ca tio n a n d h ea lth s e r v ic e s .....................................
L eisu re a n d hospitality ...............................................
O th e r s e r v i c e s ......................................
G o v e rn m e n t ...............................................

3 5 6 .0
3 5 2 .2
.6
12.9
17.8
53 .9
9.2
2 3 .0
40.1
2 6 .6
2 5 .6
142.1
3 .8

4 ,0 7 5 .3
3 ,4 8 6 .3
11.0
133.9
4 8 5 .2
7 9 4 .6
194.9
2 3 7 .9
57 5 .0
4 5 6 .5
37 5 .9
2 2 0 .7
5 8 9 .0

-.5
-.2
.7
-1.1
-7.1
-1.2
-2.0
.9
1.6
1.9
5.6
3 .5
-2.3

903
898
955
883
900
735
1 ,6 2 7
1,258
1,0 4 3
820
766
422
930

4 2
4 .2
16 9
1.7
6 .5
2 7
5 .2
7 0
3 7
3 9
6 .5
5 0
3 .3

C ook, I L ................................................................
P rivate industry .......................................................
N atural re s o u rc e s a n d m ining ......................................
C o n s tr u c tio n .................................................
M anufacturing .................................................
T ra d e , tra n sp o rta tio n , a n d u tilitie s ................................
Inform ation ........................................................
F inancial a c t iv i t i e s ...........................................
P ro fe ssio n a l a n d b u s in e s s s e r v i c e s ............................
E d u ca tio n a n d h ea lth s e r v ic e s ....................................
L eisu re a n d hospitality ..................................................
O th e r s e r v i c e s ................................................
G o v e rn m e n t ....................................................

126.7
125.5
.1
10.5
7.9
2 6 .7
2 .5
13.8
26.1
12.3
10.5
12.6
1.2

2 ,5 3 9 .8
2 ,2 2 1 .9
1.3
9 6 .7
2 6 5 .7
4 9 9 .4
66.1
2 1 9 .4
4 0 5 .5
3 5 0 .8
2 1 7 .7
95.1
3 1 7 .9

-1.2
-.9
-3.6
.0
-5.1
-.8
-4.1
-.8
-1.3
1.0
2 .8
-2.0
-3.1

922
929
1,0 3 7
1,169
975
753
1 ,1 6 4
1,471
1,206
791
375
655
871

3 .0
3 .2
3 2
-8
6 .3
4
.1
8.1
4.1
3 .7
-.3
3 0
.9

111.9
111.7
.0
2 .2
3 .5
22.1
4 .3
16.7
22 .6
7.8
10.1
16.0
.2

2 ,2 5 3 .6
1 ,8 0 0 .4
.1
30 .0
4 6 .6
2 4 7 .6
130.6
3 5 2 .0
4 3 9 .7
2 7 3 .8
188.2
82 .9
4 5 3 .2

-1.0
-.6
.0
-4.5
-4.9
-1.2
-5.1
-2.0
.5
2 .4
.4
-1.1
-2.2

1,480
1,6 2 3
1,1 9 7
1,5 6 7
1,290
1 ,1 6 4
1,751
3 ,0 3 4
1,702
918
787
871
912

7 .2
8.1
-6 5
3 .4
6 .4
5 5
7.9
16.1
2 6
7.6
6.1
6 1
.1

8 9 .4
89 .0
1.2
6 .3
4 .7
21.1
1.4
9 .7
17.0
8 .8
6 .5
10.3
.4

1,8 4 1 .5
1,595.2
6 2 .5
135.5
164.0
4 0 3 .2
3 3 .8
113.1
2 7 9 .0
188.3
155.2
5 6 .3
2 4 6 .3

-.9
-1.2
8 .7
-5.0
-4.9
-2.1
-3.9
1.7
-1.7
1.5
.7
-3.1
1.1

906
929
2 ,1 8 5
919
1,106
821
1,0 9 8
1,181
1,073
812
335
539
759

2.1
2.1
-9

3.1

8 0 .9
8 0 .5
.5
8.4
3 .3
18.6
1.6
9 .5
18.1
7.6
5 .6
5 .7
.5

1,6 2 1 .2
1 ,4 0 1 .8
9 .8
131.7
128.0
33 6 .4
36 .6
133.3
2 6 1 .5
160.5
155.8
4 4 .7
2 1 9 .4

(4)
2.2
-2.6
5.9
-2.5
1.5
-4.1
1.5
4.2
5.6
.8
-2.6
1.6

757
755
545
779
1,050
712
872
933
776
842
364
500
766

4 .0
3.9
4 4
2.1
8 .2
3 .2
.5
3 .7
3 5
5 .0
2 .8
2 .2
3 .7

N ew York, N Y .................................................
P riv ate industry ...............................................
N atural re s o u rc e s a n d m ining .......................................
C o n s tr u c tio n ...................................................
M anufacturing ...................................................
T ra d e , tra n sp o rta tio n , a n d u tilitie s ................................
Inform ation .........................................
F inancial a c t iv i t i e s .......................................
P ro fe s sio n a l a n d b u s in e s s s e r v i c e s ............................
E d u ca tio n a n d h ea lth s e rv ic e s ......................................
L eisu re a n d hospitality ................................................
O th e r s e r v i c e s .................................................
G o v e rn m e n t ............................................
H arris, T X ............................................................
P riv ate industry ..........................................................
N atural re s o u rc e s a n d m ining .......................................
C o n s tr u c tio n ..............................................................
M anufacturing .....................................................
T ra d e , tra n sp o rta tio n , a n d u tilitie s ................................
Inform ation ..............................................
F inancial a c tiv itie s .....................................................
P ro fe ssio n a l a n d b u s in e s s s e r v i c e s ............................
E d u ca tio n a n d h ea lth s e rv ic e s ......................................
L eisu re a n d hospitality ...........................................
O th er s e r v i c e s ......................................
G o v e rn m e n t ......................................................

................
...............
...............
..............
...............
...............
................
...............
...............

...............
...............
...............
................
...............
...............

M aricopa, A Z ............................................................
P rivate industry ............................................
N atural re s o u rc e s an d m ining ........................................
C o n s tr u c tio n ............................................................
M anufacturing .............................................................
T ra d e , tran sp o rta tio n , a n d u tilitie s .................................
Inform ation .............................................................
F inancial a c tiv itie s .......................................
P ro fe ssio n a l a n d b u s in e s s s e r v i c e s ........................
E d u ca tio n a n d h ea lth s e r v i c e s ...........................
L eisu re a n d hospitality ..................................
O th er s e r v i c e s ......................................
G o v e rn m en t ...........................................................

S e e fo o tn o te s a t e n d of ta b le .

90

Employment
December
2003
(thousands)

Monthly Labor Review


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

September 2004

0.0

3 .6
3 9
2 3
6 7
3 4
3 9
5 9
3 8
3 8
3 .4

2 .6
2 .3
1 0
4
4 9
3 2
1 8
-.9
4

22. Continued—Quarterly Census of Employment and Wages: 10 largest counties, fourth quarter 2003.

County by NAICS supersector

Establishments,
fourth quarter
2003
(thousands)

Employment
December
2003
(thousands)

Average weekly wage1

Percent change,
December
2002-032

Fourth
quarter
2003

Percent change,
fourth quarter
2002-032

D a lla s, T X ................................................................................................................
P riv a te in d u s try ...............................................................................................
N a tu ra l r e s o u r c e s a n d m ining ............................................................
C o n s t r u c t i o n ................................................................................................
M a n u fa c tu rin g ............................................................................................
T r a d e , tra n s p o r ta tio n , a n d u t i li t i e s ....................................................
In fo rm atio n ...................................................................................................
F in a n c ia l a c t i v i t i e s ....................................................................................
P ro fe s s io n a l a n d b u s i n e s s s e r v i c e s ................................................
E d u c a tio n a n d h e a lth s e r v ic e s ...........................................................
L e is u re a n d h o s p ita lity ...........................................................................
O th e r s e r v i c e s ............................................................................................
G o v e r n m e n t .....................................................................................................

6 8 .6
6 8 .2
.5
4 .5
3 .5
1 5 .8
1 .9
8 .6
14 .0
6 .3
5 .2
6 .7
.4

1 ,4 5 0 .8
1 ,2 9 4 .6
6 .8
7 3 .0
1 4 4 .9
326.1
6 4 .0
1 4 0 .0
2 3 7 .7
1 3 1 .4
1 2 7 .5
4 0 .5
1 5 6 .2

-1 .4
-1 .4
-2 0 .5
-2 .2
-3.1
-3 .3
-5.1
1 .2
.0
2 .4
.0
-3 .4
-1 .8

$952
970
2 ,6 8 0
909
1 ,0 7 5
898
1 ,2 7 2
1 ,2 1 5
1 ,1 5 2
887
432
587
800

4 .3
4 .8
2 2 .7
5 .5
6 .8
5 .2
8 .7
2 .9
4 .2
2 .7
4 .3
2 .8
-.1

O r a n g e , C A ............................................................................................................
P riv a te in d u s try ...............................................................................................
N a tu ra l r e s o u r c e s a n d m in in g ............................................................
C o n s t r u c t i o n ................................................................................................
M a n u fa c tu rin g ............................................................................................
T r a d e , tra n s p o r ta tio n , a n d u t i li t i e s ....................................................
In fo rm a tio n ...................................................................................................
F in a n c ia l a c t i v i t i e s ....................................................................................
P ro fe s s io n a l a n d b u s i n e s s s e r v i c e s ................................................
E d u c a tio n a n d h e a lth s e r v ic e s ...........................................................
L e is u re a n d h o s p ita lity ...........................................................................
O th e r s e r v i c e s ............................................................................................
G o v e r n m e n t .....................................................................................................

8 8 .8
8 7 .4
.3
6 .4
6.1
1 7 .3
1 .5
9 .7
1 7 .4
9.1
6 .6
1 2 .9
1 .4

1 ,4 3 6 .6
1 ,3 0 5 .5
6.1
8 5 .5
1 7 9 .9
2 7 8 .8
3 3 .8
1 2 7 .8
2 6 1 .0
1 2 6 .6
1 5 9 .9
4 6 .0
131.1

1 .3
2.1
8 .3
4 .4
-3 .0
.6
-4 .4
9 .9
1.0
6.1
2 .5
6 .3
-5 .7

874
875
579
969
1 ,0 3 6
802
1 ,1 5 2
1 ,3 5 4
942
849
358
518
859

5 .3
5 .2
.2
5 .9
1 1 .4
2 .7
5 .3
6 .2
2 .8
3 .7
3 .8
3 .0
6 .0

S a n D ie g o , C A .....................................................................................................
P riv a te in d u s try ...............................................................................................
N a tu ra l r e s o u r c e s a n d m ining ............................................................
C o n s t r u c t i o n ................................................................................................
M a n u fa c tu rin g ............................................................................................
T r a d e , tra n s p o r ta tio n , a n d u t i li t i e s ....................................................
In fo rm atio n ...................................................................................................
F in a n c ia l a c t i v i t i e s ....................................................................................
P ro fe s s io n a l a n d b u s i n e s s s e r v i c e s ................................................
E d u c a tio n a n d h e a lth s e r v ic e s ...........................................................
L e is u re a n d h o s p ita lity ...........................................................................
O th e r s e r v i c e s ............................................................................................
G o v e r n m e n t .....................................................................................................

8 5 .3
8 3 .9
.9
6 .4
3 .6
1 4 .2
1 .4
8 .8
1 4 .9
7 .6
6 .5
1 9 .5
1 .3

1 ,2 7 8 .2
1 ,0 6 0 .2
1 1 .0
81.1
1 0 5 .4
2 2 0 .4
3 6 .7
8 1 .6
2 0 8 .1
1 2 2 .6
1 4 1 .5
5 1 .6
2 1 8 .0

1 .3
1 .5
-5 .4
4 .7
-4 .2
2 .2
-4 .5
4 .8
1 .5
1 .6
3 .5
1 .8
.1

815
809
491
869
1 ,1 2 9
655
1 ,5 8 2
1 ,0 5 8
989
778
346
449
843

2 .6
2 .5
1 .0
.7
1 1 .5
.9
-2 .0
.4
2 .8
5 .7
2 .4
2 .7
2 .9

K ing, W A .................................................................................................................
P riv a te in d u s try ...............................................................................................
N a tu ra l r e s o u r c e s a n d m ining ............................................................
C o n s tr u c tio n ................................................................................................
M a n u fa c tu rin g ............................................................................................
T r a d e , tra n s p o r ta tio n , a n d u t i li t i e s ....................................................
In fo rm a tio n ...................................................................................................
F in a n c ia l a c t i v i t i e s ....................................................................................
P ro fe s s io n a l a n d b u s i n e s s s e r v i c e s ................................................
E d u c a tio n a n d h e a lth s e r v ic e s ...........................................................
L e is u re a n d h o s p ita lity ...........................................................................
O th e r s e r v i c e s ............................................................................................
G o v e r n m e n t .....................................................................................................

8 1 .6
8 1 .0
.4
6 .2
2 .7
1 4 .8
1 .5
6.1
1 1 .7
5 .9
5 .4
2 6 .4
.6

1 ,1 0 0 .6
9 4 5 .5
2 .8
5 3 .4
1 0 1 .9
2 2 5 .5
6 9 .2
7 7 .5
1 5 8 .3
1 0 8 .3
1 0 0 .5
48.1
155.1

.2
.1
-1 1 .3
-.4
-8 .2
1.1
.8
2 .4
.7
1 .5
2 .9
1 .2
1 .0

935
944
1 ,1 0 9
921
1 ,1 7 6
804
1 ,8 2 9
1 ,1 1 4
1 ,1 6 0
746
390
463
882

.2
-.3
.8
1 .4
-2.1
2 .6
-1 5 .7
3 .5
8 .4
4 .8
3 .7
.4
3 .6

M ia m i-D a d e , F L ....................................................................................................
P riv a te in d u s try ...............................................................................................
N a tu ra l r e s o u r c e s a n d m ining ............................................................
C o n s t r u c t i o n ................................................................................................
M a n u fa c tu rin g ............................................................................................
T ra d e , tr a n s p o r ta tio n , a n d u t i li t i e s ....................................................
In fo rm atio n ...................................................................................................
F in a n c ia l a c t i v i t i e s ....................................................................................
P ro fe s s io n a l a n d b u s i n e s s s e r v i c e s ................................................
E d u c a tio n a n d h e a lth s e r v ic e s ...........................................................
L e is u re a n d h o s p ita lity ...........................................................................
O th e r s e r v i c e s ............................................................................................
G o v e r n m e n t .....................................................................................................

8 0 .2
7 9 .9
.5
4 .9
2 .8
2 3 .2
1 .7
8 .2
1 5 .9
7 .8
5 .3
7 .5
.3

9 8 0 .8
8 2 7 .5
9 .9
4 0 .7
4 9 .4
2 4 7 .2
2 8 .5
6 5 .5
1 3 2 .0
1 2 3 .4
9 2 .8
3 4 .5
1 5 3 .3

-.5
-.7
-1 .8
.3
-9 .8
-1 .7
-3 .2
.7
-.2
1 .4
2.1
-1 .8
.5

765
742
421
788
695
689
990
1 ,0 6 2
948
748
432
450
886

3 .5
3 .6
4 .0
2 .7
5 .8
4 .2
1 .7
-1.1
5 .2
2 .3
9 .9
3 .0
2 .8

1 A v e r a g e w e e k ly w a g e s w e r e c a lc u la te d u s in g u n ro u n d e d d a ta .
2 P e r c e n t c h a n g e s w e r e c o m p u te d from q u a rte rly e m p lo y m e n t a n d p a y d a t a
a d j u s t e d for n o n e c o n o m ic c o u n ty r e c la s s ific a tio n s . S e e N o te s o n C u rre n t L a b o r
S ta tis tic s .
3 T o ta ls for t h e U n ite d S t a t e s d o n o t in c lu d e d a t a fo r P u e rto R ico o r th e


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

V irgin Is la n d s .
4 D a ta d o n o t m e e t B L S o r S ta t e a g e n c y d is c lo s u re s t a n d a r d s .
N O T E : In c lu d e s w o r k e rs c o v e r e d b y U n e m p lo y m e n t In s u r a n c e (U l) a n d
U n e m p lo y m e n t C o m p e n s a tio n for F e d e r a l E m p lo y e e s (U C F E ) p ro g r a m s . D a ta a r e
p re lim in ary .

Monthly Labor Review

September 2004

91

Current Labor Statistics:

23.

Labor Force Data

Quarterly Census of Employment and Wages: by State, fourth quarter 2003.
Establishments,
fourth quarter
2003
(thousands)

State

Employment
December
2003
(thousands)

Fourth
quarter
2003

Percent change,
fourth quarter
2002-03

U n ite d S t a t e s 2 .............................................

8 ,3 1 4 .1

1 2 9 ,3 4 1 .5

0 .0

$767

3 .6

A l a b a m a ..........................................................
A l a s k a .............................................................
A r i z o n a ............................................................
A r k a n s a s ........................................................
C a l i f o r n i a ........................................................
C o lo r a d o ........................................................
C o n n e c t i c u t ...................................................
D e l a w a r e ........................................................
D istrict o f C o l u m b i a ...................................
F l o r i d a .............................................................

1 1 1 .8
2 0 .0
1 2 6 .9
7 5 .2
1 ,1 9 0 .8
1 6 0 .0
109.1
27.1
3 0 .0
504.1

1,838.1
2 8 2 .7
2 ,3 5 2 .1
1 ,1 3 3 .6
1 4 ,9 2 2 .3
2 ,1 3 4 .6
1 ,6 4 8 .9
4 0 8 .4
6 5 4 .8
7 ,4 2 4 .5

-.1
1.1
2 .2
.5
.0
-1.1
-.7
.5
-.4
.8

657
746
710
587
869
784
992
825
1 ,2 3 8
685

4 .0
1.1
3 .8
4.1
3 .8
2 .0
3 .8
5 .0
3 .9
3 .8

G e o r g i a ...........................................................
H aw aii .............................................................
I d a h o ................................................................
I l l i n o is ............................................................
I n d i a n a ............................................................
Io w a .................................................................
K a n s a s ............................................................
K e n tu c k y ........................................................
L o u i s i a n a ........................................................
M a in e ...............................................................

2 4 5 .6
3 7 .4
4 8 .5
3 2 5 .7
152.1
9 0 .6
8 2 .2
1 0 5 .7
1 1 4 .0
4 7 .4

3 ,8 4 5 .6
5 8 3 .0
5 7 7 .5
5 ,7 3 8 .7
2 ,8 5 2 .2
1 ,4 1 8 .5
1 ,2 9 8 .3
1 ,7 4 0 .6
1 ,8 7 0 .9
5 9 5 .8

.2
1 .3
.6
-1 .2
-.3
.0
-.9
.3
.5
.7

734
678
579
827
675
626
631
645
628
631

2 .8
3 .7
1 .8
3 .2
3 .5
4 .7
2 .8
3 .5
2 .4
4 .6

M a ry la n d ........................................................
M a s s a c h u s e t t s ............................................
M i c h i g a n .........................................................
M in n e s o ta .....................................................
M is s is s i p p i ......................................................
M is s o u r i ...........................................................
M o n t a n a .........................................................
N e b r a s k a ........................................................
N e v a d a ............................................................
N e w H a m p s h ire .........................................

1 5 0 .4
2 0 6 .6
2 5 1 .3
1 5 9 .0
6 5 .6
1 6 5 .4
4 2 .0
5 5 .3
6 0 .3
4 7 .0

2 ,4 6 6 .4
3 ,1 5 4 .6
4 ,3 6 5 .8
2 ,5 9 1 .9
1,1 0 8 .1
2 ,6 3 3 .6
3 9 6 .6
8 8 4 .4
1 ,1 1 1 .2
6 1 4 .9

.7
-1 .9
-1.1
-.5
.4
-.7
1.1
.6
4 .4
.6

831
954
806
777
559
676
549
613
721
788

3 .6
5 .2
3 .9
3 .2
3 .7
2 .4
4 .0
3 .2
5.1
4 .0

N e w J e r s e y ...................................................
N e w M ex ico .................................................
N e w Y ork ......................................................
N o rth C a r o l i n a .............................................
N o rth D a k o t a ................................................
O h io .................................................................
O k l a h o m a .......................................................
O r e g o n ............................................................
P e n n s y l v a n i a ................................................
R h o d e I s l a n d ................................................

2 6 8 .1
5 0 .4
5 5 0 .3
2 2 7 .8
2 4 .0
2 9 4 .2
9 1 .6
1 1 8 .8
3 2 6 .9
3 4 .7

3 ,9 1 2 .8
757.1
8 ,3 7 9 .2
3 ,7 5 9 .6
3 1 7 .6
5 ,3 2 2 .4
1 ,4 2 3 .4
1 ,5 7 9 .8
5 ,5 2 4 .5
4 8 0 .5

.1
1.4
-.4
-.1
.9
-.7
-1 .3
.2
-.2
1 .2

945
612
959
679
563
713
597
694
750
738

3 .4
4.1
5 .2
4 .5
4 .3
3 .8
4 .2
3 .3
4 .7
5.1

S o u th C a r o l i n a ............................................
S o u th D a k o t a ...............................................
T e n n e s s e e ....................................................
T e x a s ...............................................................
U ta h .................................................................
V e rm o n t .........................................................
V i r g i n i a ............................................................
W a s h i n g t o n ...................................................
W e s t V i r g i n i a ................................................
W i s c o n s i n .......................................................

1 0 8 .4
28.1
1 2 8 .4
5 0 5 .3
7 3 .9
24.1
2 0 2 .6
2 2 2 .7
4 7 .2
1 5 7 .6

1 ,7 8 1 .0
3 6 5 .4
2 ,6 4 8 .0
9 ,3 0 0 .1
1 ,0 6 6 .2
3 0 0 .7
3 ,4 7 7 .5
2 ,6 5 4 .7
6 8 5 .2
2 ,7 1 5 .4

.3
.3
.4
-.3
1 .2
.3
1.2
1.0
.1
.0

623
559
689
754
630
661
786
759
587
683

3.1
4.1
4 .2
3.1
2 .3
5.1
5 .2
1 .3
2.1
4.1

W y o m i n g ........................................................

2 2 .0

2 4 1 .6

1.7

616

4.1

P u e r to R i c o ...................................................
V irgin Is la n d s ...............................................

5 0 .2
3 .2

1,0 7 4 .1
4 2 .5

3 .5
-.2

450
629

4 .7
2 .4

1 A v e r a g e w e e k ly w a g e s w e r e c a lc u la te d u s in g u n r o u n d e d d a ta .
2 T o ta ls fo r t h e U n ite d S t a t e s d o n o t in c lu d e d a t a for P u e rto R ico
o r t h e V irgin Is la n d s .

92

Average weekly wage1

Percent change,
December
2002-03

Monthly Labor Review


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

September 2004

N O T E : In c lu d e s w o r k e rs c o v e r e d by U n e m p lo y m e n t I n s u r a n c e (Ul)
a n d U n e m p lo y m e n t C o m p e n s a tio n for F e d e r a l E m p lo y e e s (U C F E )
p ro g r a m s . D a ta a r e p re lim in ary .


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

24.

Annual data: Quarterly Census of Employment and Wages, by ownership
Year

Average
establishments

Average
annual
employment

Total annual wages Average annual wage
per employee
(in thousands)

Average
weekly
wage

Total covered (Ul and UCFE)
1 9 9 3 .................................................................
1 9 9 4 .................................................................
1 9 9 5 .................................................................
1 9 9 6 .................................................................
1 9 9 7 .................................................................
1 9 9 8 .................................................................
1 9 9 9 .................................................................
2 0 0 0 .................................................................
2 001 .................................................................
2 0 0 2 .................................................................

6 ,6 7 9 ,9 3 4
6 ,8 2 6 ,6 7 7
7 ,0 4 0 ,6 7 7
7 ,1 8 9 ,1 6 8
7 ,3 6 9 ,4 7 3
7 ,6 3 4 ,0 1 8
7 ,8 2 0 ,8 6 0
7 ,8 7 9 ,1 1 6
7 ,9 8 4 ,5 2 9
8 ,1 0 1 ,8 7 2

1 0 9 ,4 2 2 ,5 7 1
1 1 2 ,6 1 1 ,2 8 7
1 1 5 ,4 8 7 ,8 4 1
1 1 7 ,9 6 3 ,1 3 2
1 2 1 ,0 4 4 ,4 3 2
1 2 4 ,1 8 3 ,5 4 9
1 2 7 ,0 4 2 ,2 8 2
1 2 9 ,8 7 7 ,0 6 3
1 2 9 ,6 3 5 ,8 0 0
1 2 8 ,2 3 3 ,9 1 9

$ 2 ,8 8 4 ,4 7 2 ,2 8 2
3 ,0 3 3 ,6 7 6 ,6 7 8
3 ,2 1 5 ,9 2 1 ,2 3 6
3 ,4 1 4 ,5 1 4 ,8 0 8
3 ,6 7 4 ,0 3 1 ,7 1 8
3 ,9 6 7 ,0 7 2 ,4 2 3
4 ,2 3 5 ,5 7 9 ,2 0 4
4 ,5 8 7 ,7 0 8 ,5 8 4
4 ,6 9 5 ,2 2 5 ,1 2 3
4 ,7 1 4 ,3 7 4 ,7 4 1

$ 2 6 ,3 6 1
2 6 ,9 3 9
2 7 ,8 4 6
2 8 ,9 4 6
3 0 ,3 5 3
3 1 ,9 4 5
3 3 ,3 4 0
3 5 ,3 2 3
3 6 ,2 1 9
3 6 ,7 6 4

$507
518
536
557
584
614
641
679
697
707

$ 2 6 ,0 5 5
2 6 ,6 3 3
2 7 ,5 6 7
2 8 ,6 5 8
3 0 ,0 5 8
3 1 ,6 7 6
3 3 ,0 9 4
3 5 ,0 7 7
3 5 ,9 4 3
3 6 ,4 2 8

$50 1
512
530
551
578
609
636
675
691
701

$ 2 5 ,9 3 4
2 6 ,4 9 6
2 7 ,4 4 1
2 8 ,5 8 2
3 0 ,0 6 4
3 1 ,7 6 2
3 3 ,2 4 4
3 5 ,3 3 7
3 6 ,1 5 7
3 6 ,5 3 9

$499
510
528
550
578
611
639
680
695
703

$ 2 8 ,6 4 3
2 9 ,5 1 8
3 0 ,4 9 7
3 1 ,3 9 7
3 2 ,5 2 1
3 3 ,6 0 5
3 4 ,6 8 1
3 6 ,2 9 6
3 7 ,8 1 4
3 9 ,2 1 2

$ 551
568
586
604
625
646
667
698
727
754

$ 2 6 ,0 9 5
2 6 ,7 1 7
2 7 ,5 5 2
2 8 ,3 2 0
2 9 ,1 3 4
3 0 ,2 5 1
3 1 ,2 3 4
3 2 ,3 8 7
3 3 ,5 2 1
3 4 ,6 0 5

$502
514
530
545
560
582
601
623
645
665

$ 3 6 ,9 4 0
3 8 ,0 3 8
3 8 ,5 2 3
4 0 ,4 1 4
4 2 ,7 3 2
4 3 ,6 8 8
4 4 ,2 8 7
4 6 ,2 2 8
4 8 ,9 4 0
5 2 ,0 5 0

$710
731
741
777
822
840
852
889
941
1,001

Ul covered
1 9 9 3 .................................................................
1 9 9 4 .................................................................
1 9 9 5 .................................................................
1 9 9 6 .................................................................
1 9 9 7 .................................................................
1 9 9 8 .................................................................
1 9 9 9 .................................................................
2 0 0 0 .................................................................
2 0 0 1 .................................................................
2 0 0 2 .................................................................

6 ,6 3 2 ,2 2 1
6 ,7 7 8 ,3 0 0
6 ,9 9 0 ,5 9 4
7 ,1 3 7 ,6 4 4
7 ,3 1 7 ,3 6 3
7 ,5 8 6 ,7 6 7
7 ,7 7 1 ,1 9 8
7 ,8 2 8 ,8 6 1
7 ,9 3 3 ,5 3 6
8 ,0 5 1 ,1 1 7

1 0 6 ,3 5 1 ,4 3 1
1 0 9 ,5 8 8 ,1 8 9
1 1 2 ,5 3 9 ,7 9 5
1 1 5 ,0 8 1 ,2 4 6
1 1 8 ,2 3 3 ,9 4 2
1 2 1 ,4 0 0 ,6 6 0
1 2 4 ,2 5 5 ,7 1 4
1 2 7 ,0 0 5 ,5 7 4
1 2 6 ,8 8 3 ,1 8 2
1 2 5 ,4 7 5 ,2 9 3

$ 2 ,7 7 1 ,0 2 3 ,4 1 1
2 ,9 1 8 ,6 8 4 ,1 2 8
3 ,1 0 2 ,3 5 3 ,3 5 5
3 ,2 9 8 ,0 4 5 ,2 8 6
3 ,5 5 3 ,9 3 3 ,8 8 5
3 ,8 4 5 ,4 9 4 ,0 8 9
4 ,1 1 2 ,1 6 9 ,5 3 3
4 ,4 5 4 ,9 6 6 ,8 2 4
4 ,5 6 0 ,5 1 1 ,2 8 0
4 ,5 7 0 ,7 8 7 ,2 1 8

Private industry covered
1 9 9 3 .................................................................
1 9 9 4 .................................................................
1 9 9 5 .................................................................
1 9 9 6 .................................................................
1 9 9 7 .................................................................
1 9 9 8 .................................................................
1 9 9 9 .................................................................
2 0 0 0 .................................................................
2 0 0 1 .................................................................
2 0 0 2 .................................................................

6 ,4 5 4 ,3 8 1
6 ,5 9 6 ,1 5 8
6 ,8 0 3 ,4 5 4
6 ,9 4 6 ,8 5 8
7 ,1 2 1 ,1 8 2
7 ,3 8 1 ,5 1 8
7 ,5 6 0 ,5 6 7
7 ,6 2 2 ,2 7 4
7 ,7 2 4 ,9 6 5
7 ,8 3 9 ,9 0 3

9 1 ,2 0 2 ,9 7 1
9 4 ,1 4 6 ,3 4 4
9 6 ,8 9 4 ,8 4 4
9 9 ,2 6 8 ,4 4 6
1 0 2 ,1 7 5 ,1 6 1
1 0 5 ,0 8 2 ,3 6 8
1 0 7 ,6 1 9 ,4 5 7
1 1 0 ,0 1 5 ,3 3 3
1 0 9 ,3 0 4 ,8 0 2
1 0 7 ,5 7 7 ,2 8 1

$ 2 ,3 6 5 ,3 0 1 ,4 9 3
2 ,4 9 4 ,4 5 8 ,5 5 5
2 ,6 5 8 ,9 2 7 ,2 1 6
2 ,8 3 7 ,3 3 4 ,2 1 7
3 ,0 7 1 ,8 0 7 ,2 8 7
3 ,3 3 7 ,6 2 1 ,6 9 9
3 ,5 7 7 ,7 3 8 ,5 5 7
3 ,8 8 7 ,6 2 6 ,7 6 9
3 ,9 5 2 ,1 5 2 ,1 5 5
3 ,9 3 0 ,7 6 7 ,0 2 5

State government covered
1 9 9 3 .................................................................
1 9 9 4 .................................................................
1 9 9 5 .................................................................
1 9 9 6 .................................................................
1 9 9 7 .................................................................
1 9 9 8 .................................................................
1 9 9 9 .................................................................
2 0 0 0 .................................................................
2 0 0 1 .................................................................
2 0 0 2 .................................................................

5 9 ,1 8 5
6 0 ,6 8 6
6 0 ,7 6 3
6 2 ,1 4 6
6 5 ,3 5 2
6 7 ,3 4 7
7 0 ,5 3 8
6 5 ,0 9 6
6 4 ,5 8 3
6 4 ,4 4 7

4 ,0 8 8 ,0 7 5
4 ,1 6 2 ,9 4 4
4 ,2 0 1 ,8 3 6
4 ,1 9 1 ,7 2 6
4 ,2 1 4 ,4 5 1
4 ,2 4 0 ,7 7 9
4 ,2 9 6 ,6 7 3
4 ,3 7 0 ,1 6 0
4 ,4 5 2 ,2 3 7
4 ,4 8 5 ,0 7 1

$ 1 1 7 ,0 9 5 ,0 6 2
1 2 2 ,8 7 9 ,9 7 7
1 2 8 ,1 4 3 ,4 9 1
1 3 1 ,6 0 5 ,8 0 0
1 3 7 ,0 5 7 ,4 3 2
1 4 2 ,5 1 2 ,4 4 5
1 4 9 ,0 1 1 ,1 9 4
1 5 8 ,6 1 8 ,3 6 5
1 6 8 ,3 5 8 ,3 3 1
1 7 5 ,8 6 6 ,4 9 2

Local government covered
1 9 9 3 .................................................................
1 9 9 4 .................................................................
1 9 9 5 .................................................................
1 9 9 6 .................................................................
1 9 9 7 .................................................................
1 9 9 8 .................................................................
1 9 9 9 .................................................................
2 0 0 0 .................................................................
2 0 0 1 .................................................................
2 0 0 2 .................................................................

1 1 8 ,6 2 6
1 2 1 ,4 2 5
1 2 6 ,3 4 2
1 2 8 ,6 4 0
1 3 0 ,8 2 9
1 3 7 ,9 0 2
1 4 0 ,0 9 3
1 4 1 ,4 9 1
1 4 3 ,9 8 9
1 4 6 ,7 6 7

1 1 ,0 5 9 ,5 0 0
1 1 ,2 7 8 ,0 8 0
1 1 ,4 4 2 ,2 3 8
1 1 ,6 2 1 ,0 7 4
1 1 ,8 4 4 ,3 3 0
1 2 ,0 7 7 ,5 1 3
1 2 ,3 3 9 ,5 8 4
1 2 ,6 2 0 ,0 8 1
1 3 ,1 2 6 ,1 4 3
1 3 ,4 1 2 ,9 4 1

$ 2 8 8 ,5 9 4 ,6 9 7
3 0 1 ,3 1 5 ,8 5 7
3 1 5 ,2 5 2 ,3 4 6
3 2 9 ,1 0 5 ,2 6 9
3 4 5 ,0 6 9 ,1 6 6
3 6 5 ,3 5 9 ,9 4 5
3 8 5 ,4 1 9 ,7 8 1
4 0 8 ,7 2 1 ,6 9 0
4 4 0 ,0 0 0 ,7 9 5
4 6 4 ,1 5 3 ,7 0 1

Federal Government covered (ÜCFE)
1 9 9 3 .................................................................
1 9 9 4 .................................................................
1 9 9 5 .................................................................
1 9 9 6 .................................................................
1 9 9 7 .................................................................
1 9 9 8 .................................................................
1 9 9 9 .................................................................
2 0 0 0 .................................................................
2 0 0 1 .................................................................
2 0 0 2 .................................................................

4 7 ,7 1 4
4 8 ,3 7 7
5 0 ,0 8 3
5 1 ,5 2 4
5 2 ,1 1 0
4 7 ,2 5 2
4 9 ,6 6 1
5 0 ,2 5 6
5 0 ,9 9 3
5 0 ,7 5 5

3 ,0 7 1 ,1 4 0
3 ,0 2 3 ,0 9 8
2 ,9 4 8 ,0 4 6
2 ,8 8 1 ,8 8 7
2 ,8 1 0 ,4 8 9
2 ,7 8 2 ,8 8 8
2 ,7 8 6 ,5 6 7
2 ,8 7 1 ,4 8 9
2 ,7 5 2 ,6 1 9
2 ,7 5 8 ,6 2 7

$ 1 1 3 ,4 4 8 ,8 7 1
1 1 4 ,9 9 2 ,5 5 0
1 1 3 ,5 6 7 ,8 8 1
1 1 6 ,4 6 9 ,5 2 3
1 2 0 ,0 9 7 ,8 3 3
1 2 1 ,5 7 8 ,3 3 4
1 2 3 ,4 0 9 ,6 7 2
1 3 2 ,7 4 1 ,7 6 0
1 3 4 ,7 1 3 ,8 4 3
1 4 3 ,5 8 7 ,5 2 3

N O T E : D etail m a y n o t a d d to to ta ls d u e to ro u n d in g . D a ta re fle c t t h e m o v e m e n t of In d ian T ribal C o u n c il e s t a b l i s h m e n t s fro m p riv a te in d u s try to
t h e p u b lic s e c to r . S e e N o te s o n C u rre n t L a b o r S ta tis tic s .

Monthly Labor Review

September 2004

93

Current Labor Statistics:

Labor Force Data

25. Annual data: Quarterly Census of Employment and Wages, establishment size and employment, private ownership bv
supersector, first quarter 2003
J
Size of establishments
Industry, establishments, and
employment

Total

Fewer than
5 workers1

5 to 9
workers

10 to 19
workers

20 to 49
workers

50 to 99
workers

100 to 249 250 to 499 500 to 999
workers
workers
workers

1,000 or
more
workers

Total all industries2
E s ta b lis h m e n ts , first q u a r te r
E m p lo y m e n t, M arch ...............

7 ,9 3 3 ,9 7 4
1 0 5 ,5 8 3 ,5 4 8

4 ,7 6 8 ,8 1 2
7 ,0 9 5 ,1 2 8

1 ,3 3 1 ,8 3 4
8 ,8 1 0 ,0 9 7

8 7 2 ,2 4 1
1 1 ,7 6 3 ,2 5 3

5 9 7 ,6 6 2
1 8 ,0 2 5 ,6 5 5

2 0 3 ,0 3 0
1 3 ,9 7 0 ,1 9 4

1 1 5 ,5 9 8
1 7 ,2 9 9 ,0 5 8

2 8 ,8 5 6
9 ,8 6 4 ,9 3 4

1 0 ,4 5 4
7 ,0 9 0 ,7 3 9

5 ,4 8 7
1 1 ,6 6 4 ,4 9 0

1 2 4 ,5 2 7
1 ,5 2 6 ,1 7 6

7 2 ,0 8 8
1 1 0 ,1 5 5

2 3 ,2 4 8
1 5 3 ,6 2 9

1 4 ,7 7 3
1 9 8 ,8 9 5

9 ,2 2 6
2 7 5 ,8 1 1

2 ,8 9 3
1 9 8 ,1 2 2

1 ,5 9 3
2 4 1 ,5 5 9

501
1 7 1 ,0 6 3

161
1 0 8 ,5 6 3

44
6 8 ,3 7 9

7 9 5 ,0 2 9
6 ,2 8 5 ,8 4 1

5 2 3 ,7 4 7
7 4 6 ,2 9 6

1 2 9 ,2 0 1
8 4 6 ,5 2 1

7 6 ,2 1 5
1 ,0 2 1 ,7 2 2

4 6 ,0 9 6
1 ,3 7 1 ,0 7 1

1 2 ,8 3 7
8 7 2 ,2 7 4

5 ,6 0 4
8 2 3 ,8 4 6

1 ,0 0 6
3 3 8 ,1 0 7

262
1 7 2 ,9 4 4

61
9 3 ,0 6 0

3 8 1 ,1 5 9
1 4 ,6 0 6 ,9 2 8

1 4 8 ,4 6 9
2 5 2 ,4 4 3

6 5 ,0 2 7
4 3 6 ,0 2 8

5 7 ,3 5 4
7 8 8 ,5 8 1

5 4 ,2 6 1
1 ,6 8 5 ,5 6 3

2 5 ,9 2 7
1 ,8 1 5 ,3 8 5

1 9 ,8 1 3
3 ,0 4 3 ,4 4 4

6 ,5 0 6
2 ,2 4 5 ,1 8 3

2 ,5 6 5
1 ,7 3 2 ,3 6 8

1 ,2 3 7
2 ,6 0 7 ,9 3 3

1 ,8 5 1 ,6 6 2
2 4 ,6 8 3 ,3 5 6

9 9 2 ,1 8 0
1 ,6 4 6 ,3 0 4

3 7 8 ,1 5 7
2 ,5 1 4 ,5 4 8

2 3 9 ,6 3 7
3 ,2 0 4 ,8 4 0

1 4 9 ,9 6 0
4 ,5 2 7 ,7 0 9

5 1 ,5 0 7
3 ,5 6 4 ,3 1 6

3 1 ,3 5 1
4 ,6 6 1 ,8 9 8

6 ,6 8 1
2 ,2 7 7 ,1 2 1

1 ,6 1 9
1 ,0 7 0 ,1 4 1

570
1 ,2 1 6 ,4 7 9

1 4 7 ,0 6 2
3 ,2 0 8 ,6 6 7

8 4 ,9 0 6
1 1 2 ,4 0 9

2 0 ,7 4 4
1 3 8 ,0 7 6

1 6 ,1 3 0
2 2 0 ,6 1 8

1 3 ,5 3 9
4 1 6 ,6 7 0

5 ,9 2 0
4 1 0 ,5 1 3

3 ,7 7 3
5 7 6 ,6 7 4

1 ,2 2 3
4 1 8 ,1 1 3

575
3 9 9 ,3 6 6

252
5 1 6 ,2 2 8

7 5 3 ,0 6 4
7 ,7 5 3 ,7 1 7

4 8 0 ,4 8 5
7 8 8 ,6 0 7

1 3 5 ,7 5 9
8 9 2 ,4 5 1

7 6 ,7 3 3
1 ,0 1 7 ,6 6 2

3 9 ,0 0 3
1 ,1 6 2 ,4 9 8

1 1 ,7 4 3
8 0 1 ,1 4 0

6 ,1 9 5
9 3 4 ,6 1 8

1 ,7 9 4
6 2 0 ,1 8 3

883
6 0 1 ,5 4 9

469
9 3 5 ,0 0 9

1 ,3 0 7 ,6 9 7
1 5 ,6 4 8 ,4 3 5

8 8 7 ,8 7 5
1 ,2 3 0 ,2 0 8

1 8 0 ,4 5 8
1 ,1 8 4 ,7 4 5

1 1 1 ,5 3 2
1 ,5 0 1 ,4 7 0

7 3 ,5 9 9
2 ,2 3 2 ,5 0 6

2 8 ,4 7 1
1 ,9 6 9 ,4 6 6

1 7 ,8 5 6
2 ,7 0 7 ,2 0 3

5 ,1 5 3
1 ,7 6 2 ,2 5 1

1 ,9 1 9
1 ,3 0 7 ,8 7 0

834
1 ,7 5 2 ,7 1 6

7 2 0 ,2 0 7
1 5 ,6 8 0 ,8 3 4

3 3 8 ,1 3 9
6 2 9 ,9 6 8

1 6 4 ,6 2 2
1 ,0 9 2 ,3 2 9

1 0 3 ,6 8 3
1 ,3 9 2 ,0 9 9

6 5 ,1 7 3
1 ,9 5 5 ,8 6 1

2 4 ,0 8 6
1 ,6 7 9 ,7 0 8

1 7 ,1 2 2
2 ,5 5 8 ,3 0 0

3 ,9 2 9
1 ,3 3 7 ,1 8 8

1,761
1 ,2 2 0 ,9 2 1

1 ,6 9 2
3 ,8 1 4 ,4 6 0

6 5 7 ,3 5 9
1 1 ,7 3 1 ,3 7 9

2 6 0 ,1 4 9
4 1 1 ,1 9 2

1 1 0 ,4 9 9
7 4 4 ,1 4 4

1 1 8 ,1 4 0
1 ,6 5 3 ,4 7 0

1 2 2 ,1 6 8
3 ,6 8 3 ,4 4 8

3 4 ,1 6 6
2 ,2 8 5 ,5 5 0

9 ,7 1 8
1 ,3 7 2 ,7 8 0

1 ,6 0 9
5 4 5 ,3 0 4

599
4 0 4 ,8 3 1

311
6 3 0 ,6 6 0

1 ,0 5 7 ,2 3 6
4 ,2 4 3 ,6 3 3

8 5 1 ,2 3 1
1 ,0 3 7 ,3 6 0

1 1 6 ,9 4 0
7 6 1 ,5 1 8

5 6 ,2 3 8
7 4 0 ,7 5 2

2 4 ,2 3 5
7 0 3 ,9 5 7

5 ,4 5 1
3 7 1 ,7 7 4

2 ,5 6 1
3 7 6 ,8 3 2

454
1 5 0 ,4 2 1

109
7 1 ,4 5 3

17
2 9 ,5 6 6

Natural resources and mining
E s ta b lis h m e n ts , first q u a r te r .
E m p lo y m e n t, M a rc h ..................

Construction
E s ta b lis h m e n ts , first q u a r te r
E m p lo y m e n t, M a rc h ...............

Manufacturing
E s ta b lis h m e n ts , first q u a r te r
E m p lo y m e n t, M a rc h ...............

Trade, transportation, and utilities
E s ta b lis h m e n ts , first q u a r te r ...........
E m p lo y m e n t, M a rc h ............................

Information
E s ta b lis h m e n ts , first q u a r te r
E m p lo y m e n t, M a rc h ...............

Financial activities
E s ta b lis h m e n ts , first q u a r te r
E m p lo y m e n t, M a rc h ...............

Professional and business services
E s ta b lis h m e n ts , first q u a r te r ..............
E m p lo y m e n t, M a rc h ................................

Education and health services
E s ta b lis h m e n ts , first q u a r te r ..
E m p lo y m e n t, M a rc h ...................

Leisure and hospitality
E s ta b lis h m e n ts , first q u a r te r
E m p lo y m e n t, M a rc h ...............

Other services
E s ta b lis h m e n ts , first q u a r te r
E m p lo y m e n t, M arch ...............

I n c lu d e s e s t a b l i s h m e n t s th a t re p o r te d n o w o r k e rs in M arch 2 0 0 3 .
In c lu d e s d a t a for u n c la s s ifie d e s t a b l i s h m e n t s , n o t s h o w n s e p a r a te ly .

94

Monthly Labor Review


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

September 2004

N O T E : D e ta ils m a y n o t a d d to to ta ls d u e to ro u n d in g .
first q u a r te r. D a ta a r e p re lim in ary .

D a ta a r e on ly p r o d u c e d for


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

26. Annual data: Quarterly Census of Employment and Wages, by
metropolitan area, 2001-02
Average annual wage2
Metropolitan area'

Percent
change,
2001-02

2001

2002

$ 3 7 ,9 0 8

$ 3 8 ,4 2 3

1 .4

A b ile n e , T X .....................................................................................................
A kron, O H ........................................................................................................
A lb an y , G A .....................................................................................................
A lb a n y - S c h e n e c ta d y -T r o y , N Y .............................................................
A lb u q u e r q u e , N M .........................................................................................
A le x a n d ria , L A ..............................................................................................
A lle n to w n -B e th le h e m -E a s to n , PA ......................................................
A lto o n a , P A .....................................................................................................
A m arillo, T X ....................................................................................................
A n c h o ra g e , A K .............................................................................................

2 5 ,1 4 1
3 2 ,9 3 0
2 8 ,8 7 7
3 5 ,3 5 5
3 1 ,6 6 7
2 6 ,2 9 6
3 3 ,5 6 9
2 6 ,8 6 9
2 7 ,4 2 2
3 7 ,9 9 8

2 5 ,5 1 7
3 4 ,0 3 7
2 9 ,9 1 3
3 5 ,9 9 4
3 2 ,4 7 5
2 7 ,3 0 0
3 4 ,7 8 9
2 7 ,3 6 0
2 8 ,2 7 4
3 9 ,1 1 2

1 .5
3 .4
3 .6
1.8
2 .6
3 .8
3 .6
1.8
3.1
2 .9

A n n A rbor, Ml ................................................................................................
A n n is to n , AL ..................................................................................................
A p p le to n -O s h k o s h -N e e n a h , W l ............................................................
A sh e v ille, NC .................................................................................................
A th e n s , G A .....................................................................................................
A tla n ta , G A .....................................................................................................
A tla n tic -C a p e M ay, N J ..............................................................................
A u b u rn -O p e lik a , A L ....................................................................................
A u g u s ta -A ik e n , G A - S C .............................................................................
A u s tin -S a n M a rc o s , T X .............................................................................

3 7 ,5 8 2
2 6 ,4 8 6
3 2 ,6 5 2
2 8 ,5 1 1
2 8 ,9 6 6
4 0 ,5 5 9
3 1 ,2 6 8
2 5 ,7 5 3
3 0 ,6 2 6
4 0 ,8 3 1

3 9 ,2 2 0
2 7 ,5 4 7
3 3 ,0 2 0
2 8 ,7 7 1
2 9 ,9 4 2
4 1 ,1 2 3
3 2 ,2 0 1
2 6 ,4 0 5
3 1 ,7 4 3
3 9 ,5 4 0

4 .4
4 .0
1.1
.9
3 .4
1.4
3 .0
2 .5
3 .6
-3 .2

B a k e rs fie ld , C A .............................................................................................
B altim o re, M D ................................................................................................
B a n g o r, M E .....................................................................................................
B a rn s ta b le -Y a rm o u th , MA ......................................................................
B a to n R o u g e , LA .........................................................................................
B e a u m o n t-P o rt A rthur, T X ......................................................................
B e llin g h a m , W A ............................................................................................
B e n to n H a rb o r, Ml ......................................................................................
B e r g e n - P a s s a i c , N J ....................................................................................
B illings, M T .....................................................................................................

3 0 ,1 0 6
3 7 ,4 9 5
2 7 ,8 5 0
3 1 ,0 2 5
3 0 ,3 2 1
3 1 ,7 9 8
2 7 ,7 2 4
3 1 ,1 4 0
4 4 ,7 0 1
2 7 ,8 8 9

3 1 ,1 9 2
3 8 ,7 1 8
2 8 ,4 4 6
3 2 ,0 2 8
3 1 ,3 6 6
3 2 ,5 7 7
2 8 ,2 8 4
3 2 ,6 2 7
4 5 ,1 8 5
2 8 ,5 5 3

3 .6
3 .3
2.1
3 .2
3 .4
2 .4
2 .0
4 .8
1.1
2 .4

B ilo x i-G u lfp o rt-P a s c a g o u la , M S ............................................................
B in g h a m to n , NY ..........................................................................................
B irm in g h a m , A L ...........................................................................................
B is m a rc k , N D .................................................................................................
B lo o m in g to n , I N ............................................................................................
B lo o m in g to n -N o rm a l, I L ............................................................................
B o is e C ity, I D .................................................................................................
B o s to n -W o rc e s te r-L a w re n c e -L o w e ll-B ro c k to n , M A-NH ...........
B o u ld e r-L o n g m o n t, C O .............................................................................
B ra z o ria , T X ....................................................................................................

2 8 ,3 5 1
3 1 ,1 8 7
3 4 ,5 1 9
2 7 ,1 1 6
2 8 ,0 1 3
3 5 ,1 1 1
3 1 ,6 2 4
4 5 ,7 6 6
4 4 ,3 1 0
3 5 ,6 5 5

2 8 ,5 1 5
3 1 ,8 3 2
3 5 ,9 4 0
2 7 ,9 9 3
2 8 ,8 5 5
3 6 ,1 3 3
3 1 ,9 5 5
4 5 ,6 8 5
4 4 ,0 3 7
3 6 ,2 5 3

.6
2.1
4.1
3 .2
3 .0
2 .9
1.0
-.2
-.6
1.7

B re m e rto n , W A .............................................................................................
B ro w n s v ille -H a rlin g e n -S a n B en ito , TX .............................................
B ry a n -C o lle g e S ta tio n , T X ......................................................................
B u ffa lo -N ia g a ra F a lls, N Y ........................................................................
B u rlin g to n , V T ................................................................................................
C a n to n -M a s s illo n , O H ..............................................................................
C a s p e r , W Y ....................................................................................................
C e d a r R a p id s , I A .........................................................................................
C h a m p a ig n -U rb a n a , I L .............................................................................
C h a rle s to n - N o rth C h a rle s to n , S C ........................................................

3 1 ,5 2 5
2 2 ,1 4 2
2 5 ,7 5 5
3 2 ,0 5 4
3 4 ,3 6 3
2 9 ,0 2 0
2 8 ,2 6 4
3 4 ,6 4 9
3 0 ,4 8 8
2 8 ,8 8 7

3 3 ,7 7 5
2 2 ,8 9 2
2 6 ,0 5 1
3 2 ,7 7 7
3 5 ,1 6 9
2 9 ,6 8 9
2 8 ,8 8 6
3 4 ,7 3 0
3 1 ,9 9 5
2 9 ,9 9 3

7.1
3 .4
1.1
2 .3
2 .3
2 .3
2 .2
.2
4 .9
3 .8

C h a rle s to n , W V ............................................................................................
C h a rlo tte -G a s to n ia -R o c k Hill, N C - S C ................................................
C h a rlo tte s v ille , V A ......................................................................................
C h a t t a n o o g a , T N - G A .................................................................................
C h e y e n n e , W Y .............................................................................................
C h ic a g o , IL .....................................................................................................
C h ic o - P a r a d is e , C A ....................................................................................
C in c in n ati, O H -K Y -IN .................................................................................
C la rk s v ille -H o p k in sv ille , T N - K Y ............................................................
C le v e la n d -L o ra in -E ly ria , O H ..................................................................

3 1 ,5 3 0
3 7 ,2 6 7
3 2 ,4 2 7
2 9 ,9 8 1
2 7 ,5 7 9
4 2 ,6 8 5
2 6 ,4 9 9
3 6 ,0 5 0
2 5 ,5 6 7
3 5 ,5 1 4

3 2 ,1 3 6
3 8 ,4 1 3
3 3 ,3 2 8
30 ,6 3 1
2 8 ,8 2 7
4 3 ,2 3 9
2 7 ,1 9 0
3 7 ,1 6 8
2 6 ,9 4 0
3 6 ,1 0 2

1.9
3.1
2 .8
2 .2
4 .5
1 .3
2 .6
3.1
5 .4
1.7

C o lo r a d o S p rin g s , C O ..............................................................................
C o lu m b ia , M O ................................................................................................
C o lu m b ia , S C ................................................................................................
C o lu m b u s , G A -A L ........................................................................................
C o lu m b u s , O H ..............................................................................................
C o r p u s C h risti, TX ......................................................................................
C o rv allis, O R ................................................................................................
C u m b e rla n d , M D-W V ................................................................................
D a lla s, T X ......................................................................................................
D anville, V A ..................................................................................................

3 4 ,3 9 1
2 8 ,4 9 0
2 9 ,9 0 4
2 8 ,4 1 2
3 5 ,0 2 8
2 9 ,3 6 1
3 5 ,5 2 5
2 5 ,5 0 4
4 2 ,7 0 6
2 5 ,4 6 5

3 4 ,6 8 1
2 9 ,1 3 5
3 0 ,7 2 1
2 9 ,2 0 7
3 6 ,1 4 4
3 0 ,1 6 8
3 6 ,7 6 6
2 6 ,7 0 4
4 3 ,0 0 0
2 6 ,1 1 6

.8
2 .3
2 .7
2 .8
3 .2
2 .7
3 .5
4 .7
.7
2 .6

M e tro p o lita n a r e a s 2 .................................................................................

S e e f o o tn o te s a t e n d of ta b le .

Monthly Labor Review

September 2004

95

Current Labor Statistics:

Labor Force Data

26. Continued—Annual data: Quarterly Census of Employment and
Wages, by metropolitan area, 2001-02
Average annual wage2
Metropolitan area1
2001

2002

Percent
change,
2001-02

D a v e n p o rt-M o lin e -R o c k Is la n d , IA -IL ...............
D a y to n -S p rin g fie ld , O H ...........................................
D a y to n a B e a c h , F L ...................................................
D e c a tu r, A L ...................................................................
D e c a tu r, I L ....................................................................
D e n v e r, C O ...................................................................
D e s M o in e s, IA ...........................................................
D etroit, Ml .....................................................................
D o th a n , A L ....................................................................
D o v e r, D E ......................................................................

$ 3 1 ,2 7 5
3 3 ,6 1 9
2 5 ,9 5 3
3 0 ,8 9 1
3 3 ,3 5 4
4 2 ,3 5 1
3 4 ,3 0 3
4 2 ,7 0 4
2 8 ,0 2 6
2 7 .7 5 4

$ 3 2 ,1 1 8
3 4 ,3 2 7
2 6 ,8 9 8
3 0 ,3 7 0
3 3 .2 1 5
4 2 ,1 3 3
3 5 ,6 4 1
4 3 ,2 2 4
2 9 ,2 7 0
2 9 ,8 1 8

D u b u q u e , I A ..................................................................
D u lu th -S u p e rio r, MN-W I .........................................
D u tc h e s s C o u n ty , NY ..............................................
E a u C la ire , W l ...................................................
El P a s o , T X ....................................................................
E lk h a r t- G o s h e n , I N ....................................................
E lm ira, NY .....................................................................
E n id , O K .........................................................................
E rie, P A ...........................................................................
E u g e n e -S p rin g tie ld , O R ...........................................

2 8 ,4 0 2
2 9 ,4 1 5
3 8 ,7 4 8
2 7 ,6 8 0
2 5 ,8 4 7
3 0 ,7 9 7
2 8 ,6 6 9
2 4 ,8 3 6
2 9 ,2 9 3
2 8 ,9 8 3

2 9 ,2 0 8
3 0 ,5 8 1
3 8 ,2 2 1
2 8 ,7 6 0
2 6 ,6 0 4
3 2 .4 2 7
2 9 .1 5 1
2 5 .5 0 7
2 9 ,7 8 0
2 9 .4 2 7

E v a n s v ille -H e n d e r s o n , IN -K Y ...............................
F a rg o - M o o rh e a d , N D - M N .......................................
F a y e tte v ille , N C ...........................................................
F a y e tte v ille -S p rin g d a le -R o g e rs , AR ..................
F la g s ta ff, A Z - U T .................................................
Flint, M l ............................................................................
F lo r e n c e , A L ..................................................................
F lo r e n c e , S C .................................................................
F o rt C o llin s -L o v e la n d , C O ......................................
F o rt L a u d e rd a le , F L ...................................................

3 1 ,0 4 2
2 7 ,8 9 9
2 6 ,9 8 1
2 9 .9 4 0
2 5 ,8 9 0
3 5 ,9 9 5
2 5 ,6 3 9
2 8 ,8 0 0
3 3 ,2 4 8
3 3 ,9 6 6

3 1 .9 7 7
2 9 .0 5 3
2 8 ,2 9 8
3 1 ,0 9 0
2 6 ,8 4 6
3 6 .5 0 7
2 6 ,5 9 1
2 9 ,5 6 3
3 4 .2 1 5
3 4 ,4 7 5

F o rt M y e r s -C a p e C o ra l, F L ....................................
F o rt P ie r c e - P o r t S t. L ucie, F L ...............................
F o rt S m ith , A R - O K .....................................................
F o rt W a lto n B e a c h , F L .............................................
F o rt W a y n e , IN ............................................................
F o rt W o rth -A rlin g to n , T X ..........................................
F r e s n o , C A ....................................................................
G a d s d e n , A L ..................................................................
G a in e s v ille , F L ..............................................................
G a lv e s to n - T e x a s C ity, T X ........................................

2 9 ,4 3 2
2 7 ,7 4 2
2 6 .7 5 5
2 6 ,1 5 1
3 1 ,4 0 0
3 6 ,3 7 9
2 7 ,6 4 7
2 5 ,7 6 0
2 6 ,9 1 7
3 1 ,0 6 7

3 0 ,3 2 4
2 9 .1 5 2
2 7 ,0 7 5
2 7 ,2 4 2
3 2 .0 5 3
3 7 ,1 9 5
2 8 ,8 1 4
2 6 .2 1 4
2 7 ,6 4 8
3 1 ,9 2 0

G a ry , IN ............................................................................
G le n s F a lls, N Y .............................................................
G o ld s b o ro , N C ..............................................................
G r a n d F o rk s , N D - M N .................................................
G r a n d J u n c tio n , C O ....................................................
G r a n d R a p id s -M u s k e g o n -H o lla n d , Ml ...............
G r e a t F a lls, M T .............................................................
G r e e le y , C O ....................................................................
G r e e n B ay , W l ...............................................................
G r e e n s b o r o - W i n s t o n - S a l e m - H i g h P o in t, NC

3 1 ,9 4 8
2 7 ,8 8 5
2 5 ,3 9 8
2 4 ,9 5 9
2 7 ,4 2 6
3 3 ,4 3 1
2 4 ,2 1 1
3 0 ,0 6 6
3 2 ,6 3 1
3 1 ,7 3 0

3 2 ,4 3 2
2 8 ,9 3 1
2 5 ,8 2 1
2 5 ,7 1 0
2 8 ,3 3 1
3 4 .2 1 4
2 5 ,0 3 5
3 1 ,1 0 4
3 3 ,6 9 8
3 2 ,3 6 9

G re e n v ille , N C ...............................................................
G r e e n v ille -S p a r ta n b u rg -A n d e rs o n , S C .............
H a g e rs to w n , M D ...........................................................
H a m ilto n -M id d leto w n , O H ........................................
H a rris b u rg - L e b a n o n - C a rlis le , P A .........................
H a rtfo rd , C T ....................................................................
H a ttie s b u r g , M S ............................................. •.............
H ic k o ry -M o rg a n to n -L e n o ir, NC ..............................
H o n o lu lu , H I ....................................................................
H o u m a , L A .......................................................................

2 8 ,2 8 9
3 0 .9 4 0
2 9 ,0 2 0
3 2 ,3 2 5
3 3 ,4 0 8
4 3 ,8 8 0
2 5 ,1 4 5
2 7 ,3 0 5
3 2 ,5 3 1
3 0 ,3 4 3

2 9 ,0 5 5
3 1 ,7 2 6
3 0 ,0 3 4
3 2 ,9 8 5
3 4 ,4 9 7
4 4 ,3 8 7
2 6 ,0 5 1
2 7 ,9 9 6
3 3 .9 7 8
3 0 ,7 5 8

3 .6
2 .5
4 .4
1 .4

H o u s to n , T X ....................................................................
H u n tin g to n -A sh la n d , W V -K Y -O H .........................
H u n tsv ille , A L .................................................................
In d ia n a p o lis , I N .............................................................
Io w a C ity, IA ...................................................................
J a c k s o n , Ml ....................................................................
J a c k s o n , M S ...................................................................
J a c k s o n , T N ....................................................................
J a c k s o n v ille , F L ............................................................
J a c k s o n v ille , N C ...........................................................

4 2 ,7 8 4
2 7 ,4 7 8
3 6 ,7 2 7
3 5 ,9 8 9
3 1 ,6 6 3
3 2 ,4 5 4
2 9 ,8 1 3
2 9 ,4 1 4
3 2 ,3 6 7
2 1 ,3 9 5

4 2 ,7 1 2
2 8 ,3 2 1
3 8 ,5 7 1
3 6 ,6 0 8
3 2 ,5 6 7
3 3 ,2 5 1
3 0 ,5 3 7
3 0 ,4 4 3
3 3 ,7 2 2
2 2 ,2 6 9

3.1
5 .0
1 .7
2 .9
2 .5
2 .4
3 .5
4 .2
4.1

S e e f o o tn o te s a t e n d o f ta b le .

96

Monthly Labor Review


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

September 2004

2 .7

2.1
3 .6
-1 .7
-.4
-.5
3 .9

1.2
4 .4
7 .4

2.8
4 .0
-1 .4
3 .9
2 .9
5 .3
1.7
2 .7
1 .7
1.5
3 .0
4.1
4 .9
3 .8
3 .7
1 .4
3 .7

2.6
2 .9
1 .5
3 .0
5.1

1.2
4 .2

2.1

2.2
4 .2

1.8
2 .7
2 .7
1 .5
3 .8
1.7
3 .0
3 .3
2 .3
3 .4
3 .5
3 .3

2.0
2 .7
2 .5
3 .5

2.0
3 .3

1.2

-.2


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

26. Continued—Annual data: Quarterly Census of Employment and
Wages, by metropolitan area, 2001-02
A v e ra g e a n n u a l w age?

M e tro p o lita n a r e a 1
P e rc e n t
change,
2 0 0 1 -0 2

2 001

2002

J a m e s t o w n , NY ............................................................................................
J a n e s v ille - B e lo it, W l ..................................................................................
J e r s e y C ity, N J .............................................................................................
J o h n s o n C ity -K In g sp o rt-B risto l, T N -V A ............................................
J o h n s to w n , P A ..............................................................................................
J o n e s b o r o , A R ..............................................................................................
J o p lin , M O ......................................................................................................
K a la m a z o o - B a ttle C re e k , M l ..................................................................
K a n k a k e e , I L ..................................................................................................
K a n s a s C ity, M O -K S ..................................................................................

$ 2 5 ,9 1 3
3 1 ,4 8 2
4 7 ,6 3 8
2 8 ,5 4 3
2 5 ,5 6 9
2 5 ,3 3 7
2 6 ,0 1 1
3 2 ,9 0 5
2 9 ,1 0 4
3 5 ,7 9 4

$ 2 6 ,4 3 0
3 2 ,8 3 7
4 9 ,5 6 2
2 9 ,0 7 6
2 6 ,1 6 1
2 6 ,1 6 5
2 6 ,5 9 4
3 4 ,2 3 7
3 0 ,0 1 5
3 6 ,7 3 1

2 .0
4 .3
4 .0
1 .9
2 .3
3 .3
2 .2
4 .0
3.1
2 .6

K e n o s h a , W l ..................................................................................................
K ille e n -T e m p le , T X .....................................................................................
K noxville, TN .................................................................................................
K o k o m o , I N .....................................................................................................
L a C r o s s e , W I - M N ......................................................................................
L a fa y e tte , L A .................................................................................................
L a fa y e tte , I N ..................................................................................................
L a k e C h a r le s , L A .........................................................................................
L a k e la n d -W in te r H a v e n , F L ....................................................................
L a n c a s te r , P A ................................................................................................

3 1 ,5 6 2
2 6 ,1 9 3
3 0 ,4 2 2
3 9 ,5 9 9
2 7 ,7 7 4
2 9 ,6 9 3
3 1 ,4 8 4
2 9 ,7 8 2
2 8 ,8 9 0
3 1 ,4 9 3

3 2 ,4 7 3
2 7 ,2 9 9
3 1 ,3 3 8
4 0 ,7 7 8
2 8 ,7 1 9
3 0 ,1 0 4
3 1 ,7 0 0
3 0 ,3 4 6
2 9 ,5 0 5
3 2 ,1 9 7

2 .9
4 .2
3 .0
3 .0
3 .4
1.4
.7
1 .9
2.1
2 .2

L a n s in g -E a s t L a n s in g , M l ........................................................................
L a re d o , T X ......................................................................................................
L a s C r u c e s , N M ............................................................................................
L a s V e g a s , N V -A Z .......................................................................................
L a w re n c e , K S ................................................................................................
L aw to n , O K .....................................................................................................
L e w is to n -A u b u rn , M E ................................................................................
L ex in g to n , K Y ................................................................................................
L im a, O H .........................................................................................................
L incoln, N E .....................................................................................................

3 4 ,7 2 4
2 4 ,1 2 8
2 4 ,3 1 0
3 2 ,2 3 9
2 5 ,9 2 3
2 4 ,8 1 2
2 7 ,0 9 2
3 1 ,5 9 3
2 9 ,6 4 4
2 9 ,3 5 2

3 5 ,7 8 5
2 4 ,7 3 9
2 5 ,2 5 6
3 3 ,2 8 0
2 6 ,6 2 1
2 5 ,3 9 2
2 8 ,4 3 5
3 2 ,7 7 6
3 0 ,3 7 9
3 0 ,6 1 4

3.1
2 .5
3 .9
3 .2
2 .7
2 .3
5 .0
3 .7
2 .5
4 .3

Little R o ck -N o rth Little R o ck , A R .........................................................
L o n g v ie w -M a rs h a ll, T X .............................................................................
L o s A n g e le s -L o n g B e a c h , C A ...............................................................
L ouisville, KY-IN ..........................................................................................
L u b b o c k , TX ..................................................................................................
L y n c h b u rg , V A ..............................................................................................
M a c o n , G A ......................................................................................................
M a d is o n , W l ....................................................................................................
M a n sfie ld , O H ................................................................................................
M cA llen -E d in b u rg -M issio n , T X .............................................................

3 0 ,8 5 8
2 8 ,0 2 9
4 0 ,8 9 1
3 3 ,0 5 8
2 6 ,5 7 7
2 8 ,8 5 9
3 0 ,5 9 5
3 4 ,0 9 7
2 8 ,8 0 8
2 2 ,3 1 3

3 1 ,6 3 4
2 8 ,1 7 2
4 1 ,7 0 9
3 3 ,9 0 1
2 7 ,6 2 5
2 9 ,4 4 4
3 1 ,8 8 4
3 5 ,4 1 0
3 0 ,1 0 4
2 3 ,1 7 9

2 .5
.5
2 .0
2 .6
3 .9
2 .0
4 .2
3 .9
4 .5
3 .9

M e d fo rd -A s h la n d , O R ................................................................................
M e lb o u rn e -T itu s v ille -P a lm B ay , F L .....................................................
M e m p h is , T N -A R -M S ................................................................................
M e rc e d , C A .....................................................................................................
M iam i, F L .........................................................................................................
M id d le s e x -S o m e r s e t-H u n te r d o n , N J .................................................
M ilw a u k e e -W a u k e s h a , W l ......................................................................
M in n e a p o lis -S t. P a u l, M N-W I ................................................................
M is s o u la , MT .................................................................................................
M obile, A L ........................................................................................................

2 7 ,2 2 4
3 2 ,7 9 8
3 4 ,6 0 3
2 5 ,4 7 9
3 4 ,5 2 4
4 9 ,9 5 0
3 5 ,6 1 7
4 0 ,8 6 8
2 6 ,1 8 1
2 8 ,1 2 9

2 8 ,0 9 8
3 3 ,9 1 3
3 5 ,9 2 2
2 6 ,7 7 1
3 5 ,6 9 4
5 0 ,4 5 7
3 6 ,5 2 3
4 1 ,7 2 2
2 7 ,2 4 9
2 8 ,7 4 2

3 .2
3 .4
3 .8
5.1
3 .4
1.0
2 .5
2.1
4.1
2 .2

M o d e s to , C A ..................................................................................................
M o n m o u th - O c e a n , N J ..............................................................................
M o n ro e , L A .....................................................................................................
M o n tg o m e ry , AL ..........................................................................................
M u n cie, IN ......................................................................................................
M yrtle B e a c h , S C .........................................................................................
N a p le s , FL ......................................................................................................
N a sh v ille , T N .................................................................................................
N a s sa u -S u ffo lk , N Y ....................................................................................
N e w H a v e n -B rid g e p o rt-S ta m fo rd -W a te rb u ry -D a n b u ry , C T ....

2 9 ,5 9 1
3 7 ,0 5 6
2 6 ,5 7 8
2 9 ,1 5 0
2 8 ,3 7 4
2 4 ,0 2 9
3 0 ,8 3 9
3 3 ,9 8 9
3 9 ,6 6 2
5 2 ,1 9 8

3 0 ,7 6 9
3 7 ,7 1 0
2 7 ,6 1 4
3 0 ,5 2 5
2 9 ,0 1 7
2 4 ,6 7 2
3 1 ,5 0 7
3 5 ,0 3 6
4 0 ,3 9 6
5 1 ,1 7 0

4 .0
1.8
3 .9
4 .7
2 .3
2 .7
2 .2
3.1
1.9
-2 .0

N e w L o n d o n -N o rw ich , C T ......................................................................
N e w O r le a n s , LA .........................................................................................
N e w Y ork, N Y ..............................................................................................
N e w a rk , N J ....................................................................................................
N e w b u rg h , N Y -PA .....................................................................................
N orfolk-V irginia B e a c h -N e w p o rt N e w s, V A - N C ...........................
O a k la n d , C A .................................................................................................
O c a la , F L ........................................................................................................
O d e s sa -M id la n d , T X .................................................................................
O k la h o m a C ity, O K ....................................................................................

3 8 ,5 0 5
3 1 ,0 8 9
5 9 ,0 9 7
4 7 ,7 1 5
2 9 ,8 2 7
2 9 ,8 7 5
4 5 ,9 2 0
2 6 ,0 1 2
3 1 ,2 7 8
2 8 ,9 1 5

3 8 ,6 5 0
3 2 ,4 0 7
5 7 ,7 0 8
4 8 ,7 8 1
3 0 ,9 2 0
3 0 ,8 2 3
4 6 ,8 7 7
2 6 ,6 2 8
3 1 ,2 9 5
2 9 ,8 5 0

.4
4 .2
-2 .4
2 .2
3 .7
3 .2
2.1
2 .4
.1
3 .2

S e e fo o tn o te s a t e n d o f ta b le .

Monthly Labor Review

September 2004

97

Current Labor Statistics:

Labor Force Data

26. Continued—Annual data: Quarterly Census of Employment and
Wages, by metropolitan area, 2001-02
Average annual wage2
Metropolitan area1
2001

2002

Percent
change,
2001-02

O ly m p ia , W A ....................................................................
O m a h a , NE-IA .......................................................
O r a n g e C o u n ty , C A .................................................. '
O rla n d o , F L ......................................................................
O w e n s b o ro , KY ...................................................
P a n a m a C ity, F L ........................................................."
P a rk e rs b u rg - M a rie tta , W V -O H ...............................
P e n s a c o la , F L .................................................................
P e o ria - P e k in , I L .............................................................
P h ila d e lp h ia , P A - N J .....................................................

$ 3 2 ,7 7 2
3 1 ,8 5 6
4 0 ,2 5 2
3 1 ,2 7 6
2 7 ,3 0 6
2 6 ,4 3 3
2 7 ,9 2 0
2 8 ,0 5 9
3 3 ,2 9 3
4 0 ,2 3 1

$ 3 3 ,7 6 5
3 3 ,1 0 7
4 1 ,2 1 9
3 2 ,4 6 1
2 8 ,1 9 6
2 7 ,4 4 8
2 9 ,5 2 9
2 8 ,1 8 9
3 4 ,2 6 1
4 1 ,1 2 1

3 .0
3 .9
2 .4
3 .8
3 .3
3 .8
5 .8
.5
2 .9
2 .2

P h o e n ix -M e s a , A Z ........................................................
P in e Bluff, A R .................................................................
P itts b u rg h , P A .................................................................
P ittsfield , M A ....................................................................
P o c a te llo , I D .............................................................
P o rtla n d , M E ....................................................................
P o rtla n d -V a n c o u v e r, O R -W A .................................
P ro v id e n c e -W a rw ic k -P a w tu c k e t, Rl .............
P r o v o - O r e m ,- U T ............................................................
P u e b lo , C O ................................................................. ™

3 5 ,5 1 4
2 7 ,5 6 1
3 5 ,0 2 4
3 1 ,5 6 1
2 4 ,6 2 1
3 2 ,3 2 7
3 7 ,2 8 5
3 3 ,4 0 3
2 8 ,2 6 6
2 7 ,0 9 7

3 6 ,0 4 5
2 8 ,6 9 8
3 5 ,6 2 5
3 2 ,7 0 7
2 5 ,2 1 9
3 3 ,3 0 9
3 7 ,6 5 0
3 4 ,6 1 0
2 8 ,4 1 6
2 7 ,7 6 3

1.5
4.1
1.7
3 .6
2 .4
3 .0
1.0
3 .6
.5
2 .5

P u n ta G o r d a , F L ............................................................
R a c in e , W l ........................................................................
R a le ig h -D u rh a m -C h a p e l Hill, N C ...........................
R a p id C ity, S D .................................................................
R e a d in g , PA .....................................................................
R e d d in g , C A ....................................................................
R e n o , N V .....................................................................
R ic h la n d -K e n n e w ic k -P a s c o , W A ............................
R ic h m o n d -P e te rs b u r g , V A .........................................
R iv e rs id e - S a n B e rn a rd in o , C A ................................

2 5 ,4 0 4
3 3 ,3 1 9
3 8 ,6 9 1
2 5 ,5 0 8
3 2 ,8 0 7
2 8 ,1 2 9
3 4 ,2 3 1
3 3 ,3 7 0
3 5 ,8 7 9
3 0 ,5 1 0

2 6 ,1 1 9
3 4 ,3 6 8
3 9 ,0 5 6
2 6 ,4 3 4
3 3 ,9 1 2
2 8 ,9 6 1
3 4 ,7 4 4
3 5 ,1 7 4
3 6 ,7 5 1
3 1 ,5 9 1

2 .8
3.1
.9
3 .6
3 .4
3 .0
1 .5
5 .4
2 .4
3 .5

R o a n o k e , VA ....................................................................
R o c h e s te r , M N .................................................................
R o c h e s te r , NY .................................................................
R o ck fo rd , IL .......................................................................
R o c k y M ount, NC ...........................................................
S a c r a m e n t o , C A .............................................................
S a g in a w - B a y C ity -M id lan d , Ml ................................
S t. C lo u d , MN ...................................................................
S t. J o s e p h , M O ................................................................
S t. L ouis, M O -IL ...............................................................

3 0 ,3 3 0
3 7 ,7 5 3
3 4 ,3 2 7
3 2 ,1 0 4
2 8 ,7 7 0
3 8 ,0 1 6
3 5 ,4 2 9
2 8 ,2 6 3
2 7 ,7 3 4
3 5 ,9 2 8

3 1 ,7 7 5
3 9 ,0 3 6
3 4 ,8 2 7
3 2 ,8 2 7
2 8 ,8 9 3
3 9 ,3 5 4
3 5 ,4 4 4
2 9 ,5 3 5
2 8 ,5 0 7
3 6 ,7 1 2

4 .8
3 .4
1.5
2 .3
.4
3 .5
.0
4 .5
2 .8
2 .2

S a le m , O R .........................................................................
S a lin a s , C A ....................................................................
S a lt L a k e C lty -O g d e n , U T ...........................................
S a n A n g e lo , TX ...............................................................
S a n A n to n io , TX .............................................................
S a n D ieg o , C A .................................................................
S a n F ra n c is c o , C A .........................................................
S a n J o s e , C A ....................................................................
S a n Luis O b i s p o - A t a s c a d e r o - P a s o R o b le s , C A
S a n t a B a r b a r a - S a n t a M a ria -L o m p o c , C A ...........

2 8 ,3 3 6
3 1 ,7 3 5
3 1 ,9 6 5
2 6 ,1 4 7
3 0 ,6 5 0
3 8 ,4 1 8
5 9 ,6 5 4
6 5 ,9 3 1
2 9 ,0 9 2
3 3 ,6 2 6

2 9 ,2 1 0
3 2 ,4 6 3
3 2 ,6 0 0
2 6 ,3 2 1
3 1 ,3 3 6
3 9 ,3 0 5
5 6 ,6 0 2
6 3 ,0 5 6
2 9 ,9 8 1
3 4 ,3 8 2

3.1
2 .3
2 .0
.7
2 .2
2 .3
-5.1
-4 .4
3.1
2 .2

S a n t a C ru z -W a ts o n v llle , C A ......................................
S a n t a F e , NM ...................................................................
S a n t a R o s a , C A ...............................................................
S a r a s o ta - B r a d e n t o n , F L ..............................................
S a v a n n a h , G A .................................................................
S c ra n to n - W llk e s -B a r re - -H a z le to n , P A .................
S e a ttle -B e lle v u e -E v e re tt, W A ....................................
S h a r o n , P A .........................................................................
S h e b o y g a n , W l .............................................................
S h e r m a n - D e n is o n , T X ..................................................

3 5 ,0 2 2
3 0 ,6 7 1
3 6 ,1 4 5
2 7 ,9 5 8
3 0 ,1 7 6
2 8 ,6 4 2
4 5 ,2 9 9
2 6 ,7 0 7
3 0 ,8 4 0
3 0 ,3 9 7

3 5 ,7 2 1
3 2 ,2 6 9
3 6 ,4 9 4
2 8 ,9 5 0
3 0 ,7 9 6
2 9 ,3 3 6
4 6 ,0 9 3
2 7 ,8 7 2
3 2 ,1 4 8
3 0 ,0 8 5

2 .0
5 .2
1.0
3 .5
2.1
2 .4
1.8
4 .4
4 .2
-1 .0

S h r e v e p o r t- B o s s ie r C ity, LA .......................................
S io u x C ity, IA -N E .............................................................
S io u x F a lls, S D .................................................................
S o u th B e n d , IN .................................................................
S p o k a n e , W A .....................................................................
S p rin g field , I L .....................................................................
S p rin g field , M O .................................................................
S p rin g fie ld , MA .................................................................
S ta t e C o lle g e , P A ............................................................
S te u b e n v ille -W e irto n , O H - W V ...................................

2 7 ,8 5 6
2 6 ,7 5 5
2 8 ,9 6 2
3 0 ,7 6 9
2 9 ,3 1 0
3 6 ,0 6 1
2 7 ,3 3 8
3 2 ,8 0 1
2 9 ,9 3 9
2 8 ,4 8 3

2 8 ,7 6 9
2 7 ,5 4 3
2 9 ,9 7 5
3 1 ,8 2 1
3 0 ,0 3 7
3 7 ,3 3 6
2 7 ,9 8 7
3 3 ,9 7 2
3 0 ,9 1 0
2 9 ,1 2 9

3 .3
2 .9
3 .5
3 .4
2 .5
3 .5
2 .4
3 .6
3 .2
2 .3

S e e f o o tn o te s a t e n d of ta b le .

98

Monthly Labor Review


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

September 2004


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

26. Continued—Annual data: Quarterly Census of Employment and
Wages, by metropolitan area, 2001-02
Average annual wage2
Metropolitan area'

Percent
change,
2001-02

2001

2002

S to c k to n -L o d i, C A ........................................................................................
S u m te r, S C .....................................................................................................
S y r a c u s e , N Y .................................................................................................
T a c o m a , W A ..................................................................................................
T a l l a h a s s e e , F L ............................................................................................
T a m p a -S t. P e te r s b u r g - C le a r w a te r , FL .............................................
T e r re F la u te , I N .............................................................................................
T e x a r k a n a , T X -T e x a rk a n a , A R .............................................................
T o le d o , O H .....................................................................................................
T o p e k a , K S .....................................................................................................

$ 3 0 ,8 1 8
2 4 ,4 5 0
3 2 ,2 5 4
3 1 ,2 6 1
2 9 ,7 0 8
3 1 ,6 7 8
2 7 ,3 3 4
2 6 ,4 9 2
3 2 ,2 9 9
3 0 ,5 1 3

$ 3 1 ,9 5 8
2 4 ,9 8 2
3 3 ,7 5 2
3 2 ,5 0 7
3 0 ,8 9 5
3 2 ,4 5 8
2 8 ,4 1 5
2 7 ,7 1 7
3 3 ,5 1 3
3 1 ,7 0 7

3 .7
2 .2
4 .6
4 .0
4 .0
2 .5
4 .0
4 .6
3 .8
3 .9

T re n to n , N J .....................................................................................................
T u c s o n , AZ .....................................................................................................
T u ls a , O K .........................................................................................................
T u s c a l o o s a , A L .............................................................................................
T y ler, T X ..........................................................................................................
U tic a -R o m e , N Y ............................................................................................
V a lle jo -F a irfie ld -N a p a , C A ......................................................................
V e n tu ra , C A ....................................................................................................
V ictoria, T X .....................................................................................................
V in ela n d -M illv ille -B rid g eto n , N J ............................................................

4 6 ,8 3 1
3 0 ,6 9 0
3 1 ,9 0 4
2 9 ,9 7 2
3 0 ,5 5 1
2 7 ,7 7 7
3 3 ,9 0 3
3 7 ,7 8 3
2 9 ,0 6 8
3 2 ,5 7 1

4 7 ,9 6 9
3 1 ,6 7 3
3 2 ,2 4 1
3 0 ,7 4 5
3 1 ,0 5 0
2 8 ,5 0 0
3 4 ,5 4 3
3 8 ,1 9 5
2 9 ,1 6 8
3 3 ,6 2 5

2 .4
3 .2
1.1
2 .6
1 .6
2 .6
1.9
1.1
.3
3 .2

V is a lia -T u la re -P o rte rv ille , C A ................................................................
W a c o , T X .........................................................................................................
W a s h in g to n , D C -M D -V A -W V .................................................................
W a te rlo o -C e d a r F a lls, IA .........................................................................
W a u s a u , W l ................................................................................................—
W e s t P a lm B e a c h - B o c a R a to n , F L .....................................................
W h e e lin g , W V -O H .......................................................................................
W ic h ita , K S .....................................................................................................
W ic h ita F a lls, T X ..........................................................................................
W illiam sp o rt, P A ..........................................................................................

2 4 ,7 3 2
2 8 ,2 4 5
4 7 ,5 8 9
2 9 ,1 1 9
2 9 ,4 0 2
3 5 ,9 5 7
2 6 ,2 8 2
3 2 ,9 8 3
2 5 ,5 5 7
2 7 ,8 0 1

2 5 ,6 5 0
2 8 ,8 8 5
4 8 ,4 3 0
2 9 ,9 1 6
3 0 ,2 9 2
3 6 ,5 5 0
2 6 ,6 9 3
3 3 ,4 2 9
2 6 ,3 8 7
2 7 ,9 8 8

3 .7
2 .3
1.8
2 .7
3 .0
1 .6
1 .6
1 .4
3 .2
.7

W ilm in g to n -N ew a rk , D E - M D ..................................................................
W ilm in g to n , N C .............................................................................................
Y a k im a , W A ....................................................................................................
Y olo, C A ..........................................................................................................
Y ork, P A ..........................................................................................................
Y o u n g s to w n -W a r re n , O H ........................................................................
Y u b a C ity, C A ................................................................................................
Y u m a , A Z .........................................................................................................

4 2 ,1 7 7
2 9 ,2 8 7
2 4 ,2 0 4
3 5 ,3 5 2
3 1 ,9 3 6
2 8 ,7 8 9
2 7 ,7 8 1
2 2 ,4 1 5

4 3 ,4 0 1
2 9 ,1 5 7
2 4 ,9 3 4
3 5 ,5 9 1
3 2 ,6 0 9
2 9 ,7 9 9
2 8 ,9 6 7
2 3 ,4 2 9

2 .9
-.4
3 .0
.7
2.1
3 .5
4 .3
4 .5

A g u a d illa, P R .................................................................................................
A recib o , P R ....................................................................................................
C a g u a s , P R ....................................................................................................
M a y a g u e z , P R ..............................................................................................
P o n c e , P R ......................................................................................................
S a n J u a n - B a y a m o n , P R ................................ ..........................................

1 8,061
1 6 ,6 0 0
1 8 ,6 5 5
1 7,101
1 7 ,3 9 7
2 0 ,9 4 8

1 9 ,2 8 3
1 8 ,0 6 3
1 9 ,7 0 6
1 7 ,5 0 0
1 8 ,1 8 7
2 1 ,9 3 0

6 .8
8 .8
5 .6
2 .3
4 .5
4 .7

1 In c lu d e s d a t a for M etro p o litan S ta tis tic a l A r e a s (M SA) a n d P rim a ry M e tro p o lita n S ta tis tic a l A r e a s
(P M SA ) a s d e f in e d by O M B B ulletin N o. 9 9 -0 4 . In t h e N e w E n g la n d a r e a s , th e N e w E n g la n d C o u n ty
M e tro p o lita n A r e a (N EC M A ) d e fin itio n s w e r e u s e d .
2 E a c h y e a r ’s to tal is b a s e d o n t h e M SA defin itio n for th e s p e c ific y e a r.
d iffe re n c e s re s u ltin g from c h a n g e s in M SA d efin itio n s.

A n n u a l c h a n g e s in c lu d e

3 T o ta ls d o n o t in c lu d e t h e six M S A s w ithin P u e rto R ico.
N O T E : In c lu d e s w o r k e rs c o v e r e d b y U n e m p lo y m e n t
for F e d e r a l E m p lo y e e s (U C F E ) p ro g r a m s .

I n s u r a n c e (Ul) a n d U n e m p lo y m e n t C o m p e n s a tio n

Monthly Labor Review

September 2004

99

Current Labor Statistics:

27.

Labor Force Data

Annual data: Employment status of the population

[Numbers in thousands]
Em ploym ent status
C ivilian n o n in s titu tio n a l p o p u la tio n ...........
C ivilian la b o r fo r c e ........................
L a b o r fo r c e p a rtic ip a tio n r a t e ..................
E m p lo y e d .........................................
E m p lo y m e n t-p o p u la tio n ra tio ...........
U n e m p lo y e d ..........................

1993

19941

1995

1996

19971

19981

19991

20001

2001

2002

2003

1 9 4 ,8 3 8

1 9 6 ,8 1 4

1 9 8 ,5 8 4

2 0 0 ,5 9 1

2 0 3 ,1 3 3

2 0 5 ,2 2 0

2 0 7 ,7 5 3

2 1 2 ,5 7 7

2 1 5 ,0 9 2

2 1 7 ,5 7 0

1 2 9 ,2 0 0

1 3 1 ,0 5 6

2 2 1 ,1 6 8

1 3 2 ,3 0 4

1 3 3 ,9 4 3

1 3 6 ,2 9 7

1 3 7 ,6 7 3

1 3 9 ,3 6 8

1 4 2 ,5 8 3

1 4 3 ,7 3 4

1 4 4 ,8 6 3

6 6 .3

1 4 6 ,5 1 0

6 6 .6

6 6 .6

6 6 .8

67.1

67.1

67.1

67.1

6 6 .8

6 6 .6

1 2 0 ,2 5 9

6 6 .2

1 2 3 ,0 6 0

1 2 4 ,9 0 0

1 2 6 ,7 0 8

1 2 9 ,5 5 8

1 3 1 ,4 6 3

1 3 3 ,4 8 8

1 3 6 ,8 9 1

1 3 6 ,9 3 3

1 3 6 ,4 8 5

6 1 .7

1 3 7 ,7 3 6

6 2 .5

6 2 .9

6 3 .2

6 3 .8

64.1

6 4 .3

6 4 .4

6 3 .7

6 2 .7

8 ,9 4 0

7 ,9 9 6

6 2 .3

7 ,4 0 4

7 ,2 3 6

6 ,7 3 9

6 ,2 1 0

5 ,8 8 0

5 ,6 9 2

6 ,8 0 1

8 ,3 7 8

8 ,7 7 4

U n e m p lo y m e n t r a t e ........................
N o t in t h e la b o r f o r c e ..............................

6 .9

6.1

5 .6

5 .4

4 .9

4 .5

4 .2

4 .0

4 .7

5 .8

6 5 ,6 3 8

6 .0

6 5 ,7 5 8

6 6 ,2 8 0

6 6 ,6 4 7

6 6 ,8 3 6

6 7 ,5 4 7

6 8 ,3 8 5

6 9 ,9 9 4

7 1 ,3 5 9

7 2 ,7 0 7

7 4 ,6 5 8

1 N ot strictly c o m p a r a b l e w ith p rio r y e a r s .

28.

Annual data: Employment levels by industry

[In thousands]________
Industry

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

9 1 ,8 5 5

9 5 ,0 1 6

9 7 ,8 6 6

1 0 0 ,1 6 9

1 0 3,113

106,021

1 0 8 ,6 8 6

1 1 0 ,9 9 6

1 1 0 ,7 0 7

1 0 8 ,8 2 8

1 0 8 ,3 5 6

T otal non fa rm e m p lo y m e n t................

1 1 0 ,8 4 4

114,291

1 1 7,298

1 1 9 ,7 0 8

1 2 2 ,7 7 0

1 2 5 ,930

G o o d s -p ro d u c in g ..............................

1 2 8 ,9 9 3

1 3 1 ,7 8 5

1 3 1 ,8 2 6

2 2 ,2 1 9

130,341

2 2 ,7 7 4

129 931

2 4 ,3 5 4

2 4 ,4 6 5

2 4 ,6 4 9

2 3 ,8 7 3

2 2 ,5 5 7

659

2 3 ,4 1 0
637

2 3 ,8 8 6

666

2 3 ,1 5 6
641

654

645

598

599

606

5 ,5 3 6
1 7 ,237

5 ,8 1 3
1 7,419

6 ,1 4 9

6 ,5 4 5

6 ,7 8 7

6 ,8 2 6

6 ,7 1 6

6 722

1 7,560

1 7 ,3 2 2

1 7,263

16,441

1 5 ,2 5 9

1 4 ,5 2 5

T otal p riv ate e m p lo y m e n t.......................

N atural re s o u r c e s a n d m ining...................
C o n s tru c tio n .........................................
M an u factu rin g ................................
P riv ate serv ic e-p ro v id in g .....................
T ra d e , tra n s p o rta tio n , a n d utilities............
W h o le sa le t r a d e ...........................
R etail t r a d e .........................................
T ra n s p o rta tio n a n d w a re h o u s in g ..........
Inform ation.................................
F inancial a c tiv ities.................................

4 ,7 7 9

5 ,0 9 5

5 ,2 7 4

1 6 ,7 4 4

17,021

17,241

583

6 9 ,6 3 6

7 2 ,2 4 2

7 4 ,7 1 0

7 6 ,7 5 9

7 9 ,2 2 7

81 ,6 6 7

84,221

8 6 ,3 4 6

8 6 ,8 3 4

2 2 ,3 7 8

86,271

2 3 ,1 2 8

2 3 ,8 3 4

2 4 ,2 3 9

2 4 ,7 0 0

2 5 ,1 8 6

25,771

2 6 ,2 2 5

2 5 ,9 8 3

5 ,0 9 3 .2

2 5 ,4 9 7

25 275

5 ,2 4 7 .3

5,433.1

5 ,5 2 2 .0

5 ,6 6 3 .9

5 ,7 9 5 .2

5 ,8 9 2 .5

5 ,9 3 3 .2

5 ,7 7 2 .7

1 3 ,0 2 0 .5

1 3 ,4 9 0 .8

1 4 ,1 4 2 .5

1 4 ,3 8 8 .9

1 4 ,6 0 9 .3

14,970.1

1 5 ,2 7 9 .8

1 5 ,2 3 8 .6

5 ,6 5 2 .3
15,025.1

5 ,6 0 5 6

1 3 ,8 9 6 .7

3 ,5 5 3 .8
7 1 0 .7

3 ,7 0 1 .0

3 ,8 3 7 .8

3 ,9 3 5 .3

4 ,0 2 6 .5

4 ,1 6 8 .0

4 ,3 0 0 .3

4 ,4 1 0 .3

4 ,2 2 3 .6

6 8 9 .3

4 ,1 7 6 .7

66 6 .2

6 3 9 .6

6 2 0 .9

6 1 3 .4

6 0 8 .5

6 0 1 .3

4 ,3 7 2 .0
5 9 9 .4

2 ,6 6 8

5 9 6 .2

2 ,7 3 8
6,8 6 7

5 8 0 .8

2 ,8 4 3
6 ,8 2 7

2 ,9 4 0

3 ,0 8 4

3 ,4 1 9

3 395

7 ,1 7 8

7 ,6 4 8

3,631
7,6 8 7

3 ,6 2 9

6 ,9 6 9

3 ,2 1 8
7 ,4 6 2

7 ,8 0 7

7 847

6 ,7 0 9

P ro fe s sio n a l a n d b u s in e s s s e r v ic e s ......

1 1 ,4 9 5

1 2 ,1 7 4

1 2 ,844

13 ,4 6 2

1 4 ,3 3 5

1 5 ,1 4 7

1 5 ,9 5 7

E d u ca tio n a n d h ea lth s e r v ic e s ............
L eisu re a n d hosp itality ....................

1 6,666

1 6 ,4 7 6

1 2 ,3 0 3

1 5 ,9 7 6

12 ,8 0 7

1 3 ,2 8 9

1 4,446

1 4,798

1 5,109

1 5 ,6 4 5

1 6,199

1 0,100

10,501

1 3,683
1 0 ,7 7 7

1 4,087

9 ,7 3 2

1 1,018

1 1 ,2 3 2

1 1,543

1 1 ,862

12 ,0 3 6

4 ,3 5 0

1 1,986

1 2 ,1 2 5

4 ,4 2 8

4 ,5 7 2

4 ,6 9 0

4 ,8 2 5

4 ,9 7 6

5 ,0 8 7

5 ,1 6 8

5 ,2 5 8

5 ,3 7 2

5 ,3 9 3

1 8,989

1 9 ,2 7 5

1 9,432

1 9 ,5 3 9

19 ,6 6 4

1 9 ,9 0 9

2 0 ,3 0 7

2 0 ,7 9 0

2 1 ,1 1 8

2 1 ,5 1 3

21 5 7 5

O th e r s e r v ic e s ................................
G o v e rn m e n t.............................

N o t e : D a ta reflect th e c o n v e rs io n to th e 2 0 0 2 v ersio n of th e N orth A m erican Industry C lassif c a tio n S y s te m (NAics), re placing th e
S tandard Ind jstrrial C la s s fication (sic)
s y s te m . N A ic s-b ase d d a ta by industry a r e not c o m p a ra b le with s ic - b a s e d d a ta . S e e "N otes on th e d ata " for a d esc rip tio n of th e m o st re c e n t b e n c h m a rk revision.

100

Monthly Labor Review


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

September 2004

15 9 9 7

29.

Annual data: Average hours and earnings of production or nonsupervisory workers on nonfarm
payrolls, by industry
Industry

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

Private sector:
A v e r a g e w e e k ly h o u r s .............................................................

3 4 .3

3 4 .5

3 4 .3

3 4 .3

3 4 .5

3 4 .5

3 4 .3

3 4 .3

3 4 .0

3 3 .9

3 3 .7

A v e r a g e h o u rly e a r n i n g s (in d o lla r s ) ................................

1 1 .0 3

1 1 .3 2

1 1 .6 4

1 2 .0 3

1 2 .4 9

1 3 .0 0

1 3 .4 7

1 4 .0 0

1 4 .5 3

1 4 .9 5

1 5 .3 5

A v e r a g e w e e k ly e a r n i n g s (in d o lla rs )...............................

3 7 8 .4 0

3 9 0 .7 3

3 9 9 .5 3

4 1 2 .7 4

4 3 1 .2 5

4 4 8 .0 4

4 6 2 .4 9

4 8 0 .4 1

4 9 3 .2 0

5 0 6 .0 7

5 1 7 .3 6

Goods-producing:
A v e r a g e w e e k ly h o u r s ..........................................................

4 0 .6

41.1

4 0 .8

4 0 .8

41.1

4 0 .8

4 0 .8

4 0 .7

3 9 .9

3 9 .9

3 9 .8

A v e r a g e h o u rly e a r n i n g s (in d o lla rs )..............................

1 2 .2 8

1 2 .6 3

1 2 .9 6

1 3 .3 8

1 3 .8 2

1 4 .2 3

14.71

1 5 .2 7

1 5 .7 8

1 6 .3 3

1 6 .8 0

A v e r a g e w e e k ly e a r n i n g s (in d o lla rs )............................

4 9 8 .8 2

5 1 9 .5 8

5 2 8 .6 2

5 4 6 .4 8

5 6 8 .4 3

5 8 0 .9 9

5 9 9 .9 9

6 2 1 .8 6

6 3 0 .0 4

6 5 1 .6 1

6 6 9 .2 3

Natural resources and mining
A v e r a g e w e e k ly h o u r s .........................................................

4 4 .9

4 5 .3

4 5 .3

4 6 .0

4 6 .2

4 4 .9

4 4 .2

4 4 .4

4 4 .6

4 3 .2

4 3 .6

A v e r a g e h o u rly e a r n i n g s (in d o lla rs )............................

1 4 .1 2

14.41

1 4 .7 8

1 5 .1 0

1 5 .5 7

1 6 .2 0

1 6 .3 3

1 6 .5 5

1 7 .0 0

1 7 .1 9

1 7 .5 8

A v e r a g e w e e k ly e a r n i n g s (in d o lla rs )...........................

6 3 4 .7 7

6 5 3 .1 4

6 7 0 .3 2

6 9 5 .0 7

7 2 0 .1 1

7 2 7 .2 8

7 2 1 .7 4

7 3 4 .9 2

7 5 7 .9 2

7 4 1 .9 7

7 6 6 .8 3

Construction:
A v e ra g e w e e k ly h o u r s .........................................................

3 8 .4

3 8 .8

3 8 .8

3 8 .9

3 8 .9

3 8 .8

3 9 .0

3 9 .2

3 8 .7

3 8 .4

3 8 .4

A v e ra g e h o u rly e a r n i n g s (in d o lla rs )............................

1 4 .0 4

1 4 .3 8

1 4 .7 3

15.11

1 5 .6 7

1 6 .2 3

1 6 .8 0

1 7 .4 8

1 8 .0 0

1 8 .5 2

1 8 .9 5

A v e r a g e w e e k ly e a r n i n g s (in d o lla rs )...........................

5 3 9 .8 1

5 5 8 .5 3

5 7 1 .5 7

5 8 8 .4 8

6 0 9 .4 8

6 2 9 .7 5

6 5 5 .1 1

6 8 5 .7 8

6 9 5 .8 9

7 1 1 .8 2

7 2 7 .1 1

Manufacturing:
A v e r a g e w e e k ly h o u r s .........................................................

41.1

4 1 .7

4 1 .3

4 1 .3

4 1 .7

4 1 .4

4 1 .4

4 1 .3

4 0 .3

4 0 .5

4 0 .4

A v e r a g e h o u rly e a r n i n g s (in d o lla r s ) ............................

1 1 .7 0

1 2 .0 4

1 2 .3 4

1 2 .7 5

1 3 .1 4

1 3 .4 5

1 3 .8 5

1 4 .3 2

1 4 .7 6

1 5 .2 9

1 5 .7 4

A v e r a g e w e e k ly e a r n i n g s (in d o lla rs )..........................

4 8 0 .8 0

5 0 2 .1 2

5 0 9 .2 6

5 2 6 .5 5

5 4 8 .2 2

5 5 7 .1 2

5 7 3 .1 7

5 9 0 .6 5

5 9 5 .1 9

6 1 8 .7 5

6 3 6 .0 7

Private service-providing:
A v e r a g e w e e k ly h o u r s ..........................................................

3 2 .5

3 2 .7

3 2 .6

3 2 .6

3 2 .8

3 2 .8

3 2 .7

3 2 .7

3 2 .5

3 2 .5

3 2 .4

A v e r a g e h o u rly e a r n i n g s (in d o lla rs ).............................

1 0 .6 0

1 0 .8 7

1 1 .1 9

1 1 .5 7

1 2 .0 5

1 2 .5 9

1 3 .0 7

1 3 .6 0

1 4 .1 6

1 4 .5 6

1 4 .9 6

A v e r a g e w e e k ly e a r n i n g s (in d o lla r s ) ...........................

3 4 5 .0 3

3 5 4 .9 7

3 6 4 .1 4

3 7 6 .7 2

3 9 4 .7 7

4 1 2 .7 8

4 2 7 .3 0

4 4 5 .0 0

4 6 0 .3 2

4 7 2 .8 8

4 8 4 .0 0

Trade, transportation, and utilities:
A v e ra g e w e e k ly h o u r s ..........................................................

34.1

3 4 .3

34.1

34.1

3 4 .3

3 4 .2

3 3 .9

3 3 .8

3 3 .5

3 3 .6

3 3 .6

A v e r a g e h o u rly e a r n i n g s (in d o lla rs )............................

1 0 .5 5

1 0 .8 0

1 1 .1 0

1 1 .4 6

1 1 .9 0

1 2 .3 9

1 2 .8 2

13.31

1 3 .7 0

1 4 .0 2

1 4 .3 4

A v e r a g e w e e k ly e a r n i n g s (in d o lla rs )...........................

3 5 9 .3 3

3 7 0 .3 8

3 7 8 .7 9

3 9 0 .6 4

4 0 7 .5 7

4 2 3 .3 0

4 3 4 .3 1

4 4 9 .8 8

4 5 9 .5 3

4 7 1 .2 7

4 8 1 .1 0

Wholesale trade:
A v e r a g e w e e k ly h o u r s .....................................................

3 8 .5

3 8 .8

3 8 .6

3 8 .6

3 8 .8

3 8 .6

3 8 .6

3 8 .8

3 8 .4

3 8 .0

3 7 .8

A v e r a g e h o u rly e a r n i n g s (in d o lla rs )........................

1 2 .5 7

1 2 .9 3

1 3 .3 4

1 3 .8 0

14.41

1 5 .0 7

1 5 .6 2

1 6 .2 8

1 6 .7 7

1 6 .9 8

1 7 .3 6

A v e r a g e w e e k ly e a r n i n g s (in d o lla rs )......................

4 8 4 .4 6

5 0 1 .1 7

5 1 5 .1 4

5 3 3 .2 9

5 5 9 .3 9

58 2 .2 1

6 0 2 .7 7

6 3 1 .4 0

6 4 3 .4 5

6 4 4 .3 8

6 5 7 .1 2

A v e r a g e w e e k ly h o u r s .....................................................

3 0 .7

3 0 .9

3 0 .8

3 0 .7

3 0 .9

3 0 .9

3 0 .8

3 0 .7

3 0 .7

3 0 .9

3 0 .9

A v e r a g e h o u rly e a r n i n g s (in d o lla rs ).......................

8 .3 6

8.61

8 .8 5

9.21

9 .5 9

1 0 .0 5

1 0 .4 5

1 0 .8 6

1 1 .2 9

1 1 .6 7

1 1 .9 0

A v e ra g e w e e k ly e a r n i n g s (in d o lla r s ) ......................

4 8 4 .4 6

5 0 1 .1 7

5 1 5 .1 4

5 3 3 .2 9

5 5 9 .3 9

5 8 2 .2 1

6 0 2 .7 7

6 3 1 .4 0

6 4 3 .4 5

6 4 4 .3 8

6 5 7 .1 2

Retail trade:

Transportation and warehousing:
A v e r a g e w e e k ly h o u r s .....................................................

3 8 .9

3 9 .5

3 8 .9

39.1

3 9 .4

3 8 .7

3 7 .6

3 7 .4

3 6 .7

3 6 .8

3 6 .8

A v e r a g e h o u rly e a r n i n g s (in d o lla rs ).......................

12.71

1 2 .8 4

1 3 .1 8

1 3 .4 5

1 3 .7 8

1 4 .1 2

1 4 .5 5

1 5 .0 5

1 5 .3 3

1 5 .7 6

1 6 .2 5

A v e r a g e w e e k ly e a r n i n g s (in d o lla r s ) ......................

4 9 4 .3 6

5 0 7 .2 7

5 1 3 .3 7

5 2 5 .6 0

5 4 2 .5 5

5 4 6 .8 6

5 4 7 .9 7

5 6 2 .3 1

5 6 2 .7 0

5 7 9 .7 5

5 9 7 .7 9

42.1

Utilities:
A v e r a g e w e e k ly h o u r s .....................................................
A v e r a g e h o u rly e a r n i n g s (in d o lla rs ).......................

4 2 .3
1 8 .6 6

4 2 .3

4 2 .0

4 2 .0

4 2 .0

4 2 .0

4 2 .0

4 1 .4

4 0 .9

41.1

1 7 .9 5

1 9 .1 9

1 9 .7 8

2 0 .5 9

2 1 .4 8

2 2 .0 3

2 2 .7 5

2 3 .5 8

2 3 .9 6

2 4 .7 6

A v e r a g e w e e k ly e a r n i n g s (in d o lla rs )......................

7 5 6 .3 5

7 8 9 .9 8

8 1 1 .5 2

8 3 0 .7 4

8 6 5 .2 6

9 0 2 .9 4

9 2 4 .5 9

9 5 5 .6 6

9 7 7 .1 8

9 7 9 .0 9

1 ,0 1 6 .9 4

Information:
A v e ra g e w e e k ly h o u r s ....................................................

3 6 .0

3 6 .0

3 6 .0

3 6 .4

3 6 .3

3 6 .6

3 6 .7

3 6 .8

3 6 .9

3 6 .5

3 6 .2

A v e r a g e h o u rly e a r n i n g s (in d o lla rs ).......................

1 4 .8 6

1 5 .3 2

1 5 .6 8

1 6 .3 0

1 7 .1 4

1 7 .6 7

1 8 .4 0

1 9 .0 7

1 9 .8 0

2 0 .2 0

2 1 .0 1

A v e r a g e w e e k ly e a r n i n g s (in d o lla rs )......................

5 3 5 .2 5

5 5 1 .2 8

5 6 4 .9 8

5 9 2 .6 8

6 2 2 .4 0

6 4 6 .5 2

6 7 5 .3 2

7 0 0 .8 9

7 3 1 .1 1

7 3 8 .1 7

7 6 1 .1 3

Financial activities:
A v e r a g e w e e k ly h o u r s .....................................................

3 5 .5

3 5 .5

3 5 .5

3 5 .5

3 5 .7

3 6 .0

3 5 .8

3 5 .9

3 5 .8

3 5 .6

3 5 .5

A v e ra g e h o u rly e a r n i n g s (in d o lla rs ).......................

1 1 .3 6
4 0 3 .0 2

1 1 .8 2

1 2 .2 8

12.71

1 3 .2 2

1 3 .9 3

1 4 .4 7

1 4 .9 8

1 6 .1 7

4 1 9 .2 0

4 3 6 .1 2

4 5 1 .4 9

4 7 2 .3 7

5 0 0 .9 5

5 1 7 .5 7

5 3 7 .3 7

1 5 .5 9
5 5 8 .0 2

1 7 .1 3
6 0 8 .8 7

A v e r a g e w e e k ly e a r n i n g s (in d o lla r s ) ......................

5 7 5 .5 1

Professional and business services:
A v e r a g e w e e k ly h o u r s .....................................................

3 4 .0

34.1

3 4 .0

34.1

3 4 .3

3 4 .3

3 4 .4

3 4 .5

3 4 .2

3 4 .2

34.1

A v e r a g e h o u rly e a r n i n g s (in d o lla rs ).......................

1 1 .9 6

1 2 .1 5

1 2 .5 3

1 3 .0 0

1 3 .5 7

1 4 .2 7

1 4 .8 5

1 5 .5 2

1 6 .3 3

16.81

1 7 .2 0

A v e ra g e w e e k ly e a r n i n g s (in d o lla rs )......................

4 0 6 .2 0

4 1 4 .1 6

4 2 6 .4 4

4 4 2 .8 1

4 6 5 .5 1

4 9 0 .0 0

5 1 0 .9 9

5 3 5 .0 7

5 5 7 .8 4

5 7 4 .6 6

5 8 6 .6 8

Education and health services:
A v e r a g e w e e k ly h o u r s ....................................................

3 2 .0

3 2 .0

3 2 .0

3 1 .9

3 2 .2

3 2 .2

32.1

3 2 .2

3 2 .3

3 2 .4

3 2 .3

A v e r a g e h o u rly e a r n i n g s (in d o lla rs ).......................

11.21

1 1 .5 0

1 1 .8 0

1 2 .1 7

1 2 .5 6

1 3 .0 0

1 3 .4 4

1 3 .9 5

1 4 .6 4

15.21

1 5 .6 4

A v e r a g e w e e k ly e a r n i n g s (in d o lla rs )......................

3 5 9 .0 8

3 6 8 .1 4

3 7 7 .7 3

3 8 8 .2 7

4 0 4 .6 5

4 1 8 .8 2

4 3 1 .3 5

4 4 9 .2 9

4 7 3 .3 9

4 9 2 .7 4

5 0 5 .7 6

A v e r a g e w e e k ly h o u r s ...................................................

2 5 .9

2 6 .0

2 5 .9

2 5 .9

2 6 .0

2 6 .2

26.1

26.1

2 5 .8

2 5 .8

2 5 .6

A v e r a g e h o u rly e a r n i n g s (in d o lla rs ).......................

6 .3 2

6 .4 6

6 .6 2

6 .8 2

7 .1 3

7 .4 8

7 .7 6

8.11

8 .3 5

8 .5 8

8 .7 6

A v e r a g e w e e k ly e a r n i n g s (in d o lla rs )......................

1 6 3 .4 5

1 6 8 .0 0

1 7 1 .4 3

1 7 6 .4 8

185.81

1 9 5 .8 2

2 0 2 .8 7

2 1 1 .7 9

2 1 5 .1 9

2 2 1 .2 6

2 2 4 .2 5

Leisure and hospitality:

Other services:
A v e r a g e w e e k ly h o u r s ...................................................

3 2 .6

3 2 .7

3 2 .6

3 2 .5

3 2 .7

3 2 .6

3 2 .5

3 2 .5

3 2 .3

3 2 .0

3 1 .4

A v e ra g e h o u rly e a r n i n g s (in d o lla rs ).......................

9 .9 0

1 0 .1 8

10.51

1 0 .8 5

1 1 .2 9

1 1 .7 9

1 2 .2 6

1 2 .7 3

1 3 .2 7

1 3 .7 2

1 3 .8 4

A v e ra g e w e e k ly e a r n i n g s (in d o lla rs )......................

3 2 2 .6 9

3 3 2 .4 4

3 4 2 .3 6

3 5 2 .6 2

3 6 8 .6 3

3 8 4 .2 5

3 9 8 .7 7

4 1 3 .4 1

4 2 8 .6 4

4 3 9 .7 6

4 3 4 .4 9

N o t e : D a ta re fle c t t h e c o n v e rs io n to th e 2 0 0 2 v e r s io n o f th e N o rth A m e ric a n In d u s try C la s s ific a tio n S y s te m ( n a ic S), re p la c in g th e S ta n d a r d In d u strial C la s s ific a tio n
(SIC) s y s t e m .

N A ic s -b a s e d d a t a b y in d u s try a r e n o t c o m p a r a b l e w ith S I C - b a s e d d a ta .


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

Monthly Labor Review

September 2004

101

Current Labor Statistics:

30.

Compensation & Industrial Relations

Employment Cost Index, compensation,' by occupation and industry group

[June 1989 = 100]
2002
Series

June

Sept.

2003
Dec.

Mar.

June

2004

Sept.

Dec.

Mar.

Percent change

June

3 m onths

12 m onths

ended

ended

June 2004

Civilian workers2............................

1 5 9 .9

1 6 1 .3

1 6 2 .2

1 6 4 .5

1 6 5 .8

1 6 7 .6

1 6 8 .4

1 7 0 .7

1 7 2 .2

0 .9

3 .9

3 6
3 8

W o r k e rs , b y o c c u p a tio n a l g ro u p :
W h ite -c o lla r w o r k e r s ............................................

162.1

1 6 3 .5

1 6 4 .3

1 6 6 .7

1 6 7 .9

1 6 9 .9

1 7 0 .7

1 7 2 .7

1 7 4 .0

P ro fe s s io n a l s p e c ia lty a n d te c h n ic a l..................................

.8

1 5 9 .3

1 6 1 .4

1 6 2 .4

164.1

1 6 5 .0

1 6 7 .0

1 6 8 .0

1 7 0 .2

1 7 1 .2

E x e c u tiv e , a d m in itra tiv e , a n d m a n a g e r i a l ..................

.6

1 6 5 .6

1 6 6 .3

1 6 6 .7

171.1

1 7 2 .0

1 7 4 .0

1 7 4 .9

1 7 5 .8

177.1

.7

A d m in istra tiv e s u p p o r t, in clu d in g c le ric a l..............................

3 0

1 6 3 .3

1 6 4 .9

166.1

1 6 8 .3

1 7 0 .0

1 7 1 .7

1 7 2 .5

1 7 5 .3

1 7 7 .2

1.1

4 2

B lu e -c o lla r w o r k e r s ............................................

155.1

1 5 6 .4

1 5 7 .5

1 5 9 .8

1 6 1 .4

1 6 2 .9

1 6 3 .7

1 6 6 .9

1 6 8 .8

S e r v ic e o c c u p a t i o n s ................................................

1.1

4 .6

1 5 9 .4

1 6 1 .3

1 6 2 .2

164.1

1 6 5 .0

1 6 6 .8

1 6 7 .9

1 6 9 .7

1 7 0 .9

.7

3 .6

W o r k e rs , b y in d u s try division:
G o o d s - p r o d u c in g .........................................................

1 5 7 .7

1 5 8 .7

1 6 9 .2

163.1

1 6 4 .6

1 6 5 .8

1 6 6 .8

1 7 0 .4

1 7 1 .9

M a n u f a c tu rin g ....................................................

.9

4 .4

158.1

159.1

1 6 0 .5

1 6 4 .0

1 6 5 .4

1 6 6 .5

167.1

1 7 1 .7

1 7 3 .2

S e r v ic e - p r o d u c in g ..................................................

.9

4 7

1 6 0 .7

1 6 2 .2

1 6 2 .8

1 6 5 .0

1 6 6 .2

1 6 8 .2

169.1

1 7 0 .8

1 7 2 .3

.9

3 .7

161.1

1 6 3 .2

1 6 3 .9

1 6 5 .3

1 6 6 .3

1 6 8 .5

1 6 9 .5

1 7 1 .2

1 7 2 .3

.6

3 .6

S e r v i c e s ........................................................
H e a lth s e r v ic e s ...............................................
H o s p ita ls ...................................................
E d u c a tio n a l s e r v ic e s ..................................................
P u b lic a d m in is tr a tio n 3 ........................................
N o n m a n u f a c tu r in g .........................................................

Private industry workers..................................
E x c lu d in g s a l e s o c c u p a t i o n s .................................

1 6 1 .8

163.1

1 6 4 .5

1 6 6 .4

1 6 7 .6

1 6 9 .3

1 7 0 .7

1 7 3 .0

1 7 4 .4

.8

4.1

1 6 3 .8

1 6 5 .7

1 6 7 .6

1 6 9 .9

1 7 0 .8

173.1

1 7 4 .8

1 7 6 .8

1 7 8 .2

.8

4 3

1 5 7 .4

1 6 1 .6

1 6 2 .8

1 6 3 .6

1 6 4 .2

1 6 6 .9

1 6 7 .6

1 6 8 .5

1 6 8 .9

.2

2 .9

1 5 7 .5

1 6 0 .2

1 6 1 .7

1 6 3 .4

1 6 4 .3

1 6 7 .3

168.1

170.1

1 7 1 .4

.8

4 .3

1 6 0 .2

1 6 1 .7

1 6 2 .4

1 6 4 .5

1 6 5 .8

1 6 7 .8

1 6 8 .6

1 7 0 .4

1 7 1 .8

.8

3 .6

1 6 0 .7

1 6 1 .6

1 6 2 .3

1 6 5 .0

1 6 6 .4

168.1

1 6 8 .8

1 7 1 .4

1 7 3 .0

.9

4 .0

1 6 0 .5

1 6 1 .6

1 6 2 .4

165.1

1 6 6 .6

168.1

1 6 9 .0

1 7 1 .6

1 7 3 .2

.9

4 .0

1 6 3 .8

1 6 4 .6

3 .7

W o r k e rs , b y o c c u p a tio n a l g ro u p :
W h ite -c o lla r w o r k e r s ................................................

1 6 5 .2

168.1

1 6 9 .4

1 7 1 .2

1 7 2 .0

1 7 4 .2

1 7 5 .7

.9

1 6 4 .3

1 6 5 .3

1 6 5 .9

169.1

1 7 0 .4

172.1

1 7 3 .0

1 7 5 .3

1 7 6 .7

.8

P ro fe s s io n a l s p e c ia lty a n d te c h n ic a l o c c u p a t i o n s .............

3 .7

1 6 2 .5

1 6 3 .6

1 6 4 .4

1 6 6 .5

1 6 7 .7

1 6 9 .4

1 7 0 .5

1 7 3 .4

1 7 4 .7

.7

4 .2

E x e c u tiv e , a d m in itra tiv e , a n d m a n a g e ria l o c c u p a tio n s ..
S a l e s o c c u p a t i o n s .......................................................

1 6 6 .6

1 6 7 .0

1 6 7 .2

172.1

173.1

1 7 5 .0

1 7 5 .9

1 7 6 .8

178.1

.7

2 .9

1 6 1 .6

1 6 1 .6

1 6 1 .9

1 6 3 .5

165.1

1 6 7 .2

167.1

1 6 9 .2

1 7 1 .2

1.2

A d m in istra tiv e s u p p o r t o c c u p a tio n s , in clu d in g c le ric a l...

1 6 4 .2

1 6 5 .6

1 6 6 .7

1 6 9 .0

1 7 0 .9

1 7 2 .3

1 7 3 .2

176.1

178.1

1.1

3 .7
4 2

155.1

1 5 6 .3

1 5 7 .3

1 5 9 .7

1 6 1 .4

1 6 2 .8

1 6 3 .6

1 6 6 .9

1 6 8 .8

1.1

4 .6

P re c is io n p ro d u c tio n , c ra ft, a n d re p a ir o c c u p a t i o n s ........

1 5 5 .7

1 5 6 .9

1 5 7 .8

1 6 0 .0

1 6 2 .0

163.1

1 6 4 .2

167.1

169.1

1 .2

4 .4

M a c h in e o p e r a t o r s , a s s e m b l e r s , a n d in s p e c t o r s ...............

1 5 4 .7

1 5 5 .4

1 5 6 .7

1 5 9 .9

161.1

1 6 2 .6

1 6 3 .2

1 6 8 .7

1 7 0 .5

E x clu d in g s a l e s o c c u p a t i o n s .............................................

B lu e -c o lla r w o r k e r s ............................................

1.1

T r a n s p o r ta tio n a n d m a te ria l m o v in g o c c u p a t i o n s .............

5 .8

1 4 9 .6

1 5 1 .0

1 5 1 .8

1 5 3 .2

155.1

1 5 6 .7

1 5 6 .9

1 5 8 .5

1 6 0 .6

1 .3

3 .5

H a n d le rs , e q u ip m e n t c l e a n e r s , h e lp e r s , a n d la b o re rs ....

1 5 9 .9

1 6 1 .4

1 6 2 .9

1 6 4 .9

1 6 6 .8

1 6 8 .6

1 6 9 .5

1 7 1 .7

1 7 3 .2

.9

3 .8

1 5 7 .4

1 5 9 .0

1 5 9 .8

1 6 1 .7

1 6 2 .6

1 6 3 .8

1 6 4 .3

1 6 6 .9

1 6 8 .2

.8

3 .4

1 5 8 .7

1 5 9 .7

1 6 0 .5

1 6 2 .6

164.1

1 6 5 .7

1 6 6 .6

1 6 9 .3

1 7 1 .0

1.0

4 .2

1 5 7 .6

1 5 8 .6

160.1

1 6 3 .0

1 6 4 .5

1 6 5 .7

1 7 0 .3

1 7 1 .8

.9

4 .4

1 5 6 .9

1 5 7 .9

1 5 9 .2

1 6 2 .4

1 6 3 .8

1 6 5 .0

1 6 5 .9

1 6 9 .8

1 7 1 .2

W h ite -c o lla r o c c u p a t i o n s ............................................

.8

4 .5

1 6 1 .9

1 6 2 .9

1 6 4 .3

1 6 7 .8

1 6 9 .2

170.1

1 7 0 .5

1 7 3 .5

1 7 4 .7

E x c lu d in g s a l e s o c c u p a t i o n s ...........................

.7

3 .3

1 6 0 .2

161.1

1 6 2 .3

1 6 6 .3

1 6 7 .5

1 6 8 .5

1 6 9 .2

1 7 2 .2

1 7 3 .3

S e r v ic e o c c u p a t i o n s ..................................................
P ro d u c tio n a n d n o n s u p e r v is o r y o c c u p a t i o n s 4 ...............
W o r k e rs , b y in d u s try division:
G o o d s - p r o d u c in g ..........................................................
E x clu d in g s a l e s o c c u p a t i o n s ...................................

.6

B lu e -c o lla r o c c u p a t i o n s ..............................................
C o n s tr u c tio n ....................................................

3 .5

1 5 4 .8

1 5 5 .9

1 5 7 .3

1 5 9 .9

1 6 1 .5

1 6 2 .9

1 6 3 .9

168.1

1 6 9 .8

1 .0

5.1

1 5 5 .2

1 5 6 .3

1 5 7 .9

159.1

161.1

1 6 2 .3

1 6 3 .3

1 6 4 .6

M a n u f a c tu rin g .........................................................

1 6 5 .9

.8

3 .0

158.1

159.1

1 6 0 .5

1 6 4 .0

1 6 5 .4

1 6 6 .5

167.1

1 7 1 .7

1 7 3 .2

W h ite -c o lla r o c c u p a t i o n s ..................................................

.9

4 .7

161.1

1 6 2 .2

167.1

1 6 8 .7

1 6 9 .5

1 6 9 .6

1 7 3 .2

1 7 4 .6

E x clu d in g s a l e s o c c u p a t i o n s ..................................

.8

3 .5

1 5 8 .6

3 .7

1 5 9 .6

1 6 3 .3
1 6 0 .7

165.1

1 6 6 .4

1 6 7 .4

1 6 7 .8

1 7 1 .3

1 7 2 .6

.8

1 5 5 .8

1 5 6 .7

1 5 8 .3

1 6 1 .6

1 6 2 .8

164.1

165.1

1 7 0 .4

1 7 2 .0

D u r a b le s ..................................................

.9

5 .7

1 5 8 .3

1 5 8 .9

1 6 0 .6

1 6 4 .4

1 6 5 .5

1 6 6 .6

1 6 7 .3

1 7 2 .4

1 7 4 .0

N o n d u r a b l e s .........................................

.9

5.1

1 5 7 .5

1 5 9 .2

1 6 0 .3

163.1

1 6 4 .9

1 6 6 .0

1 6 6 .6

1 7 0 .4

1 7 1 .7

.8

4.1

1 6 1 .8

1 6 2 .7

163.1

1 6 5 .6

1 6 7 .0

1 6 8 .8

1 6 9 .7

1 7 1 .6

1 7 3 .3

E x clu d in g s a l e s o c c u p a t i o n s ................................

1 .0

3 .8

1 6 2 .4

1 6 3 .5

1 6 4 .0

1 6 6 .6

1 6 8 .0

1 6 9 .7

1 7 0 .6

1 7 2 .5

1 7 4 .2

W h ite -c o lla r o c c u p a t i o n s ................................................

1 .0

3 7

1 6 4 .0

1 6 4 .7

165.1

1 6 7 .9

1 6 9 .2

1 7 1 .2

1 7 2 .0

174.1

1 7 5 .7

.9

3 .8

B lu e -c o lla r o c c u p a t i o n s ...........................................

S e r v ic e - p r o d u c in g ....................................................

E x c lu d in g s a l e s o c c u p a t i o n s ..........................................

1 6 5 .6

1 6 6 .5

1 6 7 .0

1 6 9 .9

1 7 1 .3

173.1

1 7 4 .2

1 7 6 .2

1 7 7 .8

B lu e -c o lla r o c c u p a t i o n s ...............................................

.9

3 8

1 5 5 .2

1 5 6 .6

1 5 6 .9

1 5 8 .7

1 6 0 .8

1 6 2 .2

1 6 2 .6

164.1

1 6 6 .4

1 .4

S e r v ic e o c c u p a t i o n s ....................................................

3 .5

1 5 7 .0

1 5 8 .5

1 5 9 .3

161.1

1 6 2 .0

1 6 3 .2

1 6 4 .3

166.1

1 6 7 .4

.8

3 3

1 5 8 .9

1 6 0 .8

1 6 1 .7

1 6 3 .2

1 6 5 .4

1 6 6 .5

1 6 7 .0

1 6 9 .8

1 7 2 .5

T r a n s p o r ta tio n ....................................................

1.6

4 .3

1 5 3 .9

1 5 5 .4

156.1

1 5 7 .8

1 5 9 .4

1 5 9 .6

1 6 2 .0

1 6 4 .7

1 .7

P u b lic u tilities...............................................

3 .7

1 6 5 .5
166.1

1 6 8 .2

1 6 9 .2

1 7 0 .5

1 7 4 .2

1 7 6 .4

1 7 7 .0

1 8 0 .4

183.1

C o m m u n ic a tio n s ............................................

1 .5

5 1

1 6 9 .0

170.1

1 7 1 .3

1 7 5 .5

1 7 8 .4

1 7 9 .0

1 8 2 .2

1 8 3 .6

.8

E lec tric, g a s , a n d s a n ita r y s e r v ic e s ..................................

4 .6

1 6 4 .8

1 6 7 .2

168.1

1 6 9 .5

1 7 2 .6

1 7 3 .8

1 7 4 .6

T r a n s p o r ta tio n a n d p u b lic u tilities.....................................

1 5 8 .9

1 7 8 .2

1 8 2 .4

2 .4

5 7

1 5 9 .5

1 5 9 .6

1 5 9 .7

1 6 1 .3

1 6 2 .5

1 6 4 .3

1 6 5 .0

1 6 6 .3

168.1

1.1

E x clu d in g s a l e s o c c u p a t i o n s ...................................
W h o le s a le t r a d e .........................................

3 .4

1 6 0 .0

1 6 0 .3

1 6 0 .4

1 6 1 .8

1 6 2 .7

1 6 5 .0

1 6 5 .9

1 6 7 .4

1 6 8 .6

.7

1 6 6 .3

1 6 5 .9

1 6 6 .7

1 6 9 .5

1 7 1 .3

1 7 2 .0

1 7 2 .0

1 7 3 .8

1 7 5 .9

1 .2

E x clu d in g s a l e s o c c u p a t i o n s ...........................................
R etail t r a d e .................................................

2 .7

1 6 4 .4

166.1

1 6 7 .2

1 6 8 .4

1 6 9 .9

1 7 1 .2

1 7 1 .3

1 7 3 .7

1 7 4 .0

.2

2 .4

W h o le s a le a n d retail t r a d e .................................

3 6

1 5 5 .6

1 5 6 .0

1 5 5 .8

1 5 6 .6

1 5 7 .4

1 5 9 .9

1 6 1 .0

162.1

1 6 3 .7

1.0

G e n e r a l m e r c h a n d i s e s t o r e s ..........................

4 .0

1 5 4 .2

156.1

155.1

1 5 6 .4

1 5 9 .2

1 6 1 .2

1 6 5 .6

1 6 5 .8

1 6 6 .2

.2

F o o d s t o r e s .........................................................

4 .4

1 5 4 .5

1 5 6 .3

1 5 6 .3

1 5 7 .5

1 5 8 .6

1 5 9 .3

1 6 0 .3

162.1

1 6 3 .5

.9

3.1

S e e f o o tn o te s a t e n d of ta b le .

102

1 6 6 .5

Monthly Labor Review


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

September 2004

30. Continued—Employment Cost Index, compensation,1 by occupation and industry group
[June 1989 = 100]
2002
Series

June

Sept.

2004

2003
Dec.

Mar.

June

Sept.

Dec.

Mar.

P ercent change

June

3 m onths

12 m onths

ended

ended

June 2004
F in a n c e , in s u r a n c e , a n d re a l e s t a t e .........................................

1 6 7 .3

1 6 8 .0

1 6 8 .5

1 7 6 .7

1 7 8 .3

1 8 0 .2

1 8 0 .9

1 8 2 .5

1 8 3 .6

0 .6

3 .0

E x c lu d in g s a l e s o c c u p a t i o n s .................................................

1 7 1 .3

172.1

173.1

1 8 2 .0

1 8 4 .0

1 ,8 5 3 .0

186.1

1 8 6 .6

1 8 8 .7

1.1

2 .6

B a n k in g , s a v i n g s a n d lo a n , a n d o th e r c re d it a g e n c i e s .

1 8 4 .2

1 8 4 .6

1 8 5 .3

2 0 4 .3

2 0 6 .3

2 0 7 .6

2 0 9 .0

2 0 7 .2

2 0 8 .9

.8

1 .3

I n s u r a n c e .............................................................................................

166.1

167.1

1 6 7 .9

172.1

1 7 3 .9

175.1

1 7 6 .2

1 7 7 .8

1 8 0 .5

1 .5

3 .8

S e r v i c e s ..................................................................................................

1 6 3 .7

1 6 4 .9

1 6 5 .4

167.1

1 6 8 .4

1 7 0 .4

1 7 1 .4

1 7 3 .5

175.1

.9

4 .0

1 6 6 .6

1 6 7 .2

1 6 7 .5

1 6 8 .5

1 6 9 .2

1 7 1 .9

1 7 2 .6

1 7 4 .8

1 7 6 .9

1 .2

4 .6

H e a lth s e r v i c e s .................................................................................

1 6 2 .0

1 6 3 .2

1 6 4 .4

1 6 6 .5

1 6 7 .9

1 6 9 .4

1 7 0 .8

1 7 3 .3

1 7 4 .8

.9

4.1

H o s p ita ls ...........................................................................................

1 6 4 .5

1 6 6 .2

168.1

1 7 0 .8

1 7 1 .9

1 7 3 .9

1 7 5 .9

178.1

1 7 9 .7

.9

4 .5

1 6 9 .0

1 7 3 .5

1 7 5 .2

1 7 6 .3

177.1

1 8 0 .2

1 8 1 .3

183.1

1 8 4 .2

.6

4 .0

C o lle g e s a n d u n iv e r s itie s .........................................................

1 6 8 .4

1 7 2 .0

1 7 3 .7

1 7 4 .5

1 7 5 .4

1 7 8 .4

1 7 9 .4

1 8 1 .2

1 8 2 .5

.7

4 .0

N o n m a n u f a c tu r in g .............................................................................

161.1

1 6 2 .0

1 6 2 .5

1 6 4 .9

1 6 6 .4

168.1

1 6 9 .0

1 7 0 .9

1 7 2 .5

.9

3 .7

W h ite -c o lla r w o r k e r s ......................................................................

164.1

1 6 4 .8

1 6 5 .3

1 6 8 .0

1 6 9 .3

1 7 1 .2

172.1

174.1

1 7 5 .7

.9

3 .8

E x clu d in g s a l e s o c c u p a t i o n s ................................................

1 6 5 .7

1 6 6 .6

167.1

1 7 0 .0

1 7 1 .4

1 7 3 .2

1 7 4 .2

1 7 6 .2

1 7 7 .7

.9

3 .7

B lu e -c o lla r o c c u p a t i o n s ................................................................

1 5 4 .0

1 5 5 .4

1 5 5 .9

1 5 7 .5

1 5 9 .7

161.1

1 6 1 .7

1 6 3 .4

1 6 5 .5

1 .3

3 .6

S e r v ic e o c c u p a t i o n s ......................................................................

1 5 6 .9

1 5 8 .4

1 5 9 .2

161.1

1 6 2 .0

1 6 3 .2

1 6 2 .4

1 6 6 .0

1 6 7 .3

.8

3 .3

State and local government workers..............................

1 5 6 .7

160.1

1 6 1 .5

1 6 2 .6

1 6 3 .2

1 6 5 .9

1 6 6 .8

1 6 8 .0

1 6 8 .7

.4

3 .4

W h ite -c o lla r w o r k e r s ..............................................................................

1 5 5 .7

1 5 9 .3

1 6 0 .7

1 6 1 .7

1 6 2 .2

1 6 4 .9

1 6 5 .7

1 6 6 .8

1 6 7 .5

.4

3 .3

P ro fe s s io n a l s p e c ia lty a n d te c h n ic a l..........................................

154.1

158.1

1 5 9 .4

1 6 0 .2

1 6 0 .8

1 6 3 .4

164.1

165.1

1 6 5 .6

.3

3 .0

W o rk e rs , b y o c c u p a tio n a l g ro u p :

E x e c u tiv e , a d m in is tr a tiv e , a n d m a n a g e r i a l ..............................

1 5 9 .6

1 6 2 .3

1 6 3 .8

1 6 5 .3

1 6 5 .7

1 6 8 .0

169.1

170.1

1 7 1 .0

.5

3 .2

A d m in istra tiv e s u p p o r t, in c lu d in g c le ric a l.................................

1 5 8 .0

1 6 1 .0

1 6 2 .4

1 6 3 .8

1 6 4 .4

1 6 7 .9

1 6 8 .5

1 7 0 .4

1 7 1 .8

.8

4 .5

B lu e -c o lla r w o r k e r s ................................................................................

1 5 4 .7

1 5 8 .4

1 5 9 .8

1 6 1 .3

1 6 1 .7

1 6 3 .6

1 6 5 .2

1 6 6 .7

1 6 7 .5

.5

3 .6

S e r v i c e s .....................................................................................................

1 5 5 .9

1 5 9 .7

1 6 0 .9

1 6 1 .8

1 6 2 .3

1 6 4 .9

1 6 5 .7

1 6 6 .5

1 6 6 .8

.2

2 .8

S e r v i c e s e x c lu d in g s c h o o l s 5 .........................................................

1 5 8 .7

1 6 1 .0

1 6 2 .8

1 6 4 .0

1 6 4 .2

1 6 6 .8

1 6 8 .2

1 6 9 .4

170.1

.4

3 .6

H e a lth s e r v ic e s .................................................................................

1 6 1 .4

1 6 3 .5

1 6 5 .5

1 6 6 .4

1 6 6 .7

1 6 9 .5

1 7 1 .0

1 7 2 .2

1 7 2 .9

.4

3 .7

W o r k e rs , b y in d u s try division:

H o s p ita ls .........................................................................................

1 6 1 .8

164.1

1 6 6 .2

1 6 7 .0

1 6 7 .3

1 7 0 .3

1 7 1 .4

1 7 2 .4

1 7 3 .2

.5

3 .5

E d u c a tio n a l s e r v ic e s ....................................................................

155.1

1 5 9 .2

1 6 0 .3

161.1

1 6 1 .7

1 6 4 .3

1 6 5 .0

1 6 5 .7

1 6 5 .9

.1

2 .6

S c h o o l s ...........................................................................................

1 5 5 .4

1 5 9 .6

1 6 0 .7

1 6 1 .4

1 6 2 .0

1 6 4 .7

1 6 5 .3

1 6 6 .0

1 6 6 .3

.2

2 .7

E le m e n ta ry a n d s e c o n d a r y .................................................

1 5 3 .6

1 5 7 .7

1 5 8 .8

1 5 9 .4

1 6 0 .0

1 6 3 .0

1 6 3 .7

1 6 4 .4

1 6 4 .6

.1

2 .9

C o lle g e s a n d u n iv e r s itie s .....................................................

1 6 0 .4

1 6 4 .7

1 6 5 .8

1 6 7 .0

1 6 7 .5

1 6 9 .2

1 7 0 .0

1 7 0 .7

1 7 1 .0

.2

2.1

P u b lic a d m in is tr a tio n 3 ..........................................................................

1 5 7 .9

1 6 0 .2

1 6 1 .7

1 6 3 .4

1 6 4 .3

1 6 7 .3

168.1

170.1

1 7 1 .4

.8

4 .3

1 C o s t ( c e n t s p e r h o u r w o rk e d ) m e a s u r e d in th e E m p lo y m e n t C o s t In d e x c o n s i s t s of
w a g e s , s a l a r i e s , a n d e m p lo y e r c o s t of e m p lo y e e b e n e fits .
2 C o n s is t s o f p riv a te in d u s try w o r k e r s (e x c lu d in g fa rm a n d h o u s e h o ld w o rk e rs ) a n d
S t a t e a n d lo ca l g o v e r n m e n t (e x c lu d in g F e d e r a l G o v e rn m e n t) w o r k e rs .


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

3 C o n s is ts of le g is la tiv e , ju d icial, a d m in is tr a tiv e , a n d re g u la to ry a c tiv itie s .
4 T h is s e r i e s h a s t h e s a m e in d u s try a n d o c c u p a tio n a l c o v e r a g e a s th e H ourly
E a r n in g s in d e x , w h ich w a s d is c o n tin u e d in J a n u a r y 1 9 8 9 .
5 In c lu d e s , for e x a m p le , library, s o c ia l, a n d h e a lth s e r v ic e s .

Monthly Labor Review

September 2004

103

Current Labor Statistics: Compensation & Industrial Relations

31.

Employment Cost Index, wages and salaries, by occupation and industry group

[June 1989 = 100]
2002

2003

2004

P ercent change

Series
June

Sept.

Dec.

Mar.

June

Sept.

Dec.

Mar.

June

3 m onths

12 m onths

ended

ended

June 2004
C iv ilia n w o r k e r s 1....................................................................

156.1

1 5 7 .2

1 5 7 .8

1 5 9 .3

1 6 0 .3

1 6 1 .8

1 6 2 .3

1 6 3 .3

1 6 4 .3

0 .6

2 .5

W o r k e rs , b y o c c u p a tio n a l g ro u p :
W h ite -c o lla r w o r k e r s ..............................................................

1 5 8 .4

1 5 9 .6

160.1

1 6 1 .9

1 6 2 .9

1 6 4 .5

165.1

166.1

167.1

P ro fe s s io n a l s p e c ia lty a n d t e c h n ic a l..........................................

1 5 6 .2

1 5 8 .0

1 5 8 .6

1 5 9 .3

160.1

1 6 1 .8

1 6 2 .5

1 6 3 .8

1 6 4 .4

.6
.4

2 .7

2 .6

E x e c u tiv e , a d m in itra tiv e , a n d m a n a g e r i a l ...............................

1 6 2 .6

1 6 3 .5

1 6 3 .8

1 6 7 .9

1 6 9 .0

1 7 0 .5

1 7 1 .2

1 7 1 .4

1 7 2 .4

.6

2 .0

A d m in istra tiv e s u p p o rt, in clu d in g c le ric a l.................................

1 5 8 .4

1 5 9 .6

1 6 0 .6

1 6 1 .8

163.1

1 6 4 .3

1 6 4 .9

1 6 6 .3

1 6 7 .5

.7

2 .7

B lu e -c o lla r w o r k e r s ................................................................................

1 5 1 .0

1 5 1 .9

1 5 2 .6

1 5 3 .8

1 5 4 .8

1 5 5 .8

1 5 6 .3

1 5 7 .3

1 5 8 .4

.7

2 .3

S e r v ic e o c c u p a t i o n s ..............................................................................

155.1

5 6 .2

1 5 6 .9

1 5 8 .0

1 5 8 .7

1 5 9 .8

1 6 0 .6

1 6 1 .2

1 6 1 .9

.4

2 .0

W o r k e rs , b y in d u s try division:
G o o d s - p r o d u c in g ...................................................................................
M a n u f a c tu rin g ........................................................................................
S e rv ic e - p r o d u c in g ..................................................................................
S e r v i c e s ...................................................................................................
H e a lth s e r v ic e s ...................................................................................

153.1

1 5 3 .9

155.1

1 5 6 .3

1 5 7 .5

1 5 8 .3

1 6 0 .6

1 5 9 .9

1 6 1 .0

.7

2 .2

1 5 4 .5

1 5 5 .4

1 5 6 .5

1 5 8 .0

1 5 9 .0

1 5 9 .7

160.1

1 6 1 .3

1 6 2 .4

.7

2.1

1 5 7 .2

1 5 6 .4

1 5 8 .8

1 6 0 .5

1 6 1 .4

1 6 3 .0

1 6 3 .6

1 6 4 .6

1 6 5 .5

.5

2 .5

1 5 8 .8

1 6 0 .7

161.1

1 6 1 .9

1 6 2 .8

1 6 4 .7

1 6 5 .4

1 6 6 .5

1 6 7 .4

.5

2 .8

1 5 8 .5

1 5 9 .6

1 6 0 .9

1 6 2 .0

1 6 3 .2

1 6 4 .7

1 6 5 .9

1 6 7 .7

1 6 8 .6

.5

3 .3

1 5 8 .6

1 6 0 .3

1 6 2 .2

1 6 3 .5

1 6 4 .4

1 6 6 .3

1 6 7 .7

1 6 9 .0

1 6 9 .9

.5

3 .3

1 5 5 .6

1 5 9 .3

160.1

1 6 0 .4

1 6 0 .7

1 6 2 .7

1 6 3 .2

1 6 3 .6

1 6 3 .8

.1

1 .9

P u b lic a d m in is tr a tio n 2 ..........................................................................

1 5 3 .4

1 5 4 .8

1 5 5 .8

1 5 7 .2

1 5 8 .0

1 5 9 .4

1 6 0 .0

161.1

1 6 1 .4

.2

2 .2
2 .6

H o s p ita ls ..............................................................................................
E d u c a tio n a l s e r v ic e s .......................................................................

N o n m a n u f a c tu r in g ..................................................................................

1 5 6 .4

1 5 7 .5

1 5 8 .0

1 5 9 .6

1 6 0 .5

162.1

1 6 2 .7

1 6 3 .7

1 6 4 .6

.5

P r i v a t e i n d u s t r y w o r k e r s .....................................................................

1 5 6 .3

1 5 7 .0

1 5 7 .5

1 5 9 .3

1 6 0 .4

1 6 1 .7

1 6 2 .3

1 6 3 .4

1 6 4 .5

.7

2 .6

E x c lu d in g s a l e s o c c u p a t i o n s ........................................................

156.1

1 5 7 .0

1 5 7 .9

1 5 9 .4

1 6 0 .5

1 6 1 .7

1 6 2 .4

1 6 3 .5

1 6 4 .5

.6

2 .5

W h ite -c o lla r w o r k e r s ...........................................................................

1 5 9 .4

1 6 0 .0

1 6 0 .4

1 6 2 .6

1 6 3 .8

1 6 5 .3

1 6 5 .9

167.1

1 6 8 .2

.7

2 .7

E x c lu d in g s a l e s o c c u p a t i o n s .....................................................

1 6 0 .0

1 6 9 .8

1 6 0 .8

1 6 3 .6

1 6 4 .8

1 6 6 .2

1 6 7 .0

168.1

1 6 9 .2

.7

2 .7

P ro fe s s io n a l s p e c ia lty a n d te c h n ic a l o c c u p a t i o n s .............

1 5 7 .4

1 5 8 .2

1 5 8 .5

1 5 9 .5

1 6 0 .5

162.1

1 6 3 .0

1 6 4 .7

1 6 5 .5

.5

3.1

E x e c u tiv e , a d m in itra tiv e , a n d m a n a g e ria l o c c u p a tio n s ..

1 6 3 .6

1 6 4 .3

1 6 4 .5

169.1

1 7 0 .3

1 7 1 .8

1 7 2 .5

1 7 2 .7

1 7 3 .9

.7

2.1

W o r k e rs , b y o c c u p a tio n a l g ro u p :

S a l e s o c c u p a t i o n s .............................................................................

1 5 7 .0

1 5 6 .9

1 5 6 .8

158.1

1 5 9 .3

1 6 1 .6

161.1

1 6 2 .6

1 6 3 .9

.8

2 .9

A d m in istra tiv e s u p p o r t o c c u p a tio n s , in c lu d in g c le ric a l...
B lu e -c o lla r w o r k e r s .............................................................................

1 5 9 .2

1 6 0 .3

1 6 1 .3

1 6 2 .6

1 6 4 .0

165.1

1 6 5 .7

1 6 7 .2

1 6 8 .6

.8

2 .8

1 5 0 .9

1 5 1 .7

1 5 2 .4

1 5 7 .2

1 5 8 .3

.7

2 .4

1 5 1 .8

1 5 2 .3

1 5 4 .6
1 5 4 .7

156.1

1 5 1 .0

1 5 3 .6
1 5 3 .4

1 5 5 .6

P re c is io n p ro d u c tio n , c ra ft, a n d re p a ir o c c u p a t i o n s ........

1 5 5 .5

1 5 6 .2

157.1

1 5 8 .3

.8

2 .3

M a c h in e o p e r a t o r s , a s s e m b l e r s , a n d in s p e c t o r s ...............

1 5 1 .6

1 5 2 .0

1 5 3 .2

1 5 4 .7

1 5 5 .3

1 5 6 .8

1 5 6 .9

1 5 8 .6

1 5 9 .8

.8

2 .9

T r a n s p o r ta tio n a n d m a te ria l m o v in g o c c u p a t i o n s .............

1 4 5 .2

1 4 6 .3

1 4 6 .9

1 4 7 .8

1 4 9 .0

1 4 9 .8

1 4 9 .8

1 5 0 .4

1 5 1 .8

.9

1 .9

H a n d le rs , e q u ip m e n t c l e a n e r s , h e lp e r s , a n d la b o re rs ....

155.1

1 5 6 .0

1 5 7 .2

1 5 8 .4

1 5 9 .0

1 5 9 .9

1 6 0 .6

1 6 1 .8

1 6 2 .7

.6

2 .3

S e r v ic e o c c u p a t i o n s ............................................................................

1 5 2 .8

1 5 3 .9

1 5 4 .4

1 5 5 .5

156.1

157.1

1 5 7 .8

1 5 8 .4

1 5 9 .3

.6

2 .0

P ro d u c tio n a n d n o n s u p e r v is o r y o c c u p a t i o n s 3 .....................

1 5 4 .0

1 5 4 .7

1 5 5 .2

1 5 6 .4

1 5 7 .4

1 5 8 .8

1 5 9 .4

1 6 0 .7

1 6 1 .7

.6

2 .7

1 5 6 .3
1 5 5 .4

1 5 7 .4

1 5 8 .3

1 5 8 .7

1 5 9 .9

1 6 0 .9

.6

2 .2

1 5 6 .5

1 5 7 .4

1 5 8 .0

1 5 9 .2

1 6 0 .2

.6

2 .4

W o r k e rs , b y in d u s try div isio n :
G o o d s - p r o d u c in g ..................................................................................

153.1

1 5 3 .9

1 5 5 .0

E x c lu d in g s a l e s o c c u p a t i o n s .................................................

1 5 2 .2

1 5 3 .0

1 5 4 .0

W h ite -c o lla r o c c u p a t i o n s .............................................................

1 5 6 .6

1 5 7 .9

1 5 8 .6

1 6 0 .0

1 6 1 .4

1 6 1 .9

162.1

1 6 3 .2

1 6 4 .5

.8

1 .9

E x c lu d in g s a l e s o c c u p a t i o n s .................................................

1 5 4 .5

1 5 5 .4

1 5 6 .3

1 5 8 .0

1 5 9 .2

1 5 9 .9

1 6 0 .4

1 6 1 .5

1 6 2 .7

.7

2 .2

B lu e -c o lla r o c c u p a t i o n s ...............................................................

1 5 0 .7

1 5 1 .5

1 5 2 .6

1 5 3 .8

1 5 4 .8

1 5 5 .9

1 5 6 .4

1 5 7 .7

1 5 8 .6

.6

2 .5

C o n s tr u c tio n .........................................................................................

1 4 8 .2

1 4 9 .0

1 5 0 .2

1 5 0 .6

1 5 2 .4

155.1

2 .3

1 5 5 .4

1 5 6 .5

1 5 8 .0

1 5 9 .0

160.1

1 6 1 .3

1 5 5 .9
1 6 2 .4

.5

1 5 4 .4

1 5 3 .6
1 5 9 .7

1 5 4 .0

M a n u f a c tu rin g .....................................................................................

.7

2.1

W h ite -c o lla r o c c u p a t i o n s .............................................................

1 5 6 .6

1 5 7 .7

1 5 8 .6

160.1

1 6 1 .6

1 6 2 .0

162.1

1 6 3 .3

1 6 4 .7

.9

1 .9

E x c lu d in g s a l e s o c c u p a t i o n s .................................................

1 5 3 .9

1 5 5 .0

1 5 5 .9

1 5 7 .7

1 5 8 .9

1 5 9 .5

1 6 0 .0

1 6 1 .2

1 6 2 .5

.8

2 .3

B lu e -c o lla r o c c u p a t i o n s ................................................................

1 5 2 .8

1 5 3 .5

1 5 4 .7

1 5 6 .3

1 5 6 .9

1 5 7 .9

1 5 8 .5

1 5 9 .8

1 6 0 .6

.5

2 .4

D u r a b l e s .................................................................................................

1 5 5 .3

1 5 6 .0

1 5 7 .3

1 5 8 .8

1 5 9 .7

1 6 0 .6

1 6 0 .9

1 6 1 .9

1 6 2 .9

.6

2 .0

N o n d u r a b l e s .........................................................................................

153.4

1 5 4 .4

1 5 5 .2

1 5 6 .6

1 5 7 .8

1 5 8 .3

1 5 8 .7

1 6 0 .4

1 6 1 .6

.7

2 .4

S e r v ic e - p r o d u c in g ..................................................................................

1 5 7 .7

1 5 8 .4

1 5 8 .6

1 6 0 .6

1 6 1 .7

1 6 3 .3

1 6 3 .9

1 6 5 .0

166.1

.7

2 .7
2 .6

E x clu d in g s a l e s o c c u p a t i o n s .................................................

1 5 8 .5

1 5 9 .3

1 5 9 .6

1 6 1 .7

1 6 2 .8

1 6 5 .0

1 6 6 .0

167.1

.7

W h ite -c o lla r o c c u p a t i o n s .............................................................

1 5 9 .9

1 6 0 .5

1 6 0 .7

1 6 3 .0

164.1

1 6 6 .0

1 6 6 .6

1 6 2 .5

1 6 2 .8

1 6 5 .3

1 6 6 .5

1 6 8 .2

1 6 9 .0

1 6 8 .9
1 7 1 .2

2 .9

1 6 1 .6

1 6 7 .8
1 7 0 .2

.7

E x clu d in g s a l e s o c c u p a t i o n s .................................................

.6

2 .8

B lu e -c o lla r o c c u p a t i o n s ................................................................

151.1

1 5 1 .8

1 5 2 .0

1 5 3 .2

1 5 4 .3

155.1

1 5 5 .4

1 5 6 .2

1 5 7 .8

1 .0

2 .3

S e r v ic e o c c u p a t i o n s .......................................................................

1 5 2 .4

1 5 3 .5

154.1

155.1

1 5 5 .6

1 5 6 .6

1 5 7 .4

1 5 8 .0

1 5 8 .8

.5

2.1

T r a n s p o r ta tio n a n d p u b lic u tilities..............................................

152.1

1 5 3 .4

154.1

1 5 4 .8

1 5 5 .6

1 5 6 .0

1 5 6 .5

1 5 7 .6

159.1

1 .0

2 .2

T r a n s p o r t a t i o n ...................................................................................

1 4 8 .6

1 4 9 .6

150.1

1 5 0 .5

1 5 0 .6

1 5 0 .4

1 5 0 .8

1 5 1 .7

1 5 3 .4

1.1

1 .9

P u b lic u tilities.....................................................................................

1 5 6 .4

1 5 8 .2

1 5 9 .3

1 6 0 .4

162.1

1 6 3 .4

164.1

1 6 5 .3

1 6 6 .4

.7

2 .7

C o m m u n ic a tio n s ..........................................................................

157.1

1 5 9 .6

1 6 0 .7

1 6 1 .9

1 6 3 .4

1 6 5 .4

1 6 5 .9

1 6 7 .0

1 6 7 .5

.3

2 .5

E lec tric, g a s , a n d s a n ita r y s e r v ic e s ...................................

1 5 5 .5

1 5 6 .5

1 5 7 .4

1 5 8 .6

1 6 0 .4

1 6 1 .0

1 6 1 .8

1 6 3 .3

165.1

1.1

2 .9

W h o le s a le a n d re ta il t r a d e ............................................................

1 5 5 .7

1 5 5 .5

1 5 6 .7
-

1 5 9 .2

1 5 9 .5

1 6 0 .3

1 6 1 .6

-

1 5 5 .5
-

1 5 7 .5

E x clu d in g s a l e s o c c u p a t i o n s ..................................................

-

-

.8
_

2 .6
_
1 .9

-

-

-

-

W h o le s a le t r a d e ...............................................................................

1 6 1 .3

1 6 0 .4

1 6 1 .0

1 6 3 .4

1 6 4 .7

1 6 4 .8

1 6 5 .3

1 6 6 .2

1 6 7 .8

1 .0

E x clu d in g s a l e s o c c u p a t i o n s ..................................................

1 6 1 .2

1 6 2 .6

1 6 3 .7

1 6 3 .9

1 6 5 .2

1 6 5 .7

1 6 6 .3

1 6 7 .8

1 6 7 .6

- 0 .1

1 .5

R etail t r a d e .........................................................................................

1 5 2 .7

1 5 2 .9

1 5 2 .7

153.1

1 5 3 .8

1 5 6 .3

1 5 6 .5

1 5 7 .3

1 5 8 .4

.7

3 .0

G e n e r a l m e r c h a n d i s e s t o r e s ...................................................

1 4 8 .9

150.1

1 4 9 .2

1 4 9 .8

1 5 2 .0

153.1

1 5 3 .6

154.1

1 5 4 .9

.5

1 .9

F o o d s t o r e s .....................................................................................

1 4 8 .9

150.1

1 5 0 .3

1 5 1 .0

1 5 1 .6

1 5 2 .2

1 5 2 .8

1 5 3 .8

1 5 4 .3

.3

1 .8

S e e f o o tn o te s a t e n d of ta b le .

104

1 6 4 .2

Monthly Labor Review


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

September 2004

31. Continued—Employment Cost Index, wages and salaries, by occupation and industry group
[June 1989 = 100]_______________________________________________________________________________
2002

2004

2003

P ercent change
3 m onths

12 m onths

ended

ended

Series
June

Sept.

Dec.

Mar.

June

Sept.

Dec.

Mar.

June

June 2004
1 .7

F in a n c e , i n s u r a n c e , a n d re a l e s t a t e .........................................

1 6 2 .0

1 6 2 .4

1 6 2 .6

171.1

1 7 2 .4

174.1

1 7 4 .5

1 7 5 .2

1 7 5 .3

0.1

E x c lu d in g s a l e s o c c u p a t i o n s .................................................

1 6 5 .7

166.1

1 6 7 .3

1 7 6 .7

1 7 8 .5

1 7 9 .2

2 1 0 .2

1 7 9 .2

1 8 0 .5

.7

1.1

B a n k in g , s a v i n g s a n d lo a n , a n d o th e r c r e d it a g e n c i e s .

1 8 2 .8

1 8 2 .7

1 8 3 .9

2 0 6 .4

2 0 8 .7

2 0 9 .1

1 6 4 .5

2 0 6 .7

2 0 7 .6

.4

- .5
2 .6

I n s u r a n c e .............................................................................................

1 5 8 .6

1 5 9 .6

159.1

1 6 1 .6

1 6 3 .0

1 6 3 .9

1 6 4 .5

165.1

1 6 7 .2

1 .3

S e r v i c e s ..................................................................................................

1 6 0 .3

1 6 1 .5

1 6 1 .7

1 6 2 .8

1 6 4 .0

1 6 5 .9

1 6 6 .7

168.1

1 6 9 .3

.7

3 .2

1 6 4 .0

1 6 4 .6

1 6 4 .8

1 6 5 .6

1 6 6 .4

169.1

1 6 9 .8

1 7 1 .0

1 7 2 .7

1 .0

3 .8
3 .4

H e a lth s e r v ic e s .................................................................................

1 5 8 .4

1 5 9 .9

1 6 0 .7

1 6 1 .9

1 6 3 .2

1 6 4 .6

1 3 5 .8

1 6 7 .8

1 6 8 .8

.6

H o s p ita ls ...........................................................................................

1 5 8 .6

1 6 0 .2

162.1

1 6 3 .6

1 6 4 .6

1 6 6 .5

1 6 7 .9

1 6 9 .4

1 7 0 .5

.6

3 .6

1 6 1 .2

1 6 5 .2

1 6 6 .5

167.1

1 6 7 .5

1 7 0 .3

1 7 1 .0

1 7 1 .9

1 7 2 .6

.4

2 .9

C o lle g e s a n d u n iv e r s itie s .........................................................

1 5 9 .9

163.1

1 6 4 .3

1 6 4 .4

165.1

1 6 7 .6

1 6 8 .4

1 6 9 .5

1 7 0 .0

.3

3 .0

N o n m a n u f a c tu r in g .............................................................................

1 5 6 .5

1 5 7 .2

1 5 7 .5

1 5 9 .4

1 6 0 .5

162.1

1 6 2 .6

1 6 3 .7

1 6 4 .8

.7

2 .7

W h ite -c o lla r w o r k e r s ......................................................................

1 5 9 .6

1 6 0 .2

1 6 0 .5

1 6 2 .8

1 6 3 .9

1 6 5 .7

1 6 6 .3

1 6 7 .5

1 6 8 .6

.7

2 .9

E x c lu d in g s a l e s o c c u p a t i o n s ................................................

1 6 1 .3

162.1

1 6 2 .5

1 6 4 .9

166.1

1 6 7 .7

1 6 8 .5

1 6 9 .7

1 7 0 .7

.6

2 .8

B lu e -c o lla r o c c u p a t i o n s ................................................................

1 4 9 .0

1 4 9 .8

1 5 0 .2

151.1

1 5 2 .4

1 5 3 .4

1 5 3 .8

1 5 4 .7

156.1

.9

2 .4

S e r v ic e o c c u p a t i o n s ......................................................................

1 5 2 .3

1 5 3 .4

1 5 4 .0

1 5 5 .0

1 5 5 .5

1 5 6 .5

1 5 7 .3

1 5 7 .9

1 5 8 .7

.5

2.1

State and local government workers..............................

1 5 6 .7

160.1

1 6 1 .5

1 6 2 .6

1 6 3 .2

1 6 5 .9

1 6 6 .8

1 6 8 .0

1 6 8 .7

.2

1 .9

W h ite -c o lla r w o r k e r s ..............................................................................

1 5 4 .4

1 5 7 .4

1 5 8 .4

1 5 8 .9

1 5 9 .2

1 6 1 .0

1 6 1 .5

162.1

1 6 2 .4

.2

2 .0

P ro fe s s io n a l s p e c ia lty a n d te c h n ic a l..........................................

154.1

1 5 7 .5

1 5 8 .4

1 5 8 .8

159.1

1 6 1 .0

1 6 1 .4

162.1

1 6 2 .3

.1

2 .0

E x e c u tiv e , a d m in is tr a tiv e , a n d m a n a g e r i a l ..............................

1 5 6 .8

1 5 9 .0

160.1

1 6 0 .9

1 6 1 .0

1 6 2 .5

1 6 3 .3

1 6 3 .5

1 6 3 .8

.2

1 .7

A d m in istra tiv e s u p p o rt, in clu d in g c le ric a l.................................

1 5 2 .8

155.1

1 5 6 .0

1 5 6 .9

1 5 7 .2

159.1

1 5 9 .5

1 6 0 .4

1 6 0 .8

.2

2 .3

152.1

1 5 4 .5

155.1

1 5 6 .2

1 5 6 .5

1 5 7 .6

1 5 8 .3

1 5 8 .9

1 5 9 .2

.2

1 .7

W o r k e rs , b y o c c u p a tio n a l g ro u p :

W o r k e rs , b y in d u s try div isio n :
S e r v i c e s ...................................................................................................

1 5 5 .0

1 5 8 .4

1 5 9 .2

1 5 9 .5

1 5 9 .8

1 6 1 .6

162.1

1 6 2 .6

1 6 2 .7

.1

1 .8

1 5 7 .3

159.1

1 6 0 .3

1 6 1 .4

1 6 1 .8

1 6 3 .2

1 6 4 .5

165.1

1 6 5 .6

.3

2 .3

4

S e r v i c e s e x c lu d in g s c h o o l s ..........................................................

1 5 8 .6

1 6 0 .5

1 6 2 .2

1 6 2 .9

1 6 3 .5

165.1

1 6 6 .7

1 6 7 .4

1 6 7 .8

.2

2 .6

H o s p ita ls .........................................................................................

1 5 8 .8

1 6 0 .6

1 6 2 .5

163.1

1 6 3 .8

1 6 5 .5

1 6 6 .7

1 6 7 .4

1 6 7 .9

.3

2 .5

1 5 4 .5

158.1

1 5 8 .9

159.1

1 5 9 .3

1 6 1 .2

1 6 1 .6

1 6 2 .0

162.1

.1

1 .8

S c h o o l s ............................................................................................

1 5 4 .6

1 5 8 .3

1 5 9 .0

1 5 9 .2

1 5 9 .5

1 6 1 .4

1 6 1 .8

162.1

1 6 2 .3

.1

1 .8
1 .9

H e a lth s e r v i c e s .................................................................................

E le m e n ta ry a n d s e c o n d a r y .................................................

1 5 3 .6

1 5 7 .4

158.1

1 5 8 .2

1 5 8 .5

1 6 0 .6

1 6 0 .9

1 6 1 .3

1 6 1 .5

.1

C o lle g e s a n d u n iv e r s itie s .....................................................

1 5 7 .3

1 6 0 .7

1 6 1 .6

162.1

162.1

1 6 3 .5

1 6 4 .0

1 6 4 .3

1 6 4 .4

.1

1 .4

P u b lic a d m in is tr a tio n ..........................................................................

1 5 3 .4

1 5 4 .8

1 5 5 .8

1 5 7 .2

1 5 8 .0

1 5 9 .4

1 6 0 .0

161.1

1 6 1 .4

.2

2 .2

’ C o n s is t s of p riv a te in d u s try w o r k e rs (e x c lu d in g fa rm a n d h o u s e h o ld w o rk e rs ) a n d
S ta t e a n d lo ca l g o v e r n m e n t (e x c lu d in g F e d e r a l G o v e rn m e n t) w o r k e rs .
2 C o n s is t s o f le g is la tiv e , ju d icial, a d m in is tr a tiv e , a n d r e g u la to ry a c tiv itie s .

32.

3 T h is s e r i e s h a s th e s a m e in d u s try a n d o c c u p a tio n a l c o v e r a g e a s t h e H ourly
E a r n in g s in d e x , w h ich w a s d is c o n tin u e d in J a n u a r y 1 9 8 9 .
4 In c lu d e s , for e x a m p le , library, s o c ia l, a n d h e a lth s e r v ic e s .

Employment Cost Index, benefits, private industry workers by occupation and industry group

[June 1989 = 100]
2004

2003

2002

P ercent change

Series
June

Sept.

Dec.

Mar.

June

Sept.

Dec.

Mar.

June

3 m onths

12 m onths

ended

ended

June 2004
1 7 9 .6

1 8 2 .0

1 8 4 .3

1 8 5 .8

1 9 2 .2

173.1

1 7 4 .6

176.1

1 7 7 .2

1 7 8 .5

1 8 3 .6

1 8 5 .5

1 8 7 .7

1 8 9 .2

1 9 4 .4

1 6 4 .0

1 6 6 .2

1 6 7 .8

1 7 2 .7

176.1

1 7 8 .4

1 7 9 .9

1 8 8 .3

1 7 1 .6

1 .6

7 .3

1 9 7 .4

1 .5

6 .4

1 9 1 .8

1 .9

8 .9

1 9 5 .3

W o r k e rs , b y o c c u p a tio n a l g ro u p :

W o r k e rs , by in d u s try division:

N o n m a n u f a c tu r in g .................................................................................


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Federal Reserve Bank of St. Louis

1 6 7 .4

1 6 8 .8

1 7 1 .0

1 7 8 .0

1 8 0 .2

1 8 2 .3

1 8 3 .8

1 9 3 .7

1 9 6 .2

1 .3

8 .9

1 7 3 .3

1 7 4 .9

1 7 5 .9

1 7 9 .9

1 8 2 .3

1 8 4 .7

1 8 6 .2

1 9 0 .6

194.1

1 .8

6 .5

1 8 2 .3
1 8 6 .7

1 9 4 .4

1 9 6 .9

1 .3

1 0 .0

1 9 0 .9

1 9 4 .3

1 .8

6 .3

1 6 5 .5

1 6 6 .8

1 6 8 .9

1 7 6 .9

1 7 9 .0

181.1

1 7 3 .5

1 7 5 .2

1 7 6 .3

1 8 0 .3

1 8 2 .8

185.1

Monthly Labor Review

September 2004

105

Current Labor Statistics: Compensation & Industrial Relations

33.

Employment Cost Index, private nonfarm workers by bargaining status, region, and area size

[June 1989 = 100]
2002

2003

2004

Percent change

Series
June

Sept.

Dec.

Mar.

June

Sept.

Dec.

Mar.

June

3 m onths

12 m onths

ended

ended

June 2004
C O M P E N S A T IO N
W o rk e rs, b y b a rg a in in g s t a t u s 1
U n io n ..............................................................

1 5 6 .3

158.1

1 5 9 .5

162.1

164.1

1 6 5 .7

1 6 6 .8

1 7 1 .4

1 7 3 .9

1 .5

G o o d s - p r o d u c in g .............................................................

6 .0

1 5 4 .7

1 5 6 .2

1 5 7 .8

1 6 1 .4

1 6 3 .4

1 6 4 .7

1 6 5 .9

1 7 2 .3

1 7 4 .6

1 .3

6 .9

S e rv ic e - p r o d u c in g ...........................................................

1 5 7 .6

1 5 9 .9

161.1

1 6 2 .6

1 6 4 .6

1 6 6 .5

1 6 7 .5

1 7 0 .2

1 7 2 .9

1 .6

M a n u f a c tu rin g .............................................................

5 .0

1 5 4 .6

1 5 5 .9

1 5 7 .9

1 6 2 .3

1 6 3 .8

1 6 5 .0

1 6 6 .3

1 7 5 .0

1 7 7 .0

1.1

8.1

N o n m a n u f a c tu r in g ....................................................

1 5 6 .6

1 5 8 .8

1 5 9 .9

1 6 1 .4

1 6 3 .7

1 6 5 .5

1 6 6 .5

1 6 8 .8

1 7 1 .6

1 .7

4 .8

N o n u n io n .............................................................................

1 6 1 .4

1 6 2 .5

1 6 2 .8

1 6 5 .4

1 6 6 .8

1 6 8 .4

169.1

1 7 1 .3

1 7 2 .7

.8

3 .5

.7

3 .6

G o o d s - p r o d u c in g .........................................................

1 5 8 .6

1 5 9 .5

1 6 0 .8

1 6 3 .6

1 6 4 .9

166.1

1 6 6 .7

1 6 9 .7

1 7 0 .9

S e rv ic e - p r o d u c in g ....................................................................

1 6 2 .2

1 6 2 .9

1 6 3 .3

1 6 5 .9

1 6 7 .2

1 6 9 .0

1 6 9 .8

1 7 1 .6

1 7 3 .2

M a n u f a c tu rin g ..................................................................

159.1

160.1

1 6 1 .3

1 6 4 .5

1 6 5 .8

1 6 6 .9

1 6 7 .3

1 7 0 .6

1 7 2 .0

N o n m a n u f a c tu r in g ....................................................................

161 7

1 6 2 .4

1 6 2 .9

1 6 5 .4

1 6 6 .7

1 6 8 .5

1 3 9 .3

.9

3 .6

.8

3 .7

.9

3 .5

W o rk e rs , b y r e g io n 1
N o r th e a s t ..........................................................................

1 5 9 .9

1 6 0 .5

1 6 1 .3

1 6 3 .8

1 6 5 .2

1 6 6 .9

1 6 7 .9

1 7 0 .2

1 7 2 .3

1.2

S o u th .........................................................................

4 .3

1 5 7 .6

1 5 8 .9

1 5 9 .0

1 6 0 .6

1 6 1 .6

1 6 3 .2

1 6 3 .9

1 6 6 .4

1 6 7 .9

.9

M id w e st (fo rm erly N o rth C e n tr a l) ...................................................

3 .9

1 6 2 .2

1 6 3 .5

1 6 4 .6

1 6 9 .0

1 7 0 .4

1 7 1 .7

1 7 2 .5

1 7 4 .7

1 7 6 .2

.9

W e s t .............................................................................

3 .4

1 6 2 .9

1 6 3 .8

1 6 5 .0

1 6 7 .3

1 6 9 .5

1 7 1 .4

1 7 2 .2

1 7 5 .3

1 7 6 .8

.9

4 .3

M e tro p o lita n a r e a s .........................................................

1 6 0 .9

1 6 1 .8

1 6 2 .5

1 6 5 .2

1 6 6 .6

1 6 8 .3

169.1

1 7 1 .5

173.1

O th e r a r e a s ...................................................................................

1 5 8 .5

1 6 0 .0

1 6 9 .8

1 6 3 .5

1 6 5 .0

166.1

1 6 6 .9

1 7 0 .2

172.1

.9
1.1

4 .3

W o rk e rs, b y a r e a s iz e 1
3 .9

W A G E S A N D S A L A R IE S
W o rk e rs, b y b a rg a in in g s t a t u s 1
U n io n ............................................................................

1 4 9 .8

1 5 1 .3

1 5 2 .5

1 5 3 .3

1 5 4 .3

1 5 5 .3

1 5 6 .2

1 5 7 .2

1 5 8 .7

1 .0

2 .9

G o o d s - p r o d u c in g .................................................................

1 5 8 .6

1 5 0 .0

1 5 1 .2

1 5 2 .4

1 5 3 .9

1 5 4 .8

1 5 5 .4

1 5 6 .3

1 5 7 .5

.8

2 .3

S e rv ic e - p r o d u c in g .......................................................................

1 5 1 .4

1 5 2 .9

154.1

1 5 4 .6

155.1

1 5 6 .3

1 5 7 .3

1 5 8 .5

1 6 0 .3

1.1

3 .4

M a n u f a c tu rin g .................................................................

1 5 0 .2

1 5 1 .6

153.1

1 5 4 .6

1 5 5 .9

1 5 6 .7

157.1

158.1

1 5 9 .2

.7

2.1

N o n m a n u f a c tu r in g ................................................................

1 4 9 .6

151.1

152.1

1 5 2 .5

1 5 3 .5

1 5 4 .6

1 5 5 .6

1 5 6 .6

1 5 8 .4

1.1

3 .2

N o n u n io n .............................................................................

1 5 7 .5

158.1

1 5 8 .5

1 6 0 .4

1 6 1 .5

1 6 3 .0

1 6 3 .4

1 6 4 .6

1 6 5 .6

.6

2 .5

G o o d s - p r o d u c in g ......................................................................

1 5 4 .8

1 5 5 .5

1 5 6 .6

1 5 7 .8

1 5 8 .9

1 5 9 .7

160.1

1 6 1 .4

1 6 2 .4

.6

2 .2

S e rv ic e - p r o d u c in g .............................................................

1 5 8 .3

1 5 8 .9

1 5 9 .0

1 6 1 .2

1 6 2 .3

1 6 4 .0

1 6 4 .5

1 6 5 .6

.6

1 5 9 .3
1 6 0 .4

1 6 0 .2

1 6 0 .9

1 6 2 .6

.7

2 .2

1 6 1 .5

163.1

1 6 1 .3
1 6 3 .7

1 6 6 .6
1 6 3 .7

1 6 4 .7

1 6 5 .7

.6

2 .6

M a n u f a c tu rin g ..............................................................................

156.1

1 5 6 .8

1 5 7 .8

N o n m a n u f a c tu r in g ...........................................................................

1 5 7 .5

158.1

1 5 8 .3

2 .6

W o rk e rs , b y re g io n 1
N o r th e a s t ............................................................................................

1 5 4 .9

155.1

1 5 5 .7

1 5 7 .3

1 5 8 .4

1 6 0 .0

1 6 0 .9

1 6 2 .0

1 6 3 .6

1 .0

3 .3

S o u th ..............................................................................................

1 5 3 .6

1 5 4 .7

1 5 4 .6

1 5 5 .3

156.1

1 5 7 .4

1 5 7 .9

159.1

160.1

.6

2 .6

M id w e st (fo rm erly N orth C e n tr a l) ................................................

1 5 8 .5

1 5 9 .2

1 6 0 .2

164.1

1 6 5 .0

166.1

1 6 6 .5

1 6 6 .9

1 6 7 .7

.5

1 .6

W e s t .................................................................................

1 5 8 .7

1 5 9 .3

160.1

1 6 1 .3

163.1

1 6 4 .7

1 6 5 .2

1 6 6 .8

1 6 7 .9

.7

2 .9

W o rk e rs, b y a r e a s iz e 1
M e tro p o lita n a r e a s ......................................................................................

1 5 6 .7

1 5 7 .4

1 5 7 .9

1 5 9 .6

1 6 0 .7

1 6 2 .2

1 6 2 .7

1 6 3 .8

1 6 4 .9

.7

2 .6

O th e r a r e a s .................................................................................................

1 5 2 .6

1 5 3 .8

1 5 4 .8

1 5 6 .8

1 5 8 .0

1 5 8 .9

1 5 9 .5

1 6 0 .8

162.1

.8

2 .6

T h e i n d e x e s a r e c a lc u la te d d iffe ren tly fro m t h o s e for t h e o c c u p a tio n a n d in d u s try g r o u p s . F o r a d e ta ile d d e s c rip tio n o f t h e in d e x c a lc u la tio n , s e e t h e M o n th ly L a b o r R e v ie w
T e c h n ic a l N o te , " E s tim a tio n p r o c e d u r e s for t h e E m p lo y m e n t C o s t In d ex ," M ay 1 9 8 2 .

106

Monthly Labor Review


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

September 2004

34. Percent of full-time employees participating in employer-provided benefit plans, and in selected features within plans,
medium and large private establishments, selected years, 1980-97______________________________________________
Ite m

1982

1980

1984

1988

1986

1989

1991

1993

1997

1995

2 1 ,3 5 2

2 1 ,0 4 3

2 1 ,0 1 3

2 1 ,3 0 3

3 1 ,0 5 9

3 2 ,4 2 8

3 1 ,1 6 3

2 8 ,7 2 8

3 3 ,3 7 4

2 0 ,711

2 0 ,3 8 3
2 0 ,1 7 2
17,231

2 0 ,2 3 8
20,451
1 6,190

2 7 ,9 5 3
2 8 ,5 7 4
1 9 ,5 6 7

2 9 ,8 3 4
3 0 ,4 8 2
2 0 ,4 3 0

2 5 ,8 6 5
2 9 ,2 9 3
1 8 ,3 8 6

2 3 ,5 1 9
2 6 ,1 7 5
1 6 ,0 1 5

2 5 ,5 4 6
2 9 ,0 7 8
1 7 ,4 1 7

2 9 ,3 4 0

2 0 ,4 9 8
1 7 ,9 3 6

2 0 ,4 1 2
20,201
1 7 ,6 7 6

10
-

9
25

9
26

10
27

11
29

10
26

8
30

9
29

76

72

71

67

68

26

26

26

28

26

P aid fu n e ral le a v e .................................................................

-

25
-

73
26
-

72

A v e ra g e m in u te s p e r d a y .................................................

75
-

88

85

84

80

83

80

A v e ra g e d a y s p e r o c c u r r e n c e ........................................

-

-

-

3 .2

3 .2

3 .3

81
3 .7

99

99

99

99

96

3 .3
92

3 .0

P aid h o lid a y s ............................................................................
A v e ra g e d a y s p e r y e a r .....................................................

3 .3
97

91

89

89

10.1

10.0

9 .8

10.0

9 .4

9 .2

10.2

9 .4

9.1

9 .3

23
3.6

25
3 .7

24

22

21

21

22

20

3 .3

3.1

3 .3

3.1

3 .3

3 .5

S c o p e of s u rv e y (in 0 0 0 's ) .....................................................
N u m b er of e m p lo y e e s (in 0 0 0 's):
W ith m ed ica l c a r e ................................................................
W ith life in s u ra n c e ...............................................................
W ith d e fin e d b en e fit p la n ..................................................

3 8 ,4 0 9

3 3 ,4 9 5
19 ,2 0 2

Time-off plans
P a rtic ip a n ts with:
P aid lunch tim e .......................................................................
A v e ra g e m in u te s p e r d a y .................................................
P aid re s t tim e ..........................................................................

P aid p e rs o n a l le a v e ..............................................................
A v e ra g e d a y s p e r y e a r .....................................................

20

24

-

3.8

P aid v a c a tio n s .........................................................................

100

99

99

100

98

97

96

97

96

95

P aid s ick l e a v e 1.....................................................................
U npaid m atern ity le a v e .......................................................
U npaid p a te rn ity le a v e ........................................................

62
-

67
-

67
-

70
-

69
33
16

68
37

67
37

58

56

18

26

65
60
53

U npaid fam ily l e a v e .............................................................

-

-

-

_

-

-

_

_

84

93

97

97

97

95

90

92

83

82

77

76

-

-

66

76

75

81

85

62

70
18

79
28

80
28

80
30

86
82
42

78

58

46
62
8

73
56

78
63

26
-

27
-

36
$ 1 1 .9 3

43
$ 1 2 .8 0

51
$ 2 6 .6 0

61
$ 3 1 .5 5

67
$ 3 3 .9 2

69
$ 3 9 .1 4

46

51

Insurance plans
P a rtic ip a n ts in m ed ica l c a r e p la n s .....................................
P e rc e n t of p a rtic ip a n ts with c o v e ra g e for:
H om e h e a lth c a r e ................................................................

P e rc e n t of p a rtic ip a n ts with e m p lo y e e
co n trib u tio n re q u ire d for:
S elf c o v e r a g e .......................................................................
A v e ra g e m onthly c o n trib u tio n ......................................

58

63

$ 7 2 .1 0

76
$ 1 0 7 .4 2

80

$ 6 0 .0 7

69
$ 9 6 .9 7

78

$ 4 1 .4 0

$ 1 1 8 .3 3

$ 1 3 0 .0 7

96

96

96

92

94

94

91

87

87

69

72

74

72

42

71
6
44

76
5
41

74
6

64

78
8
49

77
7

64

10
59

71
7

-

37

33

40

43

47

48

42

45

40

41

42

43

54

51

51

49

46

43

45

44
53

55

96

R etire e p ro tec tio n a v a ila b le ..............................................
P a rtic ip a n ts in long-term disability

47
$25.31

$ 3 5 .9 3

A v e ra g e m ontniy c o n trio u tio n ......................................

P e rc e n t of p a rtic ip a n ts with:
A ccidental d e a th a n d d is m e m b e rm e n t
in s u ra n c e ...............................................................................

44
$ 1 9 .2 9
64

66

P a rtic ip a n ts in s ic k n e s s a n d a c c id e n t
P a rtic ip a n ts in s h o rt-term disability p la n s ' ....................

Retirement plans
P a rtic ip a n ts in d efin e d benefit p en s io n p la n s ..............
P e rc e n t of p a rtic ip a n ts with:
N orm al re tire m e n t prior to a g e 6 5 ................................
Early re tire m e n t a v a ila b le ...............................................
Ad h o c p e n s io n in c re a s e in last 5 y e a r s ...................
T erm inal e a rn in g s fo rm u la ..............................................
B enefit c o o rd in a te d with S o cial S e c u rity ....................
P a rtic ip a n ts in d efin e d contribution p la n s .......................
P a rtic ip a n ts in p la n s with ta x -d e fe rre d s a v in g s
a r r a n g e m e n ts ........................................................................

84

84

82

76

63

63

59

56

52

50

55
98
-

58
97
-

63
97

64

62
97

53
45

52
45

56

98
35
57
62

59
98
26
55
62

63

55
98
7
56
54

52
95
6
61
48

52
96
4
58
51

52
95
10
56
49

-

-

-

60

45

48

48

49

55

57

-

-

-

33

36

41

44

43

54

55

47
54

22
64

Other benefits
E m p lo y e e s eligible for:
2

5

9

10

12

12

13

5

12

23

36

52

38
5

32
7

P rem ium c o n v e rs io n p la n s ...............................................
T h e definitions for p aid sick le a v e a n d sh o rt-term disability (previously s ic k n e s s an d
a c c id e n t in s u ra n c e ) w e re c h a n g e d for th e 1 9 9 5 su rv e y . P aid sick le a v e now in c lu d e s only

Prior to 1995, re im b u rse m e n t a c c o u n ts in clu d ed prem ium co n v e rs io n p la n s , w hich

p la n s th a t sp ec ify e ith e r a m axim um n u m b e r of d a y s p e r y e a r o r unlim ited d a y s . S h o rt-

specifically allow m edical plan p a rtic ip a n ts to p a y re q u ire d p lan p re m iu m s with p re ta x

te rm s disability now in c lu d e s all in s u re d , self-in su red , a n d S ta te -m a n d a te d p la n s a v a ila b le

d o llars.

on a per-disability b a s is , a s well a s t h e u n fu n d e d per-disability p la n s previously re p o rte d a s

ta b u la te d s e p a ra te ly .

Also, re im b u rse m e n t a c c o u n ts th a t w e re p art of flexible benefit p la n s w e re

s ick le a v e . S ic k n e s s a n d a c c id e n t in s u ra n c e , re p o rte d in y e a rs prior to th is su rv e y , included
only in s u re d , s elf-in su red , a n d S ta te -m a n d a te d p la n s providing per-disability b e n e -


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Monthly Labor Review

September 2004

107

Current Labor Statistics: Compensation & Industrial Relations

35. Percent of full-time employees participating in employer-provided benefit plans, and in selected features
within plans, small private establishments and State and local governments, 1987, 1990,1992, 1994, and 1996
Small private establishments

Item
1990
S c o p e of su rv e y (in 0 0 0 's )...................................................
N u m b er of e m p lo y e e s (in 0 00's):
With m edical c a r e .............................................................
With life in s u ra n c e ......................................................
With d efin e d b en e fit p la n ..................................................

1992

1994

State and local governments
1996

1987

1990

1992

1994

3 2 ,4 6 6

3 4 ,3 6 0

3 5 ,9 1 0

3 9 ,8 1 6

10,321

12,972

12,466

1 2 ,9 0 7

2 2 ,4 0 2
2 0 ,7 7 8
6 ,4 9 3

2 4 ,3 9 6
2 1 ,9 9 0
7,5 5 9

2 3 ,5 3 6
2 1 ,9 5 5
5 ,4 8 0

2 5 ,5 9 9
2 4 ,6 3 5
5,8 8 3

9 ,5 9 9
8 ,7 7 3
9 ,5 9 9

1 2,064

1 1,219
11,095
10,845

1 1 ,7 0 8

8
37

9
37

-

-

_
_

17
34

48
27
47

49
26

-

-

-

_

58
29
56
3.7

1 1 ,4 1 5
1 1,675

1 1 ,192
1 1 ,1 9 4

Time-off plans
P a rtic ip a n ts with:
P aid lunch tim e ....................................................................
A v e rag e m in u te s p e r d a y ..........................................
P aid re s t tim e .....................................................

11
36

10
34

56
29

53
29

_

65
3.7
75

62
3 .7

81

63
3.7
74

10.9
38
2.7
72

13.6
39
2 .9
67

14.2
38
2 .9
67

11.5
38
3 .0
66
94

A v e ra g e m in u te s p e r d a y ................................................
P aid funeral le a v e ..........................................................
A v e rag e d a y s p e r o c c u rre n c e .......................................
P aid h o lid a y s..................................................................

2 .9
84

50
3 .0
82

50
3.1
82

51
3 .0
80

A v e rag e d a y s p e r y e a r1...................................................
P aid p e rs o n a l le a v e ........................................................
A v e rag e d a y s p e r y e a r .................................................
P aid v a c a tio n s .................................................................

9 .5
11
2 .8
88

9.2
12
2 .6
88

7.5
13
2 .6
88

7 .6
14
3 .0
86

P aid sick le a v e 2....................................................................

47

53

50

50

97

95

95

U n p aid le a v e ...........................................................................
U n p aid pate rn ity le a v e ................................................
U n p aid family le a v e ..............................................................

17
8

18

-

_

57

51

59

47

48

73

-

93

Insurance plans
P artic ip a n ts In m edical c a r e p la n s ....................................
P e rc e n t of p artic ip a n ts with c o v e ra g e for:
H om e h ea lth c a r e ..............................................................

69

71

66

64

93

93

90

87

79

E x ten d e d c a r e fa cilities...................................................
P hysical e x a m .....................................................................

83
26

80
84

-

-

28

-

-

76
78
36

82
79
36

87
84
47

81
55

P e rc e n t of p a rtic ip a n ts with em p lo y ee
co ntribution re q u ire d for:
S elf c o v e r a g e ......................................................................
A v e rag e m onthly co n trib u tio n ......................................
F am ily c o v e r a g e .........................................................

42
$ 2 5 .1 3
67

47
$36.51
73

52
$ 4 0 .9 7
76

52
$ 4 2 .6 3
75

35
$ 1 5 .7 4
71

38
$ 2 5 .5 3
65

43
$ 2 8 .9 7
72

$ 3 0 .2 0
71

A v e ra g e m onthly co n trib u tio n ......................................

$ 1 0 9 .3 4

$ 1 5 0 .5 4

$ 1 5 9 .6 3

$ 1 8 1 .5 3

$ 7 1 .8 9

$ 1 1 7 .5 9

$ 1 3 9 .2 3

$ 1 4 9 .7 0

P a rtic ip a n ts in life in s u ra n c e p la n s ...................................
P e rc e n t of p artic ip a n ts with:
A ccidental d e a th a n d d is m e m b e rm e n t
in s u ra n c e ..............................................................................
S urvivor in co m e b e n e fits ..................................................
R etiree p rotection a v a ila b le .............................................
P a rtic ip a n ts in long-term disability
in s u ra n c e p la n s ....................................................................

64

64

61

62

85

88

89

87

78
1
19

76
1

79

77
1

67
1

67

25

13

55

1
45

74
1

64

2
20

22

31

27

28

30

14

21

22

21

84

47

46

2
46

19

23

20

P artic ip a n ts in s ic k n e s s a n d a c c id e n t
in s u ra n c e p la n s ......................................................................

6

26

26

P artic ip a n ts in sh o rt-term disability p l a n s 2....................

_

_

_

29

20

22

15

15

93

90

87

91

-

47
92
-

89
88
16
100

92
89
10
100

92
87

-

8

10

49

Retirement plans
P artic ip a n ts in d efin e d benefit p en sio n p la n s ..............
P e rc e n t of p artic ip a n ts with:
N orm al re tirem en t prior to a g e 6 5 ................................
Early re tire m e n t a v a ila b le ................................................
Ad h o c p en s io n in c re a s e in last 5 y e a r s .....................
T erm inal e a rn in g s fo rm u la..............................................

54

50
95
4
54

-

53

92
90
33
100

B enefit c o o rd in a te d with S ocial S e c u rity ....................

95
7
58
49

46

-

44

18

P a rtic ip a n ts in d efin e d contribution p la n s .......................

31

33

34

38

9

9

9

9

P artic ip a n ts in p la n s with ta x -d e fe rre d s a v in g s
a r r a n g e m e n ts ........................................................................

17

24

23

28

28

45

45

24

13
99

Other benefits
E m p lo y e e s eligible for:
Flexible b en e fits p la n s .........................................................

1

2

3

4

5

5

5

5

R e im b u rs e m e n t a c c o u n ts 3...............................................

8

14

19

12

5

31

50

64

7

_

P rem iu m co n v e rsio n p la n s .............................................
1 M eth o d s u s e d to c a lc u la te t h e a v e ra g e n u m b e r of p aid ho lid ay s w e re re v ise d

S ic k n e s s a n d ac c id e n t in s u ra n c e , re p o rte d in y e a rs prior to th is survey,

in 1 9 9 4 to c o u n t partial d a y s m o re p re cisely . A v e rag e holidays for 1994 a re

included only in su red , self-in su red , a n d S ta te -m a n d a te d p la n s providing p er-

not c o m p a ra b le with th o s e re p o rte d in 1 990 a n d 1992.

disability b e n e fits a t le s s th a n full pay.

2 T h e definitions for p aid sick le a v e a n d sh o rt-term disability (previously

3 Prior to 1996, re im b u rse m e n t a c c o u n ts included prem ium co n v e rsio n plan s,

s ic k n e s s a n d a c c id e n t in s u ra n c e ) w e re c h a n g e d for th e 1 996 su rvey. P aid sick

which

le a v e now in clu d es only p la n s th a t specify e ith e r a m axim um n u m b e r of d a y s

p re m iu m s with p re ta x dollars. Also, re im b u rse m e n t a c c o u n ts th a t w e re p art of

p e r y e a r o r unlim ited d a y s . S h o rt-term disability now in clu d es all in su red , self-

flexible benefit p la n s w e re ta b u la te d s e p a ra te ly .

specifically

allow m edical

plan

in su red , a n d S ta te -m a n d a te d p la n s a v a ila b le on a per-disability b a s is , a s well
a s th e u n fu n d e d per-disability p la n s previously re p o rte d a s sick leave.

108

Monthly Labor Review


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NOTE: Dash indicates d ata not available.

p a rtic ip a n ts to

p ay

re q u ired

plan

36. Work stoppages involving 1,000 workers or more
Annual totals

2003

2004p

Measure
2002

2003

July

Sept.

Aug.

Nov.

Oct.

Jan.

Dec.

Mar.

Feb.

May

Apr.

July

June

N u m b er of s to p p a g e s :
B eginning in p e rio d ....................................

19

14

0

3

0

5

0

0

0

1

1

0

2

3

0

20

15

1

3

2

5

3

2

1

2

1

1

2

4

1

W o rk ers involved:
B eginning in p e rio d (in th o u s a n d s ) ....

46

129.2

.0

8.2

.0

8 2 .2

8.0

.0

.0

6 .5

2 .2

.0

10 3 .0

2 7 .6

.0

In effect du rin g p erio d (in th o u s a n d s ).

47

1 3 0 .5

4 .0

8.2

3 .2

8 2 .2

7 6 .7

7 0 .5

6 1 .3

6 6 .5

2 .2

2 .2

10 3 .0

2 8 .6

1.6

6 ,5 9 6

4 ,0 9 1 .2

12.0

35 .9

51 .3

1 ,1 6 8 .5

1,2 1 9 .0

1 ,4 7 3 .4

1 ,2 0 3 .9

1,1 4 6 .5

4 4 .0

2 6 .4

2 0 4 .0

9 4 .0

3.2

(2)

.01

<2)

(2)

.04

.04

.05

.0 5

.05

.05

.00

.00

.01

.00

.00

D a y s idle:

P e rc e n t of e s tim a te d w orkina tim e 1....

1 A gricultural a n d g o v e rn m e n t e m p lo y e e s a r e in clu d ed in th e total em p lo y ed a n d total

M o n th ly L a b o r R e v ie w , O c to b e r 1968, p p .5 4 -5 6 .

w orking tim e; p riv ate h o u s e h o ld , forestry, a n d fishery e m p lo y e e s a r e ex c lu d e d . An

2 L e s s th a n 0 .0 0 5 .

ex p la n a tio n of th e m e a s u r e m e n t of id le n e s s a s a p e r c e n ta g e of t h e total tim e w o rk ed
is fo u n d in "Total e c o n o m y m e a s u r e s of strik e id len ess,"


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Monthly Labor Review

September 2004

109

Current Labor Statistics:

Price Data

37. Consumer Price Indexes for All Urban Consumers and for Urban Wage Earners and Clerical Workers: U.S. city average,
by expenditure category and commodity or service group
[1982-84 = 100, unless otherwise indicated]________________
Annual average

Series

2002

2003

2003
July

Aug.

Sept.

2004

Oct.

Nov.

Dec.

Jan

Feb.

Mar.

Apr.

May

June

July

CONSUMER PRICE INDEX
FOR ALL URBAN CONSUMERS
All ite m s ....................................................

179.9

184.0

183.9

184.6

185.2

185.0

184.5

184.3

185.2

186.2

187.4

188.0

189.1

189.7

All item s (1 9 6 7 = 100).......................................

189.4

538.8

551.1

550.9

553.0

554.7

554.3

552.7

552.1

554.9

557.9

561.5

563.2

566.4

568.2

567.5

F ood an d b e v e ra g e s .........................................

176.8

180.5

180.3

180.9

181.3

182.2

182.9

184.7

184.3

184.5

184.9

185.0

186.5

186.8

187.2

F o o d .............................................................

176.2

180.0

179.7

180.4

180.7

181.7

182.4

180.0

183.8

184.1

184.4

184.5

186.1

186.3

186.8

175.6

179.4

178.9

179.7

180.1

181.5

182.4

184.1

184.0

184.0

184.3

184.1

186.6

186.8

187.1

C e re a ls an d bak e ry p ro d u c ts ...................................

198.0

202.8

20 4 .5

204.5

20 3 .5

203.1

202.5

202.9

20 3 .9

204.4

204.8

2 0 5 .5

206.1

2 0 6 .8

2 0 7 .2

M eats, poultry, fish, an d e g g s .........................

162.1

169.3

168.2

169.7

171.1

174.0

179.3

181.1

179.9

179.7

179.5

179.2

181.1

182.3

183.7

Dairy an d re la ted p ro d u c ts 1............................
Fruits an d v e g e ta b le s ...........................................

168.1
2 2 0 .9

167.9

164.7

171.2
2 2 7 .5

173.0
232.4

172.4
232.4

172.1
229.7

171.9

22 6 .6

170.3
224.4

171.8

22 5 .9

167.5
22 4 .9

174.0
228.3

185.9
2 3 1 .7

188.8
2 2 6 .7

187.7
2 2 4 .5

F ood a t h o m e ......................................................

2 2 6 .3

230.1

N onalcoholic b e v e ra g e s an d b e v e ra g e
m ateria ls.................................................................

139.2

139.8

138.4

139.7

139.2

140.5

137.9

139.3

140.7

141.4

140.8

139.7

169.9

139.8

140.5

160.8

162.6

167.7

163.2

163.1

163.0

162.0

163.0

162.8

163.7

165.1

165.0

165.4

165.8

166.0

S u g a r an d s w e e ts .......................................

159.0

162.0

162.7

162.5

162.3

162.5

161.7

161.0

163.0

163.9

163.3

162.6

163.5

162.8

163.8

169.4

171.3

171.9
180.3

O th er foods a t h o m e ......................................................
F a ts a n d oils..............................................................

155.4

157.4

156.3

157.7

157.6

159.7

157.3

157.7

160.7

162.3

166.2

166.2

O th er fo o d s ...................................................

177.1

178.8

•179.0

179.4

179.4

178.7

177.9

179.6

178.0

178.9

180.4

180.4

O th er m isc ellan e o u s fo o d s 1,2..............

180.1

180.5

109.2

110.3

111.3

109.9

111.0

110.7

109.0

109.8

109.1

109.5

111.7

110.5

110.8

110.9

109.4

F ood aw ay from h o m e 1.........................................

178.3

182.1

182.2

182.6

182.8

183.3

183.8

184.3

184.9

185.5

185.8

186.2

186.7

187.0

187.8

O th er food aw ay from h o m e 1,2.................................
Alcoholic b e v e ra g e s .........................................

117.7

121.3
187.2

121.3
187.2

121.4
187.1

121.8

122.3

122.7

122.9

123.9

124.0

124.1

124.7

183.6

187.9

188.1

188.6

188.7

189.4

189.9

190.8

191.8

124.8
191.7

124.8
192.4

125.1
192.2

180.3
208.1

184.8

185.9

186.1

185.8

185.7

185.1

185.1

186.3

187.0

187.9

188.4

188.9

190.3

190.9

213.1

213.8

214.3

21 3 .8

2 1 4 .7

214.2

213.1

215.2

216.0

2 1 7 .8

218.4

2 1 8 .7

21 9 .2

220.0
211.2

H ousing.....................................................
S h e lte r............................................................
R en t of prim ary re s id e n c e ............................................

199.7

205.5

20 5 .6

206.1

20 6 .6

2 0 6 .9

207.5

205.5

2 0 8 .3

208.8

209.2

209.7

210.2

2 1 0 .7

Lodging aw ay from h o m e .............................................

118.3

119.3

124.8

125.1

118.5

120.9

115.0

119.3

117.2

120.0

128.1

129.1

128.2

129.1

132.2

O w n e rs' eq uivalent rent of prim ary re s id e n c e 3.....

21 4 .7

2 1 9 .9

219.6

220.1

220.7

221.4

221.9

2 1 9 .9

2 2 2 .6

222.9

22 3 .3

22 3 .9

224.3

22 4 .7

225.1

T e n a n ts ' an d h o u seh o ld in s u ra n c e 1,2......................
F u els an d utilities..............................................

108.7

114.8
154.5

115.6
159.4

115.8
159.2

115.9
159.6

116.0
155.0

114.3
152.9

114.8
154.5

114.8
156.3

115.0
156.9

115.1
155.2

115.7
155.6

116.1
158.1

116.2

143.6

165.5

116.1
166.6

127.2

138.2

143.6

143.0

143.4

138.2

135.7

138.7

139.2

139.5

137.6

138.0

140.4

148.5

F u e ls .........................................................................

149.5

Fuel oil an d o th er fu e ls .............................................

115.5

139.5

130.5

130.7

130.5

131.4

134.8

139.1

149.9

155.1

152.5

149.6

150.4

150.7

151.1

G a s (piped) an d electricity.......................................

134.4

145.0

151.6

151.0

151.5

145.6

142.6

145.0

145.5

145.5

143.5

144.2

146.8

155.8

156.9

H ousehold furnishings an d o p e ra tio n s .....................

128.3

126.1

126.1

125.5

125.2

125.1

124.9

124.7

125.3

125.7

125.7

125.6

125.4

125.6

125.2

124.0

120.9

116.2

117.2

122.0

124.8

123.1

119.0

115.8

118.6

123.5

124.3

123.4

120.1

115.9

A p p a re l.............................................................................
M en's a n d b o y s' a p p a re l...............................................

121.7

118.0

113.8

113.4

117.3

120.8

121.4

118.0

115.5

117.1

119.8

120.3

120.3

117.7

115.2

W o m e n 's a n d girls' a p p a re l.........................................

115.8

113.1

106.1

107.9

115.5

118.8

115.7

110.9

105.7

110.3

117.6

118.7

116.9

112.3

106.1

Infants' a n d to d d lers' a p p a re l1..................
F o o tw e a r..................................................................

126.4

122.1

117.9

120.8

124.1

125.2

123.0

119.2

117.7

119.3

121.9

120.5

118.1

116.2

114.5

121.4

119.6

117.5

117.8

120.3

121.8

121.0

118.5

115.9

117.0

120.1

121.0

120.3

118.4

115.1

152.9

157.6

156.8

158.3

159.4

157.1

155.7

154.7

157.0

158.8

160.5

161.8

165.2

165.7

164.0

148.8

153.6

152.4

154.1

155.4

153.0

151.7

150.8

153.2

154.9

156.6

157.9

161.5

161.9

160.0

T ra n sp o rtatio n ............................................................
P rivate tran sp o rta tio n ..................................................
N ew an d u s e d m otor v ehicles2...............................
N ew v e h ic le s..............................................

99.2

96.5

96.5

96.0

95.1

94.6

94.6

94.4

94.3

94.4

94.2

94.1

94.0

93 .6

93 .5

140.0

137.9

137.7

136.8

136.4

136.5

137.5

138.0

138.0

138.3

137.9

137.6

137.4

137.2

135.9

U se d c a r s an d tru ck s1.........................................
M otor fuel.................................................

152.0

142.9

145.7

143.3

132.1

143.1

150.5

131.3
155.9

130.6

127.8

130.8
136.7

131.8

139.0

132.0
131.2

131.2

130.6

135.1
136.6

131.0

135.8

139.0
147.1

131.0

116.6

170.5

173.3

165.2

G a so lin e (all ty p e s )...................................................

116.0

135.1

130.0

138.4

146.5

136.0

130.6

127.2

136.1

142.5

149.8

155.3

169.8

172.7

164.5

M otor vehicle p a rts an d eq u ip m en t...........................

106.9

107.8

107.6

107.9

107.7

107.9

107.9

107.8

108.0

108.0

107.8

107.9

107.9

108.2

108.8

M otor vehicle m a in te n a n c e an d re p air..............

190.2

195.6

196.0

195.7

196.2

196.9

197.2

198.0

198.2

198.2

198.5

198.6

199.0

199.7

20 0 .3

Public tra n s p o rta tio n .................................................

207.4

209.3

216.7

213.8

211.2

21 1 .3

207.9

205.6

206.3

208.1

209.9

2 1 1 .5

210.7

2 1 2 .3

214.4

M edical c a r e .......................................................................

28 5 .6

297.1

2 9 7 .6

298.4

299.2

29 9 .9

300.8

302.1

303.6

306.0

307.5

3 0 8 .3

309.0

3 1 0 .0

M edical c a re co m m o d itie s..............................................

311.0

256.4

26 2 .8

2 6 3 .6

264.1

264.9

26 4 .7

264.0

265.0

26 5 .5

26 6 .7

2 6 7 .3

26 8 .5

269.1

2 6 9 .6

2 6 9 .9

M edical c a re s e rv ic e s .......................................................

2 9 2 .9

306.0

306.4

307.2

308.2

309.1

310.6

311.9

313.8

316.6

318.4

319.2

319.8

321.0

322.3

P rofessional s e rv ic e s .................................................

2 5 3 .9

261.2

260.9

261.7

262.2

263.0

263.0

261.2

262.5

268.0

269.7

27 0 .6

2 7 0 .9

2 7 1 .6

2 7 2 .3

H ospital an d re la ted s e rv ic e s .......................................

419.1

3 6 7 .8

394.8

394.7

398.6

399.6

4 0 0 .7

405.6

4 0 7 .0

409.7

4 1 2 .5

41 3 .8

41 3 .6

4 1 4 .6

41 6 .9

R ecrea tio n 2.....................................................

106.2

107.5

107.7

107.7

107.7

107.6

107.8

107.7

107.9

108.4

108.8

109.0

108.8

108.9

108.7

Video an d a u d io 1,2....................................

102.6

103.6

103.7

103.7

103.5

103.5

103.8

103.3

103.6

104.1

104.3

104.7

104.6

104.4

104.4

E ducation an d com m unication2.......................................

107.9

109.8

108.9

110.1

110.9

110.9

110.8

110.9

111.1

111.2

111.1

110.9

110.6

110.8

110.9

E ducation2...............................................................
E ducational b o o k s an d su p p lie s ..............................

126.0

134.4

132.6

136.2

138.7

140.6

140.7

140.9

141.6

142.1

335.0

338.5

338.2

342.8

140.1
345.4

140.4

335.4

139.0
336.0

139.4

317.6

139.1
339.7

348.6

348.9

349.5

349.6

3 5 0 .6

349.5

Tuition, o th e r school fe e s , an d child c a r e ............

362.1

362.1

381.2

392.1

400.0

401.1

401.2

4 0 1 .7

403.6

404.2

404.7

404.9

40 5 .6

40 7 .6

409.4
8 6 .5

92 .3

89.7

89.4

89.0

88.6

88.4

88.2

88.2

88.1

88.1

87.7

87.4

86.9

86 .8

Inform ation a n d inform ation p ro c e s s in g 1,2...........

90.8

87.8

87.5

87.0

86.7

86.4

86.2

86.2

86.1

86.1

85.7

85.4

84.8

84 .7

84.5

T e le p h o n e s e rv ic e s 1,2............................................
Inform ation an d inform ation p ro c essin g

99.7

98.3

98.1

97.8

97.4

97.1

97.2

97.2

97.0

97.1

96.7

96.5

95.9

95 .8

95.6

18.3

16.1

16.0

15.7

15.6

15.6

15.4

15.3

15.3

15.2

15.2

15.0

14.9

14.9

14.8

C o m m unication1,2................................................

o th er than teleD hone s e rv ic e s 1,4.......................
P erso n a l co m p u ters an d peripheral
eq u ip m en t1,2........................................................
O th er g o o d s an d s e r v ic e s ...................................................

22.2

17.6

17.2

16.7

16.3

16.5

16.3

16.2

16.2

16.0

15.8

15.9

15.7

15.5

15.3

293.2

29 8 .7

299.2

29 9 .6

299.9

300.2

300.0

300.2

301.4

302.3

303.1

303.6

303.8

304.1

305.1

T o b a c c o an d sm oking p ro d u c ts ..................................

4 6 1 .5

469.0

469.1

471.8

468.7

46 9 .5

469.1

470.4

473.0

472.6

47 3 .6

47 3 .3

4 7 3 .5

4 7 6 .0

48 0 .5

P erso n a l c a r e 1..........................................

174.7

178.0

178.4

178.4

179.0

179.1

179.0

179.0

179.7

180.4

180.9

181.3

181.4

181.4

181.7

P e rso n a l c a re p ro d u c ts 1...............................................

154.7

153.5

154.2

153.5

153.4

153.6

153.2

153.4

153.8

154.5

154.5

154.5

154.6

153.8

153.4

P e rso n a l c a re s e r v ic e s 1............................................

188.4

193.2

193.2

193.9

195.4

195.6

194.2

194.3

194.6

195.2

195.8

196.1

196.6

196.9

197.5

S e e fo o tn o tes a t en d of table.

110

Monthly Labor Review


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

September 2004

37. Continued—Consumer Price Indexes for All Urban Consumers and for Urban Wage Earners and Clerical Workers: U.S. city
average, by expenditure category and commodity or service group
[1982-84 = 100, unless otherwise indicated]
Annual average
Series
M iscellan e o u s p e rso n a l s e r v ic e s .........................

2002
2 7 4 .4

2003
2 8 3 .5

2004

2003
July
284.1

Aug.
28 4 .3

Sept.
2 8 5 .3

Oct.
2 8 5 .8

Nov.
2 8 7 .0

Dec.
287.1

Jan.
28 8 .8

Feb.
290.4

Mar.
291.6

Apr.
2 9 2 .7

May
293.1

June

July

2 9 3 .6

2 9 4 .4

C om m odity a n d s erv ic e group:
C o m m o d ities.....................................................................

149.7

151.2

150.0

150.9

152.0

151.4

150.9

150.4

151.1

152.3

153.7

154.3

156.0

155.8

154.5

F ood a n d b e v e r a g e s ...................................................

176.8

180.5

180.3

180.9

181.3

182.2

182.9

184.1

184.3

184.5

184.9

185.0

186.5

186.8

187.2

C o m m odities le s s food a n d b e v e r a g e s ................

134.2

134.5

132.9

133.9

135.4

134.1

132.9

131.7

132.6

134.2

136.0

136.9

138.6

138.2

136.1

N o n d u rab les le s s food a n d b e v e r a g e s ...............

145.1

149.7

146.6

149.2

153.1

151.2

149.0

146.7

148.4

151.4

155.3

157.2

160.9

160.5

156.7

A p p a r e l......................................................................

119.0

115.8

118.6

123.5

124.3

123.4

120.1

115.9

124.0

120.9

116.2

117.2

122.0

124.8

123.1

N o n d u rab les l e s s food, b e v e ra g e s ,
a n d a p p a re l.............................................................

162.2

171.5

169.2

167.7

172.3

175.6

179.1

181.7

188.2

189.5

117.5

117.4

115.7

171.6
115.2

169.1

121.4

173.0
116.7

176.4

D u ra b le s ........................................................................

115.1

115.0

115.1

115.3

115.1

115.0

114.8

114.5

185.8
114.1
224.1

S e rv ic e s ..............................................................................

20 9 .8

2 1 6 .5

2 1 7 .6

218.0

218.1

2 1 8 .4

2 1 7 .9

2 1 7 .9

219.1

219.9

2 2 1 .0

2 2 1 .5

2 2 1 .9

2 2 3 .3

R ent of s h e lte r3............................................................
T ra n sp o rata tio n s e r v ic e s ..........................................

21 6 .7

2 2 1 .9

2 2 2 .6

223.1

22 2 .6

2 2 3 .5

2 2 3 .0

2 2 2 .9

224.1

2 2 4 .9

22 6 .8

2 2 7 .4

2 2 7 .7

2 2 8 .3

229.2

209.1

2 1 6 .3

2 1 7 .2

2 1 6 .8

21 7 .7

2 1 8 .7

2 1 9 .3

21 9 .7

25 4 .4

2 5 5 .5

2 5 7 .0

25 7 .3

25 7 .4

2 5 8 .4

2 5 9 .2

25 9 .5

220.0
2 5 9 .7

2 2 0 .0

2 4 6 .4

218.9
2 5 7 .2

2 1 8 .6

O th er s e r v ic e s ...............................................................

21 8 .0
25 3 .7

2 2 0 .5
260.2

221.6
26 0 .5

All item s le s s fo o d .......................................................

180.5

184.7

184.6

185.3

186.0

185.6

184.9

184.4

185.5

186.6

188.0

188.6

189.6

190.3

189.9

All item s le s s s h e lte r..................................................

170.8

174.6

174.2

175.0

176.0

175.5

174.9

174.7

175.6

176.7

177.6

178.2

179.6

180.2

179.6
183.2

2 5 9 .6

S p ecial in d ex e s:

All Item s le s s m edical c a r e ......................................

174.3

178.1

178.0

178.7

179.2

179.1

178.5

178.2

179.1

180.1

181.3

181.8

182.9

183.5

C o m m odities le s s fo o d .............................................

136.0

136.5

134.9

135.9

137.3

136.1

135.0

133.8

134.7

136.3

138.0

138.9

140.6

140.3

138.2

N o n d u rab les le s s fo o d ...............................................

147.4

151.9

149.0

151.5

155.2

153.3

151.3

149.2

150.8

153.7

157.5

159.3

162.8

162.4

158.8

N o n d u rab les le s s food a n d a p p a re l......................

163.3

172.1

170.0

173.4

176.6

172.2

170.0

168.8

173.0

176.1

179.4

181.7

187.7

189.0

185.6

N o n d u ra b le s .................................................................

161.1

165.3

163.5

165.2

167.4

166.8

166.1

165.4

166.4

168.1

170.3

171.4

174.1

174.0

172.2

S e rv ic e s l e s s rent of sh e lte r3..................................

2 1 7 .5

2 2 6 .4

2 2 8 .0

22 8 .4

22 9 .2

2 2 8 .7

2 2 8 .2

2 2 8 .4

22 9 .7

2 3 0 .6

23 0 .7

231.1

2 3 1 .7

2 3 4 .2

2 3 5 .0

S e rv ic e s l e s s m edical c a re s e r v ic e s .....................
E n erg y .............................................................................

2 0 2 .5
121.7

2 0 8 .7

21 0 .3
140.6

2 1 0 .3
144.6

2 1 0 .5
136.9

2 0 9 .9
133.1

20 9 .9

21 2 .7

131.8

21 1 .0
137.4

2 1 1 .7

136.5

20 9 .8
136.8

140.6

143.1

2 1 3 .2
145.9

21 3 .6
154.1

2 1 5 .0
159.7

2 1 5 .8
156.3

All item s le s s e n e rg y ..................................................

187.7

190.6

190.5

190.8

191.0

191.7

191.6

191.5

191.9

192.7

193.7

194.1

194.3

194.4

194.5

All item s le s s food a n d e n e rg y .............................

190.5

193.2

193.2

193.5

193.6

194.3

193.9

193.6

194.0

194.9

196.1

196.5

196.5

196.6

196.6

C o m m odities le s s food a n d e n e rg y .................

143.7

140.9

139.9

139.7

140.2

140.4

139.9

139.0

138.5

139.3

140.3

140.5

140.2

139.4

138.2

117.1

136.7

131.3

139.2

146.9

137.0

132.1

129.0

138.2

144.6

151.3

156.3

170.1

172.8

165.1

2 1 7 .5

22 3 .8

2 2 4 .3

2 2 4 .9

2 2 4 .9

2 2 5 .8

22 5 .6

2 2 5 .5

2 2 6 .6

22 7 .5

2 2 8 .9

22 9 .4

2 2 9 .6

23 0 .2

23 1 .0

CONSUMER PRICE INDEX FOR URBAN
WAGE EARNERS AND CLERICAL WORKERS
175.9

179.8

179.6

180.6

181.0

180.7

180.2

179.9

180.9

181.9

182.9

183.5

184.7

185.3

184.9

523.9

5 3 5 .6

535.0

537.1

53 9 .2

538.2

536.7

536.0

538.7

5 4 1 .7

54 4 .8

546.5

550.2

551.9

5 5 0 .8

F ood a n d b e v e r a g e s .......................................................

176.1

179.9

179.6

180.2

180.7

181.7

182.4

183.6

183.8

184.0

184.4

184.5

186.0

186.4

186.8

F o o d ....................................................................................

176.5

179.4

179.1

179.7

180.2

181.2

181.9

183.1

183.3

183.5

183.8

183.9

185.6

185.9

186.3

F ood at h o m e ................................................................

175.1

178.5

178.0

178.8

179.4

180.7

181.6

183.3

183.2

183.2

183.5

183.3

185.8

186.1

186.3

198.0

2 0 2 .8

2 0 4 .4

2 0 4 .5

2 0 3 .5

2 0 3 .2

2 0 2 .4

2 0 2 .4

2 0 3 .8

2 0 4 .4

2 0 4 .9

2 0 5 .5

2 0 6 .0

2 0 6 .7

2 0 7 .2

All item s (1967 = .'"00)......................................................

Fruits a n d v e g e ta b le s ...............................................

162.0

169.2

168.2

169.5

170.9

173.8

179.2

181.0

179.9

179.7

179.6

179.1

181.1

182.4

183.7

167.2
2 2 2 .9

167.6
2 2 4 .3

164.4

167.0

171.7

171.0

172.7

2 2 5 .3

2 2 9 .7

2 2 7 .5

173.6
22 5 .5

189.0

224.9

171.3
2 2 7 .8

186.1

2 2 3 .8

172.2
2 2 9 .7

171.7

2 2 5 .3

170.2
2 2 3 .4

2 2 8 .9

2 2 4 .3

187.8
2 2 2 .3

N onalcoholic b e v e ra g e s a n d b e v e ra g e
m a te ria ls ...................................................................

138.6

139.1

137.5

138.9

138.5

139.8

137.3

138.6

140.0

140.8

140.1

139.1

139.3

139.3

139.8

O th er fo o d s at h o m e ................................................

160.4

162.2

162.3

162.6

162.8

162.5

161.6

162.5

162.3

163.3

164.7

164.6

165.1

165.5

165.6

S u g a r a n d s w e e ts ...................................................

158.8

161.6

162.3

162.1

162.1

162.1

161.4

160.5

162.4

163.2

162.6

161.9

162.9

162.2

162.9

F a ts a n d o ils..............................................................

155.3

157.4

156.2

157.7

157.6

159.6

157.3

157.7

160.7

162.2

166.0

166.1

169.4

171.4

172.0

177.6

179.2

179.4

179.7

180.0

179.0

178.3

180.0

178.4

179.4

180.8

180.8

180.5

180.8

180.7

O th er m isc e lla n e o u s fo o d s 1,2.........................

109.7

110.8

111.6

110.0

111.3

111.2

109.5

110.3

109.6

110.1

112.2

111.0

111.2

111.4

109.7

F ood aw ay from h o m e 1..............................................

178.2

182.0

182.1

182.4

182.7

183.3

183.7

184.2

184.8

185.3

185.6

186.1

186.6

186.8

187.6

118.1

121.5

121.4

121.6

122.0

122.5

122.9

123.1

123.6

123.8

123.8

124.3

124.6

124.7

124.9
192.2

183.3

187.1

187.0

186.9

187.7

188.1

188.8

188.9

189.5

190.0

191.2

192.1

192.0

192.7

H o u sin g ...............................................................................

175.7

180.4

181.4

181.6

181.6

181.3

180.9

181.0

182.1

182.6

183.2

183.6

184.1

185.6

186.2

S h e lte r.............................................................................

20 1 .9

20 6 .9

2 0 7 .2

2 0 7 .7

2 0 7 .6

2 0 8 .3

20 8 .2

2 0 8 .2

209.2

20 9 .8

211.0

2 1 1 .5

2 1 1 .8

21 2 .2

2 1 3 .0
2 1 0 .3

199.0

20 4 .7

2 0 4 .8

2 0 5 .3

2 0 5 .8

206.1

20 6 .6

2 0 7 .0

207.4

20 8 .0

208.4

20 8 .9

2 0 9 .4

20 9 .9

Lodging aw a y from h o m e 2....................................

118.4

119.8

125.0

125.2

119.8

121.7

116.2

113.4

118.5

121.1

128.8

129.8

128.2

128.8

133.0

O w n e rs' eq u iv a le n t re n t of prim ary re s id e n c e 3

195.1

199.7

199.4

199.9

20 0 .4

2 0 1 .0

2 0 1 .4

2 0 1 .7

202.1

2 0 2 .3

2 0 2 .7

203.1

20 3 .6

2 0 3 .9

20 4 .2

T e n a n ts ’ a n d h o u se h o ld in s u ra n c e 12 ................

108.7

114.7

115.4

115.7

115.8

116.0

114.4

114.4

114.9

115.1

115.2

116.0

116.4

142.9

153.9

158.9

158.7

159.1

154.3

152.3

153.C

155.6

156.2

154.7

155.1

157.4

165.0

166.1

147.4

116.5

148.4

116.3

126.1

137.0

142.4

141.9

142.3

137.0

134.7

135.4

138.0

138.3

136.6

137.0

139.3

115.0

138.7

129.6

129.6

129.4

130.7

134.4

136.2

149.6

154.5

152.0

148.9

149.6

149.8

150.2

133.4

144.1

150.6

150.1

150.6

144.6

141.9

142.5

144.7

144.7

142.9

143.5

146.1

155.1

156.2

124.4

121.9

121.9

121.4

121.0

120.9

120.7

120.4

121.0

121.4

121.4

121.3

121.1

121.3

120.7

A p p a re l...............................................................................

123.1

120.0

115.2

116.1

121.0

123.9

122.6

118.7

115.7

118.3

122.9

123.8

122.8

119.6

115.6

M en’s a n d b o y s' a p p a re l.........................................

121.7

117.5

113.4

112.9

116.5

120.0

121.1

117.8

115.6

117.4

120.0

120.6

120.3

117.8

115.2

114.6

112.1

105.0

106.9

114.5

118.2

115.3

110.5

105.5

109.8

117.4

118.4

116.7

112.2

106.0

128.6

124.1

120.3

122.9

126.5

127.7

125.0

121.4

120.1

122.2

125.2

123.4

120.9

118.8

117.0

121.2

119.1

116.9

117.2

119.6

121.1

120.4

117.8

115.6

116.4

118.6

119.6

119.0

117.0

114.4

151.8

156.3

155.5

157.1

158.1

155.4

153.6

152.5

154.9

156.8

158.5

159.9

163.6

164.0

162.2

149.0

153.5

152.5

154.2

155.3

152.5

150.8

149.7

152.2

154.0

155.7

157.1

160.9

161.3

159.3

99.4

96.0

96.3

95.7

94.4

93.5

93.1

92.8

92.7

92.8

92.6

92.6

92.5

92.1

92.1

H ou se h o ld fu rnishings a n d o p e ra tio n s .............

N ew a n d u s e d m otor veh ic le s2...........................
S e e fo o tn o te s a t e n d of tab le.


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

Monthly Labor Review

September 2004

111

Current Labor Statistics:

Price Data

37. Continued—Consumer Price Indexes for All Urban Consumers and for Urban Wage Earners and Clerical Workers: U.S. city
average, by expenditure category and commodity or service group
[1982-84 = 100, unless otherwise indicated]_____
Annual average

2003

Series
2002

2003

July

Aug.

Sept.

2004

Oct.

Nov.

Dec.

Jan.

Feb.

Mar.

Apr.

May

June

July

N ew v e h ic le s............................................

141.1

139.0

137.7

137.9

137.6

137.8

138.7

139.2

139.2

139.5

139.0

138.7

138.5

138.2

137.0

U sed c a rs an d tru c k s 1............................

152.8

143.7

146.4

144.0

139.8

135.9

132.8

131.7

131.6

131.7

132.0

132.1

132.6

131.4

133.0

M otor fuel......................................

117.0

136.1

130.9

139.4

147.5

136.9

131.5

128.1

137.1

143.6

150.9

156.5

171.1

173.8

G a so lin e (all ty p e s )................................................

165.6

116.4

135.5

130.4

138.9

147.0

136.4

130.9

127.6

136.6

143.0

150.3

155.8

170.4

173.2

165.0

M otor vehicle p a rts an d e q u ip m e n t....................

106.1

107.3

107.0

107.3

107.2

107.5

M otor vehicle m a in te n a n c e an d re p air..............
Public tra n s p o rta tio n ............................................

107.5

107.3

107.6

107.6

107.4

107.5

107.5

107.8

108.2

191.7

197.3

197.7

197.3

197.9

198.6

198.9

199.8

199.9

200.1

20 0 .3

200.4

20 0 .8

2 0 1 .5

202.1

202.6

206.0

212.8

21 0 .5

208.4

20 8 .7

205.8

212.1

2 0 3 .6

2 0 4 .6

206.2

2 0 8 .0

209.4

20 8 .8

2 1 0 .0

M edical c a r e ....................................................................

284.6

296.3

296.7

297.4

2 9 8 .3

299.1

300.1

301.4

302.8

305.4

306.9

307.7

308.4

309.4

310.4

M edical c a r e c o m m o d itie s.......................................

251.1

257.4

258.2

25 8 .6

259.4

259.2

2 5 8 .5

259.4

2 5 9 .8

2 6 0 .9

2 6 1 .5

26 2 .5

2 6 3 .3

2 6 3 .8

2 6 3 .7

M edical c a r e s e r v ic e s ................................................

2 9 2 .5

305.9

3 0 6 .3

307.0

307.9

309.1

310.6

3 1 1 .9

3 1 3 .8

316.8

318.6

319.4

320.0

321.2

322.4

P ro fe ssio n a l s e rv ic e s ..............................................

256.0

263.4

264.1

263.9

264.4

265.2

2 6 5 .2

266.5

2 6 7 .8

2 7 0 .6

272.3

273.2

2 7 3 .5

274.1

2 7 4 .8

H ospital a n d re la ted s e r v ic e s ................................

363.2

391.2

390.9

394.2

3 9 5 .8

397.5

402.4

403.4

4 0 5 .9

4 0 8 .7

4 0 9 .9

4 0 9 .8

410.7

41 3.0

4 1 5 .2

104.6

105.5

105.6

105.7

105.5

105.4

105.6

105.5

105.6

106.2

106 5

102.0

102.9

102.9

102.9

102.7

102.8

103.0

102.5

102.7

103.2

103.5

103.9

103 9

107.6

109.0

108.2

109.1

109.7

109.7

109.6

109.7

109.8

110.0

109.8

109 6

Video a n d a u d io 1,2...........................................
E ducation2...........................................................
E ducational b o o k s an d su p p lie s ........................

125.9

133.8

132.3

135.5

137.8

138.1

138.0

138.0

139.1

139.4

139.6

139.7

139.9

140.6

141.0

318.5

336.5

336.3

339.6

339.6

340.6

337.5

343.8

346.1

34 9 .5

349.9

350.4

350.4

351.5

350.4

Tuition, o th e r school fe e s , a n d child c a r e .......

354.8

377.3

372.6

382.1

389.2

390.1

390.2

390.7

392.8

393.3

393.8

394.1

3 9 4 .6

396.7

398.1

93.7

91.2

90.9

90.5

90.2

89.9

89.8

89.7

89.6

89.6

89.3

89.0

88..4

88.4

88.1

Inform ation a n d inform ation p ro c e s s in g 1,2.....

92.7

89.9

89.6

89.1

89.1

88.5

88.4

88.3

88.2

88.2

87.9

8 7 .5

87.0

86.9

8 6 .7

T e le p h o n e s e r v ic e s 1,2....................................
Inform ation an d inform ation p ro c essin g

99.9

98.5

98.3

98.0

97.6

97.3

97.4

97.4

97.2

9 7 .3

96.9

96.7

96.1

96.1

9 5 .8

o th e r th a n te le o h o n e s e rv ic e s 1,4.................
P e rso n a l co m p u ters an d peripheral

19.0

16.7

16.5

16.3

16.1

16.2

15.9

15.8

15.8

15.8

15.7

15.5

15.4

15.4

15.3

e q u ip m e n t1,2...........................................
O th er g o o d s a n d s e r v ic e s ............................................

21.8

17.3

16.9

16.3

16.0

16.2

16.0

15.9

15.8

15.7

15.5

15.6

15.4

15.2

15.0

302.0

307.0

307.5

308.0

30 7 .9

308.2

307.7

308.1

309.3

310.0

310.8

3 1 1 .3

311.5

3 1 1 .8

T o b a c c o an d sm oking p ro d u c ts .............................

31 3 .2

463.2

47 0 .5

47 0 .5

473.2

46 9 .9

47 0 .7

470.2

47 1 .5

4 7 3 .8

473.2

474.2

474.1

474.4

4 7 6 .9

48 1 .6

P e rso n a l c a r e 1...........................................................

174.1

177.0

177.5

177.4

177.9

178.0

177.7

177.8

177.4

179.1

179.7

180.1

180.2

180.0

180.3

P e rso n a l c a re p ro d u c ts 1........................................

155.5

154.2

154.8

154.3

154.0

154.1

153.8

1 5 4 .2

154.3

155.0

155.0

155.1

155.1

154.3

153.9

P e rso n a l c a re s e rv ic e s 1...................................

189.1

193.9

193.9

194.6

196.1

196.3

194.8

194.9

195.1

195.7

196.3

196.6

197.1

197.5

198.1

274.0

2 8 3 .3

284.0

284.4

285.2

285.6

286.7

286.6

288.4

290.2

2 9 1 .6

2 9 2 .9

293.1

29 3 .5

2 9 4 .7

C om m u n ica tio n 1,2.................................

M iscellaneous p e rso n a l s e rv ic e s ........................
C om m odity an d s erv ic e group:
C o m m o d ities...............................................................

150.4

151.8

F ood an d b e v e ra g e s ..................................................

176.1

179.9

150.7
179.6

151.6
180.2

152.7
180.7

151.9
181.7

151.3
182.4

150.7
183.6

151.5
183.8

152.7
184.0

154.1
184.4

154.8
184.5

156.7
186.0

156.6
186.4

155.2
186.8

C om m odities le s s food an d b e v e ra g e s ...............

135.5

135.8

134.2

135.4

136.7

135.2

133.8

132.5

133.5

135.2

137.0

138.0

140.0

139.6

137.5

N o n d u rab les le s s food an d b e v e ra g e s ..............

147.0

152.1

148.7

151.7

155.9

153.6

151.4

149.0

151.0

154.3

158.4

160.5

164.7

164.4

160.4

123.1

120.0

115.2

116.1

121.0

123.9

122.6

118.7

115.7

118.3

122.9

123.8

122.8

119.6

115.6
191.8

A p p a re l............................................................
N o n d u rab les le s s food, b e v e ra g e s ,
a n d a p p a re l............................................................

165.3

175.6

173.0

177.4

181.2

175.7

172.9

171.6

176.5

180.2

184.1

187.0

194.5

196.0

D u ra b le s .......................................................................

121.8

117.4

117.6

116.9

115.5

114.7

114.2

114.0

114.0

1142.0

114.0

113.9

113.9

113.5

113.2

205.9

2 1 2 .6

213.6

2 1 4 .0

2 1 4 .3

214.4

214.1

2 1 4 .2

2 1 5 .3

2 1 6 .0

216.7

217.1

21 7 .6

21 9 .0

2 1 9 .7

R ent of s h e lte r3............................................
T ra n sp o rata tio n s e rv ic e s .........................................

194.5
20 7 .7

199.2

199.5
217.4

200.0

199.9

200.6

2 0 0 .5

2 0 0 .6

201.4

2 0 3 .7

204.4

205.1

2 1 6 .8

2 1 6 .8

219.0

2 1 8 .8

218.0

219.1

2 0 2 .0
2 1 9 .7

203.2

216.2

220.0

220.2

2 2 0 .3

22 0 .7

2 2 1 .6

O th er s e r v ic e s ...................................................

241.6

2 4 8 .5

2 4 7 .9

249.3

2 5 0 .6

2 5 0 .7

250.7

2 5 0 .9

25 1 .8

2 5 2 .6

25 2 .9

2 5 3 .0

2 5 2 .7

2 5 3 .3

2 5 3 .5

S e rv ic e s ................................................................

20 3 .9

S pecial in d ex es:
All item s le s s fo o d ............................................

175.8

179.7

179.6

180.3

181.0

180.4

179.7

179.2

180.2

181.4

182.6

183.2

184.4

185.0

184.5

All item s le s s s h e lte r................................................

168.3

171.9

171.5

172.3

173.3

172.6

171.9

171.6

172.5

173.7

174.7

175.3

176.8

177.5

176.7

All item s le s s m edical c a r e ......................................

171.1

174.8

174.5

175.2

176.0

175.6

175.0

174.7

175.6

176.6

177.6

178.2

179.4

180.0

179.6

C om m odities le s s fo o d .............................................

137.3

137.7

136.1

137.2

138.6

137.0

135.8

134.5

135.5

137.1

138.9

139.9

141.8

141.5

139.4

N o n d u rab les le s s fo o d ..............................................

149.2

154.2

151.0

151.0

157.9

155.7

153.7

151.4

153.3

156.4

160.4

162.4

166.4

166.2

162.3

184.0

186.6

193.5

194.8

191.0

N o n d u rab les le s s food a n d a p p a re l......................

166.1

175.9

173.5

177.5

181.1

176.1

173.6

172.1

176.9

180.2

N o n d u ra b le s ................................................................

161.4

166.4

164.6

166.4

168.8

168.1

167.3

166.6

167.8

169.5

171.8

173.0

175.9

175.9

174.0

S e rv ic e s le s s rent of sh e lte r3..................................
S e rv ic e s le s s m edical c a re s e r v ic e s ....................
E n erg y ........................................................

193.1

2 0 1 .3

202.8

203.1

2 0 3 .7

203.2

2 0 2 .7

202.9

204.1

2 0 4 .9

204.9

205.2

2 0 5 .8

208.2

2 0 8 .9

198.9
120.9

205.2
135.9

206.2
135.9

206.6
140.0

2 0 6 .8
144.2

206.9
136.3

206.5
132.4

20 6 .6
131.1

207.6
136.9

208.2
140.2

208.8
143.0

209.2
146.0

2 0 9 .7
154.5

211.1
159.9

21 1 .8
156.2

All item s le s s e n e rg y ..................................................

183.6

186.1

185.9

186.2

186.4

187.0

187.0

186.9

187.2

187.9

188.7

189.0

189.3

189.3

189.3

All item s le s s food a n d e n e rg y .............................

185.6

187.9

187.7

187.9

188.1

188.6

188.4

188.0

188.3

189.1

190.1

190.4

190.4

190.3

190.3

C om m odities le s s food an d e n e rg y .................

144.4

141.1

140.3

140.1

140.2

140.3

139.7

141.1

138.2

139.0

140.0

140.1

139.9

139.0

138.0

E nergy co m m o d itie s...........................................

17.3

136.8

131.4

139.5

147.2

137.2

132.1

136.8

138.3

144.7

151.5

156.7

170.7

173.3

165.5

S e rv ic e s le s s e n e rg y .............................................

2 1 3 .9

220.2

22 0 .5

221.0

22 1 .3

222.1

222.1

222.1

2 2 3 .1 1

2 2 3 .9

2 2 4 .9

225.3

22 5 .5

22 6 .0

2 2 6 .7

Not seasonally adjusted.

4 indexes on a D ecem ber 1988 = 100 base.

2 In d e x es on a D e c e m b e r 1997 = 100 b a s e .

D ash in d icate s d a ta not available.

3 Indexes on a D e c e m b e r 1982 = 100 base.

N o t e : Index applied to a month as a whole, not to any specific date.

112

Monthly Labor Review


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

September 2004

38.

Consumer Price Index: U.S. city average and available local area data: all items

[1982-84 = 100, unless otherwise indicated]
Pricing

All Urban C onsum ers

Urban W age Earners

sched-

2004

2004

ule1

Apr.

Mar.

Feb.

Apr.

Mar.

Feb.

July

June

May

June

May

July

189.1

1 8 9 .7

1 8 9 .4

1 8 1 .9

1 8 2 .9

1 8 3 .5

1 8 4 .7

1 8 5 .3

1 8 4 .9

1 9 9 .4

1 9 9 .9

2 0 1 .1

2 0 1 .0

1 9 3 .6

195.1

1 9 5 .7

1 9 6 .4

1 9 7 .5

1 9 7 .3

2 0 1 .4

2 0 2 .0

2 0 3 .3

2 0 3 .0

1 9 4 .3

1 9 5 .9

1 9 6 .3

197.1

1 9 8 .3

1 9 8 .0

118.1

1 1 8 .3

1 1 8 .7

1 1 9 .2

1 1 6 .7

1 1 7 .5

118.1

1 1 8 .4

1 1 8 .8

119.1

1 8 1 .0

1 8 1 .5

1 8 2 .9

1 8 3 .3

1 8 3 .2

1 7 5 .3

1 7 5 .8

1 7 6 .3

1 7 7 .8

1 7 8 .2

178

183.1

1 8 3 .7

1 8 5 .0

1 8 5 .3

1 8 5 .4

1 7 6 .9

1 7 7 .2

1 7 7 .9

1 7 9 .4

1 7 9 .4

1 7 9 .5

1 1 5 .6

1 1 6 .4

1 1 6 .8

1 1 6 .3

1 1 3 .8

1 1 4 .2

1 1 4 .6

1 1 5 .5

1 1 6 .0

1 1 5 .5

1 7 3 .9

1 7 6 .0

1 7 6 .9

177.1

1 7 0 .6

1 7 1 .4

1 7 1 .2

1 7 3 .2

174.1

1 7 3 .7

1 8 0 .9

1 8 2 .0

1 8 2 .9

1 8 2 .6

179.1

180.1

1 8 0 .9

1 7 8 .9

1 7 9 .7

1 7 9 .3

1 8 2 .5

1 8 3 .4

1 8 4 .3

1 8 3 .7

1 7 8 .0

1 7 8 .9

1 7 9 .7

1 8 0 .8

1 8 1 .9

1 8 1 .2

1 1 4 .9

1 1 5 .6

1 1 6 .4

1 1 7 .0

1 1 6 .9

1 1 2 .7

1 1 3 .4

1 1 4 .0

1 1 4 .8

1 1 5 .3

1 1 5 .2

1 7 6 .8

1 7 7 .7

1 7 8 .7

1 7 9 .4

1 8 0 .5

180.1

176

1 7 6 .9

1 7 7 .8

179

180

1 7 9 .4
1 8 8 .0

1 8 7 .4

M

1 8 6 .2

N o r th e a s t u r b a n ..........................................................................................

M

1 9 6 .8

1 9 8 .6

S iz e A— M o re t h a n 1 ,5 0 0 ,0 0 0 .......................................................

M

1 9 8 .6

2 0 0 .7

M

1 1 6 .6

1 1 7 .4

M

1 8 0 .2

S iz e A— M o re t h a n 1 ,5 0 0 ,0 0 0 .......................................................

M

1 8 2 .5

S iz e B /C — 5 0 ,0 0 0 to 1 ,5 0 0 ,0 0 0 ® .................................................
S iz e D— N o n m e tro p o lita n ( l e s s th a n 5 0 ,0 0 0 ) .........................

M

1 1 4 .7

1 1 5 .2

M

1 7 3 .0

174.1

S o u th u r b a n .................................................................................................

M

179.1

180.1

S iz e A— M o re t h a n 1 ,5 0 0 ,0 0 0 .......................................................

M

1 8 0 .8

1 8 1 .8

M

1 1 4 .3

M

U .S . city a v e r a g e ...............................................................................

1 8 8 .0

Region and area size2

S iz e B /C — 5 0 ,0 0 0 to 1 ,5 0 0 .0 0 0 ® ..................................................
4

S iz e B /C — 5 0 ,0 0 0 to 1 ,5 0 0 ,0 0 0 ® .................................................
S iz e D— N o n m e tro p o lita n ( le s s t h a n 5 0 ,0 0 0 ) .........................
W e s t u r b a n ..................................................................................................

M

1 9 0 .8

1 9 2 .2

1 9 2 .3

1 9 3 .4

1 9 3 .3

1 9 2 .9

1 8 5 .7

187.1

1 8 7 .3

1 8 8 .6

1 8 8 .6

S iz e A— M o re t h a n 1 ,5 0 0 ,0 0 0 .......................................................

M

1 9 3 .2

1 9 4 .5

1 9 4 .6

1 9 5 .9

1 9 5 .9

1 9 5 .4

1 8 6 .5

1 8 7 .9

1 8 8 .2

1 8 9 .6

1 8 9 .7

1 8 8 .9

M

1 1 7 .0

1 1 7 .9

1 1 7 .8

1 1 8 .2

1 1 7 .9

1 1 7 .9

1 1 6 .4

1 1 7 .2

1 1 7 .2

1 1 7 .8

1 1 7 .6

1 1 7 .4

S iz e B /C — 5 0 ,0 0 0 to 1 ,5 0 0 ,0 0 0 ® ..................................................
S iz e c l a s s e s :
a5

D

.......................................................................................................

M

1 7 0 .4

1 7 1 .5

1 7 2 .0

1 7 2 .9

1 7 3 .4

173.1

1 6 8 .6

1 6 9 .6

1 7 0 .0

1 7 1 .2

1 7 1 .7

1 7 1 .3

M

1 1 5 .2

1 1 5 .9

1 1 6 .3

1 1 7 .0

1 1 7 .3

1 1 7 .3

1 1 4 .2

1 1 4 .9

1 1 5 .3

1 1 6 .0

1 1 6 .4

1 1 6 .2

M

1 7 7 .9

1 7 8 .9

1 7 9 .3

1 8 0 .9

1 8 1 .8

1 8 1 .3

1 7 5 .8

1 7 6 .7

1 7 7 .2

1 7 8 .8

1 7 9 .7

1 7 9 .0

Selected local areas6
C h ic a g o - G a r y - K e n o s h a , IL -IN -W I................................................

M

1 8 6 .4

1 8 6 .3

1 8 7 .2

1 8 8 .7

189.1

1 8 9 .2

1 7 9 .9

1 7 9 .7

1 8 0 .6

1 8 2 .2

1 8 2 .5

1 8 2 .4

L o s A n g e le s - R iv e r s i d e - O r a n g e C o u n ty , C A .............................

M

190.1

1 9 1 .5

1 9 1 .9

1 9 3 .3

1 9 3 .7

1 9 3 .4

1 8 6 .4

1 8 4 .9

1 8 5 .2

1 8 6 .8

1 8 7 .4

1 8 6 .8

N e w Y ork, N Y - N o rth e r n N J - L o n g Is la n d , N Y - N J - C T - P A .

M

20 1 .1

2 0 3 .4

2 0 4 .0

2 0 4 .4

2 0 6 .0

2 0 5 .5

1 9 6 .3

1 9 8 .2

1 9 8 .5

199.1

2 0 0 .4

20 0 .1

-

2 0 8 .7

-

1 8 1 .3

-

2 0 8 .9

-

2 0 7 .4

-

2 0 7 .9

-

2 0 7 .9

1 8 0 .0

_

179.1

-

1 8 1 .7

-

1 7 1 .0

-

1 7 2 .6

-

1 7 2 .8

1 1 8 .9

-

179.1

-

1 7 7 .6

-

1 7 9 .5

-

1 7 9 .4

B o s to n - B r o c k t o n - N a s h u a , M A - N H -M E -C T .............................

1

C le v e la n d - A k ro n , O H .............................................................................

1

D a lla s F t W o rth T X ................................................................................

1

-

_

1 7 7 .7

W a s h in q to n - B a ltlm o r e , D C -M D -V A -W V 7 .................................

1

-

118.1

-

1 1 8 .9

-

1 2 0 .2

-

1 1 7 .6

-

1 1 8 .4

-

1 1 9 .7

A tla n ta , G A ...................................................................................................

2

1 8 0 .8

1 8 2 .3

-

1 8 4 .0

-

1 8 5 .8

178.1

-

1 8 0 .0

1 8 4 .7

-

1 7 8 .7

1 8 3 .4

_

1 8 5 .7

2

_

1 7 9 .3

-

1 8 0 .4

-

H o u s to n - G a l v e s t o n - B r a z o r i a , T X ...................................................

2

1 6 8 .5

-

1 6 9 .7

-

1 6 9 .3

-

1 6 5 .7

-

1 6 6 .8

-

1 6 7 .6

-

M ia m i-F t. L a u d e r d a le , F L ....................................................................

2

1 8 3 .6

-

1 8 5 .2

-

1 8 5 .6

-

1 8 0 .8

-

1 8 2 .6

-

1 8 3 .4

-

-

-

1 9 7 .3

P h ila d e lp h ia -W ilm in g to n -A tla n tic C ity, P A - N J - D E - M D ....

2

1 9 1 .4

-

1 9 4 .8

1 9 8 .0

1 9 1 .2

-

1 9 4 .0

S a n F r a n c i s c o - O a k l a n d - S a n J o s e , C A ........................................

2

198.1

-

1 9 8 .3

1 9 9 .0

194.1

-

1 9 4 .7

1 9 5 .4

“

S e a t t l e - T a c o m a - B r e m e r to n , W A ....................................................

2

1 9 3 .5

1 9 4 .3

1 9 5 .3

1 8 7 .8

-

189.1

1 9 0 .4

“

1 F o o d s , fu e ls , a n d s e v e r a l o th e r Ite m s p ric e d e v e ry m o n th in all a r e a s ; m o s t o th e r
g o o d s a n d s e r v ic e s p ric e d a s In d ic a te d :

W l;

M in n e a p o lls -S t. P a u l, M N -W I; P itts b u rg h , PA; P o r t- l a n d - S a l e m , O R -W A ; S t L ouis,

M— E v ery m o n th .

M O -IL ; S a n D ieg o , C A; T a m p a - S t. P e t e r s b u r g - C le a r w a t e r , FL.

1— J a n u a r y , M a rc h , M ay , J u ly , S e p t e m b e r , a n d N o v e m b e r.

7 In d e x es on a N o v em b er 1996 = 100 b a s e .

2—

F e b ru a ry , April, J u n e , A u g u s t, O c to b e r, a n d D e c e m b e r.

2 R e g io n s d e f in e d a s t h e fo u r C e n s u s re g io n s .
3 In d e x e s o n a D e c e m b e r 1 9 9 6 = 1 0 0 b a s e .
4 T h e "N o rth C e n tra l" re g io n h a s b e e n r e n a m e d th e "M idw est" re g io n by t h e
C e n s u s B u re a u . It Is c o m p o s e d o f th e s a m e g e o g r a p h ic e n title s .
5 In d e x e s o n a D e c e m b e r 1 9 8 6 = 1 0 0 b a s e .
6

R e p o rt: A n c h o ra g e , AK; C in c in n a tti, O H -K Y -IN ; K a n s a s C ity, M O -K S ; M i lw a u k e e -R a c ln e ,

NOTE:

L ocal a r e a C P I I n d e x e s a r e b y p ro d u c ts of t h e n a tio n a l C P I p ro g r a m .

E a c h local

in d e x h a s a s m a lle r s a m p l e s i z e a n d is, th e r e f o r e , s u b je c t t o s u b s ta n tia lly m o re s a m p lin g
a n d o th e r m e a s u r e m e n t e r ro r. A s a re s u lt, lo ca l a r e a i n d e x e s s h o w g r e a t e r volatility th a n
t h e n a tio n a l in d e x , a lth o u g h th e ir lo n g -te rm tr e n d s a r e sim ilar.

T h e r e fo r e , t h e B u re a u of

L a b o r S ta tis tic s s tro n g ly u r g e s u s e r s to c o n s i d e r a d o p tin g t h e n a tio n a l a v e r a g e C P I for u s e
in th e ir e s c a l a t o r c l a u s e s . In d e x a p p lie s to a m o n th a s a w h o le , n o t to a n y s p e c if ic d a t e .

In a d d itio n , t h e follow ing m e tro p o lita n a r e a s a r e p u b lis h e d s e m ia n n u a lly a n d

a p p e a r in t a b l e s 3 4 a n d 3 9 of t h e J a n u a r y a n d Ju ly i s s u e s of t h e CPI D e ta ile d


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D a s h in d ic a te s d a t a n o t a v a ila b le .

Monthly Labor Review

September 2004

113

Current Labor Statistics:

Price Data

39. Annual data: Consumer Price Index, U.S. city average, all items and major groups
[1982-84 = 100]_________
Series

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

C o n s u m e r P ric e In d e x for All U rb a n C o n s u m e r s :
All ite m s :
In d e x ..............................................

1 4 4 .5

P e r c e n t c h a n g e ..................................

3 .0

F ood a n d b e v e ra g e s:
In d e x ...............................................

2 .6

1 4 1 .6

P e r c e n t c h a n g e ............................................

2.1

1 o 3 .7
2 .3

1 6 0 .5

1 6 3 .0

1 6 6 .6

1 7 2 .2

177.1

1 7 9 .9

1 8 4 .0

2 .3

1 .6

2 .2

3 .4

2 .8

1.6

2 .3

1 5 7 .7

161.1

1 6 4 .6

1 6 8 .4

1 7 3 .6

1 7 6 .8

1 8 0 .5

2 .6

2 .2

2 .2

2 .3

3.1

1 .8

2.1

1 5 6 .8

1 6 0 .4

1 6 3 .9

1 6 9 .6

1 7 6 .4

1 8 0 .3

1 8 4 .8

2 .6

2 .3

2 .2

3 .5

4 .0

2 .2

2 .5

1 3 2 .9

1 3 3 .0

1 3 1 .3

1 2 9 .6

1 2 7 .3

1 2 4 .0

1 2 0 .9

.9

.1

-1 .3

- 1 .3

- 1 .8

- 2 .6

- 2 .5

1 4 4 .3

1 4 1 .6

1 4 4 .4

1 5 3 .3

1 5 7 .6

- 1 .9

2 .0

6 .2

1 5 4 .3
0 .7

1 5 2 .9

0 .9

- .9

3.1

2 3 4 .6

2 4 2 .1

2 5 0 .6

2 6 0 .8

2 7 2 .8

2 8 5 .6

2 9 7 .1

2 .8

3 .2

3 .5

4.1

4 .6

4 .7

4 .0

2 3 7 .7

2 5 8 .3

2 7 1 .1

2 8 2 .6

2 9 3 .2

2 9 8 .7

4 .4

5 .7

8 .7

5 .0

4 .2

3 .8

1.9

1 5 7 .6

1 5 9 .7

1 6 3 .2

1 6 8 .9

1 7 3 .5

1 7 5 .9

1 7 9 .8

2 .3

1 .3

2 .2

3 .5

2 .7

1 .4

2 .2

H o u s in g :
In d e x ....................................................

1 4 1 .2

P e r c e n t c h a n g e ........................................

2 .7

2 .5

A p p a re l:
In d e x ....................................................

.

1 3 3 .7

P e r c e n t c h a n g e ........................................

1.4

0

. _

-.2

T ra n s p o rta tio n :
In d e x .................................................

1 3 0 .4

P e r c e n t c h a n g e ............................................

3.1

3 .0

M e d ica l c a r e :
In d e x ..................................................

_

2 0 1 .4

P e r c e n t c h a n g e ......................................

5 .9

4 .8

0 .0

O th e r g o o d s a n d s e r v ic e s :
In d e x ..........................................................

r- „

1 9 2 .9

P e r c e n t c h a n g e ........................................

5 .2

2 .9

142.1

1 4 5 .6

2 .8

2 .5

C o n s u m e r P ric e In d e x fo r U r b a n W a g e E a r n e r s
a n d C le ric a l W o rk e rs :
All ite m s :
In d e x ..................................................
P e r c e n t c h a n g e ...............................................

114

Monthly Labor Review


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Federal Reserve Bank of St. Louis

September 2004

_

2 .9

2 .9

40. Producer Price Indexes, by stage of processing
[1982= 100]

Finished goods...................................

2002

2003

July

Aug.

Sept.

140.8

140.5

147.7
152.0
134.8
141.1

148.9
154.0
134.3
141.0

151.1
157.0
134.8
141.1

150.7

151.3
134.3
140.8

156.3
135.0
141.3

151.7
157.9
134.6
141.2

134.1

134.1

134.1

134.5

136.2

137.1

137.9

139.8

141.9

142.7

143.8

129.8
137.4

130.5

130.7

135.9

137.3

138.0

138.6

137.5
127.5
125.8

136.4

137.5
129.5
125.8

131.9
138.4
140.2

134.1

141.6
137.2

130.9
140.7
137.9

133.2

141.8

138.9
141.1

141.1
141.7

146.1
143.2

151.9
145.7

130.5
125.8

131.2
125.8

132.9
125.9

137.0
126.2

170.0
126.2

143.5
127.0

1 5 1 .6
144.5
146.2
127.4

147.9
147.1
149.4
127.8

153.7

155.0
113.7

155.6
110.3
153.4

155.6
111.7

156.2

163.6

116.3
154.1
144.8

118.1
154.3
146.4

166.2
122.1
156.8
147.2

167.3
123.7
158.0

142.6

153.5
142.8

158.3
116.3
153.8
143.8

160.7

116.8
153.9
143.2

147.3

126.5
159.5
148.1

159.6
142.1
168.3

1 6 2 .3
13 7 .4
176.6

131.0
181.3

127.8

133.7

133.7

134.1

M aterials a n d c o m p o n e n ts
for m an u fa ctu rin g ..............................................

126.1

129.7

129.2

129.8

123.2
129.2
124.7

134.4

133.3

135.5

137.2

136.3
127.1
125.8

153.6
113.7

127.9
125.9

147.1

147.4
151.7
134.3
140.5

Intermediate materials,
supplies, and components.................

126.1

150.3

145.0
148.2
134.3
140.2

131.1
138.9

M aterials for d u ra b le m an u fa ctu rin g ..........
C o m p o n e n ts for m an u fa c tu rin g ...................

148.7

146.2
148.7

144.8
147.6
135.0

138.9

M aterials for food m an u fa c tu rin g ................
M aterials for n o n d u ra b le m an u fa ctu rin g ...

July15

148.7
152.0
154.5

145.3
147.6
148.0

146.2
149.4
135.6

145.5
150.4

139.1

D urable g o o d s ...............................................
C apital e q u ip m e n t..........................................

Junep

149.1
152.6
155.3

145.4

150.3

145.4
150.0
131.8
139.2

138.8
139.8
133.0

May13

147.3
150.2
152.5

Feb.

151.0

148.0

144.8
149.2
131.7

145.9

Apr.p

Mar.

Jan.

147.8
148.1

144.7
148.4
133.1
139.5

F in s h e d c o n s u m e r g o o d s
ex c lu d in g fo o d s ............................................
N o n d u rab le g o o d s le s s fo o d ....................

140.1

Dec.
144.5
146.7

145.9
146.3

143.3
145.3

Nov.
144.5
146.5
150.1

145.5
147.7

143.7

145.1
144.9

138.9
139.4

Oct.

144.0
146.4

143.0

F in ish ed c o n s u m e r g o o d s .............................
F in ish ed c o n s u m e r fo o d s ............................

2004

2003

Annual average
Grouping

128.6
125.8

147.9
127.6

152.0
152.1

M aterials a n d c o m p o n e n ts
for c o n s tru c tio n ..................................................
C o n ta in e rs ..............................................................
S u p p lie s ...................................................................

151.3
96 .3
152.1
138.9

153.6
112.6
153.7

155.2

167.8

153.5
141.7

111.5
153.2
141.9

131.3
111.5
142.7

134.7
119.0
142.8

138.3
128.1
141.1

137.0
125.7
141.4

141.1
124.7
149.5

147.8
117.1
167.3

148.3
121.0
164.9

149.7

154.1

130.8
159.8

135.1
164.1

142.2
103.4
148.2

142.7
104.7
148.7

144.5
106.0
150.6
154.9
151.8

144.4
105.7
150.6
154.7

145.7

151.0
155.5
151.7

142.8
101.0
150.9
155.5
151.4

144.9

152.8
149.9

143.8
103.2
151.4
156.1
152.0

142.8
100.4

152.3
149.8

142.7
105.2
149.0
153.3
149.7

107.0
151.3
155.7

151.7

152.0

109.3
152.0
156.7
152.2

147.2
113.7
152.9
158.1
152.5

1 4 7 .0
112.8
152.7
157.8
152.5

147.6
115.1
152.1
156.8
152.4

159.2

159.0

159.4

159.1

159.3

159.7

160.1

160.1

160.0

141.5

153.8
141.5

114.5
153.6
141.2

108.1
99 .5
111.4

135.3
113.5
148.2

132.6
107.6
148.2

138.3
8 8 .8
147.3
150.8
150.2

142.4

Crude materials tor further
F o o d stu ffs a n d fe e d s tu ffs .................................
C ru d e nonfo o d m a te ria ls ..................................

162.0

Special groupings:
F in ish ed g o o d s , excluding fo o d s ...................
F in ish ed e n e rg y g o o d s .....................................
F in ish ed c o n s u m e r g o o d s le s s e n e rg y ......
F in ish ed g o o d s le s s food a n d e n e rg y .........

102.0
149.0
153.1
150.5

F in ish ed c o n s u m e r g o o d s l e s s food
a n d e n e rg y ..........................................................

157.6

157.9

157.1

157.2

157.0

159.5

C o n s u m e r n o n d u ra b le g o o d s le s s food
a n d e n e rg y ........................................................

177.5

177.9

177.8

178.0

177.8

178.6

178.5

178.9

179.7

179.1

179.0

180.2

180.6

180.3

180.5

128.5
115.5
95 .9
134.5

134.2
125.9
111.9
137.7

134.2
124.4

134.6
125.0

134.5
128.4

134.2
134.8

134.7
134.1

136.5
132.2

137.4

114.3
137.5

112.8
138.0

109.5
138.8

110.9
139.0

115.8
169.8

115.3
142.1

142.8
144.6
122.7

144.0
143.2
125.4

138.5

139.8
143.0
117.1
144.0

141.7

132.5
115.3
141.0

138.2
136.4

113.0
137.4

134.4
131.9
110.7

146.1

146.8

139.2

139.5

140.4

141.6

142.6

144.2

145.5

1 4 6 .4

147.1

141.8
136.2
170.1

163.5

156.7
138.2
187.2

147.1

156.3
147.8
185.3

165.3
151.0
178.3

178.0
147.1
176.7

146.5
191.6

In te rm e d ia te m ateria ls le s s fo o d s

In term ed iate e n e rg y g o o d s .............................

a n d e n e rg y .........................................................

135.8

138.5

138.3

138.4

138.7

139.0

102.0
108.7
135.7

147.2
123.4
152.5

148.7

139.7

132.5

118.0
148.8

121.7
151.8 I

138.2
128.2
155.5

134.3

C ru d e m ateria ls l e s s e n e rg y .........................
C ru d e nonfo o d m a te ria ls le s s e n e rg y ........

135.9
159.5

135.5
164.8


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Federal Reserve Bank of St. Louis

133.3
179.3

146.6
192.2

Monthly Labor Review

147.6
121.1
145.5

September 2004

178.3

115

Current Labor Statistics:

Price Data

41. Producer Price Indexes for the net output of major industry groups
[December 2003 = 100, unless otherwise indicated]________
NAICS

2003

Industry

Dec.
-

211
212
213
311
312
313
315
316
321
322
323
324
325
326
331
332
333
334
335
336
337
339

2004
Jan.

Feb.

Total mining industries (December 1984=100)...

136.6

Oil a n d g a s ex tra c tio n (D e c e m b e r 1985= 100)
M ining, e x c e p t oil a n d g a s ....................

1fifi 1

Mining s u p p o rt ac tiv ities......................

100.0

Total manufacturing industries (December 1984=100).
F o o d m an u fa ctu rin g (D e c e m b e r 1 9 84= 100)
B e v e ra g e a n d to b a c c o m a n u fa c tu rin g ........
T extile m ills....................................

137.7
141.1

181.1
105.9
100.8
138.9

139.3

140.3

139.3

A pparel m a n u fa c tu rin g ..........................
L e a th e r a n d allied p ro d u c t m a n u fa ctu rin g (D e c e m b e r 1 9 84= 100)
W ood p ro d u c ts m a n u fa c tu rin g ....................
P a p e r m a n u fa c tu rin g ...............................

Mar.

99 .8
143.4
100.0

143.3

143.6

Printing a n d re la te d s u p p o rt ac tiv ities...............

100.0

100.2

P etro leu m a n d c o a l p ro d u c ts m a n u fa ctu rin g (D e c e m b e r 1 9 8 4 = 1 0 0 )...
C h em ical m an u fa c tu rin g (D e c e m b e r 1 9 84= 100)

1 1 7 .5
165.3

13 1 .5
167.0

13 0 .7

P la s tic s a n d ru b b e r p ro d u c ts m a n u fa ctu rin g (D e c e m b e r 1 9 8 4 = 1 0 0 )...
P rim ary m etal m an u fa ctu rin g (D e c e m b e r 1 9 84= 100)

128.9
124.0

129.4

F a b ric a te d m etal p ro d u c t m a n u fa ctu rin g (D e c e m b e r 1 9 8 4 -1 0 0 )
M achinery m a n u fa c tu rin g .........................
C o m p u te r a n d ele ctro n ic p ro d u c ts m a n u fa c tu rin g .........
Electrical eq u ip m e n t, a p p lia n c e , a n d c o m p o n e n ts m an u fa ctu rin g .
T ra n s p o rta tio n eq u ip m e n t m a n u fa c tu rin g ............

128.8
121.4
133 7
100.0
100.0
100.0

F u rn itu re a n d re la te d p ro d u c t m a n u fa c tu rin g (D e c e m b e r 1 9 8 4 = 1 0 0 )....
M isc e lla n e o u s m a n u fa c tu rin g ...............

147.6
100.0

100.0

14 3 .8

Apr.p

Mayp

Junep

July**

13 8 .5

145.0

153.8

168.6
107.1

180.1
1 0 7 .5

195.3

19 6 .9

99 .9

1 0 0 .5

107.8
102.2

10 8 .5
10 3 .5

100.9
10 1 .6
9 9 .6

1 5 5 .2

141.8

143.4

145.8
101.7

14 8 .9
101.2

10 0 .5
100.0

100.8
100.0

148.3
1 0 1 .3
1 0 1 .4
9 9 .8

1 4 3 .5
108.1

143.6
110.2

143.1
108.4

1 4 3 .6
1 0 6 .7

100.0
101.1

102.1

1 4 6 .7

1 0 0 .9
100.9

1 0 1 .0

1 0 3 .4
1 0 1 .3

134.3

14 1 .5
1 6 9 .2

152.3
170.1

143.9
171.7

15 2 .0
1 7 2 .0

129.6

130.1
136.9

131.1

1 3 1 .4

145.1

1 4 7 .6
1 4 2 .6
102.1
9 9 .0
10 3 .7
1 0 0 .4

1 0 0 .4
167.9

134.6

1 2 8 .5
135.7

13 7 .5

9 9 .8
100.2

9 9 .5
100.7

99 .3
101.8

1 3 8 .6
101.3
100.1
10 2 .7

100.2
1 4 7 .4
100.5

100.1

130.6
141.3
140.7
10 1 .6
9 9 .9
1 0 3 .5
1 0 0 .4

148.7

149.0
100.8

149.1
101.1

150.9
100.9

101.7
100.6
94.1
98 .7

103.3
101.1
9 5 .8
9 8 .3
5 0 .3
106.3

14 2 .0
1 0 1 .7
9 9 .3
103.6
10 0 .6
152.9
1 0 1 .0

152.1
1 0 1 .3

Retail trade
441
442
443
446
447
454

M otor v eh ic le a n d p a r ts d e a l e r s ............
F u rn itu re a n d h o m e fu rn ish in g s s t o r e s ......
E lec tro n ics a n d a p p lia n c e s t o r e s ..............
H ealth a n d p e rs o n a l c a r e s t o r e s ...........

1 0 0 .0
100.0
100.0
100.0

G a s o lin e s ta tio n s (J u n e 2 0 0 1 = 1 0 0 )......
N o n sto re re ta ile rs ..........................

4 7 .9
100.0

4 5 .5

52 .6
108.6

162.7

163.3

162.1
99.7

9 9 .5
1Q0 ^

1 0 4 .3
10 2 .8
9 8 .9
9 7 .5
5 9 .0
106.8

1 0 4 .0
1 0 2 .5
9 9 .9
9 9 .5
4 6 .0
106.1

Transportation and warehousing
481
483
491

Air tra n s p o rta tio n (D e c e m b e r 1 9 9 2 = 1 0 0 ).........
W a te r tra n s p o r ta tio n .....................
P o s ta l s e rv ic e (J u n e 1 9 8 9 = 1 0 0 ).................

155.0

1 ^ .0

162.2

163.1

155.0

10 0 .3
155.0

1 0 0 .3
1 5 5 .0

1 5 5 .0

102.0

103.3

106.7

107.1

114.3
100.0
119.7

114.2
9 9 .8
119.7
140.7

11 4 .4
100.2
1 1 9 .7

1 1 4 .5
1 0 0 .0
11 9 .9
14 2 .3
102.1
9 9 .9

1 6 3 .4
1 0 0 .4

Utilities
221

U tilities......................................

101.7

Health care and social assistance
6211
6215
6216
622
6231
62321

O ffice of p h y s ic ia n s (D e c e m b e r 1 9 9 6 = 1 0 0 )...........
M edical a n d d ia g n o stic la b o ra to rie s ...........
H om e h ea lth c a r e s e r v ic e s (D e c e m b e r 1 9 96= 100)
H o sp itals (D e c e m b e r 1 9 9 2 = 1 0 0 )..............
N ursing c a r e facilities....................

112.8
100.0
119.0
137.6

100.3
1 1 9 .5
139.5

R e sid en tial m en tal re ta rd a tio n facilities.................

100.0

100.1

100.0
100.0

100.9

114.1
119.6

1 1 9 '6

140.3
101.6
9 9 .9

101.6
100.6

140.8
10 1 .3
9 9 .9

Other services industries
511
515
517
5182
523
53112
5312
5313
5321
5411
541211
5413
54181
5613
56151
56172
5621
721

P ublishing in d u stries, e x c e p t In tern et ....
B ro ad c astin g , e x c e p t In te rn e t.................
T e le c o m m u n ic a tio n s .....................
D a ta p ro c e s s in g a n d re la te d s e r v ic e s ......
S ecu rity , co m m odity c o n tra c ts , a n d like activity........
L e s s o r s o r n o n re s id e n ta l buildings (e x c e p t m in iw are h o u se)
O ffices of re al e s t a t e a g e n ts a n d b ro k e rs .........
R eal e s t a t e s u p p o rt a c tiv ities..................
A utom otive e q u ip m e n t rental a n d le a sin g (J u n e 2 0 0 1 = 1 0 0 )
Legal s e r v ic e s (D e c e m b e r 1 9 9 6 = 1 0 0 )......
O ffices of certified public a c c o u n ta n ts .........
A rchitectural, e n g in e e rin g , a n d re la te d s e r v ic e s
(D e c e m b e r 1 9 9 6 = 1 0 0 )..................
A dvertising a g e n c i e s ...............................
E m p lo y m en t s e r v ic e s (D e c e m b e r 1996= 100)
T ravel a g e n c i e s ...........................
J a n ito rial s e r v ic e s ........................
W a s te c o llec tio n ..............................
A c co m m o d atio n (D e c e m b e r 1996= 100)

100.0
100.0

116

Monthly Labor Review

September 2004

101.3
1 0 3 .6

9 9 .9
100.7
102.3

100.0
9 9 .3
10 2 .9

9 9 .0
1 0 2 .5

9 9 .6

101.8

102.3

1 0 1 .5

1 0 3 .2

100.7

100.9
102.0
104.4

100.9
9 7 .6
10 5 .2

101.1
1 0 1 .5
10 9 .7

1 0 1 .8
1 0 0 .3
9 9 .7

9 9 .9
101.8

102.0

100 0

99.1

9 9 .4

100.0

100.0

100.0
109 1
1 2 6 .5

107.9
131.4

109.8

101.1
107.4

100.9
101.6
105.4

100.0

100.8

100 7

100.8

13 1 .9
101.2

131.8
101.3

131.8
101.1

1 3 2 .0
1 0 1 .3

125.3
100.0
112.1

112.1

1 1 2 .5

113.2

126.6
99 .9
114.0

126.3
100.1
113.4

126.4
100.1
114.1

124.9

9 8 .6
100.5
101.9
124.0

9 8 .3
1 0 0 .5
101.9
125.0

9 6 .9
101.1
101.8
124.0

1 2 6 .9
10 0 .3
114.8
96.1
100.8
10 1 .3
1 2 8 .6

120.5

122.2

NOTE. D a ta reflect t h e c o n v e rs io n to th e 2 0 0 2 v ersio n of th e North A m erican Industry C lassification S y ste m
(NAICS), re p la c in g th e S ta n d a rd Industrial C lassificatio n (SIC) s y s te m .


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Federal Reserve Bank of St. Louis

101.4
102.4

101.7

101.5
100.8
100.2
100.2
101.8

123.6

42. Annual data: Producer Price Indexes, by stage of processing
Li

=

i uuj
Index

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

F in is h e d g o o d s
1 2 4 .7

1 2 5 .5

1 2 7 .9

1 3 1 .3

1 3 1 .8

1 3 0 .7

1 3 3 .0

1 3 8 .0

1 4 0 .7

1 3 8 .9

1 4 3 .3

1 2 5 .7

1 2 6 .8

1 2 9 .0

1 3 3 .6

1 3 4 .5

1 3 4 .3

135.1

1 3 7 .2

1 4 1 .3

140.1

1 4 6 .0

7 8 .0

7 7 .0

78.1

8 3 .2

8 3 .4

75.1

7 8 .8

94.1

9 6 .8

8 8 .8

1 0 2 .0

1 3 5 .8

137.1

1 4 0 .0

1 4 2 .0

1 4 2 .4

1 4 3 .7

146.1

1 4 8 .0

1 5 0 .0

1 5 0 .2

1 5 0 .5

1 1 6 .2

1 1 8 .5

1 2 4 .9

1 2 5 .7

1 2 5 .6

1 2 3 .0

1 2 3 .2

1 2 9 .2

1 2 9 .7

1 2 7 .8

1 3 3 .7

1 1 5 .6

1 1 8 .5

1 1 9 .5

1 2 5 .3

1 2 3 .2

1 2 3 .2

1 2 0 .8

1 1 9 .2

1 2 4 .3

1 2 3 .3

1 3 4 .4

8 4 .6

8 3 .0

84.1

8 9 .8

8 9 .0

8 0 .8

8 4 .3

1 0 1 .7

104.1

9 5 .9

1 1 1 .9

1 2 3 .8

127.1

1 3 5 .2

1 3 4 .0

1 3 4 .2

1 3 3 .5

133.1

1 3 6 .6

1 3 6 .4

1 3 5 .8

1 3 8 .5

In te r m e d ia te m a te r ia ls , s u p p lie s , a n d
c o m p o n e n ts

C ru d e m a te r ia ls fo r fu r th e r p r o c e s s in g

O t h e r ...................................................................................................


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Federal Reserve Bank of St. Louis

1 0 2 .4

1 0 1 .8

1 0 2 .7

1 1 3 .8

111.1

9 6 .8

9 8 .2

1 2 0 .6

1 2 1 .3

1 0 8 .1

1 3 5 .3

1 0 8 .4

1 0 6 .5

1 0 5 .8

1 2 1 .5

1 1 2 .2

1 0 3 .9

9 8 .7

1 0 0 .2

1 0 6 .2

9 9 .5

1 1 3 .5

7 6 .7

72.1

6 9 .4

8 5 .0

8 7 .3

6 8 .6

7 8 .5

122.1

1 2 2 .8

1 0 2 .0

1 4 7 .5

94.1

9 7 .0

1 0 5 .8

1 0 5 .7

1 0 3 .5

8 4 .5

91.1

1 1 8 .0

1 0 1 .8

1 0 1 .0

1 1 6 .8

Monthly Labor Review

September 2004

117

Current Labor Statistics:

Price Data

43. U.S. export price indexes by Standard International Trade Classification
[2000 =

100]__________________

SITC
Rev. 3
0
01
04
05
2
22
24
25
26
28
3
32
33
5
54

July

Aug.

Sept.

M eat a n d m ea t p re p a ra tio n s ......
C e re a ls a n d c e re a l p re p a ra tio n s .....

104.6
115.4

V e g e ta b le s , fruit, a n d n u ts, p re p a re d fresh or dry

101.2

108.9
115.7
99.7

103.9
124.8

102.3
109.2

Crude materials, inedible, except fuels......
O ils e e d s a n d o le a g in o u s fruits........
C ork a n d w o o d .......................

9 0 .6
8 5 .5
106.2
112.3

8 5 .3
107.0
117.8

C oal, c o k e , a n d b riq u e tte s ..............

109 8
111.2

P etro leu m , p etroleum p ro d u c ts, a n d re la te d m ateria ls...

P ulp a n d w a s te p a p e r...........
T extile fib ers a n d th e ir w a s te ..........
M etalliferous o re s a n d m etal s c r a p .........

Mineral fuels, lubricants, and related products.

Chemicals and related products, n.e.s.

124.2
101.4

119 1

106.2

111.2

116.3
150.9

120.2
157.2

122.3
160.9

129.0
181.6

132.8
197.1

94 .5
91 .7

9 5 .6

121.2
136.6

123.7
148.9

156.8

96.5
94.2
121.9
171.4

97 .6
98.8
115.9
176.2

125.4
168.5
98 .3

129.5
184.5

92 .5
91 .9

116.9
152.5
93.7
91 .7

120.5

119.3

92 .5
122.2

132.4
199.0
98.2
100.4
114.9

100.8
108.7

170.1

166.3

9 9 .0
100.0
101.5
176.5

135.1

130.3

136.2

123.0

123.2

116.8

114.7

120.1

119.8

135.0

127.7

133.2

99 .6

100.0
105.5

100.3
105.4

100.7

100 0

101.4

106.5
99 .4

105.8
100.1

105.6
105.7

105.8
105.8

106.8
107.9

96 .5
97 .2
102.6

98.3
96 .8
105.0

105.5
104.3
102.1
9 7 .4
104.8

105.5
105.7
104.1

95.8
97.1
102.5

104.0
105.3
104.2
100.9
97 .2
105.2

104.9

105.9
98 .9

102.9
105.4

102.2
96 .9
104.8

104.4
103.1
96.7

104.3
103.5
9 6 .4
104.8

104.3
104.3
9 7 .3
104.6

100.7

100.8

101.7

103.0

104.1

105.6

106.5

106.8

108.3

109.5

109.9

110.4

110.9

110.4

110.9

110.8

111.4

112.0

99 .7

97.6
9 9 .8
8 4 .5

97 .9
99 .7
8 5 .9

9 7 .8
99 .6
90 .9

9 7 .9
99.7
94.1

98 .7
99.7
98.1

99 .0
99.5
97 .6

9 9 .3
100.0
9 5 .4

101.6
100.1
9 5 .4

A f\r\ r\

98 .5
100.4
79 .8

100.2

9 9 .5
01 .0

Monthly Labor Review

109.5

122.8
128.6
112.1

146.0
113.3

112.9

109.5


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Federal Reserve Bank of St. Louis

120.7

127.3
141.3
111.6

106.2

110.1

Professional, scientific, and controlling
instruments and apparatus........

124.1

101.2

100.2

87

126.7
127.7

139.6
110.1

126.1
127.6
147.7

104.1

100.0

77
78

122.7
127.1

104.2

99 .9

C o m p u te r e q u ip m e n t a n d office m a c h in e s
T ele co m m u n ic atio n s a n d s o u n d re co rd in g an d
re p ro d u cin g a p p a ra tu s a n d e q u ip m e n t........
Electrical m ac h in e ry a n d eq u ip m en t
R o a d v e h ic le s .....................

119.9
125.0
135.2
108.4

113.0

101.9

75
76

July

117.0
122.8
131.6
103.1

105.9

101.9

P o w er g e n e ra tin g m ac h in e ry a n d eq u ip m en t
M achinery sp e c ia liz e d for p articular in d u stries..
G e n e ra l industrial m a c h in e s a n d p a rts , n .e .s .,
a n d m a c h in e p a r ts ..................

June

116.5
123.0
130.8
103.2

110.7

Manufactured goods classified chiefly by materials

Machinery and transport equipment.......

May

115.2
125.6
125.6
102.8

106.3

6

N onm etallic m ineral m a n u fa c tu re s , n .e .s .............................
N o nferrous m e ta ls ........................

Apr.

108.2

98.2

66
68

Mar.

108.7

97 .6
94 .8
9 8 .4

R u b b e r m a n u fa c tu re s , n .e .s ...........

Feb.

114.9
111.2

97 .5
95.1
9 8 .4
102.0

P a p e r, p a p e rb o a rd , a n d a rtic le s of p a p e r, pulp,
a n d p a p e rb o a r d ..........................

Jan.

121.1

105.8

62

!4

Dec.

119.9

E ssen tial oils; polishing a n d cle an in g p re p a ra tio n s ..
P la s tic s in prim ary f o r m s ..........
P la s tic s in n o n prim ary form s....
C h em ical m a te ria ls a n d p ro d u c ts, n .e s

64

103.2

Nov.

128.5
129.6

55
57
58
59

7

2004

Oct.

Food and live animals...........

M edicinal a n d p h a rm a c e u tic a l p ro d u c ts....

71
72
74

118

2003

Industry

100.3

9 9 .5

98.0

97 .9

97 .9

97.7

107.4
103.2

107.4
103.2

107.5
103.1

107.9
103.1

102.5
8 8 .2

102.5
88 .0

-

T

108.5
103.3
10-1

87 .8

87 .9

88 .0

9 3 .4

9 3 .4
89 .8

9 3 .3
8 9 .4
101.4

9 2 .8
8 8 .6

92.2

89 .8
101.3

102.4

102.3

102.2

102.1

102.3

September 2004

104.3

104.8

97 .8

9 7 .9

98.1

98.2

98.4

98.4

98 .4

9 8 .5

108.7
103.4

109.3
103.9

109.4
104.0

109.4
104.2

108.7
105.1

108.7
105.5

108.7
105.5

108.9
105.6

102.8
8 8 .6

103.3
8 7 .7

103.5
88.2

104.0
88 .4

104.5
88.8

104.8
8 8 .8

105.0
8 8 .7

105.4
88 .3

92 .0
88.1
101.5

92.6
88 .0
101.7

9 2 .5
8 8 .3
101.9

9 2 .4

92.2

92 .0

9 1 .9

8 8 .6
101.9

88.5
102.3

88 .5
102.3

8 8 .3
102.4

9 1 .8
8 8 .3
102.6

102.3

102.2

102.3

102.3

102.2

102.1

102.0

101.8

44. U.S. import price indexes by Standard International Trade Classification
2004

2003

SITC
Rev. 3

Industry
July

01
03

Aug.

Sept.

Oct.

Nov.

Dec.

Jan.

Feb.

Apr.

May

June

July
10 7 .7
134.2

100.2

9 9 .5

100.0

100.3

100.0

101.0

102.2

1 0 4 .7

10 5 .4

10 6 .4

106.1

106.6

106.6

108.2

112.8

115.2

117.2

120.4

117.7

1 1 8 .0

120.4

1 2 1 .7

125.1

1 2 6 .4

8 6 .0

F ish a n d c r u s ta c e a n s , m ollusks, a n d o th e r

05
07

Mar.

8 3 .5
106.9

8 2 .3
1 0 5 .5

7 9 .3
108.9

79 .2
109.4

8 3 .3
11 1 .3

8 4 .0

1 1 2 .3

8 0 .0
11 5 .7

85.1

105.0

7 9 .8
106.4

84.1

1 0 9 .5

106.1

105.9

10 3 .3

9 5 .3

9 6 .6

9 8 .6

9 5 .5

93.1

9 6 .0

100.1

1 0 1 .9

1 0 1 .7

10 3 .6

1 0 2 .4

107.1

102.7

10 5 .0

1 0 5 .3

10 5 .3

1 0 5 .4

10 5 .3

105.3

10 5 .5

10 5 .5

1 0 5 .7

10 5 .6

105.6

8 2 .2

78.2

C o ffe e, te a , c o c o a , s p ic e s , a n d m a n u fa c tu re s

104.1

104.0

104.0

104.3

104.4

104.4

104.7

11

104.0

103.9

103.9

104.2

104.2

1 0 4 .3

104.9

105.2

100.7

100.5

106.1

104.2

104.5

107.9

109.5

114.1

120.0

122.9

1 2 7 .3

1 2 5 .8

1 2 5 .7

24

100.1
9 3 .6
10 0 .3
9 9 .4

9 9 .3
9 1 .9
102.9

113.0
9 0 .4
10 3 .7

106.2

103.2

9 0 .8
104.3

91.9
108.7

108.0
9 2 .8
1 1 5 .3

108.9
93 .3
124.2

1 1 5 .7
9 1 .9
13 4 .6

1 2 3 .3
9 5 .4
148.0

1 2 7 .8
1 0 0 .8
148.2

1 3 9 .0
103.4

136.1
10 6 .5
14 0 .4

132.1
10 8 .0
144.4

9 6 .8

9 5 .7

95.1

9 4 .8

9 9 .6

9 8 .9

9 9 .5

9 9 .7

9 9 .3

1 2 0 .8

121.1
12 0 .3

1 3 1 .7

25
28
29

33
34

C ru d e an im al a n d v e g e ta b le m ateria ls, n .e .s ......................

P e tro le u m , p etro le u m p ro d u c ts , a n d re la te d m ateria ls....

52
53
54
55
57
58
59
6
62
64

E s s e n tia l oils; polishing a n d c le a n in g p re p a ra tio n s ..........

Manufactured goods classified chiefly by materials....

68
69

75
76

1 0 1 .5
9 9 .4

121.5

108.8

114.4

100.0
105.4

99 .2
106.0

9 8 .0
103.1

9 8 .3
102.5

9 9 .2
1 0 5 .4
9 7 .7

9 9 .0
10 4 .3
1 0 1 .3
9 3 .3

9 1 .8

10 1 .3
100.1
106.2

103.3
10 2 .3
106.6

108.2
106.9
113.9

100.2

100.8

101.1

108.8

101.9

98.1
102.3

111.9
99 .0
103.4

114.0
99 .6
1 0 3 .4

103.1
10 1 .4
9 1 .9

9 1 .6
102.7
1 0 1 .4
9 1 .8

91 .2
105.6
101.7
9 2 .3

9 1 .6
105.6
1 0 1 .7
93.1

9 1 .6
10 5 .5
101.8
9 3 .3

9 4 .9

9 5 .4

9 5 .7

9 6 .5

97 .4

9 8 .6

9 8 .5

9 8 .5

9 8 .5

98 .6

9 3 .2
9 7 .9

9 4 .9

9 4 .5

94 .7

9 7 .8

97.9

7 8 .0
9 8 .2

79.1
9 8 .4

9 7 .8
8 0 .7

82 .0
9 8 .7

85.1
99.1

9 8 .5

.


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1 3 1 .6

1 3 2 .7
1 3 1 .7

12 3 .3

1 2 9 .5

14 0 .0

13 7 .3

103.0
11 9 .3

1 0 3 .4

1 0 3 .8

1 0 3 .5

1 0 3 .4

1 0 3 .8

105.6

120.6
9 9 .7
10 7 .7

1 2 0 .5
9 9 .5
108.1
9 3 .7

1 1 5 .9
100.6
1 0 7 .7

117.2
1 0 0 .8
10 7 .3

1 1 9 .3
1 0 1 .0
107.2

126.7
101.2
108.1

9 3 .5
10 5 .5
102.9
9 5 .4

9 3 .4

106.9
102.9
9 5 .8

1 0 5 .8
1 0 2 .8
95.1

9 3 .5
104.6
102.1
9 5 .2

9 3 .6
108.1
1 0 2 .7
9 5 .6

9 9 .9
107.2
9 2 .7

120.0
122.9

104.4
102.1
9 4 .3

9 3 .3
105.2
1 0 2 .4
9 4 .9

9 7 .8

98 .9

1 0 1 .4

103.6

10 5 .6

106.9

106.1

106.1

9 8 .8

99 .0

9 9 .2

9 9 .7

9 9 .9

100.0

100.1

100.0

94 .2

93 .7

94.1

9 4 .5

98.1
8 7 .7

9 8 .5

9 8 .9

9 5 .0
9 9 .0

9 4 .8

98.1

9 5 .5
9 9 .4

9 5 .6
9 9 .6

9 6 .3
9 9 .8

9 2 .3
99 .7

9 7 .0

102.6

10 5 .8

101.1

1 0 2 .3

106.1
1 0 2 .3

10 1 .8
1 0 2 .3

10 1 .9

1 0 0 .3

9 9 .5

9 9 .3

1 0 2 .6

9 5 .7

9 5 .6

9 5 .5

9 5 .3

9 5 .4

9 5 .3

9 5 .4

9 5 .5

9 5 .5

9 5 .2

9 5 .2

95.1

95 .0

102.6

102.5

102.2

102.4

10 3 .3

103.6

10 4 .9

10 6 .4

106.7

10 6 .5

106.6

10 6 .4

1 0 7 .3

100.8

100.4

100.2

100.4

100.9

101.2

1 0 1 .8

8 0 .6

8 0 .6

8 0 .5

78.6

78 .5

7 8 .2

7 8 .0

1 0 2 .5
78 .0

1 0 3 .3
7 7 .7

1 0 3 .5
7 6 .5

10 3 .6
7 6 .4

1 0 3 .5
7 5 .4

1 0 4 .5
74 .9

8 8 .7
96.1
100.7

8 8 .8
96 .0
100.7

8 8 .6
9 6 .0
100.6

87 .7
95 .9
101.3

8 7 .5
9 6 .0
101.4

86 .7
9 5 .3
101.6

86 .4
9 5 .4

85.1
9 5 .6
102.0

8 4 .9
9 4 .9
102.2

8 4 .9
9 4 .9
1 0 2 .3

8 4 .8
9 4 .8
10 2 .4

8 4 .5
9 4 .4

101.9

8 5 .4
9 5 .7
10 2 .0

1 0 2 .5

99 .9

9 9 .8

9 9 .9

100.0

100.1

100.1

1 0 0 .5

1 0 0 .5

100.6

100.6

1 0 0 .6

1 0 0 .4

1 0 0 .4

100.1

99 .6

9 9 .2

9 9 .3

99 .8

99 .9

99 .9

1 0 0 .3

100.0

9 9 .4

9 9 .3

9 9 .0

9 8 .0

P h o to g ra p h ic a p p a ra tu s , e q u ip m e n t, a n d su p p lie s,
a n d o ptical q o o d s . n .e .s .......................................................... .

101.2

1 1 7 .7
11 4 .5
137.1

T e le c o m m u n ic a tio n s a n d s o u n d reco rd in g a n d

8E

9 8 .0
1 3 2 .0
13 0 .5

1 1 7 .3
11 4 .0
138.0

G e n e ra l industrial m a c h in e s a n d p a rts , n .e .s .,

77
76

se

106.5
105.6

P a p e r , p a p e rb o a r d , a n d artic le s of p a p e r, pulp,

66

72
74

106.0
10 3 .4

14 3 .5
102.1

Monthly Labor Review

September 2004

119

Current Labor Statistics:

Price Data

45. U.S. export price indexes by end-use category
[2000 = 100]
2003

Category
July

ALL COMMODITIES..........................................
F o o d s , f e e d s , a n d b e v e r a g e s ...........................................

Aug.

Sept.

9 9 .4

9 9 .4

1 1 0 .8

1 0 9 .4

2004

Oct.

Nov.

Dec.

Jan.

Feb.

Mar.

Apr.

May

June

July

9 9 .8

1 0 0 .0

1 0 0 .5

1 0 0 .8

1 0 1 .5

1 0 2 .2

1 0 3 .0

1 0 3 .7

104.1

1 0 3 .4

1 0 3 .8

1 1 5 .3

1 1 7 .2

1 2 1 .4

1 2 2 .4

123.1

1 2 5 .6

1 3 0 .5

1 3 4 .8

1 3 5 .6

1 2 9 .3

1 2 8 .3

1 2 2 .8

1 2 3 .8

1 2 4 .6

1 2 7 .2

1 3 2 .4

1 3 7 .0

1 3 8 .0

1 3 1 .2

130.1

A g ric u ltu ral fo o d s , f e e d s , a n d b e v e r a g e s ...............

1 1 1 .0

1 0 9 .5

1 1 6 .3

1 1 8 .4

N o n a g ric u ltu ra l (fish, b e v e r a g e s ) fo o d p r o d u c ts .

1 0 9 .3

1 0 9 .5

1 0 6 .5

1 0 5 .6

1 0 7 .5

1 0 8 .5

1 0 9 .5

1 1 0 .7

112.1

1 1 3 .4

1 1 2 .6

1 1 1 .2

1 1 1 .3

In d u s tria l s u p p l ie s a n d m a te r ia ls ....................................

9 9 .6

1 0 0 .0

1 0 0 .2

1 0 1 .0

1 0 1 .7

1 0 2 .5

105.1

1 0 6 .4

108.1

109.1

1 1 0 .2

1 0 9 .5

1 1 1 .0

A g ric u ltu ral in d u s tria l s u p p lie s a n d m a te r ia ls ........

1 0 4 .7

1 0 5 .5

1 0 7 .3

1 1 3 .3

1 1 9 .0

1 1 7 .5

1 1 8 .6

1 1 6 .6

1 1 7 .2

1 1 4 .8

1 1 3 .7

1 1 0 .7

1 0 8 .2

F u e ls a n d lu b r ic a n ts ..........................................................

9 7 .0

1 0 0 .4

9 7 .6

9 7 .5

9 6 .4

9 9 .0

106.1

1 0 6 .5

1 0 8 .9

1 0 9 .6

1 1 7 .5

114.1

1 1 7 .5

N o n a g ric u ltu ra l s u p p l ie s a n d m a te ria ls ,
e x c lu d in g fuel a n d b u ild in g m a t e r ia l s ......................

1 0 0 .0

100.1

1 0 0 .5

101.1

1 0 1 .7

S e l e c te d b u ild in g m a t e r ia l s .............................................

1 0 2 .5

1 0 4 .7

1 0 6 .4

108.1

1 0 9 .4

9 7 .5

9 8 .0

1 0 9 .8

9 8 .4

1 0 9 .6

1 1 1 .3

9 8 .8

99.1

9 9 .5

9 8 .7

1 0 0 .9

1 0 2 .3

1 0 3 .4

1 0 3 .9

1 0 3 .4

1 0 2 .8

C a p ita l g o o d s ....................................................................

9 7 .7

9 7 .7

9 7 .5

9 7 .3

9 7 .3

E lec tric a n d e le c tric a l g e n e r a tin g e q u ip m e n t.

9 7 .5

9 7 .5

9 7 .8

9 8 .0

98.1

1 0 1 .8

1 0 1 .6

98.1

1 0 1 .7

98.1

9 8 .2

1 0 1 .7

1 0 1 .7

N o n e le c tric a l m a c h in e r y ...........................................

1 0 1 .7

1 0 2 .0

1 0 1 .9

1 0 2 .0

9 4 .6

1 0 1 .7

1 0 1 .6

9 4 .5

1 0 1 .9

9 4 .3

9 3 .9

102.1

9 3 .9

94.1

9 3 .9

9 4 .3

9 4 .5

9 4 .6

9 4 .7

9 4 .5

9 4 .5

1 0 1 .8

1 0 1 .8

1 0 1 .8

1 0 1 .9

1 0 1 .9

1 0 1 .8

1 0 1 .9

1 0 2 .0

1 0 1 .9

1 0 2 .2

1 0 2 .3

1 0 2 .3

1 0 2 .5

A u to m o tiv e v e h ic le s , p a r ts , a n d e n g i n e s .
C o n s u m e r g o o d s , e x c lu d in g a u to m o tiv e ..

9 9 .6

9 9 .4

9 9 .4

9 9 .8

1 0 0 .0

N o n d u r a b le s , m a n u f a c t u r e d ......................

9 9 .9

1 0 0 .2

100.1

1 0 0 .2

1 0 0 .4

9 8 .8

9 8 .7

1 0 0 .5

1 0 0 .4

9 8 .5

9 9 .0

1 0 0 .9

9 9 .4

D u r a b le s , m a n u f a c t u r e d ...............................

9 9 .2

9 9 .9

9 9 .9

9 9 .9

1 0 0 .2

100.1

9 9 .9

100.1

100.1

9 9 .9

1 0 0 .3

1 0 0 .8

1 0 0 .3

1 0 0 .3

100.1

1 0 0 .0

100.1

1 0 0 .5

1 0 0 .6

1 0 0 .6

1 0 0 .9

A g ric u ltu ral c o m m o d itie s ..................................

1 0 9 .9

1 0 8 .8

1 1 4 .7

1 2 2 .7

9 8 .7

9 8 .6

9 8 .8

99.1

1 2 3 .5
9 9 .8

1 2 5 .3
1 0 0 .4

1 2 9 .7

9 8 .6

1 1 7 .5
9 8 .7

1 2 2 .2

N o n a g ric u ltu ra l c o m m o d itie s .........................

1 3 3 .0
1 0 1 .4

1 3 3 .7
1 0 1 .7

1 2 7 .5
1 0 1 .5

126 2
1 02.1

120

Monthly Labor Review


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September 2004

1 0 0 .9

46. U.S. import price indexes by end-use category
r? o n o -io o i

2004

2003
C ategory
July

Nov.

Dec.

N o n m a n u f a c tu r e d c o n s u m e r g o o d s ..............................

Apr.

June

May

July

9 6 .7

9 6 .2

9 6 .3

9 6 .8

9 7 .5

9 9 .0

9 9 .4

1 0 0 .2

1 0 0 .4

1 0 1 .9

1 0 1 .8

1 0 2 .0

1 0 2 .4

1 0 3 .2

1 0 3 .7

1 0 5 .3

1 0 5 .9

1 0 7 .2

1 0 6 .9

1 0 6 .9

1 0 7 .5
1 1 4 .2

1 0 1 .5

1 0 1 .3

1 0 1 .8

1 0 1 .9

1 0 7 .7

1 0 7 .6

1 0 8 .3

1 0 9 .0

1 0 9 .7

1 1 0 .9

1 1 2 .0

1 1 3 .4

1 1 3 .0

1 1 4 .2

114.1

1 1 4 .2

8 8 .0

8 7 .4

8 7 .6

8 6 .3

8 6 .0

8 6 .0

85.1

8 7 .2

90.1

9 1 .7

9 0 .7

9 0 .5

9 2 .5

1 0 0 .7

1 0 3 .6

1 0 8 .5

1 1 0 .0

1 1 2 .7

1 1 3 .9

1 1 9 .7

1 1 9 .5

120.1

1 0 0 .2

1 0 0 .5

9 8 .9

9 9 .5

1 0 3 .9

1 0 4 .2

9 9 .4

100.1

1 0 2 .0

1 0 7 .2

1 1 6 .5

1 1 7 .0

1 2 0 .2

1 2 0 .6

1 3 1 .0

1 3 1 .3

1 3 2 .0

1 0 1 .4

1 0 3 .2

9 7 .2

9 8 .8

1 0 0 .9

1 0 6 .0

1 1 3 .7

1 1 4 .3

120.1

1 1 9 .9

1 3 1 .3

130.1

1 3 1 .3

9 3 .9

94.1

9 4 .2

9 5 .6

9 6 .8

9 8 .2

9 9 .0

9 9 .8

9 4 .0

9 4 .0

9 3 .9

1 0 2 .3

1 0 2 .5

1 0 3 .4

1 0 4 .2

1 0 4 .4

1 0 4 .7

1 0 4 .8

1 0 5 .4

105.1

1 0 5 .3

1 0 6 .0

1 0 7 .6

1 0 2 .7

1 1 0 .3

1 0 9 .5

108.1

1 0 8 .0

1 0 6 .8

1 1 3 .7

1 1 8 .4

1 2 0 .2

1 2 3 .6

1 2 0 .4

1 1 7 .2

9 2 .2

9 2 .9

9 3 .4

9 4 .4

9 6 .4

9 9 .2

1 0 4 .5

1 0 9 .5

1 1 4 .9

1 2 1 .7

1 2 6 .2

1 2 4 .5

1 2 6 .2

9 7 .9

9 7 .3

9 7 .5

9 7 .7

98.1

9 8 .2

9 8 .5

9 9 .2

9 9 .3

9 9 .3

9 9 .0

9 8 .7

9 7 .9

9 2 .9

93.1

93.1

93.1

9 2 .6

9 2 .6

9 2 .3

9 2 .2
9 7 .6

9 3 .6

9 4 .7

1 0 2 .9
1 0 1 .8

M a te ria ls a s s o c i a t e d w ith n o n d u r a b le

U n fin is h e d m e t a l s a s s o c i a t e d w ith d u r a b le g o o d s ..

Mar.

Feb.

Jan.

Sept.

9 6 .7

N o n a g ric u ltu ra l (fish, b e v e r a g e s ) fo o d p r o d u c ts .......

Oct.

Aug.

9 3 .8

9 3 .6

9 3 .5

9 3 .0

9 3 .3

9 6 .8

9 6 .6

9 5 .8

9 6 .2

9 6 .5

9 6 .8

9 7 .4

9 7 .9

9 7 .8

9 7 .2

9 7 .2

97 .1

9 2 .3

92.1

92.1

9 1 .4

9 1 .6

91.1

9 1 .2

9 1 .2

9 1 .2

9 0 .6

9 0 .5

90.1

9 0 .0

1 0 1 .2

1 0 1 .4

1 0 1 .6

1 0 1 .7

1 0 1 .8

1 0 2 .0

1 0 2 .0

1 0 2 .2

1 0 2 .3

1 0 0 .6

1 0 0 .6

1 0 0 .5

1 0 1 .2

9 7 .9

9 7 .9

9 7 .9

98.1

98.1

9 8 .6

9 8 .7

9 8 .7

9 8 .6

9 8 .5

9 8 .5

9 8 .5

98.1
9 9 .9

9 9 .8

9 9 .7

9 9 .8

1 0 0 .0

101.1

1 0 1 .2

1 0 1 .3

101.1

1 0 1 .0

1 0 0 .9

1 0 1 .2

9 6 .3
9 5 .7

9 6 .2

9 6 .2

96 .1

9 6 .2

100.1
9 6 .2

9 6 .3

9 6 .3

9 5 .8

9 5 .8

9 6 .2

9 5 .9

9 6 .2

9 6 .3
9 6 .4

96.1

9 5 .7

9 6 .3
9 6 .4

9 6 .0

9 5 .6

9 7 .3

9 6 .8

9 5 .9
9 7 .4

47. U.S. international price Indexes for selected categories of services
[2000 = 100, unless indicated otherwise]
Mar.
Air fr e ig h t ( i n b o u n d ) ................................................................

9 3 .9

Air fr e ig h t (o u tb o u n d ) .............................................................

9 5 .9

June
9 8 .3
9 8 .4

2004

2003

2002
Category

Sept.
1 0 0 .3
9 7 .3

Dec.
1 0 5 .9
9 5 .4

Mar.

June

Sept.

9 0 .3

9 3 .5

9 3 .3

June
1 1 6 .5

1 0 9 .4

1 1 2 .5

1 1 2 .9

1 1 6 .2

9 7 .2

9 5 .4

9 5 .5

9 4 .9

96.1

9 8 .9

100.0
100.0

105.1

106.1

9 9 .3

1 1 4 .2

1 1 7 .7

119.1

121.1

In b o u n d a ir p a s s e n g e r f a r e s (D e c . 2 0 0 3 = 1 0 0 )......
9 1 .7

Mar.

1 0 8 .8

O u tb o u n d a ir p a s s e n g e r f a r e s (D e c . 2 0 0 3 = 1 0 0 )).
O c e a n lin er fre ig h t ( i n b o u n d )............................................

Dec.

9 4 .0

116.1

1 1 6 .2

N O T E : D a s h i n d ic a te s d a t a n o t a v a ila b le .


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Monthly Labor Review

September 2004

121

Current Labor Statistics:

Productivity Data

48. Indexes of productivity, hourly compensation, and unit costs, quarterly data seasonally adjusted
[1992 = 100]

Item

2001
II

III

2002
IV

1

II

2003
III

IV

I

II

2004
III

IV

1

Business
O u tp u t p e r h o u r of all p e r s o n s ...........

1 1 8 .4

C o m p e n s a tio n p e r h o u r .............
R e a l c o m p e n s a t io n p e r h o u r ....
U nit la b o r c o s t s ................

1 1 2 .8

U nit n o n la b o r p a y m e n ts ....

1 0 9 .9

1 1 7 .0

Im plicit p ric e d e f la to r ................

1 2 2 .7

1 2 3 .2

1 2 4 .7

1 4 3 .2

1 4 4 .4

1 4 5 .0

1 1 5 .2

1 1 5 .2

1 1 5 .0

1 2 5 .0
1 2 6 .2
1 4 5 .5 1 .5 1 4 7 .4
1 1 4 .8
1 1 5 .3

1 2 8 .6

1 3 1 .2

1 3 2 .0

1 3 3 .3

1 3 3 .8

1 4 9 .6

1 5 1 .7

1 5 3 .2

1 5 4 .2

1 5 5 .6

1 1 6 .8

1 1 7 .7

1 1 8 .7

1 1 6 .7

1 1 8 .4

1 1 7 .2

118.1

1 1 6 .3

1 1 6 .3

1 1 6 .8

1 1 6 .4

1 1 5 .6

1 1 3 .4

1 1 6 .0

1 1 5 .7

1 1 3 .6

1 1 5 .7

1 1 6 .3

1 1 6 .8

1 1 7 .7

1 1 9 .0

1 2 0 .8

1 2 0 .7

1 1 5 .5

1 2 2 .9

1 1 5 .9

1 2 4 .4

116.1

1 1 6 .5

117.1

1 1 7 .3

1 1 7 .5

1 1 7 .8

1 1 8 .4

1 1 9 .4

Nonfarm business
O u tp u t p e r h o u r o f all p e r s o n s ...........

118.1

C o m p e n s a tio n p e r h o u r .......
R e a l c o m p e n s a t io n p e r h o u r ...
U nit la b o r c o s t s ..................

1 1 2 .2

U nit n o n la b o r p a y m e n t s ......

1 1 1 .6

1 1O . J

Im plicit p ric e d e f la to r ................

1 1 6 .0

1 2 2 .8

124.1

1 2 4 .6

1 2 5 .8

1 2 7 .8

1 3 0 .6

1 3 1 .7

1 3 2 .8

1 4 3 .8

1 3 3 .7

1 4 4 .3

1 4 4 .7

1 4 6 .6

1 4 8 .7

1 5 0 .9

1 5 2 .5

1 5 3 .3

1 1 4 .7

1 5 4 .9

1 1 4 .4

1 1 4 .3

1 1 4 .7

116.1

117.1

1 1 8 .2

117.1

1 1 7 .7

1 1 7 .6

1 1 6 .2

116.1

1 1 6 .6 5 .5 1 1 6 .3

1 1 5 .5

1 1 5 .9

115.1

1 1 5 .4

1 1 5 .4

1 1 7 .7

1 1 5 .9

1 1 8 .9

1 1 9 .6

1 2 0 .4

1 2 2 .3

1 2 1 .9

1 1 6 .0

1 2 4 .3

1 1 6 .5

1 2 5 .7

1 1 6 .8

1 1 7 .2

1 1 7 .7

1 1 7 .8

1 1 8 .0

118.1

1 1 8 .7

1 1 9 .5

Nonfinancial corporations
O u tp u t p e r h o u r o f all e m p l o y e e s ..........

1 2 2 .8

C o m p e n s a tio n p e r h o u r .......

1 3 6 .7

R e a l c o m p e n s a t io n p e r h o u r..

1 1 0 .4

1 2 3 .0

T o ta l u n it c o s t s .................
U nit la b o r c o s t s ......................
U nit n o n la b o r c o s t s ...........
U nit p ro f its ...............................

1 1 2 .2

U nit n o n la b o r p a y m e n t s ......................

1 0 5 .6

Im plicit p ric e d e f la to r ..................

1 0 9 .4

1 2 6 .3

1 2 7 .9

1 2 9 .2

1 3 0 .2

1 3 1 .3

134.1

1 3 7 .2

1 3 8 .9

1 3 9 .9

1 3 8 .9

1 4 1 .3

142.1

1 3 9 .4

1 4 2 .9

144.1

1 4 6 .3

1 4 8 .5

1 5 0 .0

1 1 2 .7

1 5 0 .9

1 5 2 .4

1 1 2 .7

1 1 2 .8

1 1 2 .7

1 1 4 .2

1 1 5 .3

1 1 6 .2

1 1 5 .9

110.1

1 1 1 .2

1 1 0 .7

1 1 0 .4

1 1 0 .7

1 0 9 .7

1 0 9 .0

1 0 8 .7

1 0 8 .8

1 1 0 .5

1 1 0 .0
1 1 2 .7

1 0 9 .5

1 0 9 .7

109.1
1 1 1 .4

1 0 8 .2
111.1

1 0 8 .0
1 1 0 .5

1 0 8 .6

1 0 9 .3

1 1 2 .3

1 0 9 .8
1 1 3 .2

1 0 9 .5

1 0 9 .9

9 5 .7

1 0 1 .8

9 9 .2

1 1 1 .0

1 1 8 .7

1 2 3 .2

128.1

133.1

89.1

1 1 2 .9
9 4 .7

1 0 7 .4

108.1

1 0 8 .2

1 0 9 .5

1 0 9 .4

1 1 1 .3

113.1

1 1 3 .9

1 0 9 .6

1 1 4 .5

1 0 9 .7

116.1

1 0 9 .4

1 0 9 .6

1 0 9 .7

1 0 9 .8

1 0 9 .9

1 1 0 .0

1 1 0 .6

1 1 1 .6

Manufacturing
O u tp u t p e r h o u r o f all p e r s o n s ............

1 3 5 .8

C o m p e n s a tio n p e r h o u r ...............

1 3 7 .4

R e a l c o m p e n s a t io n p e r h o u r ..........

1 1 1 .0

U nit la b o r c o s t s ................

122

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1 0 1 .2 I

1 3 6 .9

1 0 0 .3

September 2004

1 4 3 .8

9 9 .3

1 1 5 .7

1 1 1 .6
1 ,1 1 0 .8
1 1 4 .0
7 5 .8

II

1 4 5 .7

1 4 7 .8

1 4 8 .8

1 5 1 .0

152.1

1 5 5 .9

1 5 7 .2

1 5 8 .3

1 4 7 .0

1 6 0 .9

1 4 8 .6

1 4 9 .9

1 5 5 .7

1 5 8 .5

1 6 1 .6

1 6 3 .9

1 1 5 .9

1 6 2 .2

1 1 7 .2

1 6 3 .5

1 1 7 .8

1 1 8 .3

1 2 1 .8

1 2 3 .8

1 2 5 .4

1 2 7 .0

1 0 0 .2

1 2 4 .6

1 0 0 .8

124.1

1 0 0 .5

1 0 0 .7

103.1

1 0 4 .2

1 0 3 .6

1 0 4 .2

1 0 2 .5

1 0 1 .6

49. Annual indexes of multifactor productivity and related measures, selected years

r-|99fi = 1001
Item

1980

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2001

Private business
P ro d u ctiv ity :

1 1 2 .4

7 5 .8

9 0 .2

9 1 .3

9 4 .8

9 5 .4

9 6 .6

9 7 .3

1 0 2 .2

1 0 5 .0

1 0 7 .7

1 1 1 .0

1 0 3 .3

9 9 .7

9 6 .5

9 8 .0

9 8 .7

1 0 0 .4

9 9 .8

1 0 0 .3

9 9 .3

9 8 .2

9 6 .6

9 2 .8

8 8 .8

9 5 .5

9 4 .5

9 6 .7

97.1

9 8 .2

9 8 .4

1 0 1 .2

1 0 2 .5

1 0 3 .4

1 0 5 .0

1 0 3 .9

5 9 .4

8 3 .6

8 2 .6

8 5 .7

8 8 .5

9 2 .8

9 5 .8

1 0 5 .2

1 1 0 .5

1 1 5 .7

1 2 0 .4

1 2 0 .2

7 1 .9

8 9 .4

8 8 .3

8 9 .3

9 1 .8

9 5 .6

9 8 .0

1 0 3 .5

106.1

1 0 9 .0

110.1

1 0 9 .5

5 7 .6

8 3 .8

8 5 .7

8 7 .5

8 9 .7

9 2 .5

9 6 .0

1 0 4 .9

1 1 1 .3

1 1 7 .9

1 2 4 .5

1 2 9 .6

6 7 .0

8 7 .5

8 7 .4

8 8 .7

91.1

9 4 .6

9 7 .3

1 0 4 .0

1 0 7 .9

1 1 0 .9

1 1 4 .7

1 1 5 .7

7 3 .4

9 0 .4

9 4 .6

9 6 .8

9 6 .6

9 6 .2

9 7 .5

1 0 1 .9

1 0 5 .8

1 0 9 .7

1 1 4 .8

121.1

1 1 1 .6

In p u ts:

Private nonfarm business
P ro d u ctiv ity :
7 7 .3

9 0 .3

9 1 .4

9 4 .8

9 5 .3

9 6 .5

9 7 .5

1 0 2 .0

1 0 4 .7

107.1

1 1 0 .3

1 0 7 .6

1 0 0 .4

9 7 .0

9 8 .2

9 9 .0

1 0 0 .4

1 0 0 .0

1 0 0 .0

9 9 .0

9 7 .6

9 5 .9

9 2 .0

9 1 .0

9 5 .8

9 4 .8

9 6 .7

9 7 .2

9 8 .2

9 8 .6

1 0 1 .0

1 0 2 .2

1 0 2 .9

1 0 4 .4

1 0 3 .3

5 9 .6

8 3 .5

8 2 .5

8 5 .5

8 8 .4

9 2 .6

9 5 .8

105.1

1 1 0 .5

1 1 5 .7

1 2 0 .2

120.1

7 0 .7

8 9 .2

8 7 .9

8 9 .0

9 1 .8

9 5 .4

9 7 .8

1 0 3 .6

1 0 6 .4

1 0 9 .5

1 1 0 .6

110.1

5 5 .4

8 3 .2

85.1

8 7 .0

8 9 .4

9 2 .2

9 5 .8

105.1

1 1 1 .7

1 1 8 .5

1 2 5 .4

1 3 0 .5

6 5 .5

8 7 .2

8 7 .0

8 8 .4

9 1 .0

9 4 .3

9 7 .2

104.1

108.1

1 1 2 .4

1 1 5 .2

1 1 6 .3

7 1 .8

8 9 .9

9 4 .3

9 6 .5

9 6 .3

96.1

9 7 .6

1 0 1 .9

1 0 5 .8

1 0 9 .7

1 1 5 .0

1 2 1 .3

1 1 9 .7

In p u ts:

Manufacturing
P ro d u ctiv ity :
6 2 .0

8 2 .2

84.1

8 8 .6

9 0 .2

9 3 .0

9 6 .5

1 0 3 .8

1 0 8 .9

1 1 4 .0

1 1 8 .3

9 7 .2

9 7 .5

9 3 .6

9 5 .9

9 6 .9

9 9 .7

1 0 0 .6

1 0 1 .4

1 0 1 .7

1 0 1 .7

1 0 1 .0

95.1

8 1 .2

9 3 .3

9 2 .4

9 4 .0

95.1

9 7 .3

9 9 .2

103.1

1 0 5 .7

1 0 8 .7

1 1 1 .3

1 1 0 .3

6 4 .3

8 3 .2

8 1 .5

8 5 .5

8 8 .3

9 2 .9

9 6 .9

1 0 5 .6

1 1 0 .5

1 1 4 .7

1 1 7 .4

112.1

1 0 3 .7

101.1

9 6 .9

9 6 .5

9 7 .8

9 9 .9

1 0 0 .4

1 0 1 .7

1 0 1 .5

1 0 0 .7

9 9 .2

9 9 .6

66.1

8 5 .3

87.1

89.1

91.1

9 3 .2

9 6 .4

104.1

1 0 8 .7

1 1 2 .8

1 1 6 .2

1 1 7 .9

86.1

93.1

9 3 .2

93.1

9 6 .6

9 9 .9

1 0 2 .3

9 7 .5

1 0 0 .6

1 0 2 .9

1 0 4 .3

9 8 .9

6 3 .9

7 7 .5

7 8 .5

8 3 .5

8 6 .5

9 0 .3

1 0 1 .9

1 0 7 .5

1 0 7 .9

1 0 6 .9

1 0 5 .5

1 0 3 .9
1 0 2 .4

103.1

1 0 5 .4

1 0 6 .5

9 7 .7

1 0 4 .6

1 0 5 .5

1 0 5 .5

1 0 1 .6

In p u ts :

C o m b in e d u n its of all fa c to r i n p u ts ......................................


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6 5 .8

8 4 .7

8 4 .6

9 2 .0

9 2 .9

9 6 .0

93.1
1 0 0 .4

79 .2

89.1

8 8 .3

9 0 .9

9 2 .8

9 5 .5

9 7 .7

Monthly Labor Review

September

2004

123

Current Labor Statistics:

Productivity Data

50. Annual indexes of productivity, hourly compensation, unit costs, and prices, selected years
[1992 = 100]
Item

1960

1970

Business

1980
*

Cï

1990

1995

5

1996

1997

1998

1999

2000

2001

2002

2003

L

O u tp u t p e r h o u r o f all p e r s o n s ....

4 8 ./

C o m p e n s a tio n p e r h o u r ........

101/

1 0 4 .5

1 0 6 .5

1 0 9 .3

1 3 .8

1 1 2 .4

1 1 5 .7

1 1 8 .3

9 0 .5

1 2 4 .0

1 0 6 .0

1 2 9 .6

R e a l c o m p e n s a tio n p e r h o u r........

1 0 9 .5

1 1 3 .0

1 1 9 .7

6 0 .5

1 2 5 .4

1 3 4 .2

1 3 9 .7

96.1

1 4 7 .8

9 8 .9

1 4 7 .9

9 9 .5

1 0 0 .5

1 0 5 .0

1 0 7 .8

1 1 1 .6

1 1 3 .0

9 5 .9

1 1 3 .7

1 0 4 .3

115.1

1 0 4 .8

106.1

1 0 9 .5

2 4 .9

1 1 1 .6

1 1 6 .0

118.1

9 3 .9

1 1 5 .2

1 0 8 .2

1 1 1 .9

114.1

1 1 3 .9

1 0 9 .9

27 .1

1 0 9 .2

1 0 7 .2

1 0 9 .5

95.1

1 1 7 .0

1 0 5 .7

1 0 7 .4

1 2 3 .0

1 0 9 .0

1 0 9 .7

1 1 0 .7

1 1 2 .7

1 1 4 .9

1 1 5 .8

1 1 7 .4

U n it la b o r c o s t s .....................

U nit n o n la b o r p a y m e n ts ..........
Im plicit p ric e d e f la to r .....................

79J0

o o .b

Nonfarm business
O u tp u t p e r h o u r o f all p e r s o n s ................

5 1 .6

C o m p e n s a tio n p e r h o u r ........

102.1

1 0 4 .7

1 0 6 .4

1 4 .4

1 0 9 .2

1 1 2 .2

1 1 5 .3

1 1 7 .8

9 0 .3

1 2 3 .6

1 0 6 .0

129.1

R e a l c o m p e n s a t io n p e r h o u r ..........

1 0 9 .4

1 1 2 .8

1 1 9 .4

1 2 4 .9

6 3 .0

1 3 3 .7

1 3 8 .9

9 5 .9

142.1

9 8 .9

1 4 7 .0

9 9 .4

1 0 0 .3

1 0 4 .7

1 0 7 .3

1 1 1 .2

1 1 2 .4

9 5 .6

1 1 3 .2

1 1 4 .4

1 0 3 .8

1 0 4 .5

1 0 6 .0

1 0 9 .3

2 4 .3

1 1 1 .3

1 1 6 .0

1 1 8 .0

9 3 .6

1 1 5 .0

1 0 9 .2

112.1

1 1 3 .9

1 1 4 .6

1 1 0 .9

2 6 .6

1 1 0 .8

1 0 8 .8

111.1

9 4 .9

1 1 9 .0

1 0 5 .8

1 2 4 .8

1 0 7 .3

109.1

1 0 9 .9

111.1

1 1 3 .3

1 1 5 .4

1 1 6 .4

1 1 7 .9

1 0 3 .4

107.1

1 0 9 .8

1 1 2 .8

1 1 6 .4

1 2 0 .6

1 2 2 .7

9 1 .0

1 2 8 .9

1 0 5 .4

1 3 6 .3

1 0 8 .4

1 1 1 .7

1 1 7 .9

1 2 3 .3

1 3 1 .7

9 6 .7

1 3 7 .0

140.1

9 8 .3

9 8 .5

1 4 5 .9

9 9 .3

1 0 3 .4

1 0 5 .9

1 0 9 .5

1 1 0 .8

1 1 1 .5

1 1 3 .5

1 0 4 .6

1 0 8 .0

1 1 1 .2

1 0 9 .4

1 0 7 .4

U nit la b o r c o s t s ....................
U nit n o n la b o r p a y m e n ts .......
Im plicit p ric e d e f la to r ................

6 7 .5

Nonfinancial corporations
O u tp u t p e r h o u r o f all e m p lo y e e s ....

5 6 .6

C o m p e n s a tio n p e r h o u r ..................

16.1

R e a l c o m p e n s a t io n p e r h o u r ...............
T o ta l u n it c o s t s ........................

7 0 .4
o /.U

7 0 .3
O u. 1

U nit la b o r c o s t s ...................
U nit n o n la b o r c o s t s ..................

9 5 .4

1 0 1 .8

1 0 0 .9

1 0 1 .2

1 0 3 .2

9 5 .3

1 0 2 .0

1 0 1 .2

1 0 1 .7

1 0 4 .5

1 0 6 .0

1 0 9 .2

1 1 1 .6

1 0 8 .6

1 0 1 .3

1 0 7 .0

9 9 .9

9 9 .8

9 9 .9

1 0 1 .0

1 0 4 .8

1 1 0 .2

9 6 .7

1 1 1 .5

1 3 6 .9

1 0 8 .4

1 4 9 .9

1 5 4 .4

1 3 7 .5

1 2 9 .8

1 0 9 .3

9 1 .4

9 7 .0

1 1 1 .4

1 3 4 .2

1 1 0 .8

1 1 3 .3

1 1 4 .4

1 0 9 .9

1 0 8 .7

1 0 4 .9

1 1 1 .5

1 1 5 .3

1 0 5 .3

1 0 5 .9

1 0 6 .3

1 0 6 .9

106.1
108.1

1 0 5 .2

9 5 .9

1 0 9 .5

1 0 9 .6

1 0 9 .8

110.1

1 1 3 .9

1 1 7 .9

1 2 3 .5

1 2 8 .2

1 3 4 .2

137.1

147.1

1 0 7 .7

1 5 4 .6

1 0 9 .9

1 1 2 .0

1 1 8 .8

1 2 3 .8

1 3 5 .0

1 3 8 .3

1 4 3 .8

1 0 0 .5

1 5 1 .9

9 9 .8

9 9 .7

1 0 4 .2

1 0 6 .3

1 1 2 .3

1 1 1 .8

2 3 .0

U nit p ro f its ................................

6 6 .5

U nit n o n la b o r p a y m e n ts .......................

30.1

Im plicit p ric e d e f la to r .......................

2 8 .9

od

.y

Manufacturing
O u tp u t p e r h o u r o f all p e r s o n s ..............

4 1 .8

C o m p e n s a tio n p e r h o u r ..........

1 4 .9

R e a l c o m p e n s a t io n p e r h o u r ........

6 5 .0

5 4 .2
9 1 .4

U nit la b o r c o s t s ....................
U nit n o n la b o r p a y m e n ts ......................
Im plicit p ric e d e f la to r ................

2 6 .8
3 0 .2

3 5 .0

D a s h in d ic a te s d a t a n o t a v a ila b le .

124

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September 2004

7 9 .9

9 9 .5

1 1 4 .5

1 1 8 .2

9 7 .8

9 6 .5

9 5 .0

9 6 .2

9 6 .6

1 0 0 .6

1 0 0 .8

9 7 .8

1 0 7 .6

9 8 .2

1 1 0 .4

1 1 0 .5

104.1

1 0 5 .0

1 0 7 .0

1 0 3 .9

1 0 5 .2

-

1 0 4 .6

-

101.1

1 0 1 .8

104 6

1 0 5 .8
103 Q

51.

Annual indexes of output per hour for selected NAICS industries, 1990-2002

[1997= 100]

______________

Industry

NAICS

1990

1992

1993

1994

1995

1996

1997

96.2
85.1
89 .9
79.9
102.2

99 .6
90.3
93 .0

69.3
82.7

95 .2
8 1 .9
86 .8
7 5 .3
91.7

83 .9
104.1

101.8
9 5 .5
94 .0
88 .2

101.7
98 .9
96 .0
9 4 .9

9 8 .5

100.0
100.0
100.0
100.0
100.0

1991

Mining
86 .8
78.8
80 .0

21
211
212
2121
2122

86.0
78 .4

2123

9 2 .3

8 9 .5

96.1

9 3 .6

9 6 .9

9 7 .3

9 5 .3
97.1

71.2
7 1 .4

73.8
72.7

74 .2

78.7
79.8

83 .0
82.1

88 .6
89.0

90.1
8 9 .0
91 .0
86 .4

89 .3
91.2
93 .8
89.7

90.2
91.1

87.3
94.7

9 0 .8

92.1

9 0 .5
90 .7
9 5 .4

90.2
93 .8
9 2 .5
93 .8
93 .9

94.5
117.5
92 .6
9 1 .9

9 6 .8
112.0
92 .3
93.5
90.1

101.5
115.3
95 .6
95 .9
9 3 .8

100.9
113.9
96 .0
102.8
93.2

77.3
74 .7

88.6

7 9 .6
80.1
81 .5
83.7
93 .0

9 0 .0
88.7

9 2 .0
9 3 .2

72 .0
97 .3
5 6 .6

73.1
98 .7
76.7

77.1

74.7

102.5
79.2

100.2
81.6
107.4

83.1
97 .0
86.1
114.7

104.7

104.0

88.1
93 .5
95 .4

9 2 .3
9 3 .7
101.3
78.9
8 9 .4

79 .3
68.1
7 9 .9

75.8

1999

2000

103.4

111.1

101.6
104.6

107.9
105.9
110.3
112.7

109.5
115.2
106.8

Fruit a n d v e g e ta b le p re serv in g a n d sp e c ia lty .........

3115
3116
3117

S e a f o o d p ro d u c t p re p ara tio n a n d p a c k a g in g ..........

3118
3119
3121

8 6 .5
81 .4

312 2
3131
3 132
3133
3141
3149

73 .9
7 5 .0
81 .7
88 .2
O th e r textile p ro d u c t millsv

91.1
85 .6
70.1
100.9
6 0 .8

3151
3152
3159
3161
316 2
3169
3211
3212
3219

102.3
105.4
8 8 .5
90 .5
96 .6
76.7
9 1 .4

3221
3222
3231
3241
3251

75 .8
84 .6
91 .4
85.1
83.2

3252
3253
3254
3255
3256

77.7
80 .4

9 9 .3

103.8
99.1

104.1

107.0
113.1

106.4

10 2 .4

103.1

110.0

114.9

109.4
107.5
104.0
106.8

109.5
114.2
107.1
108.4

109.7
112.5
111.9
109.8

99.1

94 .5

9 6 .0

100.0
100.0
100.0
100.0
100.0

99 .9
117.0
103.8
106.9
9 8 .5

100.3
130.2
105.4
108.8
92 .4

101.9
137.6
1 0 5 .3
110.2
90 .6

102.7
147.3

-

103.2
91 .7

-

100.0
100.0
100.0
100.0
100.0

98.1
102.2

9 8 .0
102.6
110.2

100.0
110.5

-

103.9
100.6
9 9 .9

92.1
104.6
109.8
101.7
101.2

109.1
109.7

—

100.0
100.0
100.0
100.0

110.4

102.0
118.8
103.3
101.6

110.2
127.7
104.9

100.0

97 .0
96 .6
104.0
110.8
9 8 .0

110.4

7 8 .6

9 6 .3
121.9
90 .5
112.6
9 1 .5

124.1

100.0
100.0

94.0
99.1
94 .3
97.1
98 .7

87 .5
91 .3
98.2
98.2

100.0
100.0
100.0
100.0
100.0

9 7 .4
114.1
96.7
100.3
97 .7

9 8 .5
108.4
99.7

9 4 .3
116.2
97 .7

101.3
99 .6

103.0
101.1

7 3 .7
84 .6

8 9 .8
87.2

9 9 .4
98 .7

85 .0
86 .0
93 .7

91 .9
87 .8
90.1

9 7 .5
92 .0
95 .8
84 .5
92 .5

9 0 .3
102.5
76 .6
99 .0
83.1

9 4 .5
104.3
80 .5
104.6

9 5 .9
109.5

75.9

75.8
90.1
74.7
81.0
92.6
85 .9
84.2

85 .5
112.4

98 .0

98 .0
85 .0
93 .3

81.7

9 0 .4

94 .3
82 .6
108.9
103.0

80 .0
85.1
105.8
99 .3

9 5 .6
73.2
91 .0
101.8
100.4

103.4
79 .7
96 .2
101.2
100.8

100.0
100.0
100.0
100.0
100.0

100.9
109.2
100.8
105.6
101.5

116.8
100.4
105.4

9 2 .9
96.3

9 7 .6
9 7 .6
98 .3
85 .6
95.1

102.0
97.2
98 .8
90.1
92 .3

9 7 .6
9 8 .3

100.0
100.0
100.0

103.1
102.7

111.4

100.1
84.5
89.9

80 .6
81 .3
88 .2
87 .6
8 3 .4

83.8
85 .6
88.1
90 .9
86.9

9 3 .5
87 .4
92 .4
94.1
88 .6

9 5 .9
90.7
96 .3
92.7
93 .9

8 4 .7

9 0 .6

9 4 .4

9 0 .3
84 .9
9 1 .5
8 4 .3

91.9
90 .4
91 .9
86.1

9 2 .6
9 4 .4
90.3
96 .6
87 .5

9 9 .9
105.4

115.8
124.4

104.0
106.8

110.0

107.6
106.5
100.5
104.0

101.5
103.5

115.7
101.9
104.9

107.8
114.7

113.2
118.4

142.7
114.1
109.0
105.0
104.6
117.5
101.0
105.6
112.2

“
-

r-

105.5
98 .8
92 .9
99.1
9 6 .6

108.8
8 7 .6
9 4 .6
9 8 .8
91.1

108.1
9 1 .4
9 3 .4
9 8 .5
9 9 .2

103.8
91.1
9 7 .4
102.1
102.7

94.2
9 7 .0
94 .4
102.6
96 .5

100.0
100.0
100.0
100.0
100.0

99 .4

109.2

103.5
100.5
101.3
102.7

109.3
101.4

120.0
111.2
103.9
103.6
109.7

111.3
113.3
104.2
9 7 .6
105.2

100.6
92 .4

103.5
113.1
9 8 .8
101.7
100.3

104.1
102.7

100.5

100.0
100.0
100.0
100.0
100.0

9 5 .5
106.5
9 4 .2

10 0 .4
9 7 .0
95 .6
108.5
96 .4

97.1
100.1
96.8
106.7
97.1
9 6 .9
100.5
109.3
121.8
110.2

-

100.7
9 8 .2

-

3273
3274

94.8
84.1
79.8
69 .6
83 .8

93.7
82.7
8 1 .4
67.2
86 .4

9 4 .8
88 .5
90 .2
74.1

9 6 .5
90.1
89 .3
81.7

9 5 .0
8 7 .8
90 .5
87 .2

89 .9

95 .9

100.0

98.2
88.8
91 .7
89.7
100.5

3313
3314
3315
3321
3322

9 1 .9
95 .6
85 .3

9 3 .3
95.8
84 .5

100.3
105.1
91 .4
93 .7
94.4

9 6 .8
102.9
93.1
94.2
97.8

9 5 .9
105.7
96.2
97 .6
104.4

100.0
100.0
100.0
100.0
100.0

101.1
111.2
101.6
103.7
100.0

9 7 .8
103.1
104.0

86.5
8 5 .4

9 6 .0
101.8
89.8
94 .6
91.7

104.3
108.9
104.9

8 8 .6
85.1

9 6 .8
9 8 .8
85 .8
91 .7
87.2

110.9
107.8

121.3
105.8

3323
3324

87 .8
90 .4

9 3 .9
97 .8
97 .3
9 9 .5
98 .7

102.6
102.8

79.8

95.1
100.5
95 .7
91.5
91 .6

100.0
100.0
100.0

101.1
101.3
101.0
111.6

78.8

93 .4
94 .8
89.6
95 .3
86 .9

100.0
100.0

84 .4
85.2

92 .5
95 .3
86.9
90 .9
87 .2

94.2
100.7

3325
3326
3327

89.1
92 .6
83 .8
88 .4

101.8
98 .9
106.5
112.9
103.9

101.0
97 .7
115.8
114.6
107.2


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

105.0
108.4
131.7
114.8
109.7

100.0
100.0
100.0
100.0
100.0

83 .0
89.2
8 0 .0

M ac h in e s h o p s a n d th re a d e d p ro d u c ts ..................

106.9

-

93 .3
92.1
99 .9
98 .3
95 .6

7 8 .0
86.3
83 .8
87.5
79.1

Iron a n d s te e l m ills a n d ferroalloy p ro d u c tio n ........

127.2
117.3
109.9
117.0
96 .2

100.0
100.0

7 6 .6
84.7

9 4 .5
92 .8
97 .4
88.8

131.8

100.5
102.1
102.5

99 .6
94 .8
9 0 .0

3259
3261
3 262
3271
327 2

3279
3311
3 312

112.3
119.3
111.7

9 6 .2

95 .5
96.1

94 .0
94 .9
9 5 .4

10 7 .7
117.4
1 0 9 .0
114.4

2002

101.2

100.0

Manufacturing
3111
3112
3113
3114

2001

112.2
143.9
103.8

106.5
109.5
101.3

Utilities
2211
2212

1998

96 .5
94.1

100.0

9 9 .3

Monthly Labor Review

103.5
108.6

September

111.0

—
-

-

-

“
■

114.6
110.6
107.2

2004

125

Current Labor Statistics:

Productivity Data

51. Continued—Annual indexes of output per hour for selected naics industries, 1990-2002
[1997= 100]____________

NAICS
3328
3329
3331
3332

Industry
C o atin g , en g rav in g , a n d h e a t tre a tin g m e ta ls ......
O th e r fa b ric a te d m etal p ro d u c ts ......
A griculture, c o n stru c tio n , a n d m ining m a c h in e ry
Industrial m a c h in e ry ..............

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

81 .6
86 7
82 .8

78.1
8 5 .9

8 6 .9

9 1 .9

9 6 .5

84.1

102.9
98 .9
95.9

100.0
100.0
10 0 .0

101.7

90 .6
79.6

102.8
97.1

105.9
100.8
10 1 .0
129.7
101.4

105.1
9 8 .2
9 9 .5

98 .8

10 1 .5
100.2
9 5 .0
105.2

108.3
106.4

110.8
102.0

-

77 .2
81.1

3333

C o m m e rcia l a n d s e rv ic e industry m ac h in e ry

91 .4

8 9 .6

9 6 .5

101.7

3334

HVAC a n d co m m ercial refrigeration e q u ip m e n t
M etalw orking m a c h in e ry ............

88 .8

8 8 .2
8 2 .3

90 .8

9 3 .8

T u rb in e a n d p o w e r tra n s m is s io n eq u ip m e n t
O th e r g e n e ra l p u rp o s e m a c h in e ry ............

85 1
ft 5 g

84 .6
8 5 .2

8 1 .2
85.1

84 .8
8 9 .8

14.3

15.8

2 0 .6

2 7 .9

4 7 .3

4 9 .3
8 2 .8

59 .3
92.1
2 9 .6

34.1

76 .0
8 6 .6

2 4 .5
8 0 .5
9 1 .2

93 .0

9 6 .«

87 .3
76 .4

8 8 .5
7 6 .4

9 3 .6
8 2 .4

3335
3336
3339
3341
3342
3343
3344

C o m p u te r a n d p erip h e ra l e q u ip m e n t...........
C o m m u n ic a tio n s e q u ip m e n t......
Audio a n d vid eo e q u ip m e n t...............

3345
3346

S e m ic o n d u c to rs a n d e le ctro n ic c o m p o n e n ts
E lectronic in s tru m e n ts ............
M ag n e tic m e d ia m an u fa ctu rin g a n d re p ro d u ctio n

3351

Electric lighting e q u ip m e n t.......................

3352

H o u s e h o ld a p p lia n c e s .......................
E lectrical e q u ip m e n t.......................

3353
3359
3361
3362
3363
3364
3365
3366
3369
3371
3372
3379
3391
3399

O th e r ele ctrica l eq u ip m e n t a n d c o m p o n e n ts
M otor v e h ic le s .......................
M otor veh ic le b o d ie s a n d trailers
M otor v eh ic le p a r ts ...........
A e ro s p a c e p ro d u c ts a n d p a r ts ...............
R ailro ad rolling s to c k .....................
S h ip a n d b o a t building.....................
O th e r tra n s p o rta tio n e q u ip m e n t.........
H o u s e h o ld a n d institutional fu rn itu re.........
O ffice furniture a n d fix tu re s ..............
O th e r fu rn itu re -re lated p ro d u c ts ................
M edical e q u ip m e n t a n d s u p p lie s ........
O th e r m isc e lla n e o u s m a n u fa c tu rin g ....

7 5 .5
2 1 .4

72 .7
7 4 .2

7 5 .3
8 6 .0
75 .8
75 .7

7 1 .8

77 .2
9 9 .6

7 4 .5
92.1
8 0 .0
9 2 .6

62 .6
87 .6

6 2 .0
88 .2

8 0 .8
88.1
8 1 .2
90.1

78 .8
8 8 .6
83.1
9 0 .6

8 1 .6
9 1 .2

8 6 .8

88 .3

9 6 .3

103.0

106.3

9 7 .3
94 .0
9 3 .3

96 .6
99.1

9 7 .8
98.1

100.0
100.0

92.1

97 .9

9 1 .5

94 .6

95.1

3 5 .9

5 1 .3

70.1

74.6

108.5
43.1
8 8 .8
106.1

140.0
6 3 .4
9 6 .8
106.7

9 4 .5

9 2 .2

95 .0
8 9 .0
8 9 .4
9 0 .3

9 2 .7
98.1
92 .0
88 .6

, 3 2 '3

99.U

8 8 .4
9 2 .9
8 6 .2
88 .4
88.1
90 .0

9 5 .6
97 .9

10 0 .0
100.0

9 1 .8
9 3 .8

94.1
9 8 .5

9 5 .0
9 1 .0
9 0 .0
101.2

97 .3
92 .3
9 3 .7
8 2 .0
93.1

2002

_

104.6
9 4 .4

10 7 .5

111.2
110.4
1 0 0 .5

1 0 0 .0
100.0

106.6
99.1
106.4

113.3

117.1

103.2

1 0 5 .6

1 1 3 .0

130.2
109.4

-

72.6

100.0

138.6

190.3

2 2 5 .4

2 3 7 .0

-

84 .3
104.7

100.0

102.7

134.0

100.0

12 3 .3

126.3

100.0
100.0
100.0

103.1
125.2

116.2

81 .8
9 7 .7
103.8

174.5
105.1
106.8

2 3 3 .3
114.3
104.0

2 3 1 .6
116.1
9 8 .6

9 5 .6
93.1
100.2
96 .0
91 .0

101.3
105.4
103.8

1 0 2 .5

101.9

105.4

-

10 4 .3
9 8 .9
114.8
123.3

1 1 7 .5
100.6
12 0 .5
110.4

122.6
101.0
1 1 3 .5
108.7

-

9 9 .8
10 5 .5
113.3

9 8 .4
1 1 2 .7
101.0
117.7
120.1

9 9 .4

-

114.8
114.7
124.7
119.8

-

102.7
104.8
11 8 .5
102.9
100.3

103.1
110.4
118.0
1 1 6 .0
112.2

100.0
100.0
100.0

110.8
102.7

113.3
103.7

100.0
100.0
100.0

100.1
107.2
108.9
101.9

9 8 .5
102.5
109.6
105.2

100.0
100.0
100.0
100.0
100.0

104.4
105.6
104.7
9 7 .5
102.9

110.9
115.3
119.8
100.8

100.0
100.0
100.0
100.0
100.0

118.2
102.4
105.9
103.5
104.2

100.0

9 9 .8
9 9 .5

91.1
9 2 .3

'

105.1

100.0

85 .6
96 .7
100.0
9 9 .6

_

100.0
100.0
100.0

100.0
100.0
100.0
100.0

93.1
97.1

155.2

100.0

9 8 .4

8 4 .3
9 4 .5
95 .0
96 .0

1 6 5 .5

_

1 0 0 .0

93.1
98.1
80 .9

9 3 .8

90 .8

102.3
104.2
9 4 .4

2001

130.9
10 2 .5
100.2

146.9
106.1
97.1

100.1
114.2
112.9

105.3
119.0
1 1 0 .9

’
-

-

-

Wholesale trade
42
423
4231
4232
4233

W h o le sa le t r a d e .....................
D u rab le g o o d s .......................

77 .8
65 .7

M otor v e h ic le s a n d p a r ts ..............
F u rn itu re a n d tu rm s h in g s .....................

76 .6
8 2 .4

66.1
7 3 .3
8 7 .2
113.2

8 2 .2
9 8 .3

9 3 .3
8 8 .9
93 .6
96 .8
103.6

103.0

7 4 .7
101.2

8 8 .4
102.7

79 .3
98 .0
89 .7

87 .8
99.1
9 3 .9

96 .2
94 .0
94 .9

L u m b er a n d co n stru c tio n s u p p lie s ........

115.0
33 .8
101.6
4 6 .8
88.8
78 .9

37 .3
102.6

4238

C o m m e rcia l e q u ip m e n t .....................
M etals a n d m in e ra ls ...........................
Electric g o o d s .............................
H a rd w a re a n d p lu m b in g ........................
M achinery a n d s u p p lie s .........

4239
424

M isc e lla n e o u s d u ra b le g o o d s .........
N o n d u ra b le g o o d s ...............

8 9 .5
98 .4

9 6 .6
9 9 .8

112.1

4241
4242

9 9 .2
9 9 .7

P a p e r a n d p a p e r p ro d u c ts ............
D ru g g ists' g o o d s ................................
A pparel a n d p ie c e g o o d s ........

101.0
99 .2

8 1 .0
8 1 .8
103.9

8 5 .5

9 6 .5

103.3

100.1

99 .0
95 .4
92 .2

9 6 .5
98 .3
99 .0

100.0
100.0
100.0
100.0

101.8
102.8
100.4
99 .6
104.1

98 .2
8 5 .9

103.6
8 5 .9

103.3

103.0
87 .7

9 9 .8
90 .6

100.0
100.0

110.5
115.8

102.1
108.7

100.0
105.9

100.0
100.0

105.9

102.5

104.5

9 4 .8
8 8 .0
8 8 .3
8 8 .4

9 6 .2
91.1

98 .7
95 .7

9 0 .5
91 .8

95 .3
96.1

9 4 .7
9 7 .0
97 .2
91 .0
97 .9

9 7 .7
98.8
98 .9
9 7 .7
9 8 .3

94.1

99 .4

9 2 .5
9 5 .9
8 9 .2
93 .7

4234
4235
4236
4237

4243
4244
4246
4247

G ro cery a n d re la te d p ro d u c ts ............
F arm p ro d u c t raw m a te ria ls ..............
C h e m ic a ls .............................
P e tro le u m .....................................

4248

A lcoholic b e v e r a g e s ......

4249

M isc e lla n e o u s n o n d u ra b le g o o d s ......
E lectronic m a rk e ts a n d a g e n ts a n d b ro k e rs ..

4245

425
42511
42512

113.9

96 .4

1 1 1.9
6 0 .5

1Ï l 7

8 6 .5
7 4 .2

8 0 .6

B u s in e s s to b u s in e s s ele ctro n ic m a rk e ts ......
W h o le sa le t ra d e a g e n ts a n d b ro k e rs ..

119.6

101.3

107.3
9 7 .3
109.4

111.2

107.3
70 7
7 0 .4
70 .8

9 8 .2
7 3 .6
7 2 .6
7 4 .0

9 3 .9
8 1 .5
8 0 .3
8 2 .3

8 8 .3
9 0 .8
7 1 .7
8 4 .0

9 2 .6
78 .3
89.1

9 0 .6
8 8 .3

106.6

9 7 .5
8 5 .9
84 .8
86 .8

104.8
141.1
9 6 .0
126.2
107.8
101.4

114.1

117.1

119.6
114.0
105.5
101.7

120.3
114.1
1 0 5 .4
108.6

148.9
9 9 .2
151.7
111.1
104.1

164.9

189.4

10 2 .2
148.1
102.6
1 0 2 .7

10 2 .2
161.2
1 0 7 .9

1 2 3 .6
127.7
12 1 .7
101.8
119.2

100.2

112.6
104.1

116.7

116.1

1 2 5 .5

103.5

106.9

1 0 5 .5
101.7
1 0 3 .5

10 5 .5
9 6 .8
102.7

109.0
101.2
102.4

112.6
12 0 .2
116.0
11 1 .5

101.9
100.4

103.6
114.2

105.2

1 0 9 .4

1 1 9 .0

12 0 .0

111.8
135.4

99 .3
115.0

98 .0
112.0

9 5 .8
1 1 2 .5

9 3 .6
11 6 .5

9 6 .9
126.0

100.0

109.7

110.1

111.0

111.6

1 1 7 .3

100.0
100.0
100.0
100.0

101.7
104.6

99.6
114.4

106.2
124.1

10 3 .5
104.8

121.7
110.5

141.3
115.7

11 0 .3
106.4
106.4

114.2
107.2
106.6

100.0
100.0

104.3
102.7
102.7
105.9
105.7

113.0
110.0

108.6
112.0

97 .8
1 0 1 .3
95 .0

100.0
100.0
100.0
100.0

101.7
102.1
10 1 .3
122.9

109.6
108.2
111.4
152.2

114.8
116.8
177.7

1 1 8 .5
121.1
115.6
199.1

2 4 0 .0

9 7 .5

100.0

106.7

112.3

113.1

115.8

119.9

104.2

9 7 .0

131.3
1 6 9 .4
114.2

132.6
2 0 5 .0
109.3

11 7 .4

12 2 .7
109.7
106.0
116.4
115.8

Retail trade
4 4 -4 5
441
4411
4412
4413
442
4421
4422
443
444

126

R etail t r a d e ..............................
M otor v eh ic le a n d p a r ts d e a le r s ...
A utom obile d e a l e r s ..............
O th e r m o to r v eh ic le d e a le r s ...........
A uto p a rts , a c c e s s o r ie s , a n d tire s t o r e s ........
: u rn itu re a n d h o m e fu rn ish in g s s t o r e s ...........
F u rn itu re s t o r e s ....................
H o m e fu rn ish in g s s t o r e s ..............
E lec tro n ics a n d a p p lia n c e s t o r e s ...........
Building m aterial a n d g a r d e n s u p p ly s t o r e s ......

Monthly Labor Review


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

83 .2
89 .7
92.1
6 9 .0
8 5 .0
80 .7
82.1
7 8 .5
4 6 .0
8 1 .8

September 2004

92 .8

9 5 .4
«

81.1

88.1

8 3 .5
7 7 .6
4 9 .2

8 6 .8
5 6 .9

6 5 .5

7 7 .6

8 0 .2

84 .0

88 .0

9 3 .7

100.0
100.0
100.0

115.7

110.0
109.1
112.6
109.3

125.1
128.6
12 1 .4

51. Continued - Annual indexes of output per hour for selected NAICS industries, 1990-2002
[1997= 100]

1990

NAICS

Industry

4441
4442

B uilding m ateria l a n d s u p p lie s d e a l e r s .......................
Law n a n d g a r d e n eq u ip m e n t a n d s u p p lie s s to re s

83 .2
7 4 .5

445
4451
4452

F o o d a n d b e v e ra g e s t o r e s ..............................................
G ro c e ry s t o r e s ......................................................................
S p e c ia lty food s t o r e s ..........................................................

107.1
10 6 .5
122.9

B eer, w ine a n d liquor s t o r e s ...........................................

100.1

H e alth a n d p e rs o n a l c a r e s t o r e s ...................................

4453
446
447
448

G a s o lin e s ta tio n s ................................................................
C lothing a n d clothing a c c e s s o r ie s s t o r e s ..................

4481

C lothing s t o r e s ....................................................................

1991
8 0 .7
7 7 .5
106.6
106.6

1992

1993

1994

1995

1996

1997

1998

1999

2000

8 4 .7
80 .2

89.1
8 1 .5
105.4

9 4 .8
8 6 .9

9 4 .8
87 .0

9 7 .6
97.1

100.0
100.0

107.6
101.2

1 1 3 .8
108.2

104.3
104.9

102.5
103.0

100.3
100.8

99 .9
1 0 0 .3
95 .0

113.7
10 3 .5
10 3 .7

115.0

106.9
106.7
111.4

105.9
107.6

10 4 .5

101.1

9 5 .5

100.0
100.0
100.0

100.2

101.0

9 4 .4

9 2 .9

96 .2

103.1

100.0

1 0 5 .8

9 2 .0
8 4 .8

9 1 .6
8 5 .7

9 0 .7

9 1 .8

9 5 .7
9 9 .4

104.1

9 6 .8

9 3 .0
9 9 .7

100.0

8 8 .5

9 1 .9
9 2 .8

6 9 .5

7 0 .5

7 5 .3

7 8 .9

8 3 .3

9 1 .2

9 7 .9

100.0
100.0

105.6
105.4

68 .9

7 1 .4

77.1

7 9 .2

81 .9

90.1

97.1

100.0

1 0 6 .7

2001

2002

11 5 .3
119.4

1 1 9 .8
121.2

1 0 7 .6

105.6

1 0 7 .5
11 0 .8

1 1 0 .3
1 1 0 .3
1 1 4 .2

9 9 .8

111.1

110.4

11 1 .8

106.9

11 1 .4

1 1 2 .7

1 1 8 .8

11 0 .6
1 1 2 .8

1 0 6 .5
1 2 0 .3

1 0 9 .8
1 2 3 .5

1 1 7 .5
129.0

1 1 3 .3

120.9

125.2

132.7

10 4 .3
99 .6

105.1
104.9

73 .7

73.1

7 8 .2

7 9 .2

8 8 .3

9 3 .7

1 0 2 .4

100.0

9 7 .8

104.9

10 9 .6

1 1 5 .8

68 .6
8 0 .8
77.1
8 9 .0

6 4 .5

9 7 .3
94 .7

100.0
100.0
100.0
1UU.U

107.0
108.7
112.9
101.0

1 1 8 .3
1 1 4 .9
12 0 .4
10 4 V

12 8 .0

84 .0
80 .6
9 1 .6

8 5 .0
8 7 .2
8 3 .9
9 4 .5

94.1

8 5 .6
8 2 .8
9 1 .8

6 5 .0
8 3 .8
7 9 .8
9 2 .5

77.1

451
4511
4512

S h o e s t o r e s ...........................................................................
Je w e lry , lu g g a g e , a n d le a th e r g o o d s s t o r e s ............
S p o rtin g g o o d s , h obby, book, a n d m u s ic s to re s ...
S p o rtin g g o o d s a n d m u sic al in stru m en t s t o r e s ....
B ook, perio d ic al, a n d m u sic s t o r e s ..............................

1 2 0 .0

121.1
1 2 8 .3
1 0 8 .0

1 2 2 .5
1 2 5 .4
1 3 0 .4
1 1 6 .0

1 2 1 .5
132.9
137.9
1 2 3 .8

452
4521
4529
453
4531

G e n e ra l m e rc h a n d is e s t o r e s ..........................................
D e p a rtm e n t s t o r e s ..............................................................
O th e r g e n e ra l m e rc h a n d is e s t o r e s ..............................
M is c e lla n e o u s s to re re ta ile rs .........................................
F lo ris ts .....................................................................................

7 5 .3
84 .0
61 .4

7 9 .0
8 8 .3
6 4 .8
6 8 .0
75.9

8 3 .0
91 .6
6 9 .7
7 4 .2
85.1

8 8 .5
9 5 .0
7 7 .8
79.1
9 1 .4

9 0 .6
95.1
8 2 .6
8 7 .0
8 5 .4

92 .2
94 .7
87 .6
8 9 .5
8 3 .5

9 6 .9
9 8 .4

100.0
100.0
100.0
100.0
100.0

105.0
100.6
113.4
108.3
101.2

113.1
1 0 4 .5
1 2 9 .8
109.8
11 7 .3

1 1 9 .9
1 0 6 .3
145.9
11 1 .3
11 6 .0

12 4 .2
104.0
162.1
1 0 8 .4
108.6

13 0 .5
10 4 .7
1 7 7 .5
115.6
12 0 .7

4532

O ffice s u p p lie s , s ta tio n e ry a n d gift s t o r e s .................

6 6 .3
83.1
6 9 .2

7 1 .5
8 9 .7

8 7 .5
8 7 .3
8 9 .7

9 0 .9
90.2

9 1 .8
9 7 .4

100.0
100.0
100.0

11 3 .0
1 1 3 .5
105.0

11 8 .0
1 0 9 .8

124.1
1 1 5 .7

125.1

U s e d m e rc h a n d is e s t o r e s ...............................................
O th e r m isc e lla n e o u s s to re re ta ile rs .............................
N o n s to re re ta ile rs ...............................................................
E lectronic s h o p p in g a n d m ail-o rd er h o u s e s ............
V e n d in g m a c h in e o p e r a to r s ...........................................
D irect selling e s ta b lis h m e n ts .........................................

6 4 .6
84 .9

7 5 .8

4533
4539
454
4541
4542

1 4 0 .3
121.4

100.0
100.0
100.0

1 1 1 .3
118.2
114.1

101.6
125.4
1 4 1 .5
118.1

9 9 .6
14 2 .8
15 9 .8
127.1

100.0

9 6 .2

9 6 .3

100.0
100.0
100.0
100.0

97 .6
102.1
99.1
1 0 1 .4

9 8 .2

9 8 .3

9 8 .8
9 8 .4
9 5 .7
9 6 .7

10 5 .5
102.0
1 0 2 .4

4482
4483

4543

70 .6
75.1

79 .6
54 .4
4 3 .5
97.1

5 5 .0
4 6 .7
9 5 .4

7 4 .7
6 3 .4
5 0 .6
95.1
82.1

8 8 .9
8 0 .5
6 6 .7
5 8 .3
9 2 .8
79 .7

70 .0

67 .6

7 7 .5
6 9 .8
8 8 .5
96.1

7 8 .2

8 1 .4

7 5 .3
9 2 .4
9 5 .8

8 2 .3
9 7 .5
9 6 .5

N e w s p a p e r, b o o k , a n d d irectory p u b lis h e rs ............

9 7 .4

96.1

S o ftw are p u b lis h e rs ...........................................................
M otion p ictu re a n d vid eo exhibition .............................
R ad io a n d telev isio n b ro a d c a s tin g ..............................
C a b le a n d o th e r su b scrip tio n p ro g ra m m in g ............

2 8 .6
109.4
96.1
9 8 .8
64 .8
76 .3
99.1

30 .6
108 .9
9 7 .8
9 4 .3
6 8 .4
7 3 .8
9 4 .3

9 5 .8
4 2 .7
104.1
102.8
9 6 .0
7 4 .5
8 5 .6
9 5 .9

104.6
101.4
9 3 .6
7 9 .7
9 4 .8
9 3 .5

8 0 .5

8 3 .2

8 3 .3

89 .8
7 0 .7

9 7 .8
7 1 .7

104.4

9 2 .4
105.0

7 3 .8
6 2 .9
94.1
8 9 .2

9 3 .0
92 .3
9 4 .5

9 0 .5
80 .9
71.9
8 9 .3
9 4 .7

9 2 .5
9 9 .3

94 .3
95 .0
96.1

9 8 .0
91 .6
84 .4
96 .9
102.2

1 1 5 .0
9 3 .2

9 2 .8

1 0 4 .3

146.9
17 7 .5
11 0 .4
9 8 .7

169.6
2 0 9 .8
1 1 3 .3
110.2

9 8 .2
1 1 4 .3
1 0 5 .5
104.9

9 1 .9
121.9
104.2
106.1

131.9
1 0 9 .4

Transportation and warehousing
481
482111
48412
491

Air tra n s p o r ta tio n ................................................................
G e n e ra l freight trucking, lo n g -d is ta n c e .....................
U .S . P o s ta l s e r v ic e .............................................................

9 5 .3

103.2

8 4 .7
8 5 .7
9 5 .6
9 9 .0

9 0 .8
88 .6
98.1
9 8 .5

9 5 .3
5 1 .7

9 3 .0
64 .6
103.4
106.0
92 .0

9 3 .5

9 2 .7

10 4 .5
115.9
99 .9
99.1
1 2 9 .3

110.1

106.4

88.0
100.0
104.1
9 3 .7

100.0
100.0
100.0
100.0
100.0

10 8 .5

7 3 .0
9 9 .9
106.1
94 .4

113.0
102.0
9 9 .4
133.2

103.9
1 0 6 .5
9 8 .4
135.7

101.9
1 0 4 .7
9 4 .3
1 2 5 .3

108.1
1 0 6 .7
104.4
10 0 .4
13 1 .4

85.1
97.1
9 1 .9

90 .6
9 8 .3
9 4 .2

9 7 .5
103.0
93 .5

100.0
100.0
100.0

10 5 .5
114.2
9 5 .7

1 1 2 .7
134.3
9 4 .5

119.9
13 9 .0
9 0 .4

121.0
17 2 .7
8 7 .6

130.6
192.0
9 3 .5

9 0 .3

92 .9

96 .0

9 9 .3

100.0

98 .0

10 1 .5

1 0 4 .2

1 0 1 .6

1 0 3 .8

6 9 .5

106.1
7 5 .8

107.9
8 2 .0

101.1
90 .3

108.9
96 .7

100.0
100.0

101.2
9 3 .7

113.1
9 7 .8

1 1 2 .0
9 5 .9

112.1
9 3 .6

113.3
9 1 .4

8 4 .7
9 9 .7

9 9 .5
111.9

119.1
111.3

119.9
106.8

9 6 .2
101.4

92.1
102.1

1 0 0 .0
100.0

105.1
95 .8

99 .2
110.1

9 1 .8
116.6

7 8 .2
1 1 6 .7

92.1
123.9

8 5 .4

9 2 .9
10 1 .7

9 7 .0
10 0 .8

100.1
99 .2
96 .3
102.2
97 .6
102.4

1 0 0 .0
101.2

102.0
10 3 .7

104.1
10 4 .9

100.0
100.0
100.0
100.0

100.0
10 2 .4
102.1
1 0 0 .0

1 0 3 .6
101.1
99 .2

10 7 .7

9 7 .8
103.6
101.1
102.6

99 .2
100.6
9 6 .6
10 4 .7
99 .3
104.4

100.0
100.0

9 7 .5
102.7
106.4
121.5

93 .0
1 0 2 .3
9 7 .7
105.6
1 0 3 .8
112.7

1 0 2 .5
106.0
9 9 .4

105.1
11 1 .7
100.4

1 0 0 .8
106.6
10 8 .4
9 8 .2

1 0 2 .0
107.1
108.1
1 0 7 .2

9 0 .0
8 5 .6
10 4 .7
9 4 .9
116.2

9 1 .2
8 4 .3
100.4
9 3 .8
123.6

9 6 .7
8 8 .7
103.6
95 .9
124.9

102.9
9 2 .4
100.4
9 8 .8
114.7

98 .9
97.1
97 .9
101.6
103.2 1

100.0
100.0
100.0
100.0
100.0

105.0
102.7
10 3 .8
105.0
9 9 .4

106.9
103.6
100.4
10 9 .5
106.9

1 0 3 .0
9 4 .5
113V
107.6

1 0 9 .3
10 9 .5
9 3 .9
121.1
11 5 .0

1 0 3 .7
1 0 4 .2

92 .0
9 5 .4

107.0

Information
5111
5112
51213
5151
5152
5171
5172
5175

W ired te le c o m m u n ic a tio n s c a rrie rs .............................
W ire le s s te le c o m m u n ic a tio n s c a rrie rs .......................
C a b le a n d o th e r p ro g ram distrib u tio n ........................

Finance and insurance
52211

C o m m e rcia l b a n k in g ........................................................

Real estate and rental and leasing
532111
53212

P a s s e n g e r c a r re n ta l........................................................
i t u c k , trailer a n a h v re n ta l a n a le a s in g ....................

541213
54181

T a x p re p a ra tio n s e r v ic e s .................................................
A dvertising a g e n c i e s ..........................................................

7211
722

F o o d s e r v ic e s a n d drinking p la c e s .............................

Professional, scientific, and technical services

Accomodation and food services

7221
7222
7223
7224

L im ited-service e a tin g p l a c e s ...................................... .
D rinking p la c e s , alcoholic b e v e r a g e s ....................... .

82 .9
102.9
99.1
103.3
107.2
12 5 .7

102.3
9 8 .3
1 0 3 .3
106.9
121.2

1 0 3 .5
1 0 0 .8

Other services (except public administration)
8111
81211
81221
8123
81292

A utom otive re p air a n d m a in te n a n c e ..........................
F u n era l h o m e s a n d fu n e ral s e r v ic e s ........................
U rycleaning a n d lau n d ry s e r v ic e s ..............................
P h o to fin ish in g ..................................................................... ,

9 2 .8
81.6
96.1
9 5 .6
11 7 .3

8 6 .5
7 9 .8
9 4 .3
9 3 .2
115.6

108.6

9 0 .9
12 0 .2
133.6

No t e : D a sh in d ic a te s d a ta a r e not av a ila b le .


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Monthly Labor Review

September

2004

127

Current Labor Statistics:

52.

International Comparison

Unemployment rates, approximating U.S. concepts, in nine countries, quarterly data
A nnual a verage
C ountry

2002

2002

2003

1

II

III

2003

IV

U n ite d S t a t e s ...........

5 .8

6 .0

5 .7

5 .8

5 .7

I

II

5 .9

5 .8

2004
III

IV

I

6.1

6.1

5 .9

5 6
6 7

C a n a d a ........................

7 .0

6 .9

7.1

6 .9

6 .7

6 .9

7 .2

6 .4

6 .8

6.1

6 .7

6 .9
6 .4

7 .0

A u s t r a lia .......................

6 .3

6 .2

6 .2

6 .2

6.1

J a p a n 1..........................

5 .8

5 .7

5 .4

5 .3

5 .4

5 .4

5 .5

5 .4

5 .4

5 .4

5 .2

5.1

F r a n c e 1........................

5 .0

8 .7

9 .3

8 .5

8 .6

8 .7

8 .9

9 .0

9 .2

9 .4

9 .4

9 .4

G e r m a n y .....................

8 .6

9 .3

8 .3

8 .5

8 .7

8 .9

9 .2

9 .4

9 .4

9 .3

9 .2

Italy1 2.............................

9.1

8 .8

9 .2

9 .2

9.1

9 .0

9 .0

8 .8

8 .7

8 .6

S w e d e n .......................

8 .6

5.1

5 .8

5 .2

5 .0

5.1

5 .2

5 .2

U n ited K in g d o m .......

5 .6

5 .8

6 .6

5 .2

6 .2

5 .0

5.1

5 .2

5 .2

5.1

5.1

5 .0

5 .0

4 .9

4 .8

2 Q u a rte rly r a t e s a r e fo r t h e first m o n th of t h e q u a r te r.

q u a lific a tio n s a n d h isto ric a l d a ta , s e e C o m p a r a tiv e C iv ilia n L a b o r

NOTE:

S ta tis tic s , J u n e 2 3 , 2 0 0 4 ), o n t h e In te r n e t a t

F o rc e

Q u a rte rly fig u re s for F r a n c e a n d G e rm a n y a r e c a lc u la te d

b y a p p ly in g a n n u a l a d j u s t m e n t fa c to r s to c u r r e n t p u b lis h e d d a ta ,

S ta tis tic s ,

Ten

C o u n trie s ,

1 9 5 9 - 2 0 0 3 (B u re a u

of

L abor

http://www.bls.gov/fls/home.htm.

a n d t h e r e f o r e s h o u ld b e v ie w e d a s l e s s p r e c i s e In d ic a to rs of

M onthly a n d q u a rte rly u n e m p lo y m e n t r a te s , u p d a te d m o n th ly , a r e

u n e m p lo y m e n t u n d e r U .S . c o n c e p t s th a n t h e a n n u a l fig u re s . S e e

a l s o o n th is s ite .

128

Monthly Labor Review


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

September 2004

53.

Annual data: employment status of the working-age population, approximating U.S. concepts, 10 countries

[N u m b e rs in t h o u s a n d s ]

E m ploym ent status and country

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

1 2 9 ,2 0 0

1 3 1 ,0 5 6

1 3 2 ,3 0 4

1 3 3 ,9 4 3

1 3 6 ,2 9 7

1 3 7 ,6 7 3

1 3 9 ,3 6 8

1 4 2 ,5 8 3

1 4 3 ,7 3 4

1 4 4 ,8 6 3

1 4 6 ,5 1 0

1 4 ,3 0 8

1 4 ,4 0 0

1 4 ,5 1 7

1 4 ,6 6 9

1 4 ,9 5 8

1 5 ,2 3 7

1 5 ,5 3 6

1 5 ,7 8 9

1 6 ,0 2 7

1 6 ,4 7 5

1 6 ,8 1 9

8 ,6 1 3

8 ,7 7 0

8 ,9 9 5

9 ,1 1 5

9 ,2 0 4

9 ,3 3 9

9 ,4 1 4

9 ,5 9 0

9 ,7 5 2

9 ,9 0 7

1 0 ,0 9 2

6 5 ,4 7 0

6 5 ,7 8 0

6 5 ,9 9 0

6 6 ,4 5 0

6 7 ,2 0 0

6 7 ,2 4 0

6 7 ,0 9 0

6 6 ,9 9 0

6 6 ,8 7 0

6 6 ,2 4 0

6 6 ,0 1 0

2 4 ,4 8 0

2 4 ,6 7 0

2 4 ,7 6 0

2 5 ,0 1 0

2 5 ,1 3 0

2 5 ,4 6 0

2 5 ,7 9 0

2 6 ,0 7 0

2 6 ,3 5 0

2 6 ,5 9 0

2 6 ,7 3 0

3 9 ,1 0 2

3 9 ,0 7 4

3 8 ,9 8 0

3 9 ,1 4 2

3 9 ,4 1 5

3 9 ,7 5 4

3 9 ,3 7 5

3 9 ,3 0 2

3 9 ,4 5 9

3 9 ,4 1 3

3 9 ,2 7 6

2 2 ,5 7 0

2 2 ,4 5 0

2 2 ,4 6 0

2 2 ,5 7 0

2 2 ,6 8 0

2 2 ,9 6 0

2 3 ,1 3 0

2 3 ,3 4 0

2 3 ,5 4 0

2 3 ,7 5 0

2 3 ,8 8 0

7 ,0 1 0

7 ,1 5 0

7 ,2 1 0

7 ,3 0 0

7 ,5 4 0

7 ,6 2 0

7 ,8 5 0

8 ,1 5 0

8 ,3 4 0

8 ,3 0 0

8 ,3 0 0

4 ,4 4 4

4 ,4 1 8

4 ,4 6 0

4 ,4 5 9

4 ,4 1 8

4 ,4 0 2

4 ,4 3 0

4 ,4 8 9

4 ,5 3 0

4 ,5 4 4

4 ,5 6 7

2 8 ,1 6 5

2 8 ,1 4 9

2 8 ,1 5 7

2 8 ,2 6 0

2 8 ,4 1 7

2 8 ,4 7 9

2 8 ,7 6 9

2 8 ,9 3 0

2 9 ,0 5 3

2 9 ,2 8 8

2 9 ,4 9 0

1993

Civilian labor force

Participation rate1
6 6 .3

6 6 .6

6 6 .6

6 6 .8

67.1

67.1

67.1

67.1

6 6 .8

6 6 .6

6 6 .2

6 5 .5

6 5 .2

6 4 .9

6 4 .7

6 5 .0

6 5 .4

6 5 .8

6 5 .9

6 6 .0

6 6 .8

6 7 .3

6 3 .5

6 3 .9

6 4 .5

6 4 .6

6 4 .3

6 4 .3

6 4 .0

6 4 .4

6 4 .4

6 4 .4

6 4 .6

6 3 .3

63.1

6 2 .9

6 3 .0

6 3 .2

6 2 .8

6 2 .4

6 2 .0

6 1 .6

6 0 .8

6 0 .3

5 5 .4

5 5 .5

5 5 .4

5 5 .6

5 5 .5

5 5 .9

5 6 .3

5 6 .6

5 6 .8

5 7 .0

5 7 .0

5 7 .8

5 7 .4

57.1

57.1

5 7 .3

5 7 .7

5 6 .8

5 6 .6

5 6 .6

5 6 .3

56.1

4 7 .9

4 7 .3

47.1

47.1

4 7 .2

4 7 .6

4 7 .8

48.1

4 8 .3

4 8 .6

4 8 .8

5 7 .9

5 8 .6

5 8 .8

5 9 .2

6 0 .8

61.1

6 2 .6

6 4 .5

6 5 .8

6 5 .0

6 4 .6

6 4 .5

6 3 .7

64.1

6 4 .0

6 3 .3

6 2 .8

6 2 .8

6 3 .8

6 3 .7

6 4 .0

6 4 .0

6 2 .7

6 2 .6

6 2 .4

6 2 .4

6 2 .6

6 2 .5

6 2 .9

6 2 .9

6 2 .7

6 2 .9

6 2 .9

1 2 0 ,2 5 9

1 2 3 ,0 6 0

1 2 4 ,9 0 0

1 2 6 ,7 0 8

1 2 9 ,5 5 8

1 3 1 ,4 6 3

1 3 3 ,4 8 8

1 3 6 ,8 9 1

1 3 6 ,9 3 3

1 3 6 ,4 8 5

1 3 7 ,7 3 6

1 2 ,7 7 0

1 3 ,0 2 7

1 3,271

1 3 ,3 8 0

1 3 ,7 0 5

1 4 ,0 6 8

1 4 ,4 5 6

1 4 ,8 2 7

1 4 ,9 9 7

1 5 ,3 2 5

1 5 ,6 6 0

7 ,6 9 9

7 ,9 4 2

8 ,2 5 6

8 ,3 6 4

8 ,4 4 4

8 ,6 1 8

8 ,7 6 2

8 ,9 8 9

9 ,0 9 1

9 ,2 7 1

9,4 8 1

6 3 ,8 1 0

6 3 ,8 6 0

6 3 ,8 9 0

6 4 ,2 0 0

6 4 ,9 0 0

6 4 ,4 5 0

6 3 ,9 2 0

6 3 ,7 9 0

6 3 ,4 7 0

6 2 ,6 5 0

6 2 ,5 1 0

2 1 ,7 1 0

2 1 ,7 5 0

2 1 ,9 6 0

2 2 ,0 4 0

2 2 ,1 7 0

2 2 ,6 0 0

2 3 ,0 5 0

2 3 ,6 9 0

2 4 ,1 4 0

2 4 ,2 8 0

2 4 ,2 5 0

3 5 ,9 8 9

3 5 ,7 5 6

3 5 ,7 8 0

3 5 ,6 3 7

3 5 ,5 0 8

3 6 ,0 6 1

3 6 ,0 4 2 -

3 6 ,2 3 6

3 6 ,3 5 0

3 6 ,0 1 8

3 5 ,6 1 5

2 0 ,2 7 0

1 9 ,9 4 0

1 9 ,8 2 0

1 9 ,9 2 0

1 9 ,9 9 0

2 0 ,2 1 0

2 0 ,4 6 0

2 0 ,8 4 0

2 1 ,2 7 0

2 1 ,5 8 0

2 1 ,7 9 0

Em ployed

6 ,5 7 0

6 ,6 6 0

6 ,7 3 0

6 ,8 6 0

7 ,1 6 0

7 ,3 2 0

7 ,6 0 0

7 ,9 1 0

8 ,1 3 0

8 ,0 7 0

8 ,0 1 0

4 ,0 2 8

3 ,9 9 2

4 ,0 5 6

4 ,0 1 9

3 ,9 7 3

4 ,0 3 4

4 ,1 1 7

4 ,2 2 9

4 ,3 0 3

4 ,3 1 0

4 ,3 0 3

2 5 ,2 4 2

2 5 ,4 2 9

2 5 ,7 1 8

2 5 ,9 6 4

2 6 ,4 3 3

2 6 ,6 9 6

2 7 ,0 4 8

2 7 ,3 5 0

2 7 ,5 7 0

2 7 ,7 6 8

2 8 ,0 1 1

Em ploym ent-population ratio2
6 1 .7

6 2 .5

6 2 .9

6 3 .2

6 3 .8

64.1

6 4 .3

6 4 .4

6 3 .7

6 2 .7

6 2 .3

5 8 .5

5 9 .0

5 9 .4

59.1

5 9 .7

6 0 .4

6 1 .3

62.1

6 1 .9

6 2 .4

6 3 .0

5 6 .8

5 7 .8

5 9 .2

5 9 .3

5 9 .0

5 9 .3

5 9 .6

6 0 .3

60.1

6 0 .3

6 0 .7

6 1 .7

6 1 .3

6 0 .9

6 0 .9

6 1 .0

6 0 .2

5 9 .4

5 9 .0

5 8 .4

5 7 .5

57.1

49.1

4 9 .0

49.1

4 9 .0

4 9 .0

4 9 .7

5 0 .3

5 1 .4

5 2 .0

5 2 .0

5 1 .7

5 3 .2

5 2 .6

5 2 .4

5 2 .0

5 1 .6

5 2 .3

5 2 .0

5 2 .2

5 2 .2

5 1 .5

5 0 .9

4 3 .0

4 2 .0

4 1 .5

4 1 .6

4 1 .6

4 1 .9

4 2 .3

4 2 .9

4 3 .6

44.1

4 4 .6

5 4 .2

5 4 .6

5 4 .9

5 5 .7

5 7 .8

5 8 .7

6 0 .6

6 2 .6

6 4 .2

6 3 .2

62.1

5 8 .5

5 7 .6

5 8 .3

5 7 .7

5 6 .9

5 7 .6

5 8 .4

60.1

6 0 .5

6 0 .7

6 0 .3

5 6 .2

5 6 .5

5 7 .0

5 7 .4

5 8 .2

5 8 .6

59.1

5 9 .4

5 9 .5

5 9 .6

5 9 .8

8 ,9 4 0

7 ,9 9 6

7 ,4 0 4

7 ,2 3 6

6 ,7 3 9

6 ,2 1 0

5 ,8 8 0

5 ,6 9 2

6 ,8 0 1

8 ,3 7 8

8 ,7 7 4

1 ,5 3 9

1 ,3 7 3

1 ,2 4 6

1 ,2 8 9

1 ,2 5 2

1 ,1 6 9

1 ,0 8 0

962

1,031

1 ,1 5 0

1 ,1 5 9

914

829

739

751

759

721

652

602

661

636

611

1 ,6 6 0

1 ,9 2 0

2 ,1 0 0

2 ,2 5 0

2 ,3 0 0

2 ,7 9 0

3 ,1 7 0

3 ,2 0 0

3 ,4 0 0

3 ,5 9 0

3 ,5 0 0

2 ,7 7 0

2 ,9 2 0

2 ,8 0 0

2 ,9 7 0

2 ,9 6 0

2 ,8 7 0

2 ,7 4 0

2 ,3 8 0

2 ,2 1 0

2 ,3 1 0

2 ,4 8 0

3 ,1 1 3

3 ,3 1 8

3 ,2 0 0

3 ,5 0 5

3 ,9 0 7

3 ,6 9 3

3 ,3 3 3

3 ,0 6 5

3 ,1 1 0

3 ,3 9 6

3 ,6 6 1

2 ,3 0 0

2 ,5 1 0

2 ,6 4 0

2 ,6 5 0

2 ,6 9 0

2 ,7 5 0

2 ,6 7 0

2 ,5 0 0

2 ,2 7 0

2 ,1 6 0

2 ,1 0 0

440

490

480

440

370

300

250

240

210

230

320

416

426

404

440

445

368

313

260

227

234

264

2 ,9 1 6

2 ,7 1 6

2 ,4 3 9

2 ,2 9 7

1 ,9 8 5

1 ,7 8 3

1,721

1 ,5 8 0

1 ,4 8 3

1 ,5 2 0

1 ,4 7 9

Unem ployed

Unem ploym ent rate

U n ite d K in g d o m ..........................................................................

6 .9

6.1

5 .6

5 .4

4 .9

4 .5

4 .2

4 .0

4 .7

5 .8

6 .0

1 0 .8

9 .5

8 .6

8 .8

8 .4

7 .7

7 .0

6.1

6 .4

7 .0

6 .9
6.1

1 0 .6

9 .4

8 .2

8 .2

8 .3

7 .7

6 .9

6 .3

6 .8

6 .3

2 .5

2 .9

3 .2

3.4

3 .4

4.1

4 .7

4 .8

5.1

5 .4

5 .3

1 1 .3

11 .8

11.3

11.9

1 1 .8

11.3

1 0 .6

9.1

8 .4

8 .7

9 .3

8 .0

8.5

8.2

9.C

9 .9

9.3

8.5

7 .8

7.9

8 .6

9 .3

10.2

11.2

11.8

11.7

1 1 .9

12.C

11.5

10.7

9.6

9.1

8 .8

6.2

6.9

6.7

6.C

4 .9

3.S

3.2

2.9

2.6

2 .7

3 .8

9.4

9.5

9.1

9.9

10.1

8.4

7.1

5.8

5.C

5.1

5 .8

10.4

9.5

8.7

8.1

7.0

6.C

6.C

5.8

5.1

5.2

5 .0

1 L a b o r fo r c e a s a p e r c e n t o f t h e w o r k in g - a g e p o p u la tio n .

F o r fu rth e r q u a lific a tio n s a n d h isto rical d a t a , s e e C o m p a r a tiv e C iv ilia n L a b o r F o rc e S ta tis tic s ,

2 E m p lo y m e n t a s a p e r c e n t of th e w o r k in g - a g e p o p u la tio n .

T e n C o u n trie s , 1 9 5 9 -2 0 0 3 (B u re a u of L a b o r S ta tis tic s , J u n e 2 3 , 2 0 0 4 ), o n th e In te r n e t a t:

NOTE: S e e n o t e s o n t h e d a t a fo r in fo rm a tio n o n b r e a k s in s e r ie s .

h t i p \/M ww


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

i s .g o v /f is /h o m e h t n .

Monthly Labor Review

September 2004

129

Current Labor Statistics:

54.

International Comparison

Annual indexes of manufacturing productivity and related measures, 12 countries

[1992 = 100]
Item and country

1960

1970

1980

1990

1991

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

Output per hour
United S ta te s ....................................................................
C a n a d a ...............................................................................

37.5
32.9

70.5
72.9
63.2
65.4

96.9
93.4
94.4
96.8

97.9
95.3
99.0
99.1

102.1
105.8
101.7
102.5

110.8
103.3
108.4

113.8
112.4
111.0
113.2

117.0
109.7
116.1
116.3

121.3
113.5
121.0
125.5

126.5
115.5
121.2
126.9

133.7
122.1
126.7
125.5

142.1
129.3
135.9
130.8

142.7
127.0
135.9
132.6

155.9
130.5
139.5
141.7

39.0
52.0
46.2
38.5
59.1
52.2
4 3 .2

61.6
77.2
78.6
69.1
77.9
73.1
54.4

93.9
99.0
96.6
98.7
98.1
94 .6
89.2

97.0
98.3
96.1
99.0
98.2
95.5
93.8

101.0
101.8
101.2
102.0
99.6
107.3
103.9

108.9
109.6
104.8
113.1
99.6
117.8
108.5

114.4
112.3
107.9
117.3
100.7
124.5
106.5

114.7
114.7
108.3
119.3
102.5
129.5
105.8

121.7
120.4
110.3
121.4
102.0
141.0
107.7

127.9
122.0
110.8
124.1
99.9
149.5
109.2

133.0
121.4

24.6
18.8
37.6
27.2
30.0

110.6
127.0
103.6
162.7
114.4

143.2
127.0
113.6
132.7
106.6
175.5
121.9

148.0
127.8
115.9
132.3
108.9
170.3
126.4

152.1
131.0
114.3
133.1
110.9
184.3
127.6

33.4
10.7
30.7
44.4
30.0
41.5
23.0
31.9
57.7
45.9
67.5

58.9
39.2
57.6
73.9
57.7
70.9
48.1
59.8
91.0
80.7
90.2

75.8
83.6
60.4
78.2
94.4
81.6
85.3
84.4
76.9
104.9
90.7
87.2

101.6
106.0
97.1
101.0
102.8
99.1
99.1
99.4
99.0
101.4
110.1
105.4

98.3
99.0
102.0
100.7
101.5
99.8
102.3
99.3
99.8
99.0
104.1
100.1

103.5
105.9
96.3
97.0
95.6
95.7
92.4
96.5
97.7
101.7
101.9
101.5

111.1
114.1
94.9
101.4
105.6
100.3
95.1
102.4
104.5
104.6
117.0
106.2

118.4
119.6
98.9
104.2
111.6
104.9
95.2
107.2
108.2
107.3
131.9
107.8

121.3
119.6
103.0
105.9
106.7
104.6
92.5
105.4
108.9
110.3
136.4
108.7

127.9
127.7
106.5
112.7
115.2
109.7
95.7
108.8
111.6
114.2
146.5
110.7

133.1
133.9
100.2
114.4
115.7
115.0
97.7
110.7
114.9
113.7
158.3
111.4

139.5
144.9
101.9
114.4
117.7
118.7
95.8
110.3
117.6
113.6
172.5
112.2

146.1
159.2
109.2
119.9
122.1
124.3
100.1
113.7
122.8
112.8
188.3
114.9

137.3
153.6
105.5
120.4
127.5
128.0
99 .9
114.6
121.7
113.4
183.1
1134.0

139.8
158.0
103.4
121.6
127.8
128.1
99.6
113.8
119.7
112.6
189.3
109.4

92.1
88.3
77.8
170.7
157.8
140.3
142.3
93.5
169.8
153.6
168.3
22 4 .6

104.4
107.1
104.4
174.7
149.5
147.8
136.3
104.0
155.5
153.9
154.7
20 8 .8

107.5
114.6
95.6
119.7
109.6
132.5
110.5
107.4
111.2
134.7
124.0
160.5

104.8
113.5
102.9
104.3
103.7
105.6
100.1
102.9
100.3
103.4
116.4
118.1

100.4
103.9
103.1
101.5
102.1
102.9
104.1
103.3
100.8
100.8
109.0
106.6

101.4
100.1
94.7
94.7
96.2
94.7
90.8
95.4
95.8
102.1
94.9
92.7

103.6
103.0
91.9
93.6

104.0
106.4
89.1
92.0

103.6
109.0
88.7
91.0

105.4
112.4
88.0
89.8

105.2
115.9
82.7
90.2

104.4
118.7
80.4
91.2

102.8
123.1
80.3
91.7

96.3
120.9
77.7
90.8

89.7
121.1
74.2
85.8

14.9

3.8
4 .3
8.1
1.8
6.2
4 .7
4.1
2.9

2 3 .7
17.1
16.4
13.7
11.1
10.5
20 .7
5.3
19.4
11.8
10.7
6.1

55.6
47.5
58.5
52.5
45.0
41.2
53.6
30.4
60.5
39.0
37.3
32.1

90.8
88.3
90.6
90.1
92.7
90.9
89.4
87.6
89.8
92 .3
87.8
82.9

95.6
95.0
96.5
97.3
96.0
96.4
91.5
94.2
94.8
97.5
95.5
93.8

102.7
102.0
102.7
104.8
103.0
103.1
106.4
105.7
104.5
101.5
97.4
105.1

26.4
31.3
30.1
13.6
21 .7
27.8
7.5
32.9
12.6
15.0
9.8

31.1
4 3 .8
4 1 .7
22.4
26 .8
39.8
11.9
50.4
20.0
2 0 .6
14.1

78.8
65.2
92.6
80.3
52.2
67.0
69.4
38.7

93.7
94.6
95.9
93.0
93.5
96.8
90.3
90.7
91.1
94.2
92.9
92.9

97.6
99.6
97.5
98.1
96.5
99.3
93.1
98.0
95.7
99.2
100.0
99.9

United S ta t e s .....................................................................
C a n a d a ................................................................................
J a p a n .....................................................................
B elgium ................................................................................
D e n m ark ................................................
F ra n c e ...................................................................
G e rm a n y .........................................................

32.9
11.0
19.4
12.0
23.4
10.4

N e th e rla n d s ........................................................
N orw ay...........................................................
S w e d e n ........................................................
United K ingdom ...........................................

14.3
15.3
11.0
16.9
15.6

36.0
15.5
27.0
18.0
25 .7
17.1
22 .3
2 4 .5
17.4
23.1
19.1

93.7
98.0
83.9
89.5
91.2
94.1
87 .3
93.3
87.9
9 3 .6
9 1 .3
93.8

97.6
105.1
91.8
92.3
91.0
93.1
87.5
97.3
90.0
95.0
96.3
100.0

B elgium ...............................................................................
D e n m a rk ..............................................
F ra n c e ................................................

N e th e rlan d s...................................................
N orw ay.............................................
S w e d e n ....................................................
United Kingdom .........................................

37.8
13.8
18.0
28.1
19.9
29.2

54.9

107.3

Output
United S ta te s ..................................................
C a n a d a .........................................................
J a p a n ..........................................................
B elgium .......................................................
D e nm ark.......................................................
F ra n c e .......................................................
G e rm a n y ...............................................................
Italy...............................................................
N e th e rla n d s ..........................................
N orw ay..................................................
S w e d e n .......................................................
United K ingdom ..........................................

Total hours
United S ta t e s .....................................................
C a n a d a .........................................................
J a p a n .....................................................................
B elgium .................................................................
D e n m a rk ...............................................................
F ra n c e ................................................................
G e rm a n y ...................................................................
Italy...............................................................
N e th e rla n d s ..............................................
Nonway..............................................................
S w e d e n ..............................................................
United K ingdom ..............................................................

_

_

_

-

_

92.1
86.8
97.7
92.4
105.0
99.4
97.9

91.7
84.8
99.4
92.3
106.6
105.9
101.2

91.2
80.6
97.3
91.2
107.6
105.3
102.8

90.2
79.5
98.6
91.9
112.0
103.9
102.8

89.9
80.1
99.9
92.6
113.7
105.9
101.9

89.2
78.9
99.8
92.6
109.6
106.0
98.1

86.8
78.8
100.1
92.5
105.9
107.3
94.3

86 .5
78.2
98.9
91.9
104.1
107.5
89.8

84.2
76.1
99.5
89.9
101.6
102.7
85.7

105.6
103.7
104.7
106.1

107.9
106.0
108.3
109.2

109.4
107.0
109.1
111.1

111.5
109.3
112.6
115.2

117.4
111.7
115.4
117.0

122.1
115.8
114.8
118.5

131.1
119.6
113.7
120.6

134.3
123.8
114.5
127.2

140.6
126.8
122.8
136.5

Compensation per hour
United S ta te s ................................................................
C a n a d a ................................................................
J a p a n .............................................................
B elgium ..............................................................
D e nm ark ..........................................................
F ra n c e ...................................................................
G e rm a n y ...................................................
N e th e rla n d s ...........................................
N orw ay...................................................
S w e d e n ...............................................................
U nited K ingdom ...................................................

Unit labor costs:

10.0
4.3
5.4

_

_

_

-

_

_

106.5
111.8
106.8
109.0
104.4
99.8
108.0

110.4
117.6
111.3
112.1
109.2
106.8
109.5

112.2
123.3
119.0
114.4
113.6
115.2
111.3

111.8
125.7
123.0
117.2
118.7
121.0
116.1

112.7
127.6
122.2
122.0
125.7
125.6
123.1

116.6
130.6
124.2
126.0
133.0
130.3
130.4

123.4
137.4
127.8
132.0
140.5
136.8
137.7

128.2
142.0
132.4
138.9
148.2
143.8
144.2

132.4
145.5
135.6
146.0
157.2
149.2
149.2

100.6
96.4
101.0
102.3
103.7
102.0
104.5
104.5
102.4
101.9
90.8
100.6

9 8 .5
93.6
101.4
97.9
96.2
97.8
102.0
101.9
96.4

93.5
97.5
94.0
95.5
103.2
97.8
107.5
109.8
95.9
110.8
89.0
105.2

91.9
96.2
93.0
91.8
99.4
91.9
104.5
111.4
96.5
116.4
85.8
107.8

92.8
96.7
95.2
92.2
102.8
88.1
104.6
110.3
98.3
125.7
84.0
112.7

9 1 .3
94.9
90.6
94.4
103.7
87.6
107.6
112.3
99.1
128.4
80.1
114.0

92.3
92.5
83.6
92.2
101.8
86.2
108.1
112.5
99.5
131.9
77.9
113.0

94.1
97.4
84.4
95.9
101.3
86.6
111.2
114.2
105.0
136.1
84.4
114.2

90.2
97.1
88.0
96.4
102.1
87.1
111.1
118.7
109.7

104.8
84.7
99.6

94.8
94.3
97.5
96.4
96.4
96.5
104.7
103.2
95.6
108.4
85.8
102.8

141.8
80.9
116.9

100.6
90.3
115.3
95.1
96.5
95.3
98.7
81.8
96.9
89.2
67.8
85.6

98.5
82.8
125.8
94.2
91.4
93.4
98.2
77.9
93.2
92.3
64.0
86.3

94.8
83.0
131.6
105.2
104.0
102.5
114.2
78.0
104.8
106.4
70.0
91.8

93.5
86.4
109.5
99.1
107.5
101.2
111.6
87.7
100.0
106.6
77.3
93.0

91.9
84.0
97.4
82.4
90.8
83.3
94.0
80.6
87.0
102.1
65.4
99.9

92.8
78.8
92.2
81.6
92.6
79.1
92.9
78.2
87.2
103.5
61.5
105.7

91.3
77.2
101.0
80.2
89.5
75 .3
91.5
76.2
84.3
102.2
56.4
104.4

92.3
75.3
98.4
67.8
76.0
64.2
79.7
66.1
73.3
93.0
49 .5
96.9

94.1
76.0
88.0
68.4
73.4
62 .6
79 .5
65.1
75.0
94.0
4 7 .6
9 3 .0

90.2
74.8
89.1
72.6
78.2
66.4
83.9
71.4
82.8
110.3
48.5
99.4

N ational currency b a sis

United S ta te s .......................................................
C a n a d a ...........................................................
J a p a n .............................................................
B elgium .........................................................
D e n m a rk ...............................................................
F ra n c e .............................................................
G e rm a n y ................................................................
Italy....................................................................
N e th e rla n d s ...................................................
N orw ay....................................................
S w e d e n ...........................................................
United K ingdom ..............................................

Unit labor costs:

87.6
50.0
51.0
59.0

U.S. dollar b a s is
78.8
67.4
51.8
88.3
55.9
83.9
59.6
55.7
77.5
62.9
70.2
7 7 .7 1

NOTE: D a ta for G e rm an y for y e a rs b efo re 1991 a r e for th e form er W est G erm any. D ata for 1991 onw ard a r e for unified G erm any. D ash indicates d a ta not available.

130

Monthly Labor Review


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

September 2004

55.

Occupational injury and illness rates by industry, United States
Incidence rates per 100 full-time workers3
Industry and type of case

19891

1990

1991

1992

1993 4 19 944 1995 4 1996 4 1997 4 1 9 984 1 9 9 9 4 2000 4 2001 4

PRIVATE SECTOR5
T otal c a s e s .......................................................................................................
Lost w orkday c a s e s ........................................................................................
Lost w o rk d a y s ...................................................................................................

6.1
3.0

5.7
2 .8

7 .3
3 .4

7.1
3 .6

7.3
3 .6

-

-

-

-

5.9
3.7

4 .9
2 .9

4 .4
2 .7

4 .7
3 .0

4 .0
2 .4

-

-

-

-

9.9
4 .5

9.5
4.4

8 .8
4 .0

8 .6
4 .2

8.8
4.1

8.9
3.9

8.5
3.8

8.4

8.1

3.9

3.8

3.6

7 .4
3.4

7.1
3.3

3.1

6 .3
3 .0

84.0

86.5

93.8

-

-

-

-

-

-

-

10.8
5.4

5.0

10.0
4.7

9.7
4.3

8.7
3.9

8 .4
4.1

7 .9
3.9

108.3

11.6
5.4
126.9

11.2

100.9

11.6
5.9
112.2

"

-

-

-

8 .5
4 .8
137.2

8.3
5.0
119.5

7.4
4 .5
129.6

7.3
4.1
2 0 4 .7

6.8
3.9

6.3
3.9

6.2
3.9

5.4
3.2

-

-

-

14.3
6 .8
143.3

14.2
6.7
147.9

13.0
6.1
148.1

13.1
5.8
161.9

12.2
5.5

11.8
5.5

10.6
4 .9

-

-

-

-

-

-

-

-

-

13.9
6 .5
137.3

13.4

10.9

8.5
3.7

3 .9

8 .0
3 .7

7 .8
3 .9

6 .9

5.1

9.0
4.0

8 .4

5.1

9.8
4 .4

3 .5

137.6

132.0

12.2
5.4
142.7

11.5

6.4

12.0
5.5

-

-

-

-

-

-

-

-

-

11.1

10.2
5.0

9 .9
4 .8

9.0
4.3

8.7

5.1

4 .3

8.2
4.1

7 .8
3 .8

7.6
3.7

7 .8
4 .0

8 .6
4 .0
78 .7

8.4

6 .7

Agriculture, forestry, and fishing5
Total c a s e s .......................................................................................................
Lost w orkday c a s e s ........................................................................................
Lost w o rk d a y s ...................................................................................................

10.9
5 .7

Mining
Total c a s e s .......................................................................................................
Lost w orkday c a s e s ........................................................................................
Lost w o rk d a y s ...................................................................................................

“

Construction
Total c a s e s .......................................................................................................
Lost w orkday c a s e s ........................................................................................
Lost w o rk d a y s ...................................................................................................
G e n e ra l building co n tra cto rs:
Total c a s e s .......................................................................................................
Lost w orkday c a s e s ........................................................................................
Lost w o rk d a y s ...................................................................................................

8 .3
4.1

7 .9
4 .0

H eavy c o n stru c tio n , e x c e p t buildinq:
Total c a s e s .......................................................................................................

13.8

13.8

Lost w orkday c a s e s ........................................................................................
Lost w o rk d a y s ...................................................................................................

6 .5
147.1

6.3
144.6

12.8
6.0

12.1
5 .4

160.1

165.8

-

-

-

-

-

"

-

-

-

S p e c ia l tr a d e s co n tra c to rs :
T otal c a s e s .......................................................................................................
Lost w orkday c a s e s ........................................................................................

14.6
6 .9

14.7
6.9

13.5
6.3

12.8
5.8

12.5
5.8

11.1
5.0

10.4
4 .8

10.0
4.7

9.1
4.1

8 .9
4 .4

8 .6
4 .3

8.2
4.1

Lost w o rk d a y s ...................................................................................................

144.9

153.1

151.3

13.8
6.1
168.3

-

-

-

-

-

-

-

-

-

13.1
5.8
113.0

13.2
5.8
120.7

12.7

12.5
5 .4
124.6

12.1
5.3

12.2

5.6
121.5

5.5

11.6
5.3

10.6
4.9
_

10.3
4 .8

9.7
4 .7
_

9 .2
4 .6
_

9 .0
4 .5
_

8.1
4.1
_

14.1

14.2

13.6

13.4

12.8

11.6

11.3

10.7

10.1

8 .8

6.0

5.7

5.7

5.6

5.1

5.1

5 .0

4 .8

1 1 6 .5

123.3

122.9

5.5
126.7

13.1
5 .4

13.5

6 .0

4 .3
_

18.4
9 .4

16.8
8.3
172.0

16.3
7.6
165.8

15.9

15.7

14.9

14.2

7.0

6.8

13.0
6 .7

12.1

7.7

13.5
6.5

13.2

7.6

177.5

18.1
8.8
172.5

16.1
7.2

16.9
7.8

15.9
7.2

14.8
6.6
128.4

14.6
6.5

15.0
7.0

13.9
6 .4

12.2
5.4

12.0
5 .8

11.4

11.5
5 .9

11.2

5 .7

15.5
7 .4
149.8

15.4
7.3
160.5

14.8
6.8
156.0

13.6
6.1
152.2

13.8
6.3

13.2
6.5

12.3
5.7

12.4
6.0

11.8
5.7

11.8
6 .0

10.7
5 .4

10.4

18.7

17.0
7.3

16.8
7.2

16.5
7.2

15.0
6 .8

15.0
7.2

14.0
7 .0

12.9

12.6
6 .3

10.7

6 .3

Manufacturing
Total c a s e s .......................................................................................................

D urable g o o d s:
T otal c a s e s .......................................................................................................

L um ber a n d w o o d p roducts:
Total c a s e s ...................................................................................................

F urniture a n d fixtures:
Total c a s e s ..................................................................................................

S to n e , clay, a n d q la s s p ro d u c ts:
T otal c a s e s ..................................................................................................

P rim ary m etal industries:
T otal c a s e s ..................................................................................................

F a b ric a te d m etal p ro d u c ts:
T otal c a s e s ..................................................................................................

6 .8

6.1

5 .9

5 .5

10.6
5 .5

11.0
5.7

10.1
5.1

8.1
168.3

19.0
8.1

17.7
7.4

17.5
7.1

180.2

169.1

175.5

18.5
7.9
147.6

18.7
7.9
155.7

17.4
7.1
146.6

16.8
6.6
144.0

16.2
6.7

16.4
6.7

15.8
6.9

14.4
6.2

14.2
6.4

13.9
6 .5

12.6
6 .0

11.9
5.5

11.1
5 .3

12.1
4 .8
86 .8

12.0
4.7
88.9

11.2
4 .4
86.6

11.1
4.2
87.7

11.1
4.2

11.6
4 .4

11.2
4.4

9.9
4.0

10.0
4.1

9 .5
4 .0

8 .5
3 .7

8 .2
3.6

11.0
6 .0

9.1
3 .9
77.5

9.1
3.8
79.4

8.6
3.7

8.4

8.3
3.5

8 .3
3.6

7.6
3.3

6.8
3.1

6.6
3.1

5 .9
2 .8

5.7

5 .7

2 .8

2 .9

5.0
2 .5

83.0

3.6
81.2

17.7

17.8

18.3

18.7

18.6

16.3

15.4

7.1

7.8

7.9

7 .0

6.6

13.7
6 .4

12.6

7 .0
166.1

14.6
6 .6

13.7

6.9
153.7

18.5
7.1

19.6

6 .8
138.6

6 .3

6 .0

186.6

5 .6
2 .5
55 .4

5.9
2.7
57 .8

6.0
2.7
64 .4

5.9
2.7
65 .3

5.6
2.5

5 .9
2.7

5.3
2 .4

5.1
2.3

4 .8
2 .3

4 .0
1.9

4 .0
1.8

4 .5
2 .2

4 .0
2 .0

11.1
5.1
97.6

11.3
5.1
113.1

11.3
5.1

10.7
5.0
108.2

10.0
4.6

9.9
4.5

9.1
4.3

9.5
4.4

8.9
4.2

8.1
3.9

8.4
4 .0

7.2
3.6

6 .4
3.2

5.3
11.1

Industrial m ac h in e ry a n d eq u ip m en t:
T otal c a s e s ..................................................................................................

E lectronic a n d o th e r electrical e q u ip m en t:
T otal c a s e s ..................................................................................................

T ra n sp o rtatio n eq u ip m en t:
Total c a s e s ..................................................................................................

In s tru m e n ts a n d re la te d p ro d u c ts:
Total c a s e s ..................................................................................................

M iscellan e o u s m an u fa ctu rin q industries:
Total c a s e s ..................................................................................................
Lost w o rk d a y s .............................................................................................

104.0

S e e footnotes at end of table.


https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis

Monthly Labor Review

September 2004

131

Current Labor Statistics:

Injury and Illness

55. Continued—Occupational injury and illness rates by industry,' United States
Incidence rates per 100 workers3

Industry and type of case2
1989 1

1990

1991

1992

1993 4 1994 4 1 9 954 1996 4 1 9 9 7 4

1998 4

1999 4

2000 4

2001 4

8.2

7.8
4.2

7.8
4.2

6.8
3 .8

12.7
7.3

12.4
7.3

10.9
6.3

5.5
2 .2

6.2
3.1

4 .2

6 .4
3.2

6.0
3 .2

5.2
2 .7

6.1
3 .0

5.0
2 .4

6 .5
3 .4

6.0
3.2

5.1
2 .6

4.6
2 .4

4 .2
2 .2

4 .0
2.1

3 .7
1.9

2 .9
1.4

10.7
5 .8

4 .8

N o n d u rab le g o o d s:
Total c a s e s ..............................
Lost w orkday c a s e s ...............
Lost w o rk d a y s ..........................

11.6

11.7

11.5
5.5
119.7

11.3

10.7

10.5

5.3
121.8

5.0

5.1

19.5
9.9
2 0 7 .2

18.8
9.5
2 1 1 .9

17.6
8.9

17.1
9.2

16.3
8.7

15.0
8.0

2 0 2 .6
7.7

6 .4

3.2
62.3

2 .8

6.0
2 .4

5.8
2.3

5.3
2 .4

5.6
2.6

6.7
2 .8

5 .9
2 .7

6 .4
3 .4

52.0

4 2 .9

-

-

-

-

-

-

9.6
4.0

10.1
4 .4

8.7
4 .0

8.2
4.1

7.8
3.6

6.7

7 .4

3.1

3 .4

88.3

9.9
4.2
87.1

9.7
4.1

85.1

-

-

-

-

-

-

-

8.6
3.8
80.5

8.8
3.9
92.1

9.2
4.2

9.0
3.8

8.9
3.9

8.2
3.6

7.4

7.0

3 .3

3.1

6.2
2 .6

5 .8
2 .8

99.9

9.5
4.0
104.6

-

-

-

-

-

-

-

12.7
5.8
132.9

12.1

Lost w o rk d ay c a s e s .........
Lost w o rk d a y s ....................

11.2
5.0
122.7

11.0
5.0
125.9

9.9
4.6

9.6
4 .5

8.5
4.2

7.9

7.3
3 .7

7.1

3.8

3 .7

7 .0
3 .7

-

-

-

-

P rinting a n d publishing:
Total c a s e s ........................
Lost w orkday c a s e s ..
Lost w o rk d a y s ............

-

-

-

6.9
3.3

6.9
3.1

6.7
3.0

6.4
3.0

6.0
2 .8

5 .7
2 .7

5 .4
2 .8

5 .0
2 .6

C h e m ic a ls a n d allied p roducts:
T otal c a s e s .................................
Lost w orkday c a s e s ...............
Lost w o rk d a y s ..........................

5.6
116.9

9.9
4.9

9.2

8.8
4.4

4.6

4.3
-

F o o d a n d kin d red p ro d u c ts:
T otal c a s e s ...........................
Lost w orkday c a s e s ...........
Lost w o rk d a y s......................

20.0
9.9

T o b a c c o p ro d u c ts:
Total c a s e s ...........................
Lost w o rk d ay c a s e s ..
Lost w o rk d a y s ............
T extile mill p ro d u c ts:
T otal c a s e s ................
Lost w orkday c a s e s ..
Lost w o rk d a y s ............

4.2

A pparel a n d o th e r textile p ro d u c ts:
Total c a s e s ........................................
Lost w orkday c a s e s .........
Lost w o rk d a y s...................
P a p e r a n d allied p roducts:
Total c a s e s ........................

5.5
124.8

14.5
8 .0

13.6
7.5

-

6.7

6.7
3.2

7.3
3.2

63.8

6.9
3.3
69.8

74.5

74.8

-

-

-

-

-

-

-

7.0
3.2
6 3 .4

6 .5
3.1
6 1 .6

6.4
3.1
62 .4

6.0
2.8
64.2

5.9
2 .7

5.7
2.8

5.5
2 .7

4 .8
2 .4

4 .8
2 .3

4 .2
2.1

4 .4
2 .3

-

-

-

-

-

-

-

6.6
3.3
68.1

6.6
3.1
77 .3

6.2
2 .9
68.2

5 .9
2.8
71.2

5.2
2 .5

4.7
2 .3

4 .8
2 .4

4.6
2.5

4 .3
2 .2

3 .9
1.8

4.1
1.8

-

-

-

-

-

-

-

R u b b e r a n d m isc e lla n e o u s p la s tic s p ro d u c ts:
Total c a s e s .............................................................
Lost w o rk d ay c a s e s ..............................................
Lost w o rk d a y s .........................................................

16.2
8.0
147.2

16.2

15.1
7.2
150.9

14.5
6.8
153.3

13.9
6.5

14.0
6.7

12.9
6.5

12.3
6.3

11.9
5 .8

11.2

10.1
5 .5

-

-

-

L e a th e r a n d le a th e r p ro d u c ts:
Total c a s e s ..............................
Lost w o rk d ay c a s e s .........................................................
Lost w o rk d a y s ...................................................................

-

-

-

-

-

13.6
6.5
130.4

12.1
5.4

12.1
5.5

12.0
5.3

11.4
4.8

10.7

5.9
152.3

12.5
5.9

4 .5

10.6
4 .3

9 .8
4 .5

10.3
5 .0

9 .0
4 .3

8.7
4 .4

140.8

128.5

-

-

-

-

-

-

-

9.6
5.5
134.1

9.3
5 .4

9.5
5 .4

9.1
5.2

8.7

8.2

5.5

5.1

4 .8

7 .3
4 .3

7 .3
4 .4

6 .9
4 .3

4.3

140.0

9.1
5.1
144.0

9.3

5 .3
121.5

-

-

-

-

-

-

-

Total c a s e s ............................................................................
Lost w orkday c a s e s .............................................................
Lost w o rk d a y s ........................................................................

8 .0
3.6
6 3 .5

3.5
65.6

8.4
3.5
80.1

8.1
3.4

7 .9
3 .4

7.5
3.2

6.8
2 .9

6 .7
3 .0

6 .5
2 .8

6.1
2 .7

5 .9
2 .7

6 .6
2 .5

72.0

-

-

-

-

W h o le sa le tra d e :
Total c a s e s ............................................................................
Lost w o rk d ay c a s e s .............................................................
Lost w o rk d a y s ........................................................................

-

-

-

-

7.7
4.0
71.9

7.4
3 .7

7.2
3.7

7.8
3.7

7.7
3.8

7.5
3.6

6.6
3.4

6 .5
3.2

6 .5
3 .3

6 .3
3 .3

5 .8
3.1

7 1 .5

79.2

7.6
3.6
8 2 .4

-

-

-

-

-

-

-

-

8.1
3.4

8.1
3 .4

7.7
3.3

8.7
3 .4

8.2
3.3

7.9
3.3

7.5
3.0

6.9
2 .8

6.8
2 .9

6 .5
2 .7

6.1
2 .5

5 .9
2 .5

5.7
2 .4

60 .0

63.2

69.1

79.2

-

-

-

-

-

-

-

2 .0
.9
17.6

2 .4
1.1

2 .4

2.9

2 .7

1.2
32 .9

1.1

2.6
1.0

2 .4

1.1
24.1

2.9
1.2

.9

2 .2
.9

.7
.5

1.8
.8

1.9
.8

1.8
.7

2 7 .3

-

-

-

-

-

-

-

6.0

6.2

7.1

6.7

2 .8
6 0 .0 1

3.0
68 .6

2 .8

6 .5
2 .8

6.4
2 .8

6.0
2.6

5.6
2 .5

5.2
2 .4

4 .9
2 .2

4 .9
2 .2

4 .6
2 .2

-

-

-

-I

-

-I

-I

P etro leu m a n d coal p roducts:
T otal c a s e s ..............................
Lost w orkday c a s e s ...............
Lost w o rk d a y s ..........................

7.8
151.3
12.1

Transportation and public utilities
Total c a s e s ...........................................................................
Lost w o rk d ay c a s e s .............................................................
Lost w o rk d a y s .......................................................................

9.2

Wholesale and retail trade

R etail tra d e :
T otal c a s e s ............................................................................
Lost w o rk d ay c a s e s .............................................................
Lost w o rk d a y s ........................................................................

7.9

7.6
3 .4

Finance, insurance, and real estate
Total c a s e s ............................................................................
Lost w orkday c a s e s ..............................................................
Lost w o rk d a y s .........................................................................

Services
T otal c a s e s .................
Lost w orkday c a s e s ..
Lost w o rk d a y s ............

5.5
2 .7
51.2

2 .8
56 .4

5.8

8.7

6.9

5.3
2 .8

N = n u m b e r of injuries a n d illn e sse s or lost w orkdays;

-------------------------------------------tA.v uuuvu W
II mo \ ji a u u c u u iu u u z> u id l Lz/cibb-

ific a tio n M a n u a l , 1 987 Edition. F or th is re a s o n , th ey a r e not strictly c o m p a ra b le with d a ta

EH = total h o u rs w o rk ed by all e m p lo y e e s durin g th e c a le n d a r y ea r; a n d

for t h e y e a rs 1 9 8 5 -8 8 , w hich w e re b a s e d on th e S ta n d a rd In d u s tria l C la s s ific a tio n
M a n u a l , 1 972 Edition, 1 977 S u p p le m en t.

2 0 0 ,0 0 0 = b a s e for 100 full-time e q u iv a le n t w o rk ers (w orking 4 0 h o u rs p e r w e ek , 5 0 w e e k s
p e r year).

2 B eginning with th e 1992 su rv e y , th e a n n u a l s u rv e y m e a s u r e s only nonfatal injuries a n d

4 B eginning with th e 1 993 su rvey, lost w o rk d ay e s tim a te s will not b e g e n e ra te d . A s of 1992,

illn e s s e s , w hile p a s t s u rv e y s c o v e re d both fatal a n d n onfatal in cid en ts. To b e tte r a d d r e s s

BLS b e g a n g e n e ra tin g p e rc e n t distributions a n d th e m ed ian n u m b e r of d a y s a w a y from w ork

fatalities, a b a s ic e le m e n t of w o rk p la ce sa fe ty , BLS im p le m en ted th e C e n s u s of F atal
O c c u p atio n al Injuries.

by industry a n d for g ro u p s of w o rk ers su s ta in in g sim ilar w ork disabilities.
5 E x clu d e s fa rm s with fe w er th a n 11 e m p lo y e e s s in c e 1976.

T h e in cid en c e r a te s re p re s e n t th e n u m b e r of injuries a n d illn e s s e s o r lost w o rk d ay s p er
100

132

full-tim e

w o rk e rs

and

w e re

c a lc u la te d

as

(N/EH)

X

2 0 0 ,0 0 0 ,

Monthly Labor Review September 2004


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NOTE: Dash indicates data not available.


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56. Fatal occupational injuries by event or exposure, 1997-2002
Fatalities
Event or exposure1

2002

1997-2001

2001 2

average

Num ber

Percent

N um ber

T o ta l.................................................................................................................

6 ,0 3 6

5 ,9 1 5

5 ,5 2 4

100

Transportation incidents......................................................

2 ,5 9 3

2 ,5 2 4

2 ,3 8 1

43

H ig h w a y in c id e n t...................................................................................................

1,421

1 ,4 0 9

1 ,3 7 2

25

C o llisio n b e t w e e n v e h ic le s , m o b ile e q u i p m e n t ...................................

697

727

635

11

M oving in s a m e d ire c tio n ..........................................................................

126

142

155

3

M oving in o p p o s ite d ire c tio n s , o n c o m in g ..........................................

254

257

202

4
3

M oving in in te r s e c tio n .................................................................................

148

138

145

V e h ic le s tru c k s ta tio n a ry o b je c t o r e q u i p m e n t ....................................

300

297

326

6

N o n c o llisio n in c id e n t........................................................................................

369

339

373

7

J a c k k n if e d o r o v e r tu r n e d — n o c o llis io n ..............................................

300

273

312

6

N o n h ig h w a y (farm , in d u strial p r e m is e s ) in c id e n t...................................

368

326

322

6
3

202

158

164

A irc raft.........................................................................................................................

248

247

192

3

W o rk e r s tru c k b y a v e h ic le ...............................................................................

382

383

356

6

W a te r v e h i c l e .........................................................................................................

99

90

71

1

68

62

64

1

964

908

840

15

709

643

609

11

S h o o tin g ...............................................................................................................

567

509

469

8

S ta b b i n g ...............................................................................................................

64

58

58

1

O th e r , in clu d in g b o m b in g .........................................................................

78

76

82

1

O v e r tu r n e d ...........................................................................................................

Assaults and violent acts......................................................

S elf-in flicte d in ju rie s .............................................................................................

221

230

199

4

Contact with objects and equipment.....................................

995

962

873

16

S tr u c k b y o b je c t.....................................................................................................

562

553

506

9

S tr u c k b y falling o b je c t...................................................................................

352

343

303

5

S tr u c k b y flying o b je c t....................................................................................

58

60

38

1

C a u g h t in o r c o m p r e s s e d by e q u ip m e n t o r o b j e c ts .............................

290

266

231

4

C a u g h t in ru n n in g e q u ip m e n t o r m a c h in e ry .........................................

156

144

110

2

C a u g h t in o r c r u s h e d in c o lla p s in g m a te r ia ls ..........................................

126

122

116

2

Falls.................................................................................................................................
Fall from l a d d e r ..................................................................................................
Fall fro m s c a ffo ld , s t a g i n g ............................................................................

737

810

714

13

654

700

634

11

111

123

126

2

155

159

143

3

91

91

87

2

61

84

63

1

529

499

538

10

C o n ta c t w ith e le c tric c u r r e n t...........................................................................

291

285

289

5

C o n ta c t w ith o v e r h e a d p o w e r lin e s ..........................................................

134

124

122

2

C o n ta c t w ith te m p e r a t u r e e x t r e m e s ............................................................
E x p o s u r e to c a u s tic , n o x io u s , o r a lle r g e n ic s u b s t a n c e s ....................

41

35

60

1

106

96

2
2

F all o n s a m e le v e l................................................................................................

52

49

98
49

O x y g e n d e f ic ie n c y ...............................................................................................
D ro w n in g , s u b m e r s i o n ...................................................................................

89

83

90

71

59

60

1

Fires and explosions...........................................................

197

188

165

3

21

24

13

-

Other events or exposures3..................................................
1 B a se d o n th e

1 9 9 2 bls O c c u p a tio n a l Injury a n d

Illn e s s

2 T h e b l s n e w s r e l e a s e i s s u e d S e p t . 2 5 , 2 0 0 2 , r e p o r te d a

to tal o f 5 ,9 0 0 fa ta l w o rk in ju ries for c a l e n d a r y e a r 2 0 0 1 . S in c e
a d d itio n a l

1 5 jo b -re la te d

3 T o ta ls fo r 2 0 0 1 e x c lu d e fa ta litie s fro m t h e S e p t e m b e r 11
te rr o ris t a tta c k s .

C la s s ific a tio n S tr u c tu r e s .

th e n , a n

1

fa ta litie s w e r e

id en tified ,

b rin g in g t h e to tal jo b -re la te d fa ta lity c o u n t for 2 0 0 1 to 5 ,9 1 5 .

3 In c lu d e s th e c a t e g o r y "B odily re a c tio n a n d e x e rtio n ."
NOTE:

T o ta ls

fo r

m a jo r c a t e g o r i e s

c a t e g o r i e s n o t s h o w n s e p a r a t e ly .

m ay

in c lu d e s u b ­

P e rc e n ta g e s m ay not a d d

to to ta ls b e c a u s e o f ro u n d in g . D a s h i n d ic a te s l e s s t h a n 0 .5
p e r c e n t.

Monthly Labor Review

September 2004

133

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Productivity and costs

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1-3; 30-33