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MONTHLY LABOR
REVIEW
Volume 131, Number 8
September 2008
The effect of business ownership change on occupational employment and wages
3
After a business changes ownership, employment falls but wages rise in some occupations,
whereas in other occupations, employment levels are maintained and wages fall
Dina Itkin
Extended mass layoffs after 2001: a comparison of New York and the Nation
24
BLS data reveal that layoff activity in New York was somewhat elevated in the years that
followed the 2001 recession
Bruce J. Bergman
Conference report
Knowing younger workers better: information from the NLSY97
42
Papers from the 10th anniversary conference of the National Longitudinal Survey of Youth,
1997 cohort addressed schooling, employment, adolescent behaviors, and many other issues
Dan Black, Robert Michael, and Charles Pierret
Regional trends
Multiple jobholding in States, 2007
James Campbell
52
53
Departments
Labor month in review 2
Précis 54
Book reviews 55
Current labor statistics 57
Editor-in-Chief: Michael D. Levi Executive Editor: William Parks II Managing Editor: Leslie Brown Joyner Editors: Brian
I. Baker, Casey P. Homan Book Review Editor: James Titkemeyer Design and Layout: Catherine D. Bowman, Edith W.
Peters Contributing editor: Lawrence H. Leith Contributor: Stephen E. Baldwin
Labor Month In Review
The September Review
Our first article this month examines
the effect of changes in business ownership on workers related to the types
of jobs they hold. Analyzing microdata from the Occupational Employment Statistics (OES) survey, Dina
Itkin demonstrates that there are differential outcomes by occupation on
employment and wage levels resulting from new ownership. Among a
number of areas of inquiry, she identifies the industry sectors most affected by ownership change. Further, she
investigates the relationship between
changes in occupational composition
resulting from new ownership and
the employment size of the affected
business. The author identifies some
limitations of the study, noting, for
instance, that some staffing changes
might be in transition and only partially captured using her methodology.
Bruce J. Bergman compares mass
layoff activity in the New York City
area with that of the Nation as a
whole in the years prior to and after
the 2001 recession. With the largest
metropolitan workforce in the country, trends in the Big Apple regarding
the separation of workers from their
employers are always going to be of
interest. Bergman finds a “qualitatively different” pattern in the industry distribution of layoffs prior to, and
after, 2001, in New York, in contrast
to the national experience.
A trio of authors with a demonstrated interest in longitudinal studies provides a Conference Report in
this month’s MLR focusing on information from the 1997 cohort of
Monthly Labor Review • September 2008
the National Longitudinal Survey of
Youth. In May of this past summer,
BLS hosted a conference highlighting
the latest research from this survey,
and Dan Black, Robert Michael, and
Charles Pierret provide a “brief and
informal characterization” of some
of the more than a dozen studies
presented. They summarize the research on topics ranging from social
behaviors (such as marriage and offspring and the influence of siblings)
to education (including the effects of
parental resources on educational attainment) to the changing characteristics of youth employment.
Finally this month, James Campbell provides his annual update to patterns of multiple jobholding among
the various States.
A profile of the working poor
The majority of the 36.5 million persons in poverty in the United States
are children or adults outside of the
labor force. However, there are many
people who are active participants in
the labor force for at least half a year,
but whose incomes still fall below the
official poverty level. Each year the
Bureau publishes data on these socalled “working poor.”
In 2006, it is estimated that 7.4
million individuals were in these circumstances, meaning they spent 27
weeks or more working or looking
for work, but lived at or below the
official poverty threshold relevant to
their family structure. They made up
5.1 percent of all persons in the labor
force for 27 weeks or more, down a
bit from 2005.
Some of the socioeconomic factors
that often are cited as contributing to
labor market outcomes are found to
influence who falls into the workingpoor status. Persons with the least
amount of education, for instance,
make up a far higher percentage of
the working poor – almost 14 percent
– than those with a college degree
(less than 2 percent). Persons in occupations that tend to be lower paying have a higher probability of being
among the working poor, as do parttime, as compared to full-time, workers. Married couple families facing
the extra expenses of childrearing are
much more likely to be among the
working poor than married couple
families without children.
A Profile of the Working Poor,
2006 can be found online at http://
www.bls.gov/cps/cpswp2006.pdf
Happy Birthday, TED!
Who is TED, you ask? As noted in
this column before, “he” is The Editor’s Desk, a daily feature published
by BLS on its Web site. TED is a reliable source of fresh content posted
every business day. It was the first
online-only publication available
from the Bureau. Since the first issue
was published in September 1998,
TED hasn’t missed a day of work, as
over 2,400 entries have been issued so
far. Congratulations to TED, and to
all who help produce this feature so
reliably.
For additional information about the
10th anniversary of The Editor’s Desk,
please go to http://www.bls.gov/opub/
ted/tenyears.htm
Business Ownership Change
The effect of business ownership change
on occupational employment and wages
An analysis of business establishment microdata reveals that,
after a business changes ownership, employment falls,
but wages rise, in occupations that performed analytical,
clerical, and production work; by contrast, employment levels
are maintained, but wages fall, in service occupations
Dina Itkin
Dina Itkin is an
economist in the
Office of Employment
and Unemployment
Statistics, Bureau of
Labor Statistics. E-mail:
itkin.dina@bls.gov
E
very year, thousands of U.S. businesses are bought, sold, or merged
to raise profits, reduce costs, increase
market share, or otherwise interact in the
dynamic economy. The national level of
business ownership change peaked in the
late 1990s, when the Nation was experiencing rapid economic growth, and declined
gradually through 2002.1 After 2003, the
number and asset trade value of ownership
changes rose steadily again. Volume in 2006
exceeded that in 2005 by 38 percent and
surpassed a 2000 record. The year-over-year
asset trade volume of ownership change as
of July 2007 was up 60 percent globally and
41 percent in the United States.2
Existing literature and anecdotal evidence
have found varying effects of ownership
changes on company profits, labor productivity, wages, and staffing in specific industries. For example, research using Census
Bureau data on manufacturing companies
found that ownership changes led to reductions in employment and wages at auxiliary
(support) offices, but had little effect on employment at production plants.3 Two other
studies—one of manufacturing firms4 and the
other of food-manufacturing firms5—found
that ownership changes resulted in employment and wage increases overall, but led to
job losses in large firms.
Trends in personnel changes in all sectors
of the economy are of interest to economists,
business owners, and workers, but there is
little, if any, recent empirical research on the
effects of ownership changes on detailed occupational employment. Such information
provides insight into the specific jobs and
skill sets that are in demand when firms reorganize or redirect their business strategies.
This study uses a recent large sample
of business establishment microdata to
examine how overall employment and occupational composition are affected when
establishments undergo a change in ownership. The study resulted in a number of interesting findings: after ownership changes,
(1) employment levels of occupations that
performed analytical, clerical, and production work were least likely to be maintained,
and most of these groups’ wages shifted toward higher ranges; (2) employment levels
of service occupations such as health care,
education, and protection services were
more likely to be maintained, but most of
these groups’ wages shifted toward lower
ranges, on average; (3) overall, employment
declines were seen in establishments that
changed ownership; and (4) among the industries that contracted the most, declines
were concentrated in occupations that serve
a support function in the industry, rather
Monthly Labor Review • September 2008
Business Ownership Change
than in occupations that are core to the industry’s output.
These findings tended to be supported across establishments of different sizes, with decreases in the share of
support occupations such as office and administrative
support, management, and sales occupations in all size
classes.
Methodology
This study was conducted with the use of microdata
from the Occupational Employment Statistics (OES)
survey. The OES program surveys approximately 200,000
establishments every 6 months, taking 3 years to collect
its full sample of 1.2 million establishments. Establishments are eligible for selection again after 3 years. The
data set consisted of all business establishments that reported to the OES survey twice over a period of 6 years.
Those establishments were put into two subsamples on
the basis of whether or not they changed ownership, as
defined by a change in the Unemployment Insurance
(UI) account number. Included in the study were microdata from all 50 States and the District of Columbia,
from establishments that reported occupational employment for all of their employees and wage data for most
of their employees.6
All establishments covered by State Unemployment
Insurance have an assigned UI account number. When
a firm changes ownership, it normally refiles with the
Unemployment Insurance program and receives a new
UI number. By contrast, the Quarterly Census of Employment and Wages (QCEW) program’s Longitudinal
Database (LDB) assigns each establishment a unique
LDB number that does not change, even if the ownership
changes. A total of 277,027 establishments reported to
the OES survey exactly twice during a 6-year period from
2000 to 2006.7 Of the establishments that reported twice
with the same LDB number, 254,829 had the same UI
number the second time they reported. These establishments serve as this study’s subsample of establishments
that did not change ownership (the control subsample).
The remaining 22,198 establishments had different UI
numbers the second time they reported and serve as the
study’s subsample of establishments that changed ownership (the ownership change subsample). Each establishment in either subsample has longitudinal occupational
staffing data for two points in time. The first reports are
included in the predecessor group, whose establishments
reported data between 2000 and 2003. The second reports
are included in the successor group, whose establishments
reported data between 2003 and 2006.
Monthly Labor Review • September 2008
Limitations of the study
Elements of the OES sampling strategy may create a bias
toward larger establishments in the study’s subsamples.
The reason is that sample selection within geographic area
and industry group strata is approximately proportional to
size, in order to provide the most occupational coverage.
Although there are more small units in the subsamples,
larger units are more likely to be selected at two points in
time and included in the subsamples. This bias is enhanced
by the fact that the study uses unweighted employment.
Although a change in UI account number in establishments with the same LDB number represents an ownership change most of the time, limitations to this definition
exist. A change in UI number does not necessarily indicate
a change in ownership (it could be the result of a change
in the type of business entity, as, for example, when a business incorporates), and perhaps not all ownership changes
were marked by a UI number change. To facilitate the
identification of establishments that changed ownership,
factors such as employment, trade names, physical addresses, and telephone numbers were used in determining
whether to maintain the LDB number.
The microdata do not differentiate among types of ownership changes, such as mergers, takeovers, divestitures, or
buyouts. If the ownership change represents a merger or
an acquisition, then changes in the acquiring establishment
are not measured; only employment data from the acquired
establishment are captured in this study. For example, if an
establishment was bought by another company, the study
would capture predecessor and successor data only for the
establishment with the same LDB number before and after
the purchase. A related limitation of the study is that the
data do not indicate whether labor was voluntarily or involuntarily removed, or whether it was contracted out or
outsourced, after the ownership change. Also, because the
time between the first and second reporting is at least 3
years for all establishments, the study might not capture
staffing changes that occurred immediately before or after
the ownership change. In some cases, the transition might
be only partially complete at the second reporting; in other
cases, the transition may already have begun at the first reporting, in anticipation of a future takeover.
Overall employment trends
Certain industries were more likely to change ownership
relative to other industries in the study subsample and to the
economy as a whole. Table 1 shows, in order by column, the
industry distributions of establishments that reported twice,
Table 1.
Concentration of establishments, by industry sector, in the ownership change subsample and across all
establishments, 2000–06
Industry sector
Number of
units that
reported
twice
Number of
units that
changed
ownership
Total.....................................................................
1
277,027
22,198
Information.................................................................
6,858
793
Accommodation and food services...................
15,283
1,760
Administrative and support and waste
management and remediation services.....
13,436
1,351
Retail trade.................................................................. 41,261 3,875
Manufacturing........................................................... 40,480 3,469
Finance and insurance............................................
10,713
915
Health care and social assistance.......................
26,317
2,226
Wholesale trade........................................................
18,742
1,516
Transportation and warehousing.......................
10,221
814
Real estate and rental and leasing.....................
7,632 576
Mining..........................................................................
1,618
122
Management of companies and enterprises
2,176
162
Professional and technical services...................
16,163
1,126
Utilities.........................................................................
1,754
121
Arts, entertainment, and recreation..................
6,465 418
Other services, except public administration.....
18,805
1,204
Construction..............................................................
21,357
1,316
Educational services................................................
11,396
273
1
Details do not sum to total because some industries are not listed
separately and some establishments lack an industry classification. The
industry sector of agriculture, forestry, fishing, and hunting is excluded
the industry distributions of establishments that changed
ownership, and the percentage of establishments that
changed ownership in each industry. The industries listed
are sorted by the percent that changed ownership. Industries
in which at least 10 percent of establishments changed ownership were information, accommodation and food services,
and administrative and support and waste management and
remediation services. The two columns headed “Percent distribution...” serve as an indication of industry distribution in
the ownership change subsample relative to the industry’s
representation in the economy. Industries that represented
a large proportion of the ownership change subsample
relative to the economy as a whole included manufacturing,
retail trade, information, health care and social assistance,
transportation and warehousing, and accommodation and
food services. At the more detailed industry level, the OES
data are consistent with other findings8 which show that,
in 2003, most ownership changes were in business services,
prepackaged software, commercial banks and bank holding
companies, real estate, mortgage bankers and brokers, and
oil and gas and petroleum refining.
Overall, there was a decline in total employment from
the predecessor group to the successor group after owner-
Percent
that
changed
ownership
Percent
distribution
of
ownership
change
subsample
Average
number of
privatesector
establishments
in 2005,
QCEW
1
1
8.01
100
8,294,662
11.56 3.57
141,871
11.52
7.93 572,791
Percent
distribution of
private sector
establishments
in 2005,
QCEW
100
1.71
6.91
1
10.06
6.09 426,681 5.14
9.39
17.46
1,038,585
12.52
8.57
15.63 365,351 4.40
8.54 4.12 462,381 5.57
8.46
10.03
689,010
8.31
8.09
6.83
601,625
7.25
7.96 3.67
212,309
2.56
7.55
2.59 351,329 4.24
7.54
.55
26,313
.32
7.44
.73 43,239
.52
6.97 5.07
902,710
10.88
6.90
.55
16,260
.20
6.47
1.88
118,614
1.43
6.40 5.42
1,102,054
13.29
6.16 5.93
845,843
10.20
2.40
1.23
78,410
.95
because the OES and QCEW have incomplete coverage of that sector. OESdesignated government industries also are excluded.
ship changes. Total employment in the predecessor group
was 2,018,250, and total employment in the successor
group was 1,890,986, a decrease of more than 6.31 percent.9 This employment decrease occurred despite overall
private-sector employment growth of 2.82 percent between
2002 and 2005.10 Almost half (10,677) of the 22,198 establishments that changed ownership experienced a decrease
in employment, 9,517 saw an increase in employment, and
the remaining 2,004 had no change in employment. Although employment decreased overall in the ownership
change subsample, employment change varied by industry,
establishment size, and occupation.
The distribution of the ownership change subsample
and the control subsample is shown by establishment size
in table 2. In the control subsample, there was an aggregate
shift toward medium and large sizes, while in establishments that changed ownership, there was an aggregate shift
toward smaller sizes. After establishments changed ownership, the concentration of establishments increased in the
1-to-9-employee and 10-to-49-employee size classes and
decreased in the three larger size classes. The concentration
in the 1-to-9-employee size class grew by nearly 5 percent in the ownership change subsample, while it grew by
Monthly Labor Review • September 2008
Business Ownership Change
Table 2.
Concentration of establishments in the OES sample, by size, in the ownership change subsample and the
control subsample, 2000–06
Ownership change subsample
Size of establishment
Number of Number of
predecessor successor
units
units
Difference
between
number of
predecessor
and
successor
units
Control subsample
Percent
change
Total..................................................
22,198
22,198
…
…
1–9 employees...................................... 5,277 5,530
253 4.79
10–49 employees.................................
9,094
9,151 57
.63
50–249 employees..............................
6,199 5,973
–226
–3.65
250–999 employees............................
1,412
1,335
–77
–5.45
1,000 or more employees.................
216
209
–7
–3.24
substantially less in the control subsample. Likewise, the
number of 10-to-49-employee establishments increased
in the ownership change subsample, while it decreased
in the control subsample. These shifts suggest that, after
ownership changes, the size distribution of establishments moved toward smaller establishments; that is, more
establishments shrank than grew. Because these numbers
capture only overall total concentrations at two different
times, the last section of this article examines employment
changes by establishment size.
Changes by occupational group
Changes in employment levels. After ownership changes,
changes in employment were spread across several occupations, with more than half of the occupational groups seeing declines in employment and other occupational groups
seeing employment increases. Table 3 presents the changes
in employment in each occupational group after ownership
changed. As shown in the column headed “Employment
difference,” the occupations that decreased in employment
level were production; office and administrative support;
sales and related; management; computer and mathematical science; business and financial operations; architecture
and engineering; transportation and material moving;
building and grounds cleaning and maintenance; personal
care and service; installation, maintenance, and repair; arts,
design, entertainment, sports, and media; construction and
extraction; and legal occupations.
At the other end of the spectrum, the occupational
groups that grew after ownership changes were health care
practitioner and technical; protective service; health care
support; education, training, and library; food prepara Monthly Labor Review • September 2008
Number of Number of
predecessor successor
units
units
254,829
69,585
108,834
60,024
14,057
2,329
254,829
70,721
107,500
60,101
14,170
2,337
Difference
between
number of
predecessor
and
successor
units
Percent
change
…
1,136
–1,334
77
113
8
…
1.63
–1.23
.13
.80
.34
tion and serving; community and social services; and life,
physical, and social science occupations. Because changes
in level do not convey growth or decline relative to other
occupational groups, an analysis of the employment shares
of total predecessor and successor employment follows.
Relative changes in employment shares. Table 3 also shows
the percentage-point difference between the predecessor
and successor employment shares in both subsamples. Occupational groups are labeled “less likely” or “more likely”
to be retained, on the basis of their change in employment
share in the ownership change subsample relative to the
control subsample. Employees who were less likely to be
retained are in occupations whose employment shares (1)
shrank in the ownership change subsample while they
grew in the control subsample, (2) grew in the ownership
change subsample by less than they grew in the control
subsample, or (3) shrank in the ownership change subsample by more than they shrank in the control subsample. This set of occupations (those which are less likely
to be retained) is plotted to the right of the diagonal in
chart 1. For each occupational group shown in the chart,
the further the point that is associated with it lies from
the origin and the diagonal, the greater is the difference
between the employment shares in establishments that
changed ownership and in establishments that did not
change ownership.
Employees who performed analytical, clerical, and production work were less likely to be retained after ownership changes. The occupational groups that shrank in
the ownership change subsample while they grew in the
control subsample (occupational groups located in quadrant IV) were computer and mathematical science; busi-
Table 3.
Occupational employment level and difference in share in the ownership change subsample and the control
subsample, 2000–06
Percentage-point
difference between
predecessor
and successor
employment share
Ownership change subsample
Control subsample
Occupational Group
Ownership
change
subsample1
Occupational groups
less likely to be retained
Computer and
mathematical science....
Business and financial
operations..........................
Arts, design, entertain ment, sports, and media...
Legal ......................................
Production.............................
Management........................
Sales and related.................
Office and administrative
support................................
Architecture and
engineering........................
Life, physical, and social
science.................................
Occupational groups
more likely to be retained
Food preparation and
serving related..................
Transportation and
material moving...............
Installation, maintenance,
and repair...........................
Building and grounds
cleaning and
maintenance......................
Protective service................
Health care support...........
Health care practitioner
and technical.....................
Education, training, and
library...................................
Community and social
services................................
Construction and
extraction............................
Groups with a change
of less than 0.01 in either
subsample
Personal care and
service..................................
Farming, fishing, and
forestry.................................
1
2
PredSucPredSucPredSuccessor
ecessor cessor
SucPredControl
Employ- ecessor
ecessor cessor
employ- employ- ecessor cessor Employ- employ- employsubment
ment
ment employ- employment
ment
sample employ- employ- difference ment
ment
ment
share
share
share
ment difference share
ment
(percent) (percent)
(percent) (percent)
–0.72
0.14
–.28
.39
–.03
–.01
–1.05
–.86
–.58
67,063 49,262
74,172
64,278
–17,801 3.32
2.61 432,022 472,447 40,425
–9,894 3.68 3.40
635,571 733,116
2.04
2.19
97,545 3.00 3.39
.07
19,136 17,435 –1,701
.95
.92
216,138 235,383
19,245
1.02
1.09
.01 4,818 4,293
-525
.24
.23
86,609 91,014 4,405
.41
.42
–.54 320,946 280,789 –40,157
15.90
14.85 2,217,795 2,149,982 –67,813
10.49
9.95
–.52
94,876 72,694 –22,182 4.70 3.84
980,344 888,859 –91,485 4.63 4.11
–.29
199,818 176,232 –23,586
9.90
9.32 1,794,334 1,771,712 –22,622
8.48
8.20
–.48
–.28 321,625 292,198
–29,427
15.94
15.45 3,336,426 3,348,698
12,272
15.77
15.49
–.21
–.06 48,962 41,897
–7,065
2.43
2.22 404,330 400,902
–3,428
1.91
1.85
11,263 324
.54
.60
176,926 198,318
21,392
.84
.92
2,865 5.64
6.18
1,069,685 1,086,022
16,337 5.06 5.02
8.83
1,670,394 1,684,016
13,622
.05
.08
10,939
.53
–.03
113,913 116,778
.23
–.11
173,556 166,968
.09
–.06
82,013
78,499
–3,514 4.06 4.15
.01
.87
.77
–.04
.11
.17
65,291
68,638
66,298
61,425
80,719
76,718
–3,866 3.24 3.25
772,076 780,072
7,996 3.65 3.61
12,081 3.40 4.27 551,749 587,624 35,875
2.61
2.72
10,420 3.28 4.06 577,304 626,014 48,710
2.73
2.90
1.02
.45
106,778 119,360
–6,588
8.60
12,582 5.29
7.79
798,334 802,064 3,730 3.77 3.71
6.31
1,306,749 1,432,698
125,949
6.18
6.63
2.50
2,262,029 2,375,172
113,143
10.69
10.99
.97 307,033 321,000
13,967
1.45
1.48
.40
.29 42,235 47,190 4,955
.10
.03
18,266
837
.11
.09 58,491 56,922
–1,569
2.90 3.01
858,143 896,039 37,896 4.06 4.14
(2)
.11 55,579 52,035
–3,544
2.75
2.75
607,194 643,456 36,262
.02
(3) 5,674 5,765
91
.28
.30
Numbers are affected by rounding.
Slight negative differences.
17,429
2.09
7.90
.86
3
90,503
93,366
2,863
2.87
2.98
.43
.43
Slight positive difference.
Monthly Labor Review • September 2008
Business Ownership Change
Chart 1.
Ownership
change
subsample
1.5
The effect of business ownership change on different types of occupations, 2000–06: percentagepoint difference between predecessor and successor employment shares
Ownership
change
subsample
Health care practitioner
and technical
d
ine
1
M
0.5
ly
like
e
r
o
to
eta
be r
1
Protective service
Health care support
Food preparation and serving related
Education, training, and library
Community and social services
Construction and extraction
Life, physical, and social science
Transportation and material moving
Installation, maintenance, and repair
0
0.5
Personal care
and service
0
Building and grounds cleaning
and maintenance
Farming, fishing,
and forestry
Arts, design, entertainment, sports, and media
Legal
Architecture
Business and financial operations
and engineering
Office and administrative support
Sales and related
Computer and mathematical science
ned
Management
etai
r
e
b
Production
ly to
–0.5
–1
Less
–1.5
1.5
Quadrant I
Quadrant II
–1
like
–1.5
Quadrant IV
Quadrant III
1.5
–0.5
–1
–0.5
0
0.5
1
1.5
Control subsample
ness and financial operations; arts, design, entertainment,
sports, and media; and legal occupations. The following
occupational groups shrank by more in the ownership
change subsample than they shrank in the control subsample (occupational groups located to the right of the
diagonal in quadrant III): production, management, sales
and related, office and administrative support, and architecture and engineering occupations. Life, physical, and
social science occupations grew in the ownership change
subsample, but by less than they grew in the control subsample (the occupational group located to the right of the
diagonal in quadrant I).
By contrast, employees who were more likely to be
retained were in occupations that (1) grew in the ownership change subsample while they shrank in the control
subsample or (2) grew in the ownership change subsample by more than they grew in the control subsample.
(None shrank in the ownership change subsample by
less than they shrank in the control subsample.) The set
of occupations in which employees were more likely to
be retained is plotted to the left of the diagonal in the
chart.
Service-related jobs, such as health care, education, and
Monthly Labor Review • September 2008
protection, were the most likely to be retained after ownership changes. The occupational groups that grew in the
ownership change subsample while they shrank in the control subsample (those occupations located in quadrant II)
were food preparation and serving related; transportation
and material moving; installation, maintenance, and repair;
and building and grounds cleaning and maintenance occupations. Occupational groups that grew by more in the
ownership change subsample than in the control subsample
(those located to the left of the diagonal in quadrant I) included protective service; health care support; health care
practitioner and technical; education, training, and library;
community and social services; and construction and extraction occupations. The types of jobs that were less likely
or more likely to be retained after ownership changes varied by industry, as the next section details.
Changes within occupational groups
Examining detailed changes within occupational groups
helps uncover trends among different business functions,
such as human resources, marketing, and sales. The occupations discussed in this section and listed in table 4
Table 4.
Difference between predecessor and successor occupational employment level and share in the ownership change
subsample, by detailed occupation, 2000–06
Occupation
Predecessor
employment
level
Management occupations
Chief executives............................................................................... 4,000
Marketing managers...................................................................... 3,802
Compensation and benefits managers................................... 534
Successor
employment
level
2,514
2,286
783
Business and financial operations occupations
Claims adjusters, examiners, and investigators....................
1,973
1,249
Compliance officers, except agriculture, construction,
health and safety, and transportation................................
1,172
1,660
Logisticians........................................................................................
698
1,536
Management analysts...................................................................
10,323
6,430
Financial analysts............................................................................ 5,110 3,170
Computer and mathematical science occupations
Computer programmers...............................................................
Computer systems analysts.........................................................
Network systems and data communications analysts......
Operations research analysts......................................................
9,777 4,261
14,673
9,258
2,149 4,562
2,603
1,418
Predecessor
Successor
employment employment
share
share
Difference
in share1
Percent
change in
share1
0.2
.19
.03
0.13
.12
.04
–0.07
–32.95
–.07
–35.83
.01 56.23
.10
.07
–.03
.06
.03
.51
.25
.09
.08
.34
.17
.03 51.12
.05
134.68
–.17
–33.53
–.09
–33.81
.48
.73
.11
.13
.23
.49
.24
.08
–.26
–.24
.13
–0.05
–32.41
–53.49
–32.65
126.48
–41.86
Architecture and engineering occupations
Aerospace engineers.....................................................................
Electrical and electronics drafters.............................................
Mechanical engineering technicians.......................................
1,518
864
1,441
932
1,143
873
.08
.04
.07
.05
.06
.05
–.03
–34.44
.02 41.12
–.03
–35.29
Community and social services occupations
Child, family, and school social workers..................................
1,574
2,309
.08
.12
.04 56.54
Education, training, and library occupations
Middle school teachers, except special and vocational
education......................................................................................
2,456 3,440
Special education teachers, middle school........................... 575
732
Special education teachers, secondary school.....................
688
1,076
Teacher assistants............................................................................ 5,092
8,839
.12
.03
.03
.25
.18
.04
.06
.47
.06 49.47
.01 35.79
.02
66.86
.22
85.26
Arts, design, entertainment, sports, and media
occupations
Graphic designers...........................................................................
1,609
Merchandise displayers and window trimmers...................
867
Coaches and scouts........................................................................ 530
Radio and television announcers.............................................. 522
Reporters and correspondents.................................................. 593
Technical writers..............................................................................
972
1,968
1,081
719
1,019
1,113
633
.08
.04
.03
.03
.03
.05
.10
.06
.04
.05
.06
.03
.02 30.61
.01 33.02
.01 44.49
.03
108.11
.03
100.34
–.01
–30.50
1,716
669
1,676
2,391
663
852
2,943 3,901
646
1,377
1,557
2,016
2,568 3,259
.09
.08
.03
.15
.03
.08
.13
.04
.13
.05
.21
.07
.11
.17
–.05
–58.35
.04 52.29
.01 37.08
.06 41.50
.04
127.50
.03 38.26
.05 35.46
Health care support occupations
Home health aides..........................................................................
15,642
21,588
Medical assistants........................................................................... 3,033 3,916
Medical equipment preparers....................................................
641
1,190
.78
.15
.03
1.14
.21
.06
.37 47.30
.06 37.79
.03
97.80
Protective service occupations
Private detectives and investigators........................................
Health care practitioner and technical occupations
Physician assistants........................................................................
Respiratory therapists....................................................................
Diagnostic medical sonographers............................................
Radiologic technologists and technicians.............................
Psychiatric technicians..................................................................
Surgical technologists...................................................................
Medical records and health information technicians........
742
1,306
.04
.07
.03
87.77
Personal care and service occupations
Nonfarm animal caretakers......................................................... 516
Residential advisors........................................................................ 565
1,231
828
.03
.03
.07
.04
.04
154.30
.02 56.43
Sales and related occupations
Securities, commodities, and financial services sales
agents............................................................................................. 3,039
Travel agents.....................................................................................
663
1,943
826
.15
.03
0.1
.04
–.05
–31.74
.01 32.83
See footnote at end of table.
Monthly Labor Review • September 2008
Business Ownership Change
Table 4.
Continued—Difference between predecessor and successor occupational employment level and share
in the ownership change subsample, by detailed occupation, 2000–06
Occupation
Predecessor
employment
level
Demonstrators and product promoters.................................
2,493
Real estate sales agents................................................................ 560
Successor
employment
level
Predecessor
Successor
employment employment
share
share
Difference
in share1
Percent
change in
share1
939
758
.12
.03
.05
.04
–.07
–59.76
.01 44.77
Office and administrative support occupations
Payroll and timekeeping clerks.................................................. 3,241 4,104
Credit authorizers, checkers, and clerks..................................
1,855
979
Interviewers, except eligibility and loan.................................
2,987 3,761
Meter readers, utilities...................................................................
639
839
Legal secretaries..............................................................................
1,758
1,117
Medical secretaries......................................................................... 3,331 5,994
Insurance claims and policy processing clerks.....................
1,631
2,621
Office machine operators, except computer........................
1,825
1,135
.16
.09
.15
.03
.09
.17
.08
.09
.22
.05
.20
.04
.06
.32
.14
.06
.06 35.12
–.04
–43.63
.05 34.39
.01 40.06
–.03
–32.15
.15
92.12
.06
71.53
–.03
–33.63
Farming, fishing, and forestry occupations
Farmworkers, farm and ranch animals.................................... 550
1,025
.03
.05
.03
98.53
788
.06
.04
–.02
–34.95
729
903
2,791 3,477
.04
.14
.05
.18
.01 32.41
.05 32.97
.03
.05
.02 56.00
.09
.51
.11
.52
.03
.32
.06
.26
–.06
–.19
–.05
–.25
–68.76
–38.18
–42.77
–48.62
.09
.04
–.05
–59.43
.56
.36
–.20
–35.66
.24
.08
.14
.04
–.10
–.05
–41.23
–57.97
.09
.05
–.04
–42.59
.08
.65
.05
.89
–.02
–30.13
.23 35.66
.24
.04
.03
.13
.05
.05
–.11
–46.64
.01 31.3
.01 36.25
Construction and extraction occupations
Helpers—pipelayers, plumbers, pipefitters, and
steamfitters...................................................................................
Installation, maintenance, and repair occupations
Control and valve installers and repairers, except
mechanical door.........................................................................
Telecommunications line installers and repairers...............
Coin, vending, and amusement machine servicers
and repairers................................................................................
1,294
605
885
Production occupations
Aircraft structure, surfaces, rigging, and systems
assemblers....................................................................................
1,737 508
Electrical and electronic equipment assemblers.................
10,291 5,960
Engine and other machine assemblers...................................
2,275
1,219
Slaughterers and meatpackers...................................................
10,402 5,007
Forging machine setters, operators, and tenders,
metal and plastic........................................................................
1,831
696
Cutting, punching, and press machine setters,
operators, and tenders, metal and plastic........................
11,262
6,789
Multiple machine tool setters, operators, and tenders,
metal and plastic........................................................................ 4,935
2,717
Bindery workers...............................................................................
1,710
674
Extruding and forming machine setters, operators,
and tenders, synthetic and glass fibers..............................
1,729
931
Separating, filtering, clarifying, precipitating, and still
machine setters, operators, and tenders...........................
1,554
1,018
Helpers—production workers....................................................
13,215
16,798
Transportation and material moving occupations
Bus drivers, transit and intercity................................................. 4,929
Service station attendants...........................................................
794
Crane and tower operators..........................................................
669
1
Numbers are affected by rounding.
are the 70 occupations with substantial growth or decline11 after the ownership changes and with employment
of at least 500 in the predecessor and successor groups.
The table shows each occupation’s employment level and
employment share in the ownership change subsample’s
predecessor group and successor group, and the difference
between them. The occupations are categorized by occupational group. Residual (“all other”) occupations are not
shown.
10
2,464
975
853
Monthly Labor Review • September 2008
Changes in employment levels. Occupations with the
greatest decline in employment level (by more than 1,500
employees) across all occupational groups in the ownership
change subsample were computer programmers, computer
systems analysts, four “assembly” production occupations,
management analysts, transit and intercity bus drivers,
financial analysts, demonstrators and product promoters,
and marketing managers. Occupations that exhibited the
greatest growth in employment level (by more than 1,500
employees) were home health aides, teacher assistants,
production worker helpers, medical secretaries, and network systems and data communications analysts.
Relative changes in employment shares. It is useful to examine in detail the occupational groups that fared poorly
after ownership changes. Table 4 also shows (see columns
titled “Predecessor employment share” and “Successor employment share”) that, in the computer and mathematical
science group, which shrank the most in the ownership
change subsample and grew in the control subsample,
there were decreases in the employment shares of computer
programmers, operations research analysts, and computer
systems analysts. Network systems and data communications analysts, by contrast, were in higher demand. Among
business and financial operations occupations, which had
the second-largest difference in employment in the ownership change subsample relative to occupations in the
control subsample, financial analysts and management
analysts were most likely to be cut. Meanwhile, logisticians
and compliance officers (except agriculture, construction,
health and safety, and transportation) were most likely
to grow. In the management group, compensation and
benefits managers saw the greatest employment increase
after ownership changes, while marketing managers saw
decreases in employment share.
One possible interpretation of these observations is
that if the establishment is acquired by an establishment
with similar staff, the employees who are more likely to
be let go are those who appear to have redundant occupations. For example, an establishment that is acquired
may no longer need a separate information technology or
marketing department. Instead, it may have an increased
need for occupations such as network systems and data
communications analysts or human resources personnel
to facilitate the organizational transition.Other occupations that deal more directly with customers or output,
such as home health aides, medical secretaries, teacher assistants, and production assembly workers, might need to
be retained in order to maintain good customer service or
productivity. These occupations tend to be closely related
to the core output of the establishment, while the others
tend to serve as operational support. The decline in certain technical jobs also might be explained by outsourcing,
although this interpretation is not examined here.12
Occupational composition by wage range
A brief analysis of occupational employment share by
wage range reveals that, after ownership changed, the
wages of the employees performing analytical and administrative work shifted upwards, while the wages of the employees performing low-skilled service work or physical
labor shifted downwards. Until November 2005, the OES
microdata included data on detailed occupational employment in the wage ranges defined in table 5.13 Different occupational groups generally have their employment
distributions concentrated in different wage ranges. For
instance, management and computer and mathematical
occupations were employed mostly in wage ranges starting at $21.50 to $27.24 and running through $55.50 to
$69.99. Production and personal care and service occupations, however, were employed mostly in ranges beginning
at $6.75 to $8.49 and going through $17.00 to $21.49.
(The actual employment distributions are not shown in
the table.)
A shift in employment concentration from relatively
lower paid employees to relatively higher paid employees
occurred in several occupational groups. In these groups,
either high-paid workers were retained or hired more
often than low-paid workers, or low-paid workers were
more likely to lose their jobs after ownership changes. A
shift from low to high wage ranges occurred in analytical and administrative occupational groups such as management; architecture and engineering; computer and
mathematical science; business and financial operations;
health care practitioner and technical; community and
social services; office and administrative support; and
arts, design, entertainment, sports, and media, among
other occupations. If high pay is correlated with tenure
and knowledge, then high-earning workers may be the
most costly to replace. This shift from low to high wage
ranges also may be a result of businesses laying off workers with less tenure: although workers in analytical and
administrative occupations were less likely to be retained
after ownership changes, the employees who remained
had higher wages.
Conversely, employees who performed low-skilled service, physical labor, or personal service work exhibited a
shift toward lower wage ranges, possibly because the lowpaid workers were retained or hired at higher rates than
their higher paid counterparts or because higher paid
workers received pay cuts. Among these workers were
food preparation and serving related, sales and related,
protective service, personal care and service, construction
and extraction, production, transportation and material
moving, and health care support occupations. Although
many of these lower skilled service, physical-labor-intensive, or personal service occupations were most likely
to be retained after ownership changes, they experienced
Monthly Labor Review • September 2008 11
Business Ownership Change
Table 5.
Difference between predecessor and successor employment shares, by hourly wage range, ownership change
subsample, 2000–061
Difference between predecessor and successor percent employment, by wage range, excluding 2006
and November 2005 successors and corresponding predecessors
Occupational major group
Under
$6.75
$6.75
to
$8.49
Wages shifted higher
Management............................. –0.33
–0.25
Architecture and
engineering.............................
– –.08
Computer and
mathematical science.........
.08
–.16
Business and financial
operations...............................
.45
.23
Health care practitioner
and technical . .....................
–.64
–1.31
Office and administrative
support.....................................
–.17
.36
Community and social
services..................................... –2.82
–3.02
Building and grounds
cleaning and
maintenance ........................ –2.23
–8.69
Farming, fishing, and
forestry...................................... –27.17
2.11
Arts, design, entertainment,
sports, and media................ –1.34
.83
Life, physical, and social
science......................................
–
.17
Legal.............................................
–
–.08
Wages shifted lower
Food preparation and
serving related.......................
6.49
.30
Protective service..................... –2.17
–1.10
Education, training, and
library........................................
–.88
.99
Personal care and service ........ –2.42
8.77
Construction and
extraction.................................
2.26
1.90
Installation, maintenance,
and repair.................................
.51
–.45
Production..................................
.51
6.02
Transportation and
material moving....................
2.63 4.24
Health care support................ –2.37
2.14
Sales and related...................... 4.37
–.37
$8.50
to
$10.74
$10.75
to
$13.49
–0.70
–0.99
.12
$17.00
to
$21.49
$21.50
to
$27.24
$27.25
to
$34.49
–1.80
–1.73
–2.74
–1.24
–.29
–.49
–2.66
–3.75
–1.27
.22
–2.31
–2.18
–.63
1.15
–2.48
–3.65
–1.29
–3.16
–3.18
–1.42
–3.97
.55
–3.77
1.67
2.36
–.55
.22
.01
2.27 3.46
1.14
–3.90 3.90
11.12
11.51
.52
$13.50
to
$16.99
$55.50
to
$69.99
$70.00
and
over
0.61 3.51
2.50 3.15
.91
2.66
2.03
1.12
.46
–.26 4.37
2.59
–.27
–.51
–.29
2.51
1.63
.92
.29
7.04 4.69
.47
.36
.57
–.09
–.03
(2)
(3)
.53
–1.74
–
–
–
.87
–.78
–.29
–.05
–.11
–.01
–
–
6.23 3.31
1.22
1.75
–
–
–
–
–
1.13
1.06
.14
–.50
1.70
1.66
–1.09
–2.97
–3.89 3.27
–.18
–.49
2.22
–5.10
–2.22
2.28
–4.56
1.20
–5.46
–3.55
.92
–1.29
.63
–2.90
2.05
–.52
2.75
2.00
2.36
8.17
–4.73
–.96
10.00 5.79
–.91
–.68
–.20
–2.26
.02
–4.30
.01
–3.80
.00
–1.15
–.02
–.30
–
–.03
–
–
14.65
–2.25
–5.56
–5.62
–7.21
–6.25
2.35
–3.10
–2.96
–.99
–4.47
–.42
1.66
–.03
.93
–
.35
–
.45 4.30
.62
–1.66
–3.88
–2.86
–.99
–.10
–.03
–
.14
12.32
–.96
–3.47
1.96
–3.55
–2.37
–3.03
2.22
2.61
–2.98
–.34
2.18
1.29
–.04
.03
–.02
–.03
–.01
–.01
–
–
–3.76
6.11
–1.14
–.11
–4.13
1.04
–.92
-1.77
–1.29
1.30
–.19
–1.35
–.74
.23
–1.22
.01
.03
.17
–.33
–.05
.04
–.34
–
.03
–.66
–
–.07
–1.34
–
–.20
Excludes 2006 and November 2005 successors and corresponding
predecessors.
2
Slight negative difference.
downward shifts in their wages. This phenomenon could
have occurred either because management was more likely
to spare cheaper labor and employees in these occupations
were willing to work at lower wages or because higher
wage workers were replaced with lower wage workers.
Table 5 shows the difference between the predecessor and
successor employment shares for each occupational group
Monthly Labor Review • September 2008
$43.75
to
$55.49
.54
1
12
$34.50
to
$43.74
Slight positve difference.
NOTE: Dash indicates fewer than 10 establishments reporting occupations.
3
in each wage range.14 This study does not examine wage
range shifts in detailed occupations within occupational
groups; therefore, it does not explain whether an occupational group’s wages shifted to lower ranges because more
low-paid occupations were hired within the group or because more high-paid occupations within the group were
laid off or accepted pay cuts.
Table 6.
Employment by industry sector, in the ownership change subsample and across all establishments, 2000–06
Industry
Total
employment
in
predecessor
units
Total
employment
in
successor
units
Information..................................................................
112,318
80,285
Professional and technical services1. .................
80,795
61,069
1
Management of companies and enterprises .....
26,810
21,305
Finance and insurance.............................................
75,040
60,222
Manufacturing............................................................ 490,076 425,913
Transportation and warehousing1......................
88,433
78,448
Retail trade...................................................................
247,052
229,464
Utilities..........................................................................
14,661
13,766
Construction1. ............................................................
62,733
61,213
Difference
between
predecessor
and
successor
employment
–32,033
–19,726
–5,505
–14,818
–64,163
–9,985
–17,588
–895
–1,520
Percent
change from
predecessor
to successor
employment
Percent
change
betweeen
2002 and 2005
average annual
employment,
QCEW
–28.52
–9.16
–24.41
6.02
–20.53
2.81
–19.75 4.13
–13.09
–6.70
–11.29
2.74
–7.12
1.58
–6.10
–7.02
–2.42
8.76
Real estate and rental and leasing1. ...................
12,794
12,524
–270
–2.11 4.79
Wholesale trade1.......................................................
74,235
72,673
–1,562
–2.10
2.41
Other services, except public administration1......
28,956
28,785
–171
–.59
1.84
Accommodation and food services....................
119,095
119,452 357
.30
6.61
Arts, entertainment, and recreation...................
21,136
21,495 359
1.70 3.86
Educational services.................................................
80,642
84,732 4,090 5.07
9.91
Administrative and support and waste
management and remediation services......
175,422
185,003
9,581 5.46
6.35
Health care and social assistance........................
286,663 309,902
23,239
8.11
7.01
Mining1. ........................................................................ 5,672
9,630 3,958
69.78
10.76
1
Ownership change subsample employment difference and overall
employment difference had opposite signs.
NOTE: Table excludes agriculture, forestry, fishing, and hunting
Sectors most affected by ownership changes
Table 6 shows total employment by industry sector in
the ownership change subsample predecessor and successor groups, as well as the employment change and the
percent change in employment from the predecessor to
the successor groups.15 To provide a basis for comparison
with all establishments in the economy, the last column
contains the percent change between 2002 and 2005
QCEW average annual private-sector employment. (See
also chart 2.)
About half of the sectors contracted in the ownership
change subsample while they grew overall in the economy:
professional and technical services; management of companies and enterprises; finance and insurance; transportation and warehousing; retail trade; construction; real estate
and rental and leasing; wholesale trade; and other services,
except public administration. Moreover, all sectors except mining and except health care and social assistance
either shrank in the ownership change subsample while
they grew overall, or grew in the subsample by a smaller
percentage than they grew overall. The information and
manufacturing sectors contracted substantially more in the
because the OES and QCEW have incomplete coverage of this sector. Table
also excludes OES-designated government industries.
ownership change subsample than they contracted across
all establishments. In the information sector, employment
in establishments that changed ownership fell by 29 percent, while employment in all establishments in this sector
fell by 9 percent over the same period. Sectors that grew
in the ownership change subsample, but by less than the
industry grew as whole, were accommodation and food
services; arts, entertainment, and recreation; administrative
and support and waste management and remediation services; and educational services. Mining grew the most in
the ownership change subsample relative to the economy.
Much of this growth was due to oil and gas extraction and
will be discussed in the next section.
That some industries experienced particularly large
employment declines in the ownership change subsample relative to the economy as a whole might explain
some large declines in occupational groups that are central to those industries. For instance, in May 2006, sales
and related occupations made up 54 percent of the retail
trade industry. The large employment drop in retail trade
establishments that changed ownership (despite overall
expansion) between 2000 and 2006 might explain the
cross-industry observation that sales and related occuMonthly Labor Review • September 2008 13
Business Ownership Change
Chart 2.
The effect of business ownership change on industry employment in the ownership change
subsample and across all establishments, 2000–06: percent change in employment
Ownership
Ownership
change
subsample
70
Quadrant II
change
subsample
70
Quadrant I
Mining
50
50
Administrative and support and waste
management and remediation services
30
10
–10
–30
30
Arts, entertainment, and recreation
Health care and social assistance
Educational services
Other services, except public administration
Accommodation and food services
Construction
Wholesale trade
Real estate and rental and leasing
Real trade
Utilities
Transportation and warehousing
Manufacturing
Finance and insurance
Management of companies
Professional and technical services
and enterprises
Information
–10
–30
–50
–50
–70 Quadrant III
–7.0
–50
10
Quadrant IV
–30
–10
10 30 50
QCEW, 2002–05
pations shrank by more in the ownership change subsample than they shrank across establishments in the
control subsample. Similarly, one might speculate that
the contraction in professional and technical services establishments and in information establishments contributed to the large decline in computer and mathematical
science occupations. Likewise, the contraction in manufacturing establishments might have contributed to the
large decline in production occupations, which made up
53 percent of the manufacturing sector in May 2006.
Without a closer look at the data, however, the relationship between the decline in the industry sector and the
overall employment decline of core occupations is not
entirely clear. To see whether industries are more likely
to reduce or retain employment in core occupations or in
operational support occupations, the next section examines changes in the occupational composition of detailed
industries.
Occupational change by detailed industry
In every establishment, workers in certain occupations are
central to its industry’s core business function, and these
14 Monthly Labor Review • September 2008
–70
–70
workers tend to be employed in relatively high concentrations. Establishments also employ operational support,
or auxiliary, workers in occupations that support the core
business function. Occupations that serve as support in
some industries can be the core of other industries. For
example, in the accounting services industry, billing clerks
might be a core occupation while janitors are an operational support occupation. By contrast, in the building
services industry, janitors might be considered the core
occupation while billing clerks are an operational support
occupation. Core occupations can be thought of as those
most directly related to the establishment’s output.
Earlier studies of OES data show that when establishments shrink, they tend to shed support jobs at higher
rates than they shed core occupations.16 In what follows, 10 industries are examined in further detail to see
whether, when the declines in employment accompany
ownership changes, the declines also are concentrated in
support occupations. The results show that 5 of the highlighted industries experienced a shift in their employment
concentration from support to core occupations after an
ownership change, 3 others experienced a shift in employment concentration from core occupations to support oc-
cupations, and 2 had little difference in the overall mix of
core and support occupations after the change.
The 10 industries that contracted the most after ownership changes were computer systems design and related
services, wired telecommunication carriers, motor vehicle
parts manufacturing, department stores, grocery stores,
securities and commodity contracts intermediation and
brokerage, management of companies and enterprises,
scheduled air transportation, depository credit intermediation, and plastics product manufacturing. These industries either expanded in the overall economy or shrank by
a lesser magnitude in the overall economy than they did in
the ownership change subsample. At the other end of the
spectrum, oil and gas extraction experienced the highest
growth in the ownership change subsample (767 percent)
and the third-highest increase in employment level after
ownership changes, and the industry grew by a substantially greater magnitude in the subsample than it did in
the economy. Tables 7–10 show how the employment of
core and support occupations changed after an ownership change in these selected industries. The percentage of
industry employment in the predecessor establishments
represents each occupational group’s employment share
in the industry, out of total industry employment of the
predecessor establishments. Likewise, the percentage of
industry employment in the successor establishments
represents each occupational group’s employment share
in the industry, out of total industry employment in the
successor establishments.
Industries with increased concentrations of core occupations.
In most industries with large employment declines, a
change in ownership resulted in an increased employment share of core occupations and a decreased share of
operational support occupations. For example, as shown
in table 7, in scheduled air transportation there was an increase in the share of core occupations—personal care and
service occupations, which include flight attendants; and
transportation and material moving occupations, which
include pilots. At the same time, there was a decrease in
the share of support occupations—office and administrative support; and installation, maintenance, and repair
occupations. It is possible that the decrease was due to
increased outsourcing in the industry, although this article
does not examine that possibility.
Similarly, wired telecommunications carriers that changed
ownership had increased shares of installation, maintenance,
and repair; computer and mathematical science; and architecture and engineering occupations, and decreased shares of
office and administrative support, management, and business
and financial operations occupations. Finally, in securities and
commodity contracts intermediation and brokerage, there
likewise was an increase in the shares of core occupations
such as business and financial operations occupations and
sales and related occupations (the latter of which includes
securities, commodities, and financial services sales agents)
and a decline in support occupations, with computer and
mathematical science occupations falling from 28 percent
before the ownership changes to 14 percent afterwards
and office and administrative support occupations dropping from 19 percent to 15 percent of total employment.
In depository credit intermediation (which shrank in the
ownership change subsample, but grew overall in the economy), which consists of credit unions and commercial banks,
the share of core business and financial operations occupations rose from 14 percent to 18 percent of total employment. The share of core office and administrative support
occupations, which include tellers and similar core occupations employed in banks, was relatively stable at 61 percent,
and sales and related occupations increased from 4 percent
to 6 percent of total employment in the industry. The share
of support occupations, such as management, computer and
mathematical science, and legal occupations, fell.
Like the aforementioned industries, management of
companies and enterprises (which shrank in the ownership change subsample, but grew overall in the economy),
in which operational support is the core business function, had increases in all core occupations and decreases in
nonessential functions. This observation confirms previous behavioral research which found that when company
headquarters and auxiliary offices undergo mergers or
acquisitions, their chief executives tend to protect their
immediate subordinates, managers, and administrators.17
Industries with decreased concentrations of core occupations.
Sometimes a change in ownership resulted in a decreased
employment share of core occupations and an increased
share of operational support occupations. Industries
that followed this trend included service industries such
as grocery stores and department stores. In department
stores and grocery stores, sales and related occupations
represent the core of the business function. After an ownership change, the share of sales and related occupations
in department stores fell from 73 percent to 67 percent,
as shown in table 8. Similarly, in grocery stores, the share
of sales and related occupations fell from 38 percent to 36
percent. In both of these industries, the share of management occupations and office and administrative support
occupations rose after a change in ownership.
In plastics product manufacturing establishments, the
Monthly Labor Review • September 2008 15
Business Ownership Change
Table 7.
Industries with increased concentrations of core occupations, 2000–06
Occupational major group
Predecessor
employment
Successor
employment
Predecessor
employment
share
Successor
employment
share
Percentagepoint
difference
NAICS 4811, Scheduled air transportation
Total, all occupations........................................
25,159
20,549
…
…
…
Management .............................................................. 376
188
1.49
.91
–.58
Business and financial operations . .....................
767
684 3.05 3.33
.28
Computer and mathematical science ................
115
139
.46
.68
.22
Architecture and engineering ..............................
640
170
2.54
.83
–1.72
Legal ..............................................................................
11
11
.04
.05
.01
Arts, design, entertainment, sports, and media....
133
89
.53
.43
–.10
Health care practitioner and technical . ............
12
15
.05
.07
.03
Protective service ......................................................
11
7
.04
.03
–.01
Food preparation and serving related . .............
91
65
.36
.32
–.05
Personal care and service . .....................................
6,892
6,234
27.39 30.34
2.94
Sales and related .......................................................
178
153
.71
.74
.04
Office and administrative support . ....................
7,356 5,902
29.24
28.72
–.52
Installation, maintenance, and repair ................ 3,531
1,761
14.03
8.57
–5.46
Transportation and material moving . ............... 4,968 5,074
19.75
24.69 4.95
NAICS 5171, Wireless telecommunication
carriers
Total, all occupations.......................................... 42,629 30,277
…
…
…
Management .............................................................. 3,351
834
7.86
2.75
–5.11
Business and financial operations . ..................... 4,807 3,293
11.28
10.88
–.40
Computer and mathematical science ................ 5,915 5,990
13.88
19.78 5.91
Architecture and engineering .............................. 3,116
2,570
7.31
8.49
1.18
Life, physical, and social science .......................... 416
152
.98
.50
–.47
Legal ..............................................................................
161 33
.38
.11
–.27
Arts, design, entertainment, sports, and media.... 575
78
1.35
.26
–1.09
Health care practitioner and technical . ............ 4
7
.01
.02
.01
Protective service ......................................................
12
6
.03
.02
–.01
Building and grounds cleaning and
maintenance ..........................................................
26
13
.06
.04
–.02
Sales and related ....................................................... 4,114
2,543
9.65
8.40
–1.25
Office and administrative support . ....................
13,138
7,404 30.82
24.45
–6.37
Construction and extraction .................................
8 5
.02
.02
–.002
Installation, maintenance, and repair ................
6,937
7,277
16.27
24.03
7.76
Production ................................................................... 3 33
.01
.11
.10
Transportation and material moving . ...............
21 39
.05
.13
.08
NAICS 5231, Securities and commodity
contracts intermediation and brokerage
Total, all occupations..........................................
9,093 3,482
…
…
…
Management ..............................................................
1,711
687
18.82
19.73
.91
Business and financial operations . .....................
1,370
1,214
15.07 34.87
19.80
Computer and mathematical science ................
2,533 489
27.86
14.04
–13.81
Legal ..............................................................................
119
26
1.31
.75
–.56
Sales and related .......................................................
992 540
10.91
15.51 4.60
Office and administrative support . ....................
1,735 509
19.08
14.62
–4.46
NAICS 5221, Depository credit
intermediation
Total, all occupations........................................
28,275
21,465
…
…
…
Management ..............................................................
2,881
1,774
10.19
8.26
–1.93
Business and financial operations . ..................... 3,860 3,762
13.65
17.52 3.87
Computer and mathematical science ................
2,718
1,378
9.61
6.42
–3.20
Architecture and engineering ..............................
88 59
.31
.27
–.04
Life, physical, and social science .......................... 45 49
.16
.23
.07
Legal ..............................................................................
80
19
.28
.09
–.19
Arts, design, entertainment, sports, and media....
116 59
.41
.27
–.14
Protective service ...................................................... 51
29
.18
.14
–.05
Building and grounds cleaning and
maintenance .......................................................... 43
25
.15
.12
–.04
16
Monthly Labor Review • September 2008
Table 7.
Continued—Industries with increased concentrations of core occupations, 2000–06
Occupational major group
Predecessor
employment
Successor
employment
Predecessor
employment
share
Successor
employment
share
Percentagepoint
difference
Sales and related........................................................
1,081
1,249 3.82 5.82
1.99
Office and administrative support........................
17,255
13,010
61.03
60.59
–.44
Installation, maintenance, and repair.................. 40 47
.14
.22
.08
Transportation and material moving...................
9 4
.03
.02
–.01
NAICS 5511, Management of companies
and enterprises
Total, all occupations..........................................
26,541
20,953
…
…
…
Management................................................................ 3,829 3,691
14.43
17.62 3.19
Business and financial operations......................... 3,480 3,581
13.11
17.09 3.98
Computer and mathematical science..................
1,930
1,748
7.27
8.34
1.07
Architecture and engineering................................
788
778
2.97 3.71
.74
Life, physical, and social science............................ 441 324
1.66
1.55
–.12
Community and social services..............................
82
64
.31
.31
.00
Legal.................................................................................
218
211
.82
1.01
.19
Education, training, and library..............................
8 30
.03
.14
.11
Arts, design, entertainment, sports, and media.....
257 324
.97
1.55
.58
Health care practitioner and technical................
736 59
2.77
.28
–2.49
Protective service........................................................
148
91
.56
.43
–.12
Food preparation and serving related................. 410
101
1.54
.48
–1.06
Building and grounds cleaning and
maintenance............................................................ 370
132
1.39
.63
–.76
Sales and related.........................................................
1,369
1,066 5.16 5.09
–.07
Office and administrative support........................
7,478
6,122
28.18
29.22
1.04
Construction and extraction...................................
259
139
.98
.66
–.31
Installation, maintenance, and repair..................
886 530 3.34
2.53
–.81
Production.....................................................................
1,892
670
7.13 3.20
–3.93
Transportation and material moving...................
1,400
1,283 5.27
6.12
.85
NOTE: Detailed data on employment may not sum to total employment because not all occupational groups are listed.
share of production occupations fell from 59 percent to 57
percent and the share of transportation and material moving occupations also fell. By contrast, the share of office
and administrative support occupations and management
occupations rose. This conjunction of events supports
Donald Siegel and Frank Lichtenberg’s finding that in
manufacturing firms, only production personnel, as opposed to nonproduction employees, experienced relative
employment declines.18
Industries without a clear shift in either core or support
occupations. Two of the 10 industries examined in this
section show little difference in the overall mix of core and
support occupations. However, there was a shift in employment among the core occupations in these industries.
As table 9 shows, in motor vehicle parts manufacturing
the share of labor-intensive production occupations rose
from 65 percent to 67 percent while architecture and engineering occupations; installation, maintenance, and repair
occupations; and transportation and material moving occupations each decreased slightly. There was little change
in support occupations, such as management occupations
and office and administrative support occupations.
In computer systems design and related services
(which shrank in the ownership change subsample, but
grew overall in the economy), there were shifts within
the core and support occupational groups, but there was
no clear shift toward core occupations. Among core occupations, computer and mathematical science occupations and architecture and engineering occupations saw
their employment shares remain relatively stable while
the share of installation, maintenance, and repair occupations, which include computer repairers, increased from
2 percent to 5 percent. Among support occupations, office and administrative support occupations shrank while
sales and related occupations grew. Core detailed occupations that increased the most included sales engineers;
logisticians; network systems and data communications
Monthly Labor Review • September 2008 17
Business Ownership Change
Table 8.
Industries with decreased concentrations of core occupations, 2000–06
Occupational major group
Predecessor
employment
Successor
employment
Predecessor
employment
share
Successor
employment
share
Percentagepoint
difference
NAICS 4521, Department stores
Total, all occupations........................................
72,158
63,752
…
…
…
Management ..............................................................
1,072
1,026
1.49
1.61
.12
Business and financial operations . ..................... 475
232
.66
.36
–.29
Computer and mathematical science ................
13
8
.02
.01
–.01
Arts, design, entertainment, sports, and
media . ...................................................................... 540 571
.75
.90
.15
Health care practitioner and technical . ............
637
622
.88
.98
.09
Health care support ................................................. 35
29
.05
.05
(1)
Protective service ......................................................
1,350
1,295
1.87
2.03
.16
Food preparation and serving related . .............
759 576
1.05
.90
–.15
Building and grounds cleaning and
maintenance ..........................................................
230 342
.32
.54
.22
Personal care and service . .....................................
715
823
.99
1.29
.30
Sales and related ....................................................... 52,902 42,904
73.31
67.30
–6.02
Office and administrative support . ....................
11,556
13,805
16.01
21.65 5.64
Construction and extraction ................................. 38
24
.05
.04
–.02
Installation, maintenance, and repair ................
216 310
.30
.49
.19
Production ................................................................... 387 369
.54
.58
.04
Transportation and material moving . ...............
1,218
816
1.69
1.28
–.41
NAICS 4451, Grocery stores
Total, all occupations........................................
83,107
75,679
…
…
…
Management ..............................................................
1,186
1,107
1.43
1.46
.04
Business and financial operations . .....................
172
167
.21
.22
.01
Computer and mathematical science ................
9
16
.01
.02
.01
Arts, design, entertainment, sports, and media.....
241
295
.29
.39
.10
Health care practitioner and technical . ............
1,554
1,830
1.87
2.42
.55
Health care support ................................................. 368 372
.44
.49
.05
Protective service ...................................................... 451
239
.54
.32
–.23
Food preparation and serving related . .............
8,731
8,915
10.51
11.78
1.27
Building and grounds cleaning and
maintenance ..........................................................
883
610
1.06
.81
–26
Personal care and service . .....................................
807 37
.97
.05
–.92
Sales and related ....................................................... 31,705
27,393 38.15 36.19
–1.96
Office and administrative support . ....................
24,598
22,598
29.60
29.86
.26
Farming, fishing, and forestry ...............................
108 53
.13
.07
–.06
Installation, maintenance, and repair ................ 386
218
.46
.29
–.18
Production ................................................................... 5,066 4,959
6.10
6.55
.46
Transportation and material moving . ...............
6,842
6,870
8.23
9.08
.84
NAICS 3261, Plastics product manufacturing
Total, all occupations..........................................
19,991
17,835
…
…
…
Management ..............................................................
758
708 3.79 3.97
.18
Business and financial operations . .....................
265 348
1.33
1.95
.63
Computer and mathematical science ................ 59 56
.30
.31
.02
Architecture and engineering .............................. 595
815
2.98 4.57
1.59
Life, physical, and social science ..........................
77
9
.39
.05
–.33
Arts, design, entertainment, sports, and
media . ...........................................................................
29 38
.15
.21
.07
Health care practitioner and technical . ............ 3
12
.02
.07
.05
Building and grounds cleaning and
maintenance ..........................................................
98
89
.49
.50
.01
Sales and related .......................................................
202
282
1.01
1.58
.57
Office and administrative support . ....................
1,509
1,435
7.55
8.05
.50
Construction and extraction ................................. 346
116
1.73
.65
–1.08
Installation, maintenance, and repair ................
1,384
1,115
6.92
6.25
–.67
Production ...................................................................
11,708
10,191 58.57 57.14
–1.43
Transportation and material moving . ...............
2,954
2,616
14.78
14.67
–.11
Slight negative percentage-point difference.
NOTE: Detailed data on employment may not sum to total employment because not all occupational groups are listed.
1
18
Monthly Labor Review • September 2008
Table 9.
Industries without a clear shift in either core or support occupations, 2000–06
Occupational major group
Predecessor
employment
Successor
employment
Predecessor
employment
share
Successor
employment
share
Percentagepoint
difference
NAICS 3363, Motor vehicle parts
manufacturing
Total, all occupations....................................... 35,706
26,443
…
…
…
Management .............................................................
1,045
716
2.93
2.71
–.22
Business and financial operations . ....................
717
618
2.01
2.34
.33
Computer and mathematical science ..............
132
122
.37
.46
.09
Architecture and engineering .............................
2,834
1,811
7.94
6.85
–1.09
Life, physical, and social science ......................... 49 58
.14
.22
.08
Arts, design, entertainment, sports, and
media . .....................................................................
61
75
.17
.28
.11
Health care practitioner and technical . ........... 37 38
.10
.14
.04
Protective service ..................................................... 36 33
.10
.12
.02
Building and grounds cleaning and
maintenance .........................................................
154
103
.43
.39
–.04
Sales and related ...................................................... 474 312
1.33
1.18
–.15
Office and administrative support . ...................
1,610
1,287 4.51 4.87
.36
Construction and extraction ................................ 537 378
1.50
1.43
–.07
Installation, maintenance, and repair ...............
2,075
1,186 5.81 4.49
–1.33
Production ..................................................................
23,033
17,730
64.51
67.05
2.54
Transportation and material moving . ..............
2,910
1,976
8.15
7.47
–.68
NAICS 5415, Computer systems design
and related services
Total, all occupations....................................... 33,688
15,081
…
…
…
Management .............................................................
2,937
1,196
8.72
7.93
–.79
Business and financial operations . .................... 3,520
1,507
10.45
9.99
–.46
Computer and mathematical science.................
15,005
6,792 44.54 45.04
.50
Architecture and engineering .............................
2,519
936
7.48
6.21
–1.27
Life, physical, and social science .........................
113
93
.34
.62
.28
Legal ............................................................................. 36
16
.11
.11
(1)
Arts, design, entertainment, sports, and
media . ..................................................................... 595
269
1.77
1.78
.02
Protective service ..................................................... 54
24
.16
.16
(1)
Sales and related ......................................................
1,025
801 3.04 5.31
2.27
Office and administrative support . ...................
6,767
2,535
20.09
16.81
–3.28
Installation, maintenance, and repair ............... 533
717
1.58 4.75 3.17
Production .................................................................. 471
66
1.40
.44
–.96
Transportation and material moving . ..............
65
78
.19
.52
.32
1
Slight negative percentage-point difference.
NOTE: Detailed data on employment may not sum to total employment because not all occupational groups are listed.
analysts; computer software engineers, systems software;
computer software engineers, applications; and computer
support specialists. Meanwhile, the core detailed occupations that decreased the most after a change in ownership
included industrial engineers; computer specialists, all
other; computer programmers; and computer hardware
engineers.
An example of an industry that grew after ownership changes.
The same study which found that shrinking establishments
shed support occupations first also found that growing establishments add support occupations first.19 In order to
contrast employment changes among industries that grew
after ownership changes with those which declined, one
growing industry is examined in detail.
The oil and gas extraction industry (which grew by a
greater magnitude in the subsample than it did overall)
exhibited a drastic shift from essential labor-intensive
occupational groups to operational support occupations,
despite the fact that each occupational group increased in
Monthly Labor Review • September 2008 19
Business Ownership Change
Table 10.
Example of an industry that grew after ownership change, 2000–06
Occupational major group
Predecessor
employment
Successor
employment
NAICS 2111, Oil and gas extraction
Total, all occupations....................................... 441 3,824
Management ............................................................. 36 534
Business and financial operations . .................... 30
997
Computer and mathematical science ...............
8
224
Architecture and engineering ............................. 33 329
Life, physical, and social science .........................
10 400
Legal .............................................................................
2
139
Sales and related ......................................................
2
200
Office and administrative support . ...................
68 486
Construction and extraction ................................
126
210
Installation, maintenance, and repair ............... 31
64
Production ..................................................................
28
76
Transportation and material moving . ..............
63
117
Predecessor
employment
share
Successor
employment
share
Percentagepoint
difference
…
…
…
8.16
13.96 5.80
6.80
26.07
19.27
1.81 5.86 4.04
7.48
8.60
1.12
2.27
10.46
8.19
.45 3.63 3.18
.45 5.23 4.78
15.42
12.71
–2.71
28.57 5.49
–23.08
7.03
1.67
–5.36
6.35
1.99
–4.36
14.29 3.06
–11.23
N.OTE: Detailed data on employment may not sum to total employment because not all occupational groups are listed.
employment level in the successor establishments. Core
construction and extraction occupations in the industry held a dominant 29-percent share before ownership
changes, but only a 6-percent share afterwards, while the
share of support business and financial operations occupations increased from almost 7 percent to a dominant
26 percent after ownership changes. In addition to construction and extraction occupations, the following laborintensive occupational groups decreased in employment
share after ownership changes: installation, maintenance,
and repair; production; and transportation and material
moving occupations. In addition to business and financial
operations occupations, the following operational support
occupations increased in employment share after ownership changes: management; computer and mathematical
science; architecture and engineering; life, physical, and
social science; and legal occupations. These findings in the
establishments that changed ownership in the oil and gas
extraction industry are consistent with those of a separate
study of recent trends in occupational employment across
all establishments in the industry.20 This research found
that, during the recent spate of oil and gas price increases,
the overall staffing of the industry was shifting away from
extraction activities and toward exploration.
Occupational employment by establishment size
This final section shows that changes in occupational com20
Monthly Labor Review • September 2008
position that followed ownership changes varied by the size
of the establishment. Establishments were grouped into
five size classes before and after the ownership change: 1 to
9 employees; 10 to 49 employees; 50 to 249 employees; 250
to 999 employees; and 1,000 or more employees. In order
to focus on changes in occupational composition within
size classes, the subsample was then divided into five size
groups based on deviations of fewer than two size classes:
very small, small, medium, large, and very large.21 Establishments chosen for the study were limited to the 21,923 out
of the 22,198 establishments that changed by fewer than
two size classes: 17,166 establishments that did not change
size class, 2,598 establishments that decreased by one size
class, and 2,159 establishments that increased by one size
class.22 As was done in the industry analysis, the percent
employment of each occupational group in predecessor
and successor establishments was calculated for every size
group. The predecessor employment share represents the
percentage of occupational employment out of total predecessor employment in the size group, and the successor employment share represents the percentage of occupational
employment out of total successor employment in the size
group. As before, growth indicates growth in the employment share, or relative importance of the occupation, not
necessarily growth in the employment level. The changes in
occupational share are shown in table 11.
Five occupational groups grew in establishments of all
sizes: life, physical, and social science; health care practi-
Table 11. Percentage-point difference between predecessor and successor employment share in the ownership
change subsample, by establishment size, 2000–06
Establishment size
Occupational major group
Very small
Management.....................................................................................
Business and financial operations.............................................
Computer and mathematical science......................................
Architecture and engineering.....................................................
Life, physical, and social science.................................................
Community and social services..................................................
Legal.....................................................................................................
Education, training, and library..................................................
Arts, design, entertainment, sports,
and media.......................................................................................
Health care practitioner and technical ...................................
Health care support........................................................................
Protective service.............................................................................
Food preparation and serving related.....................................
Building and grounds cleaning and
maintenance..................................................................................
Personal care and service..............................................................
Sales and related..............................................................................
Office and administrative support.............................................
Farming, fishing, and forestry . ..................................................
Construction and extraction........................................................
Installation, maintenance, and repair.......................................
Production..........................................................................................
Transportation and material moving .....................................
1
Small
Medium
Large
Very large
–1.03
.64
–.04
–.04
.02
.08
(1)
.30
–1.33
.52
.15
.05
.13
.04
–.04
.10
–0.86
.13
.09
.06
.03
–.08
.03
.34
–0.33
(1)
.10
–.11
.06
.18
–.06
.31
–1.14
–1.48
–2.62
–.26
.02
.28
–.04
1.54
–.15
.14
.42
.02
.26
.23
.17
.36
.27
–.46
.02
.29
.22
1.04
–.02
(1)
1.06
.97
.83
.21
–.30
2.86
1.58
.63
.79
.19
–.40
–.78
–1.10
.07
.60
–.33
.50
.64
.04
–.07
–.78
–.22
.08
.09
–.11
.45
.33
(1)
.07
–1.04
–.60
(1)
–.01
.02
–.03
.30
–.48
–.36
–1.19
–.11
.01
.11
.47
–1.21
–.47
.56
.50
–.73
–.36
.03
.04
–.45
–2.24
.81
Less than 0.05 percentage-point difference.
tioner and technical; health care support; education, training, and library; and protective service occupations. In contrast, three occupational groups shrank in establishments
of all sizes: management occupations (with its decrease the
most in small, very small, and very large establishments),
sales and related occupations (with its decrease the most in
medium and large establishments), and office and administrative support occupations (with its decrease the most in
very small establishments). The direction and magnitude of
changes in all other occupational groups, however, varied.
Analytical and production occupations—business and
financial operations; architecture and engineering; legal;
arts, design, entertainment, sports, and media; and production occupations—did not grow in large and very large establishments. Service occupations—personal care and service; food preparation and serving related; community and
social services; health care support; health care practitioner
and technical; education, training, and library; building and
grounds cleaning and maintenance; and transportation and
material moving occupations—tended to grow the most in
very large establishments.
One interesting observation is that production occupations grew only in very small or small establishments
and shrank in larger establishments. In fact, there was an
inverse correlation between the establishment size and the
effect of ownership change on production occupations.
This correlation may be the result of larger companies being able to capture economies of scale. Another observation is that computer and mathematical occupations were
fairly stable in all but the very large establishments. After
ownership changes, the share of computer and mathematical occupations fell by 2.6 percent, the largest change of
all occupational groups in any establishment size.
An overview by size group also reveals some trends. Very
small predecessor establishments, on the whole, were dominated by sales and related occupations and office and administrative support occupations. After ownership changes, the
greatest decreases were in management, office and administrative support, and sales and related occupations, and the greatest increases were in business and financial operations and
transportation and material moving occupations. In the small
size group, the greatest changes were, again, decreases in management occupations and sales and related occupations and an
increase in business and financial operations occupations.
In the medium size group, the greatest changes were an increase in protective service occupations and decreases in sales
Monthly Labor Review • September 2008 21
Business Ownership Change
and related occupations and management occupations. In the
large size group, the greatest changes were an increase in health
care practitioner and technical occupations and decreases in
production occupations and sales and related occupations.
Finally, in the very large size group, the greatest changes were
an increase in health care practitioner and technical occupations and health care support occupations and decreases in
computer and mathematical science, production, business and
financial operations, and management occupations.
tions did not grow in large establishments.
In contrast, many of the jobs that were more likely to
be retained after ownership changes were those which performed service work, such as health care and education, and
most of these groups’ wages shifted toward lower ranges.
Very large establishments were most likely to retain their
service occupations after changing ownership.
This article leaves room for future research on the effect of ownership changes on occupational employment
and wages. The methodology for identifying specific types
OCCUPATIONS THAT WERE LEAST LIKELY to be retained of ownership changes and capturing more predecessor
after ownership changes were those which performed ana- and successor establishment staffing data can be refined.
lytical, clerical, and production work, and most of these groups’ Further regression analysis can be conducted on the effect
wages shifted toward higher ranges. These occupations tended of ownership changes on core and support business functo be support occupations in the industries in which their em- tions, on wages by detailed occupation, and on staffing
ployment shares declined. Some of them declined in establish- by industry or geographic location. OES data are an imments of all sizes, although many shrank the most in large and portant input in understanding and predicting the labor
very large establishments. Analytical and production occupa- market outcomes of business dynamics.
Notes
1
Counts include mergers, full- or partial-interest acquisitions, divestitures,
and leveraged buyouts valued at $5 million. See Statistical Abstract of the
United States, 2006 (U.S. Census Bureau, 2007), Table 751, “Mergers and
Acquisitions—Summary, 1990 to 2003.”
“What Goes Up, Must Come Down?” Mergers & Acquisitions: The
Dealermaker’s Journal, July 2007, pp. 10-11; on the Internet at search.ebscohost.
com.proxy2.library.jhu.edu/login.aspx?direct=true&db=buh&AN=25593842
&site=ehost-live (visited Sept. 8, 2007).
2
3
Donald Siegel and Frank Lichtenberg, “The Effect of Ownership Changes
on the Employment and Wages of Central-Office and Other Personnel,”
Journal of Law and Economics, October 1990, pp. 383–408.
4
Robert McGuckin and Sang Nguyen, The impact of ownership changes: a view
from labor markets (U.S. Census Bureau, Center for Economic Studies, 2001).
5
Robert McGuckin, Sang Nguyen, and Arnold Reznek, “On Measuring
the Impact of Ownership Change on Labor: Evidence from U.S. FoodManufacturing Plant-Level Data,” in John Haltiwanger, Marilyn Manser, and
Robert Topel (eds.), Labor Statistics Measurement Issues, NBER Studies in Income
and Wealth, vol. 60 (Chicago, University of Chicago Press, 1998).
Approximately 2 percent of the wage data were imputed.
6
In addition, 1,233 establishments reported 3 times, and 5 firms reported 4
times; these 1,238 firms were excluded from the ownership change subsample.
The exclusion of establishments that reported more than twice should not
introduce significant bias into the subsample.
7
8
See, for example, the Thomson Financial Merger and Corporate Transactions database, on the Internet at www.census.gov/compendia/statab/2006/
tables/06s0752.xls. Mergers, full- or partial-interest acquisitions, divestitures,
and leveraged buyouts valued at $5 million or more are listed in the database.
9
The method for obtaining published OES estimates applies weights for
each sample establishment in each panel of the survey in order to represent all
establishments that were part of the in-scope frame from which the panel was
selected. In the study presented in this article, employment was not adjusted by
the unit sampling weights.
According to QCEW annual private-sector employment figures, total
employment was 107,577,281 in 2002 and 110,611,016 in 2005.
10
22
Monthly Labor Review • September 2008
11
Occupations listed are those whose employment shares grew or declined
by at least 0.01 percentage point and 30 percent from the predecessor to the
successor group.
12
For a discussion of the outsourcing of technical jobs, see Ashkok Bardhan
and Cynthia Kroll, “The New Wave of Outsourcing,” Fisher Center Research
Report No. 1103 (Berkeley, CA, Fisher Center for Real Estate & Urban
Economics, November 2003), on the Internet at repositories.cdlib.org/iber/
fcreue/reports/1103 (visited Sept. 26, 2008); Alan Blinder, “How Many U.S.
Jobs Might Be Offshorable?” CEPS Working Paper No. 142 (Princeton, NJ,
Center for Economic Policy Studies, March 2007), on the Internet at www.
princeton.edu/~ceps/workingpapers/142blinder.pdf (visited Sept. 26, 2008);
and J. Bradford Jensen and Lori G. Kletzer, “Measuring Tradable Services and
the Task Content of Offshorable Services Jobs,” paper presented at the National
Bureau of Economic Research Conference on Research in Income and Wealth,
titled “Labor in the New Economy,” November 16–17, 2007, Washington, DC,
on the Internet at people.ucsc.edu/~lkletzer/TradableServices&Job_task_
content_110907.pdf (visited Sept. 26, 2008).
13
Because the wage range definitions were revised in November 2005, the
successor data collected with November 2005 and May 2006 reference dates,
as well as their corresponding predecessor records, were removed from the
subsample solely for this wage analysis. The wage analysis used 14,828 unique
establishments (29,656 predecessor and successor records).
14
The employment share of an occupational group in, for example, the
wage range headed “Under $6.75” is the percentage of employment in that
occupational group out of total employment in the occupational group.
15
A few establishments changed their industry classification when they
reported the second time, but most that did so did not change industry sector.
For consistency, the successors’ industries were assigned to the predecessors’.
16
Zachary Warren, “Occupational Shares in Growing and Shrinking
Establishments,” Occupational Employment and Wages (Bureau of Labor
Statistics, May 2005), pp. 1–14; see especially p. 5.
17
Andre Shleifer and Robert Vishny, “Value Maximization and the
Acquisition Process,” Journal of Economic Perspectives, winter 1988, pp. 7–20.
18
Siegel and Lichtenberg, “The Effect of Ownership Changes.”
19
Warren, “Occupational Shares.”
20
Jeffrey Holt, “Recent Changes in Occupational Employment and Wages
in Oil and Gas Extraction,” internal BLS document, 2008.
21
The very small group consisted of establishments with 1–9 employees
before the ownership change and either 1–9 employees or 10–49 employees
after the ownership change. The small group comprised establishments whose
predecessors were in the 10–49-employee size class and whose successors
stayed in the same size class or changed by one size class. The medium group
encompassed establishments whose predecessors were in the 50–249-employee
size class and whose successors were in the same size class or one size class below
or above it. The large group consisted of establishments whose predecessors were
in the 250–999-employee size class and whose successors were in the same size
class or one size class below or above it. Finally, the very large group comprised
establishments whose predecessors started in the employee size class of 1,000
or more and whose successors either remained in this size class or contracted to
the 250–999-employee size class.
22
Excluded from the study were the 246 establishments that changed by
two size classes, the 25 establishments that changed by three size classes, and
the 4 establishments that changed by four size classes. Small units might have
been acquired by larger corporations with the intent to expand them, so their
occupational employment changes are relative extremes.
Monthly Labor Review • September 2008 23
New York Mass Layoffs
Extended mass layoffs after 2001:
a comparison of New York and the Nation
BLS data reveal that layoff activity in New York was somewhat
elevated in the years that followed the 2001 recession; a rising level
of job cuts due to contractual turnover among growth industries
helped transform the mass layoff experience in the metropolitan area
Bruce J. Bergman
W
ith the largest metropolitan
workforce in the Nation, the
New York area1 is at or near the
top of many lists. Separations due to layoffs, or, simply, layoff separations, are no
exception: between 2001 and 2006, New
York consistently ranked among the top 10
metropolitan areas in this category. Viewed
over the longer period of 11 years for which
comparable data are available, extended
mass layoff actions2 caused hundreds of
thousands of New York area employees to
be involuntarily separated from their workplaces. A question that arises, then, is, Was
the New York area a standout in terms of
layoffs, or did it not differ qualitatively from
the Nation in that regard? To answer that
question, this article examines data made
available for the first time from the Bureau
of Labor Statistics (BLS).
worker dislocation caused by the recession
and the September 11 terrorist attacks that
year, what differed between the New York
area and the Nation that led to divergent
trends in layoff activity after 2001? The
analysis that follows examines both the
type of layoff and the reasons for its occurrence in the context of varying employment
trends among industry sectors.
First, data from the BLS Mass Layoff
Statistics program that summarize extended mass layoff activity are used to measure
both the primary reasons for layoff events
and the magnitude of layoffs resulting from
permanent closures of the worksites.3 Then
the distribution of layoff separations by sector is examined, with the New York experience evaluated within the framework of
employment growth and the local industry
mix.
Was New York different?
New York and national layoff events
data reveal that the New York area
mass layoff experience not only deviated
from national trends, but also underwent
a significant change after 2001. While the
total number of layoffs in the United States
declined to the lowest levels recorded since
they were first tracked in 1996, New York
layoff activity remained at a relatively high
level after 2001. Following widespread
Eleven-year layoff totals. From 1996 through
2006, the New York area had 2,629 extended
mass layoff events, roughly 4.5 percent of the
national total. Although that figure amounted
to a relatively high total for New York compared with other metropolitan areas, slightly
more than 6 percent of all business establishments with at least 50 employees (the scope of
the study4) were located in the New York area.
BLS
Bruce J. Bergman is an
economist in the Office
of Field Operations,
Economic Analysis and
Information Branch,
Bureau of Labor
Statistics, New York
office.
24
Monthly Labor Review • September 2008
Layoff events in the New York area resulted in separations
of 439,198 employees, with approximately 1 out of every 5
events (about the same as the national proportion) resulting
from a permanent worksite closure.
With respect to the leading causes of layoffs, a similar pattern existed between the New York area and the
Nation, but with notable differences in magnitude.5 (See
chart 1.) Seasonal layoffs accounted for 39 percent of the
extended layoff actions in the New York metropolitan
area during the 11-year period. Twenty-five percent of the
layoff events had to do with internal company restructuring, a category that includes all events involving financial
difficulty, bankruptcy, ownership change, and reorganization. Nationally, seasonal factors and internal company
restructuring accounted for a respective 30 percent and 20
percent of all layoff actions.
The other two leading justifications for job cutbacks
involved slack work, indicating nonseasonal insufficient
demand for the company’s products or services, and the
completion of a contract. In the New York area, about 12
percent of layoff events resulted from each of these factors,
while nationally, slack work accounted for a greater share
(16 percent) of major cutbacks.
Chart 1.
Annual levels and the convergence of rates. On an annual
basis, major layoff events in the New York area ranged
from 147 in 1996 to 305 in 2005. (See table 1.) Although
these layoffs more than doubled in 10 years, when they are
compared with the number of establishments the change
is seen to be less dramatic. Approximating a rate of such
events per 100 establishments reveals relatively little
change over the period examined:6 the New York area layoff event rate remained close to 1.0, below the comparable
national rate. Nationally, a spike in the layoff event rate
from 1.2 to 1.9 occurred in 2001. Within 3 years, the national rate returned to its prerecession range, whereupon it
continued to decline further. Less pronounced, but more
protracted, was the impact in New York: the rate of layoff
events rose from 0.8 to 1.2, but it stayed close to that level
for the next 3 years. These differing trends eventually led
to the rate in the New York area (1.3) slightly exceeding
that of the Nation (1.2) in 2005. (See chart 2.)
Much has been written about the “jobless” recovery from
the recession, and BLS data indicate that, in the wake of job
destruction during the last recession, job creation slowed.
Nevertheless, during the years after the 2001 recession, in
both New York and the Nation, the unemployment rate
Percent distribution of extended mass layoff events, by reason, New York-Northern New Jersey-Long
Island and United States, 1996–2006
Percent
of all
events
45.0
Percent
of all
events
45.0
40.0
40.0
35.0
New York-Northern New Jersey-Long Island
United States
30.0
35.0
30.0
25.0
25.0
20.0
20.0
15.0
15.0
10.0
10.0
5.0
5.0
0.0
Seasonal
Internal restructuring
Slack work
Contract completed
Other
0.0
Reason for layoff
Monthly Labor Review • September 2008
25
New York Mass Layoffs
Table 1. Reasons for extended mass layoff events in New York-Northern New Jersey-Long Island and in the United States,
1996–2006
Measure
1997
147
72
75
8
42
13
12
200
111
89
15
44
15
15
1998
1999
2000
2001
2002
2003
2004
2005
2006
158
68
90
5
48
9
28
200
89
111
14
54
17
26
290
53
208
22
139
25
22
288
100
188
33
77
40
38
253
89
163
42
45
47
29
296
101
195
55
67
31
42
305
117
188
62
52
39
35
259
103
156
63
47
33
13
New York-Northern
New Jersey-Long Island
Total, private nonfarm.....................................
Seasonal...............................................................
Total, nonseasonal, nonvacation..............
Contract completed................................
Internal company restructuring..........
Slack work...................................................
Other reasons............................................
1996
233
108
125
8
53
21
43
United States1
Total, private nonfarm.....................................
Seasonal...............................................................
Total, nonseasonal, nonvacation..............
Contract completed................................
Internal company restructuring..........
Slack work...................................................
Other reasons............................................
1
Data on layoffs were reported by
District of Columbia.
4,760 4,671 4,859 4,556 4,591 7,375 6,337 6,181 5,010 4,881 4,885
1,487 1,637 1,430 1,427 1,548 1,439 1,558 1,630 1,678 1,808 1,613
3,222 2,955 3,348 3,025 2,968 5,817 4,699 4,447 3,222 2,976 3,160
512 700 670 642 575
630
754 874
772 692 1,056
1,012 798 829 926 958 1,894 1,609 1,272
989 773
818
816 655 740 563 599 1,925 1,282 949
579 566
597
882 802 1,109 894 836 1,368 1,054 1,352
882 945
689
employers in all States and the
fell to relatively low levels. But in terms of the frequency of
mass layoffs, the New York area remained close to (within
14 percent of ) the elevated level of layoffs that occurred
in 2001, while national levels declined by more than 14
percent in 2002 and continued to decline to prerecession
levels after that.
Five-year comparisons: pre- and post-2001. Another way
to view the 2001 turning point is to compare layoffs during the 5 years prior to the recession with those occurring
during the 5 years after. Prior to the recession, the New
York area averaged fewer than 100 nonseasonal, nonvacation mass layoff events; by contrast, the post-2001 average
was 178. Nationally, a comparison of 5-year averages also
shows an increase, but much less pronounced—at 19 percent, from 3,104 to 3,701. (See table 2.)
Besides identifying the magnitude of the total increase,
a comparison of the two time segments reveals another
difference between New York and the Nation. Nationally,
internal restructuring accounted for about 20 percent of
the layoff events in both periods, while contract completion remained close to 14 percent. In the New York area,
the share of layoff actions due to internal restructuring fell
to 21 percent over the 2002–06 period, from 26 percent
during 1996–2000. Job cutbacks due to contract completion increased dramatically between the two periods: from
2000 to 2006, this reason was associated with 18 percent
26
Monthly Labor Review • September 2008
SOURCE:
Bureau of Labor Statistics, Mass Layoff Statistics program.
of layoff events, whereas in the earlier period, only 5 percent of layoffs in the New York area were due to contract
completion. More significantly, in both 2005 and 2006,
contract completion caused more layoff events than did
internal restructuring.
Layoffs related to contract completion in the New
York area were less common prior to 2001 not only
relative to the period that followed, but also compared
with the Nation: during the more recent 5-year period, a
greater percentage of layoffs was due to completed contracts in the New York area than in the United States as
a whole.
With the increased importance of contract completion
and the diminished frequency of major job cuts due to
internal restructuring came a reduced likelihood of layoffs
due to worksite closure.7 Of the layoffs involving companies that underwent internal restructuring due to financial
difficulty, reorganization, bankruptcy, or a change in ownership between 1996 and 2006, permanent worksite closings factored into about 45 percent of the events in both
the New York area and the Nation. In contrast, permanent
worksite closures accounted for about 3 percent of layoff
events related to contract completion in the Nation. A
result of an increasing share of layoffs due to contract
completion was that, although the New York area tended
to have a higher percentage of layoffs due to permanent
worksite closures, those events became less frequent in
Chart 2.
Rate of extended mass layoff events, New York-Northern New Jersey-Long Island and United States,
1996–2006
Layoff events
per 100
establishments
2.0
Layoff events
per 100
establishments
2.0
United States
1.8
1.8
1.6
1.6
1.4
1.4
1.2
1.2
1.0
1.0
New York-Northern New Jersey-Long Island
0.8
0.8
0.6
0.6
0.4
0.4
0.2
0.2
0.0
1996
SOURCE:
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
0.0
BLS Mass Layoff Statistics program; and U.S. Census Bureau, County Business Patterns.
the post-2001 period. During the 5 years prior to the recession, permanent closures accounted for 36 percent of
the nonseasonal, nonvacation layoff events. In the 5 years
that followed 2001, that number dropped to 25 percent.
Nationally, the percentage was about 22 percent in both
periods. (See tables 2 and 3.)
What distinguished the New York area?
Historically, economic downturns were typically accompanied by an increase in the rate of layoffs. In better
times, with increased production, rates tended to decrease.
National data confirm this pattern, but variation may exist among areas. Locality differences in business startup
activity and in labor turnover and attrition, along with
resulting labor market flows, influence the extent of both
unemployment and layoffs in the face of industry-level
shocks.8 New York’s experience testifies that even with an
improving economy, layoffs might increase. An examination of both employment growth and business activity,
as measured by establishment entry and exit, offers some
explanation.
Business startup and migration. BLS employment data
show that overall job growth during most of the 1996–
2001 period remained close to or above that of the Nation. An analysis of major metropolitan areas prepared
for the Appalachian Regional Commission shows that,
during that period, the New York area had relatively high
business outmigration rates: about 1 percent of new and
existing firms had relocated elsewhere by the end of the
period.9 Nevertheless, aggregate business startup rates in
the New York area were even with national levels, indicating some level of strength, despite the relocations.
Employment growth and a slow recovery. Total nonfarm
employment in the New York area grew at a rate of more
than 2 percent annually between 1997 and 2000. Slowing started in early 2001, but after the terrorist attack of
September 11 and through the first half of 2002, job loss
in the metropolitan area acclerated to a rate of 2 percent
during the first half of 2002. Job loss persisted, albeit to a
lesser degree, until continuous over-the-year job growth
resumed in the second quarter of 2004. In most industry
sectors, employment followed a similar pattern of a deMonthly Labor Review • September 2008
27
New York Mass Layoffs
Table 2. Comparisons of extended mass layoff events in
New York-Northern New Jersey-Long Island and
the United States, 5- and 11-year averages,
1996–2006
Measure
11-year 1996–2000 2002–2006
average
average
average
New York-Northern
New Jersey-Long Island
All events, number..................................
Percentage involving internal
restructuring.....................................
Percentage involving contract
completion........................................
Percentage with recall expected...
Nonseasonal, nonvacation events,
number...............................................
Percentage involving permanent
worksite closure...........................
239
188
280
25.4
25.7
20.6
12.4
49.3
5.3
56.1
18.2
46.6
144
98
178
28.8
36.1
24.9
All events, number.................................. 5,282
Percentage involving internal
restructuring.....................................
20.4
Percentage involving contract
completion............................................
13.6
Percentage with recall
expected............................................
50.7
Nonseasonal, nonvacation events,
number............................................... 3,622
Percentage involving permanent
worksite closure...........................
21.8
4,687
5,459
19.3
20.6
13.2
15.2
55.9
48.8
3,104
3,701
22.1
21.5
United States1
1
Data on layoffs were reported by employers in all States and the
District of Columbia.
SOURCE: Bureau of Labor Statistics, Mass Layoff Statistics program.
layed return to prerecession (1996–2000) growth levels.
(See table 4.)
BLS Business Employment Dynamics data provide additional information about the nature of the slow recovery.
In New York State, a sustained period of expansion occurred from the first quarter of 1996 through the fourth
quarter of 2000. During that time span, job creation outpaced job destruction.10 The situation changed in 2001,
and not until the fourth quarter of 2003 would the pace of
job creation again be greater than that of job destruction.
At the national level, data also show both an increase in
job losses and a decline in job gains that characterize the
2001 recession. Employment in created jobs amounted to
8 percent of the total workforce in the mid-1990s; 10 years
later, the job creation rate was below 7 percent. Despite a
slow rate of job creation, total nonfarm employment returned to its prerecession peak sooner in the United States
as a whole than it did in the New York area.
A slow local recovery is echoed in the layoff separa28
Monthly Labor Review • September 2008
tion data. Nonseasonal, nonvacation layoffs reached their
peak in 2001. (See table 5.) That year, almost 38,000 such
separations were reported. Prior to 2001, the New York
area had had fewer than 16,000 in 4 out of 5 years, but not
until 2006 did the area total again fall below 25,000. Although the U.S. layoff peak also was in 2001, the number
of separations nationally in both 2005 and 2006 was the
lowest recorded between 1996 and 2006.
Initial claims for unemployment insurance related
to extended mass layoffs largely followed the pattern of
separations:11 elevated levels during the years following
2001, not returning to prerecession levels. But between
2003 and 2005, when claims related to extended layoffs
were declining throughout the Nation, claims in the New
York area increased. (See table 6.)
How much impact did these factors have on regional layoffs?
A graph of initial claims indexed to 1996 levels shows
clearly that initial claims in the New York area seemed to
ratchet up, even following the 2001 slowdown. (See chart
3.) At the national level, both the initial claims total and
the number of initial claims due to major layoffs returned
to earlier levels. So, too, did a similar return occur in 2 of
the 3 States in which the New York area is located: New
Jersey and Pennsylvania. These two States, as well as the
Mid-Atlantic Census Division as a whole, did not experience as sharp a spike in claims due to the recession as did
the Nation, and the number of claims returned closer to
pre-2001 levels.
That the relative growth in initial claims from the MidAtlantic Census Division was more similar to U.S. growth,
as opposed to that of the New York area, is somewhat
surprising, given that about 45 percent of the division’s
unemployed resided in the New York area, and about the
same percentage of the division’s employed worked there.
In terms of layoff separations, however, New York contributed only between one-quarter and one-third of the
division’s total.
In light of these numbers, some might interpret the indexes of initial claims to imply that New York area layoffs
did not have a significant impact on the regional economy.
BLS data on displaced workers, however, suggest that the
impact of the layoffs might go beyond the number of initial claims.12 Between 2003 and 2005, 431,000 New York,
New Jersey, and Pennsylvania workers permanently lost
jobs they had held for 3 or more years due to closures, termination of their positions or shifts, or insufficient work.
Nineteen percent of all displaced workers in the Mid-Atlantic division were collecting unemployment benefits in
2006, compared with 13 percent throughout the Nation.
Table 3. Permanent worksite closures: extended mass layoff events and separations in New York-Northern New Jersey-Long
Island and in the United States, 1996–2006
Measure
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
New York-Northern New Jersey Long Island
Events:
Total, private nonfarm.................................
Internal company restructuring............
Separations:
Total, private nonfarm.................................
Internal company restructuring............
28
22
26
17
51
31
38
29
34
24
63
45
48
31
39
16
42
28
57
31
45
27
6,620 6,034 9,545 6,565 3,655 13,011 10,326 7,395 8,079 10,202 7,423
5,762 4,278 5,763 5,532 2,842 8,606 6,792 2,742 5,883 6,657 5,359
United States1
Events:
Total, private nonfarm.................................
Internal company restructuring............
Separations:
Total, private nonfarm.................................
Internal company restructuring..............
757
435
595
326
662
356
671
405
755 1,240 1,155
492 760
677
919
536
746
500
560
371
621
417
181,589 151,966 151,526 181,970 183,335 377,360 298,634 210,903 159,867 107,399 153,718
109,331 86,550 87,131 121,915 134,584 266,042 192,982 132,615 110,732 76,408 112,341
1
Data on layoffs were reported by employers in all States and the
District of Columbia.
More research is needed to determine whether metropolitan area mass layoffs were responsible for the higher economic cost of job displacement in the Mid-Atlantic region.
Key patterns in reasons for layoff separations. Up to now,
this article has focused on the overall levels and types of
extended mass layoff events and the related initial claims
for unemployment insurance. Data show a clear difference between the 5-year periods before and after 2001 in
the New York metropolitan area. An examination of local
employment growth rates yields a similar dichotomy between the two periods. Data on separations by reason for
layoff and by industry help validate these findings and also
may help answer the question, “Was a slow local recovery
solely to blame for increased job cuts?”
Separations data confirm that two significant factors
contributed to the shift in layoff activity in the New York
area: (1) increased slack work, reflecting a period of reduced demand after 2001; and (2) an increase in completed contracts, suggesting an increased number of shorter
term employment contracts. Layoffs resulting from slack
work peaked in New York in 2002–03, contrasting with
the national total, which peaked in 2001. Beyond this
factor, New York layoffs related to contract completion
reached their highest levels in 11 years during 2004–05.
Nationally, separations due to completed contracts were
at relatively average levels during those years. Chart 4
illustrates these differences between the New York area
and the Nation in the distribution of layoff separations by
reason. Slack work and contract completion piggybacked
SOURCE:
Bureau of Labor Statistics, Mass Layoff Statistics program.
on the primary reason for major cutbacks—internal restructuring—resulting in a sustained elevated level of
separations. The number of separations due to internal
company restructuring peaked both nationally and in
New York in 2001.
Layoffs separations by industry. To complete the evaluation of what distinguished the New York area, a closer
look at layoff data by industry is necessary. Although data
that quantify reasons associated with layoffs are not available for local industries, comparisons with national figures
reveal some interesting findings.
Between 1996 and 2006, manufacturing accounted for
97,256 (or 22 percent of all) extended mass layoff separations in the New York area, followed by transportation and
warehousing with 62,449 (or 14 percent) of the separations.
More than 40,000 separations occurred in both the construction and the arts, entertainment, and recreation sectors.
Finance and insurance, as well as accommodation and food
services, recorded over 30,000 mass layoff separations, and
both the information and administrative and waste services
sectors experienced more than 20,000 layoffs.
Economic circumstances of sectors differ, especially
with regard to competition, the use of contingent workers,
and business demand. Accordingly, the 2001 slowdown
did not affect all sectors in the same way. In fact, the recession was not responsible for the largest number of layoffs
in every sector either. For example, manufacturing had
almost 34,000 separations due to major layoffs between
1996 and 1998, the worst 3-year period the industry had
Monthly Labor Review • September 2008
29
New York Mass Layoffs
Table 4. Percent distribution of employment among industries, and over-the-year employment change, private sector,
New York-Northern New Jersey-Long Island and United States, 1996–2006
Industry
Share of
total
employment 1996
Over-the-year employment change as a percentage of base-year employment
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
New York-Northern New
Jersey-Long Island
Total private nonfarm.............
Construction and mining...............
Manufacturing...................................
Trade, transportation, and
utilities...............................................
Wholesale trade..............................
Retail trade.......................................
Transportation and
warehousing..............................
Information.........................................
Financial activities............................
Finance and insurance.................
Professional and business
services..............................................
Professional and technical
services.........................................
Administrative and waste
services.........................................
Education and health services.....
Health care and social
assistance ...................................
Leisure and hospitality....................
Accommodation and food
services.........................................
Other services, except public
administration ...............................
100.0
4.5
8.4
1.6
2.5
–2.0
2.4
4.6
.1
2.7
7.1
–.9
2.7
9.3
–2.3
2.5
5.9
–2.3
0.0
3.1
–6.8
–2.0
.1
–8.3
–0.5
–1.1
–5.5
0.5
1.4
–3.5
0.7
.8
–3.8
1.3
3.9
–2.7
22.7
6.3
11.8
.5
.0
1.2
1.4
1.2
1.7
1.5
1.3
2.0
2.4
1.0
3.2
2.2
.5
3.2
–.8
.7
–1.4
–2.2
–3.5
–.5
–.2
–.2
.3
.3
–.4
.9
.1
–.3
.7
.6
.2
.4
4.2
4.4
11.3
8.6
–.1
2.8
–.1
–.6
2.3
3.3
1.0
.7
1.7
2.5
2.3
2.2
2.8
3.4
1.3
1.0
2.2
6.5
1.3
1.3
–1.9
4.8
–2.3
–2.6
–5.2
–9.0
–3.5
-4.2
–2.2
–6.3
–.7
–1.4
–.2
–2.6
.6
.2
–1.0
.0
1.2
1.3
1.6
1.3
1.5
1.7
17.4
4.7
5.2
5.5
4.8
4.4
.6
-4.0
–1.3
.6
1.2
2.1
8.6
3.6
5.6
7.0
5.7
5.6
–.1
-4.9
–2.2
.9
2.4
4.4
6.8
18.3
7.3
2.7
5.6
2.1
5.2
2.9
4.9
2.7
4.8
1.8
1.4
2.2
–4.1
3.1
–1.1
2.1
.4
1.4
–.5
1.6
–.1
2.1
14.9
8.2
1.8
2.0
2.1
3.2
2.6
2.9
2.8
2.8
1.9
3.4
1.7
1.9
3.1
.7
2.9
2.3
1.2
2.8
1.7
1.4
2.0
2.0
6.5
1.6
2.8
2.7
2.3
2.9
1.5
–.1
3.3
2.5
1.9
2.0
4.8
2.7
2.6
3.0
4.7
2.8
1.4
1.4
1.1
2.1
2.9
.3
100.0
2.4
.3
2.8
2.5
2.1
–.3
–1.7
–.4
1.3
1.9
2.0
6.7
14.7
4.4
.0
4.8
1.1
5.1
.8
5.1
–1.4
3.4
–.3
.6
–4.8
–1.8
–7.2
.1
–4.9
3.6
–1.3
5.2
–.6
5.1
–.2
23.5
5.3
13.8
1.7
1.6
1.8
1.9
2.6
1.7
2.0
2.3
1.5
2.3
1.7
2.5
1.8
.7
2.1
–.9
–2.7
–.3
–1.9
–2.1
–1.4
–.8
–.8
–.7
1.0
1.0
.9
1.7
1.8
1.5
1.0
2.3
.3
3.9
3.0
7.1
5.3
2.5
3.4
2.1
1.6
2.3
4.9
3.0
2.9
3.5
.4
4.0
4.3
3.2
6.2
2.5
2.5
2.6
6.2
.5
.2
–.9
–.1
1.6
1.6
–3.4
–6.4
.5
.8
–.9
–6.1
1.7
1.8
1.5
–2.2
.7
.4
2.6
–2.8
1.5
1.2
2.4
–.2
2.6
2.7
14.7
4.8
6.5
5.7
5.3
4.4
–1.1
–3.0
.1
2.6
3.4
3.5
8.6
4.6
6.0
6.5
5.9
5.6
2.5
–3.3
–.7
2.2
4.1
4.5
7.1
14.5
6.0
3.0
8.2
3.0
6.0
2.5
5.9
2.4
4.2
2.1
–4.2
3.5
–2.6
3.5
1.0
2.4
2.9
2.2
3.1
2.5
2.8
2.7
12.2
11.0
2.9
2.6
2.8
2.2
2.4
1.9
2.2
2.8
1.9
2.8
3.3
1.5
3.2
–.4
2.5
1.6
2.1
2.6
2.4
2.6
2.6
2.6
9.4
2.4
1.8
1.8
2.6
2.4
1.4
–.1
1.5
2.7
2.6
2.7
4.8
2.6
2.9
3.1
2.2
1.6
1.7
2.2
.5
.1
–.3
.7
United States1
Total private nonfarm.............
Construction and mining...............
Manufacturing...................................
Trade, transportation, and
utilities...............................................
Wholesale trade..............................
Retail trade.......................................
Transportation and
warehousing .............................
Information ........................................
Financial activities............................
Finance and insurance ................
Professional and business
services..............................................
Professional and technical
services.........................................
Administrative and waste
services.........................................
Education and health services.....
Health care and social
assistance ...................................
Leisure and hospitality....................
Accommodation and food
services.........................................
Other services, except public
administration.................................
1
Data on layoffs were reported by employers in all States and the
District of Columbia.
30
Monthly Labor Review • September 2008
SOURCE: Bureau of Labor Statistics, Current Employment Statistics
program.
Table 5.
Extended mass layoff separations by industry and reason for layoff, private nonfarm sector, New York-Northern
New Jersey-Long Island, 1996–2006
Measure
Total, private nonfarm..............................
Industry
Construction.........................................................
Manufacturing.....................................................
Wholesale trade...................................................
Retail trade............................................................
Transportation and warehousing.................
Information...........................................................
Finance and insurance......................................
Real estate and rental and leasing................
Professional and technical services . ...........
Administrative and waste services...............
Health care and social assistance..................
Arts, entertainment, and recreation.............
Accommodation and food services ............
Other services, except public
administration...................................................
Reason
Seasonal.................................................................
Total, nonseasonal, nonvacation...................
Contract completion......................................
Internal company restructuring.................
Slack work...........................................................
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
34,828 36,942 37,823 22,153 27,430 54,928 52,335 39,527 51,118 47,597 33,517
4,006 5,599 1,305
7,594 10,754 15,643
430 1,296 758
1,387 1,693 1,124
5,296 4,801 6,867
–
( 1 )
1,886
2,554 771 2,881
( 1 )
( 1 )
( 1 )
( 1 )
( 1 )
( 1 )
2,019 1,044 1,512
1,774 2,196 1,033
5,267 4,260 1,561
2,012 747 1,486
330
946
915
( 1 )
6,628
1,160
1,087
5,812
246
1,283
( 1 )
475
944
1,015
1,209
1,445
459
19,123 21,473 17,106 10,245
15,705 15,469 20,717 11,908
1,801 2,757 885 604
9,571 8,309 8,152 7,578
2,304 2,080 2,773 858
Data do not meet BLS or State agency disclosure standards.
NOTE: Dash represents zero.
1
during the 11 years studied. By contrast, the worst 3-year
period for construction was from 2003 through 2005,
when the industry recorded 19,000 separations.
The extent of layoffs related to permanent worksite closure, accounting for about 20 percent of New York area
layoff separations, also is instructive regarding the variation
among industries that exists with business turnover. About
one-third of the annual average of 2,866 manufacturing
separations per year involved closures. Of all industries,
manufacturing had the highest number of separations due
to workplace closings every year, with the exception of 1996
and 2001. (See table 7.) Nevertheless, in 6 of the 11 years
studied, another industry in decline—wholesale trade—had
a higher percentage of layoffs due to permanent closures. In
retail trade, a large industry characterized by high turnover,
closures caused about half of the layoff separations, on average, and this percentage also exceeded that of manufacturing in 6 of the 11 years examined.
Construction separations
Looking at extended mass layoff activity in relatively high
layoff sectors in the context of overall employment growth
highlights additional differences between New York and
the Nation. A healthy real estate market, along with in-
1,009 1,159
8,689 9,948
727 1,003
609 1,967
7,062 11,193
718 2,211
1,095 6,424
554 1,775
446 3,096
512 2,646
1,594 948
2,381 4,147
515 6,681
996
926
13,511 17,094
13,919 37,834
1,339 3,014
6,038 25,013
3,177 5,296
SOURCE:
5,007
10,236
510
1,204
4,595
4,925
7,382
1,350
1,810
3,911
704
5,117
3,443
5,468
8,960
2,129
635
3,806
3,386
1,724
( 1 )
1,712
2,075
1,607
4,925
893
6,041
6,578
1,053
2,022
5,581
6,394
4,596
1,784
2,466
2,248
3,095
4,048
4,249
7,982
7,220
945
1,372
2,622
3,090
2,045
310
4,109
2,204
2,603
4,307
7,469
695
628
465
376
4,353
5,006
715
1,113
4,814
2,040
570
–
1,721
3,497
1,503
3,810
3,708
(1)
17,307 11,581 14,200 16,145 13,756
35,028 27,946 36,918 31,452 19,761
7,704 8,104 10,522 8,935 6,235
13,920 7,979 12,187 10,453 7,934
6,421 5,989 5,947 3,627 3,247
Bureau of Labor Statistics, Mass Layoff Statistics program.
tensive efforts to rebuild lower Manhattan, fueled growth
among the building trades. Between 1999 and 2004,
New York area construction employment grew by about
13 percent, while the number of establishments grew by
14 percent. Nationally, the employee and establishment
counts both grew by less than 10 percent. (See table 8.)
As regards layoffs, construction accounted for at least
10 percent of the separations in the United States every
year except 2001 and 2002. In New York, a similar situation existed: during the 5 years after 2001, the construction sector averaged more than 5,500 separations per year
due to extended mass layoffs, amounting to 12 percent of
the total separations in the New York area. (See table 9.)
In both the New York area and the United States,
the quantity of construction layoffs was disproportionate to the sector’s employment. Nationally, construction
accounted for about 6 percent of total private nonfarm
employment. Among establishments with at least 50 employees, from which the layoff statistics were derived, construction employees amounted to yet a smaller percentage
of all employees. The disparity between relative shares of
total layoffs and total employment was even more evident
in the New York area, where construction had a location
quotient of 0.72, indicating less industry concentration
compared with that of the Nation.13
Monthly Labor Review • September 2008
31
New York Mass Layoffs
Table 6. Initial claimants for unemployment insurance resulting from extended mass layoffs, private nonfarm sector,
selected areas in the Mid-Atlantic Census Division and the United States, 1996–2006
Area
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
United States........................................................ 805,810 879,831 1,056,462 796,917 846,267 1,457,512 1,218,143 1,200,811 903,079 834,533 950,157
Mid-Atlantic Division...................................... 156,959 134,635 152,283 122,073 116,224 201,435 210,161 189,699 181,403 158,413 178,957
New Jersey.................................................... 30,489 35,347
31,910 22,353 25,945
39,114
41,868
38,747 33,841 28,075 30,517
New York........................................................ 38,416 26,113
37,478 27,260 28,481
54,877
79,493
73,111 75,146 75,311 79,472
Pennsylvania................................................ 88,054 73,175
82,895 72,460 61,798 107,444
88,800
77,841 72,416 55,027 68,968
New York-Northern New Jersey Long Island................................................... 21,302 27,262 32,346 21,242 27,368 46,964 47,988 36,467 51,846 50,222 40,867
SOURCE: Bureau of Labor Statistics, Mass Layoff Statistics program.
This pattern of relatively high layoff activity also was
reflected in national layoff and discharge rates, as captured by the BLS Job Openings and Labor Turnover
Survey (JOLTS):14 between 2001 and 2006, construction
recorded the highest layoff and discharge rates among all
sectors.
With the use of extended mass layoff separations data,
a rate similar to the turnover rate can be computed in
the context of relative employment levels to help gauge
extended mass layoff activity over time among establishments with at least 50 employees. This measure, too, confirms that construction tended to have the highest rate of
separations among national sectors. With the exception of
2001, construction led the other sectors, with a separation
rate that ranged from 4.5 percent to 7.8 percent. From
2003 through 2006, the national rate declined each year,
from 5.8 percent to 4.5 percent. (See table 10.)
Rather than reflecting an industry in decline, construction layoff activity was more indicative of the short-term
employment relationship that has become more characteristic of the industry. National data indicate that more
than 85 percent of all construction layoffs were due to the
ending of seasonal work and the completion of contracts,
with specialty trade contractors having a high percentage
of separations due to contract completion. Furthermore,
construction employers expected a recall in 59 percent
of the layoff events in the United States, above the 52percent average for private industry as a whole. Laid-off
construction workers were reemployed relatively quickly:
construction had one of the shortest average jobless durations among all sectors.
Manufacturing layoffs
In the late 1990s, manufacturing employment declined in
New York, as it did throughout the Nation, but the rate
of job loss worsened with the 2001 recession. Over-the32
Monthly Labor Review • September 2008
year job loss accelerated in the New York area, while it
moderated nationally. The deterioration in manufacturing was particularly pronounced in the New York area, as
a comparison of 2004 with 1999 figures indicates. Seventeen percent fewer manufacturing establishments were in
New York, while the decline in the Nation was 6 percent.
Among establishments employing at least 50 employees,
the decline was more significant: by 2004, the number of
manufacturers of that size contracted by 23 percent in the
New York area, while the number of like-sized manufacturing establishments in the United States dropped by
14 percent.
Manufacturing accounted for a dwindling, but significant, share of national employment, declining steadily
from about 25 percent in 1996 to about 18 percent in
2006. Meanwhile, at least 25 percent (ranging up to 47
percent in 1998) of all extended mass layoff separations
occurred in the sector each year. In New York, the story
was different: the only years that manufacturing accounted
for at least one-quarter of the separations were between
1997 and 2000, when the area economy was adding jobs
at its fastest pace during the 11 years studied. Since 2004,
when manufacturing amounted to 7 percent of total New
York area employment, the sector has accounted for 15
percent or less of the layoff separations in New York.
Nationwide, manufacturing separations due to extended
mass layoffs reached their height in 2001, with 627,930, a
rate of 4.7 percent. Since then, both levels and rates have
declined, and between 2004 and 2006, the rate of manufacturing separations in the United States was not more
than 2.5 percent. Above the private-industry average, the
manufacturing separations rate was still well behind that of
construction.
In the New York area, however, a relatively high number of major manufacturing job cuts failed to color the
total extended mass layoff picture as it did nationally.
The primary reason was that manufacturing was less
Chart 3.
Indexes of initial unemployment insurance claims, New York-Northern New Jersey-Long
Island, United States, and Mid-Atlantic Division, 1996–2006
Index
(1996 = 100)
250.0
Index
(1996 = 100)
250.0
200.0
200.0
150.0
150.0
100.0
100.0
50.0
U.S., all claims
U.S., extended mass layoff claims
New York-Northern New Jersey Long Island, extended mass layoff claims
0.0
Mid-Atlantic, all claims
Mid-Atlantic, extended mass layoff
claims
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
SOURCES: BLS Mass Layoff Statistics program, Employment and Training Administration, Office of Workforce Security.
concentrated in New York than throughout the Nation:
a location quotient of 0.54 indicates less of a presence
for the sector in the New York area than throughout the
Nation.
What accounted for the sharper decline in New York
area manufacturing employment if not mass layoffs? Production jobs may have moved out of high-priced Manhattan to lower cost areas either within New York City or
beyond the metropolitan area. If such moves were partial
and gradual, and did not result in at least 50 people being
laid off over a 5-week period, the job cuts would not be
captured in the mass layoff numbers, but the net result
would be reflected in the BLS employment data.15
Beyond less industry concentration, a different factor tempered the impact of mass layoffs in manufacturing in the New York area. Four industries accounted for
half of the 97,256 extended mass layoff separations in
manufacturing: apparel recorded 14,906 (15.3 percent)
of the separations, followed by chemical products with
12,226 (12.6 percent), food products with 11,202 (11.5
percent), and machinery with 10,795 (11.1 percent). (See
table 11.)
50.0
0.0
Although the apparel industry had the highest number
of extended mass layoff separations, only 15 percent of
those separations in the New York area involved permanent worksite closures. (See chart 5.) The low number of
separations due to the permanent closure of New York
apparel manufacturers stood in stark contrast to the situation in the Nation as a whole, where 56 percent of this
industry’s separations involved shutdowns.
Apparel manufacturing continued to be one of the metropolitan area’s primary industries, while maintaining international prominence, even with declining employment.
Between 1996 and 2001, despite low business startup
activity in almost every manufacturing industry, apparel
startups were high. Many of the large apparel manufacturers that had remained in the New York area adapted
to changing business conditions by trimming staff, as opposed to closing down permanently.16 In 1996, 23 percent
of all apparel establishments in the United States were located in metropolitan New York. The percentage decreased
to 19 percent in 2006, while the area’s employment share
for the industry grew from 12 percent to 14 percent of the
U.S. total during the same period. Meanwhile, the average
Monthly Labor Review • September 2008
33
New York Mass Layoffs
Chart 4.
Extended mass layoff separations, by reason for layoff, New York-Northern New Jersey-Long Island and
United States, 1996–2006
Separations
Separations
28,000
28,000
New York-Northern New Jersey-Long Island
24,000
24,000
Internal restructuring
20,000
20,000
Seasonal
16,000
16,000
12,000
12,000
Contract
completed
8,000
8,000
4,000
0
4,000
Slack work
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
0
Separations
Separations
600,000
600,000
United States
500,000
500,000
Internal restructuring
400,000
400,000
Seasonal
300,000
300,000
200,000
200,000
Contract
completed
100,000
100,000
Slack work
0
1996
1997
1998
1999
2000
SOURCE: BLS Mass Layoff Statistics program.
34
Monthly Labor Review • September 2008
2001
2002
2003
2004
2005
2006
0
Table 7. Permanent worksite closures: extended mass layoff separations, by selected industry, New YorkNorthern New Jersey-Long Island, 1996–2006
Industry
Construction.........................................................
Manufacturing.....................................................
Wholesale trade .................................................
Retail trade............................................................
Transportation and warehousing ................
Information...........................................................
Finance and insurance......................................
Administrative and waste services ..............
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
–
( 1 )
–
–
–
( 1 )
–
–
–
603 624
2,157 2,311 3,889 3,611 1,531 2,380 3,215 4,852 2,775 2,228 2,819
–
636 494
930
( 1 )
608
( 1 )
( 1 )
( 1 )
495 410
871
–
357
927 289 1,506
644 295 835 923 436
1
1
1
1
( )
( )
494
( )
–
2,423 1,500
( )
951 423
–
–
( 1 )
975
–
( 1 )
442 1,400
( 1 )
( 1 )
( 1 )
495
2,256 ( 1 ) 1,882
355
( 1 )
( 1 )
931
( 1 )
737 655
(1)
850 ( 1 )
( 1 )
–
( 1 )
355
999 267
–
( 1 ) 1,399
Data do not meet BLS or State agency disclosure standards.
NOTE: Dash represents zero.
1
establishment size in apparel declined in both New York
and the Nation.17
The New York experience contrasted with that of the
United States, in which manufacturing weighed heavily
on the layoff picture. In the Nation, the sector accounted
for close to 30 percent of all extended separations from
2002 to 2006. In New York, manufacturing accounted for
17 percent of the layoff separations, and between 2004
and 2006 the share fell to 14 percent.
Transportation and warehousing layoffs
Compared with its share of national employment among
establishments with at least 50 employees, transportation
and warehousing consistently had a higher percentage of
total separations. Since 2002, the national rate of extended
mass layoffs in transportation and warehousing has been
relatively close to manufacturing’s national rate. Separations in this sector usually have amounted to between 5
percent and 8 percent of the U.S. total since 1996.
In the New York area, however, extended mass layoff
separations in the transportation and warehousing sector
accounted for 10 percent of total extended mass layoff
separations, or about 4,300 separations per year, on average, between 2002 and 2006. As with manufacturing, the
layoff share during this period, though relatively high, was
down from earlier years: from 1996 to 2001, transportation and warehousing accounted for between 13 percent
and 26 percent of New York area layoffs, averaging about
6,000 separations annually. This reduced level of layoff
activity contrasts with the national experience: during the
5 years before 2001, between 49,000 and 58,000 separations occurred in the sector, while the average for the 5
years ending in 2006 was 73,000.
SOURCE:
Bureau of Labor Statistics, Mass Layoff Statistics program.
Leisure and hospitality turnover
In the years that followed 2001, New York area separations due to layoffs in the arts, entertainment, and recreation sector ranged from 3,810 to 5,117, averaging 8
percent of the private-industry total, compared with 3.5
percent nationally. In New York, as well as in the United
States, the sector accounted for about 2 percent of total
employment.
A higher incidence of layoffs also was evident in accommodation and food services. Employment in this
sector in the New York area was characterized by growth
over most of the 11-year period studied, similar to the
rest of the United States. After 2001, the sector accounted
for about 7.5 percent of New York area layoff separations,
compared with 6 percent nationally.
The difference in layoff proportions between the New
York accommodation and food services sector and its national counterpart may have been influenced by higher establishment growth in the metropolitan area. Employment
data show that establishment growth in New York became
more concentrated among smaller sizes (outside the scope
of the BLS Mass Layoff Statistics program), while nationally, the sector became increasingly more consolidated among
larger establishments. Between 1999 and 2004, employment growth in the sector in New York outpaced growth
in both construction and retail trade. The number of establishments grew by 16 percent, but among establishments
with 50 or more employees, the increase measured just
10 percent. On a national basis, the number of accommodation and food service establishments increased by 10
percent, but those with more than 49 employees increased
by 17 percent.
Accommodation and food services had a relatively high
Monthly Labor Review • September 2008
35
New York Mass Layoffs
Table 8. Change in the number of establishments, and employment by industry and establishment size, New YorkNorthern NewJersey-Long Island and United States, 1999–2004
All establishments
Industry
Employment change,
1999–2004
Establishments employing at least 50 workers
Establishment change,
1999–2004
Employment change,
1999–2004
Establishment change
as a percentage of all
establishments, 2004
New York -Northern
New Jersey-Long Island
Total private.............................................................
Construction.....................................................................
Manufacturing . ..............................................................
Wholesale trade..............................................................
Retail trade .......................................................................
Transportation and warehousing ............................
Information.......................................................................
Finance and insurance . ...............................................
Real estate and rental and leasing...........................
Professional and technical services ........................
Administrative and waste services...........................
Health care and social assistance .............................
Accommodation and food services ........................
Other services, except public administration .....
3.7
12.7
–19.4
–4.2
12.7
.3
10.4
–.6
12.1
6.9
–1.5
11.4
13.6
8.8
5.0
13.7
–16.6
–3.1
5.0
8.5
6.7
2.0
11.2
9.0
–.3
12.3
15.7
6.5
3.2
11.1
–22.7
–5.6
24.0
13.3
4.8
–3.1
8.7
3.3
–1.1
14.2
9.6
4.2
4.5
2.2
10.3
4.2
4.3
7.9
10.6
5.7
1.3
2.8
7.2
5.1
4.8
1.7
3.9
7.2
17.0
–1.1
6.0
13.0
7.4
8.7
11.3
17.7
4.1
14.1
11.5
5.1
5.4
8.9
–5.9
–4.6
.8
10.4
10.4
12.5
17.0
14.2
2.4
12.6
9.5
2.3
4.0
9.4
–14.0
–3.1
7.9
21.0
2.1
3.8
7.5
11.6
–.9
14.3
17.0
5.4
5.3
2.8
16.0
4.8
5.4
7.1
9.1
3.7
1.4
2.6
8.5
6.3
7.7
1.7
United States
Total private.............................................................
Construction.....................................................................
Manufacturing . ..............................................................
Wholesale trade..............................................................
Retail trade . .....................................................................
Transportation and warehousing.............................
Information . ....................................................................
Finance and insurance . ...............................................
Real estate and rental and leasing...........................
Professional and technical services ........................
Administrative and waste services . ........................
Health care and social assistance ............................
Accommodation and food services ........................
Other services, except public administration.......
SOURCE:
U.S. Census Bureau, County Business Patterns.
number of layoffs, despite a low industry concentration.
At 0.72, the area location quotient for accommodation
and food services was the same as that for construction,
indicating a smaller share of local, compared with national, employment. The 2002–06 period was worse than the
5 years prior to 2001 in terms of layoff separations in the
industry, and that was true at both the local and national
level, despite continued growth.
Information layoffs
Increased layoff activity despite sector growth also was
evident in the information sector. Annual job gains in New
York were strong between 1996 and 2001, averaging from
36
Monthly Labor Review • September 2008
2.5 percent to 6.5 percent. Communications industry startup activity was 20 percent above national averages during
this period. The recession, however, hit the sector particularly hard: in 2002, job losses for the year amounted to 9
percent. Although nationally the sector continued to lose
jobs, in the New York metropolitan area the information
industry rebounded in 2006, finally adding employment, at
a rate of 1.3 percent.
JOLTS data indicate that, between 2001 and 2006, the
information sector ranked among the sectors with the
lowest national layoff and discharge rates. However, in
terms of extended mass layoffs, the sector experienced an
above-average rate exceeding 2 percent of the U.S. employed between 2002 and 2003, as it did earlier, in 1996
Table 9. Percent distribution of extended mass layoff separations by industry, New York-Northern New Jersey-Long Island
and United States, 1996–2006
Industry
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
100.0
11.5
21.8
1.2
4.0
15.2
–
7.3
( 1 )
( 1 )
5.8
5.1
15.1
5.8
100.0
15.2
29.1
3.5
4.6
13.0
( 1 )
2.1
( 1 )
( 1 )
2.8
5.9
11.5
2.0
100.0
3.5
41.4
2.0
3.0
18.2
5.0
7.6
( 1 )
( 1 )
4.0
2.7
4.1
3.9
100.0
( 1 )
29.9
5.2
4.9
26.2
1.1
5.8
( 1 )
2.1
4.3
4.6
5.5
6.5
100.0
3.7
31.7
2.7
2.2
25.7
2.6
4.0
2.0
1.6
1.9
5.8
8.7
1.9
100.0
2.1
18.1
1.8
3.6
20.4
4.0
11.7
3.2
5.6
4.8
1.7
7.5
12.2
100.0
9.6
19.6
1.0
2.3
8.8
9.4
14.1
2.6
3.5
7.5
1.3
9.8
6.6
100.0
13.8
22.7
5.4
1.6
9.6
8.6
4.4
( 1 )
4.3
5.2
4.1
12.5
2.3
100.0
11.8
12.9
2.1
4.0
10.9
12.5
9.0
3.5
4.8
4.4
6.1
7.9
8.3
100.0
16.8
15.2
2.0
2.9
5.5
6.5
4.3
.7
8.6
4.6
5.5
9.0
15.7
100.0
13.0
14.9
2.1
3.3
14.4
6.1
1.7
–
5.1
10.4
4.5
11.4
11.1
New York-New JerseyLong Island
Total, private nonfarm............................
Construction.......................................................
Manufacturing...................................................
Wholesale trade.................................................
Retail trade..........................................................
Transportation and warehousing...............
Information.........................................................
Finance and insurance ...................................
Real estate and rental and leasing..............
Professional and technical services............
Administrative and waste services.............
Health care and social assistance................
Arts, entertainment, and recreation...........
Accommodation and food services...........
Other services, except public
administration.................................................
.9
2.6
2.4
2.1
3.6
1.7
1.3
1.6
.9
.8
(1)
100.0
11.2
37.0
2.1
12.3
4.6
5.2
3.0
.4
2.7
6.4
3.8
3.3
4.8
100.0
14.0
34.1
1.6
10.1
6.1
6.1
2.2
.4
3.5
5.3
3.6
5.0
5.2
100.0
10.8
47.3
1.4
5.9
5.7
4.4
2.3
.2
2.2
5.4
3.1
3.1
4.8
100.0
13.0
39.5
1.9
10.2
5.5
2.6
2.4
.2
2.7
6.8
3.9
2.9
4.3
100.0
12.1
40.0
1.9
9.6
5.5
1.6
3.4
.2
2.4
8.5
4.2
2.8
4.5
100.0
7.3
41.2
1.9
8.7
7.7
4.0
2.2
.5
3.4
11.0
1.6
2.6
5.2
100.0
9.3
35.7
1.9
10.7
6.4
4.6
3.0
.2
4.6
10.6
2.4
3.6
4.0
100.0
10.9
31.6
2.5
10.5
7.2
5.4
3.3
.3
3.3
12.2
2.7
3.1
4.4
100.0
12.0
25.6
1.6
14.5
5.9
3.7
3.4
.4
3.3
11.4
4.4
3.8
6.9
100.0
13.8
25.2
1.5
9.0
7.6
2.6
2.1
.3
4.7
10.6
4.9
5.9
8.5
100.0
13.5
29.4
1.5
10.7
7.5
2.0
3.3
.2
4.7
9.8
3.2
4.6
7.2
.8
1.2
1.2
1.3
1.2
.7
1.1
1.0
1.5
1.5
1.1
United States2
Total, private nonfarm............................
Construction.......................................................
Manufacturing...................................................
Wholesale trade.................................................
Retail trade..........................................................
Transportation and warehousing...............
Information.........................................................
Finance and insurance ...................................
Real estate and rental and leasing..............
Professional and technical services . .........
Administrative and waste services.............
Health care and social assistance................
Arts, entertainment, and recreation...........
Accommodation and food services ..........
Other services, except public
administration ...............................................
Data do not meet BLS or State agency disclosure standards.
Data on layoffs were reported by employers in all States and the
District of Columbia.
1
2
and 1997 (while the sector was expanding).
In the New York area, extended mass layoffs in the information sector resulted in about 4,000 separations, on
average, between 2002 and 2006, or 6.7 percent of all metropolitan area separations. The largest number of separations during these years occurred in 2004, when the overall
employment picture was starting to improve. Nationally,
this sector accounted for 3.6 percent of all private-industry
layoff separations. The disparity between local and national
proportions, however, was consistent with the difference in
employment shares: as indicated by a 1.47 location quotient, information sector employment was more highly
concentrated in the New York area.
NOTE: Dash represents zero.
SOURCE: Bureau of Labor Statistics, Mass Layoff Statistics program.
Finance and insurance separations
After a slow period in 1996 and 1997, finance and insurance employment grew between 1 percent and 2 percent annually in the New York area prior to the 2001
recession. Employment declined between 2001 and
2003, but by 2005 growth had returned to prerecession
rates, unlike growth rates in most of the other sectors
in the area.
Finance and insurance layoff separations varied quite
a bit from year to year, with the peak occurring in 2002,
when there were more than 7,000 extended separations.
In 2006, the sector saw 570 separations, the lowest numMonthly Labor Review • September 2008
37
New York Mass Layoffs
Table 10. Rates of extended mass layoff separations, by industry, United States,1 1996–2006
Average percent
employment in
Industry
establishments with 1996
50 or more employees
Total, private nonfarm........................
Construction . ................................................
Manufacturing...............................................
Wholesale trade.............................................
Retail trade......................................................
Transportation and warehousing ..........
Information.....................................................
Finance and insurance................................
Real estate and rental and leasing..........
Professional and technical services . .....
Administrative and waste services ........
Health care and social assistance............
Accommodation and food services ......
Other services, except public
administration.............................................
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
57.4
36.0
79.2
42.0
50.1
67.0
72.4
57.9
29.3
46.1
71.2
66.7
42.8
1.7
6.8
2.6
1.0
1.7
1.8
2.4
1.0
.8
1.0
1.5
.5
1.2
1.7
7.8
2.4
.7
1.4
2.3
2.6
.7
.7
1.3
1.1
.4
1.3
1.7
5.7
3.3
.6
.8
2.2
1.9
.7
.3
.8
1.1
.4
1.2
1.5
5.6
2.6
.7
1.3
1.9
1.0
.7
.3
.8
1.2
.4
.9
1.5
4.8
2.6
.7
1.2
1.8
.6
1.0
.4
.7
1.4
.5
1.0
2.4
4.6
4.7
1.2
1.7
4.1
2.2
1.0
1.2
1.5
3.1
.3
1.8
2.1
5.1
3.8
1.0
1.8
3.1
2.3
1.2
.5
1.9
2.6
.3
1.2
2.0
5.8
3.4
1.3
1.7
3.3
2.9
1.2
.6
1.4
2.9
.4
1.3
1.7
5.1
2.3
.7
1.9
2.2
1.6
1.0
.7
1.1
2.2
.5
1.6
1.5
4.9
2.0
.6
1.1
2.5
1.1
.6
.5
1.3
1.7
.5
1.7
1.5
4.5
2.5
0.6
1.3
2.5
.9
.9
.3
1.3
1.6
.3
1.5
23.3
.9
1.4
1.3
1.3
1.2
1.1
1.5
1.2
1.5
1.4
1.1
1
Data on layoffs were reported by employers in all States and the
District of Columbia.
ber recorded for finance and insurance during the 11 years
studied.
In the 5 years after 2001, this sector accounted for
6.7 percent of all separations in the New York area,
compared with just 3.0 percent nationally over the same
period. However, the metropolitan area’s share of separations was not disproportionate to its portion of total
employment: in the New York area, about 8 percent of all
private-industry workers were employed in finance and
insurance. Nationally, the share was between 5 percent
and 6 percent. Furthermore, a slightly greater percentage of finance establishments staff at least 50 employees
in the New York area compared with the Nation: about
6 percent of all finance establishments in New York employed at least 50 employees, while nationally the figure
was approximately 4 percent.
Thus, even though major job cuts in finance were a
significant part of the layoff activity in the New York
area, they were neither extraordinary (on the basis of
industry concentration and size) nor permanently damaging to the sector’s local strength. Nevertheless, BLS
layoff data show that finance separations were costly:
in 2005 and 2006, the longest average jobless duration,
based on the average number of continued claims in
the United States, was experienced by claimants laid
off from finance and insurance companies. Employees
from that sector also exhausted their benefits at high
rates.
38
Monthly Labor Review • September 2008
SOURCES: Bureau of Labor Statistics, Mass Layoff Statistics program and
Quarterly Census of Employment and Wages.
Table 11. Total extended mass layoff separations, by selected
industries, New York-Northern New Jersey-Long
Island, 1996–2006
Industry
Manufacturing..............................................
Apparel .......................................................
Chemicals ..................................................
Food..............................................................
Machinery .................................................
Miscellaneous manufacturing..........
Transportation equipment.................
Computer and electronic
products.................................................
Paper . ..........................................................
Printing and related support
activities.................................................
Leather and allied products..............
Fabricated metal products.................
Plastics and rubber products............
Electrical equipment and
appliances . ..........................................
Nonmetallic mineral products.........
Primary metals .......................................
Furniture and related products.......
Textile mills................................................
Textile product mills..............................
Petroleum and coal products...........
Beverage and tobacco products.....
Wood products........................................
All layoff
separations
Permanent
worksite
closure
separations
97,256
14,906
12,226
11,202
10,795
9,254
8,760
31,768
2,224
4,760
4,666
3,492
3,509
2,681
5,766
3,744
1,757
1,210
3,520
3,318
3,140
3,086
909
539
865
1,450
2,024
1,365
1,261
1,012
590
387
325
(1)
(1)
1,262
629
( 1)
773
(1)
(1)
(1)
(1)
(1)
Data do not meet BLS or State agency disclosure standards.
SOURCE: Bureau of Labor Statistics, Mass Layoff Statistics program.
1
Chart 5.
Percent of separations not involving permanent worksite closure in manufacturing, New YorkNorthern New Jersey-Long Island, 1996–2006
Industry
All manufacturing
Apparel
Leather and allied products
Printing and related support activities
Fabricated metal products
Computer and electronic products
Transportation equipment
Paper
Machinery
Other manufacturing
Miscellaneous manufacturing
Chemicals
Food
Nonmetallic mineral products
Plastics and rubber products
Electrical equipment and appliances
Furniture and related products
0
SOURCE:
20
40
60
Layoff separations (percent)
Bureau of Labor Statistics, Mass Layoff Statistics program.
Administrative and waste services
After continued strong growth in the late 1990s, amounting to increases of between 5 percent and 7 percent a year,
employment in New York area administrative and support and waste management and remediation services (or,
simply, administrative and waste services) slowed with
the recession and then remained relatively unchanged.
Layoffs in New York in this sector reached their peak
of 3,911 in 2002. In the years that followed, administrative and waste services had at least 2,000 layoffs annually,
compared with an average of 1,206 during the 5 years
prior to 2001.
From 2002 through 2006, separations in administrative and waste services amounted to 4.9 percent of the
total in New York, while nationally, the sector accounted
for almost 11 percent of all layoffs, slightly more than
its share of employment among establishments with at
least 50 employees. A large number of separations due
to contract completion occurred in this sector, which
includes temporary help agencies and professional employer organizations.
80
100
TWO SECTORS THAT WERE RESPONSIBLE for a substantial portion of layoffs in the greater New York area prior to
2001 were the manufacturing sector and the transportation
and warehousing sector. The share of area separations in
these two sectors declined after 2001, while layoff activity
increased in four other sectors: construction; administrative and waste services; arts, entertainment, and recreation;
and accommodation and food services. The differences
between the manufacturing sector and the transportation and warehousing sector, reflected in the nature of,
and reason for, the layoffs, as well as the extent of related
permanent closures, contributed to a fundamental change
in the character of job displacement in the New York area.
Particularly noteworthy is the fact that layoff displacement
increased among several local industries during periods of
employment growth.
The mass layoff experience in the greater New York area
after 2001 was qualitatively different from what it was prior
to 2001, in contrast to the national pattern. Although some
of the difference might be explained by the local industry
mix, other factors helped transform the character of extended mass layoffs in New York. Foremost, the New York
Monthly Labor Review • September 2008
39
New York Mass Layoffs
area experienced dramatic growth in layoff actions due
to the completion of employment contracts. In 2005 and
2006, contract completion accounted for more nonseasonal layoff events than internal company restructuring
did, reversing the pattern of the past. A possible explanation for this shift is that increased business activity, especially within construction, coupled with a drive to keep
costs down throughout industry, led to both an increase
in contracting and a decrease in costly restructuring.18
Furthermore, as suggested by the analysis of New York
area data presented in this article, the ability of employers to adapt to both competitive pressures and slack work
by trimming staffs varied by industry. For example, large
employers in apparel, a key local manufacturing industry,
reduced the size of their workforce more often than permanently closing down operations.
The analysis presented herein has attempted to make
comparisons between the New York metropolitan area
and the Nation over time. Additional information is
needed, however, to complete an assessment of extended
mass layoffs, affording opportunities for future research.
Information on business turnover and job creation and
destruction, by firm or establishment size in metropolitan
areas, would round out the employment picture and help
explain layoff trends. Beyond this benefit, the information could aid in the distribution of funds for employment
services19 and provide a more robust picture of industry
health. As the Workforce Information Council concluded
in a report about local data needs, “Understanding the
impact of layoffs and plant closings on labor markets,
workers, and communities requires information on other
dynamic aspects of the labor market.”20 Indeed, local layoff data, such as those presented herein, would be greatly
enhanced with local job dynamics data.
Notes
1
The New York-Northern New Jersey-Long Island Metropolitan
Statistical Area (MSA), as defined by the Office of Management and
Budget in Bulletin 06–01, is composed of New York City and Nassau,
Putnam, Rockland, Suffolk, and Westchester Counties in New York;
Bergen, Essex, Hudson, Hunterdon, Middlesex, Monmouth, Morris,
Ocean, Passaic, Somerset, Sussex, and Union Counties in New Jersey,
and Pike County, Pennsylvania. For convenience, the New York-Northern New Jersey-Long Island MSA is referred to as the New York area, or
simply New York, throughout this article.
2
Each extended layoff event causes at least 50 employees to lose
work for more than 30 days. If large layoffs occur gradually, in such
a way that the requirement of 50 unemployment claims filed in a 5week period is not reached, then the layoff event is not counted as
an extended layoff by the Mass Layoff Statistics program. The 31-day
minimum duration for qualification as a layoff limits the focus of the
survey program to more permanent job dislocation. Most layoff events
involving 50 or more workers last for 30 days or less. Along with the
minimum required duration, in cases with no direct job loss, such as
employers transferring work elsewhere without laying off workers, no
information is collected, even though some displacement may result.
3
The Mass Layoff Statistics program is a Federal-State program
that utilizes a standardized, automated approach to identifying, describing, and tracking the effects of major job cutbacks, using data from each
State’s unemployment insurance database. Each month, States report on
establishments with at least 50 initial claims filed against them during
a consecutive 5-week period. The establishments are contacted by the
State agency to determine whether these separations lasted 31 days or
longer; if so, other information concerning the layoff is collected. The
program also provides measures of laid-off workers’ spells of unemployment to the point when regular unemployment insurance benefits are
exhausted. These measures include the average number of continued
claims, as well as the percentage of claimants receiving final payment.
(A continued claim is a claim filed after the initial claim, either by mail,
by telephone, or in person, for waiting-period credit or for payment for a
certified week of unemployment.)
4
An establishment is a unit at a single physical location at which
predominantly one type of economic activity is conducted.
40
Monthly Labor Review • September 2008
Of the 25 categories currently used to classify justifications for
a layoff, only a handful accounted for most of the separations in the
New York area. Other, less frequently used reasons failed to yield publishable local-level results. Recently, the BLS concluded an in-depth
review of all reasons for separation, in an effort to improve the capture
and classification of economic reasons. Data published for 2007 now
reflect an enhanced classification scheme. Additional and enhanced
categories, as well as aggregations of related reasons, are currently
available.
5
6
Not an output of the BLS Mass Layoff Statistics program, the
rates produced for these analyses were used to facilitate comparisons
across years and among industry sectors. The layoff event rate indicates
the number of layoff events per 100 establishments (in which at least
50 workers are employed). To compute this rate, establishment counts
by size of establishment were derived from the U.S. Census Bureau’s
County Business Patterns. The layoff separation rate, indicating the
number of extended mass layoff separations per 1,000 workers employed, was computed at the national level with employment data by
size of establishment from the BLS Quarterly Census of Employment
and Wages (QCEW).
7
A worksite closure involves the complete shutdown of either a
multiunit or a single-unit establishment, or the partial closure of a
multiunit establishment wherein entire worksites affected by layoffs
are closed or planned to be closed.
8
See Steven J. Davis, R. Jason Faberman, and John Haltiwanger,
“The Flow Approach to Labor Markets: New Data Sources and Micro-Macro Links,” NBER working paper 12167 (National Bureau of
Economic Research, April 2006); on the Internet at papers.nber.org/
papers/w12167.pdf.
9
“Analysis of Business Formation, Survival, and Attrition Rates of
New and Existing Firms and Related Job Flows in Appalachia” (Camp
Hill, PA, The Brandow Company, October 2001); on the Internet at
www.arc.gov/images/reports/bizform/analysis-final.pdf.
10
See non-seasonally-adjusted historical data on State gross job
gains and losses, on the Internet at www.bls.gov/bdm.
11
An initial claimant is a person who files any notice of unemploy-
ment to initiate a request either for a determination of entitlement to,
and eligibility for, compensation or for a subsequent period of unemployment within a benefit year or other period of eligibility.
12
Important distinctions exist between extended mass layoff data
and displaced worker data. In addition to tallying those who lost jobs,
the displaced worker count includes workers who left jobs in anticipation of losing them. Displaced workers are persons 20 years of age and
older who lost or left jobs. Displaced worker data are restricted to longtenured employees: those who had worked for their employer for at least
3 years. Extended mass layoff data cover only separated workers, without
any age or tenure restrictions. (See “Worker Displacement, 2003–2005,”
BLS news release (Bureau of Labor Statistics, Aug 17, 2006), on the
Internet at www.bls.gov/news.release/archives/disp_08172006.pdf.)
13
The location quotient is the ratio of employment in a particular
industry in a certain geographical area (in this article, the New York
metropolitan area) to base-industry employment (in this article, the
private-sector total), divided by the ratio of employment in the same
industry in the base area (the United States) to base-industry employment in the base area. For this computation, 2006 annual averages
from the QCEW were used.
“Job Openings and Labor Turnover: January 2007,” BLS news
release (Bureau of Labor Statistics, Mar. 13, 2007), on the Internet at
www.bls.gov/news.release/archives/jolts_03132007.pdf. Layoffs and
discharges are involuntary separations initiated by the employer and include 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 discharges for cause; terminations of permanent
or short-term employees; and terminations of seasonal employees.
14
15
Movement of work within the same company or to a different
company, either domestically or outside the country, occurred in less
than 10 percent of all nonseasonal layoff events in the United States.
In 2004, the BLS Mass Layoff Statistics program added offshoring and
outsourcing of work as reasons that identify job loss associated with the
movement of work, within a company and to another company, domestically and out of the country. Nearly all the overseas relocations occurred
in manufacturing. Nevertheless, because of publishability criteria, data
on movement of work and overseas relocations were not available for
the New York area. Criteria that safeguard confidentiality restrict what is
published at the local level and result in the suppression of information
that is available at the national level, such as additional information on
relocations.
See “New York City’s Garment Industry: A New Look?” (New
York and Albany, Fiscal Policy Institute, August 2003).
16
17
In 1996, businesses with between 50 and 999 workers accounted
for 16.4 percent of U.S. apparel establishments and 71.2 percent of em-
ployment in the industry. By 2006, the share had declined to 9.6 percent
of establishments and 60.8 percent of employment. It must be pointed
out, however, that small apparel manufacturers, namely, those employing
fewer than 50 workers (and not studied by the BLS Mass Layoff Statistics
program), accounted for 90 percent of establishments in 2006.
Without knowing the exact reasons for layoffs in each New
York area industry, however, this hypothesis cannot be completely
validated. Additional data limitations include employer coverage and
the duration of layoffs. BLS mass layoff data cover only establishments
that employ 50 or more workers. Smaller establishments were outside
the scope of the survey, although layoff activity in these establishments is documented to have been significant. Between 1992 and the
fourth quarter of 2006, more than half of the gross job losses were in
firms with fewer than 50 employees; during that period, 87.1 percent
of firms which closed were in that size class. BLS Business Employment Dynamics size class statistics are measured at the firm level
rather than the establishment level. (A firm is a business organization consisting of one or more domestic establishments in the same
area and industry under common ownership or control. The firm and
the establishment are the same for single-establishment firms.) (See
“Business Employment Dynamics: Second Quarter 2006,” BLS news
release (Bureau of Labor Statistics Aug. 16, 2007), on the Internet
at www.bls.gov/news.release/archives/cewbd_08162007.pdf; and
“New Quarterly Data from BLS on Business Employment Dynamics
by Size of Firm,” BLS news release (Bureau of Labor Statistics, Dec.
8, 2005), on the Internet at www.bls.gov/news.release/pdf/cewfs.
pdf.) Although a large percentage of job flows occurs in smaller firms,
BLS data indicate that larger size classes experienced more quarters
of net loss, as reflected in negative net employment change, related
to the 2001 recession.
18
The Workforce Reinvestment Act (Public Law 105–220—Aug.
7, 1998) mandates the development of a comprehensive workforce
information system that includes “the incidence of, industrial and geographical location of, and number of workers displaced by, permanent
layoffs and plant closings.” Analysis of such information, as intended
by the Act, is not only for the allocation of Federal funds, but also for
national, State, and local policymaking, the implementation of Federal
policies, program planning and evaluation, and researching labor market dynamics.
19
The Workforce Information Council is a collaboration of Federal and State agency officials that plans, guides, and oversees the U.S.
workforce information system. The report, titled Needs and Alternatives
for Plant Closing and Layoff Statistics: Report to the Workforce Information
Council (Plant Closing and Layoff Statistics Work Team, Mar. 22, 2000),
is on the Internet at www.workforceinfocouncil.org/documents/wg_
LayoffStats.zip.
20
Monthly Labor Review • September 2008
41
Conference Report
Knowing younger workers better:
information from the NLSY97
Papers from the 10th anniversary conference
of the National Longitudinal Survey of Youth,
1997 cohort, addressed schooling, employment, adolescent
behaviors, and many other aspects of youths’ lives
Dan Black,
Robert Michael,
and Charles Pierret
Dan Black is a professor
of public policy at the
University of Chicago and
Principal Investigator of
the National Longitudinal Survey of Youth 1997
Cohort at NORC.
Robert Michael is the
Eliakim Hastings Moore
Distinguished
Service
Professor Emeritus at the
University of Chicago
and the Project Director
of the National Longitudinal Surveys Program at
NORC.
Charles Pierret is director
of the National Longitudinal Surveys Program at
the Bureau of Labor Statistics. E-mail:
pierret.charles@bls.gov
The statements in this
article do not necessarily
reflect the views of any
of the aforementioned
institutions.
42
F
or more than 40 years, the U.S. Department of Labor has undertaken
a series of major, national studies
that track labor force behavior. These studies follow the same men and women, year
after year, and by doing so reveal much
about what affects wages and hours of work,
how new skills influence success in the job
market, how health and schooling interact
to influence careers, and how unexpected
events—from plant closings and bad weather to product innovations and the openings
of new markets—affect earnings. The National Longitudinal Surveys (NLS) program
has become one of the Nation’s most respected and influential sources of data about
the work force since its inception in 1966,
administered through the Employment and
Training Administration until 1984 and
through BLS thereafter. The NLS program
consists of seven samples of men and women who have been surveyed periodically and
have reported on many of their behaviors in
and related to labor markets. These surveys
have been used in thousands of research
projects within the Government and in research universities and analytic think tanks.
The studies constitute a major component of
what researchers now know about the roles
of schooling, intellectual ability, health, mi-
Monthly Labor Review • September 2008
gration, community, and family in developing the “human capital” and “social capital”
that influence the distribution of earnings
in the United States and the level of our
Nation’s gross domestic product.
In May 2008, BLS hosted a conference
to highlight new research using the most
recent data from one of these data sources,
the National Longitudinal Survey of Youth,
1997 cohort (NLSY97).1 This survey of
young people born from 1980 to 1984 (age
12 to 17 in the first year of the survey) has
now taken place for 10 consecutive years.
The face-to-face interview of these youths
asks about their schooling, employment, adolescent behaviors, and many other aspects
of their lives. In the data that were available
for study at the time of the conference, these
nearly 9,000 men and women from across
the Nation were only in their early- to mid20s, but already their reported experiences
and behaviors revealed important facts that
will have an impact on the labor force for
decades to come. This article offers a brief
and informal characterization of a few of the
studies on which presenters reported at the
conference. The conference presentations
were based on preliminary research findings
of these studies that are now undergoing
peer scrutiny prior to official publication in
scholarly journals and books. (See the box.)
Employment
Changing characteristics of youth. Employment of the
NLSY97 youths is perhaps the central behavior of interest.
One important paper concerning employment presented
at the conference was written by Joseph Altonji, Prashant
Bharadwaj, and Fabian Lange from Yale University and
entitled “Changes in the Characteristics of American
Youth: Implications for Adult Outcomes.” The paper asks
what one can predict today about the labor force 20 years
from now when the NLSY97 cohort will be in its peak
earning years. The analysis is based on the experiences of
the National Longitudinal Survey of Youth 1979 Cohort
(NLSY79)—an earlier NLS cohort, fielded in 1979—with
respondents born between 1957 and 1964. The authors
use the relationship between early labor-market-relevant
characteristics of youths in the NLSY79 and their subsequent mid-career labor market outcomes to predict midcareer labor market outcomes of the NLSY97 cohort on
the basis of their current characteristics.
The paper comprises two parts. In the first, the authors
“create a set of youth characteristics that correlate with
adult outcomes and are comparable across the NLSY97
and the NLSY79.” Even though the authors attempt to
make the two data sets directly comparable, differences
in sampling, attrition, and questions make this a complicated exercise. For example, the NLSY97 was sampled
at younger ages (12–17) than the NLSY79 (14–22). Although a greater percent of youths eligible for the sample
were actually interviewed in the first round of the NLSY97,
Tenth Anniversary Conference Papers, NLSY97, May 29–30, 2008
Joseph G. Altonji, Prashant Bharadwaj, and Fabian Lange,
“Changes in the Characteristics of American Youth: Implications for Adult Outcomes.”
Joseph G. Altonji, Sarah Cattan, and Iain Ware, “Sibling
Influences on Teenage Risky Behaviors.”
Alison Aughinbaugh and Rosella M. Gardecki, “Attrition
in the National Longitudinal Survey of Youth 1997.”
Philippe Belley, Marc Frenette, and Lance Lochner, “PostSecondary Attendance by Parental Income: A Canada-U.S.
Comparison.”
Dan A. Black, Kerwin Charles, and Seth Sanders, “The
Problem with Men.”
Dan A. Black, Robert T. Michael, and Kanru Xia, “The
Propensity to be an NLSY97 Respondent: Evidence from the
Screener Data.”
A. Rupa Datta Parvati Krishnamurty, “High School Experience: Comparing Self-Report and Transcript Data from
the NLSY97.”
Keith Finlay, “Effect of Employer Access to Criminal History Data on the Labor Market Outcomes of Ex-Offenders
and Non-Offenders.”
Tricia Gladden and Charles Pierret, “Employment Before
Age 16: Does it Make a Difference?”
Jeffrey Grogger, “Speech Patterns and Black-White Wage
Inequality.”
Carolyn J. Hill, Harry J. Holzer and Henry Chen, “Against
the Tide: Household Structure, Opportunities, and Outcomes
among White and Minority Youth,” chapters 3 and 4.
Robert Kaestner and Michael Grossman, “Effects of
Weight on Adolescent Educational Attainment.”
Jennifer Manlove, Mindy E. Scott, Erum Ikramullah, Kate
Perper, and Emily Lilja, “Relationship Context and the Transition to a Nonmarital Birth.”
Kristin Moore, and Kassim Mbwana, “Preventing Risky
Sex and Adolescent Parenthood: Does the Effectiveness of
Parenting Practices Differ For Children with Varied Risks?”
Randall J.Olsen, “The Desirability of Partner Traits and
Two Decades of Change in the Marriage Market: A Oneand-a-Half Sex Model of Marriage.”
Michael R. Pergamit, “Who Runs Away from Home? An
Exploratory Analysis.”
James R. Walker, “Choice, Enrollment and Educational
Attainment within the NLSY79 and NLSY97.”
Kenneth I. Wolpin, and Antonio Merlo, “Youth Crime and
High School Completion.”
Lawrence Wu and Pamela Kaufman, “Two Decades of
Change in Premarital First Births: Cohort Comparisons from
the NLSY79 and NLSY97.”
NOTE: Many of those papers which are available can be found online at: http://harrisschool.uchicago.edu/research/conferences/NLSYConf/
Monthly Labor Review • September 2008
43
Conference Report
subsequent attrition has been higher. Because they were
younger when they were first interviewed, NLSY97 sample
members had more years to drop out of the survey before
age 22, when many of the characteristics that the authors
study are measured. The authors devote a great deal of effort to ensuring that any differences in measured characteristics are real and not an artifact of survey differences.
The authors’ most substantive finding is important: they
find that the NLSY97 had more skills at the age of 22 than
the NLSY79 did. The greatest advantage of the NLSY97
was in education; along all measured dimensions of educational attainment, the younger cohort was clearly superior to the older cohort. By age 22, the 1997 cohort had
completed more than one-third of a year more of school,
was more likely to have a high school diploma—or, failing
that, to have a GED—and was much more likely to still
be attending school or to have finished 14 years of school
than the 1979 cohort. This skills advantage manifested itself in significant gains on the Armed Forces Qualifying
Test (AFQT), the test the military uses to determine skill
levels when making admission and job assignments. These
gains were especially remarkable for minority youth, with
African Americans’ (or Blacks’) scores improving by 36
percent and Hispanics’ scores improving by 24 percent
between the two cohorts (compared with a 5 percent improvement for Whites). Gains in parents’ education were
also significant, with the average NLSY97 youth having a
mother with 1 year more of education and a father with
three-quarters of a year more education than the mother
and father of the youth’s counterpart in the NLSY79.
Where the 1997 cohort falls short in comparison
with the 1979 cohort is in the area of family structure.
A much larger percentage (47 percent versus 25 percent)
of the 1997 cohort was living in families in which one of
the parents was not present. So although parents of the
younger cohort had more skills to impart to their children,
they had less contact with their children.
The second part of the Altonji, Bharadwaj, and Lange
paper uses the reported childhood experiences from the
1979 and 1997 cohorts, along with the experiences from
adulthood from the 1979 cohort, to predict outcomes for
the 1997 cohort as adults. Using the characteristics derived in the first part of the paper, the authors estimate
the impact that changes in skill level will have on the
wage distribution when the cohort has reached middle
age. Overall, they expect wages to increase by 6 percent to
7 percent, though the increase will be greater at the upper
end of the distribution and lesser at the lower end. This
means an increase in inequality over the next decades.
The authors suggest that increases in skills for groups
44
Monthly Labor Review • September 2008
that were relatively disadvantaged in the 1979 cohort,
however, will result in diminishing gaps between the sexes
and among races. Black and Hispanic males will gain significantly on white males except at the very top of the
wage distribution. From the bottom of the wage distribution to the 90th percentile, the wage gap should close by
about 4 percentage points for both black and Hispanic
males relative to white males. Similarly, wage gains for
females should exceed those of males, causing the wage
gap between the sexes to decrease by around 2 percentage
points. Within-group inequality will grow as skills become
more unequal within groups, but average skills across sex
and race groups will become less unequal, resulting in less
wage inequality across groups. So while the increase in
inequality that has plagued the economy for the last 30
years is likely to continue, it will be based less on race and
sex than it has been in the past.
The authors remind readers that their conclusions rest,
necessarily, on the assumptions that the labor market premium or discount for a racial or ethnic group or for one
sex or the other remains the same over time. Similarly,
their expectations of the future labor market do not take
into account broader questions pertaining to how the financial returns of schooling will change as markets and
products develop or how the continued competitiveness
of global markets might affect labor market trends. In this
sense, the analysis undertaken by Altonji, Bharadwaj, and
Lange offers only a partial answer to the question of how
the workforce will fare in the years ahead, but their answer, cautiously constructed and conditioned as it is, uses
these NLSY longitudinal data sets in the best way possible
and offers a decidedly optimistic assessment of future developments in the labor force.
Employment before age 16. Another paper from the conference that focuses on employment is one that exploits
the NLSY97’s data on work history and its links across several domains to examine the consequences of employment
at a very young age among the youths in the cohort. Tricia
Gladden and Charles Pierret from the Bureau of Labor
Statistics use the extensive data on very early employment
in the NLSY97 in their paper “Employment Before Age
16: Does it Make a Difference?” They point out that collecting information on teen employment was a key reason
that the survey was started. Standard labor market surveys
such as the Current Population Survey only report about
employment starting at age 16. However, a majority of
youths in the NLSY97 reported doing some work for pay
before this age. Gladden and Pierret posit that it is unclear whether early employment is ultimately beneficial
to these youths. On the one hand, early employment may
teach important lessons such as responsibility, perseverance, and self-reliance and allow youths to accumulate
experience that will prove useful later in their careers. On
the other hand, early employment may be distracting,
taking youths away from educational and developmental
activities that will prove more beneficial than the menial
jobs that are available to young workers. It may also introduce them to older youths who are engaged in behaviors
that are not age-appropriate for the young workers. Gladden and Pierret’s paper explores the correlation between
youth employment and a number of outcomes in the late
teen years as a first attempt to measure the effects of early
employment.
The NLSY97 interviewed youths as young as 12 and
asked them to report on jobs they held at any time after their 12th birthday. Because these children were not
legally able to hold a job with an employer, the NLSY97
concentrated on “freelance jobs” among this group. These
are informal jobs such as babysitting or yard work where
the employee works directly for the ultimate consumer of
the service, usually on an as-needed basis. Respondents
older than 14 were also asked about traditional “employee
jobs”—that is, those in which the youth worked for an
employer who provided goods or services to many consumers. Restaurants and retail establishments provided
typical employee jobs for teens in the sample.
Gladden and Pierret identify respondents who worked
in freelance jobs between the ages of 11 and 15 and those
who worked in employee jobs at 14 or 15. They then follow these youths until the age of 20, examining various
outcomes along the way. Two findings are notable from
this research. First, once youths enter the labor force, they
tend to continue to work throughout their teen years. Between 80 percent and 90 percent of youths who worked at
a given age worked again at the next age. Thus, those who
start young will likely continue to work at least part of the
year until age 20. Second, after controlling for standard
background variables (race, sex, income, family structure,
parents’ education, and AFQT score) working at freelance
jobs at young ages is correlated with a number of negative
outcomes. Those who worked at freelance jobs before age
15 achieved less schooling by age 20; smoked, drank alcohol, and used marijuana more often before age 16; and
were more likely to carry a handgun, assault someone, or
be arrested by age 18 than youths who waited until age 16
for their first job. Gladden and Pierret are quick to point
out that this may be largely an effect of selection—those
who are likely to work at a young age may also be the type
to want less schooling and to engage in substance abuse
and delinquent behavior, in which case the correlation
does not imply that working per se causes these behaviors.
But the link between early employment and these outcomes certainly warrants further investigation.
Access to criminal records. One of the attractive features of
the NLSY97 data set is that it captures a lot of information
that is tangentially related to employment. One of these
pieces of information is the youth’s criminal record—the
data include information on many illegal actions that
resulted in arrests, convictions, periods of incarceration,
and other run-ins with the law. Incarcerations, naturally,
influence labor market behavior, especially when youths
are incarcerated long enough to prevent them from participating in the regular labor market. The NLSY97, being
a longitudinal data set, can be used to assess the impact of
the incarceration on subsequent employment.
Keith Finlay from Tulane University, in his paper “Effect of Employer Access to Criminal History Data on
the Labor Market Outcomes of Ex-Offenders and NonOffenders,” uses the information about incarceration
and subsequent employment along with one other piece
of information—the State in which the young man or
woman resides post incarceration. He points out that over
the interval of interest for these cohorts of youths—1997
to 2003—some 16 States, starting with Florida in 1997,
adopted the practice of releasing on the Internet information from the criminal records of all convicted felons.
Finlay studies the employment experience of people who
have and have not been incarcerated, in States with and
without Internet reporting. An employer may have a notion that a job applicant of a particular type—age, sex,
race, or ethnic group, for example—is more likely to have
a criminal record. If this notion causes the employer not
to hire someone of that type, this is a phenomenon called
“statistical discrimination.” However, argues Finlay, in a
State that puts information concerning people’s criminal
records on the Internet—making it easy for employers to
determine whether a particular job candidate is a convicted felon—employers have far less reason to “statistically discriminate” against non-felons. In short, this State
policy is expected to be detrimental to the employment
prospects of people who have been incarcerated but to be
helpful to those from high-incarcerated groups who have
not themselves been jailed.
Finlay explains that there are 369 NLSY97 respondents
who have been incarcerated as adults (4.4 percent of his
whole sample). For men age 19, the cumulative rates of
adult incarceration were: 3 percent of white males, 8 percent of African-American males, 4 percent of Hispanic
Monthly Labor Review • September 2008
45
Conference Report
males, and less than 1 percent of each of the three groups
of females. For men age 24, however, the cumulative rates
of those same six groups were dramatically higher: 8
percent of white males, 19 percent of African-American
males, 12 percent of Hispanic males, and 2 percent to 3
percent of the respective groups of females.
Finlay studies the relationship between incarceration
and employment, wages, and earnings; his findings confirm his expectations: “ex-offenders are less likely to be
employed, have lower wages, and have lower earnings in
[S]tates with Internet sites providing information about
ex-offenders.” And the magnitude of this effect is considerable: in the open-records States, ex-offenders have
a 5-percentage-point lower likelihood of employment, 9
percent lower hourly wages and 19 percent lower annual
earnings. The evidence is less striking, but again affirming, for the effects of open records for non-offenders from
groups with high rates of incarceration; however, the association is not statistically significant.
Education
Educational attainment. Education is certainly a key factor in the attainment of a successful career. The NLS data
sets, with their depth of information on the educational
experiences of cohorts 20 years apart, provide excellent
data on the change in educational attainment over the
last 2 decades. James Walker of the University of Wisconsin at Madison, in his paper titled “College Choice,
Enrollment and Educational Attainment in the NLSY79
and NLSY97,” provides a detailed comparison of the two
cohorts and emphasizes some fascinating developments
in the educational attainment of individuals in the two
data sets at ages 24 or 25. He reports an increase in mean
years of schooling of 0.4 year from the 1979 cohort to the
1997 cohort; median years of schooling increased from
12 years for the 1979 cohort to 13 years for the cohort
of 1997. Somewhat surprisingly, the interquartile range
of schooling increased dramatically, from 1.5 years in the
NLSY79 to 3.5 years in the NLSY97.
Walker documents a substantial decline in the percentage of people who did not obtain a high school diploma or
pass the General Educational Development (GED) tests.
Among males, for example, this fraction dropped from
14.8 percent in the 1979 cohort to just 7.6 percent in the
1997 cohort. For women, the drop was a bit less dramatic,
from 11.8 percent in the 1979 cohort to 7.8 percent in the
1997 cohort. One can see the same pattern of improvement in education when considering those without a high
school degree—either dropouts or those with GEDs. The
46
Monthly Labor Review • September 2008
percentage of men without a high school degree declined
from 23.8 percent in the 1979 cohort to just 16.7 percent
in the 1997 cohort. For women, the gain is again somewhat muted; in the 1979 cohort, 19.7 percent of women
did not have a high school degree, but by the 1997 cohort
the figure had shrunk to 15.1 percent. This decline represents a substantial improvement in human capital across
these two cohorts.
Results at other levels of education are equally encouraging. About 20.9 percent of men in the 1979 cohort had
a bachelor’s degree, a figure that increased to 24.2 percent
in the 1997 cohort. For women, the increase was astonishing; in the 1979 cohort, 18.6 percent had a bachelor’s
degree, but by the 1997 cohort, 30.4 percent of women
had a bachelor’s degree. Thus, in the 1979 cohort, there
were 1.12 men for each woman with a bachelor’s degree,
but by the 1997 cohort, this had fallen to just 0.80 man
per woman.
This striking change reflects a difference between the
sexes in college enrollment rates—while men’s attendance
at 4-year universities increased from 34.3 percent to 42.3
percent, women’s attendance at 4-year universities increased from 30.9 percent to 47.8 percent. The graduation
rate conditional on attending 4-year universities declined
for men from 60.9 percent in the 1979 cohort to 57.2
percent in the 1997 cohort. Despite the large increase in
college attendance among women, their graduation rate
increased from 60.2 percent to 63.6 percent. Thus, in the
1997 cohort, women were more likely than men to attend
university, and those who did were more likely than men
to graduate.
African Americans, too, made considerable progress,
although the gains are much more concentrated in the
upper end of the distribution for Blacks than for Whites.
For instance, the percentage of black respondents who
did not obtain either a GED or a high school diploma
declined from 16.5 to 13.5 from the 1979 cohort to the
1997 cohort, whereas the corresponding percentage of
white respondents declined from 11.3 to 5.8. Thus, despite starting from a smaller percentage of nongraduates,
Whites experienced a greater decline in the percentage
who did not obtain either a GED or high school diploma
than did Blacks. Similarly, the percentage of black respondents without a high school degree was essentially unchanged, increasing from 25.2 in the 1979 cohort to 25.3
in the 1997 cohort. For Whites, however, that percentage
dropped from 19.0 in the 1979 cohort to 13.2 in the 1997
cohort. Progress was even more dramatic for Hispanics. In
the 1979 cohort, 36.5 percent of respondents did not have
a high school degree, but this dropped to 19.6 percent in
the 1997 cohort. Thus, in one generation, African Americans replaced Hispanic Americans as the group having the
highest fraction of youth without a high school degree.
At the other end of the distribution, however, African
Americans showed a much more substantial improvement
than did Hispanics. In the 1979 cohort, 8.5 percent of
the African American population had a bachelor’s degree
by age 25, but this percentage grew to 15.0 by the 1997
cohort. In contrast, in the 1979 cohort, 9.4 percent of Hispanics had a bachelor’s degree by age 25, but this grew
much less rapidly, to 11.7 percent in the 1997 cohort. By
comparison, the percentage of whites with a bachelor’s
degree grew from 23.9 in the 1979 cohort to 32.6 in the
later cohort.
Thus, there is a very distinctive pattern among the three
major race/ethnic groups. For Whites, education levels
have increased across the distribution, with fewer who
fail to obtain a high school degree and an ever-greater
proportion obtaining a bachelor’s degree. The 1980s and
1990s were a period of spectacular increase in the returns
to investment of schooling, and the change in the behavior of the white Americans in the cohort is generally and
properly viewed as a response to that increase in returns.
In contrast, the Hispanic Americans in the cohort exhibited a modest growth in the proportion obtaining a
bachelor’s degree but a substantial decline in the proportion without a high school degree. Thus, the distribution
of education levels among Hispanics became much more
concentrated in younger cohorts. African Americans had
a substantial expansion in the proportion with a bachelor’s
degree but virtually no change in the proportion without
a high school degree. Thus, the distribution of educational
levels among African Americans became more diffuse in
the younger cohorts. Understanding the reasons for these
three distinct changes in the distribution of educational
levels will be an important goal for future research.
Walker also reports differences in educational attainment by the respondents’ scores on the Armed Forces
Qualification Test (AFQT). He divides the respondents
into thirds (“terciles”), and reports the educational attainment of each. Here, again, the news is good: in each ability
tercile the fraction without a high school degree declined
and the fraction with a bachelor’s degree increased. Not
surprisingly, the largest drop in the proportion of people
without a high school degree was in the lowest tercile of
AFQT scores. In the 1979 cohort, 39.5 percent of the lowest ability third did not receive a high school degree, but
this fell to 35.3 percent in the 1997 cohort. Walker also
documents a large increase in the proportion of people
getting a GED in this bottom tercile: 11.3 percent did so
in the 1979 cohort, whereas 14.3 percent did so in the
1997 cohort. The largest growth in the proportion with a
bachelor’s degree occurred in the middle tercile of AFQT
scores, a rise from 18.2 percent in the 1979 cohort to 22.1
percent in the 1997 cohort.
The effects of parental resources. A similar pattern emerges
when Walker partitions the sample into terciles by parents’ income, measured in the first round for both cohorts.
From the 1979 cohort to the 1997 cohort, in each tercile
the proportion without a high school degree declined, and
the proportion with a bachelor’s degree increased. There is
one important difference in the results for parental income
compared with the results for the AFQT. The greatest gain
in the proportion obtaining a bachelor’s degree occurred
in the lowest tercile of the AFQT score distribution but in
the highest tercile of parental income. Indeed, there is a
strong monotonic relationship between income and the
percentage point gain in the proportion with a bachelor’s
degree: the highest tercile had an 11.4-percentage-point
increase, the middle tercile had a 7.8-percentage-point
increase, and the lowest tercile only had a 1.7 percentagepoint increase. Thus, the correlation between the possession of a bachelor’s degree and parental income became
even stronger in the younger cohort.
This increased correlation of educational attainment
and parental income suggests a growing importance of
parental resources in determining who can afford college.
In a paper they presented at the recent NLSY97 conference, Philippe Belley and Lance Lochner of the University of Western Ontario and Marc Frenette of Statistics
Canada reported on a preliminary investigation that is
further exploring this correlation using the NLSY97 and
a Canadian longitudinal data set.2 They expand upon a
paper that Belley and Lochner recently published in the
first issue of the Journal of Human Capital;3 in it, Belley
and Lochner use a structural model and the NLSY79 and
NLSY97 to estimate the impact of parental resources on
educational attainment. Consistent with several other
studies, Belley and Lochner find that parental income and
resources played virtually no role in the determination of
enrollment rates for the 1979 cohort. For the 1997 cohort,
however, parental resources were much more important
in determining who attended college. The paper explains
that parental income is important because students are
constrained from borrowing against their future earnings.
Thus, though it makes economic sense to attend college,
many members of the younger cohort were able to do so
only if their parents could help them financially.
Both the paper published in the Journal of Human CapMonthly Labor Review • September 2008
47
Conference Report
ital and the paper presented at the conference highlight a
potentially serious problem in American higher education.
In the years between the two cohorts, the cost of highquality university education has skyrocketed. For instance,
the Chicago Tribune has reported that the cost of sending
an in-State student to the University of Illinois at Champaign-Urbana—an elite public institution—now exceeds
$20,000 a year. Because the growth of college tuition and
fees has far outstripped the growth in federally funded
student loans, one might expect that the increased costs
would limit access to costly, elite schools. Nevertheless,
Americans face a staggering quantity of choice in higher
education with wide variation in prices. Community colleges, for example, often represent an attractive option at
a price that is an order of magnitude lower than the cost
at an elite school. These drastically lower prices, coupled
with the possibility of living at home and avoiding additional costs, could lead one to believe that capital market
constraints would not prevent aspiring college students
from attending higher education.
However, there exists evidence to the contrary. In a series of papers, Todd R. Stinebrickner of the University of
Western Ontario and Ralph Stinebrickner of Berea College examine the behavior of Berea College students. Berea
is an especially useful college to study because it charges
no tuition and provides students with a modest stipend
as payment for a campus job. The policy is intended to
assure that no students are excluded from Berea because
they cannot afford the tuition bill. Yet, Stinebrickner and
Stinebrickner find that despite the free tuition and limited
direct cost of attending Berea, family income is still critically important for graduation.4 The reason seems to be
that there are many events and circumstances—a parent’s
illness or unemployment, for example—that may make
it difficult for students to complete their college studies.
Students from wealthier families have a larger number of
options available to address these difficulties. Understanding the roles of capital markets and family resources in
accessing and completing college is an important research
agenda for the future.
Obesity. A topic that has been a focus of much research
in health economics is the direction of causality in the
strong link between health and schooling. Some researchers suggest that schooling affects health, others suggest
that health affects schooling, and still others suggest that
there are other factors— third forces—that influence both
in the same direction, causing the observed positive association. One of the authors of a paper at the recent NLSY97
conference, Michael Grossman of the City University of
48
Monthly Labor Review • September 2008
New York Graduate Center, has been the primary scholar
in this debate over the past several decades; the paper he
and his colleague, Robert Kaestner of the University of
Illinois at Chicago, presented at the conference addresses
one small piece of this puzzle.5
Kaestner and Grossman note that adolescent obesity has risen dramatically in recent years, and they ask
whether obesity has an effect on educational attainment
among adolescents. If it does, that would be one avenue
through which health status influences the level of education. Kaestner and Grossman point out that a relationship
between obesity and educational attainment could work
in several ways logically, and economic theory alone does
not shed much light on which of several potential routes
of influence might dominate. Obese adolescents might
suffer from discrimination from teachers and/or peers
that could adversely affect their schooling, and they might
also have related health troubles such as sleeping disorders
and depression that could adversely affect their cognitive
functioning or cause them to miss days of school. Conversely, overweight youths might engage less in sports and
physical activities and even in social activities, and as a
result they may spend more, not less, time studying and
thus perform better academically. Kaestner and Grossman
turn to the NLSY97 data for evidence.
This is a case in which a negative finding is noteworthy.
After undertaking a quite thorough study, with sophisticated formal theoretical modeling and statistical analyses,
the researchers conclude that there is very little evidence
in the NLSY97 data that obesity has any discernible effect on the educational attainment of these young adults,
either positive or negative. They study boys and girls separately, looking at the extreme tails of the distribution of
weight and noting the highest grade of school attended,
the highest grade completed, and whether or not the student dropped out of school. In neither estimates from very
simple models nor in Kaestner and Grossman’s estimates
from quite complex and highly controlled models is there
evidence of an effect of weight on schooling. Obesity, they
conclude, does not play a direct role in the strong, positive
association between health and schooling.
Social Behaviors
Although a primary motivation for the NLS program is
a better understanding of the labor market experiences
of the workforce, BLS has understood the importance of
investigating a wide range of other behaviors, both within
the family and in the community, as forces that affect
employment, marketable skills, occupation choices and
opportunities, and career trajectories, as well as hours of
work, wages, and earnings. The NLS data sets have long
been used for studying many types of youth and adult behaviors, and the recent conference suggests that the most
recent NLSY97 data have much to contribute to our understanding of family and youth behaviors.
Marriage and offspring. Robert Michael of the University
of Chicago, in remarks that opened the conference, pointed
to both the continuity and change in demographic trends
between the 1979 and 1997 cohorts. The most dramatic
trend, he claimed, is found in terms of formal marriage:
8.7 percent of 18-year-old females in the 1979 cohort had
married, whereas only 1.6 percent of their counterparts in
the 1997 cohort had done so. By age 21 the trend was even
more striking, with 33.4 percent of the females from the
1979 cohort married but only 12.1 percent from the 1997
cohort married. Similarly, 15.1 percent of 21-year-old
men from the 1979 cohort were married, compared with
5.2 percent from the 1997 cohort. Although these figures
reflect the well-documented decline in formal marriage in
the United States, if instead one considers the percentage
of the 1997 cohort who have formed a dyadic partnership,
the numbers look much like the 1979 numbers for formal
marriages: 33.1 percent of the females reported having
formed a cohabitational partnership, and 19.1 percent of
the males reported having done so. The big decline is in
formal marriage, not in forming a dyadic partnership.
Concerning the percentage of young mothers, there
was essentially no difference between the 1979 and 1997
cohorts—7.8 percent of women in the 1979 cohort had a
child by age 18, compared with 7.6 percent of the 1997
cohort. The difference between cohorts in the percentage
of those who were mothers by age 21 is also small; 23.2
percent of the NLSY79 met the criteria, compared with
23.8 percent of the NLSY97. For the males, there was a
slight increase in reported parentage at age 18, with 1.3
percent of the 1979 cohort having at least one child at
age 18, compared with 2.3 percent of the 1997 cohort.
By age 21, 8.6 percent of the males from the 1979 cohort
reported being a father, compared with 11.2 percent of the
males in the 1997 cohort.
Adolescent sexual activity. Researchers from Child
Trends, a Washington, DC, think tank that focuses on
issues of child development and policy, investigated the
risky behavior of adolescent sexual activity and the role
that parents play in affecting this behavior.6 Kristin Moore
and Kassim Mbwana examined whether the youths who
were 12–14 at the beginning of the survey began having
sex before age 17 (53 percent did so), whether they used
contraceptives or engaged in “unsafe sex” when they did
have sex (16 percent were judged to have had unsafe sex
in the 12 months before age 17), whether those who were
sexually active had multiple partners by the time they
turned 17 (some 44 percent had two or more partners),
and whether or not they had become teenage parents before turning 18 (6 percent did so). This study examined
three aspects of how the teenagers’ parents’ styles of supervision, guidance, and support affected these elements of
the youths’ sexual behavior. First, the authors investigated
the influences of different parenting styles on sexual risktaking by adolescents. Second, the researchers examined
whether the influence of parenting style varied depending
upon the risks that the adolescent faced. Finally, Moore
and Mbwana examined whether parental awareness of
children’s activities prevented the children from engaging
in sexual activity.
The NLSY97 data have considerable detail regarding
how parents guide and monitor their children’s social and
private lives. One set of measures used in this study—measures that are well-explored by developmental psychologists and believed to be influential in the development of
preschool and elementary school children—characterizes
parental styles into a four-category typology: some parents are “authoritative” (which means they are rather strict,
yet highly supportive, of their adolescent children), others
are “permissive” (which means they are not strict, but are
quite supportive), others are “uninvolved” (meaning they
are neither strict with their children nor supportive), while
still others are “authoritarian” (meaning they are strict, but
not supportive). Moore and Mbwana’s study borrows this
typology and uses it to analyze the influence of parenting
styles on the sexual behaviors of adolescents. In particular,
the study focuses on the influence of an “authoritative”
(strict but supportive) style of parenting.
The findings at this stage in the investigation are robust ones: holding constant many of the known factors
that affect adolescent behaviors, authoritative parenting
was clearly associated with less sexual risk taking by girls,
specifically through later initiation of sex, less unsafe sex,
fewer sex partners, and lower rates of teenage parenting.
For boys, the effects were not as strong, but where the
effects were in evidence—in the age of onset of sexual activity—more authoritative parenting was associated with
a delay in the age at first sex.
Greater levels of risky sexual activity occurring among
adolescents’ peers, in their schools, and in their neighborhoods were also associated with a higher probability of
early sex, unsafe sex, more partners, and teen parenthood;
Monthly Labor Review • September 2008
49
Conference Report
however, little evidence was found that the importance
of parenting varies by risk level. These studies concerning parenting styles control for several important factors
that also influence this behavior. For example, adolescents
who live with both their biological parents engage in less
sexual risk taking, those whose mothers were themselves
teenage parents exhibit more risky sexual behaviors, and
those who grew up in an impoverished family take more
sexual risks.
The last issue that the Moore and Mbwana paper explores is the influence of parental awareness of adolescents’ activities, as measured by how well the parents know
their child’s close friends, how well they know those close
friends’ parents, whether they know with whom their
child spends time when he or she is not at home, and
how well they know their child’s teachers. The findings
suggest that parental awareness results in both boys and
girls delaying sexual activity, engaging in less unsafe sex,
and being less likely to have multiple sexual partners. The
study concludes that “[p]arents matter for all adolescents”
in this important arena of sexual risk taking.
The influence of siblings. Another paper presented at the
conference also looks within the family at factors that appear to be associated with risky behaviors, but this one
focuses on the influence of siblings instead of parenting
styles.7 Joseph Altonji of Yale, Sarah Cattan of the University of Chicago, and Iain Ware of 3iGroup point out
that several studies have found substantial correlations
in risky behavior between siblings, raising the possibility
that adolescents may directly influence the actions of their
brothers or sisters. The researchers note that there is an
insightful body of literature in psychology that suggests
that such sibling effects may exist, particularly for younger
children who look to their older siblings for cues about
appropriate teenage behaviors. The authors note, however,
that much of the published empirical analyses of sibling
effects are compromised by the difficulty of distinguishing
direct influences from the impact of shared unobserved
factors. Multivariate regressions relating the behavior
of siblings undoubtedly reflect the fact that a variety of
common influences affect the actions of all siblings in
a household, so the fact that siblings behave similarly
does not necessarily imply that one child affects his or
her brother or sister. Altonji, Cattan, and Ware look at a
wide range of risky activities from the NLSY97 data set
and find strong positive sibling correlations. The primary
contribution of the paper is their assessment of the extent
to which these correlations are due to causal effects from
one sibling to another.
50
Monthly Labor Review • September 2008
The researchers articulate a sibling model of consumer
choice that serves as a basis for their econometric identification strategy. It is based on the fact that the behavior of
a child at a given point in time cannot directly influence
a sibling’s actions in a prior year. The authors also assume
that the direction of any influence is from an older sibling
to a younger sibling. They estimate a joint dynamic model
of the behavior of older and younger siblings that allows
for family effects, individual specific heterogeneity, and
past choices. Their results suggest that smoking, drinking,
and marijuana use are influenced by the example of older
siblings, although much of the link between siblings reflects association rather than causation.
Running away from home. One of the more unusual topics explored at the recent conference addressed the issue
of adolescents running away from home.8 In his paper,
Michael Pergamit of the Urban Institute explains what
the published literature reveals about runaways. He states
that nearly all the available information regarding this
phenomenon comes from samples of youths in homeless
shelters, in crisis centers, or living on the street; these data
sources, unfortunately, do not permit analysts to compare
youths who have run away with those who have not. For
example, one cannot investigate the prevalence of running
away using data of that nature, nor can one track how
runaways and youths who have never run away differ in
their developmental pathways prior to or after running
away. Moreover, the information about the family and
schooling experiences prior to running away are, in the
shelter samples, necessarily collected after the running
away episode and may thereby be tainted or shaded by the
experience itself.
The NLSY97 annually asked the youths if they had ever
run away from home. The survey used the definition supplied by the Department of Justice, that running away
is “staying away at least one night without parents’ prior
knowledge or permission.” Each year, as long as the youth
was residing with parents and was under age 18, he or she
was asked about incidents of running away occurring since
the previous interview; consequently, this study captures a
sample of runaways that reflects the whole set of children
who ran away, not just those who ended up in shelters or
crisis centers. In some cases, the data also include key information about the youth from years prior to episodes of running away. The paper exploits these features of the NLSY97
data, focusing primarily on children who were age 12 or 13
in the first year of the study.
The prevalence of running away is itself one of the most
interesting findings in this paper, which estimates that of
the roughly 20 million U.S. youths born between 1980
and 1984, some 17.8 percent had run away by the age of
18. The rate is higher for females—19.8 percent—than for
males—15.8 percent. It is also slightly higher for Hispanic
youths than for Whites or African Americans: 19.4 percent
of Hispanics and 17.4 percent of both Whites and African
Americans had run away by age 18. Of all children who had
run away, about half had done so only once, but approximately 10 percent had done so seven or more times; of the
youths who reported incidents of running away, the average number of these incidents was 3.3. About one-third of
children who ran away had done so before age 14.
In a statistical model that identified which adolescents
had run away from home while controlling for several attributes, it is interesting that the sex of the adolescents
was not a factor. As if to illustrate the challenge of summarizing findings from complex studies, however, the
paper notes that boys who did run away did so less often
than girls but that boys did so at a younger age than girls.
African Americans and Hispanics were both less likely to
run away than were Whites after statistical controls were
introduced. Similarly, having siblings had no apparent effect on running away. Children with higher scores on the
AFQT were less likely to run away, while, as one might
expect, youths who had a poor relationship with parents,
who scored high on measures of behavioral problems, or
who had mental health problems were significantly more
likely to run away. Urban youths were much more likely to
run away than youths in rural settings. The study also finds
that “the more things the family does together the lower
is the probability of running away.” The author notes that
it will be important to track the effects of running away
on the life trajectories of these young men and women
as they age through their 20s and beyond. This is surely
one of the key benefits of a data set like the NLSY97 that
identifies behaviors and events early in life and can then
reveal whether that behavior is associated with later life
events, and, if so, to what extent.
THE FINDINGS BRIEFLY SUMMARIZED IN THIS ARTICLE represent about half the research papers delivered at
the Tenth Anniversary Conference in May 2008. In turn,
the papers presented at the conference reflect only a small
portion of the new facts and relationships discovered so far
by researchers working with the NLSY97 data sets. Assuming the survey respondents continue to be willing to accept
the request for an hour-long interview each year, as their
lives unfold over the next decade or so, researchers’ understanding of the U.S. labor market and the behavior of the
cohort born between 1980 and 1984 will continue to grow.
The ever-improving understanding of the forces shaping
labor market experiences should help policymakers, and
the deeper understanding of the consequences of private
decisions should be of value to families everywhere.
Notes
ACKNOWLEDGMENT:
The authors thank Rupa Datta and Donna Rothstein for contributions to this summary paper.
dence from a Liberal Arts College with a Full Tuition Subsidy Program,” Journal of Human Resources, Summer 2003, pp. 591–617.
The NLSY97 Tenth Anniversary Conference, held in 2008 at the
Bureau of Labor Statistics in Washington, DC, May 29–30, was supported by grants from the Spencer Foundation, the NORC Population
Research Center, and the Harris School’s Center for Human Potential
and Public Policy.
Robert Kaestner and Michael Grossman, “Effects of Weight on
Adolescent Educational Attainment.” Paper presented at the NLSY97
Tenth Anniversary Conference, Washington, DC, May 2008.
1
Philippe Belley, Marc Frenette, and Lance Lochner, “Post-Secondary Attendance by Parental Income: A Canada-U.S. Comparison.”
Paper presented at the NLSY97 Tenth Anniversary Conference, Washington, DC, May 2008.
2
Phillipe Belley and Lance Lochner, “The Changing Role of Family Income and Ability in Determining Educational Achievement,”
Journal of Human Capital, Winter 2007, pp. 37–90.
3
Ralph Stinebrickner and Todd R. Stinebrickner, “Understanding
Educational Outcomes of Students from Low-Income Families: Evi4
5
Kristin Moore and Kassim Mbwana, “Preventing Risky Sex and
Adolescent Parenthood: Does the Effectiveness of Parenting Practices
Differ For Children with Varied Risks?” Paper presented at the NLSY97
Tenth Anniversary Conference, Washington, DC, May 2008.
6
7
Joseph G. Altonji, Sarah Cattan and Iain Ware, “Sibling Influences on Teenage Risky Behaviors.” Paper presented at the NLSY97 Tenth
Anniversary Conference, Washington, DC, May 2008.
Michael R. Pergamit, “Who Runs Away from Home? An Exploratory Analysis.” Paper presented at the NLSY97 Tenth Anniversary
Conference, Washington, DC, May 2008.
8
Monthly Labor Review • September 2008
51
Regional Trends
Multiple Jobholding in
States in 2007
Jim Campbell
I
n 2007, 26 States and the District
of Columbia experienced decreases in their multiple jobholding rates
from 2006, 20 States recorded increases, and 4 States had no change.1
The national multiple jobholding
rate was unchanged in 2007, at 5.2
percent. The largest over-the-year
rate decreases among the States were
Jim Campbell is an economist in the Division of
Local Area Unemployment Statistics, Bureau of
Labor Statistics. E-mail: Campbell.Jim@bls.gov
posted in Idaho (–1.8 percentage
points), Alaska (–1.6 points), and
Wyoming (–1.3 points). Kansas experienced the largest increase among
the States (+1.4 percentage points),
followed by Kentucky (+0.8 point)
and West Virginia (+0.7 point).
Although the U.S. multiple jobholding rate was the same as in 2006,
it was 1.0 percentage point lower
than in 1996, when it peaked at 6.2
percent.2 Compared with 1996, 44
States and the District of Columbia
had lower multiple jobholding rates
in 2007, and only 6 States had higher
rates. The largest declines over this
period occurred in Idaho (–3.0 per-
centage points), Indiana and Missouri
(–2.8 points each), and Arkansas (–2.6
points). Over the 1996–2007 period,
only one State had an increase in its
multiple jobholding rate that was
greater than 0.4 percentage point:
Vermont (+0.8 point).
The multiple jobholding rates for
individual States varied considerably
from the U.S. average. (See chart 1.)
Overall, 28 States had higher multiple jobholding rates than the national
average, 20 States and the District
of Columbia had lower rates, and 2
States had the same rate. Northern
States generally had higher rates than
southern States.
Table 1. Multiple jobholders as a percentage of total employment by State, 2006 and 2007 annual averages
State/area
2006
United States..............................................
5.2
Alabama.......................................................
4.5
Alaska............................................................
2007
State/area
2006
2007
5.2 Missouri..............................................
6.7
6.2
4.7 Montana.............................................
8.1
8.0
9.0
7.4 Nebraska............................................
9.9
9.7
Arizona..........................................................
4.7
4.5 Nevada................................................
4.0
3.8
Arkansas.......................................................
5.4
4.5 New Hampshire...............................
7.3
6.9
California......................................................
4.2
4.4 New Jersey.........................................
4.9
4.6
Colorado.......................................................
5.8
6.0 New Mexico.......................................
5.3
5.0
Connecticut.................................................
5.9
6.3 New York............................................
4.5
4.2
Delaware......................................................
4.4
4.4 North Carolina..................................
5.3
5.3
District of Columbia.................................
5.4
4.6 North Dakota....................................
8.4
8.7
Florida...........................................................
3.9
3.9 Ohio.....................................................
6.4
6.3
Georgia.........................................................
3.5
4.1 Oklahoma..........................................
4.7
4.4
Hawaii............................................................
8.0
8.2 Oregon................................................
6.3
5.7
52
Idaho..............................................................
8.3
6.5 Pennsylvania.....................................
5.5
5.3
Illinois............................................................
4.9
5.2 Rhode Island.....................................
6.9
6.6
Indiana..........................................................
4.3
4.7 South Carolina..................................
4.5
4.9
Iowa................................................................
8.9
8.8 South Dakota....................................
9.9
10.2
Kansas...........................................................
7.5
8.9 Tennessee..........................................
5.1
4.5
Kentucky.......................................................
5.6
6.4 Texas....................................................
4.3
4.5
Louisiana......................................................
4.5
4.4 Utah.....................................................
7.5
6.9
Maine.............................................................
8.2
8.1 Vermont..............................................
9.3
9.4
Maryland......................................................
5.5
5.9 Virginia................................................
4.9
4.8
Massachusetts............................................
5.6
5.2 Washington.......................................
5.7
5.9
Michigan......................................................
5.6
5.7 West Virginia.....................................
3.5
4.2
Minnesota....................................................
8.7
8.7 Wisconsin...........................................
7.7
7.5
Mississippi....................................................
4.1
4.7 Wyoming............................................
9.3
8.0
Monthly Labor Review • September 2008
Chart 1. Multiple jobholding rates by State, 2007 annual averages
(U.S. rate = 5.2 percent)
Mountain
West
North Central
East
North Central
New England
Middle
Atlantic
#
#
#
#
#
D.C.
Pacific
South
Atlantic
East
South Central
West
South Central
7.6 percent or more
5.6 to 7.5 percent
4.6 to 5.5 percent
4.5 percent or below
SOURCE: Current Population Survey.
All seven States in the West North
Central division continued to register
multiple jobholding rates above that
of the Nation. The northern States
in the Mountain and New England
divisions also continued to have relatively high rates. South Dakota recorded the highest rate, 10.2 percent,
followed by Nebraska and Vermont,
at 9.7 and 9.4 percent, respectively.
Many of the upper Plains States
with high multiple jobholding rates
also have high shares of agricultural
and part-time employment. In addition, multiple jobholding seems
generally to be highest in States that
have low average commuting times.3
Most of the States with high multiple jobholding rates in 2007 have
had consistently high rates over the
1996–2007 period.
Thirteen of the 16 States in the South
region, as well as the District of Columbia, had multiple jobholding rates below
the U.S. figure.4 Among the 9 States
with rates below 4.5 percent, 6 were in
the South. Nevada recorded the lowest
multiple jobholding rate in 2007, 3.8
percent, followed by Florida, at 3.9 percent, and Georgia, at 4.1 percent.
Notes
1
Data on multiple jobholders are from the Current Population Survey (CPS), a survey of about
60,000 households selected to represent the U.S.
civilian noninstitutional population aged 16 years
and older. The CPS is conducted monthly by the U.S.
Census Bureau for the Bureau of Labor Statistics.
Multiple jobholders are those who report in the
reference week that they are wage or salary workers
who hold two or more jobs, self-employed workers
who also hold a wage or salary job, or unpaid family
workers who also hold a wage or salary job.
2
Annual multiple jobholding data for States became available following the redesign of the Current
Population Survey in 1994.
3
Average commute times are from the 2000
Census of Population and Housing.
4
The South region is composed of the East
South Central, South Atlantic, and West South
Central divisions.
Monthly Labor Review • September 2008
53
Précis
Procrastination: an
economic analysis
Most people are quite familiar with
procrastination—a tendency that affects the way they complete (or do
not complete) projects in the workplace, in school, at home, and elsewhere. A conventional explanation
for procrastination is that people act
rationally, choosing to postpone tasks
because they find it difficult to muster the self-discipline to begin them
earlier. In “An Economic Model of
the Planning Fallacy” (NBER Working Paper Series, National Bureau of
Economic Research, August 2008),
Markus K. Brunnermeier, Filippos
Papakonstantinou, and Jonathan A.
Parker use advanced mathematics,
along with data from experiments, to
argue in favor of an alternative theory.
They contend that the only cause of
procrastination is people’s tendency
to underestimate the amount of time
needed to complete a project.
Various studies—in both laboratory and nonlaboratory settings—have
demonstrated that when given an
unpleasant task, the average person
takes much longer to complete it than
he or she predicted before beginning
the task. The paper’s authors call the
faulty reasoning behind this behavior
“the planning fallacy.” Because of the
planning fallacy, people often spend
a disproportionately large amount
of time working on projects close
to the deadline. The authors explain
that people do this because the utility derived from the felicitous belief
that a project will be easy to complete
outweighs the cost of not properly
“smoothing” work over time. The researchers believe that, subconsciously,
people actually do realize about how
long most projects take; yet, when
faced with a new project, they still
consciously believe that the project
will take less time.
54
Monthly Labor Review • September 2008
When people are asked to complete a simple, non-onerous task in
an experiment, they actually tend
to complete the task slightly more
quickly than they predicted beforehand. However, when people are
paid on the basis of how quickly they
complete either a non-onerous or a
burdensome task, they tend to underestimate the amount of time necessary to finish it. By contrast, financial
incentives for accurate prediction can
eliminate the planning fallacy.
Brunnermeier, Papakonstantinou,
and Parker argue that the results of
the aforementioned experiments bolster their view that procrastination
is based on the planning fallacy. The
greater the anticipatory benefit to believing that the project will take little
time, the stronger is the tendency to
underestimate the amount of time
necessary to complete it. Nevertheless, most people are aware of their
penchant for postponing work; consequently, they often set intermediate
deadlines in an effort to mitigate their
procrastination.
U.S. economy as a very large business.
This fictional business employs all
of the workers in the U.S. economy,
owns all of the capital, and returns
all of its profits to its “shareholders,”
the U.S. public. Campbell presents
tools for evaluating the contributions of particular product lines to
U.S. economic growth and the effect
they have on the business cycle. He
extends his analysis by using the same
tools to measure a large firm’s exposure to macroeconomic risks.
Campbell employs two macroeconomic concepts to assess the contributions to overall economic growth
made by particular sectors, as well as
the sustainability of that growth: the
fundamental national product accounting identity, which divides the total
value of goods and services produced
by the economy into discrete expenditure components, and the contributions to growth formula, which equates
the rate of GDP growth with the sum
of the individual component growth
rates multiplied by their share of expenditures in the previous quarter.
When he applies these concepts
to the U.S. economy, Campbell finds
Business cycle analysis
that macroeconomic risks are largely
Policymakers and business managers the result of periodic fluctuations
alike must regularly face the chal- in nonresidential fixed investment,
lenge presented by the recurrent cy- which accounts for a substantial
clical fluctuations in the U.S. econo- portion of overall economic activmy. Understanding the business cycle ity. (Nonresidential fixed investis crucial to both: policymakers must ment consists of purchases by firms
make decisions about monetary and of nonresidential structures, equipfiscal policy in an effort to smooth ment, and software.) Expenditures
out the cycles, while profit-maximiz- on nondurable goods and services,
ing managers must make informed which represent a very large portion
decisions about their individual firms of national income, fluctuate little
during the various stages of the busi- from quarter to quarter and thus
ness cycle. In “How the U.S. economy contribute only marginally to macresembles a (very) big business” (Eco- roeconomic risks.
nomic Perspectives, Federal Reserve
Campbell suggests that his methBank of Chicago, third quarter 2008), odology might be used by others to
senior Bank economist Jeffrey R. set macroeconomic benchmarks and
Campbell analyzes the fluctuations in “start a conversation about a business’s
U.S. economic growth by treating the place in the larger economy.”
Book Reviews
Employment and
America’s future
A Future of Good Jobs? America’s
Challenge in the Global Economy.
By Timothy J. Bartik and Susan N.
Houseman, Kalamazoo, MI, Upjohn
Institute for Employment Research,
2008, 327 pp., $20.00/paperback;
$40.00/cloth.
The papers in this volume were prepared by editors Timothy J. Bartik
and Susan N. Houseman for a conference held in June 2007, in honor
of the 75th anniversary of the W.E.
Upjohn Unemployment Trustee
Corporation. In the 15 months between the conference and the writing
of this review, the state of the U.S.
economy has worsened. Although
the need to address the labor market and related problems identified
in this excellent collection of papers
is even greater now than when they
were written, macroeconomic conditions make it more difficult to do so.
It is as if able diagnosticians supplied
the prognosis for a patient with several interacting chronic conditions,
only to have the patient come down
with the flu. The suggested treatment plan may have to be postponed
or modified until the temporary ailment is over.
Chapter 1 provides a clear synthesis of the topics discussed by the
authors of the remaining six chapters: Robert J. Lerman on education and training; Katherine Swartz
on health care financing; Lori G.
Kletzer on trade and immigration;
Katharine G. Abraham and Susan
N. Houseman on labor market issues
for older workers; Paul Osterman on
demand-side policies aiding lowerskill workers; and Steven Raphael
on problems and policies relating
to disadvantaged workers in general
and former convicts in particular. The
analysis and policy proposals focus
on problems facing workers in the
lower 4/5 of the income distribution.
The net impact of economic change
in recent decades is manifested in
growing income inequality, but the
way in which inequality has grown
has intensified the problem. Over
the quarter century from 1980 to the
mid-2000s, real wages have declined
for the bottom 10th percentile of the
wage distribution, and increased by
less than 20 percent for the group between the 10th and 80th percentiles.
Presumably coincidentally, the
chapters divide into two groups by
authors’ gender. The three by the
male authors concentrate on problems faced by workers with lower
levels of skill and education, whereas
those written by the female authors
are about issues that affect most of
the population and workforce. This is
not to imply that the former group is
dealing with less important problems;
rather, that those issues with broader
impact may receive greater policy
attention and political support than
those affecting a smaller segment of
the population.
Nearly 20 years ago, Gary Burtless
edited a collection of papers on the
plight of the unskilled, especially unskilled men, titled A Future of Lousy
Jobs? (See Burtless, Gary, ed. A Future
of Lousy Jobs? The Changing Structure
of U.S. Wages, The Brookings Institution, Washington, DC 1990.) According to Burtless:
“If the demand for unskilled labor has
dropped, the obvious policy response
is to improve the qualifications of less
skilled workers to match the developing requirements of the job market. If
the [N]ation has too many unskilled
workers, rather than too many bad
jobs, both efficiency and equity will
be served by improving the skills of
workers now lodged at the bottom.”
In addition to the play on that
title, the current book’s most direct
link with the earlier work is in the
chapters by Lerman, Osterman and
Raphael. The “Lousy Jobs” analysis
attributed the declining economic
fortunes of less skilled men to their
excess supply, combined with greater
demand for more skilled workers,
when firms and industries changed
the skill mix of their labor inputs to
meet the needs of the new technologies. There are simply not enough
jobs for the less skilled, and, according to Burtless, the remedy is to upgrade the education and training of
those at the bottom of the economic
ladder.
The three authors just mentioned
are generally in accord with this diagnosis for the less skilled worker in the
contemporary labor market. Rapid
technological change and increased
globalization, plus the declining
impact of institutional protections
such as unions, make the outlook
for less-skilled workers even bleaker
today than it was in the early 1990s.
Lerman’s prescription includes developing educational approaches
that raise and better reward noncognitive and occupational skills that
are in short supply. This will require
changes in emphasis within the educational sector, favoring work-based
learning, which means a need for further investment by employers in the
skills of workers. Osterman also calls
for enhanced programs to encourage
job upgrading in skills and pay; he
sees the need as well for workers to
have restored institutional safeguards,
Monthly Labor Review • September 2008 55
Book Reviews
such as increased minimum wages
and acceptance of unions, which will
complement the incentives provided
to employers to promote upgrading.
Raphael recommends helping lowwage workers directly by expanding
the Earned Income Tax Credit (EITC)
to bring in childless adults, especially
low-income married couples. He also
points to the often neglected subsector of the low-wage, low-skill population and the growing number of
individuals with prison records, and
advocates specific policies to reduce
the barriers they face to obtaining
productive, legal jobs.
Katherine Swartz is concerned
with reforming how the United
States finances health insurance in
the face of declining percentages
of workers (and retirees) presently
covered by employer-based plans.
The three principles of her proposed
strategy are:
1. Everyone should be enrolled in
a health insurance plan for which
they pay some minimum amount;
2. Additional premiums paid by
individuals and families should be
in proportion to their income; and
3. Contributions (taxes) should be
collected from employers.
Swartz argues that such a comprehensive cost-sharing plan should not
be more expensive than the present
system of spotty coverage that emphasizes cost-shifting and contains
56
Monthly Labor Review • September 2008
perverse incentives for both workers
and employers.
The remaining two chapters focus
on the problems facing workers who
are dislocated or need to find new jobs
for other reasons. Two of the initiating factors analyzed by Lori Kletzer
are increasing trade and immigration.
Jobs may disappear due to import
competition or outsourcing, while
increased inflows of foreign-born
workers augment the labor supply at
both the low skill and high skill ends
of the labor market. The consensus
among economists is that, although
there is a net social gain from trade
and immigration, those who experience losses are concentrated among
the less skilled native-born population, worsening their income and
employment prospects. Kletzer notes,
however, that the largest and most
comprehensive adjustment assistance
program (Unemployment Insurance
or UI), needs to be changed to reflect
the new economic realities. Other
programs are neither large enough
nor appropriately targeted to offset
the gaps in the present UI system.
Katharine G. Abraham and Susan
N. Houseman address a problem that
is caused by a major social success;
more of us are living longer, healthier
lives. The challenge is how to maintain living standards during these
“golden years.” One response to this
need to make savings and income last
longer is for older workers to stay in,
or return to, the labor market for more
years than they perhaps had hoped.
Less certain pension and health care
coverage from employers, and changes to Social Security and Medicare,
both favor a trend by Americans to
work more hours and retire later.
However, this pressure runs up
against the existence of impediments
to older worker employment, on both
the supply and demand sides. Funding for employment and training
programs targeted on older workers
is substantially below levels of a decade ago in real terms, without taking
into account the increased universe
of eligibility. Program implementation can be sharpened to better meet
the needs of older workers but issues
such as health insurance, which may
act as a disincentive to employers for
hiring older workers, also have to be
addressed in a broader context.
As these authors individually and
collectively realize, there is no onesize-fits-all solution to lowering the
barriers to good jobs faced by people
in various situations. The policy proposals they suggest range from incremental changes in program performance standards to a comprehensive
reworking of our health care financing system. But they do all have the
common goal of working toward a
more equitable society, for which the
authors should be applauded.
—Stephen E. Baldwin
Economist
Bethesda, MD
Current Labor Statistics
Monthly Labor Review
September 2008
NOTE: Many of the statistics in the
following pages were subsequently
revised. These pages have not been
updated to reflect the revisions.
To obtain BLS data that reflect all revisions, see
http://www.bls.gov/data/home.htm
For the latest set of "Current Labor Statistics,"
see http://www.bls.gov/opub/mlr/curlabst.htm
Current Labor Statistics
Notes on current labor statistics . ..............
58
Comparative indicators
1. Labor market indicators..................................................... 70
2. Annual and quarterly percent changes in
compensation, prices, and productivity........................... 71
3. Alternative measures of wages and
compensation changes.................................................... 71
Labor force data
4. Employment status of 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 State, seasonally adjusted.............
11. Employment of workers by State,
seasonally adjusted..........................................................
12. Employment of 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 of 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........................................................
72
73
74
74
Labor compensation and collective
bargaining data
30.
31.
32.
33.
Employment Cost Index, compensation .......................... 99
Employment Cost Index, wages and salaries .................... 101
Employment Cost Index, benefits, private industry .......... 103
Employment Cost Index, private industry workers,
by bargaining status, and region..................................... 104
34. National Compensation Survey, retirement benefits,
private industry ............................................................. 105
35. National Compensation Survey, health insurance,
private industry............................................................... 108
36. National Compensation Survey, selected benefits,
private industry.............................................................. 110
37. Work stoppages involving 1,000 workers or more............. 110
Price data
81
82
83
38. Consumer Price Index: U.S. city average, by expenditure
category and commodity and service groups.................. 111
39. Consumer Price Index: U.S. city average and
local data, all items ........................................................ 114
40. Annual data: Consumer Price Index, all items
and major groups........................................................... 115
41. Producer Price Indexes by stage of processing................... 116
42. Producer Price Indexes for the net output of major
industry groups.............................................................. 117
43. Annual data: Producer Price Indexes
by stage of processing..................................................... 118
44. U.S. export price indexes by end-use category................... 118
45. U.S. import price indexes by end-use category................... 119
46. U.S. international price indexes for selected
categories of services...................................................... 119
84
Productivity data
85
47. Indexes of productivity, hourly compensation,
and unit costs, data seasonally adjusted.......................... 120
48. Annual indexes of multifactor productivity........................ 121
49. Annual indexes of productivity, hourly compensation,
unit costs, and prices...................................................... 122
50. Annual indexes of output per hour for select industries..... 123
75
75
76
76
77
80
85
86
86
22. Quarterly Census of Employment and Wages,
10 largest counties . ....................................................... 87
23. Quarterly Census of Employment and Wages, by State... 89
24. Annual data: Quarterly Census of Employment
and Wages, by ownership............................................... 90
25. Annual data: Quarterly Census of Employment and Wages,
establishment size and employment, by supersector....... 91
26. Annual data: Quarterly Census of Employment and
Wages, by metropolitan area ......................................... 92
27. Annual data: Employment status of the population.......... 97
28. Annual data: Employment levels by industry ................. 97
29. Annual data: Average hours and earnings level,
by industry..................................................................... 98
International comparisons data
51. Unemployment rates in 10 countries,
seasonally adjusted......................................................... 127
52. Annual data: Employment status of the civilian
working-age population, 10 countries........................... 128
53. Annual indexes of productivity and related measures,
16 economies................................................................ 129
Injury and Illness data
54. Annual data: Occupational injury and illness..................... 131
55. Fatal occupational injuries by event or exposure ................ 133
Monthly Labor Review • September 2008 57
Notes on Current Labor Statistics
Current Labor Statistics
This section of the Review presents the
principal statistical series collected and
calculated by the Bureau of Labor Statistics:
series on labor force; employment; unemployment; labor compensation; consumer,
producer, and international prices; productivity; international comparisons; and injury
and illness statistics. In the notes that follow,
the data in each group of tables are briefly
described; key definitions are given; notes
on the data are set forth; and sources of additional information are cited.
General notes
The following notes apply to several tables
in this section:
Seasonal adjustment. Certain monthly
and quarterly data are adjusted to eliminate
the effect on the data of such factors as climatic conditions, industry production schedules, opening and closing of schools, holiday
buying periods, and vacation practices, which
might prevent short-term evaluation of the
statistical series. Tables containing data that
have been adjusted are identified as “seasonally adjusted.” (All other data are not seasonally adjusted.) Seasonal effects are estimated
on the basis of current and past experiences.
When new seasonal factors are computed
each year, revisions may affect seasonally
adjusted data for several preceding years.
Seasonally adjusted data appear in tables
1–14, 17–21, 48, and 52. Seasonally adjusted
labor force data in tables 1 and 4–9 and seasonally adjusted establishment survey data
shown in tables 1, 12–14, and 17 are revised
in the March 2007 Review. A brief explanation of the seasonal adjustment methodology
appears in “Notes on the data.”
Revisions in the productivity data in table
54 are usually introduced in the September
issue. Seasonally adjusted indexes and percent changes from month-to-month and
quarter-to-quarter are published for numerous Consumer and Producer Price Index
series. However, seasonally adjusted indexes
are not published for the U.S. average AllItems CPI. Only seasonally adjusted percent
changes are available for this series.
Adjustments for price changes. Some
data—such as the “real” earnings shown in
table 14—are adjusted to eliminate the effect
of changes in price. These adjustments are
made by dividing current-dollar values by
the Consumer Price Index or the appropriate
component of the index, then multiplying
by 100. For example, given a current hourly
wage rate of $3 and a current price index
number of 150, where 1982 = 100, the hourly
rate expressed in 1982 dollars is $2 ($3/150
x 100 = $2). The $2 (or any other resulting
58
Monthly Labor Review • September 2008
values) are described as “real,” “constant,” or
“1982” dollars.
Sources of information
Data that supplement the tables in this section are published by the Bureau in a variety
of sources. Definitions of each series and
notes on the data are contained in later sections of these Notes describing each set of
data. For detailed descriptions of each data
series, see BLS Handbook of Methods, Bulletin
2490. Users also may wish to consult Major
Programs of the Bureau of Labor Statistics,
Report 919. News releases provide the latest statistical information published by the
Bureau; the major recurring releases are
published according to the schedule appearing on the back cover of this issue.
More information about labor force,
employment, and unemployment data and
the household and establishment surveys
underlying the data are available in the
Bureau’s monthly publication, Employment
and Earnings. Historical unadjusted and
seasonally adjusted data from the household
survey are available on the Internet:
www.bls.gov/cps/
Historically comparable unadjusted and seasonally adjusted data from the establishment
survey also are available on the Internet:
www.bls.gov/ces/
Additional information on labor force data
for areas below the national level are provided in the BLS annual report, Geographic
Profile of Employment and Unemployment.
For a comprehensive discussion of the
Employment Cost Index, see Employment
Cost Indexes and Levels, 1975–95, BLS Bulletin 2466. The most recent data from the
Employee Benefits Survey appear in the following Bureau of Labor Statistics bulletins:
Employee Benefits in Medium and Large Firms;
Employee Benefits in Small Private Establishments; and Employee Benefits in State and Local
Governments.
More detailed data on consumer and
producer prices are published in the monthly
periodicals, The CPI Detailed Report and Producer Price Indexes. For an overview of the
1998 revision of the CPI, see the December
1996 issue of the Monthly Labor Review. Additional data on international prices appear
in monthly news releases.
Listings of industries for which productivity indexes are available may be found on
the Internet:
www.bls.gov/lpc/
For additional information on international comparisons data, see Interna-
tional Comparisons of Unemployment, Bulletin
1979.
Detailed data on the occupational injury
and illness series are published in Occupational Injuries and Illnesses in the United States,
by Industry, a BLS annual bulletin.
Finally, the Monthly Labor Review carries
analytical articles on annual and longer term
developments in labor force, employment,
and unemployment; employee compensation
and collective bargaining; prices; productivity; international comparisons; and injury
and illness data.
Symbols
n.e.c. =
n.e.s. =
p =
r =
not elsewhere classified.
not elsewhere specified.
preliminary. To increase
the timeliness of some series,
preliminary figures are issued
based on representative but
incomplete returns.
revised. Generally, this revision
reflects the availability of later
data, but also may reflect other
adjustments.
Comparative Indicators
(Tables 1–3)
Comparative indicators tables provide an
overview and comparison of major bls statistical series. Consequently, although many
of the included series are available monthly,
all measures in these comparative tables are
presented quarterly and annually.
Labor market indicators include employment measures from two major surveys
and information on rates of change in
compensation provided by the Employment
Cost Index (ECI) program. The labor force
participation rate, the employment-population ratio, and unemployment rates for major
demographic groups based on the Current
Population (“household”) Survey are presented, while measures of employment and
average weekly hours by major industry sector are given using nonfarm payroll data. The
Employment Cost Index (compensation),
by major sector and by bargaining status, is
chosen from a variety of BLS compensation
and wage measures because it provides a
comprehensive measure of employer costs for
hiring labor, not just outlays for wages, and it
is not affected by employment shifts among
occupations and industries.
Data on changes in compensation, prices, and productivity are presented in table 2.
Measures of rates of change of compensation
and wages from the Employment Cost Index
program are provided for all civilian nonfarm
workers (excluding Federal and household
workers) and for all private nonfarm workers.
Measures of changes in consumer prices for
all urban consumers; producer prices by stage
of processing; overall prices by stage of processing; and overall export and import price
indexes are given. Measures of productivity
(output per hour of all persons) are provided
for major sectors.
Alternative measures of wage and compensation rates of change, which reflect the
overall trend in labor costs, are summarized
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.
Employment and
Unemployment Data
4 weeks. Persons who did not look for work
because they were on layoff are also counted
among the unemployed. The unemployment
rate represents the number unemployed as a
percent of the civilian labor force.
The civilian labor force consists of all
employed or unemployed persons in the civilian noninstitutional population. Persons not
in the labor force are those not classified 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 sometime in the past
12 months (or since the end of their last job
if they held one within the past 12 months),
but are not currently looking, because they
believe there are no jobs available or there are
none for which they would qualify. The civilian noninstitutional population comprises
all persons 16 years of age and older who are
not inmates of penal or mental institutions,
sanitariums, or homes for the aged, infirm,
or needy. The civilian labor force participation rate is the proportion of the civilian
noninstitutional population that is in the
labor force. The employment-population
ratio is employment as a percent of the civilian noninstitutional population.
(Tables 1; 4–29)
Notes on the data
Household survey data
From time to time, and especially after a decennial census, adjustments are made in the
Current Population Survey figures to correct
for estimating errors during the intercensal
years. These adjustments affect the comparability of historical data. A description of
these adjustments and their effect on the
various data series appears in the Explanatory Notes of Employment and Earnings. For
a discussion of changes introduced in January
2003, see “Revisions to the Current Population Survey Effective in January 2003” in
the February 2003 issue of Employment and
Earnings (available on the BLS Web site at
www.bls.gov/cps/rvcps03.pdf).
Effective in January 2003, BLS began
using the X-12 ARIMA seasonal adjustment
program to seasonally adjust national labor
force data. This program replaced the X-11
ARIMA program which had been used since
January 1980. See “Revision of Seasonally
Adjusted Labor Force Series in 2003,” in
the February 2003 issue of Employment and
Earnings (available on the BLS Web site at
www.bls.gov/cps/cpsrs.pdf) for a discussion
of the introduction of 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 of each calendar year,
historical seasonally adjusted data usually
are revised, and projected seasonal adjustment factors are calculated for use during the
Notes on the data
Definitions of each series and notes on the
data are contained in later sections of these
notes describing each set of data.
Description of the series
Employment data in this section are obtained from the Current Population Survey,
a program of personal interviews conducted
monthly by the Bureau of the Census for
the Bureau of Labor Statistics. The sample
consists 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 consecutive
months.
Definitions
Employed persons include (1) all those who
worked for pay any time during the week
which includes the 12th day of 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 of illness, vacation, 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 of hours.
Unemployed persons are those who did
not work during the survey week, but were
available for work except for temporary illness
and had looked for jobs within the preceding
January–June period. The historical seasonally adjusted data usually are revised for only
the most recent 5 years. In July, new seasonal
adjustment factors, which incorporate the
experience through June, are produced for
the July–December period, but no revisions
are made in the historical data.
F OR ADDITIONAL INFORMATION on
national 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 compiled from payroll records
reported monthly on a voluntary basis to
the Bureau of Labor Statistics and its cooperating State agencies by about 160,000
businesses and government agencies, which
represent approximately 400,000 individual
worksites and represent all industries except
agriculture. The active CES sample covers
approximately one-third of all nonfarm
payroll workers. Industries are classified in
accordance with the 2002 North American
Industry Classification System. In most
industries, the sampling probabilities are
based on the size of the establishment; most
large establishments are therefore in the
sample. (An establishment is not necessarily
a firm; it may be a branch plant, for example,
or warehouse.) Self-employed persons and
others not on a regular civilian payroll are
outside the scope of the survey because they
are excluded from establishment records.
This largely accounts for the difference in
employment figures between the household
and establishment surveys.
Definitions
An establishment is an economic unit which
produces goods or services (such as a factory
or store) at a single location and is engaged
in one type of economic activity.
Employed persons are all persons who
received pay (including holiday and sick pay)
for any part of the payroll period including
the 12th day of the month. Persons holding
more than one job (about 5 percent of all
persons in the labor force) are counted in
each establishment which reports them.
Production workers in the goods-producing industries cover employees, 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,
Monthly Labor Review • September 2008
59
Current Labor Statistics
managerial, and supervisory positions. Those
workers mentioned in tables 11–16 include
production workers in manufacturing and
natural resources and mining; construction
workers in construction; and nonsupervisory workers in all private service-providing
industries. Production and nonsupervisory
workers account for about four-fifths of the
total employment on private nonagricultural
payrolls.
Earnings are the payments production
or nonsupervisory workers receive during
the survey period, including premium pay
for overtime or late-shift work but excluding irregular bonuses and other special
payments. Real earnings are earnings
adjusted to reflect the effects of changes
in consumer prices. The deflator for this
series is derived from the Consumer Price
Index for Urban Wage Earners and Clerical
Workers (CPI-W).
Hours represent the average weekly
hours of production or nonsupervisory
workers for which pay was received, and are
different from standard or scheduled hours.
Overtime hours represent the portion of
average weekly hours which was in excess
of regular hours and for which overtime
premiums were paid.
The Diffusion Index represents the
percent of industries in which employment
was rising over the indicated period, plus
one-half of the industries with unchanged
employment; 50 percent indicates an equal
balance between industries with increasing
and decreasing employment. In line with
Bureau practice, data for the 1-, 3-, and 6month 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 of economic gains or
losses and are also economic indicators.
Notes on the data
Establishment survey data are annually
adjusted to comprehensive counts of employment (called “benchmarks”). The March
2003 benchmark was introduced in February
2004 with the release of data for January
2004, published in the March 2004 issue of
the Review. With the release in June 2003,
CES completed a conversion from the Standard Industrial Classification (SIC) system to
the North American Industry Classification
System (naics) and completed the transition
from its original quota sample design to a
probability-based sample design. The industry-coding update included reconstruction
of historical estimates in order to preserve
60
Monthly Labor Review • September 2008
time series for data users. Normally 5 years
of 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 of all CES time series.
Also in June 2003, the CES program introduced concurrent seasonal adjustment for
the national establishment data. Under this
methodology, the first preliminary estimates
for the current reference month and the
revised estimates for the 2 prior months will
be updated with concurrent factors with each
new release of data. Concurrent seasonal
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 of Employment and Earnings
and “Recent changes in the national Current
Employment Statistics survey,” Monthly Labor Review, June 2003, pp. 3–13.
Revisions in State data (table 11) occurred with the publication of January 2003
data. For information on the revisions for
the State data, see the March and May 2003
issues of Employment and Earnings, and “Recent changes in the State and Metropolitan
Area CES survey,” Monthly Labor Review,
June 2003, pp. 14–19.
Beginning in June 1996, the BLS uses
the X-12-ARIMA methodology to seasonally adjust establishment survey data. This
procedure, developed by the Bureau of the
Census, controls for the effect of varying
survey intervals (also known as the 4- versus
5-week effect), thereby providing improved
measurement of over-the-month changes
and underlying economic trends. Revisions
of 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
incomplete returns and are published as preliminary in the tables (12–17 in the Review).
When all returns have been received, the
estimates are revised and published as “final”
(prior to any benchmark revisions) in the
third month of their appearance. Thus, December data are published as preliminary in
January and February and as final in March.
For the same reasons, quarterly establishment data (table 1) are preliminary for the
first 2 months of publication and final in the
third month. Fourth-quarter data are published as preliminary in January and February
and as final in March.
F OR ADDITIONAL INFORMATION on
establishment survey data, contact the Division of 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 Statistics (LAUS) program, which is conducted in
cooperation with State employment security
agencies.
Monthly estimates of the labor force,
employment, and unemployment for States
and sub-State areas are a key indicator of local economic conditions, and form the basis
for determining the eligibility of an area for
benefits under Federal economic assistance
programs such as the Job Training Partnership Act. Seasonally adjusted unemployment
rates are presented in table 10. Insofar as possible, the concepts and definitions underlying
these data are those used in the national
estimates obtained from the CPS.
Notes on the data
Data refer to State of residence. Monthly
data for all States and the District of Columbia are derived using standardized procedures
established by BLS. Once a year, estimates are
revised to new population controls, usually
with publication of January estimates, and
benchmarked to annual average CPS levels.
FOR ADDITIONAL INFORMATION on data
in this series, call (202) 691–6392 (table 10)
or (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 quarterly
tax reports submitted to State employment
security agencies by private and State and
local government employers subject to State
unemployment insurance (ui) laws and from
Federal, agencies subject to the Unemployment Compensation for Federal Employees
(ucfe) program. Each quarter, State agencies edit and process the data and send the
information to the Bureau of Labor Statistics.
The Quarterly Census of Employment
and Wages (QCEW) data, also referred as ES202 data, are the most complete enumeration
of employment and wage information by
industry at the national, State, metropolitan
area, and county levels. They have broad
economic significance in evaluating labor
market trends and major industry developments.
Definitions
In general, the Quarterly Census of Employment 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 of
the month. Covered private industry employment includes most corporate officials,
executives, supervisory personnel, professionals, clerical workers, wage earners, piece
workers, and part-time workers. It excludes
proprietors, the unincorporated self-employed, unpaid family members, and certain
farm and domestic workers. Certain types
of nonprofit employers, such as religious
organizations, are given a choice of coverage
or exclusion in a number of States. Workers
in these organizations are, therefore, reported
to a limited degree.
Persons on paid sick leave, paid holiday,
paid vacation, and the like, are included.
Persons on the payroll of more than one
firm during the period are counted by each
ui-subject employer if they meet the employment definition noted earlier. The employment count excludes workers who earned no
wages during the entire applicable pay period
because of work stoppages, temporary layoffs,
illness, or unpaid vacations.
Federal employment data are based on
reports of monthly employment and quarterly 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 security
agencies, which are omitted for security reasons. Employment for all Federal agencies
for any given month is based on the number
of persons who worked during or received
pay for the pay period that included the 12th
of the month.
An establishment is an economic unit,
such as a farm, mine, factory, or store, that
produces goods or provides services. It is
typically at a single physical location and
engaged in one, or predominantly one, type
of economic activity for which a single industrial classification may be applied. Occasionally, a single physical location encompasses
two or more distinct and significant activities.
Each activity should be reported as a separate
establishment if separate records are kept
and the various activities are classified under
different NAICS industries.
Most employers have only one establishment; thus, the establishment is the
predominant reporting unit or statistical
entity for reporting employment and wages
data. Most employers, including State and
local governments who operate more than
one establishment in a State, file a Multiple
Worksite Report each quarter, in addition
to their quarterly ui report. The Multiple
Worksite Report 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-establishment employers do not file a
Multiple Worksite Report. When the total
employment in an employer’s secondary
establishments (all establishments other
than the largest) is 10 or fewer, the employer
generally will file a consolidated report for all
establishments. Also, some employers either
cannot 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 reporting unit is the installation: a single location
at which a department, agency, or other government body has civilian employees. Federal
agencies follow slightly different criteria than
do private employers when breaking down
their reports by installation. They are permitted to combine as a single statewide unit: 1)
all installations with 10 or fewer workers,
and 2) all installations that have a combined
total in the State of 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 installation. 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 of reporting units is always larger
than the number of employers (or government agencies) but smaller than the number
of actual establishments (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 appropriate 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 quarter,
regardless of when the services were performed. 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 compensation is paid. Under most State laws or
regulations, wages include bonuses, stock
options, the cash value of meals and lodging,
tips and other gratuities, and, in some States,
employer contributions to certain deferred
compensation plans such as 401(k) plans.
Covered employer contributions for
old-age, survivors, and disability insurance
(oasdi), health insurance, unemployment insurance, 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 of covered Federal workers represent the gross amount of all payrolls for all
pay periods ending within the quarter. This
includes cash allowances, the cash equivalent
of any type of remuneration, severance pay,
withholding taxes, and retirement deductions. Federal employee remuneration generally covers the same types of services as for
workers in private industry.
Average annual wage per employee for
any given industry are computed by dividing total annual wages by annual average
employment. 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 wage is affected by the ratio of full-time to part-time
workers as well as the number of individuals
in high-paying and low-paying occupations.
When average pay levels between States and
industries are compared, these factors should
be taken into consideration. For example,
industries characterized by high proportions
of part-time workers will show average wage
levels appreciably less than the weekly pay
levels of regular full-time employees in these
industries. The opposite effect characterizes
industries with low proportions of part-time
workers, or industries that typically schedule
heavy weekend 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 of data for 2001,
publications presenting data from the Covered Employment and Wages program have
switched to the 2002 version of the North
Monthly Labor Review • September 2008
61
Current Labor Statistics
American Industry Classification System
(NAICS) as the basis for the assignment and
tabulation of economic data by industry.
NAICS is the product of a cooperative effort on the part of the statistical agencies
of the United States, Canada, and Mexico.
Due to difference in NAICS 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
began assigning Indian Tribal Councils and
related 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 Federal
Unemployment Tax Act. This law requires
federally recognized Indian Tribes to be treated similarly to State and local governments.
In the past, the Covered Employment and
Wage (CEW) program coded Indian Tribal
Councils and related establishments in the
private sector. As a result of 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 of that entity.
To insure the highest possible quality
of data, State employment security agencies
verify with employers and update, if necessary, the industry, location, and ownership
classification of all establishments on a 3-year
cycle. Changes in establishment classification codes resulting from the verification
process are introduced with the data reported
for the first quarter of the year. Changes
resulting from improved employer reporting
also are introduced in the first quarter. For
these reasons, some data, especially at more
detailed geographic levels, may not be strictly
comparable with earlier years.
County definitions are assigned according
to Federal Information Processing Standards
Publications as issued by the National Institute of Standards and Technology. Areas
shown as counties include those designated
as independent cities in some jurisdictions
and, in Alaska, those areas designated 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 townships are the
more common designation used in New
England (and New Jersey).
The Office of Management and Budget
62
Monthly Labor Review • September 2008
(OMB) 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 OMB in definitions issued June 30, 1999
(OMB Bulletin No. 99-04). These definitions
reflect information obtained from the 1990
Decennial Census and the 1998 U.S. Census
Bureau population estimate. A complete list
of metropolitan area definitions is available
from the National Technical Information
Service (NTIS), Document Sales, 5205 Port
Royal Road, Springfield, Va. 22161, telephone 1-800-553-6847.
OMB defines metropolitan areas in terms
of 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 (NECMA) because county-level data are the most detailed available
from the Quarterly Census of Employment
and Wages. The NECMA is a county-based
alternative to the city- and town-based metropolitan areas in New England. The NECMA for
a Metropolitan Statistical Area (MSA) include:
(1) the county containing the first-named city
in that MSA title (this county may include
the first-named cities of other MSA, and (2)
each additional county having at least half its
population in the MSA in which first-named
cities are in the county identified in step 1.
The NECMA is officially defined areas that
are meant to be used by statistical programs
that cannot use the regular metropolitan area
definitions in New England.
For additional information on the
covered employment and wage data, contact
the Division of Administrative Statistics and
Labor Turnover at (202) 691–6567.
Job Openings and Labor
Turnover Survey
Description of the series
Data for the Job Openings and Labor
Turnover Survey (JOLTS) are collected and
compiled from a sample of 16,000 business
establishments. Each month, data are collected for total employment, job openings,
hires, quits, layoffs and discharges, and other
separations. 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 of Columbia. The
JOLTS sample design is a random sample
drawn from a universe of more than eight
million establishments compiled as part of the
operations of the Quarterly Census of Employment and Wages, or QCEW, program. This
program includes all employers subject to
State unemployment insurance (UI) laws and
Federal agencies subject to Unemployment
Compensation for Federal Employees (UCFE).
The sampling frame is stratified by ownership, 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 (CES)
survey. A ratio of CES to JOLTS employment
is used to adjust the levels for all other JOLTS
data elements. Rates then are computed from
the adjusted 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 nonfarm sector, 16 private industry
divisions and 2 government divisions based
on the North American Industry Classification System (NAICS), and four geographic
regions. Seasonally adjusted data on job
openings, hires, total separations, and quits
levels and rates are available for the total
nonfarm sector, selected industry sectors, and
four geographic regions.
Definitions
Establishments submit job openings infor-mation for the last business day of the
reference 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 layoffs
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, outside
contractors, or consultants. The job openings
rate is computed by dividing the number of
job openings by the sum of employment and
job openings, and multiplying that quotient
by 100.
Hires are the total number of additions
to the payroll occurring at any time during
the reference month, including both new and
rehired employees and full-time and parttime, permanent, short-term and seasonal
employees, employees recalled to the location
after a layoff lasting more than 7 days, on-call
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 promotions within the reporting site, employees
returning from strike, employees of temporary
help agencies or employee leasing companies,
outside contractors, or consultants. The hires
rate is computed by dividing the number of
hires by employment, and multiplying that
quotient by 100.
Separations are the total number of
terminations of employment occurring at
any time during the reference month, and
are reported by type of separation—quits,
layoffs and discharges, and other separations.
Quits are voluntary separations by employees
(except for retirements, which are reported
as other separations). Layoffs and discharges
are involuntary separations initiated by the
employer and include 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 discharges 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 location or employees on
strike.
The separations rate is computed by dividing the number of separations by employment, and multiplying that quotient by 100.
The quits, layoffs and discharges, and other
separations rates are computed similarly,
dividing the number by employment and
multiplying by 100.
Notes on the data
The JOLTS data series on job openings, hires,
and separations are relatively new. The full
sample is divided into panels, with one panel
enrolled each month. A full complement of
panels for the original data series based on the
1987 Standard Industrial Classification (SIC)
system was not completely enrolled in the
survey until January 2002. The supple-mental
panels of establishments needed to create NAICS estimates were not completely enrolled
until May 2003. The data collected up until
those points are from less than a full sample.
Therefore, estimates from earlier months
should be used with caution, as fewer sampled
units were reporting data at that time.
In March 2002, BLS procedures for collecting hires and separations data were revised to
address possible underreporting. As a result,
JOLTS hires and separations estimates for
months prior to March 2002 may not be
comparable with estimates for March 2002
and later.
The Federal Government reorganization
that involved transferring approximately
180,000 employees to the new Department
of Homeland Security is not reflected in
the JOLTS hires and separations estimates
for the Federal Government. The Office of
Personnel Management’s record shows these
transfers were completed in March 2003. The
inclusion of transfers in the JOLTS definitions
of hires and separations is intended to cover
ongoing movements of workers between
establishments. The Department of Homeland Security reorganization was a massive
one-time event, and the inclusion of these
intergovernmental transfers would distort
the Federal Government time series.
Data users should note that seasonal
adjustment of the JOLTS series is conducted
with fewer data observations than is customary. The historical data, therefore, may
be subject to larger than normal revisions.
Because the seasonal patterns in economic
data series typically emerge over time, the
standard use of moving averages as seasonal
filters to capture these effects requires longer
series than are currently available. As a result,
the stable seasonal filter option is used in the
seasonal adjustment of the JOLTS data. When
calculating seasonal factors, this filter takes
an average for each calendar month after
detrending the series. The stable seasonal
filter assumes that the seasonal factors are
fixed; a necessary assumption until sufficient
data are available. 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, it is expected that more series,
such as layoffs and discharges and additional
industries, may be seasonally adjusted when
more data are available.
JOLTS hires and separations estimates
cannot be used to exactly explain net changes
in payroll employment. Some reasons why it
is problematic to compare changes in payroll
employment with JOLTS hires and separations, especially on a monthly basis, are: (1)
the reference period for payroll employment
is the pay period including the 12th of the
month, while the reference period for hires
and separations is the calendar month; and
(2) payroll employment can vary from month
to month simply because part-time and oncall workers may not always work during
the pay period that includes the 12th of the
month. Additionally, research has found that
some reporters systematically underreport
separations relative to hires due to a number of factors, including the nature of their
payroll systems and practices. The shortfall
appears to be about 2 percent or less over a
12-month period.
F OR ADDITIONAL INFORMATION on
the Job Openings and Labor Turnover
Survey, contact the Division of Administrative Statistics and Labor Turnover at (202)
961–5870.
Compensation and
Wage Data
(Tables 1–3; 30–37)
The National Compensation Survey (NCS)
produces a variety of compensation data. These
include: The Employment Cost Index (ECI)
and NCS benefit measures of the incidence and
provisions of selected employee benefit plans.
Selected samples of these measures appear in
the following tables. NCS also compiles data on
occupational wages and the Employer Costs
for Employee Compensation (ECEC).
Employment Cost Index
Description of the series
The Employment Cost Index (ECI) is a
quarterly measure of the rate of change in
compensation per hour worked and includes
wages, salaries, and employer costs of employee benefits. It is a Laspeyres Index that
uses fixed employment weights to measure
change in labor costs free from the influence
of employment shifts among occupations
and industries.
The ECI provides data for the civilian
economy, which includes the total private
nonfarm economy excluding private households, and the public sector excluding the
Federal government. Data are collected each
quarter for the pay period including the
12th day of March, June, September, and
December.
Sample establishments are classified by
industry categories based on the 2002 North
American Classification System (NAICS).
Within a sample establishment, specific job
categories are selected and classified into
about 800 occupations according to the 2000
Standard Occupational Classification (SOC)
System. Individual occupations are comMonthly Labor Review • September 2008
63
Current Labor Statistics
bined to represent one of ten intermediate
aggregations, such as professional and related
occupations, or one of five higher level aggregations, such as management, professional,
and related occupations.
Fixed employment weights are used
each quarter to calculate the most aggregate
series—civilian, private, and State and local
government. These fixed weights are also used
to derive all of the industry and occupational
series indexes. Beginning with the March
2006 estimates, 2002 fixed employment
weights from the Bureau’s Occupational
Employment Statistics survey were introduced. From March 1995 to December 2005,
1990 employment counts were used. These
fixed weights ensure that changes in these
indexes reflect only changes in compensation,
not employment shifts among industries or
occupations with different levels of wages
and compensation. For the series based on
bargaining status, census region and division,
and metropolitan area status, fixed employment data are not available. The employment
weights are reallocated within these series
each quarter based on the current eci sample.
The indexes for these series, consequently, are
not strictly comparable with those for aggregate, occupational, and industry series.
Definitions
Total compensation costs include wages,
salaries, and the employer’s costs for employee benefits.
Wages and salaries consist of earnings
before payroll deductions, including production bonuses, incentive earnings, commissions, and cost-of-living adjustments.
Benefits include the cost to employers
for paid leave, supplemental pay (including nonproduction bonuses), insurance,
retirement and savings plans, and legally
required benefits (such as Social Security,
workers’ compensation, and unemployment
insurance).
Excluded from wages and salaries and
employee benefits are such items as paymentin-kind, free room and board, and tips.
Notes on the data
The ECI data in these tables reflect the
con-version to the 2002 North American
Industry Classification System (NAICS) and
the 2000 Standard Occupational Classification (SOC) system. The NAICS and SOC data
shown prior to 2006 are for informational
purposes only. ECI series based on NAICS
and SOC became the official BLS estimates
starting in March 2006.
The ECI for changes in wages and salaries
64
Monthly Labor Review • September 2008
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 government sector and
in the civilian nonfarm economy (excluding
Federal employees) were published beginning in 1981. Historical indexes (December
2005=100) are available on the Internet:
www.bls.gov/ect/
A DDITIONAL INFORMATION on the
Employment Cost Index is available at www.
bls.gov/ncs/ect/home.htm or by telephone
at (202) 691–6199.
National Compensation Survey
Benefit Measures
Description of the series
benefit measures of employee benefits
are published in two separate reports. The
annual summary provides data on the incidence of (access to and participation in)
selected benefits and provisions of paid
holidays and vacations, life insurance plans,
and other selected benefit programs. Data on
percentages of establishments offering major
employee benefits, and on the employer and
employee shares of contributions to medical
care premiums also are presented. Selected
benefit data appear in the following tables. A
second publication, published later, contains
more detailed information about health and
retirement plans.
NCS
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 employee also are included. For example, long-term
care insurance paid entirely by the employee
are included because the guarantee of insurability and availability at group premium
rates are considered a benefit.
Employees are considered as having access to a benefit plan if it is available for their
use. For example, if an employee is permitted
to participate in a medical care plan offered
by the employer, but the employee declines to
do so, he or she is placed in the category with
those having access to medical care.
Employees in contributory plans are
considered as participating in an insurance
or retirement plan if they have paid required
contributions and fulfilled any applicable
service requirement. Employees in noncontributory plans are counted as participating
regardless of whether they have fulfilled the
service requirements.
Defined benefit pension plans use predetermined formulas to calculate a retirement
benefit (if any), and obligate the employer to
provide those benefits. Benefits are generally
based on salary, years of service, or both.
Defined contribution plans generally
specify the level of employer and employee
contributions to a plan, but not the formula
for determining eventual benefits. Instead,
individual accounts are set up for participants, and benefits are based on amounts
credited to these accounts.
Tax-deferred savings plans are a type of
defined contribution plan that allow participants to contribute a portion of their salary
to an employer-sponsored plan and defer
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 of coverage within
a given benefit.
Notes on the data
ADDITIONAL INFORMATION ON THE NCS
benefit measures is available at www.bls.
gov/ncs/ebs/home.htm or by telephone at
(202) 691–6199.
Work stoppages
Description of the series
Data on work stoppages measure the number
and duration of major strikes or lockouts
(involving 1,000 workers or more) occurring
during the month (or year), the number of
workers involved, and the amount of work
time lost because of stoppage. These data are
presented in table 37.
Data are largely from a variety of published sources and cover only establishments
directly involved in a stoppage. They do not
measure the indirect or secondary effect of
stoppages on other establishments whose
employees are idle owing to material shortages or lack of service.
Definitions
Number of stoppages: The number of
strikes and lockouts involving 1,000 workers or more and lasting a full shift or longer.
Workers involved: The number of workers directly involved in the stoppage.
Number of days idle: The aggregate
number of workdays lost by workers involved
in the stoppages.
Days of idleness as a percent of estimated working time: Aggregate workdays
lost as a percent of the aggregate number of
standard workdays in the period multiplied
by total employment in the period.
Notes on the data
This series is not comparable with the one
terminated in 1981 that covered strikes involving six workers or more.
A DDITIONAL INFORMATION on work
stop-pages data is available at www. bls.
gov/cba/home.htm or by telephone at (202)
691–6199.
Price Data
(Tables 2; 38–46)
Price data are gathered by the Bureau
of Labor Statistics from retail and primary markets in the United States. Price
indexes are given in relation to a base period—December 2003 = 100 for many Producer Price Indexes (unless otherwise noted),
1982–84 = 100 for many Consumer Price
Indexes (unless otherwise noted), and 1990
= 100 for International Price Indexes.
Consumer Price Indexes
Description of the series
The Consumer Price Index (CPI) is a measure
of the average change in the prices paid by
urban consumers for a fixed market basket
of goods and services. The CPI is calculated
monthly for two population groups, one
consisting only of 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 index (CPI-W) is
a continuation of the historic index that was
introduced well over a half-century 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 of the 1993–95 buying habits of about
87 percent of the noninstitutional population
of the United States at that time, compared
with 32 percent represented in the CPI-W. In
addition to wage earners and clerical workers,
the CPI-U covers professional, managerial, and
technical workers, the self-employed, shortterm workers, the unemployed, retirees, and
others not in the labor force.
The CPI is based on prices of food, clothing,
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 of these items are kept
essentially unchanged between major revisions
so that only price changes will be measured. All
taxes directly associated with the purchase and
use of items are included in the index.
Data collected from more than 23,000 retail
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 presented in table
39.The areas listed are as indicated 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 of the change was to separate
shelter costs from the investment component
of homeownership so that the index would
reflect only the cost of shelter services provided
by owner-occupied homes. An updated CPI-U
and CPI-W were introduced with release of the
January 1987 and January 1998 data.
FOR ADDITIONAL INFORMATION, contact the Division of Prices and Price Indexes:
(202) 691–7000.
Producer Price Indexes
Description of the series
Producer Price Indexes (PPI) measure average changes in prices received by domestic
producers of commodities in all stages of
processing. The sample used for calculating
these indexes currently contains about 3,200
commodities and about 80,000 quotations
per month, selected to represent the movement of prices of all commodities produced
in the manufacturing; agriculture, forestry,
and fishing; mining; and gas and electricity
and public utilities sectors. The stage-of-processing structure of PPI organizes products by
class of buyer and degree of fabrication (that is,
finished goods, intermediate goods, and crude
materials). The traditional commodity structure of PPI organizes products by similarity of
end use or material composition. The industry
and product structure of PPI organizes data in
accordance with the 2002 North American
Industry Classification System and product
codes developed by the U.S. Census Bureau.
To the extent possible, prices used in
calculating Producer Price Indexes apply to
the first significant commercial transaction
in the United States from the production
or central marketing point. Price data are
generally collected monthly, primarily by
mail questionnaire. Most prices are obtained
directly from producing companies on a voluntary and confidential basis. Prices generally are reported for the Tuesday of the week
containing the 13th day of the month.
Since January 1992, price changes for
the various commodities have been averaged
together with implicit quantity weights representing their importance in the total net
selling value of all commodities as of 1987. The
detailed data are aggregated to obtain indexes
for stage-of-processing groupings, commodity
groupings, durability-of-product groupings,
and a number of special composite groups. All
Producer Price Index data are subject to revision 4 months after original publication.
FOR ADDITIONAL INFORMATION, contact the Division of 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
services traded between the United States
and the rest of the world. The export price
index provides a measure of price change
for all products sold by U.S. residents to
foreign buyers. (“Residents” is defined as in
the national income accounts; it includes
corporations, businesses, and individuals, but
does not require the organizations to be U.S.
owned nor the individuals to have U.S. citizenship.) The import price index provides a
measure of 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 manufactures, and finished manufactures, including 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 exporter 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.
Monthly Labor Review • September 2008
65
Current Labor Statistics
border for imports. For nearly all products, the
prices refer to transactions completed during
the first week of the month. Survey respondents are asked to indicate all discounts, allowances, and rebates applicable to the reported
prices, so that the price used in the calculation
of 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 defined
according to the five-digit level of detail for the
Bureau of Economic Analysis End-use Classification, the three-digit level for the Standard
International Trade Classification (SITC), and
the four-digit level of detail for the Harmonized System. Aggregate import indexes by
country or region of origin are also available.
BLS publishes indexes for selected categories of internationally traded services,
calculated on an international basis and on a
balance-of-payments basis.
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 period, it
is necessary to recognize when a product’s
specifications or terms of transaction have
been modified. For this reason, the Bureau’s
questionnaire requests detailed descriptions of
the physical and functional characteristics of
the products being priced, as well as information on the number of units bought or sold,
discounts, credit terms, packaging, class of
buyer or seller, and so forth. When there are
changes in either the specifications 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 linking procedure
is employed which allows for the continued
repricing of the item.
FOR ADDITIONAL INFORMATION, contact the Division of International Prices:
(202) 691–7155.
Productivity Data
(Tables 2; 47–50)
Business and major sectors
Description of the series
The productivity measures relate real output
to real input. As such, they encompass a fam66
Monthly Labor Review • September 2008
ily of measures which include single-factor
input measures, such as output per hour,
output per unit of labor input, or output per
unit of capital input, as well as measures of
multifactor productivity (output per unit
of combined labor and capital inputs). The
Bureau indexes show the change in output
relative to changes in the various inputs.
The measures cover the business, nonfarm
business, manufacturing, and nonfinancial
corporate sectors.
Corresponding indexes of hourly compensation, unit labor costs, unit nonlabor
payments, and prices are also provided.
Definitions
Output per hour of all persons (labor
productivity) is the quantity of goods and
services produced per hour of labor input.
Output per unit of capital services (capital
productivity) is the quantity of goods and
services produced per unit of capital services input. Multifactor productivity is the
quantity of goods and services produced per
combined inputs. For private business and
private nonfarm business, inputs include
labor and capital units. For manufacturing,
inputs include labor, capital, energy, nonenergy
materials, and purchased business services.
Compensation per hour is total compensation divided by hours at work. Total
compensation equals the wages and salaries
of employees plus employers’ contributions for
social insurance and private benefit plans, plus
an estimate of these payments for the self-employed (except for nonfinancial corporations
in which there are no self-employed). Real
compensation per hour is compensation per
hour deflated by the change in the Consumer
Price Index for All Urban Consumers.
Unit labor costs are the labor compensation costs expended in the production of a
unit of output and are derived by dividing
compensation by output. Unit nonlabor
payments include profits, depreciation,
interest, and indirect taxes per unit of output.
They are computed by subtracting compensation of all persons from current-dollar value
of output and dividing by output.
Unit nonlabor costs contain all the components of unit nonlabor payments except
unit profits.
Unit profits include corporate profits
with inventory valuation and capital consumption adjustments per unit of output.
Hours of all persons are the total hours
at work of payroll workers, self-employed
persons, and unpaid family workers.
Labor inputs are hours of all persons
adjusted for the effects of changes in the
education and experience of the labor force.
Capital services are the flow of services
from the capital stock used in production. It
is developed from measures of the net stock
of physical assets—equipment, structures,
land, and inventories—weighted by rental
prices for each type of asset.
Combined units of 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 Tornquist index-number formula).
Notes on the data
Business sector output is an annually-weighted index constructed by excluding from real
gross domestic product (GDP) the following
outputs: general government, nonprofit
institutions, paid employees of private households, and the rental value of owner-occupied
dwellings. Nonfarm business also excludes
farming. Private business and private nonfarm business further exclude government
enterprises. The measures are supplied by
the U.S. Department of Commerce’s Bureau
of Economic Analysis. Annual estimates of
manufacturing sectoral output are produced
by the Bureau of Labor Statistics. Quarterly manufacturing output indexes from the
Federal Reserve Board are adjusted to these
annual output measures by the BLS. Compensation data are developed from data of the
Bureau of 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 47–50 describe the relationship between output in real terms and
the labor and capital inputs involved in its
production. They show the changes from
period to period in the amount of goods and
services produced per unit of input.
Although these measures relate output
to hours and capital services, they do not
measure the contributions of labor, capital,
or any other specific factor of production.
Rather, they reflect the joint effect of many
influences, including changes in technology;
shifts in the composition of the labor force;
capital investment; level of output; changes
in the utilization of capacity, energy, material,
and research and development; the organi-
zation of production; managerial skill; and
characteristics and efforts of the work force.
FOR ADDITIONAL INFORMATION on this
productivity series, contact the Division of
Productivity Research: (202) 691–5606.
Industry productivity measures
Description of the series
The BLS industry productivity indexes measure the relationship between output and
inputs for selected industries and industry
groups, and thus reflect trends in industry efficiency over time. Industry measures include
labor productivity, multifactor productivity,
compensation, and unit labor costs.
The industry measures differ in methodology and data sources from the productivity
measures for the major sectors because the
industry measures are developed independently of 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 of labor
input. For most industries, output indexes
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 quantity
of production.
The labor input series is based on the
hours of all workers or, in the case of some
transportation industries, on the number of
employees. For most industries, the series
consists of the hours of all employees. For
some trade and services industries, the series
also includes the hours of partners, proprietors, and unpaid family workers.
Unit labor costs represent the labor compensation costs per unit of output produced,
and are derived by dividing an index of labor
compensation by an index of output. Labor
compensation includes payroll as well as
supplemental payments, including both
legally required expenditures and payments
for voluntary programs.
Multifactor productivity is derived by
dividing an index of industry output by an index of combined inputs consumed in producing that output. Combined inputs include
capital, labor, and intermediate purchases.
The measure of capital input represents the
flow of services from the capital stock used
in production. It is developed from measures
of the net stock of physical assets—equipment, structures, land, and inventories. The
measure of intermediate purchases is a
combination of purchased materials, services,
fuels, and electricity.
Notes on the data
The industry measures are compiled from
data produced by the Bureau of Labor Statistics and the Census Bureau, with additional
data supplied by other government agencies,
trade associations, and other sources.
FOR ADDITIONAL INFORMATION on this
series, contact the Division of Industry Productivity Studies: (202) 691–5618, or visit the
Web site at: www.bls.gov/lpc/home.htm
International Comparisons
(Tables 51–53)
Labor force and unemployment
Description of the series
Tables 51 and 52 present comparative
measures of the labor force, employment,
and unemployment approximating U.S.
concepts for the United States, Canada,
Australia, Japan, and six European countries.
The Bureau adjusts the figures for these
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 provide
a better basis for international comparisons than the figures regularly published
by each country. For further information
on adjustments and comparability issues,
see Constance Sorrentino, “International
unemployment rates: how comparable are
they?” Monthly Labor Review, June 2000,
pp. 3–20, available on the Internet at www.
bls.gov/opub/mlr/2000/06/art1full.pdf.
Definitions
For the principal U.S. definitions of the labor
force, employment, and unemployment, see
the Notes section on Employment and Unemployment Data: Household survey data.
Notes on the data
Foreign country data are adjusted as closely
as possible to the U.S. definitions. Primary
areas of adjustment address conceptual differences in upper age limits and defini-
tions of employment and unemployment,
provided that reliable data are available to
make these adjustments. Adjustments are
made where applicable to include employed
and unemployed persons above upper age
limits; some European countries do not
include persons older than age 64 in their
labor force measures, because a large portion
of this population has retired. Adjustments
are made to exclude active duty military
from employment figures, although a small
number of career military may be included
in some European countries. Adjustments
are made to exclude unpaid family workers
who worked fewer than 15 hours per week
from employment figures; U.S. concepts do
not include them in employment, whereas
most foreign countries include all unpaid
family workers regardless of the number
of hours worked. Adjustments are made
to include full-time students seeking work
and available for work as unemployed when
they are classified as not in the labor force.
Where possible, lower age limits are based
on the age at which compulsory schooling
ends in each country, rather than based on
the U.S. standard of 16. Lower age limits
have ranged between 13 and 16 over the years
covered; currently, the lower age limits are
either 15 or 16 in all 10 countries.
Some adjustments for comparability are
not made because data are unavailable for
adjustment purposes. For example, no adjustments to unemployment are usually made for
deviations from U.S. concepts in the treatment
of persons waiting to start a new job or passive
jobseekers. These conceptual differences have
little impact on the measures. Furthermore,
BLS studies have concluded that no adjustments should be made for persons on layoff
who are counted as employed in some countries because of their strong job attachment as
evidenced by, for example, payment of salary
or the existence of a recall date. In the United
States, persons on layoff have weaker job attachment and are classified as unemployed.
The annual labor force measures are obtained from monthly, quarterly, or continuous household surveys and may be calculated
as averages of monthly or quarterly data.
Quarterly and monthly unemployment
rates are based on household surveys. For
some countries, they are calculated by applying annual adjustment factors to current published data and, therefore, are less
precise indicators of unemployment under
U.S. concepts than the annual figures. The
labor force measures may have breaks in
series over time due to changes in surveys,
sources, or estimation methods. Breaks are
noted in data tables.
For up-to-date information on adjustments and breaks in series, see the Technical
Monthly Labor Review • September 2008
67
Current Labor Statistics
Notes of Comparative Civilian Labor Force
Statistics, 10 Countries, on the Internet at
www.bls.gov/fls/flscomparelf.htm, and the
Notes of Unemployment rates in 10 countries,
civilian labor force basis, approximating U.S.
concepts, seasonally adjusted, on the Internet
at www.bls.gov/fls/flsjec.pdf.
F OR ADDITIONAL INFORMATION on
this series, contact the Division of Foreign
Labor Statistics: (202) 691-5654 or flshelp@
bls.gov.
Manufacturing productivity
and labor costs
Description of the series
Table 53 presents comparative indexes of
manufacturing output per hour (labor productivity), output, total hours, compensation
per hour, and unit labor costs for the United
States, Australia, Canada, Japan, the Republic
of Korea, Taiwan, and 10 European countries.
These measures are trend comparisons—that
is, series that measure changes over time—
rather than level comparisons. BLS does
not recommend using these series for level
comparisons because of technical problems.
BLS constructs the comparative indexes
from three basic aggregate measures—output, total labor hours, and total compensation. The hours and compensation measures
refer to employees (wage and salary earners)
in Belgium and Taiwan. For all other economies, the measures refer to all employed
persons, including employees, self-employed
persons, and unpaid family workers.
The data for recent years are based on the
United Nations System of National Accounts
1993 (SNA 93). Manufacturing is generally defined according to the International Standard
Industrial Classification (ISIC). However, the
measures for France include parts of mining
as well. For the United States and Canada, it
is defined according to the North American
Industry Classification System (NAICS 97).
Definitions
Output. For most economies, the output
measures are real value added in manufacturing from national accounts. However, output for Japan prior to 1970 and
for the Netherlands prior to 1960 are
indexes of industrial production. The
manufacturing value added measures for the
United Kingdom are essentially identical
to their indexes of industrial production.
For United States, the output measure for
the manufacturing sector is a chain-weighted
68
Monthly Labor Review • September 2008
index of real gross product originating (deflated value added) produced by the Bureau
of Economic Analysis of the U.S. Department of Commerce. Most of the other
economies now also use chain-weighted
as opposed to a fixed-year weights that are
periodically updated.
To preserve the comparability of the U.S.
measures with those of other economies,
BLS uses gross product originating in manufacturing for the United States. The gross
product originating series differs from the
manufacturing output series that BLS publishes in its quarterly news releases on 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 hours refer to hours worked in all
economies. The measures are developed from
statistics of manufacturing employment and
average hours. For most other economies, recent years’ aggregate hours series are obtained
from national statistical offices, usually from
national accounts. However, for some economies and for earlier years, BLS calculates the
aggregate hours series using employment
figures published with the national accounts,
or other comprehensive employment series,
and data on average hours worked.
Hourly compensation is total compensation divided by total hours. Total compensation includes all payments in cash or in-kind
made directly to employees plus employer
expenditures for legally required insurance
programs and contractual and private benefit plans. For Australia, Canada, France,
and Sweden, compensation is increased
to account for important taxes on payroll
or employment. For the United Kingdom,
compensation is reduced between 1967 and
1991 to account for subsidies.
Labor productivity is defined as real
output per hour worked. Although the labor
productivity measure presented in this release
relates output to the hours worked of persons
employed in manufacturing, it does not measure
the specific contributions of labor as a single
factor of production. Rather, it reflects the joint
effects of many influences, including new technology, capital investment, capacity utilization,
energy use, and managerial skills, as well as the
skills and efforts of the workforce.
Unit labor costs are defined as the cost
of labor input required to produce one unit
of output. They are computed as compensation in nominal terms divided by real output.
Unit labor costs can also be computed by
dividing hourly compensation by output per
hour, that is, by labor productivity.
Notes on the data
The measures for recent years may be
based on current indicators of manufacturing output (such as industrial production
indexes), employment, average hours, and
hourly compensation until national accounts and other statistics used for the
long-term measures become available.
F OR ADDITIONAL INFORMATION on
this series, go to http://www.bls.gov/news.
release/prod4.toc.htm or contact the Division of Foreign Labor Statistics at (202)
691–5654.
Occupational Injury
and Illness Data
(Tables 54–55)
Survey of Occupational Injuries
and Illnesses
Description of the series
The Survey of Occupational Injuries and
Illnesses collects data from employers about
their workers’ job-related nonfatal injuries
and illnesses. The information that employers
provide is based on records that they maintain
under 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 cooperative
program with an independent sample selected for each participating State. A stratified
random sample with a Neyman allocation
is selected to represent all private industries
in the State. The survey is stratified by Standard Industrial Classification and size of
employment.
Definitions
Under the Occupational Safety and Health
Act, employers maintain records of nonfatal
work-related injuries and illnesses that involve one or more of the following: loss of
consciousness, restriction of work or motion,
transfer to another job, or medical treatment
other than first aid.
Occupational 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
condition or disorder, other than one resulting from an occupational injury, caused by
exposure to factors associated with employment. It includes acute and chronic illnesses
or disease which may be caused by inhalation,
absorption, ingestion, or direct contact.
Lost workday injuries and illnesses are
cases that involve days away from work, or
days of restricted work activity, or both.
Lost workdays 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,
because of an occupational injury or illness.
BLS measures of the number and incidence
rate of lost workdays were discontinued beginning with the 1993 survey. The number
of days away from work or days of restricted
work activity does not include the day of injury
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.
Incidence rates are computed as the
number of injuries and/or illnesses or lost
work days per 100 full-time workers.
Notes on the data
The definitions of occupational injuries and
illnesses are from Recordkeeping Guidelines
for Occupational Injuries and Illnesses (U.S.
Department of Labor, Bureau of Labor Statistics, September 1986).
Estimates are made for industries and employment 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 separately for injuries.
Illness data are available for seven categories:
occupational skin diseases or disorders, dust
diseases of the lungs, respiratory conditions
due to toxic agents, poisoning (systemic
effects of toxic agents), disorders due to
physical agents (other than toxic materials),
disorders associated with repeated trauma,
and all other occupational illnesses.
The survey continues to measure the
number of new work-related illness cases
which are recognized, diagnosed, and reported during 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 recognized and reported. These
long-term latent illnesses are believed to be
understated in the survey’s illness measure. In
contrast, the overwhelming majority of the
reported new illnesses are those which are
easier to directly relate to workplace activity
(for example, contact dermatitis and carpal
tunnel syndrome).
Most of the estimates are in the form
of incidence rates, defined as the number
of injuries and illnesses per 100 equivalent
full-time workers. For this purpose, 200,000
employee hours represent 100 employee years
(2,000 hours per employee). Full detail on the
available measures is presented in the annual
bulletin, Occupational Injuries and Illnesses:
Counts, Rates, and Characteristics.
Comparable data for more than 40 States
and territories are available from the bls
Office of Safety, Health and Working Conditions. Many of these States publish data
on State and local government employees in
addition to private industry data.
Mining and railroad data are furnished to
BLS by the Mine Safety and Health Administration and the Federal Railroad Administration. Data from these organizations are
included in both the national and State data
published annually.
With the 1992 survey, BLS began publishing details on serious, nonfatal incidents
resulting in days away from work. Included
are some major characteristics of the injured
and ill workers, such as occupation, age, gender, race, and length of service, as well as the
circumstances of their injuries and illnesses
(nature of the disabling condition, part of
body affected, event and exposure, and the
source directly producing the condition). In
general, these data are available nationwide
for detailed industries and for individual
States at more aggregated industry levels.
FOR ADDITIONAL INFORMATION on occupational injuries and illnesses, contact the
Office of Occupational Safety, Health and
Working Conditions at (202) 691–6180, or
access the Internet at: www.bls. gov/iif/
Census of Fatal
Occupational Injuries
The Census of Fatal Occupational Injuries
compiles a complete roster of fatal job-related 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 Administration and Mine Safety
and Health Administration records, medical
examiner and autopsy reports, media accounts, State motor vehicle fatality records,
and follow-up questionnaires to employers.
In addition to private wage and salary
workers, the self-employed, family members, and Federal, State, and local government workers are covered by the program.
To be included in the fatality census, the
decedent must have been employed (that is
working for pay, compensation, or profit)
at the time of the event, engaged in a legal
work activity, or present at the site of the
incident as a requirement of his or her job.
Definition
A fatal work injury is any intentional or
unintentional wound or damage to the body
resulting in death from acute exposure to
energy, such as heat or electricity, or kinetic
energy from a crash, or from the absence of
such essentials 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 work-related illnesses,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
injured worker, the fatal incident, and the
machinery or equipment involved. Summary worker demographic data and event
characteristics are included in a national news
release 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 of the national news release.
F OR ADDITIONAL INFORMATION on
the Census of Fatal Occupational Injuries
contact the BLS Office of Safety, Health,
and Working Conditions at (202) 691–
6175, or the Internet at: www.bls.gov/iif/
Monthly Labor Review • September 2008
69
Current Labor Statistics: Comparative Indicators
1. Labor market indicators
Selected indicators
2006
2006
2007
II
III
2007
IV
I
II
2008
III
IV
I
II
Employment data
Employment status of the civilian noninstitutional
population (household survey):
1
Labor force participation rate........................................................
Employment-population ratio........................................................
Unemployment rate………………………………………………….…
Men………………………………………………..…….….…………
16 to 24 years...........................................................................
25 years and older....................................................................
Women……………………………………………….….……………
16 to 24 years...........................................................................
25 years and older....................................................................
Employment, nonfarm (payroll data), in thousands:
66.2
63.1
4.6
4.6
11.2
3.5
4.6
9.7
3.7
66.0
63.0
4.6
4.7
11.6
3.6
4.5
9.4
3.6
66.2
63.1
4.7
4.7
11.2
3.6
4.6
9.3
3.8
66.2
63.1
4.7
4.6
11.4
3.5
4.7
10.1
3.8
66.3
63.4
4.4
4.5
11.0
3.3
4.4
9.7
3.5
66.2
63.2
4.5
4.6
10.8
3.6
4.4
9.0
3.5
66.0
63.0
4.5
4.6
11.5
3.5
4.4
9.0
3.6
66.0
62.9
4.7
4.8
11.8
3.6
4.6
9.8
3.7
66.0
62.8
4.8
4.9
12.2
3.7
4.7
9.9
3.8
66.0
62.7
4.9
5.0
12.7
3.8
4.8
10.0
3.9
66.1
62.6
5.3
5.5
13.3
4.2
5.1
11.0
4.1
1
Total nonfarm…………………….................................................... 136,086
Total private....................................................................... 114,113
137,626
115,423
135,910
113,996
136,528
114,472
136,982
114,899
137,310
115,167
137,625
115,423
137,837
115,610
138,078
115,759
137,831
115,454
137,640
115,181
22,531
Manufacturing………….………………..………………………… 14,155
22,221
13,883
22,570
14,200
22,564
14,138
22,436
14,033
22,362
13,953
22,267
13,890
22,138
13,822
21,976
13,772
21,737
13,644
21,505
13,537
Service-providing……………………………………………….…………..…113,556
115,405
113,340
113,964
114,546
114,948
115,358
115,699
116,102
116,094
116,135
Goods-producing ……………………………………………….…………..
Average hours:
Total private........................................…………..........................
Manufacturing………...……………………………………………
Overtime……..………….………………...………………………
33.9
41.1
4.4
33.8
41.2
4.2
33.9
41.2
4.5
33.8
41.3
4.4
33.9
41.1
4.2
33.9
41.2
4.1
33.9
41.4
4.1
33.8
41.4
4.2
33.8
41.1
4.0
33.8
41.2
4.0
33.7
40.8
3.9
Civilian nonfarm ……………………………….…………………………….……
3.3
3.3
.9
1.1
.6
.9
.8
1.0
.6
.8
.7
Private nonfarm……………...............………...............................
3.2
3.0
.9
.8
.7
.8
.9
.8
.6
.9
.7
2.5
2.4
1.0
.7
.5
.4
1.0
.5
.6
1.0
.7
1, 2, 3
Employment Cost Index
Total compensation:
4
5
Goods-producing ……………………………………………….…………
5
Service-providing ……………………………………………….…………
State and local government ……………….………………………
Workers by bargaining status (private nonfarm):
Union……………………………………………………………………
Nonunion…………………………………………………………………
1
3.4
3.2
.8
.9
.7
.9
.9
.9
.6
.9
.7
4.1
4.1
.4
2.3
.9
1.0
.6
1.8
.7
.5
.5
3.0
3.2
2.0
3.2
1.3
.8
.6
.9
.6
.6
-.3
1.0
1.2
.9
.5
.8
.7
.6
.8
.9
.8
.7
Quarterly data seasonally adjusted.
Annual changes are December-to-December changes. Quarterly changes
are calculated using the last month of each quarter.
3
The Employment Cost Index data reflect the conversion to the 2002 North
American Classification System (NAICS) and the 2000 Standard Occupational
Classification (SOC) system. The NAICS and SOC data shown prior to 2006 are
for informational purposes only. Series based on NAICS and SOC became the
official BLS estimates starting in March 2006.
2
70
Monthly Labor Review • September 2008
4
Excludes Federal and private household workers.
Goods-producing industries include mining, construction, and manufacturing. Serviceproviding industries include all other private sector industries.
5
NOTE: Beginning in January 2003, household survey data reflect revised population
controls. Nonfarm data reflect the conversion to the 2002 version of the North
American Industry Classification System (NAICS), replacing the Standard Industrial
Classification (SIC) system. NAICS-based data by industry are not comparable with SIC
based data.
2. Annual and quarterly percent changes in compensation, prices, and productivity
Selected measures
2006
2006
2007
II
2007
III
IV
I
II
2008
III
IV
I
II
1, 2, 3
Compensation data
Employment Cost Index—compensation:
Civilian nonfarm...................................................................
Private nonfarm...............................................................
Employment Cost Index—wages and salaries:
Civilian nonfarm……………………………………………….
Private nonfarm...............................................................
Price data
3.3
3.2
3.3
3.0
0.9
.9
1.1
.8
0.6
.7
0.9
.8
0.8
.9
1.0
.8
0.6
.6
0.8
.9
0.7
.7
3.2
3.2
3.4
3.3
.8
1.0
1.1
.8
.6
.7
1.1
1.1
.7
.8
1.0
.9
.7
.6
.8
.9
.7
.7
3.2
2.8
1.6
.0
-.5
1.8
1.5
.1
.7
1.7
2.5
3.0
3.5
1.6
6.5
1.4
3.9
4.5
1.8
4.0
12.2
1.7
2.1
.2
3.0
1.8
-.9
-1.3
.0
-.4
1.2
.1
-.2
1.3
-.8
4.0
2.2
2.8
.3
1.5
5.7
1.9
2.5
-.1
3.2
3.8
.1
.2
-.1
.1
-2.4
1.8
1.9
1.2
2.0
11.9
2.9
3.5
.9
4.8
16.0
4.0
5.2
.4
7.0
14.9
1.0
1.0
1.6
1.6
.8
.8
-1.5
-1.6
1.2
1.8
.2
.7
3.6
2.2
6.4
6.0
.9
1.8
2.2
2.6
2.3
2.2
1.3
-
-1.8
3.1
1.3
.7
2.1
2.9
.9
1.0
-
1
Consumer Price Index (All Urban Consumers): All Items......
Producer Price Index:
Finished goods.....................................................................
Finished consumer goods.................................................
Capital equipment……………………………………………
Intermediate materials, supplies, and components…………
Crude materials.....................................................................
4
Productivity data
Output per hour of all persons:
Business sector.....................................................................
Nonfarm business sector.......................................................
5
Nonfinancial corporations ……………….…………...………………
1
Annual changes are December-to-December changes. Quarterly changes are
calculated using the last month of each quarter. Compensation and price data are not
seasonally adjusted, and the price data are not compounded.
2
only. Series based on NAICS and SOC became the official BLS estimates starting in
March 2006.
4
Annual rates of change are computed by comparing annual averages. Quarterly
percent changes reflect annual rates of change in quarterly indexes. The data are
seasonally adjusted.
Excludes Federal and private household workers.
3
The Employment Cost Index data reflect the conversion to the 2002 North American
Classification System (NAICS) and the 2000 Standard Occupational Classification (SOC)
system. The NAICS and SOC data shown prior to 2006 are for informational purposes
5
Output per hour of all employees.
3. Alternative measures of wage and compensation changes
Quarterly change
Components
2007
II
Four quarters ending—
2008
III
IV
I
2007
II
II
III
2008
IV
I
II
1
Average hourly compensation:
All persons, business sector..........................................................
All persons, nonfarm business sector...........................................
Employment Cost Index—compensation:
3.6
3.3
4.4
5.4
5.0
5.2
3.8
3.6
4.4
4.2
4.8
4.6
3.7
3.6
3.7
3.6
4.2
4.3
.8
.9
1.2
.9
.6
1.0
.8
.5
.8
1.8
.6
.6
.7
.6
.7
.8
.9
.8
.9
.5
.7
.7
.8
.7
.5
3.3
3.1
2.1
3.3
4.8
3.3
3.1
2.0
3.2
4.3
3.3
3.0
2.0
3.2
4.1
3.3
3.2
3.1
3.2
3.6
3.1
3.0
2.7
3.0
3.5
.7
.8
.9
.8
.5
1.0
.9
.7
.9
1.7
.7
.6
.3
.7
.7
.8
.9
.8
.9
.6
.7
.7
1.1
.7
.5
3.4
3.3
2.5
3.4
3.8
3.3
3.4
2.7
3.4
3.5
3.4
3.3
2.3
3.5
3.5
3.2
3.2
2.6
3.3
3.5
3.2
3.1
2.9
3.2
3.4
2
3
Civilian nonfarm ……….………………………………………….…………..…
Private nonfarm….......................................................................
Union…………..........................................................................
Nonunion…………....................................................................
State and local government….....................................................
Employment Cost Index—wages and salaries:
3
1.9
.8
2
Civilian nonfarm ……….………………………………………….…………..…
Private nonfarm….......................................................................
Union…………..........................................................................
Nonunion…………....................................................................
State and local government….....................................................
1
Seasonally adjusted. "Quarterly average" is percent change from a
quarter ago, at an annual rate.
2
The Employment Cost Index data reflect the conversion to the 2002
North American Classification System (NAICS) and the 2000 Standard
Occupational Classification (SOC) system. The NAICS and SOC data shown
prior to 2006 are for informational purposes only. Series based on NAICS
and SOC became the official BLS estimates starting in March 2006.
3
Excludes Federal and private household workers.
Monthly Labor Review • September 2008 71
Current Labor Statistics: Labor Force Data
4. Employment status of the population, by sex, age, race, and Hispanic origin, monthly data seasonally adjusted
[Numbers in thousands]
Employment status
2007
Annual average
2006
2007
July
Aug.
Sept.
Oct.
2008
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
July
TOTAL
Civilian noninstitutional
1
population ……………………. 228,815
Civilian labor force.............. 151,428
66.2
Participation rate...........
Employed........................ 144,427
Employment-pop63.1
ulation ratio 2……………
7,001
Unemployed...................
4.6
Unemployment rate.....
Not in the labor force........ 77,387
231,867 231,958 232,211 232,461 232,715 232,939 233,156 232,616 232,809 232,995 233,198 233,405 233,627 233,864
153,124 153,182 152,886 153,506 153,306 153,828 153,866 153,824 153,374 153,784 153,957 154,534 154,390 154,603
66.0
66.0
65.8
66.0
65.9
66.0
66.0
66.1
65.9
66.0
66.0
66.2
66.1
66.1
146,047 146,045 145,753 146,260 146,016 146,647 146,211 146,248 145,993 145,969 146,331 146,046 145,891 145,819
63.0
7,078
4.6
78,743
63.0
7,137
4.7
78,776
62.8
7,133
4.7
79,325
62.9
7,246
4.7
78,955
62.7
7,291
4.8
79,409
63.0
7,181
4.7
79,111
62.7
7,655
5.0
79,290
62.9
7,576
4.9
78,792
62.7
7,381
4.8
79,436
62.6
7,815
5.1
79,211
62.7
7,626
5.0
79,241
62.6
8,487
5.5
78,871
62.4
8,499
5.5
79,237
62.4
8,784
5.7
79,261
Men, 20 years and over
Civilian noninstitutional
1
population ……………………. 102,145
Civilian labor force.............. 77,562
75.9
Participation rate...........
Employed........................ 74,431
Employment-pop72.9
ulation ratio 2……………
3,131
Unemployed...................
4.0
Unemployment rate.....
Not in the labor force……… 24,584
103,555 103,598 103,723 103,847 103,973 104,087 104,197 103,866 103,961 104,052 104,152 104,258 104,371 104,490
78,596
78,619
78,526
78,689
78,664
79,075
79,004
78,864
78,748
78,838
78,776
78,878
79,037
79,327
75.9
75.9
75.7
75.8
75.7
76.0
75.8
75.9
75.7
75.8
75.6
75.7
75.7
75.9
75,337
75,324
75,274
75,332
75,274
75,834
75,499
75,427
75,362
75,197
75,148
75,001
74,998
75,094
72.8
3,259
4.1
24,959
72.7
3,295
4.2
24,979
72.6
3,252
4.1
25,197
72.5
3,357
4.3
25,158
72.4
3,389
4.3
25,309
72.9
3,240
4.1
25,012
72.5
3,505
4.4
25,193
72.6
3,437
4.4
25,002
72.5
3,386
4.3
25,213
72.3
3,641
4.6
25,214
72.2
3,628
4.6
25,376
71.9
3,877
4.9
25,380
71.9
4,038
5.1
25,334
71.9
4,234
5.3
25,163
Women, 20 years and over
Civilian noninstitutional
1
population ……………………. 109,992
Civilian labor force.............. 66,585
60.5
Participation rate...........
Employed........................ 63,834
Employment-pop58.0
ulation ratio 2……………
2,751
Unemployed...................
4.1
Unemployment rate.....
Not in the labor force……… 43,407
111,330 111,367 111,479 111,590 111,703 111,805 111,903 111,739 111,822 111,902 111,990 112,083 112,183 112,290
67,516
67,566
67,616
67,795
67,623
67,776
67,866
67,982
67,816
68,159
68,176
68,390
68,446
68,303
60.6
60.7
60.7
60.8
60.5
60.6
60.6
60.8
60.6
60.9
60.9
61.0
61.0
60.8
64,799
64,792
64,826
65,033
64,827
64,980
64,912
65,098
64,950
65,055
65,260
65,138
65,238
65,167
58.2
2,718
4.0
43,814
58.2
2,774
4.1
43,801
58.2
2,790
4.1
43,863
58.3
2,762
4.1
43,795
58.0
2,796
4.1
44,080
58.1
2,796
4.1
44,029
58.0
2,954
4.4
44,037
58.3
2,885
4.2
43,756
58.1
2,865
4.2
44,006
58.1
3,104
4.6
43,743
58.3
2,916
4.3
43,814
58.1
3,252
4.8
43,693
58.2
3,208
4.7
43,737
58.0
3,135
4.6
43,988
16,982
7,012
41.3
5,911
16,993
6,997
41.2
5,930
17,009
6,744
39.7
5,653
17,024
7,021
41.2
5,895
17,040
7,020
41.2
5,914
17,048
6,977
40.9
5,832
17,056
6,996
41.0
5,801
17,012
6,978
41.0
5,724
17,027
6,810
40.0
5,681
17,041
6,787
39.8
5,717
17,056
7,005
41.1
5,923
17,064
7,266
42.6
5,907
17,073
6,907
40.5
5,655
17,084
6,973
40.8
5,558
34.8
1,101
15.7
9,970
34.9
1,067
15.3
9,996
33.2
1,092
16.2
10,264
34.6
1,126
16.0
10,003
34.7
1,105
15.7
10,020
34.2
1,145
16.4
10,071
34.0
1,196
17.1
10,059
33.6
1,254
18.0
10,034
33.4
1,130
16.6
10,216
33.5
1,070
15.8
10,254
34.7
1,082
15.4
10,051
34.6
1,358
18.7
9,798
33.1
1,253
18.1
10,166
32.5
1,415
20.3
10,110
Both sexes, 16 to 19 years
Civilian noninstitutional
1
population ……………………. 16,678
7,281
Civilian labor force..............
43.7
Participation rate...........
6,162
Employed........................
Employment-pop36.9
ulation ratio 2……………
1,119
Unemployed...................
15.4
Unemployment rate.....
Not in the labor force……… 9,397
White3
Civilian noninstitutional
1
population ……………………. 186,264
Civilian labor force.............. 123,834
66.5
Participation rate...........
Employed........................ 118,833
Employment-pop63.8
ulation ratio 2……………
5,002
Unemployed...................
4.0
Unemployment rate.....
Not in the labor force……… 62,429
188,253 188,312 188,479 188,644 188,813 188,956 189,093 188,787 188,906 189,019 189,147 189,281 189,428 189,587
124,935 124,945 124,596 125,316 125,151 125,430 125,460 125,340 124,940 125,190 125,171 125,762 125,704 125,971
66.4
66.3
66.1
66.4
66.3
66.4
66.3
66.4
66.1
66.2
66.2
66.4
66.4
66.4
119,792 119,713 119,340 119,992 119,883 120,194 119,889 119,858 119,534 119,574 119,667 119,661 119,518 119,542
63.6
5,143
4.1
63,319
63.6
5,232
4.2
63,368
63.3
5,256
4.2
63,883
63.6
5,324
4.2
63,329
63.5
5,268
4.2
63,662
63.6
5,235
4.2
63,526
63.4
5,571
4.4
63,633
63.5
5,482
4.4
63,447
63.3
5,406
4.3
63,966
63.3
5,616
4.5
63,829
63.3
5,504
4.4
63,975
63.2
6,101
4.9
63,519
63.1
6,186
4.9
63,724
63.1
6,428
5.1
63,616
27,485
17,496
63.7
16,051
27,498
17,593
64.0
16,172
27,541
17,524
63.6
16,176
27,584
17,483
63.4
16,046
27,627
17,430
63.1
15,946
27,666
17,453
63.1
15,980
27,704
17,538
63.3
15,961
27,640
17,713
64.1
16,090
27,675
17,632
63.7
16,169
27,709
17,702
63.9
16,116
27,746
17,753
64.0
16,234
27,780
17,742
63.9
16,029
27,816
17,716
63.7
16,085
27,854
17,767
63.8
16,040
58.4
1,445
8.3
9,989
58.8
1,421
8.1
9,905
58.7
1,347
7.7
10,017
58.2
1,437
8.2
10,101
57.7
1,483
8.5
10,197
57.8
1,473
8.4
10,212
57.6
1,577
9.0
10,165
58.2
1,623
9.2
9,927
58.4
1,463
8.3
10,043
58.2
1,586
9.0
10,007
58.5
1,520
8.6
9,992
57.7
1,713
9.7
10,038
57.8
1,632
9.2
10,100
57.6
1,726
9.7
10,088
Black or African American3
Civilian noninstitutional
1
population ……………………. 27,007
Civilian labor force.............. 17,314
64.1
Participation rate...........
Employed........................ 15,765
Employment-pop58.4
ulation ratio 2……………
1,549
Unemployed...................
8.9
Unemployment rate.....
Not in the labor force……… 9,693
See footnotes at end of table.
72
Monthly Labor Review • September 2008
4. Continued—Employment status of the population, by sex, age, race, and Hispanic origin, monthly data seasonally adjusted
[Numbers in thousands]
Employment status
2007
Annual average
2006
2007
July
Aug.
31,383
21,602
68.8
20,382
31,423
21,613
68.8
20,345
31,520
21,781
69.1
20,578
64.9
1,220
5.6
9,781
64.7
1,269
5.9
9,809
65.3
1,204
5.5
9,738
Sept.
2008
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
July
31,617
21,872
69.2
20,619
31,714
21,778
68.7
20,554
31,809
21,872
68.8
20,623
31,903
21,888
68.6
20,517
31,643
21,698
68.6
20,320
31,732
21,755
68.6
20,401
31,820
21,775
68.4
20,269
31,911
21,917
68.7
20,404
31,998
22,102
69.1
20,573
32,087
22,131
69.0
20,420
32,179
22,071
68.6
20,435
65.2
1,253
5.7
9,745
64.8
1,224
5.6
9,936
64.8
1,249
5.7
9,938
64.3
1,371
6.3
10,016
64.2
1,378
6.3
9,946
64.3
1,354
6.2
9,977
63.7
1,507
6.9
10,045
63.9
1,512
6.9
9,994
64.3
1,529
6.9
9,896
63.6
1,711
7.7
9,956
63.5
1,636
7.4
10,108
Hispanic or Latino
ethnicity
Civilian noninstitutional
1
population ……………………. 30,103
Civilian labor force.............. 20,694
68.7
Participation rate...........
Employed........................ 19,613
Employment-pop65.2
ulation ratio 2……………
1,081
Unemployed...................
5.2
Unemployment rate.....
Not in the labor force ………… 9,409
1
The population figures are not seasonally adjusted.
Civilian employment as a percent of the civilian noninstitutional population.
3
Beginning in 2003, persons who selected this race group only; persons who
selected more than one race group are not included. Prior to 2003, persons who
reported more than one race were included in the group they identified as the main
race.
NOTE: Estimates for the above race groups (white and black or African American) do not
sum to totals because data are not presented for all races. In addition, persons whose
ethnicity is identified as Hispanic or Latino may be of any race and, therefore, are classified
by ethnicity as well as by race. Beginning in January 2003, data reflect revised population
controls used in the household survey.
2
5. Selected employment indicators, monthly data seasonally adjusted
[In thousands]
Selected categories
Annual average
2006
2007
2007
July
Aug.
Sept.
2008
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
July
Characteristic
Employed, 16 years and older.. 144,427 146,047 146,045 145,753 146,260 146,016 146,647 146,211 146,248 145,993 145,969 146,331 146,046 145,891 145,819
Men....................................... 77,502
78,254
78,237
78,066
78,229
78,177
78,604
78,260
78,157
78,113
77,948
78,038
77,954
77,794
77,823
Women............................…… 66,925
67,792
67,808
67,687
68,030
67,838
68,043
67,951
68,091
67,880
68,021
68,293
68,092
68,097
67,996
Married men, spouse
45,700
46,314
46,307
46,193
46,235
46,189
46,339
46,213
46,063
46,136
45,961
45,964
45,862
45,911
46,120
35,272
35,832
35,938
35,794
35,712
35,449
35,689
35,565
35,536
35,648
35,749
36,177
36,171
36,270
36,185
4,162
4,401
4,332
4,517
4,499
4,401
4,513
4,665
4,769
4,884
4,914
5,220
5,233
5,416
5,724
2,658
2,877
2,751
2,955
2,991
2,788
3,008
3,174
3,247
3,291
3,323
3,558
3,595
3,816
4,194
1,189
1,210
1,210
1,175
1,166
1,215
1,223
1,236
1,163
1,222
1,362
1,323
1,281
1,336
1,286
reasons……………………… 19,591
19,756
19,957
19,779
19,812
19,337
19,539
19,526
19,613
19,348
19,409
19,809
19,428
19,496
19,406
4,071
4,317
4,259
4,466
4,397
4,302
4,453
4,577
4,677
4,790
4,797
5,125
5,164
5,308
5,599
2,596
2,827
2,711
2,916
2,922
2,745
2,981
3,120
3,174
3,231
3,238
3,513
3,531
3,744
4,156
1,178
1,199
1,205
1,152
1,153
1,207
1,205
1,219
1,149
1,216
1,354
1,331
1,288
1,328
1,277
reasons.................………… 19,237
19,419
19,569
19,469
19,451
19,157
19,224
19,225
19,296
19,019
19,072
19,456
19,047
19,106
19,051
present................................
Married women, spouse
present................................
Persons at work part time1
All industries:
Part time for economic
reasons…………………….…
Slack work or business
conditions………….........
Could only find part-time
work………………………
Part time for noneconomic
Nonagricultural industries:
Part time for economic
reasons…………………….…
Slack work or business
conditions.......................
Could only find part-time
work………………………
Part time for noneconomic
1
Excludes persons "with a job but not at work" during the survey period for such reasons as vacation, illness, or industrial disputes.
NOTE: Beginning in January 2003, data reflect revised population controls used in the household survey.
Monthly Labor Review • September 2008 73
Current Labor Statistics: Labor Force Data
6. Selected unemployment indicators, monthly data seasonally adjusted
[Unemployment rates]
Annual average
Selected categories
2006
2007
2007
2008
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
July
Characteristic
Total, 16 years and older............................
Both sexes, 16 to 19 years.....................
Men, 20 years and older.........................
Women, 20 years and older...................
4.6
15.4
4.0
4.1
4.6
15.7
4.1
4.0
4.7
15.3
4.2
4.1
4.7
16.2
4.1
4.1
4.7
16.0
4.3
4.1
4.8
15.7
4.3
4.1
4.7
16.4
4.1
4.1
5.0
17.1
4.4
4.4
4.9
18.0
4.4
4.2
4.8
16.6
4.3
4.2
5.1
15.8
4.6
4.6
5.0
15.4
4.6
4.3
5.5
18.7
4.9
4.8
5.5
18.1
5.1
4.7
5.7
20.3
5.3
4.6
White, total 1………………………………
4.0
13.2
14.6
11.7
3.5
3.6
4.1
13.9
15.7
12.1
3.7
3.6
4.2
13.8
15.5
12.0
3.8
3.6
4.2
14.4
16.5
12.2
3.8
3.7
4.2
14.3
16.4
12.2
3.9
3.5
4.2
14.0
15.9
12.0
3.8
3.6
4.2
14.7
17.8
11.8
3.7
3.7
4.4
14.4
16.8
12.1
3.9
4.0
4.4
15.6
19.0
12.3
3.9
3.8
4.3
14.4
17.1
11.8
3.9
3.8
4.5
13.2
14.7
11.7
4.1
4.1
4.4
13.8
15.2
12.4
4.1
3.7
4.9
16.4
17.7
14.9
4.4
4.1
4.9
16.6
17.8
15.3
4.5
4.2
5.1
19.0
22.2
15.6
4.7
4.1
8.9
29.1
32.7
25.9
8.3
7.5
8.3
29.4
33.8
25.3
7.9
6.7
8.1
27.0
31.1
23.5
7.6
6.9
7.7
31.2
33.2
29.4
6.8
6.5
8.2
28.9
33.9
24.2
7.5
7.1
8.5
27.9
36.0
20.1
8.2
7.1
8.4
29.7
34.6
24.9
7.9
7.0
9.0
34.7
39.5
30.1
8.4
7.0
9.2
35.7
41.3
28.5
8.3
7.3
8.3
31.7
32.6
30.9
7.9
6.5
9.0
31.3
38.9
25.4
8.4
7.5
8.6
24.5
27.9
21.9
8.4
7.4
9.7
32.3
40.1
25.2
8.9
8.2
9.2
29.6
35.5
23.9
9.3
7.4
9.7
32.0
38.0
26.5
10.0
7.5
5.2
2.4
2.9
4.5
5.1
5.6
2.5
2.8
4.6
4.9
5.9
2.7
2.9
4.6
5.1
5.5
2.5
3.1
4.6
4.9
5.7
2.5
2.9
4.7
4.7
5.6
2.6
2.9
4.7
5.0
5.7
2.6
3.0
4.6
5.0
6.3
2.7
3.1
4.9
5.6
6.3
2.7
3.1
4.8
5.4
6.2
2.7
3.1
4.8
5.0
6.9
2.8
3.3
5.0
5.3
6.9
2.8
3.0
5.0
4.9
6.9
2.9
3.1
5.5
5.5
7.7
3.0
3.3
5.5
5.4
7.4
3.2
3.3
5.7
5.5
Both sexes, 16 to 19 years................
Men, 16 to 19 years........................
Women, 16 to 19 years..................
Men, 20 years and older....................
Women, 20 years and older..............
Black or African American, total 1………
Both sexes, 16 to 19 years................
Men, 16 to 19 years........................
Women, 16 to 19 years..................
Men, 20 years and older....................
Women, 20 years and older..............
Hispanic or Latino ethnicity………………
Married men, spouse present................
Married women, spouse present...........
Full-time workers...................................
Part-time workers..................................
Educational attainment2
Less than a high school diploma................
6.8
7.1
7.2
6.7
7.5
7.4
7.6
7.6
7.7
7.3
8.2
7.8
8.3
8.7
8.5
Some college or associate degree………..
4.3
3.6
4.4
3.6
4.5
3.6
4.4
3.7
4.6
3.4
4.6
3.5
4.5
3.3
4.7
3.7
4.6
3.6
4.7
3.7
5.1
3.8
5.0
3.9
5.2
4.3
5.1
4.2
5.2
4.5
Bachelor's degree and higher 4…………….
2.0
2.0
2.1
2.1
2.0
2.1
2.2
2.2
2.1
2.1
2.1
2.1
2.2
2.3
2.4
Feb.
Mar.
May
June
High school graduates, no college 3………
1
Beginning in 2003, persons who selected this race group only; persons who
selected more than one race group are not included. Prior to 2003, persons who
reported more than one race were included in the group they identified as the main
race.
2
Data refer to persons 25 years and older.
7. Duration of unemployment, monthly data seasonally adjusted
[Numbers in thousands]
Weeks of
unemployment
Less than 5 weeks...........................
5 to 14 weeks..................................
15 weeks and over..........................
15 to 26 weeks.............................
27 weeks and over.......................
Mean duration, in weeks...................
Median duration, in weeks...............
Annual average
2006
2,614
2,121
2,266
1,031
1,235
16.8
8.3
2007
2,542
2,232
2,303
1,061
1,243
16.8
8.5
2007
July
2,496
2,220
2,402
1,091
1,311
17.3
8.9
Aug.
2,610
2,201
2,375
1,124
1,252
16.9
8.6
Sept.
2,537
2,330
2,392
1,112
1,280
16.6
8.9
2008
Oct.
2,508
2,454
2,367
1,052
1,315
17.0
8.7
Nov.
2,633
2,157
2,398
1,014
1,384
17.2
8.7
NOTE: Beginning in January 2003, data reflect revised population controls used in the household survey.
74
Monthly Labor Review • September 2008
Dec.
2,793
2,330
2,520
1,182
1,338
16.6
8.4
Jan.
2,634
2,396
2,503
1,124
1,380
17.5
8.8
2,639
2,396
2,377
1,079
1,299
16.8
8.4
2,767
2,525
2,400
1,118
1,282
16.2
8.1
Apr.
2,484
2,495
2,626
1,272
1,353
16.9
9.3
3,244
2,469
2,773
1,223
1,550
16.6
8.3
2,712
2,999
2,916
1,328
1,587
17.5
10.0
July
2,835
2,823
3,118
1,440
1,678
17.1
9.7
8. Unemployed persons by reason for unemployment, monthly data seasonally adjusted
[Numbers in thousands]
Reason for
unemployment
Job losers 1…………………….…
On temporary layoff..............
Not on temporary layoff........
Job leavers..............................
Reentrants...............................
New entrants...........................
Annual average
2006
2007
2007
July
Aug.
Sept.
2008
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
July
3,321
921
2,400
827
2,237
616
3,515
976
2,539
793
2,142
627
3,629
983
2,646
823
2,082
602
3,632
981
2,652
794
2,076
603
3,622
963
2,660
839
2,154
685
3,731
1,064
2,668
790
2,103
709
3,609
979
2,630
783
2,160
669
3,857
975
2,882
798
2,343
697
3,796
1,040
2,756
830
2,201
667
3,854
971
2,883
769
2,112
648
4,154
1,056
3,098
781
2,117
681
4,014
1,099
2,915
850
2,134
624
4,282
1,113
3,169
870
2,460
828
4,370
1,077
3,292
833
2,498
748
4,407
1,037
3,370
861
2,705
811
47.4
13.2
34.3
11.8
32.0
8.8
49.7
13.8
35.9
11.2
30.3
8.9
50.8
13.8
37.1
11.5
29.2
8.4
51.1
13.8
37.3
11.2
29.2
8.5
49.6
13.2
36.4
11.5
29.5
9.4
50.9
14.5
36.4
10.8
28.7
9.7
50.0
13.6
36.4
10.8
29.9
9.3
50.1
12.7
37.5
10.4
30.4
9.1
50.7
13.9
36.8
11.1
29.4
8.9
52.2
13.2
39.0
10.4
28.6
8.8
53.7
13.7
40.1
10.1
27.4
8.8
52.7
14.4
38.2
11.2
28.0
8.2
50.7
13.2
37.5
10.3
29.1
9.8
51.7
12.7
39.0
9.9
29.6
8.9
50.2
11.8
38.4
9.8
30.8
9.2
2.4
.5
1.4
.4
2.4
.5
1.4
.4
2.4
.5
1.4
.4
2.4
.5
1.4
.5
2.3
.5
1.4
.4
2.5
.5
1.5
.5
2.5
.5
1.4
.4
2.5
.5
1.4
.4
2.7
.5
1.4
.4
2.6
.6
1.4
.4
2.8
.6
1.6
.5
2.8
.5
1.6
.5
2.9
.6
1.7
.5
Jan.
Feb.
Mar.
Apr.
Percent of unemployed
Job losers 1…………………….…
On temporary layoff...............
Not on temporary layoff.........
Job leavers...............................
Reentrants................................
New entrants............................
Percent of civilian
labor force
2.2
2.3
Job losers 1…………………….…
.5
.5
Job leavers...............................
1.5
1.4
Reentrants................................
.4
.4
New entrants............................
1
Includes persons who completed temporary jobs.
NOTE: Beginning in January 2003, data reflect revised population controls used in the household survey.
9. Unemployment rates by sex and age, monthly data seasonally adjusted
[Civilian workers]
Sex and age
Annual average
2006
2007
Total, 16 years and older..................
16 to 24 years...............................
16 to 19 years............................
16 to 17 years.........................
18 to 19 years.........................
20 to 24 years............................
25 years and older........................
25 to 54 years.........................
55 years and older..................
4.6
10.5
15.4
17.2
14.1
8.2
3.6
3.8
3.0
4.6
10.5
15.7
17.5
14.5
8.2
3.6
3.7
3.1
Men, 16 years and older.................
16 to 24 years.............................
16 to 19 years..........................
16 to 17 years.......................
18 to 19 years.......................
20 to 24 years..........................
25 years and older......................
25 to 54 years.......................
55 years and older................
4.6
11.2
16.9
18.6
15.7
8.7
3.5
3.6
3.0
Women, 16 years and older...........
16 to 24 years.............................
16 to 19 years..........................
16 to 17 years…………………
18 t0 19 years…………………
20 to 24 years..........................
25 years and older......................
25 to 54 years.......................
55 years and older 1…………
1
2007
July
Aug.
Sept.
4.7
10.6
15.3
17.0
14.0
8.5
3.7
3.8
3.2
4.7
10.8
16.2
18.6
14.6
8.4
3.6
3.8
3.2
4.7
11.0
16.0
18.6
14.3
8.8
3.7
3.8
3.1
4.7
11.6
17.6
19.4
16.5
8.9
3.6
3.7
3.2
4.7
11.5
16.9
19.3
15.4
9.2
3.6
3.7
3.4
4.7
11.6
18.0
21.7
15.2
8.9
3.6
3.7
3.4
4.6
9.7
13.8
15.9
12.4
7.6
3.7
3.9
4.5
9.4
13.8
15.7
12.5
7.3
3.6
3.8
4.6
9.6
13.6
14.8
12.6
7.7
3.8
3.9
2.9
3.0
3.5
2008
Oct.
Nov.
Dec.
4.8
10.8
15.7
17.5
14.3
8.6
3.7
3.8
3.1
4.7
10.7
16.4
19.0
14.4
8.0
3.7
3.8
3.0
5.0
11.8
17.1
19.6
15.4
9.4
3.9
4.1
3.2
4.9
11.7
18.0
20.4
15.9
8.7
3.8
3.9
3.2
4.8
11.3
16.6
18.3
15.5
8.9
3.8
3.9
3.2
5.1
11.3
15.8
18.6
14.0
9.3
4.0
4.2
3.4
5.0
11.0
15.4
19.7
13.2
8.9
3.9
4.2
3.0
May
5.5
13.0
18.7
21.2
17.5
10.4
4.1
4.4
3.3
June
5.5
12.6
18.1
23.3
15.6
10.1
4.3
4.5
3.3
July
5.7
13.4
20.3
24.9
17.3
10.2
4.4
4.6
3.6
4.9
12.2
18.3
21.9
16.2
9.5
3.7
3.8
3.3
4.9
12.0
18.1
19.0
16.8
9.3
3.7
3.8
3.1
4.7
11.8
19.5
21.4
17.8
8.6
3.6
3.7
3.1
5.1
12.8
19.8
22.1
18.4
9.8
3.8
4.0
3.2
5.1
13.1
21.8
24.0
19.5
9.4
3.8
4.0
3.2
4.9
12.5
18.7
20.5
18.0
9.9
3.7
3.8
3.2
5.2
12.5
17.8
22.0
15.2
10.3
4.0
4.1
3.3
5.1
12.0
16.9
22.2
14.5
9.9
4.0
4.3
3.0
5.6
14.1
20.7
23.3
19.6
11.0
4.2
4.4
3.4
5.7
13.8
19.9
26.2
17.1
11.2
4.3
4.6
3.4
6.1
15.2
23.4
29.4
19.9
11.6
4.6
4.9
3.7
4.6
10.0
14.4
15.5
13.9
7.9
3.7
3.9
4.5
9.8
13.7
15.6
12.3
7.9
3.7
3.8
4.6
9.6
13.3
16.1
11.6
7.7
3.7
3.9
4.6
9.4
13.4
17.1
10.7
7.4
3.8
4.0
4.9
10.7
14.4
17.3
12.3
8.8
3.9
4.1
4.7
10.1
14.2
17.2
12.1
8.0
3.8
3.9
4.7
9.9
14.5
16.2
12.8
7.7
3.8
4.0
5.0
10.0
13.8
15.5
12.8
8.1
4.1
4.2
4.8
9.8
14.0
17.5
11.8
7.7
3.9
4.0
5.3
11.9
16.6
19.0
15.2
9.6
4.1
4.4
5.2
11.2
16.3
20.3
13.9
8.8
4.2
4.4
5.2
11.4
17.1
20.4
14.6
8.7
4.2
4.3
3.4
3.0
3.0
2.8
2.9
3.4
3.3
3.4
2.8
2.8
3.4
4.3
Data are not seasonally adjusted.
NOTE: Beginning in January 2003, data reflect revised population controls used in the household survey.
Monthly Labor Review • September 2008 75
Current Labor Statistics: Labor Force Data
10. Unemployment rates by State, seasonally adjusted
June
2007
State
May
June
2007p
2008p
June
2007
State
June
2008p
Alabama............................…………………
Alaska........................................................
Arizona............................……………………
Arkansas....................................................
California............................…………………
3.5
6.1
3.6
5.4
5.3
4.7
6.9
4.4
5.1
6.8
4.7
6.7
4.8
5.0
7.0
Missouri………………………………………
Montana.....................................................
Nebraska............................…………………
Nevada......................................................
New Hampshire............................…………
5.0
3.1
3.1
4.8
3.6
6.0
4.2
3.2
6.2
4.0
5.7
4.1
3.3
6.4
4.0
Colorado....................................................
Connecticut............................………………
Delaware...................................................
District of Columbia............................……
Florida........................................................
3.7
4.4
3.3
5.7
4.0
4.9
5.4
4.1
6.6
5.6
5.1
5.5
4.2
6.3
5.5
New Jersey................................................
New Mexico............................………………
New York...................................................
North Carolina............................……………
North Dakota.............................................
4.2
3.5
4.6
4.7
3.2
5.4
3.8
5.2
5.9
3.3
5.3
3.9
5.3
5.9
3.2
Georgia............................…………………
Hawaii........................................................
Idaho............................………………………
Illinois.........................................................
Indiana............................……………………
4.4
2.6
2.7
5.0
4.5
5.7
3.6
3.6
6.4
5.3
5.6
3.8
3.8
6.8
5.9
Ohio............................………………………
Oklahoma..................................................
Oregon............................……………………
Pennsylvania.............................................
Rhode Island............................……………
5.7
4.4
5.2
4.3
5.0
6.3
3.5
5.6
5.2
7.2
6.6
3.9
5.5
5.2
7.5
Iowa............................………………………
Kansas.......................................................
Kentucky............................…………………
Louisiana...................................................
Maine............................……………………
3.8
4.1
5.5
3.7
4.7
3.9
4.6
6.2
4.0
5.4
4.0
4.3
6.3
3.8
5.3
South Carolina............................…………
South Dakota.............................................
Tennessee............................………………
Texas.........................................................
Utah............................………………………
5.7
2.9
4.6
4.3
2.7
6.5
2.9
6.4
4.5
3.2
6.1
2.8
6.5
4.4
3.3
Maryland............................…………………
Massachusetts...........................................
Michigan............................…………………
Minnesota..................................................
Mississippi............................………………
3.6
4.5
7.1
4.5
6.3
4.0
4.9
8.5
5.4
6.9
4.0
5.2
8.5
5.3
7.0
Vermont............................…………………
Virginia.......................................................
Washington............................………………
West Virginia.............................................
Wisconsin............................………………
Wyoming....................................................
3.8
3.0
4.5
4.5
4.8
3.1
4.9
3.9
5.3
5.3
4.4
2.9
4.7
4.0
5.4
5.3
4.6
3.2
p
= preliminary
11. Employment of workers on nonfarm payrolls by State, seasonally adjusted
State
June
2007
May
June
2007p
2008p
State
June
2007
May
June
2007p
2008p
Alabama............................………… 2,182,845 2,206,959 2,193,795
Alaska.............................................
352,104
360,020
359,753
Arizona............................…………… 3,021,368 3,068,807 3,071,144
Arkansas........................................ 1,366,002 1,383,946 1,374,363
California............................………… 18,182,148 18,446,229 18,431,325
Missouri……………………………… 3,030,362
Montana.........................................
501,499
Nebraska............................…………
985,015
Nevada........................................... 1,334,388
New Hampshire............................…
738,169
3,031,728
503,998
996,099
1,394,653
745,382
3,013,754
504,237
994,983
1,394,472
746,147
Colorado......................................... 2,701,057
Connecticut............................……… 1,861,099
Delaware........................................
442,229
District of Columbia........................
323,288
Florida............................................ 9,135,410
2,765,873
1,886,487
446,064
331,839
9,263,932
2,759,853
1,886,827
446,101
328,482
9,250,317
New Jersey.....................................
New Mexico............................……
New York........................................
North Carolina............................…
North Dakota..................................
4,467,625
942,437
9,528,910
4,526,537
365,424
4,516,789
949,666
9,590,326
4,561,644
373,012
4,505,006
951,334
9,620,555
4,559,713
372,443
Georgia............................………… 4,811,005
Hawaii.............................................
649,855
Idaho............................……………
755,181
Illinois............................................. 6,705,295
Indiana............................…………… 3,208,264
4,901,799
663,369
755,212
6,824,185
3,229,677
4,889,808
663,245
752,324
6,775,620
3,219,283
Ohio............................………………
Oklahoma.......................................
Oregon............................……………
Pennsylvania..................................
Rhode Island............................……
5,980,866
1,734,455
1,927,115
6,297,400
577,971
6,005,619
1,735,085
1,945,592
6,405,503
571,560
5,988,368
1,733,393
1,938,370
6,394,738
572,128
Iowa............................………………
Kansas...........................................
Kentucky............................…………
Louisiana........................................
Maine............................……………
1,659,989
1,479,438
2,045,058
1,989,101
703,976
1,679,525
1,494,578
2,047,456
2,008,102
708,936
1,672,261
1,491,211
2,041,828
2,012,118
710,175
South Carolina............................… 2,133,783 2,150,865 2,142,982
South Dakota..................................
442,728
444,744
444,627
Tennessee............................……… 3,033,878 3,062,538 3,043,947
Texas.............................................. 11,484,815 11,712,220 11,682,351
Utah............................……………… 1,360,251 1,388,270 1,380,611
Maryland............................…………
Massachusetts...............................
Michigan............................…………
Minnesota.......................................
Mississippi............................………
2,975,302
3,409,437
5,023,547
2,931,395
1,311,772
3,017,148
3,391,913
5,007,445
2,951,882
1,341,915
3,012,875
3,409,561
4,990,167
2,935,404
1,327,847
Vermont............................…………
353,877
Virginia........................................... 4,051,667
Washington............................……… 3,402,395
West Virginia..................................
808,350
Wisconsin............................……… 3,087,244
Wyoming........................................
287,901
NOTE: Some data in this table may differ from data published elsewhere because of the continual updating of the database.
p
76
May
2007p
= preliminary
Monthly Labor Review • September 2008
352,292
4,125,326
3,451,292
816,375
3,089,857
290,173
353,420
4,124,453
3,449,748
813,277
3,078,458
290,369
12. Employment of workers on nonfarm payrolls by industry, monthly data seasonally adjusted
[In thousands]
Industry
Annual average
2006
TOTAL NONFARM................. 136,086
TOTAL PRIVATE........................ 114,113
2007
2007
July
Aug.
Sept.
2008
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
Junep
Julyp
137,623 137,682 137,756 137,837 137,977 138,037 138,078 138,002 137,919 137,831 137,764 137,717 137,666 137,615
115,420 115,512 115,544 115,610 115,715 115,759 115,745 115,666 115,557 115,454 115,363 115,264 115,170 115,094
22,531
22,221
22,242
22,176
22,138
22,101
22,049
21,976
21,907
21,816
21,737
21,628
21,577
21,500
21,454
684
64.4
619.7
134.5
1
220.3
Mining, except oil and gas ……
78.0
Coal mining……………………
Support activities for mining……
264.9
7,691
Construction................................
Construction of buildings........... 1,804.9
985.1
Heavy and civil engineering……
Speciality trade contractors....... 4,901.1
Manufacturing.............................. 14,155
Production workers................ 10,137
8,981
Durable goods...........................
6,355
Production workers................
558.8
Wood products..........................
509.6
Nonmetallic mineral products
464.0
Primary metals..........................
Fabricated metal products......... 1,553.1
1,183.2
Machinery……….....................
Computer and electronic
723
60.8
662.1
146.0
224.5
77.6
291.6
7,614
1,761.0
1,001.2
4,851.9
13,884
9,979
8,816
6,257
519.7
503.4
456.0
1,563.3
1,188.2
726
59.9
666.3
146.3
225.4
77.4
294.6
7,632
1,765.3
1,002.3
4,863.9
13,884
9,985
8,817
6,258
523.4
504.4
456.4
1,564.2
1,192.5
727
59.5
667.2
147.0
226.4
77.6
293.8
7,605
1,751.2
999.0
4,854.7
13,844
9,956
8,792
6,239
518.5
501.2
452.7
1,562.8
1,187.5
727
59.7
667.4
147.3
226.7
78.0
293.4
7,589
1,749.4
998.8
4,840.3
13,822
9,958
8,778
6,245
513.1
501.0
451.6
1,565.0
1,186.2
727
59.1
667.8
148.9
226.9
78.1
292.0
7,577
1,736.6
999.5
4,841.3
13,797
9,934
8,761
6,232
511.8
500.9
451.5
1,568.0
1,189.0
735
59.9
675.0
152.3
226.0
78.7
296.7
7,520
1,716.4
999.0
4,804.8
13,794
9,944
8,763
6,242
509.0
499.5
452.6
1,565.6
1,189.9
739
60.6
677.9
153.1
225.2
78.3
299.6
7,465
1,702.4
993.8
4,768.4
13,772
9,933
8,739
6,220
507.2
496.4
452.2
1,562.7
1,191.0
744
60.7
683.2
154.5
227.0
78.6
301.7
7,426
1,690.2
984.6
4,750.8
13,737
9,922
8,718
6,214
503.5
494.4
452.3
1,560.9
1,193.8
744
60.2
684.0
153.8
225.7
78.7
304.5
7,382
1,673.0
977.6
4,731.8
13,690
9,879
8,685
6,182
498.6
492.2
451.4
1,557.1
1,191.7
750
60.1
689.7
155.2
226.2
79.2
308.3
7,343
1,668.2
976.9
4,697.5
13,644
9,847
8,652
6,152
492.9
487.7
451.3
1,556.9
1,195.1
752
60.8
690.9
154.2
225.8
79.3
310.9
7,284
1,648.2
967.4
4,668.0
13,592
9,799
8,607
6,112
490.9
486.3
450.1
1,544.1
1,193.1
760
59.5
700.6
158.3
229.6
80.5
312.7
7,246
1,634.9
965.3
4,645.6
13,571
9,784
8,594
6,100
482.4
482.1
448.7
1,544.2
1,195.1
767
57.4
709.6
160.5
230.4
80.8
318.7
7,197
1,623.9
959.9
4,613.3
13,536
9,749
8,575
6,078
477.6
479.6
448.1
1,539.2
1,195.6
778
57.9
719.9
162.8
231.7
80.7
325.4
7,175
1,622.8
958.6
4,593.6
13,501
9,731
8,558
6,070
473.7
477.5
447.4
1,537.4
1,201.7
products 1……………………… 1,307.5
Computer and peripheral
1,271.9
1,268.3
1,265.6
1,260.5
1,256.5
1,260.5
1,257.6
1,256.3
1,251.9
1,254.1
1,253.8
1,250.1
1,246.1
1,243.6
GOODS-PRODUCING………………
Natural resources and
mining…………..……….......……
Logging....................................
Mining..........................................
Oil and gas extraction……………
equipment..............................
Communications equipment…
196.2
136.2
186.9
128.6
186.2
127.5
186.1
128.5
185.9
128.5
185.1
128.1
185.5
129.5
185.4
129.0
184.9
129.5
185.9
128.7
186.0
129.4
186.7
130.9
186.2
130.4
184.3
131.5
185.6
129.6
Semiconductors and
electronic components..........
Electronic instruments……….
457.9
444.5
444.5
444.0
443.7
443.1
439.9
442.5
437.4
442.0
435.8
441.9
437.0
443.0
434.9
443.7
433.5
444.3
429.7
442.9
428.7
446.2
426.7
445.7
424.2
445.6
422.1
444.6
421.9
443.4
Electrical equipment and
appliances...............................
Transportation equipment.........
432.7
1,768.9
427.2
1,710.9
427.7
1,704.7
426.1
1,705.7
426.0
1,706.1
427.2
1,689.3
426.6
1,693.5
423.8
1,684.7
421.6
1,678.1
420.8
1,672.0
419.9
1,651.1
421.5
1,630.6
422.1
1,636.8
422.7
1,637.1
423.5
1,628.8
Furniture and related
products.....……………………… 560.1
643.7
Miscellaneous manufacturing
Nondurable goods.....................
5,174
Production workers................
3,782
Food manufacturing.................. 1,479.4
534.5
641.0
5,068
3,723
1,481.3
536.1
639.5
5,067
3,727
1,488.8
533.0
638.8
5,052
3,717
1,480.6
530.6
637.6
5,044
3,713
1,476.0
528.3
638.2
5,036
3,702
1,478.6
527.0
638.8
5,031
3,702
1,477.9
523.8
639.9
5,033
3,713
1,486.3
520.4
636.4
5,019
3,708
1,483.2
516.0
633.3
5,005
3,697
1,482.7
511.2
632.0
4,992
3,695
1,477.0
506.4
630.2
4,985
3,687
1,473.8
503.5
629.1
4,977
3,684
1,473.5
501.6
627.0
4,961
3,671
1,471.8
499.3
624.9
4,943
3,661
1,467.6
Beverages and tobacco
products…………………………
Textile mills………………………
Textile product mills...................
Apparel………………………….
Leather and allied products.......
Paper and paper products.........
194.2
195.0
166.7
232.4
36.8
470.5
195.7
169.9
158.4
213.0
33.9
460.6
197.0
168.1
157.1
212.8
33.1
459.8
196.1
166.4
156.9
211.3
33.3
459.1
195.7
164.8
156.3
209.2
34.0
459.0
195.2
164.9
155.9
206.8
33.7
459.2
194.3
164.9
157.2
206.4
34.1
458.6
192.0
163.0
155.7
204.8
33.7
460.3
191.1
162.0
154.0
202.0
34.5
459.0
189.3
161.4
153.0
200.6
33.5
457.8
190.8
158.7
153.3
198.1
33.5
457.9
193.3
156.4
152.2
198.0
33.9
458.4
193.7
155.1
151.0
196.6
33.7
458.1
193.0
152.0
149.2
195.5
34.3
456.8
193.0
149.4
148.0
194.4
33.4
456.6
Printing and related support
activities…………………………
Petroleum and coal products.....
Chemicals..................................
Plastics and rubber products..
634.4
113.2
865.9
785.5
624.2
113.4
862.9
754.0
623.3
112.5
862.5
752.4
621.0
112.5
864.2
750.2
623.0
112.9
864.3
748.4
622.2
112.6
860.7
745.9
622.0
112.1
860.5
743.0
619.5
111.7
862.0
744.2
620.1
112.2
861.2
739.7
614.6
112.5
861.0
738.7
614.2
112.2
860.5
735.6
611.7
112.2
861.3
734.1
607.3
113.4
861.6
732.8
601.7
114.0
861.3
731.1
598.5
114.6
859.2
728.2
SERVICE-PROVIDING...................
113,556
115,402 115,440 115,580 115,699 115,876 115,988 116,102 116,095 116,103 116,094 116,136 116,140 116,166 116,161
PRIVATE SERVICEPROVIDING……………………… 91,582
Trade, transportation,
and utilities................................
Wholesale trade.........................
Durable goods…………………..
Nondurable goods……………
26,276
5,904.5
3,074.8
2,041.3
93,199
93,270
93,368
93,472
93,614
93,710
93,769
93,759
93,741
93,717
93,735
93,687
93,670
93,640
26,608
6,028.3
3,130.7
2,069.3
26,617
6,040.7
3,140.2
2,069.2
26,640
6,047.1
3,141.9
2,072.7
26,649
6,055.6
3,143.4
2,078.5
26,644
6,069.8
3,147.4
2,086.5
26,693
6,075.0
3,152.4
2,086.6
26,658
6,072.9
3,145.0
2,089.3
26,631
6,067.3
3,138.0
2,090.9
26,579
6,057.6
3,127.3
2,088.4
26,552
6,054.3
3,127.8
2,087.5
26,496
6,043.9
3,118.1
2,086.9
26,451
6,038.4
3,109.8
2,089.3
26,436
6,035.3
3,105.4
2,088.0
26,397
6,018.4
3,097.3
2,078.7
Electronic markets and
agents and brokers……………
788.5
828.4
831.3
832.5
833.7
835.9
836.0
838.6
838.4
841.9
839.0
838.9
839.3
841.9
842.4
Retail trade................................. 15,353.3 15,490.7 15,489.1 15,502.3 15,487.3 15,469.1 15,513.1 15,487.8 15,472.2 15,428.8 15,401.4 15,355.7 15,331.8 15,325.5 15,309.0
Motor vehicles and parts
dealers 1………………………
Automobile dealers..................
1,909.7
1,246.7
1,913.1
1,245.3
1,911.9
1,244.7
1,914.7
1,245.6
1,916.0
1,246.6
1,911.9
1,247.4
1,911.0
1,244.9
1,909.3
1,244.6
1,910.2
1,244.0
1,905.1
1,236.2
1,901.5
1,233.7
1,897.6
1,228.8
1,892.9
1,224.2
1,885.6
1,217.4
1,875.0
1,209.0
Furniture and home
furnishings stores....................
586.9
581.0
577.7
579.2
576.2
577.3
584.9
584.5
579.9
575.9
570.6
569.0
568.5
568.2
567.9
Electronics and appliance
stores.......................................
541.1
543.7
545.0
542.7
540.1
537.1
542.6
540.4
534.3
533.6
535.0
534.7
539.3
535.8
536.9
See notes at end of table.
Monthly Labor Review • September 2008 77
Current Labor Statistics: Labor Force Data
12. Continued–Employment of workers on nonfarm payrolls by industry, monthly data seasonally adjusted
[In thousands]
Annual average
Industry
2007
2008
2007
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
Junep
Julyp
1,305.3
2,848.5
1,307.3
2,847.1
1,315.6
2,852.2
1,291.9
2,856.0
1,285.4
2,859.6
1,279.9
2,871.9
1,271.6
2,871.9
1,266.0
2,880.1
1,258.5
2,885.7
1,250.8
2,890.1
1,240.5
2,882.4
1,240.3
2,880.7
1,236.1
2,881.6
1,230.6
2,882.3
961.1
864.1
988.6
861.2
985.6
861.5
989.4
860.8
990.1
864.2
991.0
862.0
998.6
859.1
999.9
850.5
1,000.6
853.8
993.5
854.2
993.9
852.6
993.4
847.4
990.9
841.2
990.7
844.9
988.6
844.2
Clothing and clothing
accessories stores …………………1,450.9
1,500.4
1,496.7
1,501.5
1,502.4
1,500.9
1,524.5
1,508.6
1,498.2
1,496.3
1,498.9
1,495.4
1,494.5
1,496.2
1,496.9
General merchandise stores 1…… 2,935.0
Department stores………………… 1,557.2
Miscellaneous store retailers……… 881.0
Nonstore retailers…………………… 432.8
658.2
2,984.6
1,576.7
868.7
437.6
660.5
2,987.0
1,580.1
871.3
437.5
661.8
2,978.9
1,573.0
869.7
435.8
665.1
2,976.5
1,570.5
873.3
435.5
664.0
2,975.8
1,568.5
869.0
435.1
664.0
2,968.2
1,560.6
868.3
440.1
661.6
2,976.7
1,568.4
866.3
446.5
667.2
2,971.1
1,564.3
869.4
441.4
661.9
2,955.7
1,543.3
865.3
443.1
658.6
2,943.9
1,534.3
862.8
442.7
651.5
2,939.0
1,528.1
863.3
441.5
653.2
2,928.5
1,514.7
860.8
441.0
651.1
2,939.3
1,514.2
858.6
437.4
648.2
2,943.2
1,512.0
859.2
436.0
Transportation and
warehousing................................. 4,469.6
Air transportation…………….……… 487.0
Rail transportation……...…………… 227.5
62.7
Water transportation………...………
Truck transportation………..……… 1,435.8
4,536.0
492.6
234.4
64.3
1,441.2
4,533.0
493.4
234.4
65.0
1,437.4
4,535.4
494.6
234.4
65.1
1,438.2
4,551.2
494.5
234.6
65.0
1,440.6
4,548.7
495.2
234.0
64.9
1,433.6
4,549.0
503.0
233.8
65.0
1,428.7
4,539.9
502.1
232.5
64.4
1,423.1
4,534.5
504.7
233.8
63.8
1,422.5
4,535.5
508.2
233.7
62.5
1,417.4
4,537.7
507.5
233.7
61.6
1,420.4
4,538.3
504.5
233.5
62.3
1,415.2
4,524.1
501.3
233.0
61.3
1,409.8
4,517.7
499.4
233.0
61.8
1,399.2
4,511.9
498.5
234.4
61.1
1,394.1
2006
Building material and garden
supply stores................................ 1,324.1
Food and beverage stores............. 2,821.1
Health and personal care
stores………………………………
Gasoline stations……………………
Sporting goods, hobby,
book, and music stores……………
645.5
Transit and ground passenger
transportation………...……………
Pipeline transportation………...……
399.3
38.7
410.0
40.1
411.0
40.0
413.3
40.1
417.8
40.1
417.4
40.3
411.5
40.6
411.8
40.8
411.9
40.6
413.5
40.9
412.9
41.2
418.3
41.3
412.9
42.2
416.8
42.7
415.6
43.2
Scenic and sightseeing
transportation…….…………………
27.5
29.4
28.9
29.3
29.8
30.3
30.9
31.3
31.0
31.5
31.7
31.3
31.1
31.0
30.6
Support activities for
transportation………………..……
Couriers and messengers……...……
Warehousing and storage…………
Utilities………………………….………......
Information…………………...….
570.6
582.4
638.1
548.5
3,038
582.9
582.5
658.7
553.4
3,029
583.7
580.1
659.1
554.3
3,027
583.7
579.2
657.5
555.1
3,024
586.5
580.3
662.0
554.8
3,031
589.9
577.9
665.2
556.1
3,027
589.2
584.4
661.9
555.5
3,022
587.1
588.1
658.7
557.1
3,018
584.9
585.5
655.8
557.1
3,014
585.9
586.0
655.9
557.0
3,016
586.3
585.3
657.1
558.2
3,013
588.2
585.0
658.7
557.7
3,007
587.1
587.2
658.2
557.1
3,002
586.6
588.1
659.1
557.6
2,996
586.9
588.8
658.7
557.8
2,983
Publishing industries, except
Internet…………………...…………
902.4
898.2
898.7
897.0
893.7
894.6
892.2
889.7
889.2
886.8
882.9
882.8
879.7
877.0
873.6
Motion picture and sound
recording industries……...………… 375.7
328.3
Broadcasting, except Internet..
380.0
326.4
377.9
325.1
376.3
325.2
384.3
327.0
380.5
324.8
376.3
325.0
376.3
321.9
372.9
323.0
380.1
322.1
383.0
322.5
382.5
320.8
380.9
321.2
380.2
319.8
375.5
320.2
Internet publishing and
broadcasting………………...………
Telecommunications………….…… 1,047.6
1,028.3
1,026.6
1,025.1
1,024.4
1,023.6
1,026.4
1,026.8
1,025.3
1,022.0
1,020.1
1,018.0
1,017.7
1,018.1
1,012.9
270.5
125.7
8,308
6,146.6
272.8
126.3
8,331
6,165.8
272.3
127.6
8,312
6,148.4
273.1
128.8
8,294
6,136.0
273.2
130.0
8,283
6,124.5
272.6
129.5
8,260
6,115.5
273.5
129.3
8,252
6,111.2
273.0
130.5
8,244
6,106.2
274.2
131.2
8,231
6,102.2
272.3
131.9
8,231
6,103.4
272.2
130.7
8,229
6,103.8
272.1
130.1
8,226
6,098.8
271.3
130.0
8,213
6,086.7
270.5
130.2
8,213
6,084.6
21.2
21.1
20.8
21.1
20.9
20.8
20.7
20.7
20.7
20.9
20.9
21.1
21.0
20.9
20.9
related activities 1………………… 2,924.9
Depository credit
2,881.6
2,892.3
2,870.4
2,856.7
2,844.8
2,834.3
2,829.2
2,825.0
2,820.4
2,811.8
2,807.9
2,800.5
2,792.3
2,788.5
intermediation 1…………………… 1,802.0
Commercial banking..…………… 1,322.9
1,822.5
1,345.8
1,823.8
1,346.7
1,825.8
1,347.3
1,831.0
1,350.1
1,829.3
1,350.1
1,823.4
1,344.7
1,824.6
1,345.9
1,821.5
1,342.2
1,823.3
1,344.9
1,821.6
1,343.4
1,822.9
1,344.2
1,820.6
1,343.4
1,818.4
1,343.2
1,817.3
1,342.5
818.3
847.9
851.2
852.6
853.2
855.0
856.9
856.7
859.2
862.5
865.8
867.2
866.6
866.2
865.2
Insurance carriers and
related activities………………...… 2,303.7
2,308.1
2,314.2
2,315.4
2,317.0
2,315.3
2,315.6
2,316.8
2,313.9
2,311.1
2,318.4
2,319.7
2,323.2
2,319.5
2,322.3
87.9
87.8
87.3
88.9
88.2
88.6
88.0
87.8
87.4
87.3
86.5
87.9
87.5
87.8
87.7
Real estate and rental
and leasing………………………..… 2,172.5
Real estate……………………….… 1,499.0
Rental and leasing services………
645.5
2,161.7
1,491.9
640.3
2,165.4
1,493.8
641.4
2,163.3
1,493.9
638.9
2,157.7
1,489.8
637.8
2,158.6
1,489.1
639.7
2,144.7
1,477.1
637.4
2,140.6
1,476.4
633.6
2,138.0
1,471.4
635.2
2,128.6
1,466.0
631.0
2,127.8
1,465.0
631.1
2,124.9
1,465.7
627.4
2,127.3
1,466.4
629.5
2,126.2
1,465.7
628.6
2,128.5
1,463.3
632.8
ISPs, search portals, and
data processing………..…………
Other information services…………
263.2
120.8
8,328
Financial activities………………..…
Finance and insurance……………..…6,156.0
Monetary authorities—
central bank…………………..……
Credit intermediation and
Securities, commodity
contracts, investments……………
Funds, trusts, and other
financial vehicles…………….……
Lessors of nonfinancial
intangible assets………………..…
28.1
29.5
30.2
30.5
30.1
29.8
30.2
30.6
31.4
31.6
31.7
31.8
31.4
31.9
32.4
Professional and business
services…………………………...…
17,566
17,962
17,958
17,979
18,000
18,070
18,079
18,131
18,101
18,073
18,014
18,031
17,982
17,943
17,919
services1…………………………… 7,356.7
Legal services……………..……… 1,173.2
7,662.0
1,176.4
7,664.2
1,173.7
7,688.0
1,174.2
7,729.7
1,178.6
7,759.3
1,179.7
7,784.8
1,175.2
7,820.5
1,173.9
7,819.2
1,173.0
7,829.2
1,174.9
7,823.5
1,172.6
7,845.6
1,172.5
7,839.1
1,172.2
7,856.3
1,172.7
7,866.8
1,173.3
889.0
947.2
947.8
954.0
964.5
971.3
979.4
993.3
992.3
991.9
983.3
986.1
973.8
977.5
977.8
Architectural and engineering
services…………………………… 1,385.7
1,436.0
1,436.5
1,439.0
1,443.2
1,451.1
1,453.9
1,460.4
1,460.5
1,463.0
1,461.8
1,464.9
1,464.9
1,469.3
1,471.4
Professional and technical
Accounting and bookkeeping
services……………………………
.
See notes at end of table
78
Monthly Labor Review • September 2008
12. Continued—Employment of workers on nonfarm payrolls by industry, monthly data seasonally adjusted
[In thousands]
Industry
Annual average
2007
2008
2006
2007
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
Junep
Julyp
1,284.6
1,359.8
1,366.8
1,371.2
1,375.5
1,380.0
1,387.5
1,391.4
1,391.6
1,393.5
1,391.3
1,403.9
1,408.9
1,412.2
1,419.3
886.4
952.8
946.6
956.3
967.2
974.8
985.1
994.3
989.2
992.7
997.0
1,001.3
1,006.9
1,015.2
1,019.3
1,810.9
1,846.0
1,845.0
1,849.2
1,854.7
1,860.9
1,850.0
1,847.8
1,845.5
1,844.7
1,839.7
1,841.0
1,836.4
1,836.8
1,832.8
Administrative and waste
services…………………………… 8,398.3
Administrative and support
8,453.6
8,448.6
8,441.3
8,415.3
8,449.6
8,444.1
8,462.8
8,436.2
8,398.6
8,351.2
8,344.4
8,306.0
8,250.0
8,219.6
8,096.7
3,600.9
2,605.1
805.5
8,092.2
3,584.6
2,596.5
805.5
8,083.4
3,570.2
2,589.4
803.8
8,057.4
3,533.0
2,565.1
802.7
8,092.2
3,567.7
2,592.0
798.5
8,081.4
3,563.9
2,583.7
798.9
8,099.3
3,566.9
2,578.5
803.7
8,070.8
3,562.1
2,574.6
797.4
8,036.1
3,531.6
2,536.8
796.6
7,987.3
3,483.7
2,506.0
794.1
7,978.9
3,462.2
2,487.1
792.8
7,939.8
3,421.8
2,451.6
789.2
7,883.9
3,366.2
2,418.6
786.9
7,853.4
3,332.0
2,389.6
786.3
Computer systems design
and related services…………
Management and technical
consulting services……………
Management of companies
and enterprises……..……….....
services 1……………………… 8,050.2
Employment services 1……… 3,680.9
Temporary help services…… 2,637.4
792.9
Business support services……
Services to buildings
and dwellings…………………
1,801.4
1,851.2
1,854.9
1,858.0
1,863.2
1,866.3
1,861.1
1,872.0
1,861.3
1,859.7
1,857.3
1,864.6
1,865.9
1,869.3
1,867.9
Waste management and
remediation services………….
348.1
356.9
356.4
357.9
357.9
357.4
362.7
363.5
365.4
362.5
363.9
365.5
366.2
366.1
366.2
17,826
2,900.9
18,327
2,949.1
18,360
2,962.7
18,422
2,981.3
18,451
2,967.7
18,490
2,974.9
18,522
2,975.5
18,568
2,984.5
18,617
3,003.4
18,665
3,009.6
18,709
3,018.6
18,757
3,030.5
18,820
3,047.3
18,875
3,080.8
18,914
3,086.1
Educational and health
services………………...……….
Educational services…….………
Health care and social
assistance……….……………… 14,925.3 15,377.6 15,396.8 15,440.8 15,483.0 15,515.1 15,546.7 15,583.2 15,613.6 15,655.0 15,690.5 15,726.1 15,772.4 15,794.0 15,828.3
Ambulatory health care
services 1……………………… 5,285.8
Offices of physicians…………… 2,147.8
Outpatient care centers………
492.6
865.6
Home health care services……
Hospitals………………………… 4,423.4
5,477.1
2,204.0
507.1
913.3
4,517.3
5,484.7
2,204.7
505.0
917.7
4,524.2
5,504.4
2,211.7
507.2
923.0
4,533.4
5,523.1
2,219.1
509.3
925.2
4,541.6
5,547.3
2,226.1
511.4
930.3
4,549.7
5,554.8
2,232.2
511.0
929.1
4,558.8
5,566.0
2,235.6
513.0
930.9
4,572.4
5,581.7
2,240.8
511.5
934.7
4,579.3
5,600.0
2,248.2
512.0
939.5
4,592.8
5,612.5
2,251.7
511.9
943.3
4,606.4
5,632.8
2,259.6
514.9
946.1
4,616.2
5,649.9
2,265.2
516.6
951.0
4,635.0
5,667.3
2,272.8
516.8
954.6
4,640.2
5,688.5
2,279.3
520.6
959.6
4,650.6
2,952.0
1,600.8
2,431.2
849.2
13,474
2,954.9
1,602.2
2,433.0
847.7
13,476
2,960.0
1,604.8
2,443.0
850.7
13,494
2,962.8
1,604.3
2,455.5
857.4
13,552
2,963.1
1,603.1
2,455.0
853.3
13,604
2,967.5
1,605.9
2,465.6
856.7
13,628
2,971.2
1,608.2
2,473.6
857.1
13,635
2,974.6
1,608.8
2,478.0
859.2
13,644
2,979.9
1,613.3
2,482.3
858.6
13,660
2,983.4
1,609.6
2,488.2
861.8
13,676
2,987.3
1,610.7
2,489.8
858.1
13,690
2,989.8
1,612.1
2,497.7
860.2
13,679
2,991.5
1,611.7
2,495.0
850.5
13,686
2,992.8
1,611.8
2,496.4
845.5
13,687
Nursing and residential
care facilities 1………………… 2,892.5
Nursing care facilities………… 1,581.4
Social assistance 1……………… 2,323.5
818.3
Child day care services………
Leisure and hospitality………..
13,110
Arts, entertainment,
and recreation……….…….……
1,928.5
1,977.5
1,968.8
1,970.5
1,985.3
1,996.4
2,001.4
2,010.3
2,016.1
2,019.1
2,025.7
2,021.1
2,013.1
2,008.2
2,005.5
Performing arts and
spectator sports…………………
398.5
412.4
405.8
409.2
414.3
419.0
426.4
429.9
429.5
431.0
433.9
436.4
434.7
436.8
434.9
Museums, historical sites,
zoos, and parks…………………
123.8
130.2
131.9
131.1
131.6
131.9
131.6
131.5
132.6
131.7
133.4
132.6
133.9
132.1
131.5
1,406.3
1,434.9
1,431.1
1,430.2
1,439.4
1,445.5
1,443.4
1,448.9
1,454.0
1,456.4
1,458.4
1,452.1
1,444.5
1,439.3
1,439.1
Amusements, gambling, and
recreation………………………
Accommodations and
food services…………………… 11,181.1 11,496.3 11,507.0 11,523.6 11,567.0 11,607.5 11,626.8 11,624.7 11,628.0 11,640.7 11,650.7 11,668.7 11,665.8 11,677.4 11,681.1
Accommodations………………. 1,832.1
1,856.4 1,853.6 1,844.1 1,856.4 1,863.6 1,870.3 1,858.1 1,854.9 1,854.4 1,849.4 1,853.0 1,849.0 1,849.2 1,849.7
Food services and drinking
places…………………………… 9,349.0
Other services……………………
5,438
Repair and maintenance……… 1,248.5
Personal and laundry services
1,288.4
9,639.9
5,491
1,257.0
1,305.2
9,653.4
5,501
1,257.8
1,307.9
9,679.5
5,497
1,259.6
1,305.7
9,710.6
5,495
1,262.5
1,304.4
9,743.9
5,496
1,260.1
1,303.4
9,756.5
5,506
1,258.0
1,309.7
9,766.6
5,507
1,255.5
1,306.9
9,773.1
5,508
1,252.9
1,306.6
9,786.3
5,517
1,255.2
1,306.4
9,801.3
5,522
1,254.8
1,308.5
9,815.7
5,525
1,254.0
1,309.9
9,816.8
5,527
1,251.7
1,310.6
9,828.2
5,521
1,246.1
1,312.2
9,831.4
5,527
1,245.2
1,313.3
Membership associations and
organizations…………………… 2,901.2
Government..................................
Federal........................................
Federal, except U.S. Postal
Service....................................
U.S. Postal Service………………
State...........................................
Education................................
Other State government..........
Local...........................................
Education................................
Other local government...........
2,928.8
2,935.4
2,931.2
2,927.6
2,932.8
2,938.0
2,944.4
2,948.9
2,955.6
2,959.0
2,961.4
2,964.3
2,963.1
2,968.1
21,974
2,732
22,203
2,727
22,170
2,726
22,212
2,724
22,227
2,721
22,262
2,722
22,278
2,728
22,333
2,735
22,336
2,717
22,362
2,725
22,377
2,726
22,401
2,734
22,453
2,740
22,496
2,742
22,521
2,739
1,962.6
769.7
5,075
2,292.5
2,782.0
14,167
7,913.0
6,253.8
1,964.6
762.3
5,125
2,318.4
2,806.6
14,351
7,976.6
6,374.5
1,964.3
761.6
5,123
2,313.8
2,808.8
14,321
7,938.2
6,382.5
1,963.4
760.6
5,123
2,313.6
2,809.5
14,365
7,972.0
6,393.4
1,961.4
759.3
5,138
2,327.7
2,810.3
14,368
7,970.6
6,397.5
1,963.5
758.3
5,138
2,325.9
2,812.4
14,402
7,994.6
6,406.9
1,966.7
761.7
5,131
2,314.3
2,816.5
14,419
7,999.6
6,419.2
1,972.3
763.1
5,153
2,332.5
2,820.9
14,445
8,016.5
6,428.2
1,977.3
739.7
5,159
2,335.1
2,824.0
14,460
8,018.0
6,441.5
1,982.9
741.6
5,158
2,332.9
2,824.9
14,479
8,031.9
6,447.5
1,986.6
739.1
5,157
2,332.9
2,823.8
14,494
8,035.7
6,457.8
1,996.0
737.9
5,170
2,340.8
2,829.1
14,497
8,032.1
6,465.0
2,006.5
733.3
5,174
2,344.4
2,829.7
14,539
8,060.0
6,479.2
2,011.2
730.8
5,186
2,352.3
2,833.8
14,568
8,075.0
6,493.0
2,010.5
728.6
5,198
2,359.0
2,838.9
14,584
8,077.2
6,506.5
1
Includes other industries not shown separately.
NOTE: See "Notes on the data" for a description of the most recent benchmark revision.
p = preliminary.
Monthly Labor Review • September 2008 79
Current Labor Statistics: Labor Force Data
13. Average weekly hours of production or nonsupervisory workers1 on private nonfarm payrolls, by industry, monthly
data seasonally adjusted
Industry
Annual average
2006
2007
2007
2008
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
Junep Julyp
TOTAL PRIVATE…………………………
33.9
33.8
33.8
33.8
33.8
33.8
33.8
33.8
33.7
33.7
33.8
33.8
33.7
33.7
GOODS-PRODUCING………………………
40.5
40.6
40.6
40.6
40.6
40.6
40.7
40.5
40.4
40.4
40.5
40.4
40.2
40.3
40.3
Natural resources and mining……………
45.6
45.9
45.9
45.7
46.2
46.0
46.2
45.8
45.7
45.7
46.2
44.9
44.6
45.0
44.9
Construction…………………………………
39.0
39.0
38.9
38.8
38.9
39.0
39.1
39.0
38.8
38.7
38.9
38.9
38.5
38.7
38.7
Manufacturing……………………..............
Overtime hours..................................
41.1
4.4
41.2
4.2
41.4
4.2
41.3
4.2
41.4
4.2
41.2
4.1
41.3
4.1
41.1
4.0
41.1
4.0
41.1
4.0
41.2
4.0
41.0
4.0
41.0
3.9
41.0
3.8
41.0
3.8
Durable goods..…………………............
Overtime hours..................................
Wood products.....................................
Nonmetallic mineral products...............
Primary metals.....................................
Fabricated metal products...................
Machinery…………………………………
Computer and electronic products……
Electrical equipment and appliances…
Transportation equipment....................
Furniture and related products………..
Miscellaneous manufacturing..............
41.4
4.4
39.8
43.0
43.6
41.4
42.4
40.5
41.0
42.7
38.8
38.7
41.5
4.2
39.4
42.3
42.9
41.6
42.6
40.6
41.2
42.8
39.2
38.9
41.6
4.2
39.9
42.6
43.2
41.7
42.5
40.3
41.4
43.3
39.2
39.2
41.7
4.2
39.6
42.8
43.0
41.7
42.6
40.6
41.2
43.1
39.7
39.4
41.6
4.2
39.7
42.7
42.6
41.9
42.7
40.6
41.2
42.8
39.4
39.7
41.5
4.1
39.5
42.6
42.6
41.7
42.9
40.6
40.7
42.7
39.1
39.0
41.5
4.1
39.0
42.9
42.7
41.7
42.9
40.9
41.2
42.6
38.9
38.8
41.3
4.0
39.2
41.5
42.2
41.6
42.9
40.5
41.6
42.1
39.1
38.8
41.4
4.1
39.0
42.2
42.5
41.6
43.1
40.4
41.4
42.6
38.3
39.0
41.4
4.1
39.0
42.1
42.4
41.7
43.0
40.5
41.1
42.9
38.2
38.8
41.5
4.0
38.7
43.1
42.9
41.7
42.7
41.0
41.3
42.3
38.7
39.3
41.3
4.0
38.8
42.2
42.4
41.6
42.5
41.1
41.1
42.3
38.7
39.3
41.2
3.9
39.1
42.3
42.2
41.4
42.1
41.2
41.1
42.1
38.8
39.2
41.2
3.8
39.3
42.1
42.5
41.2
42.1
41.2
41.0
42.2
39.0
39.2
41.3
3.8
39.0
42.6
42.2
41.2
42.2
41.2
40.8
42.6
38.4
39.3
Nondurable goods..................................
Overtime hours..................................
Food manufacturing............................…
Beverage and tobacco products..........
Textile mills………………………………
Textile product mills……………………
Apparel.................................................
Leather and allied products..................
Paper and paper products………………
40.6
4.4
40.1
40.8
40.6
39.8
36.5
38.9
42.9
40.8
4.1
40.7
40.8
40.3
39.7
37.2
38.1
43.2
40.9
4.1
40.8
40.7
40.2
40.8
37.5
37.5
43.0
40.8
4.1
40.6
41.0
39.9
39.9
37.2
37.7
43.1
40.9
4.1
40.7
40.8
40.4
39.9
37.2
37.9
43.2
40.8
4.1
40.8
40.6
40.2
39.2
36.6
37.7
43.3
40.9
4.1
40.6
40.5
39.9
39.1
36.9
38.1
43.7
40.8
4.0
40.4
40.8
40.2
39.9
37.5
39.1
44.0
40.6
3.9
40.5
40.5
38.7
38.6
36.7
38.2
44.0
40.6
3.9
40.6
40.1
38.8
39.3
36.8
38.2
43.9
40.7
3.9
40.7
40.4
38.8
39.3
36.7
38.7
43.6
40.5
3.9
40.8
39.6
38.4
38.3
36.6
38.6
43.3
40.5
3.8
40.8
39.7
39.0
38.7
36.0
38.7
42.5
40.5
3.8
40.6
39.0
38.9
39.1
36.4
38.5
42.7
40.5
3.7
40.6
39.1
39.3
39.1
36.8
38.3
42.4
Printing and related support
activities.............................................
Petroleum and coal products……………
Chemicals…………………………………
Plastics and rubber products……………
39.2
45.0
42.5
40.6
39.1
44.2
41.9
41.3
38.8
44.0
42.2
41.5
39.1
43.7
42.1
41.3
38.9
43.4
42.0
41.6
38.8
42.9
41.7
41.7
39.0
43.8
42.1
42.1
38.8
44.0
41.5
41.4
38.4
43.8
41.6
41.1
38.2
43.6
41.4
41.2
38.6
43.5
41.9
41.1
38.5
43.2
41.3
41.0
38.5
44.2
41.3
41.0
38.1
44.4
41.8
41.1
38.0
45.2
41.8
41.3
PRIVATE SERVICEPROVIDING………………………………
32.5
32.4
32.4
32.4
32.4
32.4
32.4
32.4
32.4
32.3
32.4
32.4
32.4
32.4
32.3
Trade, transportation, and
utilities.......……………….......................
Wholesale trade........……………….......
Retail trade…………………………………
Transportation and warehousing…………
Utilities………………………………………
Information…………………………………
Financial activities…………………………
33.4
38.0
30.5
36.9
41.4
36.6
35.7
33.3
38.2
30.2
36.9
42.4
36.5
35.9
33.2
38.1
30.1
36.8
42.6
36.6
35.9
33.3
38.2
30.1
36.9
42.4
36.4
35.8
33.3
38.2
30.2
36.9
42.5
36.5
35.7
33.2
38.1
30.1
36.7
42.2
36.2
35.7
33.3
38.1
30.2
36.8
42.5
36.2
35.8
33.3
38.3
30.1
36.8
42.8
36.3
35.8
33.4
38.4
30.2
36.6
43.1
36.3
35.8
33.3
38.2
30.1
36.7
42.8
36.2
35.8
33.4
38.4
30.2
36.7
43.3
36.6
35.8
33.4
38.3
30.2
36.7
42.6
36.5
35.9
33.3
38.3
30.1
36.5
42.4
36.6
36.0
33.3
38.3
30.1
36.5
42.8
36.6
35.9
33.2
38.4
30.0
36.4
42.3
36.7
35.7
Professional and business
services……………………………………
Education and health services……………
Leisure and hospitality……………………
Other services……………........................
34.6
32.5
25.7
30.9
34.8
32.6
25.5
30.9
34.8
32.6
25.3
30.9
34.7
32.6
25.4
30.8
34.8
32.6
25.4
30.9
34.8
32.6
25.4
30.8
34.7
32.6
25.3
30.9
34.8
32.6
25.3
30.8
34.7
32.6
25.3
30.8
34.6
32.6
25.3
30.8
34.8
32.7
25.3
30.9
34.8
32.6
25.4
30.8
34.8
32.7
25.3
30.8
34.8
32.6
25.3
30.8
34.8
32.6
25.2
30.8
1
Data relate to production workers in natural resources and mining and
manufacturing, construction workers in construction, and nonsupervisory workers
in the service-providing industries.
80
Monthly Labor Review • September 2008
NOTE: See "Notes on the data" for a description of the most recent benchmark
revision.
p = preliminary.
33.7
14. Average hourly earnings of production or nonsupervisory workers1 on private nonfarm payrolls, by industry,
monthly data seasonally adjusted
Industry
Annual average
2007
2008
2006
2007
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
Junep
Julyp
TOTAL PRIVATE
Current dollars………………………
Constant (1982) dollars……………
$16.76
8.24
$17.42
8.32
$17.47
8.33
$17.51
8.35
$17.57
8.35
$17.59
8.34
$17.64
8.27
$17.70
8.27
$17.75
8.26
$17.81
8.29
$17.87
8.28
$17.89
8.27
$17.95
8.24
$18.00
8.17
$18.07
8.12
GOODS-PRODUCING...............................
18.02
18.67
18.69
18.73
18.78
18.77
18.84
18.90
18.98
19.04
19.12
19.12
19.17
19.25
19.35
19.90
20.02
16.81
15.96
17.68
15.33
20.96
20.95
17.26
16.43
18.19
15.67
20.95
20.94
17.30
16.46
18.23
15.70
21.09
21.01
17.33
16.49
18.27
15.71
20.99
21.12
17.34
16.50
18.28
15.74
21.05
21.07
17.34
16.52
18.28
15.73
21.02
21.20
17.40
16.58
18.31
15.85
21.54
21.30
17.41
16.60
18.33
15.86
21.75
21.38
17.49
16.68
18.41
15.92
21.69
21.47
17.55
16.74
18.49
15.94
22.01
21.56
17.61
16.79
18.54
16.03
21.61
21.60
17.62
16.80
18.58
15.99
21.71
21.70
17.65
16.85
18.61
16.04
22.01
21.77
17.71
16.93
18.67
16.11
22.54
21.86
17.79
17.00
18.76
16.15
PRIVATE SERVICEPROVIDING..........………………..............
16.42
17.10
17.15
17.19
17.26
17.28
17.33
17.39
17.44
17.50
17.55
17.58
17.64
17.69
17.75
Trade,transportation, and
utilities…………………………………....
Wholesale trade....................................
Retail trade...........................................
Transportation and warehousing………
Utilities……………………………………
Information..............................................
Financial activities..................................
15.39
18.91
12.57
17.28
27.40
23.23
18.80
15.79
19.59
12.76
17.73
27.87
23.94
19.64
15.82
19.58
12.79
17.78
27.82
23.92
19.67
15.85
19.66
12.80
17.79
27.99
23.97
19.75
15.90
19.72
12.83
17.86
28.14
24.01
19.76
15.94
19.77
12.86
17.86
28.32
24.10
19.78
15.93
19.86
12.81
17.93
28.18
24.11
19.87
16.00
19.93
12.81
18.07
28.52
24.18
19.91
16.02
19.97
12.80
18.10
28.61
24.33
20.00
16.07
20.00
12.84
18.21
28.58
24.41
20.05
16.11
20.03
12.86
18.25
28.77
24.53
20.11
16.11
20.05
12.85
18.33
28.56
24.50
20.16
16.16
20.06
12.90
18.38
28.81
24.67
20.23
16.19
20.12
12.90
18.39
29.14
24.74
20.26
16.19
20.16
12.90
18.38
28.61
24.87
20.31
Professional and business
services.................................................
19.13
20.13
20.19
20.25
20.36
20.31
20.42
20.46
20.53
20.63
20.74
20.84
20.90
21.01
21.12
Education and health
services.................................................
Leisure and hospitality..........................
Other services.........................................
17.38
9.75
14.77
18.11
10.41
15.42
18.14
10.46
15.46
18.20
10.50
15.51
18.29
10.55
15.55
18.34
10.60
15.59
18.43
10.61
15.66
18.48
10.65
15.71
18.54
10.67
15.74
18.59
10.73
15.76
18.61
10.74
15.77
18.64
10.79
15.79
18.71
10.81
15.81
18.75
10.85
15.85
18.83
10.87
15.89
Natural resources and mining...............
Construction...........................................
Manufacturing.........................................
Excluding overtime...........................
Durable goods……………………………
Nondurable goods………………………
1
Data relate to production workers in natural resources and mining and
manufacturing, construction workers in construction, and nonsupervisory
workers in the service-providing industries.
NOTE: See "Notes on the data" for a description of the most recent benchmark revision.
p = preliminary.
Monthly Labor Review • September 2008 81
Current Labor Statistics: Labor Force Data
15. Average hourly earnings of production or nonsupervisory workers1 on private nonfarm payrolls, by industry
Industry
Annual average
2006
TOTAL PRIVATE……………………………… $16.76
Seasonally adjusted…………………….
–
2007
2007
July
Aug.
Sept.
Oct.
2008
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
Junep Julyp
$17.42 $17.44 $17.42 $17.64 $17.60 $17.63 $17.75 $17.80 $17.85 $17.92 $17.91 $17.90 $17.96 $17.99
– 17.47 17.51 17.57 17.59 17.64 17.70 17.75 17.81 17.87 17.89 17.95 18.00 18.07
GOODS-PRODUCING......................................
18.02
18.67
18.72
18.81
18.91
18.86
18.88
18.96
18.90
18.94
19.03
19.06
19.13
19.24
19.38
Natural resources and mining……………..
19.90
20.96
20.87
20.97
20.93
21.02
20.99
21.68
21.96
21.87
22.26
21.77
21.51
21.74
22.44
Construction.…………..................................
20.02
20.95
21.02
21.13
21.32
21.25
21.26
21.38
21.24
21.35
21.43
21.48
21.60
21.69
21.92
Manufacturing…………………………………… 16.81
17.26
17.22
17.31
17.39
17.34
17.42
17.51
17.53
17.55
17.60
17.63
17.63
17.71
17.72
Durable goods..…………………..................
Wood products .........................................
Nonmetallic mineral products ………………
Primary metals .........................................
Fabricated metal products …....................
Machinery …………..………………………
Computer and electronic products ...........
Electrical equipment and appliances ........
Transportation equipment ........................
Furniture and related products .................
Miscellaneous manufacturing ...................
17.68
13.39
16.59
19.36
16.17
17.20
18.94
15.54
22.41
13.80
14.36
18.19
13.67
16.93
19.66
16.53
17.72
19.95
15.94
23.02
14.32
14.66
18.10
13.62
17.04
19.85
16.52
17.82
20.08
16.09
22.67
14.36
14.82
18.27
13.61
16.88
19.72
16.58
17.69
20.06
16.03
23.33
14.31
14.77
18.35
13.65
16.94
19.83
16.61
17.79
20.20
16.10
23.42
14.36
14.78
18.30
13.81
16.94
19.81
16.69
17.68
20.28
15.80
23.20
14.36
14.70
18.36
13.82
17.05
19.69
16.70
17.74
20.22
15.68
23.41
14.35
14.72
18.46
13.88
16.94
19.73
16.82
17.95
20.33
15.73
23.46
14.50
15.00
18.43
13.90
16.99
20.04
16.77
17.72
20.51
15.70
23.34
14.38
14.91
18.50
13.82
16.86
19.99
16.78
17.81
20.60
15.73
23.48
14.37
14.95
18.53
13.89
16.80
20.21
16.85
17.85
20.80
15.66
23.46
14.42
15.08
18.56
13.96
17.12
20.20
16.81
17.88
20.90
15.76
23.52
14.45
14.97
18.57
14.08
16.90
20.23
16.84
17.98
20.99
15.69
23.53
14.48
14.97
18.67
14.12
16.98
20.25
16.92
17.87
21.06
15.75
23.79
14.58
15.15
18.64
14.23
16.94
20.47
16.93
17.94
21.16
15.86
23.72
14.49
15.35
Nondurable goods………………………......
Food manufacturing ...........................……
Beverages and tobacco products .............
15.33
13.13
18.18
15.67
13.54
18.49
15.74
13.57
18.61
15.69
13.61
17.78
15.77
13.65
18.40
15.71
13.61
18.69
15.83
13.63
19.54
15.90
13.70
19.69
15.99
13.87
19.55
15.93
13.74
19.64
16.01
13.83
19.59
16.03
13.86
19.26
16.04
13.89
19.05
16.08
13.95
18.57
16.20
14.01
18.80
12.55
11.86
10.65
11.44
18.01
15.80
24.11
19.60
14.97
13.00
11.78
11.05
12.04
18.43
16.15
25.26
19.56
15.38
13.13
11.89
11.15
12.18
18.68
16.19
25.12
19.70
15.31
13.21
11.74
11.12
12.10
18.30
16.28
25.43
19.47
15.45
13.16
11.73
11.17
12.24
18.54
16.37
25.95
19.52
15.45
12.93
11.75
11.16
12.10
18.50
16.48
24.92
19.35
15.41
13.06
11.67
11.20
12.50
18.47
16.33
26.95
19.52
15.49
13.13
11.75
11.28
12.12
18.71
16.65
25.52
19.57
15.65
13.29
11.68
11.43
12.78
18.78
16.51
26.55
19.46
15.56
13.35
11.62
11.46
12.68
18.61
16.49
26.51
19.40
15.58
13.45
11.78
11.35
12.81
18.66
16.65
27.22
19.35
15.69
13.45
11.78
11.51
12.63
18.58
16.64
27.12
19.39
15.77
13.50
11.86
11.43
12.88
18.74
16.66
27.01
19.37
15.71
13.58
11.80
11.36
12.88
18.89
16.78
27.17
19.33
15.69
13.76
11.80
11.35
12.85
19.18
16.79
27.69
19.43
15.86
Textile mills ..............................................
Textile product mills .................................
Apparel .....................................................
Leather and allied products ………………
Paper and paper products …………………
Printing and related support activities…...
Petroleum and coal products ………………
Chemicals ……………………………………
Plastics and rubber products ....................
PRIVATE SERVICEPROVIDING …………………………………….
16.42
17.10
17.10
17.05
17.31
17.27
17.31
17.45
17.52
17.58
17.65
17.62
17.59
17.64
17.64
Trade, transportation, and
utilities…….……..........................................
Wholesale trade ………………………………
Retail trade ……………………………………
Transportation and warehousing ……………
Utilities ………..…..….………..………………
15.39
18.91
12.57
17.28
27.40
15.79
19.59
12.76
17.73
27.87
15.89
19.70
12.84
17.90
27.70
15.81
19.58
12.78
17.84
27.73
16.00
19.85
12.91
17.96
28.27
15.94
19.75
12.85
17.89
28.44
15.84
19.89
12.70
17.94
28.17
15.89
20.10
12.64
18.04
28.61
16.02
20.01
12.78
18.08
28.62
16.08
20.03
12.82
18.14
28.61
16.16
20.08
12.90
18.19
28.88
16.16
20.01
12.90
18.28
28.69
16.14
19.93
12.91
18.33
28.83
16.20
20.05
12.92
18.44
29.01
16.20
20.11
12.93
18.49
28.41
Information………………………………….....
23.23
23.94
23.77
23.85
24.22
24.15
24.11
24.34
24.44
24.44
24.58
24.52
24.60
24.73
24.74
Financial activities……..………....................
18.80
19.64
19.66
19.65
19.88
19.79
19.83
19.97
19.96
20.07
20.18
20.22
20.20
20.27
20.22
19.13
20.13
20.26
20.01
20.34
20.19
20.33
20.67
20.65
20.77
20.93
20.84
20.81
21.03
21.01
services………………………………………… 17.38
Professional and business
services…………………………………………
Education and health
18.11
18.18
18.20
18.33
18.33
18.42
18.51
18.61
18.58
18.62
18.63
18.64
18.68
18.87
Leisure and hospitality ………………………
9.75
10.41
10.33
10.39
10.53
10.61
10.67
10.77
10.73
10.82
10.76
10.80
10.82
10.77
10.72
Other services…………………......................
14.77
15.42
15.39
15.43
15.58
15.55
15.61
15.75
15.74
15.78
15.84
15.82
15.84
15.85
15.80
1 Data relate to production workers in natural resources and mining and
manufacturing, construction workers in construction, and nonsupervisory
workers in the service-providing industries.
82
Monthly Labor Review • September 2008
16. Average weekly earnings of production or nonsupervisory workers1 on private nonfarm payrolls, by industry
Industry
Annual average
2006
2007
2008
May.
Junep
Julyp
$599.99
604.68
$601.44
604.92
$612.44
606.60
$606.26
608.96
766.91
766.21
769.03
783.07
779.08
988.20
986.34 1,017.28
970.94
950.74
987.00 1,007.56
805.00
800.63
825.06
824.83
833.76
852.42
859.26
728.42
716.98
714.29
723.36
722.83
721.07
729.65
719.43
763.78
534.83
731.45
842.73
701.40
762.82
771.63
546.87
696.23
844.44
708.12
780.83
759.32
530.98
696.59
851.70
695.96
763.73
758.50
523.78
686.20
847.58
693.01
762.27
767.14
531.99
715.68
869.03
702.65
763.98
766.53
538.86
722.46
852.44
699.30
761.69
765.08
553.34
718.25
853.71
697.18
756.96
774.81
564.80
726.74
868.73
698.80
754.11
760.51
559.24
726.73
853.60
690.74
749.89
827.42
833.06
841.66
822.45
826.06
852.80
854.81
862.69
873.99
865.44
659.69
658.83
666.54
943.07 1,012.52 1,011.74
649.38
992.96
652.29
671.67
999.61 1,006.43
649.98
638.64
994.28 1,002.60
645.19
994.70
646.16
999.60
640.15
648.90
985.91 1,013.45
640.74
977.26
562.91
561.48
559.65
545.00
555.17
553.44
557.48
556.42
2007
July
Aug.
Sept.
$589.72
–
$596.45
590.49
$592.28
591.84
$603.29
593.87
$594.88
594.54
$594.13
596.23
$605.28
598.26
$592.74
598.18
$596.19
600.20
$605.70
604.01
730.16
757.06
758.16
769.33
777.20
771.37
770.30
771.67
756.00
751.92
907.95
961.78
957.93
962.52
979.52
981.63
969.74
992.94
781.21
816.06
828.19
836.75
842.14
841.50
829.14
825.27
691.02
711.36
704.30
718.37
725.16
717.88
722.93
732.00
532.99
Wood products .........................
712.71
Nonmetallic mineral products....
Primary metals…………………… 843.59
668.98
Fabricated metal products.........
Machinery………………………… 728.84
754.12
539.10
716.79
843.28
687.13
753.99
743.91
546.16
729.31
849.58
682.28
753.79
763.69
543.04
732.59
844.02
693.04
750.06
770.70
548.73
735.20
848.72
699.28
761.41
763.11
548.26
730.11
841.93
700.98
762.01
766.96
809.19
801.19
812.43
828.20
636.95
957.65
656.58
985.57
535.90
561.03
TOTAL PRIVATE………………… $567.87
Seasonally adjusted..........
–
GOODS-PRODUCING……………
Natural resources
and mining………………………..
CONSTRUCTION
Manufacturing……………………
Durable goods……………………
Oct.
Nov.
Dec
Jan.
Feb.
Mar.
Apr.
Computer and electronic
products..................................
Electrical equipment and
appliances...............................
Transportation equipment………
Furniture and related
products………………………..
576.69
572.96
578.55
541.75
571.54
Miscellaneous
manufacturing..........................
555.90
569.98
573.53
581.94
588.24
574.77
571.14
589.50
580.00
575.58
594.15
586.82
583.83
595.40
597.12
Nondurable goods.......................
621.97
525.99
639.99
550.65
639.04
552.30
641.72
556.65
651.30
566.48
644.11
560.73
653.78
562.92
656.67
561.70
646.00
556.19
638.79
546.85
648.41
555.97
647.61
559.94
646.41
565.32
652.85
566.37
652.86
567.41
741.34
509.39
472.24
389.20
445.47
772.39
753.80
524.47
467.96
411.52
459.43
795.20
761.15
519.95
477.98
413.67
450.66
799.50
739.65
524.44
468.43
412.55
453.75
788.73
747.04
536.93
468.03
414.41
462.67
813.91
751.34
515.91
457.08
410.69
458.59
806.60
787.46
521.09
457.46
415.52
478.75
816.37
793.51
539.64
478.23
423.00
484.80
834.47
778.09
514.32
449.68
416.05
484.36
826.32
769.89
512.64
454.34
420.58
480.57
805.81
785.56
521.86
464.13
418.82
499.59
807.98
768.47
515.14
450.00
423.57
491.31
802.66
763.91
523.80
454.24
412.62
502.32
788.95
733.52
529.62
468.46
415.78
501.03
804.71
736.96
533.89
459.02
414.28
485.73
807.48
618.92
632.08
621.70
638.18
644.98
644.37
640.14
654.35
630.68
629.92
644.36
640.64
638.08
634.28
629.63
Food manufacturing...................
Beverages and tobacco
products..................................
Textile mills………………………
Textile product mills……………
Apparel……………………………
Leather and allied products.......
Paper and paper products…….
Printing and related
support activities………………
Petroleum and coal
products………………………… 1,085.50 1,115.24 1,117.84 1,106.21 1,144.40 1,074.05 1,204.67 1,099.91 1,157.58 1,134.63 1,165.02 1,163.45 1,188.44 1,228.08 1,270.97
819.99
823.46
819.69
821.79
801.09
823.74
818.03
809.54
801.22
810.77
800.81
794.17
811.86
810.23
Chemicals………………………… 833.67
Plastics and rubber
products…………………………
PRIVATE SERVICEPROVIDING…………....................
Trade, transportation,
and utilities………………………
Wholesale trade......…………......
Retail trade…………………………
608.41
635.15
624.65
635.00
647.36
642.60
652.13
657.30
639.52
637.22
644.86
646.57
644.11
649.57
645.50
532.78
554.78
560.88
554.13
567.77
557.82
559.11
570.62
558.89
564.32
573.63
567.36
566.40
578.59
571.54
514.34
718.63
383.02
526.38
748.90
385.20
535.49
758.45
392.90
529.64
747.96
388.51
542.40
768.20
396.34
529.21
752.48
386.79
525.89
757.81
382.27
535.49
779.88
385.52
525.46
758.38
379.57
529.03
759.14
380.75
538.13
775.09
387.00
534.90
764.38
385.71
534.23
761.33
387.30
545.94
779.95
394.06
541.08
770.21
391.78
Transportation and
654.83
664.09
663.65
668.11
656.56
661.99
678.30
650.88
654.85
667.57
663.56
665.38
680.44
673.04
warehousing……………………… 636.97
Utilities……………………………… 1,135.34 1,182.17 1,180.02 1,175.75 1,215.61 1,208.70 1,194.41 1,221.65 1,222.07 1,218.79 1,241.84 1,225.06 1,219.51 1,247.43 1,201.74
Information…………………………
850.42
873.63
884.24
870.53
896.14
874.23
872.78
893.28
877.40
879.84
902.09
887.62
890.52
917.48
910.43
Financial activities………………… 672.21
705.29
717.59
699.54
721.64
702.55
705.95
726.91
708.58
716.50
730.52
721.85
721.14
739.86
719.83
Professional and
business services………………
709.10
696.35
715.97
702.61
705.45
727.58
704.17
714.49
734.64
725.23
724.19
744.46
729.05
662.27
700.15
Education and Education and
health services…………………… 564.94
590.18
598.12
593.32
603.06
595.73
600.49
607.13
604.83
603.85
608.87
603.61
605.80
610.84
615.16
Leisure and hospitality………….
250.34
265.45
271.68
270.14
269.57
268.43
266.75
272.48
262.89
269.42
272.23
272.16
273.75
278.94
276.58
Other services……………………… 456.50
476.80
480.17
478.33
484.54
478.94
480.79
488.25
480.07
482.87
489.46
485.67
486.29
492.94
488.22
1 Data relate to production workers in natural resources and mining and manufacturing,
NOTE: See "Notes on the data" for a description of the most recent benchmark revision.
construction workers in construction, and nonsupervisory workers in the service-
Dash indicates data not available.
providing industries.
p = preliminary.
Monthly Labor Review • September 2008 83
Current Labor Statistics: Labor Force Data
17. Diffusion indexes of employment change, seasonally adjusted
[In percent]
Timespan and year
Jan.
Feb.
Mar.
Apr.
May
June
July
Aug. Sept. Oct.
Nov.
Dec.
Private nonfarm payrolls, 278 industries
Over 1-month span:
2004...............................................
2005..............................................
2006..............................................
2007…………………………………
2008…………………………………
50.5
52.2
65.1
51.6
45.4
50.5
60.6
60.9
51.8
41.4
64.1
54.2
64.4
52.7
47.4
62.6
58.2
59.3
51.1
45.6
61.7
55.8
53.3
56.6
46.4
58.9
58.2
52.7
50.4
42.3
56.0
58.0
60.4
52.2
41.4
50.0
61.3
58.9
51.6
56.9
54.7
53.5
56.4
56.9
53.6
55.8
54.6
51.3
62.4
57.1
48.2
51.8
54.7
56.0
48.5
Over 3-month span:
2004...............................................
2005..............................................
2006..............................................
2007…………………………………
2008…………………………………
54.4
52.2
67.2
58.4
46.7
52.9
55.5
66.2
54.7
42.7
57.3
57.5
66.6
55.3
42.3
63.5
60.8
65.5
54.7
44.0
68.8
58.9
60.6
56.2
43.1
66.6
61.9
58.2
53.3
44.0
61.3
60.4
56.0
53.1
38.3
56.4
63.9
58.9
54.7
57.7
61.1
55.7
58.4
59.5
54.4
56.4
56.8
61.9
54.9
57.1
54.7
54.6
61.3
58.4
52.4
Over 6-month span:
2004...............................................
2005..............................................
2006..............................................
2007…………………………………
2008…………………………………
50.0
54.6
63.1
59.1
51.5
51.6
57.3
64.4
56.4
49.8
55.3
56.8
67.2
57.5
44.7
60.9
57.5
67.0
56.8
46.5
63.7
57.5
64.4
58.8
43.6
65.1
58.2
66.4
58.2
39.1
65.1
64.4
61.5
56.2
38.9
63.9
62.8
61.7
58.0
60.4
62.0
60.4
58.2
61.7
59.3
59.7
57.1
58.2
61.5
60.8
54.6
56.0
62.0
56.0
53.8
Over 12-month span:
2004...............................................
2005..............................................
2006..............................................
2007…………………………………
2008…………………………………
40.5
60.6
67.2
62.6
53.8
42.3
60.8
65.1
59.1
54.6
45.1
59.7
65.5
60.4
52.6
48.9
58.9
62.6
58.9
50.4
51.3
58.0
64.8
59.5
49.3
58.2
60.0
66.4
58.4
45.8
57.5
60.9
64.4
57.5
45.8
55.7
63.3
64.4
58.8
57.3
60.4
66.2
61.7
58.8
58.9
65.1
60.4
60.6
59.5
64.4
59.9
60.8
61.7
65.5
57.7
Manufacturing payrolls, 84 industries
Over 1-month span:
2004...............................................
2005..............................................
2006..............................................
2007…………………………………
2008…………………………………
43.5
36.3
57.7
47.6
40.5
47.6
48.8
45.8
35.7
28.6
47.0
42.9
54.8
30.4
38.1
63.7
44.6
48.8
29.8
35.1
50.6
42.3
38.1
37.5
44.6
51.2
35.1
53.0
39.3
30.4
58.3
38.1
50.6
41.7
28.6
42.9
47.0
44.0
33.3
42.9
45.8
36.3
40.5
48.2
46.4
40.5
45.2
42.3
47.0
38.1
44.6
39.9
47.0
39.3
36.3
Over 3-month span:
2004...............................................
2005..............................................
2006..............................................
2007…………………………………
2008…………………………………
41.1
38.1
54.8
33.9
35.7
40.5
39.3
52.4
28.6
27.4
43.5
42.3
47.6
32.1
26.8
56.5
44.6
48.8
27.4
29.2
58.9
36.3
44.6
29.8
29.8
61.3
37.5
50.6
32.7
35.7
57.7
33.3
42.9
31.0
23.8
47.0
39.9
47.6
34.5
46.4
45.8
36.3
32.1
41.7
41.7
37.5
39.3
44.6
38.7
32.1
44.0
38.7
49.4
34.5
41.7
Over 6-month span:
2004...............................................
2005..............................................
2006..............................................
2007…………………………………
2008…………………………………
29.2
33.9
42.9
34.5
34.5
31.5
38.1
45.2
27.4
33.9
32.7
35.1
50.6
23.8
32.1
44.6
36.9
47.6
27.4
28.0
49.4
32.1
48.2
31.5
26.8
54.8
32.1
47.6
34.5
20.8
59.5
41.7
46.4
33.3
21.4
56.0
35.7
48.8
31.0
51.2
36.3
43.5
29.2
51.8
36.9
41.7
35.1
44.0
37.5
38.7
34.5
38.7
42.3
29.8
32.7
Over 12-month span:
2004...............................................
2005..............................................
2006..............................................
2007…………………………………
2008…………………………………
13.1
44.6
44.6
39.3
29.8
14.3
43.5
40.5
36.3
29.8
13.1
41.7
40.5
36.9
29.8
20.2
40.5
39.3
28.6
24.4
23.2
36.3
39.3
29.8
27.4
35.7
35.1
44.6
26.2
24.4
36.9
32.1
41.7
26.8
25.0
38.1
33.9
42.3
29.2
36.9
32.7
46.4
30.4
44.0
33.3
48.2
29.8
44.6
33.3
45.2
33.3
44.6
38.1
44.0
33.9
NOTE: Figures are the percent of industries with employment
increasing plus one-half of the industries with unchanged
employment, where 50 percent indicates an equal balance
between industries with increasing and decreasing
employment.
84
Monthly Labor Review • September 2008
See the "Definitions" in this section. See "Notes on the data"
for a description of the most recent benchmark revision.
Data for the two most recent months are preliminary.
18. Job openings levels and rates by industry and region, seasonally adjusted
1
Levels (in thousands)
Industry and region
Jan.
2
Total ………………………………………………
Percent
2008
Feb.
Mar.
2008
Apr.
May
p
June
Jan.
July
Feb.
2.7
Mar.
2.7
Apr.
2.6
May
2.6
June
2.6
2.5
p
July
3,889
3,799
3,672
3,612
3,631
3,497
3,416
2.4
Total private 2…………………………………
3,449
3,350
3,225
3,192
3,185
3,073
2,983
2.9
2.8
2.7
2.7
2.7
2.6
2.5
Construction………………………………
133
123
102
99
130
100
84
1.8
1.6
1.4
1.3
1.8
1.4
1.2
Manufacturing……………………………
286
239
251
244
249
241
233
2.0
1.7
1.8
1.8
1.8
1.7
1.7
Trade, transportation, and utilities………
643
598
562
550
572
539
591
2.4
2.2
2.1
2.0
2.1
2.0
2.2
Professional and business services……
752
699
714
676
649
670
600
4.0
3.7
3.8
3.6
3.5
3.6
3.2
Education and health services…………
680
737
696
684
648
682
674
3.5
3.8
3.6
3.5
3.3
3.5
3.4
Leisure and hospitality……………………
515
530
501
491
503
452
436
3.6
3.7
3.5
3.5
3.5
3.2
3.1
439
450
441
422
451
417
432
1.9
2.0
1.9
1.8
2.0
1.8
1.9
2.2
Industry
Government…………………………………
Region 3
Northeast…………………………………
662
576
602
618
600
608
588
2.5
2.2
2.3
2.3
2.3
2.3
South………………………………………
1,536
1,485
1,386
1,364
1,386
1,440
1,360
3.0
2.9
2.7
2.7
2.7
2.8
2.7
Midwest……………………………………
749
766
781
752
721
676
647
2.3
2.4
2.4
2.3
2.2
2.1
2.0
West………………………………………
966
954
918
883
937
789
831
3.0
3.0
2.9
2.8
2.9
2.5
2.6
1
Detail will not necessarily add to totals because of the independent seasonal
adjustment of the various series.
2
Includes natural resources and mining, information, financial activities, and other
services, not shown separately.
3
Northeast: Connecticut, Maine, Massachusetts, New Hampshire, New Jersey,
New York, Pennsylvania, Rhode Island, Vermont; South: Alabama, Arkansas,
Delaware, District of Columbia, Florida, Georgia, Kentucky, Louisiana, Maryland,
Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia,
West Virginia; Midwest: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri,
Nebraska, North Dakota, Ohio, South Dakota, Wisconsin; West: Alaska, Arizona, California,
Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, Wyoming.
NOTE: The job openings level is the number of job openings on the last business day of the
month; the job openings rate is the number of job openings on the last business day of the month
as a percent of total employment plus job openings.
P
= preliminary.
19. Hires levels and rates by industry and region, seasonally adjusted
1
Levels (in thousands)
Industry and region
Jan.
Total2………………………………………………
Percent
2008
Feb.
Mar.
Apr.
2008
May
June
Julyp
Jan.
3.4
Feb.
3.3
Mar.
3.3
Apr.
3.4
May
3.0
June
3.2
Julyp
4,639
4,586
4,569
4,715
4,123
4,438
4,062
3.0
Total private 2…………………………………
4,227
4,203
4,147
4,311
3,871
4,136
3,792
3.7
3.6
3.6
3.7
3.4
3.6
3.3
Construction………………………………
319
349
350
385
286
354
267
4.3
4.7
4.8
5.3
3.9
4.9
3.7
Manufacturing……………………………
326
285
309
300
274
285
253
2.4
2.1
2.3
2.2
2.0
2.1
1.9
Trade, transportation, and utilities………
916
882
884
943
828
906
893
3.4
3.3
3.3
3.6
3.1
3.4
3.4
Professional and business services……
897
780
893
858
770
889
788
5.0
4.3
5.0
4.8
4.3
5.0
4.4
Education and health services…………
516
522
501
510
479
485
473
2.8
2.8
2.7
2.7
2.5
2.6
2.5
Leisure and hospitality……………………
824
868
801
841
847
741
775
6.0
6.4
5.9
6.1
6.2
5.4
5.7
394
387
429
407
329
340
325
1.8
1.7
1.9
1.8
1.5
1.5
1.4
2.6
Industry
Government…………………………………
Region 3
Northeast…………………………………
767
713
715
743
646
761
658
3.0
2.8
2.8
2.9
2.5
3.0
South………………………………………
1,814
1,769
1,703
1,725
1,538
1,666
1,507
3.6
3.6
3.4
3.5
3.1
3.4
3.0
Midwest……………………………………
998
944
986
986
914
966
947
3.2
3.0
3.1
3.1
2.9
3.1
3.0
1,058
1,186
1,170
1,246
1,111
1,084
1,017
3.4
3.8
3.8
4.0
3.6
3.5
3.3
West………………………………………
1
Detail will not necessarily add to totals because of the independent seasonal
adjustment of the various series.
2
Includes natural resources and mining, information, financial activities, and other
services, not shown separately.
Midwest: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri,
Nebraska, North Dakota, Ohio, South Dakota, Wisconsin; West: Alaska, Arizona,
California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah,
Washington, Wyoming.
3
Northeast: Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New
York, Pennsylvania, Rhode Island, Vermont; South: Alabama, Arkansas, Delaware,
District of Columbia, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi,
North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, West Virginia;
NOTE: The hires level is the number of hires during the entire month; the hires rate is
the number of hires during the entire month as a percent of total employment.
p
= preliminary.
Monthly Labor Review • September 2008 85
Current Labor Statistics: Labor Force Data
20. Total separations levels and rates by industry and region, seasonally adjusted
1
Levels (in thousands)
Industry and region
Jan.
2
Total ………………………………………………
Percent
2008
Feb.
Mar.
Apr.
2008
May
June
p
July
Jan.
3.2
Feb.
3.3
Mar.
3.2
Apr.
3.2
May
3.1
p
June
July
4,477
4,503
4,390
4,404
4,313
4,368
4,308
3.2
3.1
Total private 2…………………………………
4,188
4,224
4,100
4,112
4,046
4,115
4,085
3.6
3.7
3.6
3.6
3.5
3.6
3.5
Construction………………………………
311
329
367
378
393
409
436
4.2
4.5
5.0
5.2
5.4
5.7
6.1
2.3
Industry
Manufacturing……………………………
348
350
304
390
359
353
304
2.5
2.6
2.2
2.9
2.6
2.6
Trade, transportation, and utilities………
1,005
957
941
1,003
868
1,003
1,025
3.8
3.6
3.5
3.8
3.3
3.8
3.9
Professional and business services……
790
861
806
739
741
799
756
4.4
4.8
4.5
4.1
4.1
4.5
4.2
Education and health services…………
447
459
449
429
434
417
465
2.4
2.5
2.4
2.3
2.3
2.2
2.5
Leisure and hospitality……………………
800
854
776
722
801
749
674
5.9
6.2
5.7
5.3
5.8
5.5
4.9
290
278
291
295
269
259
237
1.3
1.2
1.3
1.3
1.2
1.1
1.1
2.9
Government…………………………………
Region 3
Northeast…………………………………
697
770
737
709
685
658
750
2.7
3.0
2.9
2.8
2.7
2.6
South………………………………………
1,699
1,673
1,617
1,666
1,614
1,681
1,602
3.4
3.4
3.3
3.4
3.3
3.4
3.2
Midwest……………………………………
975
902
918
949
915
954
911
3.1
2.9
2.9
3.0
2.9
3.0
2.9
1,107
1,167
1,101
1,094
1,096
1,089
1,069
3.6
3.8
3.6
3.5
3.5
3.5
3.5
West………………………………………
1
Detail will not necessarily add to totals because of the independent seasonal
adjustment of the various series.
Midwest: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska,
North Dakota, Ohio, South Dakota, Wisconsin; West: Alaska, Arizona, California,
Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington,
Wyoming.
2
Includes natural resources and mining, information, financial activities, and other
services, not shown separately.
3
Northeast: Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New
York, Pennsylvania, Rhode Island, Vermont; South: Alabama, Arkansas, Delaware,
District of Columbia, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi,
North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, West Virginia;
NOTE: The total separations level is the number of total separations during the entire
month; the total separations rate is the number of total separations during the entire
month as a percent of total employment.
p
= preliminary
21. Quits levels and rates by industry and region, seasonally adjusted
Levels1 (in thousands)
Industry and region
Jan.
Total2………………………………………………
Percent
2008
Feb.
Mar.
Apr.
2008
May
June
p
July
Jan.
1.8
Feb.
1.8
Mar.
1.7
Apr.
1.8
May
1.7
June
Julyp
2,493
2,522
2,375
2,444
2,336
2,365
2,324
1.7
1.7
Total private 2…………………………………
2,355
2,384
2,258
2,301
2,210
2,242
2,212
2.0
2.1
2.0
2.0
1.9
1.9
1.9
Construction………………………………
113
133
111
127
124
139
144
1.5
1.8
1.5
1.7
1.7
1.9
2.0
Manufacturing……………………………
183
187
157
182
163
154
134
1.3
1.4
1.2
1.3
1.2
1.1
1.0
Trade, transportation, and utilities………
598
532
535
550
495
545
561
2.2
2.0
2.0
2.1
1.9
2.1
2.1
Professional and business services……
351
492
386
385
391
413
403
1.9
2.7
2.1
2.1
2.2
2.3
2.3
Education and health services…………
276
271
279
270
229
246
270
1.5
1.5
1.5
1.4
1.2
1.3
1.4
Leisure and hospitality……………………
525
539
529
516
547
525
482
3.8
3.9
3.9
3.8
4.0
3.8
3.5
138
135
126
144
126
123
115
.6
.6
.6
.6
.6
.5
.5
Industry
Government…………………………………
Region 3
Northeast…………………………………
358
410
334
368
327
344
357
1.4
1.6
1.3
1.4
1.3
1.3
1.4
South………………………………………
1,045
1,021
996
1,001
937
969
916
2.1
2.1
2.0
2.0
1.9
2.0
1.8
Midwest……………………………………
502
475
491
500
485
515
536
1.6
1.5
1.6
1.6
1.5
1.6
1.7
West………………………………………
583
632
568
575
584
539
519
1.9
2.0
1.8
1.9
1.9
1.7
1.7
1
Detail will not necessarily add to totals because of the independent seasonal
adjustment of the various series.
2
Includes natural resources and mining, information, financial activities, and other
services, not shown separately.
Midwest: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri,
Nebraska, North Dakota, Ohio, South Dakota, Wisconsin; West: Alaska, Arizona,
California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon,
Utah, Washington, Wyoming.
3
Northeast: Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New
York, Pennsylvania, Rhode Island, Vermont; South: Alabama, Arkansas, Delaware,
District of Columbia, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi,
North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, West
Virginia;
86
Monthly Labor Review • September 2008
NOTE: The quits level is the number of quits during the entire month; the quits
rate is the number of quits during the entire month as a percent of total
employment.
p
= preliminary.
22. Quarterly Census of Employment and Wages: 10 largest counties, third quarter 2007.
County by NAICS supersector
Establishments,
third quarter
2007
(thousands)
Average weekly wage1
Employment
September
2007
(thousands)
Percent change,
September
2006-072
Third
quarter
2007
Percent change,
third quarter
2006-072
United States3 ..............................................................................
Private industry ........................................................................
Natural resources and mining ..............................................
Construction .........................................................................
Manufacturing ......................................................................
Trade, transportation, and utilities ........................................
Information ...........................................................................
Financial activities ................................................................
Professional and business services .....................................
Education and health services .............................................
Leisure and hospitality .........................................................
Other services ......................................................................
Government .............................................................................
9,012.8
8,721.6
124.7
895.5
361.4
1,916.9
144.3
871.8
1,484.6
825.8
726.7
1,162.9
291.2
136,246.9
114,790.8
1,931.5
7,774.4
13,845.4
26,299.2
3,033.1
8,123.2
18,017.6
17,506.6
13,562.6
4,433.8
21,456.1
0.9
.9
1.7
-1.0
-2.2
1.2
.0
-.7
1.7
2.9
1.9
1.2
1.0
$818
810
820
876
987
707
1,274
1,200
998
775
348
531
859
4.3
4.5
7.8
5.7
4.3
3.2
4.6
5.9
6.4
3.6
4.2
4.1
3.2
Los Angeles, CA ..........................................................................
Private industry ........................................................................
Natural resources and mining ..............................................
Construction .........................................................................
Manufacturing ......................................................................
Trade, transportation, and utilities ........................................
Information ...........................................................................
Financial activities ................................................................
Professional and business services .....................................
Education and health services .............................................
Leisure and hospitality .........................................................
Other services ......................................................................
Government .............................................................................
401.9
397.9
.5
14.3
15.2
55.3
8.8
25.2
43.4
28.2
27.1
179.8
4.0
4,191.6
3,626.2
12.7
160.4
444.7
811.9
216.3
243.7
608.9
480.4
401.1
246.0
565.4
.4
.1
5.0
-.9
(4)
-.1
8.5
-2.6
-.3
1.8
1.8
.0
2.3
925
901
1,095
945
961
765
1,520
1,483
1,051
851
518
439
1,080
3.4
3.1
-8.3
5.4
(4)
2.0
-.3
(4)
6.3
( 4)
2.8
5.8
(4)
Cook, IL ........................................................................................
Private industry ........................................................................
Natural resources and mining ..............................................
Construction .........................................................................
Manufacturing ......................................................................
Trade, transportation, and utilities ........................................
Information ...........................................................................
Financial activities ................................................................
Professional and business services .....................................
Education and health services .............................................
Leisure and hospitality .........................................................
Other services ......................................................................
Government .............................................................................
138.0
136.6
.1
12.1
7.1
27.6
2.5
15.8
28.2
13.6
11.6
13.8
1.4
2,541.5
2,232.8
1.3
98.2
237.2
472.2
58.4
215.4
441.6
369.2
240.0
95.0
308.7
.0
.2
-7.7
-1.6
-1.9
-.9
.6
-1.5
.9
1.6
2.2
.7
-.9
961
958
1,063
1,207
981
776
1,402
1,547
1,179
843
430
691
985
3.3
3.6
3.5
5.5
3.0
-.5
9.1
7.8
3.1
3.7
4.6
3.0
2.3
New York, NY ...............................................................................
Private industry ........................................................................
Natural resources and mining ..............................................
Construction .........................................................................
Manufacturing ......................................................................
Trade, transportation, and utilities ........................................
Information ...........................................................................
Financial activities ................................................................
Professional and business services .....................................
Education and health services .............................................
Leisure and hospitality .........................................................
Other services ......................................................................
Government .............................................................................
118.0
117.7
.0
2.3
3.1
22.1
4.4
18.7
24.6
8.6
11.2
17.4
.3
2,350.3
1,906.7
.1
35.8
37.5
248.2
135.6
380.0
482.2
283.3
208.5
87.2
443.5
2.0
2.3
-1.9
6.9
-4.7
1.7
1.0
2.0
2.3
2.0
3.3
1.5
.7
1,544
1,667
1,749
1,461
1,158
1,124
1,916
3,047
1,769
1,011
728
889
1,014
8.7
9.6
11.8
5.3
3.0
4.3
4.5
16.3
8.6
4.8
6.1
3.7
1.5
Harris, TX .....................................................................................
Private industry ........................................................................
Natural resources and mining ..............................................
Construction .........................................................................
Manufacturing ......................................................................
Trade, transportation, and utilities ........................................
Information ...........................................................................
Financial activities ................................................................
Professional and business services .....................................
Education and health services .............................................
Leisure and hospitality .........................................................
Other services ......................................................................
Government .............................................................................
95.1
94.5
1.5
6.6
4.6
21.7
1.3
10.5
18.9
10.0
7.3
11.0
.5
2,028.0
1,783.4
78.4
151.5
182.2
424.7
32.8
120.7
341.2
214.7
176.2
58.4
244.6
3.8
4.3
(4)
5.5
3.5
3.9
2.6
2.0
4.9
5.4
3.2
3.9
.6
1,015
1,027
2,580
968
1,290
901
1,258
1,256
1,156
824
366
595
922
6.7
7.1
(4)
6.1
7.7
6.0
9.1
7.3
7.5
1.7
2.2
7.6
3.1
Maricopa, AZ ................................................................................
Private industry ........................................................................
Natural resources and mining ..............................................
Construction .........................................................................
Manufacturing ......................................................................
Trade, transportation, and utilities ........................................
Information ...........................................................................
Financial activities ................................................................
Professional and business services .....................................
Education and health services .............................................
Leisure and hospitality .........................................................
Other services ......................................................................
Government .............................................................................
99.3
98.6
.5
10.6
3.6
21.6
1.6
12.7
21.8
9.7
7.2
7.2
.7
1,825.1
1,605.3
8.5
165.8
132.2
374.9
30.4
148.6
316.8
198.9
177.6
50.1
219.9
.2
-.1
2.9
-7.6
-3.7
2.0
-.7
-2.4
.3
4.4
1.4
2.2
2.8
822
811
723
834
1,116
777
1,030
1,024
825
879
387
570
908
3.8
4.1
6.0
3.9
3.2
3.5
.4
.0
9.1
5.5
5.7
5.2
1.2
See footnotes at end of table.
Monthly Labor Review • September 2008 87
Current Labor Statistics: Labor Force Data
22. Continued—Quarterly Census of Employment and Wages: 10 largest counties, second quarter 2007.
County by NAICS supersector
Establishments,
second quarter
2007
(thousands)
Average weekly wage1
Employment
June
2007
(thousands)
Percent change,
June
2006-072
Second
quarter
2007
Percent change,
second quarter
2006-072
Orange, CA ..................................................................................
Private industry ........................................................................
Natural resources and mining ..............................................
Construction .........................................................................
Manufacturing ......................................................................
Trade, transportation, and utilities ........................................
Information ...........................................................................
Financial activities ................................................................
Professional and business services .....................................
Education and health services .............................................
Leisure and hospitality .........................................................
Other services ......................................................................
Government .............................................................................
94.7
93.3
.2
7.1
5.4
17.8
1.4
11.4
19.2
9.8
7.0
14.0
1.4
1,519.5
1,363.2
6.2
105.6
177.1
278.2
30.1
128.1
274.6
139.6
175.1
48.4
156.3
-1.0
-1.3
-6.8
-3.5
(4)
.4
-2.2
-7.7
(4)
2.9
1.7
-.4
1.1
$952
939
588
1,016
1,150
892
1,340
1,445
1,000
833
410
561
1,062
3.4
2.8
10.7
7.2
(4)
(4)
7.5
(4)
(4)
3.3
5.1
4.1
6.7
Dallas, TX .....................................................................................
Private industry ........................................................................
Natural resources and mining ..............................................
Construction .........................................................................
Manufacturing ......................................................................
Trade, transportation, and utilities ........................................
Information ...........................................................................
Financial activities ................................................................
Professional and business services .....................................
Education and health services .............................................
Leisure and hospitality .........................................................
Other services ......................................................................
Government .............................................................................
67.6
67.1
.6
4.4
3.2
15.0
1.7
8.7
14.4
6.6
5.2
6.4
.5
1,492.6
1,330.0
7.1
84.1
144.2
307.2
48.6
145.7
274.3
144.7
131.2
40.6
162.5
3.2
3.2
-4.7
4.4
-.4
2.3
-4.6
2.8
5.9
6.6
3.6
1.2
2.9
1,011
1,022
2,879
935
1,202
974
1,371
1,331
1,108
968
430
602
920
5.4
5.4
-1.1
1.4
8.1
6.1
7.3
5.2
5.8
6.8
2.6
2.9
5.0
San Diego, CA .............................................................................
Private industry ........................................................................
Natural resources and mining ..............................................
Construction .........................................................................
Manufacturing ......................................................................
Trade, transportation, and utilities ........................................
Information ...........................................................................
Financial activities ................................................................
Professional and business services .....................................
Education and health services .............................................
Leisure and hospitality .........................................................
Other services ......................................................................
Government .............................................................................
91.7
90.4
.8
7.2
3.2
14.6
1.3
9.9
16.4
8.0
6.9
22.1
1.3
1,334.7
1,108.8
11.6
90.9
102.4
219.8
37.5
81.5
217.9
127.1
163.6
56.6
225.9
.2
-.1
-4.1
-6.5
(4)
.3
.5
-3.3
.6
(4)
2.8
1.1
1.7
890
868
540
916
1,190
730
1,873
1,108
1,076
812
389
482
996
4.8
4.7
4.0
6.3
6.6
5.8
1.7
3.5
6.0
4.1
3.5
2.8
4.8
King, WA ......................................................................................
Private industry ........................................................................
Natural resources and mining ..............................................
Construction .........................................................................
Manufacturing ......................................................................
Trade, transportation, and utilities ........................................
Information ...........................................................................
Financial activities ................................................................
Professional and business services .....................................
Education and health services .............................................
Leisure and hospitality .........................................................
Other services ......................................................................
Government .............................................................................
75.9
75.4
.4
6.8
2.5
14.8
1.8
7.0
12.9
6.3
6.0
16.7
.5
1,182.2
1,027.6
3.3
72.9
112.0
219.5
75.8
76.4
188.1
120.6
113.7
45.4
154.6
2.9
3.3
3.4
11.0
1.9
2.0
5.0
-1.0
4.4
2.7
3.9
.9
.6
1,028
1,033
1,224
1,002
1,386
903
1,829
1,272
1,180
812
427
571
995
3.8
3.5
1.4
6.5
.8
6.1
4.1
3.3
1.1
4.5
2.4
7.9
6.0
Miami-Dade, FL ............................................................................
Private industry ........................................................................
Natural resources and mining ..............................................
Construction .........................................................................
Manufacturing ......................................................................
Trade, transportation, and utilities ........................................
Information ...........................................................................
Financial activities ................................................................
Professional and business services .....................................
Education and health services .............................................
Leisure and hospitality .........................................................
Other services ......................................................................
Government .............................................................................
85.9
85.6
.5
6.2
2.6
23.1
1.5
10.4
17.3
8.9
5.7
7.6
.3
1,002.1
868.2
9.2
53.5
48.0
252.6
20.7
71.6
136.4
135.4
101.8
35.7
133.9
1.0
.8
.3
1.5
-1.7
.9
-.7
-.9
-1.5
3.1
1.3
1.9
2.4
814
788
496
841
735
747
1,163
1,161
949
796
458
525
969
3.8
3.7
6.0
-1.1
1.9
2.3
4.6
5.6
7.5
4.6
2.5
5.8
4.8
1
Average weekly wages were calculated using unrounded data.
2
Percent changes were computed from quarterly employment and pay data
adjusted for noneconomic county reclassifications. See Notes on Current Labor
Statistics.
3
88
Totals for the United States do not include data for Puerto Rico or the
Monthly Labor Review • September 2008
Virgin Islands.
4
Data do not meet BLS or State agency disclosure standards.
NOTE: Includes workers covered by Unemployment Insurance (UI) and
Unemployment Compensation for Federal Employees (UCFE) programs. Data are
preliminary.
23. Quarterly Census of Employment and Wages: by State, second quarter 2007.
State
Establishments,
second quarter
2007
(thousands)
Average weekly wage1
Employment
June
2007
(thousands)
Percent change,
June
2006-07
Second
quarter
2007
Percent change,
second quarter
2006-07
United States2 ...................................
8,945.9
137,018.2
1.2
$820
4.6
Alabama ............................................
Alaska ...............................................
Arizona ..............................................
Arkansas ...........................................
California ...........................................
Colorado ...........................................
Connecticut .......................................
Delaware ...........................................
District of Columbia ...........................
Florida ...............................................
120.1
21.1
158.9
82.7
1,291.3
179.4
112.5
29.1
31.9
604.8
1,965.4
325.8
2,612.4
1,186.5
15,832.5
2,326.9
1,714.2
430.2
683.2
7,894.2
1.1
-.5
1.2
.3
.8
2.2
.9
.0
.8
.2
697
832
786
639
935
832
1,033
870
1,357
743
3.6
5.6
4.4
4.2
5.4
4.8
6.4
2.2
4.3
3.2
Georgia .............................................
Hawaii ...............................................
Idaho .................................................
Illinois ................................................
Indiana ..............................................
Iowa ..................................................
Kansas ..............................................
Kentucky ...........................................
Louisiana ...........................................
Maine ................................................
270.4
38.6
57.1
358.6
158.2
93.4
85.7
109.8
119.9
50.0
4,091.5
631.2
679.1
5,956.3
2,933.4
1,518.6
1,370.7
1,828.2
1,880.2
619.6
1.4
1.4
3.0
.8
.5
.9
2.0
1.7
3.2
.6
792
736
626
874
702
664
702
700
711
658
6.5
4.2
2.3
4.4
2.6
3.9
4.8
4.2
4.1
4.1
Maryland ...........................................
Massachusetts ..................................
Michigan ............................................
Minnesota .........................................
Mississippi .........................................
Missouri .............................................
Montana ............................................
Nebraska ...........................................
Nevada ..............................................
New Hampshire ................................
164.0
210.1
257.1
170.7
69.7
174.7
42.3
58.7
74.7
49.0
2,584.9
3,300.7
4,252.9
2,730.9
1,137.4
2,764.6
449.8
930.9
1,297.9
643.7
.7
1.2
-1.4
.0
.9
.8
1.7
1.6
1.0
.7
899
1,008
807
834
609
727
611
654
776
823
5.3
4.8
2.9
5.6
3.6
3.4
6.3
3.5
3.7
6.3
New Jersey .......................................
New Mexico ......................................
New York ..........................................
North Carolina ...................................
North Dakota .....................................
Ohio ..................................................
Oklahoma ..........................................
Oregon ..............................................
Pennsylvania .....................................
Rhode Island .....................................
278.1
53.7
576.8
251.0
25.1
290.5
99.1
130.8
338.7
36.1
4,066.7
833.3
8,688.8
4,090.5
347.7
5,384.6
1,538.5
1,761.6
5,740.3
492.9
.4
1.1
1.3
3.0
1.5
-.1
1.6
1.7
1.1
.3
989
686
1,020
718
619
740
665
742
802
774
4.3
5.2
5.9
4.1
4.7
3.4
4.1
4.5
4.6
2.5
South Carolina ..................................
South Dakota ....................................
Tennessee ........................................
Texas ................................................
Utah ..................................................
Vermont ............................................
Virginia ..............................................
Washington .......................................
West Virginia .....................................
Wisconsin ..........................................
115.8
30.1
140.7
548.7
86.3
24.7
227.4
216.7
48.7
158.2
1,917.4
404.3
2,768.7
10,296.1
1,233.7
306.6
3,731.5
2,989.8
717.1
2,845.8
3.0
2.1
.7
3.4
4.4
-.5
1.0
2.7
.3
.4
665
590
729
827
698
698
859
835
659
709
2.9
4.8
3.6
5.9
6.6
5.0
4.4
4.6
3.6
3.7
Wyoming ...........................................
24.4
288.3
3.3
739
8.0
Puerto Rico .......................................
Virgin Islands ....................................
56.9
3.4
1,020.7
46.9
-1.6
3.4
460
707
6.0
4.1
1
2
Average weekly wages were calculated using unrounded data.
Totals for the United States do not include data for Puerto Rico
or the Virgin Islands.
NOTE: Includes workers covered by Unemployment Insurance (UI)
and Unemployment Compensation for Federal Employees (UCFE)
programs. Data are preliminary.
Monthly Labor Review • September 2008 89
Current Labor Statistics: Labor Force Data
24. Annual data: Quarterly Census of Employment and Wages, by ownership
Year
Average
establishments
Average
annual
employment
Total annual wages
(in thousands)
Average annual wage
per employee
Average
weekly
wage
Total covered (UI and UCFE)
1997 ..................................................
1998 ..................................................
1999 ..................................................
2000 ..................................................
2001 ..................................................
2002 ..................................................
2003 ..................................................
2004 ..................................................
2005 ..................................................
2006 ..................................................
7,369,473
7,634,018
7,820,860
7,879,116
7,984,529
8,101,872
8,228,840
8,364,795
8,571,144
8,784,027
121,044,432
124,183,549
127,042,282
129,877,063
129,635,800
128,233,919
127,795,827
129,278,176
131,571,623
133,833,834
$3,674,031,718
3,967,072,423
4,235,579,204
4,587,708,584
4,695,225,123
4,714,374,741
4,826,251,547
5,087,561,796
5,351,949,496
5,692,569,465
$30,353
31,945
33,340
35,323
36,219
36,764
37,765
39,354
40,677
42,535
$584
614
641
679
697
707
726
757
782
818
$30,058
31,676
33,094
35,077
35,943
36,428
37,401
38,955
40,270
42,124
$578
609
636
675
691
701
719
749
774
810
$30,064
31,762
33,244
35,337
36,157
36,539
37,508
39,134
40,505
42,414
$578
611
639
680
695
703
721
753
779
816
$32,521
33,605
34,681
36,296
37,814
39,212
40,057
41,118
42,249
43,875
$625
646
667
698
727
754
770
791
812
844
$29,134
30,251
31,234
32,387
33,521
34,605
35,669
36,805
37,718
39,179
$560
582
601
623
645
665
686
708
725
753
$42,732
43,688
44,287
46,228
48,940
52,050
54,239
57,782
59,864
62,274
$822
840
852
889
941
1,001
1,043
1,111
1,151
1,198
UI covered
1997 ..................................................
1998 ..................................................
1999 ..................................................
2000 ..................................................
2001 ..................................................
2002 ..................................................
2003 ..................................................
2004 ..................................................
2005 ..................................................
2006 ..................................................
7,317,363
7,586,767
7,771,198
7,828,861
7,933,536
8,051,117
8,177,087
8,312,729
8,518,249
8,731,111
118,233,942
121,400,660
124,255,714
127,005,574
126,883,182
125,475,293
125,031,551
126,538,579
128,837,948
131,104,860
$3,553,933,885
3,845,494,089
4,112,169,533
4,454,966,824
4,560,511,280
4,570,787,218
4,676,319,378
4,929,262,369
5,188,301,929
5,522,624,197
Private industry covered
1997 ..................................................
1998 ..................................................
1999 ..................................................
2000 ..................................................
2001 ..................................................
2002 ..................................................
2003 ..................................................
2004 ..................................................
2005 ..................................................
2006 ..................................................
7,121,182
7,381,518
7,560,567
7,622,274
7,724,965
7,839,903
7,963,340
8,093,142
8,294,662
8,505,496
102,175,161
105,082,368
107,619,457
110,015,333
109,304,802
107,577,281
107,065,553
108,490,066
110,611,016
112,718,858
$3,071,807,287
3,337,621,699
3,577,738,557
3,887,626,769
3,952,152,155
3,930,767,025
4,015,823,311
4,245,640,890
4,480,311,193
4,780,833,389
State government covered
1997 ..................................................
1998 ..................................................
1999 ..................................................
2000 ..................................................
2001 ..................................................
2002 ..................................................
2003 ..................................................
2004 ..................................................
2005 ..................................................
2006 ..................................................
65,352
67,347
70,538
65,096
64,583
64,447
64,467
64,544
66,278
66,921
4,214,451
4,240,779
4,296,673
4,370,160
4,452,237
4,485,071
4,481,845
4,484,997
4,527,514
4,565,908
$137,057,432
142,512,445
149,011,194
158,618,365
168,358,331
175,866,492
179,528,728
184,414,992
191,281,126
200,329,294
Local government covered
1997 ..................................................
1998 ..................................................
1999 ..................................................
2000 ..................................................
2001 ..................................................
2002 ..................................................
2003 ..................................................
2004 ..................................................
2005 ..................................................
2006 ..................................................
130,829
137,902
140,093
141,491
143,989
146,767
149,281
155,043
157,309
158,695
11,844,330
12,077,513
12,339,584
12,620,081
13,126,143
13,412,941
13,484,153
13,563,517
13,699,418
13,820,093
$345,069,166
365,359,945
385,419,781
408,721,690
440,000,795
464,153,701
480,967,339
499,206,488
516,709,610
541,461,514
Federal government covered (UCFE)
1997 ..................................................
1998 ..................................................
1999 ..................................................
2000 ..................................................
2001 ..................................................
2002 ..................................................
2003 ..................................................
2004 ..................................................
2005 ..................................................
2006 ..................................................
52,110
47,252
49,661
50,256
50,993
50,755
51,753
52,066
52,895
52,916
NOTE: Data are final. Detail may not add to total due to rounding.
90
Monthly Labor Review • September 2008
2,810,489
2,782,888
2,786,567
2,871,489
2,752,619
2,758,627
2,764,275
2,739,596
2,733,675
2,728,974
$120,097,833
121,578,334
123,409,672
132,741,760
134,713,843
143,587,523
149,932,170
158,299,427
163,647,568
169,945,269
25. Annual data: Quarterly Census of Employment and Wages, establishment size and employment, private ownership, by
supersector, first quarter 2006
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
workers
250 to 499
workers
500 to 999
workers
1,000 or
more
workers
Total all industries2
Establishments, first quarter ..................
Employment, March ...............................
8,413,125
111,001,540
5,078,506
7,540,432
Natural resources and mining
Establishments, first quarter ..................
Employment, March ...............................
123,076
1,631,257
69,188
111,354
23,230
153,676
15,106
203,446
9,842
296,339
3,177
216,952
1,783
267,612
516
177,858
175
115,367
59
88,653
Construction
Establishments, first quarter ..................
Employment, March ...............................
861,030
7,299,087
558,318
823,891
141,743
929,155
84,922
1,140,245
52,373
1,565,409
15,118
1,027,718
6,762
994,696
1,358
454,918
337
220,788
99
142,267
Manufacturing
Establishments, first quarter ..................
Employment, March ...............................
362,959
14,098,486
137,311
240,304
61,852
415,575
55,135
757,991
53,364
1,662,309
25,712
1,798,423
19,573
3,006,794
6,423
2,207,979
2,469
1,668,696
1,120
2,340,415
Trade, transportation, and utilities
Establishments, first quarter ..................
Employment, March ...............................
1,880,255
25,612,515
999,688
1,663,203
380,100
2,529,630
245,926
3,293,292
158,053
4,772,401
53,502
3,695,250
33,590
5,001,143
7,071
2,419,416
1,796
1,166,322
529
1,071,858
Information
Establishments, first quarter ..................
Employment, March ...............................
142,974
3,037,124
81,209
113,399
21,094
140,632
16,356
223,171
13,313
411,358
5,553
384,148
3,568
544,418
1,141
392,681
512
355,421
228
471,896
Financial activities
Establishments, first quarter ..................
Employment, March ...............................
836,365
8,102,371
541,333
874,114
151,952
1,002,449
80,853
1,068,474
40,558
1,206,411
12,146
832,505
6,245
936,343
1,890
655,392
928
641,926
460
884,757
Professional and business services
Establishments, first quarter ..................
Employment, March ...............................
1,403,142
17,162,560
948,773
1,333,479
192,581
1,265,155
121,585
1,639,285
80,222
2,431,806
30,997
2,148,736
20,046
3,038,221
5,849
1,995,309
2,169
1,469,170
920
1,841,399
Education and health services
Establishments, first quarter ..................
Employment, March ...............................
787,747
16,838,748
375,326
684,886
175,191
1,163,519
112,455
1,512,272
72,335
2,177,055
26,364
1,835,664
18,400
2,754,731
4,106
1,400,469
1,832
1,282,903
1,738
4,027,249
Leisure and hospitality
Establishments, first quarter ..................
Employment, March ...............................
699,767
12,633,387
270,143
430,588
118,147
796,935
128,663
1,802,270
131,168
3,945,588
38,635
2,583,745
10,459
1,475,115
1,602
540,014
648
437,645
302
621,487
Other services
Establishments, first quarter ..................
Employment, March ...............................
1,121,269
4,326,368
912,768
1,087,667
118,306
771,276
56,724
747,842
24,734
718,557
5,570
377,961
2,629
388,231
418
139,473
99
63,337
21
32,024
1
Includes establishments that reported no workers in March 2006.
2
Includes data for unclassified establishments, not shown separately.
1,392,481
919,182
636,264
216,815
123,061
30,375
9,219,319 12,406,793 19,195,647 14,903,811 18,408,166 10,383,792
10,965
5,476
7,421,575 11,522,005
NOTE: Data are final. Detail may not add to total due to rounding.
Monthly Labor Review • September 2008 91
Current Labor Statistics: Labor Force Data
26. Average annual wages for 2005 and 2006 for all covered
workers1 by metropolitan area
Average annual wages3
Metropolitan area2
2006
Metropolitan areas4 ..............................................................
$42,253
$44,165
4.5
Abilene, TX ............................................................................
Aguadilla-Isabela-San Sebastian, PR ...................................
Akron, OH ..............................................................................
Albany, GA ............................................................................
Albany-Schenectady-Troy, NY ..............................................
Albuquerque, NM ...................................................................
Alexandria, LA .......................................................................
Allentown-Bethlehem-Easton, PA-NJ ....................................
Altoona, PA ............................................................................
Amarillo, TX ...........................................................................
27,876
18,717
37,471
31,741
39,201
35,665
30,114
38,506
29,642
31,954
29,842
19,277
38,088
32,335
41,027
36,934
31,329
39,787
30,394
33,574
7.1
3.0
1.6
1.9
4.7
3.6
4.0
3.3
2.5
5.1
Ames, IA ................................................................................
Anchorage, AK ......................................................................
Anderson, IN ..........................................................................
Anderson, SC ........................................................................
Ann Arbor, MI ........................................................................
Anniston-Oxford, AL ..............................................................
Appleton, WI ..........................................................................
Asheville, NC .........................................................................
Athens-Clarke County, GA ....................................................
Atlanta-Sandy Springs-Marietta, GA .....................................
33,889
41,712
31,418
29,463
45,820
31,231
34,431
30,926
32,512
44,595
35,331
42,955
32,184
30,373
47,186
32,724
35,308
32,268
33,485
45,889
4.3
3.0
2.4
3.1
3.0
4.8
2.5
4.3
3.0
2.9
Atlantic City, NJ .....................................................................
Auburn-Opelika, AL ...............................................................
Augusta-Richmond County, GA-SC ......................................
Austin-Round Rock, TX .........................................................
Bakersfield, CA ......................................................................
Baltimore-Towson, MD ..........................................................
Bangor, ME ............................................................................
Barnstable Town, MA ............................................................
Baton Rouge, LA ...................................................................
Battle Creek, MI .....................................................................
36,735
29,196
34,588
43,500
34,165
43,486
30,707
35,123
34,523
37,994
38,018
30,468
35,638
45,737
36,020
45,177
31,746
36,437
37,245
39,362
3.5
4.4
3.0
5.1
5.4
3.9
3.4
3.7
7.9
3.6
Bay City, MI ...........................................................................
Beaumont-Port Arthur, TX .....................................................
Bellingham, WA .....................................................................
Bend, OR ...............................................................................
Billings, MT ............................................................................
Binghamton, NY ....................................................................
Birmingham-Hoover, AL ........................................................
Bismarck, ND .........................................................................
Blacksburg-Christiansburg-Radford, VA ................................
Bloomington, IN .....................................................................
33,572
36,530
31,128
31,492
31,748
33,290
39,353
31,504
32,196
30,080
35,094
39,026
32,618
33,319
33,270
35,048
40,798
32,550
34,024
30,913
4.5
6.8
4.8
5.8
4.8
5.3
3.7
3.3
5.7
2.8
Bloomington-Normal, IL .........................................................
Boise City-Nampa, ID ............................................................
Boston-Cambridge-Quincy, MA-NH ......................................
Boulder, CO ...........................................................................
Bowling Green, KY ................................................................
Bremerton-Silverdale, WA .....................................................
Bridgeport-Stamford-Norwalk, CT .........................................
Brownsville-Harlingen, TX .....................................................
Brunswick, GA .......................................................................
Buffalo-Niagara Falls, NY ......................................................
39,404
34,623
54,199
49,115
31,306
36,467
71,095
24,893
30,902
35,302
41,359
36,734
56,809
50,944
32,529
37,694
74,890
25,795
32,717
36,950
5.0
6.1
4.8
3.7
3.9
3.4
5.3
3.6
5.9
4.7
Burlington, NC .......................................................................
Burlington-South Burlington, VT ............................................
Canton-Massillon, OH ...........................................................
Cape Coral-Fort Myers, FL ....................................................
Carson City, NV .....................................................................
Casper, WY ...........................................................................
Cedar Rapids, IA ...................................................................
Champaign-Urbana, IL ..........................................................
Charleston, WV .....................................................................
Charleston-North Charleston, SC ..........................................
31,084
38,582
32,080
35,649
38,428
34,810
37,902
33,278
35,363
33,896
32,835
40,548
33,132
37,065
40,115
38,307
38,976
34,422
36,887
35,267
5.6
5.1
3.3
4.0
4.4
10.0
2.8
3.4
4.3
4.0
Charlotte-Gastonia-Concord, NC-SC ....................................
Charlottesville, VA .................................................................
Chattanooga, TN-GA .............................................................
Cheyenne, WY ......................................................................
Chicago-Naperville-Joliet, IL-IN-WI .......................................
Chico, CA ..............................................................................
Cincinnati-Middletown, OH-KY-IN .........................................
Clarksville, TN-KY .................................................................
Cleveland, TN ........................................................................
Cleveland-Elyria-Mentor, OH .................................................
43,728
37,392
33,743
32,208
46,609
30,007
40,343
29,870
32,030
39,973
45,732
39,051
35,358
35,306
48,631
31,557
41,447
30,949
33,075
41,325
4.6
4.4
4.8
9.6
4.3
5.2
2.7
3.6
3.3
3.4
Coeur d’Alene, ID ..................................................................
College Station-Bryan, TX .....................................................
Colorado Springs, CO ...........................................................
Columbia, MO ........................................................................
Columbia, SC ........................................................................
Columbus, GA-AL ..................................................................
Columbus, IN .........................................................................
Columbus, OH .......................................................................
Corpus Christi, TX .................................................................
Corvallis, OR .........................................................................
28,208
29,032
37,268
31,263
33,386
31,370
38,446
39,806
32,975
39,357
29,797
30,239
38,325
32,207
35,209
32,334
40,107
41,168
35,399
40,586
5.6
4.2
2.8
3.0
5.5
3.1
4.3
3.4
7.4
3.1
See footnotes at end of table.
92
Percent
change,
2005-06
2005
Monthly Labor Review • September 2008
26. Average annual wages for 2005 and 2006 for all covered
workers1 by metropolitan area — Continued
Average annual wages3
Metropolitan area2
Percent
change,
2005-06
2005
2006
Cumberland, MD-WV ............................................................
Dallas-Fort Worth-Arlington, TX ............................................
Dalton, GA .............................................................................
Danville, IL .............................................................................
Danville, VA ...........................................................................
Davenport-Moline-Rock Island, IA-IL .....................................
Dayton, OH ............................................................................
Decatur, AL ............................................................................
Decatur, IL .............................................................................
Deltona-Daytona Beach-Ormond Beach, FL .........................
$28,645
45,337
32,848
31,861
28,449
35,546
37,922
33,513
38,444
29,927
$29,859
47,525
33,266
33,141
28,870
37,559
39,387
34,883
39,375
31,197
4.2
4.8
1.3
4.0
1.5
5.7
3.9
4.1
2.4
4.2
Denver-Aurora, CO ................................................................
Des Moines, IA ......................................................................
Detroit-Warren-Livonia, MI ....................................................
Dothan, AL .............................................................................
Dover, DE ..............................................................................
Dubuque, IA ...........................................................................
Duluth, MN-WI .......................................................................
Durham, NC ...........................................................................
Eau Claire, WI .......................................................................
El Centro, CA .........................................................................
45,940
39,760
46,790
30,253
33,132
32,414
32,638
46,743
30,763
29,879
48,232
41,358
47,455
31,473
34,571
33,044
33,677
49,314
31,718
30,035
5.0
4.0
1.4
4.0
4.3
1.9
3.2
5.5
3.1
0.5
Elizabethtown, KY .................................................................
Elkhart-Goshen, IN ................................................................
Elmira, NY .............................................................................
El Paso, TX ............................................................................
Erie, PA .................................................................................
Eugene-Springfield, OR .........................................................
Evansville, IN-KY ...................................................................
Fairbanks, AK ........................................................................
Fajardo, PR ...........................................................................
Fargo, ND-MN .......................................................................
30,912
35,573
32,989
28,666
32,010
32,295
35,302
39,399
20,011
32,291
32,072
35,878
33,968
29,903
33,213
33,257
36,858
41,296
21,002
33,542
3.8
0.9
3.0
4.3
3.8
3.0
4.4
4.8
5.0
3.9
Farmington, NM .....................................................................
Fayetteville, NC .....................................................................
Fayetteville-Springdale-Rogers, AR-MO ...............................
Flagstaff, AZ ..........................................................................
Flint, MI ..................................................................................
Florence, SC ..........................................................................
Florence-Muscle Shoals, AL ..................................................
Fond du Lac, WI ....................................................................
Fort Collins-Loveland, CO .....................................................
Fort Smith, AR-OK .................................................................
33,695
30,325
34,598
30,733
37,982
32,326
28,885
32,634
36,612
29,599
36,220
31,281
35,734
32,231
39,409
33,610
29,518
33,376
37,940
30,932
7.5
3.2
3.3
4.9
3.8
4.0
2.2
2.3
3.6
4.5
Fort Walton Beach-Crestview-Destin, FL ..............................
Fort Wayne, IN ......................................................................
Fresno, CA ............................................................................
Gadsden, AL ..........................................................................
Gainesville, FL .......................................................................
Gainesville, GA ......................................................................
Glens Falls, NY ......................................................................
Goldsboro, NC .......................................................................
Grand Forks, ND-MN .............................................................
Grand Junction, CO ...............................................................
32,976
34,717
32,266
28,438
32,992
33,828
31,710
28,316
28,138
31,611
34,409
35,641
33,504
29,499
34,573
34,765
32,780
29,331
29,234
33,729
4.3
2.7
3.8
3.7
4.8
2.8
3.4
3.6
3.9
6.7
Grand Rapids-Wyoming, MI ..................................................
Great Falls, MT ......................................................................
Greeley, CO ...........................................................................
Green Bay, WI .......................................................................
Greensboro-High Point, NC ...................................................
Greenville, NC .......................................................................
Greenville, SC .......................................................................
Guayama, PR ........................................................................
Gulfport-Biloxi, MS .................................................................
Hagerstown-Martinsburg, MD-WV .........................................
36,941
28,021
33,636
35,467
34,876
31,433
34,469
23,263
31,688
33,202
38,056
29,542
35,144
36,677
35,898
32,432
35,471
24,551
34,688
34,621
3.0
5.4
4.5
3.4
2.9
3.2
2.9
5.5
9.5
4.3
Hanford-Corcoran, CA ...........................................................
Harrisburg-Carlisle, PA ..........................................................
Harrisonburg, VA ...................................................................
Hartford-West Hartford-East Hartford, CT .............................
Hattiesburg, MS .....................................................................
Hickory-Lenoir-Morganton, NC ..............................................
Hinesville-Fort Stewart, GA ...................................................
Holland-Grand Haven, MI ......................................................
Honolulu, HI ...........................................................................
Hot Springs, AR .....................................................................
29,989
39,144
30,366
50,154
28,568
30,090
30,062
36,362
37,654
27,024
31,148
39,807
31,522
51,282
30,059
31,323
31,416
36,895
39,009
27,684
3.9
1.7
3.8
2.2
5.2
4.1
4.5
1.5
3.6
2.4
Houma-Bayou Cane-Thibodaux, LA ......................................
Houston-Baytown-Sugar Land, TX ........................................
Huntington-Ashland, WV-KY-OH ...........................................
Huntsville, AL .........................................................................
Idaho Falls, ID .......................................................................
Indianapolis, IN ......................................................................
Iowa City, IA ..........................................................................
Ithaca, NY ..............................................................................
Jackson, MI ...........................................................................
Jackson, MS ..........................................................................
33,696
47,157
31,415
42,401
29,795
39,830
34,785
36,457
35,879
33,099
38,417
50,177
32,648
44,659
31,632
41,307
35,913
38,337
36,836
34,605
14.0
6.4
3.9
5.3
6.2
3.7
3.2
5.2
2.7
4.5
See footnotes at end of table.
Monthly Labor Review • September 2008 93
Current Labor Statistics: Labor Force Data
26. Average annual wages for 2005 and 2006 for all covered
workers1 by metropolitan area — Continued
Average annual wages3
Metropolitan area2
2006
Jackson, TN ...........................................................................
Jacksonville, FL .....................................................................
Jacksonville, NC ....................................................................
Janesville, WI ........................................................................
Jefferson City, MO .................................................................
Johnson City, TN ...................................................................
Johnstown, PA .......................................................................
Jonesboro, AR .......................................................................
Joplin, MO .............................................................................
Kalamazoo-Portage, MI .........................................................
$33,286
38,224
24,803
34,107
30,991
29,840
29,335
28,550
29,152
36,042
$34,477
40,192
25,854
36,732
31,771
31,058
29,972
28,972
30,111
37,099
3.6
5.1
4.2
7.7
2.5
4.1
2.2
1.5
3.3
2.9
Kankakee-Bradley, IL ............................................................
Kansas City, MO-KS ..............................................................
Kennewick-Richland-Pasco, WA ...........................................
Killeen-Temple-Fort Hood, TX ...............................................
Kingsport-Bristol-Bristol, TN-VA ............................................
Kingston, NY ..........................................................................
Knoxville, TN .........................................................................
Kokomo, IN ............................................................................
La Crosse, WI-MN .................................................................
Lafayette, IN ..........................................................................
31,802
39,749
38,453
30,028
33,568
30,752
35,724
44,462
31,029
35,176
32,389
41,320
38,750
31,511
35,100
33,697
37,216
45,808
31,819
35,380
1.8
4.0
0.8
4.9
4.6
9.6
4.2
3.0
2.5
0.6
Lafayette, LA .........................................................................
Lake Charles, LA ...................................................................
Lakeland, FL ..........................................................................
Lancaster, PA ........................................................................
Lansing-East Lansing, MI ......................................................
Laredo, TX .............................................................................
Las Cruces, NM .....................................................................
Las Vegas-Paradise, NV .......................................................
Lawrence, KS ........................................................................
Lawton, OK ............................................................................
34,729
33,728
32,235
35,264
38,135
27,401
28,569
38,940
28,492
28,459
38,170
35,883
33,530
36,171
39,890
28,051
29,969
40,139
29,896
29,830
9.9
6.4
4.0
2.6
4.6
2.4
4.9
3.1
4.9
4.8
Lebanon, PA ..........................................................................
Lewiston, ID-WA ....................................................................
Lewiston-Auburn, ME ............................................................
Lexington-Fayette, KY ...........................................................
Lima, OH ...............................................................................
Lincoln, NE ............................................................................
Little Rock-North Little Rock, AR ...........................................
Logan, UT-ID .........................................................................
Longview, TX .........................................................................
Longview, WA ........................................................................
30,704
29,414
31,008
36,683
32,630
32,711
34,920
25,869
32,603
33,993
31,790
30,776
32,231
37,926
33,790
33,703
36,169
26,766
35,055
35,140
3.5
4.6
3.9
3.4
3.6
3.0
3.6
3.5
7.5
3.4
Los Angeles-Long Beach-Santa Ana, CA .............................
Louisville, KY-IN ....................................................................
Lubbock, TX ..........................................................................
Lynchburg, VA .......................................................................
Macon, GA .............................................................................
Madera, CA ...........................................................................
Madison, WI ...........................................................................
Manchester-Nashua, NH .......................................................
Mansfield, OH ........................................................................
Mayaguez, PR .......................................................................
46,592
37,144
30,174
32,025
33,110
29,356
38,210
45,066
32,688
19,597
48,680
38,673
31,977
33,242
34,126
31,213
40,007
46,659
33,171
20,619
4.5
4.1
6.0
3.8
3.1
6.3
4.7
3.5
1.5
5.2
McAllen-Edinburg-Pharr, TX ..................................................
Medford, OR ..........................................................................
Memphis, TN-MS-AR ............................................................
Merced, CA ............................................................................
Miami-Fort Lauderdale-Miami Beach, FL ..............................
Michigan City-La Porte, IN .....................................................
Midland, TX ...........................................................................
Milwaukee-Waukesha-West Allis, WI ....................................
Minneapolis-St. Paul-Bloomington, MN-WI ...........................
Missoula, MT .........................................................................
25,315
30,502
39,094
30,209
40,174
30,724
38,267
40,181
45,507
29,627
26,712
31,697
40,580
31,147
42,175
31,383
42,625
42,049
46,931
30,652
5.5
3.9
3.8
3.1
5.0
2.1
11.4
4.6
3.1
3.5
Mobile, AL ..............................................................................
Modesto, CA ..........................................................................
Monroe, LA ............................................................................
Monroe, MI ............................................................................
Montgomery, AL ....................................................................
Morgantown, WV ...................................................................
Morristown, TN ......................................................................
Mount Vernon-Anacortes, WA ...............................................
Muncie, IN .............................................................................
Muskegon-Norton Shores, MI ................................................
33,496
34,325
29,264
39,449
33,441
31,529
31,215
31,387
32,172
33,035
36,126
35,468
30,618
40,938
35,383
32,608
31,914
32,851
30,691
33,949
7.9
3.3
4.6
3.8
5.8
3.4
2.2
4.7
-4.6
2.8
Myrtle Beach-Conway-North Myrtle Beach, SC ....................
Napa, CA ...............................................................................
Naples-Marco Island, FL .......................................................
Nashville-Davidson--Murfreesboro, TN .................................
New Haven-Milford, CT .........................................................
New Orleans-Metairie-Kenner, LA .........................................
New York-Northern New Jersey-Long Island, NY-NJ-PA ......
Niles-Benton Harbor, MI ........................................................
Norwich-New London, CT .....................................................
Ocala, FL ...............................................................................
26,642
40,180
38,211
38,753
43,931
37,239
57,660
35,029
42,151
30,008
27,905
41,788
39,320
41,003
44,892
42,434
61,388
36,967
43,184
31,330
4.7
4.0
2.9
5.8
2.2
14.0
6.5
5.5
2.5
4.4
See footnotes at end of table.
94
Percent
change,
2005-06
2005
Monthly Labor Review • September 2008
26. Average annual wages for 2005 and 2006 for all covered
workers1 by metropolitan area — Continued
Average annual wages3
Metropolitan area2
Percent
change,
2005-06
2005
2006
Ocean City, NJ ......................................................................
Odessa, TX ............................................................................
Ogden-Clearfield, UT .............................................................
Oklahoma City, OK ................................................................
Olympia, WA ..........................................................................
Omaha-Council Bluffs, NE-IA ................................................
Orlando, FL ............................................................................
Oshkosh-Neenah, WI ............................................................
Owensboro, KY .....................................................................
Oxnard-Thousand Oaks-Ventura, CA ...................................
$31,033
33,475
31,195
33,142
36,230
36,329
36,466
38,820
31,379
44,597
$31,801
37,144
32,890
35,846
37,787
38,139
37,776
39,538
32,491
45,467
2.5
11.0
5.4
8.2
4.3
5.0
3.6
1.8
3.5
2.0
Palm Bay-Melbourne-Titusville, FL ........................................
Panama City-Lynn Haven, FL ...............................................
Parkersburg-Marietta, WV-OH ..............................................
Pascagoula, MS ....................................................................
Pensacola-Ferry Pass-Brent, FL ...........................................
Peoria, IL ...............................................................................
Philadelphia-Camden-Wilmington, PA-NJ-DE-MD ................
Phoenix-Mesa-Scottsdale, AZ ...............................................
Pine Bluff, AR ........................................................................
Pittsburgh, PA ........................................................................
38,287
31,894
30,747
34,735
32,064
39,871
46,454
40,245
30,794
38,809
39,778
33,341
32,213
36,287
33,530
42,283
48,647
42,220
32,115
40,759
3.9
4.5
4.8
4.5
4.6
6.0
4.7
4.9
4.3
5.0
Pittsfield, MA ..........................................................................
Pocatello, ID ..........................................................................
Ponce, PR .............................................................................
Portland-South Portland-Biddeford, ME ................................
Portland-Vancouver-Beaverton, OR-WA ...............................
Port St. Lucie-Fort Pierce, FL ................................................
Poughkeepsie-Newburgh-Middletown, NY ............................
Prescott, AZ ...........................................................................
Providence-New Bedford-Fall River, RI-MA ..........................
Provo-Orem, UT ....................................................................
35,807
27,686
19,660
35,857
41,048
33,235
38,187
29,295
37,796
30,395
36,707
28,418
20,266
36,979
42,607
34,408
39,528
30,625
39,428
32,308
2.5
2.6
3.1
3.1
3.8
3.5
3.5
4.5
4.3
6.3
Pueblo, CO ............................................................................
Punta Gorda, FL ....................................................................
Racine, WI .............................................................................
Raleigh-Cary, NC ..................................................................
Rapid City, SD .......................................................................
Reading, PA ..........................................................................
Redding, CA ..........................................................................
Reno-Sparks, NV ...................................................................
Richmond, VA ........................................................................
Riverside-San Bernardino-Ontario, CA .................................
30,165
31,937
37,659
39,465
28,758
36,210
32,139
38,453
41,274
35,201
30,941
32,370
39,002
41,205
29,920
38,048
33,307
39,537
42,495
36,668
2.6
1.4
3.6
4.4
4.0
5.1
3.6
2.8
3.0
4.2
Roanoke, VA .........................................................................
Rochester, MN .......................................................................
Rochester, NY .......................................................................
Rockford, IL ...........................................................................
Rocky Mount, NC ..................................................................
Rome, GA ..............................................................................
Sacramento--Arden-Arcade--Roseville, CA ...........................
Saginaw-Saginaw Township North, MI ..................................
St. Cloud, MN ........................................................................
St. George, UT ......................................................................
32,987
41,296
37,991
35,652
30,983
33,896
42,800
36,325
31,705
26,046
33,912
42,941
39,481
37,424
31,556
34,850
44,552
37,747
33,018
28,034
2.8
4.0
3.9
5.0
1.8
2.8
4.1
3.9
4.1
7.6
St. Joseph, MO-KS ................................................................
St. Louis, MO-IL .....................................................................
Salem, OR .............................................................................
Salinas, CA ............................................................................
Salisbury, MD ........................................................................
Salt Lake City, UT ..................................................................
San Angelo, TX .....................................................................
San Antonio, TX ....................................................................
San Diego-Carlsbad-San Marcos, CA ...................................
Sandusky, OH .......................................................................
30,009
39,985
31,289
36,067
32,240
36,857
29,530
35,097
43,824
32,631
31,253
41,354
32,764
37,974
33,223
38,630
30,168
36,763
45,784
33,526
4.1
3.4
4.7
5.3
3.0
4.8
2.2
4.7
4.5
2.7
San Francisco-Oakland-Fremont, CA ...................................
San German-Cabo Rojo, PR .................................................
San Jose-Sunnyvale-Santa Clara, CA ..................................
San Juan-Caguas-Guaynabo, PR .........................................
San Luis Obispo-Paso Robles, CA ........................................
Santa Barbara-Santa Maria-Goleta, CA ................................
Santa Cruz-Watsonville, CA ..................................................
Santa Fe, NM ........................................................................
Santa Rosa-Petaluma, CA ....................................................
Sarasota-Bradenton-Venice, FL ............................................
58,634
18,745
71,970
23,952
33,759
39,080
38,016
33,253
40,017
33,905
61,343
19,498
76,608
24,812
35,146
40,326
40,776
35,320
41,533
35,751
4.6
4.0
6.4
3.6
4.1
3.2
7.3
6.2
3.8
5.4
Savannah, GA .......................................................................
Scranton--Wilkes-Barre, PA ..................................................
Seattle-Tacoma-Bellevue, WA ..............................................
Sheboygan, WI ......................................................................
Sherman-Denison, TX ...........................................................
Shreveport-Bossier City, LA ..................................................
Sioux City, IA-NE-SD .............................................................
Sioux Falls, SD ......................................................................
South Bend-Mishawaka, IN-MI ..............................................
Spartanburg, SC ....................................................................
34,104
32,057
46,644
35,067
32,800
31,962
31,122
33,257
34,086
35,526
35,684
32,813
49,455
35,908
34,166
33,678
31,826
34,542
35,089
37,077
4.6
2.4
6.0
2.4
4.2
5.4
2.3
3.9
2.9
4.4
See footnotes at end of table.
Monthly Labor Review • September 2008 95
Current Labor Statistics: Labor Force Data
26. Average annual wages for 2005 and 2006 for all covered
workers1 by metropolitan area — Continued
Average annual wages3
Metropolitan area2
2006
Spokane, WA .........................................................................
Springfield, IL .........................................................................
Springfield, MA ......................................................................
Springfield, MO ......................................................................
Springfield, OH ......................................................................
State College, PA ..................................................................
Stockton, CA ..........................................................................
Sumter, SC ............................................................................
Syracuse, NY .........................................................................
Tallahassee, FL .....................................................................
$32,621
39,299
36,791
30,124
30,814
34,109
35,030
27,469
36,494
33,548
$34,016
40,679
37,962
30,786
31,844
35,392
36,426
29,294
38,081
35,018
4.3
3.5
3.2
2.2
3.3
3.8
4.0
6.6
4.3
4.4
Tampa-St. Petersburg-Clearwater, FL ..................................
Terre Haute, IN ......................................................................
Texarkana, TX-Texarkana, AR ..............................................
Toledo, OH ............................................................................
Topeka, KS ............................................................................
Trenton-Ewing, NJ .................................................................
Tucson, AZ ............................................................................
Tulsa, OK ...............................................................................
Tuscaloosa, AL ......................................................................
Tyler, TX ................................................................................
36,374
30,597
31,302
35,848
33,303
52,034
35,650
35,211
34,124
34,731
38,016
31,341
32,545
37,039
34,806
54,274
37,119
37,637
35,613
36,173
4.5
2.4
4.0
3.3
4.5
4.3
4.1
6.9
4.4
4.2
Utica-Rome, NY .....................................................................
Valdosta, GA .........................................................................
Vallejo-Fairfield, CA ...............................................................
Vero Beach, FL ......................................................................
Victoria, TX ............................................................................
Vineland-Millville-Bridgeton, NJ .............................................
Virginia Beach-Norfolk-Newport News, VA-NC .....................
Visalia-Porterville, CA ............................................................
Waco, TX ...............................................................................
Warner Robins, GA ...............................................................
30,902
25,712
38,431
32,591
34,327
36,387
34,580
28,582
32,325
36,762
32,457
26,794
40,225
33,823
36,642
37,749
36,071
29,772
33,450
38,087
5.0
4.2
4.7
3.8
6.7
3.7
4.3
4.2
3.5
3.6
Washington-Arlington-Alexandria, DC-VA-MD-WV ...............
Waterloo-Cedar Falls, IA .......................................................
Wausau, WI ...........................................................................
Weirton-Steubenville, WV-OH ...............................................
Wenatchee, WA .....................................................................
Wheeling, WV-OH .................................................................
Wichita, KS ............................................................................
Wichita Falls, TX ....................................................................
Williamsport, PA ....................................................................
Wilmington, NC ......................................................................
55,525
33,123
33,259
30,596
27,163
29,808
35,976
29,343
30,699
31,792
58,057
34,329
34,438
31,416
28,340
30,620
38,763
30,785
31,431
32,948
4.6
3.6
3.5
2.7
4.3
2.7
7.7
4.9
2.4
3.6
Winchester, VA-WV ...............................................................
Winston-Salem, NC ...............................................................
Worcester, MA .......................................................................
Yakima, WA ...........................................................................
Yauco, PR .............................................................................
York-Hanover, PA ..................................................................
Youngstown-Warren-Boardman, OH-PA ...............................
Yuba City, CA ........................................................................
Yuma, AZ ...............................................................................
33,787
36,654
41,094
27,334
17,818
36,834
32,176
32,133
27,168
34,895
37,712
42,726
28,401
19,001
37,226
33,852
33,642
28,369
3.3
2.9
4.0
3.9
6.6
1.1
5.2
4.7
4.4
1 Includes workers covered by Unemployment
Insurance (UI) and Unemployment Compensation
for Federal Employees (UCFE) programs.
2 Includes data for Metropolitan Statistical
Areas (MSA) as defined by OMB Bulletin No.
04-03 as of February 18, 2004.
96
Percent
change,
2005-06
2005
Monthly Labor Review • September 2008
3 Each year’s total is based on the MSA
definition for the specific year. Annual changes
include differences resulting from changes in
MSA definitions.
4 Totals do not include the six MSAs within
Puerto Rico.
27. Annual data: Employment status of the population
[Numbers in thousands]
Employment status
1997
Civilian noninstitutional population...........
Civilian labor force............................……
Labor force participation rate...............
Employed............................…………
Employment-population ratio..........
Unemployed............................………
Unemployment rate........................
Not in the labor force............................…
1
203,133
136,297
67.1
129,558
63.8
6,739
4.9
66,837
19981
205,220
137,673
67.1
131,463
64.1
6,210
4.5
67,547
19991
20001
20011
2002
2003
2004
2005
2006
2007
207,753
139,368
67.1
133,488
64.3
5,880
4.2
68,385
212,577
142,583
67.1
136,891
64.4
5,692
4
69,994
215,092
143,734
66.8
136,933
63.7
6,801
4.7
71,359
217,570
144,863
66.6
136,485
62.7
8,378
5.8
72,707
221,168
146,510
66.2
137,736
62.3
8,774
6
74,658
223,357
147,401
66
139,252
62.3
8,149
5.5
75,956
226,082
149,320
66
141,730
62.7
7,591
5.1
76,762
228,815
151,428
66.2
144,427
63.1
7,001
4.6
77,387
231,867
153,124
66
146,047
63
7,078
4.6
78,743
Not strictly comparable with prior years.
28. Annual data: Employment levels by industry
[In thousands]
Industry
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Total private employment............................…
103,113
106,021
108,686
110,996
110,707
108,828
108,416
109,814
111,899
114,184
115,717
Total nonfarm employment……………………
Goods-producing............................………
Natural resources and mining.................
Construction............................……………
Manufacturing............................…………
122,776
23,886
654
5,813
17,419
125,930
24,354
645
6,149
17,560
128,993
24,465
598
6,545
17,322
131,785
24,649
599
6,787
17,263
131,826
23,873
606
6,826
16,441
130,341
22,557
583
6,716
15,259
129,999
21,816
572
6,735
14,510
131,435
21,882
591
6,976
14,315
133,703
22,190
628
7,336
14,226
136,174
22,570
684
7,689
14,197
137,969
22,378
722
7,624
14,032
Private service-providing..........................
79,227
Trade, transportation, and utilities..........
24,700
Wholesale trade............................……… 5,663.90
Retail trade............................………… 14,388.90
Transportation and warehousing.........
4,026.50
Utilities............................………………
620.9
Information............................……………
3,084
Financial activities............................……
7,178
Professional and business services……
14,335
Education and health services…………
14,087
11,018
Leisure and hospitality……………………
Other services……………………………
4,825
81,667
25,186
5,795.20
14,609.30
4,168.00
613.4
3,218
7,462
15,147
14,446
11,232
4,976
84,221
25,771
5,892.50
14,970.10
4,300.30
608.5
3,419
7,648
15,957
14,798
11,543
5,087
86,346
26,225
5,933.20
15,279.80
4,410.30
601.3
3,631
7,687
16,666
15,109
11,862
5,168
86,834
25,983
5,772.70
15,238.60
4,372.00
599.4
3,629
7,807
16,476
15,645
12,036
5,258
86,271
25,497
5,652.30
15,025.10
4,223.60
596.2
3,395
7,847
15,976
16,199
11,986
5,372
86,599
25,287
5,607.50
14,917.30
4,185.40
577
3,188
7,977
15,987
16,588
12,173
5,401
87,932
25,533
5,662.90
15,058.20
4,248.60
563.8
3,118
8,031
16,395
16,953
12,493
5,409
89,709
25,959
5,764.40
15,279.60
4,360.90
554
3,061
8,153
16,954
17,372
12,816
5,395
91,615
26,231
5,897.60
15,319.30
4,465.80
548.5
3,055
8,363
17,552
17,838
13,143
5,432
93,339
26,472
6,005.30
15,382.00
4,531.20
553.5
3,087
8,446
17,920
18,377
13,565
5,472
19,909
20,307
20,790
21,118
21,513
21,583
21,621
21,804
21,990
22,252
Government……………………………………
19,664
Monthly Labor Review • September 2008 97
Current Labor Statistics: Labor Force Data
29. Annual data: Average hours and earnings of production or nonsupervisory workers on nonfarm
payrolls, by industry
Industry
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Private sector:
Average weekly hours.......…….................................
Average hourly earnings (in dollars).........................
Average weekly earnings (in dollars)........................
34.5
12.51
431.86
34.5
13.01
448.56
34.3
13.49
463.15
34.3
14.02
481.01
34
14.54
493.79
33.9
14.97
506.72
33.7
15.37
518.06
33.7
15.69
529.09
33.8
16.13
544.33
33.9
16.76
567.87
33.8
17.41
589.36
Goods-producing:
Average weekly hours.............................................
Average hourly earnings (in dollars).......................
Average weekly earnings (in dollars)......................
41.1
13.82
568.43
40.8
14.23
580.99
40.8
14.71
599.99
40.7
15.27
621.86
39.9
15.78
630.04
39.9
16.33
651.61
39.8
16.8
669.13
40
17.19
688.17
40.1
17.6
705.31
40.5
18.02
729.87
40.5
18.64
755.73
46.2
15.57
720.11
44.9
16.2
727.28
44.2
16.33
721.74
44.4
16.55
734.92
44.6
17
757.92
43.2
17.19
741.97
43.6
17.56
765.94
44.5
18.07
803.82
45.6
18.72
853.71
45.6
19.9
908.01
45.9
20.99
962.54
Average weekly hours............................................
Average hourly earnings (in dollars)......................
Average weekly earnings (in dollars).....................
Manufacturing:
38.9
15.67
609.48
38.8
16.23
629.75
39
16.8
655.11
39.2
17.48
685.78
38.7
18
695.89
38.4
18.52
711.82
38.4
18.95
726.83
38.3
19.23
735.55
38.6
19.46
750.22
39
20.02
781.04
38.9
20.94
814.83
Average weekly hours............................................
Average hourly earnings (in dollars)......................
Average weekly earnings (in dollars).....................
Private service-providing:
41.7
13.14
548.22
41.4
13.45
557.12
41.4
13.85
573.17
41.3
14.32
590.65
40.3
14.76
595.19
40.5
15.29
618.75
40.4
15.74
635.99
40.8
16.15
658.59
40.7
16.56
673.37
41.1
16.8
690.83
41.2
17.23
710.51
Average weekly hours..………................................
Average hourly earnings (in dollars).......................
Average weekly earnings (in dollars)......................
32.8
12.07
395.51
32.8
12.61
413.5
32.7
13.09
427.98
32.7
13.62
445.74
32.5
14.18
461.08
32.5
14.59
473.8
32.4
14.99
484.81
32.3
15.29
494.22
32.4
15.74
509.58
32.5
16.42
532.84
32.4
17.09
554.47
Trade, transportation, and utilities:
Average weekly hours.............................................
Average hourly earnings (in dollars).......................
Average weekly earnings (in dollars)......................
Wholesale trade:
34.3
11.9
407.57
34.2
12.39
423.3
33.9
12.82
434.31
33.8
13.31
449.88
33.5
13.7
459.53
33.6
14.02
471.27
33.6
14.34
481.14
33.5
14.58
488.42
33.4
14.92
498.43
33.4
15.4
514.61
33.4
15.82
528.22
Average weekly hours.........................................
Average hourly earnings (in dollars)...................
Average weekly earnings (in dollars)..................
Retail trade:
38.8
14.41
559.39
38.6
15.07
582.21
38.6
15.62
602.77
38.8
16.28
631.4
38.4
16.77
643.45
38
16.98
644.38
37.9
17.36
657.29
37.8
17.65
667.09
37.7
18.16
685
38
18.91
718.3
38.2
19.56
747.7
Average weekly hours.........................................
Average hourly earnings (in dollars)...................
Average weekly earnings (in dollars)..................
Transportation and warehousing:
Average weekly hours.........................................
Average hourly earnings (in dollars)...................
Average weekly earnings (in dollars)..................
Utilities:
Average weekly hours.........................................
Average hourly earnings (in dollars)...................
Average weekly earnings (in dollars)..................
Information:
Average weekly hours.........................................
Average hourly earnings (in dollars)...................
Average weekly earnings (in dollars)..................
Financial activities:
38.8
14.41
559.39
38.6
15.07
582.21
38.6
15.62
602.77
38.8
16.28
631.4
38.4
16.77
643.45
38
16.98
644.38
37.9
17.36
657.29
37.8
17.65
667.09
37.7
18.16
685
38
18.91
718.3
30.2
12.8
747.7
39.4
13.78
542.55
38.7
14.12
546.86
37.6
14.55
547.97
37.4
15.05
562.31
36.7
15.33
562.7
36.8
15.76
579.75
36.8
16.25
598.41
37.2
16.52
614.82
37
16.7
618.58
36.9
17.28
637.14
37
17.76
656.95
42
20.59
865.26
42
21.48
902.94
42
22.03
924.59
42
22.75
955.66
41.4
23.58
977.18
40.9
41.1
40.9
41.1
41.4
42.4
23.96
24.77
25.61
26.68
27.42
27.93
979.09 1,017.27 1,048.44 1,095.90 1,136.08 1,185.08
36.3
17.14
622.4
36.6
17.67
646.52
36.7
18.4
675.32
36.8
19.07
700.89
36.9
19.8
731.11
36.5
20.2
738.17
36.2
21.01
760.81
36.3
21.4
777.05
36.5
22.06
805
36.6
23.23
850.81
36.4
23.92
871.03
Average weekly hours.........................................
Average hourly earnings (in dollars)...................
Average weekly earnings (in dollars)..................
Professional and business services:
Average weekly hours.........................................
Average hourly earnings (in dollars)...................
Average weekly earnings (in dollars)..................
Education and health services:
Average weekly hours.........................................
Average hourly earnings (in dollars)...................
Average weekly earnings (in dollars)..................
Leisure and hospitality:
Average weekly hours.........................................
Average hourly earnings (in dollars)...................
Average weekly earnings (in dollars)..................
Other services:
Average weekly hours.........................................
Average hourly earnings (in dollars)...................
Average weekly earnings (in dollars)..................
35.7
13.22
472.37
36
13.93
500.95
35.8
14.47
517.57
35.9
14.98
537.37
35.8
15.59
558.02
35.6
16.17
575.51
35.5
17.14
609.08
35.5
17.52
622.87
35.9
17.94
645.1
35.8
18.8
672.4
35.9
19.66
706.01
34.3
13.57
465.51
34.3
14.27
490
34.4
14.85
510.99
34.5
15.52
535.07
34.2
16.33
557.84
34.2
16.81
574.66
34.1
17.21
587.02
34.2
17.48
597.56
34.2
18.08
618.87
34.6
19.12
662.23
34.8
20.15
700.96
32.2
12.56
404.65
32.2
13
418.82
32.1
13.44
431.35
32.2
13.95
449.29
32.3
14.64
473.39
32.4
15.21
492.74
32.3
15.64
505.69
32.4
16.15
523.78
32.6
16.71
544.59
32.5
17.38
564.95
32.6
18.03
587.2
26
7.32
190.52
26.2
7.67
200.82
26.1
7.96
208.05
26.1
8.32
217.2
25.8
8.57
220.73
25.8
8.81
227.17
25.6
9
230.42
25.7
9.15
234.86
25.7
9.38
241.36
25.7
9.75
250.11
25.5
10.41
265.03
32.7
11.29
368.63
32.6
11.79
384.25
32.5
12.26
398.77
32.5
12.73
413.41
32.3
13.27
428.64
32
13.72
439.76
31.4
13.84
434.41
31
13.98
433.04
30.9
14.34
443.37
30.9
14.77
456.6
30.9
15.22
470.05
Natural resources and mining
Average weekly hours............................................
Average hourly earnings (in dollars)......................
Average weekly earnings (in dollars).....................
Construction:
NOTE: Data reflect the conversion to the 2002 version of the North American Industry Classification System (NAICS), replacing the Standard Industrial Classification
(SIC) system. N AICS-based data by industry are not comparable with SIC-based data.
98
Monthly Labor Review • September 2008
30. Employment Cost Index, compensation,1 by occupation and industry group
[December 2005 = 100]
2006
Series
June
Sept.
2007
Dec.
Mar.
June
2008
Sept.
Dec.
Mar.
Percent change
June
3 months
ended
12 months
ended
June 2008
2
Civilian workers ……….…….........…………………………………….…
101.6
102.7
103.3
104.2
105.0
106.1
106.7
107.6
108.3
0.7
3.1
Management, professional, and related………………………
Management, business, and financial……………………
Professional and related……………………………………
Sales and office…………………………………………………
Sales and related……………………………………………
Office and administrative support…………………………
101.6
101.9
101.4
101.6
101.1
101.9
103.0
102.7
103.2
102.4
101.7
102.8
103.7
103.2
104.0
103.0
102.3
103.5
104.7
104.4
104.9
103.8
102.4
104.7
105.5
105.2
105.7
104.8
103.6
105.5
106.7
106.2
107.0
105.5
104.1
106.4
107.2
106.6
107.6
106.4
105.2
107.1
108.3
108.2
108.4
106.8
105.0
108.0
109.0
108.9
109.0
107.7
106.1
108.6
.6
.6
.6
.8
1.0
.6
3.3
3.5
3.1
2.8
2.4
2.9
Natural resources, construction, and maintenance…………
Construction and extraction………………………………
Installation, maintenance, and repair……………………
Production, transportation, and material moving……………
Production……………………………………………………
Transportation and material moving………………………
Service occupations……………………………………………
102.0
102.0
102.0
101.1
101.0
101.3
101.4
103.0
103.0
103.0
101.8
101.6
102.2
102.5
103.6
103.7
103.6
102.4
102.0
102.8
103.5
104.1
104.3
103.7
102.7
102.1
103.4
104.8
105.1
105.7
104.4
103.5
102.8
104.4
105.5
106.1
106.5
105.6
104.2
103.3
105.3
106.9
106.8
107.4
106.2
104.7
104.1
105.6
107.7
107.7
108.5
106.7
105.6
104.8
106.6
108.4
108.4
109.6
107.0
106.2
105.3
107.3
109.1
.6
1.0
.3
.6
.5
.7
.6
3.1
3.7
2.5
2.6
2.4
2.8
3.4
Workers by industry
Goods-producing………………………………………………
Manufacturing…………………………………………………
Service-providing………………………………………………
Education and health services……………………………
Health care and social assistance………………………
Hospitals…………………………………………………
Nursing and residential care facilities………………
Education services………………………………………
Elementary and secondary schools…………………
101.3
101.0
101.6
101.3
102.0
101.9
101.4
100.7
100.5
102.0
101.4
102.9
103.5
103.5
103.2
102.6
103.4
103.5
102.5
101.8
103.5
104.2
104.3
104.0
103.7
104.1
104.2
102.9
102.0
104.4
104.9
105.4
105.1
104.5
104.5
104.6
103.9
102.9
105.2
105.5
106.1
105.7
105.0
104.9
105.0
104.4
103.2
106.4
107.2
107.1
106.7
105.6
107.3
107.4
105.0
103.8
107.0
107.9
107.9
107.5
106.3
107.9
107.9
106.1
104.7
107.8
108.6
108.9
108.4
107.3
108.3
108.2
106.8
105.1
108.5
109.2
109.6
109.2
108.2
108.9
108.8
.7
.4
.6
.6
.6
.7
.8
.6
.6
2.8
2.1
3.1
3.5
3.3
3.3
3.0
3.8
3.6
Public administration ……………………………………… 101.2
Workers by occupational group
3
102.4
103.8
105.6
106.6
108.0
109.1
109.7
110.1
.4
3.3
101.7
102.5
103.2
104.0
104.9
105.7
106.3
107.3
108.0
.7
3.0
Workers by occupational group
Management, professional, and related………………………
Management, business, and financial……………………
Professional and related……………………………………
Sales and office…………………………………………………
Sales and related……………………………………………
Office and administrative support…………………………
Natural resources, construction, and maintenance…………
Construction and extraction…………………………………
Installation, maintenance, and repair………………………
Production, transportation, and material moving……………
Production……………………………………………………
Transportation and material moving………………………
Service occupations……………………………………………
101.9
102.0
101.8
101.6
101.1
101.9
102.1
102.2
102.1
101.1
101.0
101.2
101.5
102.9
102.7
103.1
102.3
101.7
102.7
103.0
103.1
103.0
101.7
101.6
102.0
102.3
103.5
103.1
103.9
102.9
102.3
103.4
103.6
103.7
103.4
102.3
102.0
102.6
103.1
104.6
104.3
104.9
103.7
102.4
104.5
104.0
104.4
103.5
102.5
102.1
103.1
104.5
105.5
105.1
105.9
104.7
103.6
105.4
105.0
105.7
104.1
103.3
102.8
104.1
105.2
106.4
106.0
106.7
105.3
104.2
106.0
105.9
106.5
105.2
103.9
103.2
104.9
106.4
106.8
106.3
107.3
106.1
105.2
106.7
106.7
107.4
105.8
104.5
104.0
105.3
107.0
108.1
108.0
108.3
106.6
105.0
107.8
107.6
108.6
106.3
105.5
104.8
106.4
107.8
108.9
108.7
109.0
107.5
106.2
108.5
108.3
109.7
106.6
106.0
105.2
107.2
108.7
.7
.6
.6
.8
1.1
.6
.7
1.0
.3
.5
.4
.8
.8
3.2
3.4
2.9
2.7
2.5
2.9
3.1
3.8
2.4
2.6
2.3
3.0
3.3
Workers by industry and occupational group
Goods-producing industries……………………………………
Management, professional, and related……………………
Sales and office………………………………………………
Natural resources, construction, and maintenance………
Production, transportation, and material moving………..
101.3
100.7
102.7
101.9
101.0
102.0
101.6
102.1
102.7
101.6
102.5
102.0
102.8
103.3
102.0
102.9
102.7
103.0
104.0
102.1
103.9
103.8
103.7
105.3
102.9
104.4
104.3
104.1
106.1
103.3
105.0
104.4
104.8
107.0
104.0
106.1
106.1
105.1
108.1
104.8
106.8
106.6
106.3
109.0
105.3
.7
.5
1.1
.8
.5
2.8
2.7
2.5
3.5
2.3
Construction…………………………………………………
Manufacturing…………………………………………………
Management, professional, and related…………………
Sales and office……………………………………………
Natural resources, construction, and maintenance……
Production, transportation, and material moving……..
101.9
101.0
100.5
102.8
100.8
100.9
103.0
101.4
101.3
101.3
101.5
101.5
103.6
101.8
101.4
102.1
102.1
101.9
104.7
102.0
102.0
102.4
101.7
101.9
105.9
102.9
103.3
103.2
102.4
102.6
106.9
103.2
103.3
103.5
102.8
103.1
107.6
103.8
103.5
104.3
103.9
103.8
108.9
104.7
104.9
105.0
104.6
104.5
110.1
105.1
105.2
106.1
104.5
105.0
1.1
.4
.3
1.0
-.1
.5
4.0
2.1
1.8
2.8
2.1
2.3
Service-providing industries…………………………………
Management, professional, and related……………………
Sales and office………………………………………………
Natural resources, construction, and maintenance………
Production, transportation, and material moving………..
Service occupations…………………………………………
101.8
102.2
101.5
102.5
101.3
101.5
102.7
103.2
102.3
103.6
101.9
102.3
103.4
103.8
102.9
104.0
102.6
103.1
104.3
105.0
103.7
104.0
103.0
104.5
105.2
105.9
104.8
104.5
104.0
105.3
106.1
106.8
105.4
105.7
104.7
106.4
106.7
107.3
106.3
106.2
105.2
107.1
107.7
108.5
106.8
106.7
106.4
107.9
108.5
109.3
107.7
107.3
107.0
108.7
.7
.7
.8
.6
.6
.7
3.1
3.2
2.8
2.7
2.9
3.2
Trade, transportation, and utilities…………………………
101.4
102.4
103.0
103.1
104.2
104.7
105.5
106.1
107.3
1.1
3.0
Private industry workers………………………………………
See footnotes at end of table.
Monthly Labor Review • September 2008 99
Current Labor Statistics: Compensation & Industrial Relations
30. Continued—Employment Cost Index, compensation,1 by occupation and industry group
[December 2005 = 100]
2006
Series
June
Sept.
2007
Dec.
Mar.
June
2008
Sept.
Dec.
Mar.
Percent change
June
3 months
ended
12 months
ended
June 2008
Wholesale trade……………………………………………
Retail trade…………………………………………………
Transportation and warehousing………………………
Utilities………………………………………………………
Information…………………………………………………
Financial activities…………………………………………
Finance and insurance…………………………………
Real estate and rental and leasing……………………
Professional and business services………………………
Education and health services……………………………
Education services………………………………………
Health care and social assistance……………………
Hospitals………………………………………………
Leisure and hospitality……………………………………
Accommodation and food services……………………
Other services, except public administration……………
100.8
101.2
101.0
109.3
102.1
101.8
102.4
99.3
102.2
101.8
101.5
101.9
102.0
101.3
101.4
102.7
102.4
101.9
101.6
110.1
103.0
102.1
102.6
100.2
102.9
103.2
103.2
103.2
103.2
102.4
102.5
103.6
102.9
102.7
102.2
110.4
103.2
102.5
102.9
100.8
103.5
104.1
104.2
104.1
103.9
103.7
104.0
104.0
103.7
102.9
102.8
102.8
104.3
104.2
104.6
102.2
104.7
105.1
104.5
105.2
105.0
105.3
105.8
105.7
104.6
103.9
104.0
104.7
105.6
104.6
104.9
103.0
105.9
105.7
104.9
105.9
105.6
106.0
106.4
106.1
104.2
105.1
104.5
105.0
105.8
105.4
105.7
104.1
106.9
106.9
106.7
106.9
106.5
107.5
108.1
107.1
105.3
106.1
104.5
105.6
106.1
105.6
106.1
103.7
107.5
107.7
107.5
107.8
107.3
108.1
108.6
107.6
105.7
106.6
105.6
106.5
106.1
106.8
107.0
105.5
109.0
108.6
108.1
108.8
108.2
109.0
109.5
108.7
107.2
107.6
106.4
108.1
106.2
107.3
107.7
105.7
109.9
109.4
109.1
109.4
109.1
109.3
110.0
109.4
1.4
.9
.8
1.5
.1
.5
.7
.2
.8
.7
.9
.6
.8
.3
.5
.6
2.5
3.6
2.3
3.2
.6
2.6
2.7
2.6
3.8
3.5
4.0
3.3
3.3
3.1
3.4
3.1
100.9
103.2
104.1
105.1
105.7
107.6
108.4
108.9
109.4
.5
3.5
Workers by occupational group
Management, professional, and related………………………
Professional and related……………………………………
Sales and office…………………………………………………
Office and administrative support…………………………
Service occupations……………………………………………
100.8
100.8
101.5
101.6
101.2
103.3
103.4
103.3
103.5
103.1
104.0
104.0
104.1
104.2
104.5
104.9
104.8
105.6
105.7
105.4
105.4
105.3
106.2
106.4
106.3
107.5
107.5
107.9
108.2
108.0
108.3
108.2
108.6
108.9
109.1
108.8
108.6
108.8
109.3
109.7
109.3
109.1
109.3
109.8
110.0
.5
.5
.5
.5
.3
3.7
3.6
2.9
3.2
3.5
Workers by industry
Education and health services………………………………
Education services………………………………………
Schools…………………………………………………
Elementary and secondary schools………………
Health care and social assistance………………………
Hospitals…………………………………………………
100.8
100.5
100.5
100.5
102.9
101.3
103.7
103.5
103.5
103.6
105.1
103.3
104.3
104.1
104.1
104.2
105.7
104.3
104.8
104.6
104.6
104.7
107.1
105.6
105.3
105.0
104.9
105.0
107.6
106.3
107.5
107.4
107.4
107.4
108.6
107.5
108.2
108.0
108.0
108.0
109.3
108.2
108.6
108.4
108.4
108.3
110.1
109.2
109.1
108.8
108.8
108.8
111.1
109.7
.5
.4
.4
.5
.9
.5
3.6
3.6
3.7
3.6
3.3
3.2
101.2
102.4
103.8
105.6
106.6
108.0
109.1
109.7
110.1
.4
3.3
State and local government workers…………………………
3
Public administration ………………………………………
1
Cost (cents per hour worked) measured in the Employment Cost Index consists of
wages, salaries, and employer cost of employee benefits.
2
Consists of private industry workers (excluding farm and household workers) and
State and local government (excluding Federal Government) workers.
3
Consists of legislative, judicial, administrative, and regulatory activities.
100
Monthly Labor Review • September 2008
NOTE: The Employment Cost Index data reflect the conversion to the 2002 North
American Classification System (NAICS) and the 2000 Standard Occupational
Classification (SOC) system. The NAICS and SOC data shown prior to 2006 are for
informational purposes only. Series based on NAICS and SOC became the official BLS
estimates starting in March 2006.
31. Employment Cost Index, wages and salaries, by occupation and industry group
[December 2005 = 100]
2006
Series
June
Sept.
2007
Dec.
Mar.
June
2008
Sept.
Dec.
Mar.
Percent change
June
3 months
ended
12 months
ended
June 2008
1
Civilian workers ……….…….........…………………………………….…
101.5
102.6
103.2
104.3
105.0
106.0
106.7
107.6
108.4
0.7
3.2
Management, professional, and related………………………
Management, business, and financial……………………
Professional and related……………………………………
Sales and office…………………………………………………
Sales and related……………………………………………
Office and administrative support…………………………
101.6
102.0
101.4
101.6
101.3
101.8
102.9
102.7
103.1
102.4
102.0
102.6
103.6
103.1
103.8
103.0
102.5
103.3
104.7
104.7
104.7
103.8
102.7
104.5
105.4
105.4
105.3
104.8
103.9
105.3
106.6
106.4
106.7
105.4
104.3
106.1
107.1
106.7
107.4
106.2
105.5
106.8
108.2
108.2
108.3
106.7
105.2
107.8
109.0
109.0
109.0
107.7
106.6
108.5
.7
.7
.6
.9
1.3
.6
3.4
3.4
3.5
2.8
2.6
3.0
Natural resources, construction, and maintenance…………
Construction and extraction………………………………
Installation, maintenance, and repair……………………
Production, transportation, and material moving……………
Production……………………………………………………
Transportation and material moving………………………
Service occupations……………………………………………
101.8
101.9
101.6
101.2
101.2
101.2
101.2
102.7
102.9
102.6
101.9
101.8
102.1
102.2
103.4
103.7
103.1
102.5
102.3
102.7
103.2
104.3
104.6
103.8
103.2
103.2
103.3
104.6
105.1
105.7
104.4
103.9
103.6
104.2
105.3
106.3
106.6
105.8
104.7
104.3
105.1
106.5
107.1
107.7
106.4
105.1
104.7
105.5
107.3
108.1
109.0
107.0
106.1
105.7
106.6
108.0
109.0
109.9
107.8
106.9
106.5
107.3
108.7
.8
.8
.7
.8
.8
.7
.6
3.7
4.0
3.3
2.9
2.8
3.0
3.2
Workers by industry
Goods-producing………………………………………………
Manufacturing…………………………………………………
Service-providing………………………………………………
Education and health services……………………………
Health care and social assistance………………………
Hospitals…………………………………………………
Nursing and residential care facilities………………
Education services………………………………………
Elementary and secondary schools…………………
101.8
101.7
101.5
101.1
101.8
101.7
101.2
100.5
100.3
102.3
101.9
102.7
103.1
103.2
102.9
102.2
103.0
102.9
102.9
102.3
103.3
103.8
104.1
103.8
103.3
103.5
103.4
103.9
103.3
104.3
104.4
105.1
104.8
104.1
103.7
103.6
104.7
103.9
105.1
104.9
105.9
105.6
104.7
104.0
103.8
105.4
104.5
106.2
106.6
107.1
106.7
105.8
106.2
106.0
106.0
104.9
106.8
107.4
107.9
107.4
106.4
106.9
106.6
107.1
105.9
107.7
108.0
108.9
108.4
107.4
107.3
107.0
108.0
106.7
108.5
108.7
109.6
109.4
108.1
107.9
107.5
.8
.8
.7
.6
.6
.9
.7
.6
.5
3.2
2.7
3.2
3.6
3.5
3.6
3.2
3.8
3.6
Public administration ……………………………………… 101.1
102.0
103.5
104.5
105.2
106.4
107.4
108.2
108.6
.4
3.2
101.7
102.5
103.2
104.3
105.1
106.0
106.6
107.6
108.4
.7
3.1
Workers by occupational group
Management, professional, and related………………………
Management, business, and financial……………………
Professional and related……………………………………
Sales and office…………………………………………………
Sales and related……………………………………………
Office and administrative support…………………………
Natural resources, construction, and maintenance…………
Construction and extraction…………………………………
Installation, maintenance, and repair………………………
Production, transportation, and material moving……………
Production……………………………………………………
Transportation and material moving………………………
Service occupations……………………………………………
102.0
102.2
101.8
101.6
101.3
101.9
101.8
102.0
101.6
101.2
101.2
101.2
101.3
103.0
102.8
103.1
102.4
102.0
102.6
102.8
103.0
102.6
101.8
101.7
102.0
102.0
103.6
103.1
104.0
103.0
102.6
103.3
103.4
103.7
103.0
102.4
102.2
102.6
102.9
104.9
104.7
105.1
103.8
102.8
104.5
104.2
104.7
103.7
103.1
103.1
103.2
104.6
105.8
105.5
106.0
104.8
104.0
105.4
105.1
105.8
104.2
103.8
103.6
104.1
105.3
106.7
106.3
107.0
105.3
104.4
106.0
106.2
106.7
105.6
104.5
104.2
105.0
106.5
107.2
106.6
107.6
106.2
105.5
106.7
107.1
107.8
106.1
105.0
104.6
105.4
107.1
108.5
108.2
108.7
106.7
105.3
107.7
108.1
109.2
106.8
106.0
105.6
106.5
107.9
109.3
109.0
109.5
107.7
106.6
108.5
109.0
110.1
107.6
106.8
106.4
107.4
108.8
.7
.7
.7
.9
1.2
.7
.8
.8
.7
.8
.8
.8
.8
3.3
3.3
3.3
2.8
2.5
2.9
3.7
4.1
3.3
2.9
2.7
3.2
3.3
Workers by industry and occupational group
Goods-producing industries……………………………………
Management, professional, and related……………………
Sales and office………………………………………………
Natural resources, construction, and maintenance………
Production, transportation, and material moving………..
101.8
101.7
103.4
101.9
101.3
102.3
102.4
102.2
102.7
101.9
102.9
102.8
103.1
103.4
102.4
103.9
104.4
103.4
104.4
103.2
104.7
105.3
104.1
105.6
103.7
105.4
105.9
104.7
106.5
104.4
106.0
106.0
105.5
107.6
104.8
107.1
107.7
105.8
108.8
105.7
108.0
108.4
107.2
109.6
106.6
.8
.6
1.3
.7
.9
3.2
2.9
3.0
3.8
2.8
Construction…………………………………………………
Manufacturing…………………………………………………
Management, professional, and related…………………
Sales and office……………………………………………
Natural resources, construction, and maintenance……
Production, transportation, and material moving……..
102.0
101.7
101.5
103.8
101.7
101.3
102.9
101.9
102.2
101.1
102.3
101.8
103.7
102.3
102.3
102.0
103.0
102.3
104.9
103.3
103.8
102.4
103.8
103.1
106.0
103.9
104.6
103.2
104.3
103.6
107.0
104.5
105.0
103.9
105.0
104.2
107.8
104.9
105.3
104.7
105.9
104.5
109.0
105.9
106.7
105.5
106.8
105.4
110.0
106.7
107.2
106.9
107.1
106.3
.9
.8
.5
1.3
.3
.9
3.8
2.7
2.5
3.6
2.7
2.6
Service-providing industries…………………………………
Management, professional, and related……………………
Sales and office………………………………………………
Natural resources, construction, and maintenance………
Production, transportation, and material moving………..
Service occupations…………………………………………
101.7
102.0
101.4
101.8
101.0
101.3
102.6
103.1
102.4
103.0
101.7
102.0
103.3
103.7
102.9
103.4
102.4
102.9
104.4
105.0
103.8
103.9
103.0
104.6
105.3
105.9
104.9
104.3
104.0
105.3
106.1
106.8
105.4
105.7
104.6
106.6
106.8
107.4
106.3
106.3
105.2
107.2
107.7
108.6
106.8
106.9
106.3
108.0
108.6
109.4
107.7
108.0
107.1
108.8
.8
.7
.8
1.0
.8
.7
3.1
3.3
2.7
3.5
3.0
3.3
Trade, transportation, and utilities…………………………
100.9
102.1
102.7
103.2
104.3
104.6
105.5
105.9
107.2
1.2
2.8
Workers by occupational group
2
Private industry workers………………………………………
See footnotes at end of table.
Monthly Labor Review • September 2008 101
Current Labor Statistics: Compensation & Industrial Relations
31. Continued—Employment Cost Index, wages and salaries, by occupation and industry group
[December 2005 = 100]
2006
Series
June
Sept.
2007
Dec.
Mar.
June
2008
Sept.
Dec.
Mar.
Percent change
June
3 months
ended
12 months
ended
June 2008
Wholesale trade……………………………………………
Retail trade…………………………………………………
Transportation and warehousing………………………
Utilities………………………………………………………
Information…………………………………………………
Financial activities…………………………………………
Finance and insurance…………………………………
Real estate and rental and leasing……………………
Professional and business services………………………
Education and health services……………………………
Education services………………………………………
Health care and social assistance……………………
Hospitals………………………………………………
Leisure and hospitality……………………………………
Accommodation and food services……………………
Other services, except public administration……………
100.7
100.9
100.7
102.1
101.7
102.3
102.8
99.9
102.3
101.6
101.4
101.6
101.8
101.3
101.3
102.6
102.7
101.9
101.4
103.0
102.6
102.5
102.9
100.8
103.0
103.0
103.1
103.0
102.9
102.3
102.2
103.4
103.0
102.8
101.9
103.5
102.4
102.8
103.2
101.4
103.5
104.0
104.1
103.9
103.7
103.7
103.8
103.8
103.8
103.1
102.5
104.3
103.8
104.7
105.4
101.6
104.8
104.8
104.2
104.9
104.6
105.7
106.0
105.7
104.8
104.2
103.7
105.5
104.9
104.9
105.5
102.4
105.9
105.6
104.6
105.8
105.4
106.4
106.5
106.1
104.0
105.1
104.1
106.1
105.2
106.0
106.5
103.6
106.7
106.9
106.4
107.0
106.5
108.1
108.4
107.3
105.2
106.1
104.2
106.8
105.3
105.9
106.6
103.1
107.5
107.7
107.4
107.8
107.2
108.8
109.0
107.9
105.2
106.4
105.0
108.0
105.3
107.2
107.9
104.5
109.1
108.6
107.9
108.7
108.2
109.7
110.0
109.2
107.2
107.6
106.0
109.3
106.3
107.7
108.4
104.7
110.0
109.2
108.6
109.4
109.2
109.9
110.4
109.9
1.9
1.1
1.0
1.2
.9
.5
.5
.2
.8
.6
.6
.6
.9
.2
.4
.6
2.3
3.3
2.2
3.6
1.3
2.7
2.7
2.2
3.9
3.4
3.8
3.4
3.6
3.3
3.7
3.6
100.8
102.8
103.5
104.1
104.6
106.4
107.1
107.7
108.2
.5
3.4
Workers by occupational group
Management, professional, and related………………………
Professional and related……………………………………
Sales and office…………………………………………………
Office and administrative support…………………………
Service occupations……………………………………………
100.7
100.7
101.2
101.4
100.8
102.9
103.0
102.6
102.7
102.4
103.5
103.6
103.2
103.4
103.9
104.0
103.9
104.5
104.7
104.5
104.3
104.2
104.8
105.0
105.2
106.3
106.3
106.3
106.5
106.5
107.0
107.0
107.0
107.3
107.7
107.6
107.5
107.4
107.8
108.3
108.2
108.1
107.9
108.3
108.6
.6
.6
.5
.5
.3
3.7
3.7
3.0
3.1
3.2
Workers by industry
Education and health services………………………………
Education services………………………………………
Schools…………………………………………………
Elementary and secondary schools………………
Health care and social assistance………………………
Hospitals…………………………………………………
100.7
100.4
100.4
100.3
103.0
101.4
103.1
103.0
103.0
103.0
104.8
103.1
103.6
103.4
103.4
103.4
105.5
104.4
104.0
103.7
103.6
103.6
106.6
105.7
104.2
103.9
103.9
103.8
107.2
106.5
106.3
106.1
106.1
106.0
108.2
107.6
107.1
106.8
106.8
106.6
109.2
108.6
107.5
107.2
107.2
106.9
110.1
109.8
108.1
107.7
107.7
107.5
111.0
110.3
.6
.5
.5
.6
.8
.5
3.7
3.7
3.7
3.6
3.5
3.6
101.1
102.0
103.5
104.5
105.2
106.4
107.4
108.2
108.6
.4
3.2
State and local government workers…………………………
2
Public administration ………………………………………
1
Consists of private industry workers (excluding farm and household workers) and
State and local government (excluding Federal Government) workers.
2
Consists of legislative, judicial, administrative, and regulatory activities.
NOTE: The Employment Cost Index data reflect the conversion to the 2002 North
102
Monthly Labor Review • September 2008
American Classification System (NAICS) and the 2000 Standard Occupational
Classification (SOC) system. The NAICS and SOC data shown prior to 2006 are for
informational purposes only. Series based on NAICS and SOC became the official
BLS estimates starting in March 2006.
32. Employment Cost Index, benefits, by occupation and industry group
[December 2005 = 100]
2006
Series
June
Sept.
2007
Dec.
Mar.
June
2008
Sept.
Dec.
Mar.
Percent change
June
3 months
ended
12 months
ended
June 2008
Civilian workers………………………………………………….
101.6
102.8
103.6
104.0
105.1
106.1
106.8
107.6
108.1
0.5
2.9
Private industry workers………………………………………… 101.7
102.5
103.1
103.2
104.3
105.0
105.6
106.5
107.0
.5
2.6
Workers by occupational group
Management, professional, and related………………………
Sales and office…………………………………………………
Natural resources, construction, and maintenance…………
Production, transportation, and material moving……………
101.8
101.6
102.7
101.0
102.8
102.0
103.5
101.6
103.4
102.9
104.0
102.0
103.8
103.4
103.4
101.2
104.9
104.3
104.8
102.4
105.6
105.2
105.3
102.7
106.0
106.0
105.9
103.7
107.3
106.5
106.5
104.4
107.9
107.0
107.0
104.5
.6
.5
.5
.1
2.9
2.6
2.1
2.1
Service occupations……………………………………………
102.2
103.0
103.6
104.2
105.1
106.0
106.7
107.6
108.5
.8
3.2
Goods-producing………………………………………………
100.4
Manufacturing………………………………………………… 99.7
Service-providing……………………………………………… 102.3
101.3
100.5
103.0
101.7
100.8
103.7
100.9
99.6
104.1
102.2
101.0
105.2
102.4
100.7
106.0
103.2
101.7
106.6
104.0
102.3
107.6
104.4
102.2
108.1
.4
-.1
.5
2.2
1.2
2.8
104.1
105.2
107.0
108.0
110.3
111.0
111.4
111.8
.4
3.5
Workers by industry
State and local government workers…………………………
101.3
NOTE: The Employment Cost Index data reflect the conversion to
the 2002 North American Classification System (NAICS) and the 2000
Standard Occupational Classification (SOC) system. The NAICS and
SOC data shown prior
to 2006 are for informational purposes only. Series based on NAICS and SOC became the official
BLS estimates starting in March 2006.
Monthly Labor Review • September 2008 103
Current Labor Statistics: Compensation & Industrial Relations
33. Employment Cost Index, private industry workers by bargaining status and region
[December 2005 = 100]
2006
Series
June
Sept.
2007
Dec.
Mar.
June
2008
Sept.
Dec.
Mar.
Percent change
June
3 months
ended
12 months
ended
June 2008
COMPENSATION
Workers by bargaining status1
Union…………………………………………………………………
Goods-producing…………………………………………………
Manufacturing…………………………………………………
Service-providing…………………………………………………
101.8
101.2
100.1
102.2
102.4
101.8
100.5
102.9
103.0
102.2
100.8
103.6
102.7
101.5
99.2
103.7
103.9
102.8
100.0
104.7
104.4
103.1
100.0
105.4
105.1
104.0
101.0
106.0
105.9
104.6
101.4
107.0
106.7
105.6
101.7
107.5
0.8
1.0
.3
.5
2.7
2.7
1.7
2.7
Nonunion……………………………………………………………
Goods-producing…………………………………………………
Manufacturing…………………………………………………
Service-providing…………………………………………………
101.7
101.4
101.3
101.8
102.6
102.0
101.7
102.7
103.2
102.5
102.1
103.4
104.2
103.3
102.8
104.4
105.1
104.2
103.7
105.3
105.9
104.8
104.1
106.2
106.5
105.4
104.6
106.8
107.5
106.5
105.6
107.7
108.3
107.1
106.2
108.6
.7
.6
.6
.8
3.0
2.8
2.4
3.1
Workers by region1
Northeast……………………………………………………………
South…………………………………………………………………
Midwest………………………………………………………………
West…………………………………………………………………
101.8
101.6
101.7
101.8
102.5
102.8
102.3
102.5
103.3
103.5
102.8
103.0
104.0
104.3
103.3
104.2
105.1
105.3
104.2
104.9
106.2
106.1
104.6
105.7
106.8
106.7
105.3
106.5
107.4
107.8
106.0
107.8
108.1
108.5
107.0
108.4
.7
.6
.9
.6
2.9
3.0
2.7
3.3
Workers by bargaining status1
Union…………………………………………………………………
Goods-producing…………………………………………………
Manufacturing…………………………………………………
Service-providing…………………………………………………
101.2
101.6
101.2
100.9
101.7
101.9
101.4
101.6
102.3
102.3
101.7
102.2
102.8
102.7
102.0
102.9
103.7
103.6
102.5
103.8
104.4
104.3
102.9
104.6
104.7
104.3
102.6
104.9
105.5
105.2
103.4
105.8
106.7
106.4
104.4
106.9
1.1
1.1
1.0
1.0
2.9
2.7
1.9
3.0
Nonunion……………………………………………………………
Goods-producing…………………………………………………
Manufacturing…………………………………………………
Service-providing…………………………………………………
101.8
101.9
101.8
101.7
102.7
102.4
102.0
102.7
103.3
103.0
102.5
103.4
104.5
104.2
103.6
104.6
105.3
105.0
104.2
105.4
106.2
105.8
104.9
106.3
106.9
106.4
105.5
107.0
107.9
107.7
106.6
107.9
108.7
108.4
107.3
108.8
.7
.6
.7
.8
3.2
3.2
3.0
3.2
Workers by region1
Northeast……………………………………………………………
South…………………………………………………………………
Midwest………………………………………………………………
West…………………………………………………………………
101.7
101.6
101.4
102.1
102.5
102.9
102.0
102.7
103.1
103.6
102.6
103.2
104.0
104.6
103.6
104.8
105.0
105.6
104.4
105.4
106.1
106.5
105.0
106.2
106.6
107.0
105.6
107.0
107.5
108.1
106.3
108.3
108.2
109.1
107.5
108.9
.7
.9
1.1
.6
3.0
3.3
3.0
3.3
WAGES AND SALARIES
1
The indexes are calculated differently from those for the
occupation and industry groups. For a detailed description of
the index calculation, see the Monthly Labor Review Technical
Note, "Estimation procedures for the Employment Cost Index,"
May 1982.
104
Monthly Labor Review • September 2008
NOTE: The Employment Cost Index data reflect the conversion to the 2002 North American
Classification System (NAICS) and the 2000 Standard Occupational Classification (SOC) system. The
NAICS and SOC data shown prior to 2006 are for informational purposes only. Series based on NAICS
and SOC became the official BLS estimates starting in March 2006.
34. National Compensation Survey: Retirement benefits in private industry by
access, participation, and selected series, 2003–2007
Series
Year
2003
2004
2005
2007 1
2006
All retirement
Percentage of workers with access
All workers………………………………………………………
57
59
60
60
White-collar occupations 2 ……………………………………
67
69
70
69
-
-
-
-
-
76
64
Management, professional, and related ……………….
61
Sales and office ……………………………………………
-
-
-
-
Blue-collar occupations 2………………………………………
59
59
60
62
-
-
-
-
-
61
Natural resources, construction, and maintenance...…
Production, transportation, and material moving…...…
Service occupations……………………………………………
-
-
-
-
65
28
31
32
34
36
Full-time…………………………………………………………
67
68
69
69
70
Part-time………………………………………………………
24
27
27
29
31
Union……………………………………………………………
86
84
88
84
84
Non-union………………………………………………………
54
56
56
57
58
Average wage less than $15 per hour……...………………
45
46
46
47
47
Average wage $15 per hour or higher……...………………
76
77
78
77
76
Goods-producing industries…………………………………
70
70
71
73
70
Service-providing industries…………………………………
53
55
56
56
58
Establishments with 1-99 workers……………………………
42
44
44
44
45
Establishments with 100 or more workers…………………
75
77
78
78
78
All workers………………………………………………………
49
50
50
51
51
White-collar occupations 2 ……………………………………
59
61
61
60
-
-
-
-
-
69
54
Percentage of workers participating
Management, professional, and related ……………….
Sales and office ……………………………………………
-
-
-
-
Blue-collar occupations 2………………………………………
50
50
51
52
-
-
-
-
-
51
Natural resources, construction, and maintenance…...
Production, transportation, and material moving…...…
Service occupations……………………………………………
-
-
-
-
54
21
22
22
24
25
Full-time…………………………………………………………
58
60
60
60
60
Part-time………………………………………………………
18
20
19
21
23
Union……………………………………………………………
83
81
85
80
81
Non-union………………………………………………………
45
47
46
47
47
Average wage less than $15 per hour……...………………
35
36
35
36
36
Average wage $15 per hour or higher……...………………
70
71
71
70
69
Goods-producing industries…………………………………
63
63
64
64
61
Service-providing industries…………………………………
45
47
47
47
48
Establishments with 1-99 workers……………………………
35
37
37
37
37
Establishments with 100 or more workers…………………
65
67
67
67
66
-
-
85
85
84
20
21
22
21
21
23
24
25
23
-
-
-
-
-
29
19
3
Take-up rate (all workers) ……………………………………
Defined Benefit
Percentage of workers with access
All workers………………………………………………………
2
White-collar occupations ……………………………………
Management, professional, and related ……………….
Sales and office ……………………………………………
2
Blue-collar occupations ………………………………………
Natural resources, construction, and maintenance...…
-
-
-
-
24
26
26
25
-
-
-
-
-
26
26
Production, transportation, and material moving…...…
-
-
-
-
Service occupations……………………………………………
8
6
7
8
8
Full-time…………………………………………………………
24
25
25
24
24
Part-time………………………………………………………
8
9
10
9
10
Union……………………………………………………………
74
70
73
70
69
Non-union………………………………………………………
15
16
16
15
15
Average wage less than $15 per hour……...………………
12
11
12
11
11
Average wage $15 per hour or higher……...………………
34
35
35
34
33
Goods-producing industries…………………………………
31
32
33
32
29
Service-providing industries…………………………………
17
18
19
18
19
9
9
10
9
9
34
35
37
35
34
Establishments with 1-99 workers……………………………
Establishments with 100 or more workers…………………
See footnotes at end of table.
Monthly Labor Review • September 2008 105
Current Labor Statistics: Compensation & Industrial Relations
34. Continued—National Compensation Survey: Retirement benefits in private industry
by access, participation, and selected series, 2003–2007
Series
Year
2003
2004
2005
2007
2006
1
Percentage of workers participating
All workers………………………………………………………
2
White-collar occupations ……………………………………
Management, professional, and related ……………….
Sales and office ……………………………………………
Blue-collar occupations 2……………………………………
Natural resources, construction, and maintenance...…
Production, transportation, and material moving…...…
Service occupations…………………………………………
Full-time………………………………………………………
Part-time………………………………………………………
Union……………………………………………………………
Non-union………………………………………………………
Average wage less than $15 per hour……...………………
20
22
24
7
24
8
72
15
11
21
24
25
6
24
9
69
15
11
21
24
26
7
25
9
72
15
11
20
22
25
7
23
8
68
14
10
20
28
17
25
25
7
23
9
67
15
10
Average wage $15 per hour or higher……...………………
33
35
34
33
32
Goods-producing industries…………………………………
31
31
32
31
28
Service-providing industries…………………………………
16
18
18
17
18
Establishments with 1-99 workers…………………………
8
9
9
9
9
Establishments with 100 or more workers…………………
33
34
36
33
32
Take-up rate (all workers) 3……………………………………
-
-
97
96
95
All workers………………………………………………………
51
53
53
54
55
White-collar occupations 2 ……………………………………
62
64
64
65
-
-
-
-
-
71
60
Defined Contribution
Percentage of workers with access
Management, professional, and related ……………….
-
-
-
-
Blue-collar occupations 2……………………………………
Sales and office ……………………………………………
49
49
50
53
-
Natural resources, construction, and maintenance...…
-
-
-
-
51
56
Production, transportation, and material moving…...…
-
-
-
-
Service occupations…………………………………………
23
27
28
30
32
Full-time………………………………………………………
60
62
62
63
64
Part-time………………………………………………………
21
23
23
25
27
Union……………………………………………………………
45
48
49
50
49
Non-union………………………………………………………
51
53
54
55
56
Average wage less than $15 per hour……...………………
40
41
41
43
44
Average wage $15 per hour or higher……...………………
67
68
69
69
69
Goods-producing industries…………………………………
60
60
61
63
62
Service-providing industries…………………………………
48
50
51
52
53
Establishments with 1-99 workers…………………………
38
40
40
41
42
Establishments with 100 or more workers…………………
65
68
69
70
70
All workers………………………………………………………
40
42
42
43
43
White-collar occupations 2 ……………………………………
51
53
53
53
-
-
-
-
-
60
47
Percentage of workers participating
Management, professional, and related ……………….
-
-
-
-
Blue-collar occupations 2……………………………………
Sales and office ……………………………………………
38
38
38
40
-
Natural resources, construction, and maintenance...…
-
-
-
-
40
41
Production, transportation, and material moving…...…
-
-
-
-
Service occupations…………………………………………
16
18
18
20
20
Full-time………………………………………………………
48
50
50
51
50
Part-time………………………………………………………
14
14
14
16
18
Union……………………………………………………………
39
42
43
44
41
Non-union………………………………………………………
40
42
41
43
43
Average wage less than $15 per hour……...………………
29
30
29
31
30
Average wage $15 per hour or higher……...………………
57
59
59
58
57
Goods-producing industries…………………………………
49
49
50
51
49
Service-providing industries…………………………………
37
40
39
40
41
Establishments with 1-99 workers…………………………
31
32
32
33
33
Establishments with 100 or more workers…………………
51
53
53
54
53
-
-
78
79
77
3
Take-up rate (all workers) ……………………………………
See footnotes at end of table.
106
Monthly Labor Review • September 2008
34. Continued—National Compensation Survey: Retirement benefits in private industry
by access, participation, and selected series, 2003–2007
Series
Year
2003
2004
2005
2007 1
2006
Employee Contribution Requirement
Employee contribution required…………………………
Employee contribution not required………………………
Not determinable……………………………………………
-
-
61
31
8
61
33
6
65
35
0
Percent of establishments
Offering retirement plans……………………………………
Offering defined benefit plans………………………………
Offering defined contribution plans……………………….
47
10
45
48
10
46
51
11
48
48
10
47
46
10
44
1
The 2002 North American Industry Classification System (NAICS) replaced the 1987 Standard Industrial Classification (SIC)
System. Estimates for goods-producing and service-providing (formerly service-producing) industries are considered comparable.
Also introduced was the 2000 Standard Occupational Classification (SOC) to replace the 1990 Census of Population system.
Only service occupations are considered comparable.
2
The white-collar and blue-collar occupation series were discontinued effective 2007.
3
The take-up rate is an estimate of the percentage of workers with access to a plan who participate in the plan.
Note: Where applicable, dashes indicate no employees in this category or data do not meet publication criteria.
Monthly Labor Review • September 2008 107
Current Labor Statistics: Compensation & Industrial Relations
35. National Compensation Survey: Health insurance benefits in private industry
by access, particpation, and selected series, 2003-2007
Series
Year
2003
2004
2005
2007
2006
1
Medical insurance
Percentage of workers with access
All workers…………………………………………………………………………
60
69
70
71
2
White-collar occupations ………………………………………………………
65
76
77
77
-
-
-
-
-
85
71
Management, professional, and related …………………………………
Sales and office………………………………………………………………
Blue-collar occupations 2………………………………………………………
Natural resources, construction, and maintenance………………………
71
-
-
-
-
64
76
77
77
-
-
-
-
-
76
Production, transportation, and material moving…………………………
-
-
-
-
78
Service occupations……………………………………………………………
38
42
44
45
46
Full-time…………………………………………………………………………
73
84
85
85
85
Part-time…………………………………………………………………………
17
20
22
22
24
Union………………………………………………………………………………
67
89
92
89
88
Non-union…………………………………………………………………………
59
67
68
68
69
Average wage less than $15 per hour…………………………………………
51
57
58
57
57
Average wage $15 per hour or higher…………………………………………
74
86
87
88
87
Goods-producing industries……………………………………………………
68
83
85
86
85
Service-providing industries……………………………………………………
57
65
66
66
67
Establishments with 1-99 workers………………………………………………
49
58
59
59
59
Establishments with 100 or more workers……………………………………
72
82
84
84
84
All workers…………………………………………………………………………
45
53
53
52
52
White-collar occupations 2 ………………………………………………………
50
59
58
57
-
-
-
-
-
67
48
Percentage of workers participating
Management, professional, and related …………………………………
Sales and office………………………………………………………………
Blue-collar occupations 2………………………………………………………
Natural resources, construction, and maintenance………………………
-
-
-
-
51
60
61
60
-
-
-
-
-
61
Production, transportation, and material moving…………………………
-
-
-
-
60
Service occupations……………………………………………………………
22
24
27
27
28
Full-time…………………………………………………………………………
56
66
66
64
64
Part-time…………………………………………………………………………
9
11
12
13
12
Union………………………………………………………………………………
60
81
83
80
78
Non-union…………………………………………………………………………
44
50
49
49
49
Average wage less than $15 per hour…………………………………………
35
40
39
38
37
Average wage $15 per hour or higher…………………………………………
61
71
72
71
70
Goods-producing industries……………………………………………………
57
69
70
70
68
Service-providing industries……………………………………………………
42
48
48
47
47
Establishments with 1-99 workers………………………………………………
36
43
43
43
42
Establishments with 100 or more workers……………………………………
55
64
65
63
62
-
-
75
74
73
All workers…………………………………………………………………………
40
46
46
46
46
2
White-collar occupations ………………………………………………………
47
53
54
53
-
-
-
-
-
62
47
3
Take-up rate (all workers) ………………………………………………………
Dental
Percentage of workers with access
Management, professional, and related …………………………………
Sales and office………………………………………………………………
2
Blue-collar occupations ………………………………………………………
Natural resources, construction, and maintenance………………………
-
-
-
47
47
46
-
-
-
-
-
43
Production, transportation, and material moving…………………………
-
-
-
-
49
Service occupations……………………………………………………………
22
25
25
27
28
Full-time…………………………………………………………………………
49
56
56
55
56
Part-time…………………………………………………………………………
9
13
14
15
16
Union………………………………………………………………………………
57
73
73
69
68
Non-union…………………………………………………………………………
38
43
43
43
44
Average wage less than $15 per hour…………………………………………
30
34
34
34
34
Average wage $15 per hour or higher…………………………………………
55
63
62
62
61
Goods-producing industries……………………………………………………
48
56
56
56
54
Service-providing industries……………………………………………………
37
43
43
43
44
Establishments with 1-99 workers………………………………………………
27
31
31
31
30
Establishments with 100 or more workers……………………………………
55
64
65
64
64
See footnotes at end of table.
108
40
Monthly Labor Review • September 2008
35. Continued—National Compensation Survey: Health insurance benefits in
private industry by access, particpation, and selected series, 2003-2007
Series
Year
2003
2004
2005
2007
2006
1
Percentage of workers participating
All workers……………………………………………………………………………
32
37
36
36
White-collar occupations 2 ………………………………………………………
37
43
42
41
-
Management, professional, and related ……………………………………
-
-
-
-
51
33
Sales and office…………………………………………………………………
Blue-collar occupations 2…………………………………………………………
Natural resources, construction, and maintenance…………………………
36
-
-
-
-
33
40
39
38
-
-
-
-
-
36
Production, transportation, and material moving……………………………
-
-
-
-
38
Service occupations………………………………………………………………
15
16
17
18
20
Full-time……………………………………………………………………………
40
46
45
44
44
Part-time……………………………………………………………………………
6
8
9
10
9
Union………………………………………………………………………………
51
68
67
63
62
Non-union…………………………………………………………………………
30
33
33
33
33
Average wage less than $15 per hour…………………………………………
22
26
24
23
23
Average wage $15 per hour or higher…………………………………………
47
53
52
52
51
Goods-producing industries………………………………………………………
42
49
49
49
45
Service-providing industries………………………………………………………
29
33
33
32
33
Establishments with 1-99 workers………………………………………………
21
24
24
24
24
Establishments with 100 or more workers………………………………………
44
52
51
50
49
Take-up rate (all workers) 3…………………………………………………………
-
-
78
78
77
Percentage of workers with access………………………………………………
25
29
29
29
29
Percentage of workers participating………………………………………………
19
22
22
22
22
Percentage of workers with access………………………………………………
-
-
64
67
68
Percentage of workers participating………………………………………………
-
-
48
49
49
Percent of estalishments offering healthcare benefits …………………......…
58
61
63
62
60
Vision care
Outpatient Prescription drug coverage
Percentage of medical premium paid by
Employer and Employee
Single coverage
Employer share……………………………………………………………………
82
82
82
82
81
Employee share…………………………………………………………………
18
18
18
18
19
Family coverage
Employer share……………………………………………………………………
70
69
71
70
71
Employee share…………………………………………………………………
30
31
29
30
29
1
The 2002 North American Industry Classification System (NAICS) replaced the 1987 Standard Industrial Classification (SIC)
System. Estimates for goods-producing and service-providing (formerly service-producing) industries are considered comparable.
Also introduced was the 2000 Standard Occupational Classification (SOC) to replace the 1990 Census of Population system.
Only service occupations are considered comparable.
2
The white-collar and blue-collar occupation series were discontinued effective 2007.
3
The take-up rate is an estimate of the percentage of workers with access to a plan who participate in the plan.
Note: Where applicable, dashes indicate no employees in this category or data do not meet publication criteria.
Monthly Labor Review • September 2008 109
Current Labor Statistics: Compensation & Industrial Relations
36. National Compensation Survey: Percent of workers in private industry
with access to selected benefits, 2003-2007
Year
Benefit
2003
2004
2005
2006
2007
Life insurance……………………………………………………
50
51
52
52
58
Short-term disabilty insurance…………………………………
39
39
40
39
39
Long-term disability insurance…………………………………
30
30
30
30
31
Long-term care insurance………………………………………
11
11
11
12
12
Flexible work place………………………………………………
4
4
4
4
5
Flexible benefits………………………………………………
-
-
17
17
17
Dependent care reimbursement account…………..………
-
-
29
30
31
Healthcare reimbursement account……………………...…
-
-
31
32
33
Health Savings Account………………………………...………
-
-
5
6
8
Employee assistance program……………………….…………
-
-
40
40
42
Section 125 cafeteria benefits
Paid leave
Holidays…………………………………………...……………
79
77
77
76
77
Vacations……………………………………………..………
79
77
77
77
77
Sick leave………………………………………..……………
-
59
58
57
57
Personal leave…………………………………………..……
-
-
36
37
38
Paid family leave…………………………………………….…
-
-
7
8
8
Unpaid family leave………………………………………..…
-
-
81
82
83
Employer assistance for child care…………………….………
18
14
14
15
15
Nonproduction bonuses………………………...………………
49
47
47
46
47
Family leave
Note: Where applicable, dashes indicate no employees in this category or data do not
meet publication criteria.
37. Work stoppages involving 1,000 workers or more
Annual average
Measure
2006
Number of stoppages:
Beginning in period.............................
In effect during period…......................
2007
2007
July
Aug.
Sept.
2008
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
Junep Julyp
May
20
23
21
23
1
1
1
1
5
6
3
3
1
2
2
4
0
1
2
3
2
4
1
2
2
4
2
2
1
1
Workers involved:
Beginning in period (in thousands)…..
70.1
In effect during period (in thousands)… 191.0
189.2
220.9
1.1
1.1
1.0
1.0
108.3
108.3
41.7
41.7
10.5
14.2
6.5
20.7
.0
10.5
6.2
16.7
5.7
11.9
2.3
6.0
3.4
9.4
4.2
4.2
8.5
8.5
Days idle:
Number (in thousands)….................... 2,687.5
1,264.8
6.6
9.0
261.5
73.9
284.0
254.8
220.5
148.8
140.9
104.4
125.0
12.3
42.5
.01
0
0
.01
0
.01
.01
.01
.01
0
0
0
0
0
1
Percent of estimated working time ……
.01
1
Agricultural and government employees are included in the total employed
and total working time; private household, forestry, and fishery employees are
excluded. An explanation of the measurement of idleness as a percentage of
the total time
110
Monthly Labor Review • September 2008
worked is found in "Total economy measures of strike idleness," Monthly Labor Review ,
October 1968, pp. 54–56.
NOTE:
p = preliminary.
38. 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
2006
CONSUMER PRICE INDEX
FOR ALL URBAN CONSUMERS
All items...........................................................................
All items (1967 = 100)......................................................
Food and beverages......................................................
Food..................….........................................................
Food at home…...........................................................
Cereals and bakery products….................................
Meats, poultry, fish, and eggs…................................
201.6
603.9
195.7
195.2
193.1
212.8
186.6
1
Dairy and related products ……….………………………… 181.4
Fruits and vegetables…............................................. 252.9
Nonalcoholic beverages and beverage
materials…..............................................................
Other foods at home…...............................................
Sugar and sweets….................................................
Fats and oils….........................................................
Other foods…...........................................................
Other miscellaneous foods
1,2
……….…………………
2008
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
July
207.342
621.106
203.300
202.916
201.245
222.107
195.616
208.299
623.970
203.533
203.121
201.401
223.297
196.690
207.917
622.827
204.289
203.885
202.126
223.981
197.204
208.490
624.543
205.279
204.941
203.193
223.372
198.323
208.936
625.879
206.124
205.796
204.333
224.691
198.474
210.177
629.598
206.563
206.277
204.745
225.668
198.616
210.036
629.174
206.936
206.704
205.208
226.461
198.755
211.080
632.301
208.837
208.618
207.983
228.661
200.035
211.693
634.139
209.462
209.166
208.329
233.389
199.688
213.528
639.636
209.692
209.385
208.203
236.261
199.775
214.823
643.515
211.365
211.102
210.851
240.034
200.770
216.632
648.933
212.251
212.054
211.863
244.192
200.960
218.815
655.474
213.383
213.243
213.171
245.758
202.914
219.964
658.915
215.326
215.299
215.785
250.321
205.075
194.770 197.899 201.739 203.541 205.319 205.959 205.299 206.905 208.166 206.171 207.680 207.778 209.117 213.981
262.628 254.616 252.845 259.100 263.648 268.407 272.482 279.072 272.129 268.446 272.746 276.481 277.957 280.209
147.4
169.6
171.5
168.0
185.0
153.432
173.275
176.772
172.921
188.244
113.9
115.105 115.017 116.072 114.628 114.850 115.396 115.267 115.162 118.182 117.321 118.500 118.744 118.453 120.510
1
Food away from home ……….………………………………… 199.4
1,2
Other food away from home ……….…………………… 136.6
Alcoholic beverages….................................................. 200.7
Housing.......................................................................... 203.2
Shelter...............…....................................................... 232.1
Rent of primary residence…...................................... 225.1
Lodging away from home……………………………… 136.0
3
2007
2007
206.659
144.068
207.026
209.586
240.611
234.679
153.384
174.440
178.235
173.691
189.518
206.931
144.785
207.624
211.286
242.067
234.732
154.791
174.686
178.256
174.251
189.781
207.756
145.376
208.264
211.098
242.238
235.311
155.007
174.201
178.172
174.105
189.076
208.805
146.752
208.408
210.865
241.990
236.058
155.545
174.695
177.236
176.050
189.695
209.275
146.074
209.126
210.701
242.405
237.135
154.299
173.963
178.600
175.327
188.340
209.854
146.628
209.018
210.745
242.207
238.169
153.648
174.057
178.631
176.068
188.325
210.233
145.814
208.704
210.933
242.372
239.102
157.863
176.085
180.193
181.813
190.037
211.070
146.649
210.425
212.244
243.871
239.850
157.805
177.863
180.588
184.878
192.064
211.878
148.385
212.044
213.026
244.786
240.325
158.089
178.238
182.214
182.808
192.597
212.537
148.564
212.407
214.389
245.995
240.874
159.730
181.806
184.878
190.640
195.993
213.083
148.667
213.503
214.890
246.004
241.474
158.336
182.680
185.097
193.364
196.787
213.967
149.666
213.532
215.809
246.069
241.803
158.320
183.804
185.558
196.150
197.888
215.015
149.873
213.912
217.941
247.083
242.640
159.346
185.725
187.067
201.205
199.566
216.376
151.120
214.394
219.610
248.075
243.367
142.813 153.016 150.236 144.480 143.172 136.703 133.545 140.176 144.092 149.434 146.378 145.634 148.621 153.032
238.2
246.235 246.149 246.815 247.487 248.075 248.876 249.532 250.106 250.481 250.966 251.418 251.576 252.170 252.504
116.5
194.7
177.1
234.9
182.1
127.0
119.5
114.1
110.7
117.004
200.632
181.744
251.453
186.262
126.875
118.998
112.368
110.296
116.577
206.140
187.624
245.680
193.184
126.894
113.500
109.568
101.291
116.926
204.334
185.453
246.542
190.710
126.520
114.439
109.032
103.237
116.783
204.264
185.306
252.580
190.158
126.193
119.535
112.380
110.973
116.640
200.836
181.509
261.745
185.337
126.233
121.846
114.953
113.402
116.997
202.161
182.725
291.845
184.753
126.252
121.204
114.807
112.166
117.003
203.006
183.516
299.296
185.155
126.066
118.257
112.026
109.418
117.435
204.796
185.107
306.937
186.475
126.515
115.795
110.691
104.367
117.622
205.795
185.994
308.269
187.376
126.753
117.839
112.917
106.340
117.701
209.221
189.693
332.139
190.105
127.423
120.881
114.994
110.645
118.422
213.302
194.121
342.811
194.379
127.332
122.113
116.653
111.221
118.411
219.881
201.212
363.872
200.999
127.598
120.752
116.479
108.722
119.092
231.412
213.762
389.423
213.375
127.625
117.019
112.011
104.312
118.764
239.039
221.742
395.706
221.805
127.884
114.357
109.669
100.049
116.5
123.5
180.9
177.0
113.948
122.374
184.682
180.778
108.759
119.375
187.690
183.619
110.221
120.329
184.480
180.408
113.611
123.183
184.532
180.586
117.149
124.675
184.952
180.919
117.339
125.005
190.677
186.839
113.779
122.258
189.984
186.134
113.861
121.148
190.839
186.978
115.750
122.377
190.520
186.571
116.037
124.407
195.189
191.067
116.358
126.212
198.608
194.574
114.582
125.537
205.262
201.133
111.555
123.568
211.787
207.257
109.218
122.421
212.806
208.038
2
New and used motor vehicles ……….…………………… 95.6
New vehicles…........................................................ 137.6
1
Used cars and trucks ……….……………………………… 140.0
Motor fuel…............................................................... 221.0
Gasoline (all types)…............................................... 219.9
Motor vehicle parts and equipment…........................ 117.3
Motor vehicle maintenance and repair…................... 215.6
Public transportation...............….................................. 226.6
Medical care................................................................... 336.2
Medical care commodities...............…......................... 285.9
Medical care services...............…................................ 350.6
Professional services…............................................. 289.3
Hospital and related services…................................. 468.1
2
Recreation ……….………………………………………….……… 110.9
1,2
Video and audio ……….……………………………………… 104.6
2
Education and communication ……….……………………… 116.8
94.303
136.254
135.747
239.070
237.959
121.583
222.963
230.002
351.054
289.999
369.302
300.792
498.922
111.443
102.949
119.577
93.961
135.415
136.024
252.909
251.883
121.514
223.487
235.767
351.643
290.257
370.008
301.131
499.400
111.347
102.779
119.025
94.121
135.204
137.138
238.194
237.108
121.730
224.019
233.112
352.961
291.164
371.461
302.259
501.026
111.139
102.311
120.311
93.985
134.927
137.142
239.104
237.993
122.292
224.302
230.694
353.723
291.340
372.432
302.410
504.206
111.400
102.759
121.273
94.201
135.344
136.950
239.048
237.819
123.017
224.939
232.725
355.653
292.161
374.750
303.532
510.006
111.753
103.157
121.557
94.562
136.250
136.616
262.282
260.943
123.487
225.672
233.758
357.041
293.201
376.250
303.780
515.359
111.842
102.719
121.409
94.754
136.664
136.943
258.132
256.790
123.928
226.120
233.408
357.661
293.610
376.940
304.784
515.677
111.705
102.691
121.506
94.834
136.827
137.203
260.523
259.338
124.282
227.732
234.334
360.459
295.355
380.135
306.529
523.313
112.083
102.986
121.762
94.581
136.279
137.248
259.242
257.845
125.225
228.731
235.724
362.155
296.130
382.196
307.928
527.971
112.365
103.171
121.766
94.318
135.727
137.225
278.739
276.497
126.325
229.765
242.929
363.000
297.308
382.872
308.726
528.968
112.731
103.548
121.832
93.973
135.175
136.787
294.291
291.910
126.049
230.528
244.164
363.184
296.951
383.292
309.227
530.144
112.874
103.477
122.073
93.705
134.669
136.325
322.124
319.787
126.824
231.730
251.600
363.396
294.896
384.505
310.917
531.022
112.987
102.988
122.348
93.598
134.516
135.980
347.418
344.981
127.824
233.162
264.681
363.616
295.194
384.685
311.317
531.606
112.991
102.306
122.828
93.650
134.397
135.840
349.731
347.357
129.118
234.788
270.002
363.963
294.777
385.361
311.926
533.558
113.277
102.203
123.445
Owners' equivalent rent of primary residence ………
1,2
Tenants' and household insurance ……….…………
Fuels and utilities…...................................................
Fuels...............…......................................................
Fuel oil and other fuels….......................................
Gas (piped) and electricity…..................................
Household furnishings and operations…...................
Apparel ..........................................................................
Men's and boys' apparel….........................................
Women's and girls' apparel…....................................
1
Infants' and toddlers' apparel ……….……………………
Footwear…................................................................
Transportation................................................................
Private transportation...............…................................
2
Education ……….………………………………………….……… 162.1
Educational books and supplies…........................... 388.9
Tuition, other school fees, and child care….............
1,2
Communication ……….………………………………………
1,2
Information and information processing
……….…
1,2
Telephone services ……….……………………………
Information and information processing
other than telephone services
1,4
……….……………
468.1
84.1
171.388 169.490 172.873 175.486 176.339 176.717 176.927 177.440 177.460 177.407 177.754 177.994 178.385 179.229
420.418 418.394 427.425 430.114 431.432 431.606 434.352 437.822 439.052 439.906 442.160 442.770 443.309 444.382
494.079 488.382 498.071 505.924 508.449 509.605 510.016 511.301 511.253 511.013 511.887 512.579 513.743 516.264
83.367 83.553 83.655 83.690 83.659 83.250 83.282 83.396 83.391 83.502 83.670 83.929 84.394 84.840
81.7
95.8
80.720
98.247
80.840
98.570
80.944
98.813
80.976
98.882
80.946
99.031
80.519
98.775
80.546
98.792
80.642
98.906
80.638
98.837
80.752
99.031
80.921
99.494
81.080 81.513 81.965
99.879 100.677 101.339
12.5
10.597
10.528
10.487
10.477
10.385
10.204
10.215
10.229
10.253
10.246
10.170
10.118
10.071
10.087
Personal computers and peripheral
1,2
120.9
321.7
519.9
108.411 107.439 106.575 105.806 104.336 100.104 100.000 100.998 100.545 100.359 98.853 97.028 95.663 94.711
333.328 333.415 333.325 334.801 335.680 336.379 337.633 339.052 340.191 341.827 343.410 344.709 345.885 346.810
554.184 553.987 555.217 559.636 560.626 561.967 566.696 572.684 575.227 574.890 576.359 581.185 589.904 596.782
1
Personal care ……….………………………………………….… 190.2
1
Personal care products ……….…………………………… 155.8
1
Personal care services ……….…………………………… 209.7
195.622 195.704 195.521 196.202 196.763 197.156 197.643 198.112 198.716 199.982 201.028 201.523 201.537 201.545
158.285 158.457 157.788 157.643 158.381 158.561 158.236 158.201 157.677 158.440 159.398 158.790 158.868 158.989
216.559 216.720 217.028 217.589 217.887 218.604 219.656 219.932 220.848 222.752 222.799 223.649 223.520 223.719
equipment ……….…………………………………
Other goods and services..............................................
Tobacco and smoking products...............…................
See footnotes at end of table.
Monthly Labor Review • September 2008 111
Current Labor Statistics: Price Data
38. 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
2006
2007
Series
Miscellaneous personal services...............…....
July
Aug.
2007
Sept. Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
2008
Apr.
May
June
July
313.6 324.984 324.579 325.566 327.783 328.056 328.610 329.908 332.183 333.826 335.427 337.685 339.824 340.547 340.077
Commodity and service group:
Commodities...........…............................................
Food and beverages….........................................
Commodities less food and beverages….............
Nondurables less food and beverages…............
Apparel ….........................................................
and apparel….................................................
Durables…..........................................................
Services…..............................................................
3
Rent of shelter ……….……………………………………
Transportation services…....................................
Other services…..................................................
Special indexes:
All items less food…............................................
All items less shelter…........................................
All items less medical care…...............................
Commodities less food….....................................
Nondurables less food….....................................
Nondurables less food and apparel….................
Nondurables….....................................................
3
Services less rent of shelter ……….…………………
Services less medical care services…................
Energy…..............................................................
All items less energy…........................................
All items less food and energy….......................
Commodities less food and energy…..............
Energy commodities......................................
Services less energy…....................................
164.0 167.509 167.938 166.955 167.952 168.664 171.043 170.511 171.179 171.530 173.884 175.838 178.341 180.534 181.087
195.7
145.9
176.7
119.5
203.300
147.515
182.526
118.998
203.533
148.016
183.947
113.500
204.289
146.317
180.480
114.439
205.279
147.289
182.902
119.535
206.124
147.924
184.091
121.846
206.563
151.067
190.560
121.204
206.936
150.162
188.635
118.257
208.837
150.303
188.692
115.795
209.462
150.530
189.420
117.839
209.692
153.682
196.185
120.881
211.365
155.690
200.926
122.113
212.251
158.778
207.875
120.752
213.383
161.337
213.489
117.019
215.326
161.301
213.363
114.357
216.3 226.224 231.983 225.694 226.509 227.026 238.067 236.735 238.389 238.297 247.546 254.599 266.943 278.584 280.062
114.5
238.9
241.9
230.8
277.5
112.473
246.848
250.813
233.731
285.559
112.177
248.331
252.358
234.632
284.859
112.036
248.555
252.530
234.563
286.492
111.746
248.700
252.272
234.322
288.469
111.889
248.878
252.713
235.458
289.307
112.103
248.974
252.495
236.449
289.592
112.093
249.225
252.669
236.504
289.945
112.300
250.648
254.239
237.347
290.905
112.094
251.527
255.199
237.929
291.406
112.059
252.817
256.470
239.556
292.218
111.671
253.426
256.463
240.150
293.016
111.362
254.509
256.532
242.343
293.959
111.232
256.668
257.585
245.759
294.668
111.275
258.422
258.637
247.869
295.677
202.7 208.098 209.179 208.607 209.100 209.478 210.846 210.610 211.512 212.136 214.236 215.462 217.411 219.757 220.758
191.9
194.7
148.0
178.2
213.9
186.7
253.3
229.6
196.9
203.7
205.9
140.6
223.0
244.7
196.639
200.080
149.720
184.012
223.411
193.468
260.764
236.847
207.723
208.925
210.729
140.053
241.018
253.058
197.408
201.042
150.225
185.382
228.641
194.326
262.284
238.357
217.274
208.980
210.756
138.757
253.696
253.998
196.803
200.598
148.591
182.170
223.057
192.869
262.588
238.507
209.294
209.399
211.111
138.895
239.885
254.491
197.708
201.159
149.541
184.450
223.802
194.616
263.243
238.604
209.637
210.000
211.628
139.828
241.120
254.706
198.171
201.544
150.180
185.610
224.338
195.646
263.109
238.657
207.588
210.714
212.318
140.501
241.642
255.385
199.998
202.770
153.234
191.668
234.241
199.253
263.599
238.671
219.009
210.888
212.435
140.547
265.420
255.549
199.734
202.600
152.344
189.844
233.014
198.422
263.966
238.894
217.506
210.890
212.356
140.014
261.976
255.785
200.609
203.569
152.531
190.000
234.667
199.346
265.311
240.201
219.465
211.846
213.138
139.845
264.660
257.220
201.110
204.136
152.799
190.781
234.736
200.030
266.154
241.004
219.311
212.545
213.866
140.324
263.508
258.098
203.217
205.992
155.881
197.167
243.109
203.767
267.567
242.310
230.505
213.420
214.866
141.056
283.362
259.249
205.040
207.317
157.870
201.693
249.571
207.096
269.007
242.921
240.194
213.851
215.059
141.156
298.757
259.503
207.566
209.170
160.880
208.233
260.703
211.240
271.467
243.982
257.106
214.101
215.180
140.677
326.414
260.049
210.242
211.408
163.385
213.538
271.235
214.783
275.200
246.219
275.621
214.600
215.553
139.925
351.886
261.216
211.468
212.576
163.364
213.447
272.612
215.628
277.982
248.007
280.833
215.335
216.045
139.535
354.423
262.323
CONSUMER PRICE INDEX FOR URBAN
WAGE EARNERS AND CLERICAL WORKERS
All items....................................................................
197.1 202.767 203.700 203.199 203.889 204.338 205.891 205.777 206.744 207.254 209.147 210.698 212.788 215.223 216.304
All items (1967 = 100)...............................................
Food and beverages................................................
587.2
194.9
194.4
192.2
213.1
186.1
180.9
251.0
Food..................…..................................................
Food at home…....................................................
Cereals and bakery products…..........................
Meats, poultry, fish, and eggs….........................
1
Dairy and related products ……….…………………
Fruits and vegetables…......................................
Nonalcoholic beverages and beverage
materials….......................................................
Other foods at home….......................................
Sugar and sweets….........................................
Fats and oils…..................................................
Other foods…...................................................
1,2
Other miscellaneous foods ……….……………
1
Food away from home ……….……………………………
1,2
Other food away from home ……….………………
Alcoholic beverages…...........................................
Housing....................................................................
Shelter...............…................................................
Rent of primary residence…...............................
2
Lodging away from home ……….……………………
3
Owners' equivalent rent of primary residence …
1,2
Tenants' and household insurance ……….……
Fuels and utilities…...........................................
Fuels...............…..............................................
Fuel oil and other fuels…................................
Gas (piped) and electricity…..........................
Household furnishings and operations…............
Apparel ...................................................................
Men's and boys' apparel….................................
Women's and girls' apparel….............................
1
Infants' and toddlers' apparel ……….………………
Footwear….........................................................
Transportation..........................................................
Private transportation...............….........................
2
New and used motor vehicles ……….………………
See footnotes at end of table.
112
603.982
202.531
202.134
200.273
222.409
195.193
194.474
260.484
606.759
202.823
202.409
200.569
223.663
196.323
198.027
252.703
605.267
203.610
203.207
201.321
224.220
196.844
201.598
251.575
607.324
204.584
204.241
202.351
223.895
197.980
203.464
257.223
608.662
205.428
205.082
203.442
224.897
198.146
205.100
261.774
613.287
205.763
205.451
203.741
225.941
198.325
205.850
265.736
612.948
206.141
205.855
204.141
226.696
198.489
205.149
269.533
615.828
208.055
207.794
206.870
229.105
199.686
206.652
275.843
617.345
208.674
208.317
207.242
233.915
199.141
207.750
268.954
622.985
208.927
208.571
207.196
236.764
199.484
205.660
266.030
627.606
210.559
210.252
209.657
240.663
200.285
207.135
270.169
633.830
211.438
211.200
210.624
244.648
200.501
207.088
274.136
641.082
212.700
212.514
212.079
246.493
202.424
208.510
276.641
644.303
214.662
214.577
214.679
250.972
204.557
213.582
278.885
146.7 152.786 152.829 154.152 154.501 154.873 153.610 152.883 157.130 157.456 157.488 158.799 157.285 157.309 158.527
169.1
170.5
168.7
185.2
114.2
199.1
136.2
200.6
172.630
175.323
173.640
188.405
115.356
206.412
143.462
207.097
173.727
176.736
174.109
189.667
115.355
206.657
144.439
207.647
173.997
176.664
174.872
189.941
116.348
207.533
144.938
208.253
173.463
176.458
175.039
189.110
114.584
208.578
145.783
208.286
174.215
176.248
176.683
189.987
115.378
209.037
144.764
209.176
173.393
176.845
176.101
188.657
115.803
209.518
145.233
208.958
173.511
177.051
176.736
188.646
115.658
209.931
144.454
208.934
175.572
178.902
182.307
190.364
115.658
210.776
145.625
210.473
177.442
179.740
185.292
192.430
118.828
211.517
146.924
212.507
177.713
181.033
183.706
192.832
117.754
212.193
147.188
212.748
181.215
183.725
191.560
196.106
118.751
212.794
147.335
213.633
182.241
184.127
194.228
197.081
119.248
213.723
148.517
213.486
183.342
184.378
197.155
198.153
118.879
214.851
149.306
213.976
185.174
186.054
201.821
199.722
121.015
216.177
150.232
214.440
198.5
224.8
224.2
135.3
216.0
116.8
204.795
232.998
233.806
142.339
223.175
117.366
206.183
233.848
233.855
153.107
223.093
116.912
206.054
234.169
234.457
149.919
223.693
117.287
206.050
234.275
235.175
143.727
224.321
117.142
205.916
234.812
236.259
142.666
224.811
116.982
206.288
235.069
237.288
136.244
225.548
117.370
206.638
235.480
238.216
133.179
226.151
117.396
207.692
236.550
238.955
139.825
226.703
117.740
208.268
237.158
239.419
143.046
227.057
117.921
209.388
237.965
239.932
148.110
227.488
117.999
210.161
238.261
240.507
145.936
227.893
118.683
211.191
238.353
240.818
144.979
228.007
118.615
213.441
239.198
241.623
148.378
228.536
119.293
215.026
239.845
242.276
152.248
228.824
119.006
193.1
174.4
234.0
180.2
122.6
119.1
114.0
110.3
118.6
123.1
198.863
179.031
251.121
184.357
122.477
118.518
112.224
110.202
116.278
122.062
204.272
184.725
245.633
191.010
122.550
113.157
109.580
101.709
110.906
119.278
202.397
182.518
246.382
188.511
122.190
114.146
108.556
103.960
112.879
119.831
202.304
182.357
252.684
187.963
121.820
118.986
111.981
110.847
115.896
122.846
198.796
178.539
261.972
183.172
122.039
121.536
114.710
113.623
119.670
124.372
200.151
179.777
292.098
182.781
122.031
120.920
114.784
112.165
119.897
124.649
200.831
180.379
298.656
183.066
121.880
118.126
112.487
109.375
116.419
122.029
202.663
182.025
306.087
184.522
122.322
115.866
111.494
104.456
116.323
121.137
203.584
182.823
307.599
185.324
122.547
117.883
113.592
106.512
118.442
122.408
206.861
186.315
329.271
188.143
123.184
120.809
115.808
110.712
118.990
124.343
210.912
190.657
339.009
192.434
123.108
121.855
117.136
110.971
119.200
126.150
217.388
197.554
358.947
199.045
123.287
120.407
116.621
108.594
117.213
125.335
228.843
209.843
381.903
211.398
123.434
116.706
112.395
104.062
114.057
123.381
236.381
217.640
388.208
219.612
123.798
113.978
109.969
99.772
111.502
122.380
180.3 184.344 187.606 184.147 184.361 184.639 190.761 189.967 190.918 190.639 195.710 199.556 206.757 213.633 214.533
177.5 181.496 184.684 181.218 181.495 181.717 187.951 187.159 188.093 187.762 192.740 196.641 203.781 210.423 211.201
94.7
93.300 93.042 93.229 93.118 93.268 93.529 93.733 93.842 93.664 93.455 93.158 92.850 92.714 92.686
Monthly Labor Review • September 2008
38. 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]
2006
New vehicles…............................................
1
Used cars and trucks ……….……………………
Motor fuel…...................................................
Gasoline (all types)…..................................
Motor vehicle parts and equipment…............
Motor vehicle maintenance and repair….......
Public transportation...............….....................
Medical care.......................................................
Medical care commodities...............…............
Medical care services...............…...................
Professional services….................................
Hospital and related services….....................
2
Recreation ……….………………………………………
Video and audio
1,2
……….……………………………
2
Education and communication ……….……………
2
2007
2008
2007
Annual average
Series
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
July
138.6 137.415 136.663 136.414 136.129 136.509 137.372 137.736 137.931 137.445 136.910 136.456 135.933 135.728 135.556
140.8
221.6
220.7
116.9
218.1
225.0
136.586
239.900
238.879
121.356
225.535
228.531
136.880
253.893
252.957
121.350
226.090
233.390
137.999
239.097
238.100
121.584
226.636
231.082
137.996
240.271
239.252
122.144
226.881
229.148
137.798
240.040
238.906
122.830
227.472
231.182
137.457
263.248
262.013
123.302
228.267
231.999
137.791
259.032
257.792
123.786
228.692
231.363
138.052
261.531
260.457
124.416
230.255
232.594
138.094
260.402
259.112
125.238
231.349
233.979
138.070
279.975
277.842
126.330
232.344
240.729
137.616
295.618
293.349
126.032
232.983
241.966
137.145
323.495
321.291
126.742
234.221
249.310
136.790
348.762
346.459
127.750
235.550
261.779
136.639
351.124
348.888
128.997
237.324
266.259
335.7
279.0
351.1
291.7
463.6
350.882
282.558
370.111
303.169
493.740
351.346
282.662
370.696
303.481
493.563
352.704
283.379
372.261
304.677
495.191
353.571
283.712
373.306
304.841
498.533
355.719
284.517
375.899
306.072
505.077
357.165
285.475
377.498
306.300
510.836
357.745
285.913
378.119
307.333
510.961
360.710
287.703
381.507
309.169
518.853
362.329
288.335
383.510
310.426
523.654
363.069
289.254
384.149
311.259
524.534
363.356
288.796
384.753
311.757
526.495
363.462
286.825
385.769
313.294
527.230
363.628
287.033
385.911
313.618
527.948
363.942
286.562
386.560
314.235
529.798
108.2 108.572 108.403 108.179 108.495 108.793 108.805 108.702 109.046 109.315 109.742 109.775 109.876 109.905 110.198
103.9 102.559 102.358 101.923 102.427 102.833 102.465 102.523 102.839 103.028 103.525 103.414 102.958 102.306 102.267
113.9 116.301 115.980 116.981 117.707 117.891 117.686 117.782 118.097 118.079 118.155 118.462 118.737 119.264 119.852
Education ……….………………………………………
Educational books and supplies…..............
160.3 169.280 167.527 170.635 173.060 173.700 174.016 174.276 175.134 175.118 175.101 175.545 175.791 176.148 176.879
390.7 423.730 421.529 431.089 433.670 434.800 434.979 437.391 441.207 441.927 442.639 444.594 445.394 445.740 446.741
Tuition, other school fees, and child care…
453.3 477.589 472.395 480.960 488.199 490.061 491.022 491.554 493.797 493.672 493.546 494.711 495.384 496.449 498.598
86.0 85.782 86.015 86.148 86.184 86.182 85.807 85.834 85.935 85.919 86.016 86.244 86.496 87.017 87.490
1,2
Communication ……….……………………………
1,2
Information and information processing …
1,2
Telephone services ……….…………………
Information and information processing
other than telephone services
1,4
……….…
84.3
83.928
84.111
84.248
84.283
84.282
83.894
83.917
84.008
83.992
84.091
84.320
84.511
95.9
98.373
98.721
98.964
99.024
99.149
98.874
98.887
98.988
98.931
99.090
99.566
99.939 100.723 101.375
85.007
13.0
11.062
11.001
10.965
10.958
10.877
10.710
10.722
10.737
10.754
10.745
10.671
10.621
10.585
85.484
10.600
Personal computers and peripheral
1,2
equipment ……….………………………
Other goods and services..................................
Tobacco and smoking products...............…....
1
Personal care ……….…………………………………
121.0 108.164 107.371 106.531 105.713 104.366 100.257 100.000 101.067 100.582 100.265 98.820 97.010 95.766 94.691
330.9 344.004 344.221 344.214 345.800 346.742 347.427 348.830 350.630 351.979 353.351 354.887 356.523 358.419 359.961
521.6 555.502 555.366 556.517 561.092 562.134 563.435 568.410 574.724 577.359 576.910 578.296 583.296 592.248 599.180
188.3 193.590 193.792 193.598 194.160 194.769 195.122 195.467 195.885 196.564 197.803 198.859 199.367 199.404 199.495
1
155.7 158.268 158.445 157.813 157.654 158.408 158.579 158.407 158.167 157.877 158.730 159.585 158.993 159.052 159.237
1
209.8 216.823 217.040 217.354 217.822 218.149 218.897 219.945 220.324 221.338 223.043 223.088 223.922 223.838 223.994
314.1 326.100 326.135 327.235 329.329 329.706 330.258 330.850 333.154 334.868 336.476 338.851 341.212 341.921 341.763
Personal care products ……….…………………
Personal care services ……….…………………
Miscellaneous personal services...............…
Commodity and service group:
Commodities...........….......................................
Food and beverages…....................................
Commodities less food and beverages…........
Nondurables less food and beverages…......
Apparel …...................................................
165.7
194.9
148.7
182.6
119.1
169.554
202.531
150.865
189.507
118.518
170.252
202.823
151.724
191.603
113.157
169.122
203.610
149.781
187.515
114.146
170.141
204.584
150.795
189.981
118.986
170.865
205.428
151.448
191.230
121.536
173.489
205.763
155.011
198.661
120.920
172.952
206.141
154.086
196.636
118.126
173.711
208.055
154.345
196.910
115.866
174.083
208.674
154.603
197.606
117.883
176.727
208.927
158.156
205.166
120.809
178.900
210.559
160.488
210.558
121.855
181.837
211.438
164.188
218.794
120.407
184.495
212.700
167.344
225.585
116.706
185.105
214.662
167.376
225.595
113.978
Nondurables less food, beverages,
and apparel…............................................
Durables…....................................................
Services….........................................................
3
Rent of shelter ……….………………………………
Transporatation services…............................
Other services….............................................
226.1 237.858 244.695 237.329 238.345 238.798 251.442 249.863 251.751 251.621 262.252 270.496 285.024 298.593 300.341
114.6 112.640 112.425 112.362 112.114 112.241 112.413 112.450 112.688 112.560 112.549 112.171 111.845 111.769 111.820
234.1 241.696 242.901 243.118 243.436 243.572 243.906 244.275 245.484 246.154 247.197 248.045 249.175 251.365 252.991
216.6 224.617 225.455 225.760 225.867 226.393 226.636 227.035 228.071 228.660 229.443 229.719 229.810 230.620 231.255
230.6 233.420 233.737 233.831 233.868 234.848 235.874 236.020 236.883 237.426 238.496 239.044 240.728 243.395 245.005
268.2 275.218 274.766 276.015 277.702 278.404 278.513 278.783 279.780 280.199 281.017 281.829 282.720 283.449 284.449
Special indexes:
All items less food….......................................
All items less shelter…...................................
All items less medical care…..........................
Commodities less food…...............................
Nondurables less food…................................
Nondurables less food and apparel…............
Nondurables…...............................................
3
Services less rent of shelter ……….……………
Services less medical care services…...........
Energy…........................................................
All items less energy…...................................
All items less food and energy…..................
Commodities less food and energy…........
Energy commodities.................................
Services less energy…...............................
1
Not seasonally adjusted.
2
Indexes on a December 1997 = 100 base.
3
Indexes on a December 1982 = 100 base.
197.5
189.2
191.3
150.6
183.8
223.0
189.5
202.698
193.940
196.564
152.875
190.698
234.201
196.772
203.750
194.913
197.504
153.730
192.714
240.471
198.000
203.011
194.109
196.949
151.846
188.873
233.817
196.266
203.638
195.018
197.629
152.837
191.210
234.745
198.017
204.015
195.440
198.022
153.499
192.442
235.233
199.075
205.783
197.479
199.565
156.977
199.471
246.726
203.087
205.575
197.174
199.431
156.073
197.551
245.286
202.222
206.371
198.113
200.329
156.365
197.892
247.136
203.268
206.877
198.592
200.800
156.670
198.660
247.188
203.933
209.055
200.904
202.713
160.152
205.843
256.899
208.101
210.583
202.931
204.290
162.455
211.005
264.488
211.757
212.870
205.774
206.423
166.070
218.809
277.717
216.582
215.498
208.817
208.906
169.169
225.276
290.127
220.813
216.407
210.069
210.002
169.213
225.309
291.760
221.740
224.7
225.3
196.8
198.0
199.2
141.1
223.0
239.9
230.876
232.195
208.066
203.002
203.554
140.612
241.257
247.888
232.367
233.415
217.795
202.849
203.310
139.352
254.282
248.434
232.450
233.562
209.441
203.319
203.710
139.557
240.247
248.977
232.982
233.839
209.933
204.037
204.363
140.491
241.692
249.398
232.628
233.850
207.885
204.797
205.107
141.236
241.955
250.127
233.029
234.115
219.861
205.066
205.355
141.254
265.598
250.546
233.314
234.468
218.104
205.155
205.377
140.815
261.928
250.925
234.576
235.557
220.163
205.991
205.992
140.696
264.633
252.103
235.258
236.154
219.983
206.588
206.605
141.238
263.601
252.756
236.483
237.201
231.533
207.296
207.406
141.973
283.359
253.589
237.922
238.048
241.518
207.812
207.687
142.040
298.852
254.031
240.181
239.167
258.903
208.021
207.747
141.558
326.565
254.517
243.780
241.422
277.597
208.458
208.007
140.878
351.873
255.513
246.411
243.071
282.579
209.062
208.317
140.492
354.402
256.365
4
Indexes on a December 1988 = 100 base.
NOTE: Index applied to a month as a whole, not to any specific date.
Monthly Labor Review • September 2008 113
Current Labor Statistics: Price Data
39. Consumer Price Index: U.S. city average and available local area data: all items
[1982–84 = 100, unless otherwise indicated]
Pricing
All Urban Consumers
sched-
2008
ule1
U.S. city average……………………………………………
Feb.
Mar.
Apr.
Urban Wage Earners
2008
May
June
July
Feb.
Mar.
Apr.
May
June
July
M
211.693 213.528 214.823 216.632 218.815 219.964 207.254 209.147 210.698 212.788 215.223 216.304
Northeast urban……….………………………………………….………
M
225.213 226.926 228.133 230.089 232.649 234.545 221.702 223.209 224.794 227.114 229.829 231.488
Size A—More than 1,500,000...........................................
M
227.411 229.087 230.038 232.005 234.518 236.460 222.315 223.795 225.144 227.412 230.120 231.808
M
133.511 134.611 135.739 136.913 138.542 139.623 133.893 134.846 136.141 137.624 139.286 140.253
M
201.896 203.723 205.393 207.168 208.968 210.071 197.110 198.989 200.788 202.912 204.867 206.038
M
203.347 205.141 206.590 208.291 209.813 211.003 197.549 199.378 200.989 202.969 204.509 205.761
M
128.922 130.121 131.484 132.682 134.018 134.595 128.695 129.922 131.354 132.867 134.409 135.037
Region and area size2
3
Size B/C—50,000 to 1,500,000 ……….…………………………
4
Midwest urban ……….………………………………………….…………
Size A—More than 1,500,000...........................................
3
Size B/C—50,000 to 1,500,000 ……….…………………………
Size D—Nonmetropolitan (less than 50,000)………….....
M
197.596 199.472 200.841 202.720 205.122 206.435 195.774 197.864 199.325 201.494 204.023 205.452
South urban…….…..............................................................
M
205.060 206.676 208.085 210.006 212.324 213.304 202.291 204.044 205.669 207.912 210.469 211.438
Size A—More than 1,500,000...........................................
M
207.605 209.065 209.987 211.846 214.359 215.373 205.588 207.336 208.511 210.748 213.549 214.379
M
130.351 131.442 132.516 133.714 134.980 135.643 129.144 130.243 131.428 132.808 134.222 134.952
3
Size B/C—50,000 to 1,500,000 ……….…………………………
Size D—Nonmetropolitan (less than 50,000)………….....
M
205.189 206.933 208.746 211.225 214.739 215.274 205.523 207.600 209.641 212.533 216.357 216.901
West urban…….…...............................................................
M
216.339 218.533 219.437 221.009 223.040 223.867 210.816 213.159 214.355 216.029 218.508 219.248
Size A—More than 1,500,000...........................................
M
219.799 221.997 222.689 224.704 226.767 227.562 212.614 214.954 216.055 218.141 220.603 221.232
M
131.538 132.896 133.694 134.023 135.283 136.021 131.148 132.640 133.570 134.133 135.738 136.478
M
M
M
193.685 195.314 196.191 197.898 199.840 200.941 191.982 193.702 194.886 196.844 199.028 200.009
130.728 131.892 132.974 133.997 135.330 136.055 130.092 131.273 132.471 133.729 135.240 135.986
203.803 205.730 207.238 209.308 211.989 212.555 202.292 204.422 205.951 208.246 211.236 211.929
Chicago–Gary–Kenosha, IL–IN–WI…………………………..
Los Angeles–Riverside–Orange County, CA……….…………
M
M
209.526 211.542 212.662 214.932 215.738 217.459 202.497 204.742 205.885 208.403 209.021 211.020
221.431 223.606 224.625 226.651 229.033 229.886 214.231 216.493 217.914 219.702 222.435 223.245
New York, NY–Northern NJ–Long Island, NY–NJ–CT–PA…
M
231.020 233.122 233.822 236.151 238.580 240.273 225.281 226.951 228.215 230.923 233.776 235.446
Boston–Brockton–Nashua, MA–NH–ME–CT……….…………
1
– 233.084
– 235.344
– 241.258
– 232.656
– 235.419
– 240.511
Cleveland–Akron, OH……………………………………………
1
– 202.500
– 204.882
– 206.941
– 192.995
– 195.898
– 198.063
Dallas–Ft Worth, TX…….………………………………………
1
– 198.596
– 202.357
– 206.413
– 201.892
– 206.258
– 210.830
Washington–Baltimore, DC–MD–VA–WV ……….………………
1
– 138.090
– 139.649
– 142.065
– 137.544
– 139.332
– 141.622
Atlanta, GA……………………..…………………………………
2
204.166
– 206.371
– 212.032
– 203.473
– 205.801
– 212.013
Detroit–Ann Arbor–Flint, MI……………………………………
2
202.378
– 205.281
– 207.593
– 197.670
– 201.037
– 203.524
–
Houston–Galveston–Brazoria, TX………………………………
2
187.585
– 188.795
– 193.567
– 185.904
– 188.463
– 193.742
–
Miami–Ft. Lauderdale, FL……………...………………………
2
219.082
– 221.324
– 225.079
– 216.971
– 219.456
– 223.849
–
Philadelphia–Wilmington–Atlantic City, PA–NJ–DE–MD……
2
220.935
– 223.622
– 228.408
– 220.718
– 223.295
– 228.429
–
San Francisco–Oakland–San Jose, CA…….…………………
2
219.612
– 222.074
– 225.181
– 214.913
– 217.913
– 221.454
–
Seattle–Tacoma–Bremerton, WA………………...……………
2
221.728
– 223.196
– 228.068
– 216.332
– 218.483
– 223.573
–
3
Size B/C—50,000 to 1,500,000 ……….…………………………
Size classes:
5
A ……….………………………………………….…………..……………
3
B/C ……………………….….………………………………………….…
D…………….…………......................................................
Selected local areas 6
7
1
Foods, fuels, and several other items priced every month in all areas; most other
goods and services priced as indicated:
M—Every month.
1—January, March, May, July, September, and November.
2—February, April, June, August, October, and December.
Report :
Anchorage,
AK;
Cincinnatti,
OH–KY–IN;
Kansas
City,
MO–KS;
Milwaukee–Racine, WI; Minneapolis–St. Paul, MN–WI; Pittsburgh, PA; Port-land–Salem,
OR–WA; St Louis, MO–IL; San Diego, CA; Tampa–St. Petersburg–Clearwater, FL.
2
Regions defined as the four Census regions.
3
Indexes on a December 1996 = 100 base.
NOTE: Local area CPI indexes are byproducts of the national CPI program. Each local
index has a smaller sample size and is, therefore, subject to substantially more sampling
and other measurement error. As a result, local area indexes show greater volatility than
the national index, although their long-term trends are similar. Therefore, the Bureau of
Labor Statistics strongly urges users to consider adopting the national average CPI for use
in their escalator clauses. Index applies to a month as a whole, not to any specific date.
Dash indicates data not available.
4
The "North Central" region has been renamed the "Midwest" region by the Census
Bureau. It is composed of the same geographic entities.
5
Indexes on a December 1986 = 100 base.
6
In addition, the following metropolitan areas are published semiannually and
appear in tables 34 and 39 of the January and July issues of the CPI Detailed
114
Monthly Labor Review • September 2008
7
Indexes on a November 1996 = 100 base.
–
40. Annual data: Consumer Price Index, U.S. city average, all items and major groups
[1982–84 = 100]
Series
Consumer Price Index for All Urban Consumers:
All items:
Index..................……...............................................
Percent change............................……………………
Food and beverages:
Index................…….................................................
Percent change............................……………………
Housing:
Index....………………...............................................
Percent change............................……………………
Apparel:
Index........................…….........................................
Percent change............................……………………
Transportation:
Index........................………......................................
Percent change............................……………………
Medical care:
Index................…….................................................
Percent change............................……………………
Other goods and services:
Index............…….....................................................
Percent change............................……………………
Consumer Price Index for Urban Wage Earners
and Clerical Workers:
All items:
Index....................……………...................................
Percent change............................……………………
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
160.5
2.3
163.0
1.6
166.6
2.2
172.2
3.4
177.1
2.8
179.9
1.6
184.0
2.3
188.9
2.7
195.3
3.4
201.6
3.2
207.342
2.8
157.7
2.6
161.1
2.2
164.6
2.2
168.4
2.3
173.6
3.1
176.8
1.8
180.5
2.1
186.6
3.3
191.2
2.5
195.7
2.4
203.300
3.9
156.8
2.6
160.4
2.3
163.9
2.2
169.6
3.5
176.4
4.0
180.3
2.2
184.8
2.5
189.5
2.5
195.7
3.3
203.2
3.8
209.586
3.1
132.9
.9
133.0
.1
131.3
–1.3
129.6
–1.3
127.3
–1.8
124.0
–2.6
120.9
–2.5
120.4
–.4
119.5
–.7
119.5
.0
118.998
-0.4
144.3
0.9
141.6
–1.9
144.4
2.0
153.3
6.2
154.3
0.7
152.9
–.9
157.6
3.1
163.1
3.5
173.9
6.6
180.9
4.0
184.682
2.1
234.6
2.8
242.1
3.2
250.6
3.5
260.8
4.1
272.8
4.6
285.6
4.7
297.1
4.0
310.1
4.4
323.2
4.2
336.2
4.0
351.054
4.4
224.8
4.4
237.7
5.7
258.3
8.7
271.1
5.0
282.6
4.2
293.2
3.8
298.7
1.9
304.7
2.0
313.4
2.9
321.7
2.6
333.328
3.6
157.6
2.3
159.7
1.3
163.2
2.2
168.9
3.5
173.5
2.7
175.9
1.4
179.8
2.2
184.5
5.1
191.0
1.1
197.1
3.2
202.767
2.9
Monthly Labor Review • September 2008 115
Current Labor Statistics: Price Data
41. Producer Price Indexes, by stage of processing
[1982 = 100]
Grouping
Finished goods....……………………………
Finished consumer goods.........................
Finished consumer foods........................
Annual average
2006
2007
2007
July
Aug.
Sept.
Oct.
2008
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.p
Mayp Junep Julyp
160.4
166.0
156.7
166.6
173.5
167.0
168.5
176.2
166.4
166.1
173.0
166.3
167.4
174.8
168.4
168.6
175.9
169.7
171.4
179.4
169.5
170.4
178.2
172.2
172.0
180.1
174.5
172.3
180.4
173.6
175.1
184.2
176.0
176.7
186.0
175.4
179.6
190.1
177.7
182.5
193.9
180.1
185.0
197.1
180.9
excluding foods.....................................
Nondurable goods less food.................
Durable goods......................................
Capital equipment...................................
169.2
182.6
136.9
146.9
175.6
191.7
138.3
149.5
179.7
198.1
137.6
149.1
175.3
191.8
137.2
149.0
177.0
194.6
136.7
148.9
177.9
194.5
139.8
150.6
182.9
201.5
140.2
151.0
180.1
197.9
139.5
150.7
181.9
200.3
140.1
151.4
182.7
201.4
140.2
151.8
187.1
208.2
139.9
151.8
189.8
211.4
140.7
152.5
194.7
219.6
140.1
152.5
199.1
226.5
139.8
152.7
203.2
232.5
140.3
153.6
Intermediate materials,
supplies, and components........…………
164.0
170.7
173.6
171.5
172.2
172.2
176.2
175.7
177.8
179.1
184.5
186.9
192.6
196.9
202.5
for manufacturing......................................
Materials for food manufacturing..............
Materials for nondurable manufacturing...
Materials for durable manufacturing.........
Components for manufacturing................
155.9
146.2
175.0
180.5
134.5
162.4
161.4
184.0
189.8
136.3
164.5
163.6
187.1
195.1
136.4
163.4
164.5
185.0
191.8
136.5
163.3
166.6
186.0
189.1
136.5
164.4
166.3
189.4
189.0
136.6
166.1
166.6
195.1
188.6
136.7
166.3
169.8
195.1
188.1
136.8
168.4
173.6
199.3
189.5
137.4
170.1
176.7
201.5
193.1
137.8
173.1
180.0
206.0
200.3
137.9
174.5
179.7
207.7
203.5
138.8
178.8
182.8
214.4
212.8
139.3
181.6
185.7
220.1
216.3
139.9
186.6
187.7
231.9
219.4
141.4
Materials and components
for construction.........................................
Processed fuels and lubricants...................
Containers..................................................
Supplies......................................................
188.4
162.8
175.0
157.0
192.5
173.9
180.3
161.7
193.5
183.0
180.2
161.9
193.5
175.3
180.5
162.0
193.2
178.4
181.0
162.3
193.2
175.5
182.3
163.0
193.2
189.7
183.2
163.9
193.4
186.3
183.4
164.6
194.4
188.6
185.1
166.8
195.7
189.0
185.7
168.1
197.3
206.1
185.9
170.0
199.3
212.3
187.0
170.5
203.4
227.2
188.0
172.9
206.3
238.6
188.5
174.3
209.9
249.6
191.6
177.7
Crude materials for further
processing.......................…………………
Foodstuffs and feedstuffs...........................
Crude nonfood materials............................
184.8
119.3
230.6
207.1
146.7
246.3
210.3
150.0
249.2
202.8
147.8
237.6
204.6
151.9
237.4
211.8
150.0
252.0
225.6
152.9
274.1
229.0
158.5
275.4
235.5
162.6
283.8
245.5
165.4
299.9
262.1
169.2
327.7
274.3
166.5
349.9
294.4
172.7
385.4
305.2
178.9
399.6
317.9
179.3
423.3
Special groupings:
Finished goods, excluding foods................
Finished energy goods...............................
Finished goods less energy........................
Finished consumer goods less energy.......
Finished goods less food and energy.........
161.0
145.9
157.9
162.7
158.7
166.2
156.3
162.8
168.7
161.7
168.8
166.4
162.4
168.3
161.4
165.8
155.6
162.5
168.4
161.5
166.9
159.7
163.0
169.2
161.5
168.1
159.1
164.7
170.8
163.2
171.6
170.4
164.9
171.0
163.6
169.6
163.8
165.5
172.0
163.5
171.0
166.6
166.7
173.5
164.4
171.7
167.2
167.0
173.7
165.0
174.6
177.5
167.6
174.7
165.1
176.7
182.6
168.1
174.9
165.9
179.8
193.8
168.8
176.0
166.1
182.8
204.3
169.5
177.0
166.2
185.9
213.0
170.4
177.8
167.1
and energy................................................
Consumer nondurable goods less food
166.7
170.0
169.7
170.0
170.0
171.8
172.2
172.2
173.2
174.0
174.1
175.0
175.3
175.4
176.2
and energy..............................................
191.5
197.0
197.1
197.9
198.3
199.0
199.3
200.0
201.4
203.0
203.6
204.2
205.9
206.4
207.6
Intermediate materials less foods
and feeds..................................................
Intermediate foods and feeds.....................
Intermediate energy goods.........................
Intermediate goods less energy..................
165.4
135.2
162.8
162.1
171.5
154.4
174.6
167.6
174.5
155.9
184.2
168.8
172.3
156.3
177.0
168.1
172.9
158.2
179.5
168.2
172.9
159.6
177.4
168.9
177.0
161.4
191.1
170.2
176.3
164.6
187.8
170.4
178.2
170.6
190.5
172.3
179.4
175.0
191.5
173.7
184.7
180.3
208.6
176.0
187.4
178.6
213.8
177.4
193.1
184.8
228.6
181.1
197.4
186.8
240.5
183.4
203.0
194.6
253.0
187.3
and energy................................................
163.8
168.4
169.6
168.8
168.9
169.5
170.8
170.9
172.5
173.7
175.8
177.5
181.0
183.2
186.9
Crude energy materials..............................
Crude materials less energy.......................
Crude nonfood materials less energy.........
226.9
152.3
244.5
232.8
182.6
282.6
236.8
185.5
284.0
221.7
183.8
284.7
219.9
188.3
289.9
237.7
187.4
292.8
267.1
189.2
289.9
268.3
194.1
291.7
273.6
200.9
307.3
291.7
205.9
319.7
325.4
211.7
332.1
344.1
215.4
359.4
389.0
224.4
376.2
409.7
229.1
374.5
437.9
232.2
387.2
Finished consumer goods
Materials and components
Finished consumer goods less food
Intermediate materials less foods
p = preliminary.
116
Monthly Labor Review • September 2008
42. Producer Price Indexes for the net output of major industry groups
[December 2003 = 100, unless otherwise indicated]
NAICS
Industry
Total mining industries (December 1984=100).............................
2007
July
Aug.
Sept.
Oct.
2008
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.p
May
p
June
p
July
p
222.3
269.6
162.4
168.9
212.5
254.1
160.8
168.6
214.3
256.2
162.2
169.7
228.3
279.6
162.4
168.5
249.3
314.8
161.3
168.7
249.5
315.9
161.2
164.9
254.2
321.9
164.9
167.2
263.8
335.0
170.3
168.8
287.2
371.6
174.8
169.8
299.0
390.3
176.4
170.0
328.9
440.5
174.3
171.3
345.9
463.5
185.1
174.6
368.9
499.4
189.3
176.5
164.9
160.4
109.2
108.4
101.5
149.4
108.4
115.4
106.7
283.1
163.0
160.3
109.9
108.6
101.5
149.9
107.8
115.6
106.8
258.0
163.7
160.8
110.3
108.7
101.3
150.0
107.2
116.1
107.0
267.4
164.5
160.7
111.1
108.9
101.5
150.4
106.5
117.1
107.1
266.9
168.0
161.4
111.1
109.1
101.5
150.5
106.1
117.8
107.2
305.5
166.9
162.8
111.2
109.3
101.5
151.1
106.1
118.0
107.4
288.4
168.5
165.8
112.1
110.1
101.8
152.0
105.7
118.5
107.8
294.9
169.6
167.5
112.7
110.3
101.8
152.4
105.5
119.2
108.1
298.4
173.4
169.8
112.7
110.4
102.0
152.6
105.9
119.6
108.2
337.1
175.1
170.9
113.0
110.8
102.2
152.8
106.0
120.2
109.2
347.6
179.3
174.2
114.4
111.7
102.2
152.7
108.3
120.4
109.4
384.1
182.0
176.3
114.2
111.7
102.2
153.9
109.5
120.8
109.5
406.0
185.6
180.1
115.2
112.6
102.4
154.4
109.0
121.6
110.0
428.9
325
326
(December 1984=100)………………………………….…………
Chemical manufacturing (December 1984=100)…………………… 203.6
150.4
Plastics and rubber products manufacturing
204.9
151.3
205.0
151.2
206.4
151.6
209.2
152.2
210.4
153.2
213.6
154.8
215.8
155.6
218.4
156.4
220.4
156.3
224.1
158.5
227.8
159.5
233.7
162.7
331
332
333
334
335
336
337
Primary metal manufacturing (December 1984=100)………………
Fabricated metal product manufacturing (December 1984=100)…
Machinery manufacturing………………………..……………………
Computer and electronic products manufacturing…………………
Electrical equipment, appliance, and components manufacturing
Transportation equipment manufacturing……………………………
Furniture and related product manufacturing
196.4
162.3
112.1
94.1
123.0
104.4
165.6
192.1
162.9
112.3
93.5
123.6
104.2
165.7
188.8
162.8
112.5
93.3
123.7
103.8
165.9
188.6
163.3
112.7
93.1
124.2
106.3
166.1
188.9
163.7
113.0
92.8
124.5
106.6
166.6
188.6
164.3
113.1
92.6
124.4
106.0
166.4
190.4
165.6
113.8
92.6
125.2
106.6
167.1
194.2
166.8
114.3
92.8
125.9
106.6
167.8
202.4
168.3
114.6
92.7
127.1
106.1
168.3
210.5
170.6
115.2
92.7
127.3
106.5
169.7
221.6
172.9
115.7
92.8
128.1
106.3
170.6
228.5
174.7
116.5
92.8
128.4
105.9
171.7
233.2
177.3
117.9
93.0
129.0
106.5
172.1
339
Miscellaneous manufacturing………………………………………… 106.9
107.0
107.1
107.2
107.5
107.7
108.5
108.7
109.2
109.5
109.7
110.0
110.4
115.6
116.5
111.6
123.6
81.6
123.1
114.9
119.6
109.8
124.3
71.3
128.3
116.0
119.0
107.8
123.9
73.7
126.0
115.3
120.1
111.1
123.5
78.0
130.2
116.1
121.1
114.9
123.8
73.7
125.7
118.0
119.0
89.3
123.8
66.6
134.7
118.3
119.6
109.0
124.8
67.1
136.0
118.4
118.8
110.2
124.5
61.6
133.8
117.9
120.1
113.4
125.5
60.6
133.1
119.0
119.2
110.9
128.0
65.6
136.2
118.5
118.6
109.5
127.9
60.9
136.9
118.6
119.8
111.3
128.0
67.3
138.0
118.1
120.3
110.1
135.4
80.1
140.9
Air transportation (December 1992=100)…………………………… 188.0
Water transportation…………………………………………………… 113.6
Postal service (June 1989=100)……………………………………… 175.5
189.1
114.7
175.5
180.5
115.3
175.5
187.2
117.2
175.5
189.4
116.5
175.5
187.1
116.4
175.5
192.0
119.0
175.5
191.8
119.2
175.5
198.6
120.6
175.5
199.5
122.1
175.5
201.4
122.3
180.5
211.7
127.0
180.5
211.4
129.3
180.5
130.8
129.3
127.2
126.6
127.4
127.8
129.7
131.1
133.6
135.7
141.1
146.3
122.2
107.0
123.8
158.1
114.9
112.9
122.2
107.7
123.9
158.0
115.7
113.2
122.9
107.6
124.1
158.2
115.8
113.5
122.9
107.7
125.1
161.3
116.4
113.9
121.5
106.7
125.3
161.9
116.5
114.3
122.7
106.7
125.3
161.9
117.0
114.6
123.3
107.3
125.4
162.4
117.9
115.4
123.3
107.3
125.5
162.6
118.0
117.2
123.3
107.3
125.5
162.9
118.3
117.7
122.3
107.4
125.5
162.9
118.2
118.0
123.2
107.4
125.5
162.7
118.1
117.6
123.2
106.6
125.4
162.8
118.1
117.6
123.2
106.9
125.4
163.2
119.1
117.8
108.2
98.7
102.2
100.4
120.5
106.2
111.1
103.8
121.2
153.7
112.2
108.4
98.7
101.3
100.4
120.4
107.9
111.1
103.2
122.3
153.8
112.6
108.4
99.6
102.0
100.4
121.1
109.0
110.7
102.9
117.2
154.3
112.4
108.5
101.0
101.8
100.3
121.4
108.5
110.5
103.5
118.9
154.8
113.1
108.5
102.3
101.2
100.5
124.2
108.5
110.5
106.1
118.4
155.1
112.9
108.5
103.6
100.7
100.4
123.0
110.0
109.9
105.6
119.1
155.1
113.0
109.7
104.4
100.6
100.4
122.5
108.1
110.3
106.6
121.3
159.9
115.6
109.8
104.6
100.9
100.5
122.9
108.2
109.8
106.0
121.3
160.3
114.1
110.4
105.2
100.6
100.5
121.0
109.7
110.0
106.8
125.1
160.7
113.8
110.7
102.4
102.1
100.5
119.2
109.1
110.0
107.1
117.8
160.8
111.9
110.4
103.4
101.3
100.9
120.1
109.2
106.1
107.1
123.2
160.9
114.2
110.2
102.7
101.1
100.9
120.7
109.7
105.4
107.4
125.2
160.9
112.4
110.8
103.3
101.0
101.0
118.8
110.2
107.0
109.7
132.6
161.5
115.8
140.3
105.1
121.8
101.1
105.5
107.3
147.1
140.8
105.1
121.9
101.0
105.5
107.9
147.2
140.7
105.1
122.0
100.9
106.8
108.9
145.0
140.8
105.1
122.4
102.5
106.9
108.9
145.8
140.8
105.1
122.3
101.7
107.1
109.5
144.7
140.8
105.1
122.2
100.2
108.7
108.4
143.7
139.2
105.2
122.3
98.8
108.9
110.7
145.4
140.3
105.3
123.0
98.8
109.1
112.1
145.2
140.3
105.3
123.0
98.8
108.9
112.0
145.3
140.4
106.0
122.3
98.8
109.0
112.3
146.0
140.5
105.8
122.7
98.8
109.7
112.0
144.8
141.9
105.7
122.9
98.8
109.2
112.8
149.6
141.5
105.7
123.1
98.8
109.1
112.1
152.8
211
212
213
311
312
313
315
316
321
322
323
324
Oil and gas extraction (December 1985=100) .............................
Mining, except oil and gas……………………………………………
Mining support activities………………………………………………
Total manufacturing industries (December 1984=100)................
Food manufacturing (December 1984=100)…………………………
Beverage and tobacco manufacturing...........................................
Textile mills....................................................................................
Apparel manufacturing………………………………...………………
Leather and allied product manufacturing (December 1984=100)
Wood products manufacturing………………………………………
Paper manufacturing.....................................................................
Printing and related support activities...........................................
Petroleum and coal products manufacturing
(December 1984=100)………….…………………………………
(December 1984=100)………………………………………………
Retail trade
441
442
443
446
447
454
Motor vehicle and parts dealers………………………………………
Furniture and home furnishings stores………………………………
Electronics and appliance stores……………………………………
Health and personal care stores………………………………………
Gasoline stations (June 2001=100)…………………………………
Nonstore retailers………………………………………………………
Transportation and warehousing
481
483
491
Utilities
221
Utilities…………………………………………………………………… 131.6
Health care and social assistance
6211
6215
6216
622
6231
62321
Office of physicians (December 1996=100)…………………………
Medical and diagnostic laboratories…………………………………
Home health care services (December 1996=100)…………………
Hospitals (December 1992=100)……………………………………
Nursing care facilities…………………………………………………
Residential mental retardation facilities………………………………
Other services industries
511
515
517
5182
523
53112
5312
5313
5321
5411
541211
5413
Publishing industries, except Internet ………………………………
Broadcasting, except Internet…………………………………………
Telecommunications……………………………………………………
Data processing and related services………………………………
Security, commodity contracts, and like activity……………………
Lessors or nonresidental buildings (except miniwarehouse)………
Offices of real estate agents and brokers……………………………
Real estate support activities…………………………………………
Automotive equipment rental and leasing (June 2001=100)………
Legal services (December 1996=100)………………………………
Offices of certified public accountants………………………………
Architectural, engineering, and related services
(December 1996=100)………………………………………………
54181
Advertising agencies……………………………………………………
5613
Employment services (December 1996=100)………………………
56151
Travel agencies…………………………………………………………
56172
Janitorial services………………………………………………………
5621
Waste collection…………………………………………………………
721
Accommodation (December 1996=100)……………………………
p = preliminary.
Monthly Labor Review • September 2008 117
Current Labor Statistics: Price Data
43. Annual data: Producer Price Indexes, by stage of processing
[1982 = 100]
Index
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Finished goods
Total...............................................................................
Foods............................…………………………….……
Energy............……………………………………….….…
Other…...............................………………………….……
131.8
134.5
83.4
142.4
130.7
134.3
75.1
143.7
133.0
135.1
78.8
146.1
138.0
137.2
94.1
148.0
140.7
141.3
96.8
150.0
138.9
140.1
88.8
150.2
143.3
145.9
102.0
150.5
148.5
152.7
113.0
152.7
155.7
155.7
132.6
156.4
160.4
156.7
145.9
158.7
166.6
166.9
156.4
161.7
Intermediate materials, supplies, and
components
Total...............................................................................
Foods............……………………………………….….…
Energy…...............................………………………….…
Other.................…………...………..........………….……
125.6
123.2
89.0
134.2
123.0
123.2
80.8
133.5
123.2
120.8
84.3
133.1
129.2
119.2
101.7
136.6
129.7
124.3
104.1
136.4
127.8
123.2
95.9
135.8
133.7
134.4
111.9
138.5
142.6
145.0
123.2
146.5
154.0
146.0
149.2
154.6
164.0
146.2
162.8
163.8
170.6
161.5
174.6
168.4
111.1
112.2
87.3
103.5
96.8
103.9
68.6
84.5
98.2
98.7
78.5
91.1
120.6
100.2
122.1
118.0
121.0
106.1
122.3
101.5
108.1
99.5
102.0
101.0
135.3
113.5
147.2
116.9
159.0
127.0
174.6
149.2
182.2
122.7
234.0
176.7
184.8
119.3
226.9
210.0
207.3
146.7
233.0
238.8
Crude materials for further processing
Total...............................................................................
Foods............................…………………………….……
Energy............……………………………………….….…
Other…...............................………………………….……
44. U.S. export price indexes by end-use category
[2000 = 100]
Category
2007
July
Aug.
Sept.
Oct.
2008
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
July
ALL COMMODITIES……………....................................
116.1
116.3
116.7
117.6
118.7
119.3
120.7
121.8
123.8
124.4
124.8
126.1
127.9
Foods, feeds, and beverages……………...……………
Agricultural foods, feeds, and beverages….............
Nonagricultural (fish, beverages) food products……
149.2
151.5
130.2
151.4
153.7
132.2
157.8
160.8
133.0
164.1
167.6
134.2
165.9
169.8
133.1
171.1
175.2
136.1
180.5
185.0
142.0
188.7
193.8
144.7
196.9
202.6
148.3
192.8
198.2
146.4
193.3
198.8
145.2
198.2
204.2
145.8
211.7
219.2
146.5
Industrial supplies and materials……………...………… 148.6
118
148.8
148.8
150.5
153.9
154.1
157.1
159.1
165.5
167.9
169.6
173.3
177.8
Agricultural industrial supplies and materials…........
138.6
137.4
140.0
142.7
144.9
144.7
146.0
150.6
159.3
157.9
156.9
158.0
162.7
Fuels and lubricants…...............................…………
202.9
197.4
200.9
204.8
224.7
222.8
232.1
225.6
249.5
259.3
275.8
297.6
312.2
Nonagricultural supplies and materials,
excluding fuel and building materials…………...…
Selected building materials…...............................…
144.6
114.1
145.7
114.0
145.0
114.4
146.5
114.2
147.9
113.8
148.5
113.7
150.9
113.3
154.1
113.8
158.2
114.2
160.1
114.1
160.1
113.9
161.6
113.7
165.1
113.9
Capital goods……………...…………………………….… 99.7
Electric and electrical generating equipment…........ 106.6
Nonelectrical machinery…...............................……… 93.1
99.8
106.7
93.1
99.9
106.7
93.1
100.1
107.1
93.2
100.3
107.2
93.4
100.6
107.5
93.6
100.9
107.7
93.7
101.3
108.3
93.9
101.2
108.6
93.7
101.5
108.7
93.9
101.6
108.6
93.8
101.9
108.6
94.1
101.7
108.6
93.9
Automotive vehicles, parts, and engines……………...
106.2
106.2
106.3
106.5
106.5
106.7
106.9
107.0
107.1
107.5
107.5
107.5
107.6
Consumer goods, excluding automotive……………... 106.1
Nondurables, manufactured…...............................… 107.0
Durables, manufactured…………...………..........…… 104.0
106.3
107.2
104.2
106.2
107.0
104.2
106.4
107.4
104.2
106.8
108.0
104.4
107.3
108.2
105.2
107.3
108.1
105.2
107.4
108.2
105.5
108.0
109.3
105.4
108.1
109.8
105.1
108.1
110.0
105.1
108.2
110.1
105.2
108.6
110.0
106.2
Agricultural commodities……………...…………………
Nonagricultural commodities……………...……………
150.5
113.8
156.8
113.8
162.8
114.4
165.0
115.4
169.3
115.7
177.5
116.6
185.6
117.3
194.3
118.8
190.5
119.6
190.8
120.1
195.4
121.2
208.4
122.2
Monthly Labor Review • September 2008
149.0
113.7
45. U.S. import price indexes by end-use category
[2000 = 100]
2007
Category
July
Aug.
Sept.
2008
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
July
ALL COMMODITIES……………....................................
121.5
121.1
121.8
123.6
127.5
127.3
129.2
129.5
133.5
137.3
141.2
145.3
147.8
Foods, feeds, and beverages……………...……………
Agricultural foods, feeds, and beverages….............
Nonagricultural (fish, beverages) food products……
129.4
141.4
102.7
130.1
142.1
103.2
131.8
144.4
103.5
133.2
146.5
103.2
133.4
147.1
102.5
134.4
148.3
103.0
138.1
153.1
104.3
137.8
152.6
104.4
141.8
157.3
106.8
143.7
159.8
107.2
145.0
162.3
105.8
147.5
165.0
107.9
149.7
167.5
109.2
Industrial supplies and materials……………...………… 190.9
188.5
190.7
197.2
212.8
211.3
218.2
219.0
234.5
248.7
264.7
282.2
291.5
Fuels and lubricants…...............................…………
Petroleum and petroleum products…………...……
249.8
260.3
244.0
256.4
250.0
264.4
262.4
277.7
294.8
312.2
290.3
306.7
301.9
319.6
300.0
315.6
329.0
347.5
354.6
375.8
387.6
411.8
421.5
448.4
438.5
466.4
Paper and paper base stocks…...............................
110.3
110.7
111.2
112.2
108.0
109.2
112.5
113.4
114.1
116.2
117.1
117.9
120.0
Materials associated with nondurable
supplies and materials…...............................………
Selected building materials…...............................…
Unfinished metals associated with durable goods…
Nonmetals associated with durable goods…...........
126.6
116.9
215.1
102.1
127.3
116.5
215.3
102.2
128.2
116.9
209.1
102.5
131.4
115.7
211.0
103.0
133.7
115.6
214.8
103.3
135.3
116.0
217.2
103.8
143.6
115.9
215.3
105.4
146.6
113.8
224.5
105.9
147.8
114.1
241.5
105.2
148.7
114.3
259.2
106.2
149.6
116.2
263.7
107.5
152.6
119.2
275.0
107.9
156.3
121.8
277.8
111.7
Capital goods……………...…………………………….… 91.6
Electric and electrical generating equipment…........
105.8
Nonelectrical machinery…...............................……… 87.4
91.8
106.4
87.6
91.9
106.5
87.7
92.0
106.8
87.7
92.1
107.5
87.7
92.2
107.9
87.7
91.9
107.7
87.4
92.0
108.7
87.4
92.2
109.3
87.5
93.0
111.5
88.0
93.3
111.7
88.4
93.2
112.0
88.2
93.5
113.0
88.4
Automotive vehicles, parts, and engines……………...
104.8
105.0
105.2
105.6
106.2
106.8
107.1
107.2
107.4
107.8
107.8
107.9
108.0
Consumer goods, excluding automotive……………...
101.7
Nondurables, manufactured…...............................… 104.8
Durables, manufactured…………...………..........…… 98.3
Nonmanufactured consumer goods…………...……… 103.1
102.0
104.9
98.8
103.4
102.1
105.0
98.8
103.4
102.2
105.1
99.0
103.3
102.4
105.3
99.2
103.3
102.6
105.5
99.3
103.8
103.1
106.5
99.6
104.0
103.5
106.8
100.0
104.1
104.0
107.5
100.4
104.3
104.6
107.9
101.1
105.6
104.8
108.0
101.3
105.8
104.9
108.0
101.6
106.6
105.2
108.3
101.8
106.9
46. U.S. international price Indexes for selected categories of services
[2000 = 100, unless indicated otherwise]
Category
2006
June
Sept.
2007
Dec.
Mar.
June
2008
Sept.
Dec.
Mar.
June
Import air freight……………...........................................
Export air freight……………...……………………………
135.2
115.9
133.1
117.9
131.2
116.7
130.7
117.0
132.3
117.0
134.2
119.8
141.8
127.1
144.4
132.0
155.4
142.2
Import air passenger fares (Dec. 2006 = 100)……………
Export air passenger fares (Dec. 2006 = 100)…............
136.7
139.3
130.9
142.4
125.4
137.3
122.9
140.2
144.6
147.3
140.2
154.6
135.3
155.7
131.3
156.4
171.6
169.0
Monthly Labor Review • September 2008 119
Current Labor Statistics: Productivity Data
47. Indexes of productivity, hourly compensation, and unit costs, quarterly data seasonally adjusted
[1992 = 100]
2005
Item
II
2006
III
IV
I
134.2
161.6
119.5
120.4
129.5
123.8
135.6
164.1
119.6
121.1
131.6
125.0
135.2
165.8
119.6
122.6
132.4
126.3
136.1
168.0
120.6
123.5
133.4
127.2
133.4
160.8
118.9
120.5
130.8
124.3
134.6
163.2
118.9
121.2
133.2
125.6
134.2
164.7
118.8
122.7
134.2
126.9
143.7
158.6
117.3
110.6
110.4
111.4
166.8
126.2
115.7
142.8
160.8
117.2
113.5
112.6
115.7
152.2
125.5
116.9
172.0
164.2
121.4
95.5
172.9
166.5
121.3
96.3
II
2007
III
IV
I
136.6
168.1
119.6
123.1
136.2
128.0
135.9
168.9
119.1
124.3
136.2
128.8
135.9
172.6
122.1
127.0
133.4
129.4
135.9
174.7
122.4
128.5
134.3
130.7
135.1
166.8
119.7
123.5
135.5
127.9
135.7
167.1
118.9
123.1
138.6
128.8
134.9
167.9
118.3
124.4
138.3
129.5
135.0
171.7
121.4
127.1
134.9
130.0
144.8
161.2
116.3
111.8
111.4
113.1
177.4
130.3
117.7
146.3
164.5
118.1
112.5
112.4
112.9
182.5
131.5
118.8
146.0
164.5
117.0
113.1
112.6
114.4
183.1
132.8
119.4
147.0
165.1
116.3
112.8
112.3
114.2
193.0
135.3
120.0
172.8
165.3
119.2
95.6
172.6
170.9
122.7
99.0
172.7
169.5
120.7
98.2
174.5
170.3
120.0
97.6
II
2008
III
IV
I
II
137.6
175.5
121.7
127.5
137.4
131.2
139.7
177.1
121.9
126.8
139.7
131.6
139.7
179.0
121.7
128.1
139.2
132.2
140.5
181.2
121.9
128.9
139.5
132.9
141.3
182.9
121.6
129.4
139.2
133.1
135.0
173.7
121.8
128.7
135.2
131.1
136.4
174.1
120.7
127.7
138.2
131.5
138.3
175.5
120.9
126.9
140.3
131.8
138.6
177.8
121.0
128.3
139.8
132.5
139.5
180.1
121.2
129.1
140.3
133.2
140.3
181.7
120.8
129.5
140.0
133.4
146.0
167.8
118.7
115.3
114.9
116.2
173.9
131.6
120.5
146.2
170.3
119.4
116.7
116.5
117.2
171.8
131.8
121.6
147.4
171.3
118.7
116.5
116.2
117.4
172.5
132.2
121.5
148.1
172.5
118.7
116.8
116.5
117.8
166.8
130.9
121.3
148.8
175.0
119.0
117.9
117.6
118.9
155.9
128.8
121.3
149.2
177.1
119.2
118.7
118.7
118.7
149.8
127.0
121.5
175.4
174.6
123.5
99.5
177.0
176.9
124.0
100.0
178.7
176.4
122.3
98.7
180.6
176.4
121.4
97.6
182.5
179.7
122.2
98.5
184.0
182.4
122.8
99.1
Business
Output per hour of all persons........................................
Compensation per hour…………………………….………
Real compensation per hour………………………………
Unit labor costs…...............................……………………
Unit nonlabor payments…………...………..........………
Implicit price deflator………………………………………
Nonfarm business
Output per hour of all persons........................................
Compensation per hour…………………………….………
Real compensation per hour………………………………
Unit labor costs…...............................……………………
Unit nonlabor payments…………...………..........………
Implicit price deflator………………………………………
Nonfinancial corporations
Output per hour of all employees...................................
Compensation per hour…………………………….………
Real compensation per hour………………………………
Total unit costs…...............................……………………
Unit labor costs.............................................................
Unit nonlabor costs......................................................
Unit profits......................................................................
Unit nonlabor payments…………...………..........………
Implicit price deflator………………………………………
–
–
–
–
–
–
–
–
–
Manufacturing
Output per hour of all persons........................................
Compensation per hour…………………………….………
Real compensation per hour………………………………
Unit labor costs…...............................……………………
NOTE: Dash indicates data not available.
120
Monthly Labor Review • September 2008
183.3
184.5
122.7
100.6
48. Annual indexes of multifactor productivity and related measures, selected years
[2000 = 100, unless otherwise indicated]
Item
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Private business
Productivity:
Output per hour of all persons......……………..............
87.4
Output per unit of capital services……………………… 104.6
Multifactor productivity……………………………………
93.7
Output…...............................………………………….……
79.2
90.0
104.7
95.3
82.8
91.7
104.9
96.2
87.2
94.3
103.5
97.5
91.5
97.2
102.3
98.7
96.2
100.0
100.0
100.0
100.0
102.8
96.0
100.1
100.5
107.1
94.8
101.8
102.0
111.2
95.6
104.4
105.2
114.5
97.5
107.0
109.7
116.8
98.6
108.8
113.8
118.0
99.1
109.4
117.4
120.2
98.1
110.1
120.1
88.8
75.7
84.4
83.6
90.7
79.1
86.9
85.9
94.2
83.2
90.6
87.4
96.4
88.4
93.9
91.1
99.0
94.1
97.5
95.0
100.0
100.0
100.0
100.0
98.6
104.6
100.3
107.0
97.2
107.6
100.2
112.9
97.0
110.0
100.7
116.3
98.4
112.5
102.5
117.4
100.2
115.4
104.6
118.4
102.8
118.5
107.4
119.1
103.8
122.3
109.2
122.3
Productivity:
Output per hour of all persons........……………………… 88.2
Output per unit of capital services……………………… 105.6
94.5
Multifactor productivity……………………………………
Output…...............................………………………….……
79.3
90.5
105.5
95.9
82.8
92.0
105.3
96.5
87.2
94.5
103.9
97.8
91.5
97.3
102.5
98.8
96.3
100.0
100.0
100.0
100.0
102.7
96.0
100.1
100.5
107.1
94.7
101.8
102.1
111.0
95.4
104.3
105.2
114.2
97.3
106.8
109.6
116.4
98.3
108.6
113.7
117.6
98.7
109.0
117.4
119.7
97.9
109.7
120.1
88.2
75.0
83.9
83.5
90.2
78.5
86.4
85.8
93.9
82.7
90.3
87.3
96.2
88.1
93.6
91.0
99.0
93.9
97.4
94.9
100.0
100.0
100.0
100.0
98.7
104.7
100.5
107.0
97.2
107.8
100.2
113.1
97.1
110.3
100.8
116.4
98.6
112.7
102.6
117.4
100.4
115.6
104.7
118.4
103.1
118.9
107.6
119.1
104.1
122.8
109.4
122.4
Productivity:
Output per hour of all persons...…………………………
Output per unit of capital services………………………
Multifactor productivity……………………………………
Output…...............................………………………….……
79.8
98.7
90.8
80.3
82.7
98.0
91.2
83.1
87.3
100.6
93.8
89.2
92.0
100.7
95.9
93.8
96.1
100.4
96.7
97.4
100.0
100.0
100.0
100.0
101.6
93.5
98.7
94.9
108.6
92.3
102.4
94.3
115.3
93.2
105.2
95.2
117.9
95.4
108.0
96.9
123.5
98.9
108.4
100.4
125.0
100.2
110.1
102.3
–
–
–
–
Inputs:
Hours of all persons.....................................................
Capital services…………...………..........………….……
Energy……………….……….........................................
Nonenergy materials....................................................
Purchased business services.......................................
Combined units of all factor inputs…………...………...
100.6
81.4
113.7
78.9
88.8
88.5
100.4
84.8
110.4
86.0
88.5
91.1
102.2
88.7
108.2
92.9
92.1
95.1
101.9
93.2
105.4
97.7
95.0
97.8
101.3
97.0
105.5
102.6
100.0
100.7
100.0
100.0
100.0
100.0
100.0
100.0
93.5
101.5
90.6
93.3
100.7
96.2
86.8
102.1
89.3
88.4
98.2
92.1
82.6
102.1
84.4
87.7
99.1
90.5
82.2
101.6
84.0
87.3
97.0
89.7
81.3
101.5
91.6
92.4
104.5
92.7
81.8
102.0
86.6
91.5
106.6
92.9
–
–
–
–
–
–
Inputs:
Labor input...................................................................
Capital services…………...………..........………….……
Combined units of labor and capital input………………
Capital per hour of all persons.......................……………
Private nonfarm business
Inputs:
Labor input...................................................................
Capital services…………...………..........………….……
Combined units of labor and capital input………………
Capital per hour of all persons......…………………………
Manufacturing [1996 = 100]
NOTE: Dash indicates data not available.
Monthly Labor Review • September 2008 121
Current Labor Statistics: Productivity Data
49. Annual indexes of productivity, hourly compensation, unit costs, and prices, selected years
[1992 = 100]
Item
1962
1972
1982
1992
1999
2000
2001
2002
2003
2004
2005
2006
2007
Business
Output per hour of all persons........................................
Compensation per hour…………………………….………
Real compensation per hour………………………………
Unit labor costs…...............................……………………
Unit nonlabor payments…………...………..........………
Implicit price deflator………………………………………
52.9
15.1
65.2
28.5
26.1
27.6
71.2
26.7
83.3
37.4
35.7
36.8
80.1
63.6
90.6
79.4
70.1
75.9
100.0
100.0
100.0
100.0
100.0
100.0
112.8
125.8
108.1
111.5
109.4
110.7
116.1
134.7
112.0
116.0
107.2
112.7
119.1
140.3
113.5
117.9
110.0
114.9
123.9
145.3
115.7
117.3
114.2
116.1
128.7
151.2
117.7
117.5
118.3
117.8
132.4
156.9
119.0
118.5
124.7
120.8
135.0
163.2
119.7
120.9
130.8
124.5
136.4
169.6
120.5
124.4
134.6
128.2
139.0
178.3
123.2
128.3
135.4
131.0
55.9
15.6
67.3
27.8
25.8
27.1
73.1
26.9
84.0
36.8
34.9
36.1
80.8
63.9
91.1
79.1
69.3
75.5
100.0
100.0
100.0
100.0
100.0
100.0
112.5
125.2
107.6
111.3
110.9
111.1
115.7
134.2
111.6
116.0
108.7
113.3
118.6
139.5
112.8
117.7
111.6
115.4
123.5
144.6
115.1
117.1
116.0
116.7
128.0
150.4
117.1
117.5
119.6
118.3
131.6
155.9
118.2
118.5
125.5
121.1
134.1
162.1
118.9
120.9
132.4
125.1
135.4
168.5
119.7
124.5
136.4
128.9
137.9
177.1
122.3
128.4
136.2
131.3
60.4
17.4
75.1
27.3
28.7
23.4
54.5
31.7
29.7
74.2
28.8
90.0
37.5
38.8
33.9
54.1
39.3
39.0
83.1
66.5
94.7
80.4
80.0
81.3
75.2
79.7
79.9
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
117.9
124.2
106.7
104.0
105.3
100.4
129.1
108.0
106.2
122.5
133.0
110.6
107.4
108.6
104.2
108.7
105.4
107.5
124.7
138.6
112.1
111.6
111.2
112.6
82.2
104.5
108.9
129.7
143.6
114.3
110.7
110.7
110.8
98.0
107.4
109.6
134.6
149.5
116.4
111.0
111.0
111.1
109.9
110.7
110.9
139.6
153.9
116.7
110.0
110.3
109.3
144.8
118.8
113.1
141.6
159.8
117.2
112.7
112.9
112.2
154.4
123.5
116.4
142.6
165.4
117.5
115.4
116.0
113.8
162.9
126.9
119.7
144.8
173.4
119.8
118.5
119.8
114.9
153.5
125.2
121.6
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
100.0
100.0
100.0
100.0
100.0
100.0
133.7
123.5
106.1
92.4
102.9
99.5
139.1
134.7
112.0
96.9
103.5
101.4
141.2
137.8
111.5
97.6
102.0
100.6
151.0
147.8
117.7
97.9
100.3
99.5
160.4
158.2
123.2
98.7
102.9
101.5
163.9
161.5
122.4
98.5
110.2
106.4
171.9
168.3
123.5
97.9
121.1
113.5
173.8
173.0
122.8
99.5
126.2
117.4
179.7
182.6
126.1
101.6
–
–
Nonfarm business
Output per hour of all persons........................................
Compensation per hour…………………………….………
Real compensation per hour………………………………
Unit labor costs…...............................……………………
Unit nonlabor payments…………...………..........………
Implicit price deflator………………………………………
Nonfinancial corporations
Output per hour of all employees...................................
Compensation per hour…………………………….………
Real compensation per hour………………………………
Total unit costs…...............................……………………
Unit labor costs.............................................................
Unit nonlabor costs......................................................
Unit profits......................................................................
Unit nonlabor payments…………...………..........………
Implicit price deflator………………………………………
Manufacturing
Output per hour of all persons........................................
Compensation per hour…………………………….………
Real compensation per hour………………………………
Unit labor costs…...............................……………………
Unit nonlabor payments…………...………..........………
Implicit price deflator………………………………………
Dash indicates data not available.
122
Monthly Labor Review • September 2008
50. Annual indexes of output per hour for selected NAICS industries
[1997=100]
NAICS
Industry
Mining
1987
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
85.5
80.1
80.1
69.8
58.5
71.2
88.5
100.0
100.0
100.0
100.0
100.0
100.0
100.0
103.6
101.2
101.2
104.5
106.5
109.3
101.3
111.4
107.9
107.9
105.8
110.3
112.3
101.2
111.0
119.4
119.4
106.3
115.8
122.0
96.2
109.1
121.6
121.6
109.0
114.6
131.9
99.3
113.6
123.8
123.8
110.9
112.4
138.6
103.6
116.0
130.1
130.1
113.6
113.2
142.8
108.1
106.8
111.7
111.7
115.9
112.8
137.4
114.2
96.0
107.8
107.8
114.0
107.6
130.0
118.2
87.2
100.3
100.3
110.6
100.0
123.4
118.7
-
65.6
67.8
100.0
100.0
103.7
99.0
103.5
102.7
107.0
113.2
106.4
110.1
102.9
115.4
105.1
114.1
107.5
118.3
114.3
122.2
115.4
119.0
-
21
211
2111
212
2121
2122
2123
Mining………………………………………………….
Oil and gas extraction…………………………………
Oil and gas extraction…………………………………
Mining, except oil and gas……………………………
Coal mining……………………………………………
Metal ore mining………………………………………
Nonmetallic mineral mining and quarrying…………
2211
2212
Power generation and supply…………………………
Natural gas distribution………………………………
311
3111
3112
3113
3114
Food………………………………………………….
Animal food……………………………………………
Grain and oilseed milling………………………………
Sugar and confectionery products……………………
Fruit and vegetable preserving and specialty………
94.1
83.6
81.1
87.6
92.4
100.0
100.0
100.0
100.0
100.0
103.9
109.0
107.5
103.5
107.1
105.9
110.9
116.1
106.5
109.5
107.1
109.7
113.1
109.9
111.8
109.5
131.4
119.5
108.6
121.4
113.8
142.7
122.4
108.0
126.9
116.8
165.8
123.9
112.5
123.0
117.3
149.5
130.3
118.2
126.2
123.3
165.5
133.0
130.7
132.0
121.1
150.4
130.7
129.2
126.9
-
3115
3116
3117
3118
3119
Dairy products…………………………………………
82.7
Animal slaughtering and processing………………… 97.4
Seafood product preparation and packaging……… 123.1
Bakeries and tortilla manufacturing………………… 100.9
Other food products…………………………………… 97.5
100.0
100.0
100.0
100.0
100.0
100.0
100.0
120.2
103.8
107.8
93.6
101.2
131.6
108.6
111.4
95.9
102.6
140.5
108.3
112.6
97.1
103.7
153.0
109.9
106.2
105.0
107.3
169.8
108.9
111.9
110.5
106.6
173.2
109.3
118.8
107.4
108.0
162.2
113.8
119.3
109.6
117.4
186.1
115.4
116.2
110.2
116.9
203.8
110.5
116.3
-
312
3121
3122
313
3131
Beverages and tobacco products……………………
Beverages………………………………………………
Tobacco and tobacco products………………………
Textile mills……………………………………………
Fiber, yarn, and thread mills…………………………
78.1
77.1
71.9
73.7
66.5
100.0
100.0
100.0
100.0
100.0
97.6
99.0
98.5
102.6
102.1
87.3
90.7
91.0
106.2
103.9
88.3
90.8
95.9
106.7
101.3
89.5
92.7
98.2
109.5
109.1
82.6
99.4
67.0
125.3
133.3
90.9
108.3
78.7
136.1
148.8
94.7
114.1
82.4
138.6
154.1
100.5
120.3
93.1
152.8
143.5
94.0
112.0
94.9
150.5
139.7
-
3132
3133
314
3141
3149
Fabric mills……………………………………………
Textile and fabric finishing mills………………………
Textile product mills……………………………………
Textile furnishings mills………………………………
Other textile product mills……………………………
68.0
91.3
93.0
91.2
92.2
100.0
100.0
100.0
100.0
100.0
104.2
101.2
98.7
99.3
96.7
110.0
102.2
102.5
99.1
107.6
110.1
104.4
107.1
104.5
108.9
110.3
108.5
104.5
103.1
103.1
125.4
119.8
107.3
105.5
105.1
137.3
125.1
112.7
114.4
104.2
138.6
127.7
123.4
122.3
120.4
164.2
139.8
128.0
125.7
128.9
170.5
126.2
121.1
117.3
126.1
-
315
3151
3152
3159
316
Apparel…………………………………………………
Apparel knitting mills…………………………………
Cut and sew apparel…………………………………
Accessories and other apparel………………………
Leather and allied products…………………………
71.9
76.2
69.8
97.8
71.6
100.0
100.0
100.0
100.0
100.0
101.8
96.1
102.3
109.0
106.6
111.7
101.4
114.6
99.3
112.7
116.8
108.9
119.8
98.3
120.3
116.5
105.6
119.5
105.2
122.4
102.9
112.0
103.9
76.1
97.7
112.4
105.6
117.2
78.7
99.8
103.4
96.6
108.4
70.8
109.5
110.9
120.0
113.5
74.0
123.6
114.0
123.7
117.6
67.3
132.5
-
3161
3162
3169
321
3211
Leather and hide tanning and finishing………………
Footwear………………………………………………
Other leather products…………………………………
Wood products…………………………………………
Sawmills and wood preservation……………………
94.0
76.7
92.3
95.0
77.6
100.0
100.0
100.0
100.0
100.0
100.3
102.1
113.3
101.2
100.3
98.1
117.3
110.4
102.9
104.7
100.1
122.3
122.8
102.7
105.4
100.3
130.7
117.6
106.1
108.8
81.2
102.7
96.2
113.6
114.4
82.2
104.8
100.3
114.7
121.3
93.5
100.7
127.7
115.6
118.2
118.7
105.6
149.7
123.1
127.3
118.1
115.4
174.6
124.9
129.7
-
3212
3219
322
3221
3222
Plywood and engineered wood products…………… 99.7
Other wood products………………………………… 103.0
Paper and paper products……………………………
85.8
Pulp, paper, and paperboard mills…………………… 81.7
Converted paper products……………………………
89.0
100.0
100.0
100.0
100.0
100.0
105.1
101.0
102.3
102.5
102.5
98.7
104.5
104.1
111.1
100.1
98.8
103.0
106.3
116.3
101.1
105.2
104.7
106.8
119.9
100.5
110.3
113.9
114.2
133.1
105.6
107.0
113.9
118.9
141.4
109.6
102.9
119.6
123.4
148.0
112.9
110.2
126.3
124.5
147.7
114.8
117.4
125.3
127.3
151.1
116.6
-
323
3231
324
3241
325
Printing and related support activities………………
Printing and related support activities………………
Petroleum and coal products…………………………
Petroleum and coal products…………………………
Chemicals………………………………………………
97.6
97.6
71.1
71.1
85.9
100.0
100.0
100.0
100.0
100.0
100.6
100.6
102.2
102.2
99.9
102.8
102.8
107.1
107.1
103.5
104.6
104.6
113.5
113.5
106.6
105.3
105.3
112.1
112.1
105.3
110.2
110.2
118.0
118.0
114.2
111.1
111.1
119.2
119.2
118.4
114.5
114.5
123.4
123.4
125.8
119.5
119.5
123.8
123.8
134.1
121.1
121.1
122.8
122.8
137.5
-
3251
3252
3253
3254
3255
Basic chemicals………………………………………
Resin, rubber, and artificial fibers……………………
Agricultural chemicals…………………………………
Pharmaceuticals and medicines……………………
Paints, coatings, and adhesives……………………
94.6
77.4
80.4
87.3
89.4
100.0
100.0
100.0
100.0
100.0
102.8
106.0
98.8
93.8
100.1
115.7
109.8
87.4
95.7
100.3
117.5
109.8
92.1
95.6
100.8
108.8
106.2
90.0
99.5
105.6
123.8
123.1
99.2
97.4
108.9
136.0
122.2
108.4
101.5
115.2
154.4
121.9
117.4
104.1
119.1
165.2
130.5
132.5
110.0
120.8
169.3
134.9
130.7
115.0
115.4
-
3256
3259
326
3261
3262
Soap, cleaning compounds, and toiletries…………
Other chemical products and preparations…………
Plastics and rubber products…………………………
Plastics products………………………………………
Rubber products………………………………………
84.4
75.4
80.9
83.1
75.5
100.0
100.0
100.0
100.0
100.0
98.0
99.2
103.2
104.2
99.4
93.0
109.3
107.9
109.9
100.2
102.8
119.7
110.2
112.3
101.7
106.0
110.4
112.3
114.6
102.3
124.1
120.8
120.8
123.8
107.1
118.2
123.0
126.0
129.5
111.0
135.3
121.3
128.7
131.9
114.4
153.1
123.5
132.6
135.6
118.7
162.9
118.1
132.8
133.8
124.9
-
327
3271
3272
3273
Nonmetallic mineral products…………………………
Clay products and refractories………………………
Glass and glass products……………………………
Cement and concrete products………………………
87.6
86.9
82.4
93.6
100.0
100.0
100.0
100.0
103.7
101.2
101.3
105.1
104.3
102.7
106.7
105.9
102.5
102.9
108.1
101.6
100.0
98.4
102.9
98.0
104.6
99.7
107.5
102.4
111.2
103.5
115.3
108.3
108.7
109.2
113.8
102.8
115.3
114.6
123.1
106.5
114.6
111.9
132.9
103.1
-
Utilities
Manufacturing
Monthly Labor Review • September 2008 123
Current Labor Statistics: Productivity Data
50. Continued - Annual indexes of output per hour for selected NAICS industries
[1997=100]
NAICS
124
1987
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
3274
3279
331
3311
3312
Lime and gypsum products……………………………
Other nonmetallic mineral products…………………
Primary metals…………………………………………
Iron and steel mills and ferroalloy production………
Steel products from purchased steel…………………
Industry
88.2
83.0
81.0
64.8
79.7
100.0
100.0
100.0
100.0
100.0
114.9
99.0
102.0
101.3
100.6
104.4
95.6
102.8
104.8
93.8
98.5
96.6
101.3
106.0
96.4
101.8
98.6
101.0
104.4
97.9
99.0
106.9
115.2
125.1
96.8
107.1
113.6
118.2
130.4
93.9
104.7
110.6
132.0
164.9
88.6
119.3
118.9
135.5
163.1
90.8
116.5
116.3
134.3
163.5
86.1
-
3313
3314
3315
332
3321
Alumina and aluminum production…………………
Other nonferrous metal production…………………
Foundries………………………………………………
Fabricated metal products……………………………
Forging and stamping…………………………………
90.5
96.8
81.4
87.3
85.4
100.0
100.0
100.0
100.0
100.0
101.5
111.3
101.2
101.3
103.5
103.5
108.4
104.5
103.0
110.9
96.6
102.3
103.6
104.8
121.1
96.2
99.5
107.4
104.8
120.7
124.5
107.6
116.7
110.9
125.0
126.8
120.6
116.3
114.4
133.1
137.3
123.1
123.9
113.4
142.0
154.4
122.3
128.6
116.9
147.6
151.7
115.7
131.8
119.7
152.7
-
3322
3323
3324
3325
3326
Cutlery and handtools…………………………………
Architectural and structural metals…………………
Boilers, tanks, and shipping containers……………
Hardware………………………………………………
Spring and wire products……………………………
86.3
88.7
86.0
88.7
82.2
100.0
100.0
100.0
100.0
100.0
99.9
100.9
100.0
100.5
110.6
108.0
102.0
96.5
105.2
111.4
105.9
100.6
94.2
114.3
112.6
110.3
101.6
94.4
113.5
111.9
113.4
106.0
98.9
115.5
125.7
113.2
108.8
101.6
125.4
135.3
107.6
105.4
93.6
126.0
133.8
114.1
109.2
95.7
131.8
143.2
116.6
113.5
96.6
131.1
140.6
-
3327
3328
3329
333
3331
Machine shops and threaded products………………
Coating, engraving, and heat treating metals………
Other fabricated metal products………………………
Machinery………………………………………………
Agriculture, construction, and mining machinery…
76.9
75.5
91.0
82.3
74.6
100.0
100.0
100.0
100.0
100.0
99.6
100.9
101.9
102.9
103.3
104.2
101.0
99.6
104.7
94.3
108.2
105.5
99.9
111.5
100.3
108.8
107.3
96.7
109.0
100.3
114.8
116.1
106.5
116.6
103.7
115.7
118.3
111.6
125.2
116.1
114.6
125.3
111.2
127.0
125.4
116.3
136.5
112.5
134.1
129.4
117.1
135.5
117.7
137.4
129.1
-
3332
3333
3334
3335
3336
Industrial machinery……………………………………
Commercial and service industry machinery………
HVAC and commercial refrigeration equipment……
Metalworking machinery………………………………
Turbine and power transmission equipment………
75.1
87.0
84.0
85.1
80.2
100.0
100.0
100.0
100.0
100.0
95.1
106.3
106.2
99.1
105.0
105.8
110.0
110.2
100.3
110.8
130.0
101.3
107.9
106.1
114.9
105.8
94.5
110.8
103.3
126.9
117.6
97.8
118.6
112.7
130.7
117.0
104.7
130.0
115.2
143.0
126.5
106.5
132.8
117.1
126.4
122.4
115.1
137.1
127.3
132.5
135.3
122.3
133.4
128.3
128.5
-
3339
334
3341
3342
3343
Other general purpose machinery……………………
Computer and electronic products……………………
Computer and peripheral equipment…………………
Communications equipment…………………………
Audio and video equipment…………………………
83.5
28.4
11.0
39.8
61.7
100.0
100.0
100.0
100.0
100.0
103.7
118.4
140.4
107.1
105.4
106.0
149.5
195.9
135.4
119.6
113.7
181.8
235.0
164.1
126.3
110.5
181.4
252.2
152.9
128.4
117.9
188.0
297.4
128.2
150.1
128.1
217.2
373.4
143.1
171.0
127.1
244.3
415.1
148.4
239.3
138.4
259.6
543.3
143.7
230.2
143.8
282.2
715.7
178.2
240.7
-
3344
3345
3346
335
3351
Semiconductors and electronic components………
Electronic instruments…………………………………
Magnetic media manufacturing and reproduction…
Electrical equipment and appliances…………………
Electric lighting equipment……………………………
17.0
70.2
85.7
75.5
91.1
100.0
100.0
100.0
100.0
100.0
125.8
102.3
106.4
103.9
104.4
173.9
106.7
108.9
106.6
102.8
232.2
116.7
105.8
111.5
102.0
230.0
119.3
99.8
111.4
106.7
263.1
118.1
110.4
113.4
112.4
321.6
125.3
126.1
117.2
111.4
360.0
145.4
142.6
123.3
122.7
381.6
146.6
142.1
130.0
130.3
380.4
150.6
137.7
129.4
136.7
-
3352
3353
3359
336
3361
Household appliances…………………………………
Electrical equipment……………………………………
Other electrical equipment and components………
Transportation equipment……………………………
Motor vehicles…………………………………………
73.3
68.7
78.8
81.6
75.4
100.0
100.0
100.0
100.0
100.0
105.2
100.2
105.8
109.7
113.4
104.0
98.7
114.7
118.0
122.6
117.2
99.4
119.7
109.4
109.7
124.6
101.0
113.1
113.6
110.0
132.3
101.8
114.0
127.4
126.0
146.7
103.4
116.2
137.5
140.7
159.6
110.8
115.6
134.9
142.1
164.5
118.5
121.6
140.9
148.4
173.2
118.1
115.7
142.4
163.8
-
3362
3363
3364
3365
3366
Motor vehicle bodies and trailers……………………
Motor vehicle parts……………………………………
Aerospace products and parts………………………
Railroad rolling stock…………………………………
Ship and boat building…………………………………
85.0
78.7
87.2
55.6
95.5
100.0
100.0
100.0
100.0
100.0
102.9
104.9
119.1
103.3
99.3
103.1
110.0
120.8
116.5
112.0
98.8
112.3
103.4
118.5
122.0
88.7
114.8
115.7
126.1
121.5
105.4
130.5
118.6
146.1
131.0
109.8
137.0
119.0
139.8
133.9
110.7
138.0
113.2
131.5
138.7
114.2
144.1
125.0
137.3
131.7
110.9
143.7
117.9
148.0
127.3
-
3369
337
3371
3372
3379
Other transportation equipment………………………
Furniture and related products………………………
Household and institutional furniture…………………
Office furniture and fixtures……………………………
Other furniture related products………………………
73.8
84.8
85.2
85.8
86.3
100.0
100.0
100.0
100.0
100.0
111.5
102.0
102.2
100.0
106.9
113.8
101.6
103.1
98.2
102.0
132.4
101.4
101.9
100.2
99.5
140.2
103.4
105.5
98.0
105.0
150.9
112.6
111.8
115.9
110.2
163.0
117.0
114.7
125.2
110.0
168.3
118.4
113.6
130.7
121.3
184.1
125.0
120.8
134.9
128.3
197.8
127.8
124.0
134.4
130.8
-
339
3391
3399
Miscellaneous manufacturing…………………………
Medical equipment and supplies……………………
Other miscellaneous manufacturing…………………
81.1
76.3
85.4
100.0
100.0
100.0
105.2
109.0
102.1
107.8
111.1
105.0
114.7
115.5
113.6
116.6
120.7
111.8
124.2
129.1
118.0
132.7
138.9
124.7
134.9
139.5
128.6
144.6
148.5
137.8
149.8
152.8
143.2
-
42
423
4231
4232
4233
4234
Wholesale trade………………………………………
73.2
Durable goods…………………………………………
62.3
Motor vehicles and parts……………………………… 74.5
Furniture and furnishings……………………………
80.5
Lumber and construction supplies…………………… 109.1
Commercial equipment………………………………
28.0
100.0
100.0
100.0
100.0
100.0
100.0
103.4
107.1
106.4
99.9
105.4
125.5
111.2
119.2
120.4
102.3
109.3
162.0
116.5
125.0
116.7
112.5
107.7
181.9
117.7
128.9
120.0
110.7
116.6
217.9
123.3
140.2
133.4
116.0
123.9
264.9
127.5
146.6
137.6
123.9
133.0
299.1
134.8
161.5
143.5
130.0
139.4
352.8
135.8
167.4
146.5
127.1
140.2
402.0
138.6
174.5
162.7
130.6
135.4
447.3
141.5
178.4
161.8
131.1
124.5
508.5
4235
4236
4237
4238
4239
424
Metals and minerals…………………………………… 101.7
Electric goods…………………………………………
42.8
82.2
Hardware and plumbing………………………………
Machinery and supplies………………………………
74.1
Miscellaneous durable goods………………………… 89.8
Nondurable goods……………………………………
91.0
100.0
100.0
100.0
100.0
100.0
100.0
100.9
105.9
101.8
104.3
100.8
99.1
94.0
127.5
104.4
102.9
113.7
100.8
93.9
152.8
103.7
105.5
114.7
105.1
94.4
147.6
100.5
102.9
116.8
105.1
96.3
159.5
102.6
100.3
124.6
105.8
97.5
165.7
103.9
103.4
119.6
110.5
106.3
194.1
107.3
112.4
135.0
113.6
104.2
204.6
104.5
117.6
135.5
114.3
99.9
222.1
105.6
121.2
122.3
113.1
94.4
235.1
105.8
121.5
118.4
115.0
Wholesale trade
Monthly Labor Review • September 2008
2007
50. Continued - Annual indexes of output per hour for selected NAICS industries
[1997=100]
NAICS
Industry
1987
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
85.6
70.7
86.3
87.9
81.6
100.0
100.0
100.0
100.0
100.0
98.4
94.2
103.6
101.1
94.3
100.1
93.1
105.1
101.0
101.6
100.9
85.9
108.8
102.4
105.1
104.6
84.9
115.2
101.9
102.1
116.6
89.8
122.8
98.6
98.1
119.7
100.2
125.9
104.9
98.2
130.9
105.8
131.0
104.1
109.3
141.7
112.1
140.8
103.4
111.0
136.9
109.7
146.6
103.8
117.9
146.5
104.3
148.3
109.7
125.1
4246
4247
4248
4249
425
4251
Chemicals……………………………………………… 90.4
Petroleum………………………………………………
84.4
Alcoholic beverages…………………………………… 99.3
Miscellaneous nondurable goods…………………… 111.2
Electronic markets and agents and brokers………… 64.3
Electronic markets and agents and brokers………… 64.3
100.0
100.0
100.0
100.0
100.0
100.0
97.1
88.5
106.5
105.4
102.4
102.4
93.3
102.9
105.6
106.8
112.3
112.3
87.9
138.1
108.4
115.0
120.1
120.1
85.3
140.6
106.4
111.9
110.7
110.7
89.1
153.6
106.8
106.1
109.8
109.8
92.2
151.1
107.9
109.8
104.5
104.5
91.2
163.2
103.1
120.7
101.6
101.6
87.4
153.3
104.0
124.1
91.5
91.5
85.1
149.4
107.4
121.9
95.0
95.0
86.4
149.1
108.5
117.1
98.3
98.3
44-45
441
4411
4412
4413
Retail trade……………………………………………
Motor vehicle and parts dealers………………………
Automobile dealers……………………………………
Other motor vehicle dealers…………………………
Auto parts, accessories, and tire stores……………
79.2
78.4
79.2
74.1
71.8
100.0
100.0
100.0
100.0
100.0
105.7
106.4
106.5
109.6
105.1
112.7
115.1
116.3
114.8
107.6
116.1
114.3
113.7
115.3
108.4
120.1
116.0
115.5
124.6
101.3
125.6
119.9
117.2
133.6
107.7
131.6
124.3
119.5
133.8
115.1
137.9
127.3
124.7
143.3
110.1
141.3
126.7
123.5
134.6
115.5
147.3
129.3
125.8
142.6
115.9
152.7
132.2
129.8
146.9
112.0
442
4421
4422
443
4431
Furniture and home furnishings stores………………
Furniture stores…………………………………………
Home furnishings stores………………………………
Electronics and appliance stores……………………
Electronics and appliance stores……………………
75.1
77.3
71.3
38.0
38.0
100.0
100.0
100.0
100.0
100.0
104.1
104.3
104.1
122.6
122.6
110.8
107.5
115.2
150.6
150.6
115.9
112.0
121.0
173.7
173.7
122.4
119.7
126.1
196.7
196.7
129.3
125.2
134.9
233.5
233.5
134.6
128.8
142.6
292.7
292.7
146.7
139.2
156.8
334.1
334.1
150.5
142.3
161.4
367.5
367.5
158.2
151.1
168.3
412.0
412.0
168.7
156.6
184.6
471.1
471.1
444
4441
4442
445
4451
Building material and garden supply stores………… 75.8
Building material and supplies dealers……………… 77.6
Lawn and garden equipment and supplies stores…
66.9
Food and beverage stores…………………………… 110.8
Grocery stores………………………………………… 111.1
100.0
100.0
100.0
100.0
100.0
107.4
108.3
102.4
99.9
99.6
113.8
115.3
105.5
101.9
102.5
113.3
115.1
103.1
101.0
101.1
116.8
116.7
118.4
103.8
103.3
120.8
121.3
118.3
104.7
104.8
127.1
127.4
125.7
107.2
106.7
134.6
134.0
140.1
112.9
112.2
134.8
134.9
134.7
117.9
116.8
137.9
138.0
138.3
120.6
118.2
142.2
140.0
162.1
123.8
120.6
4452
4453
446
4461
447
Specialty food stores………………………………… 138.5
Beer, wine, and liquor stores………………………… 93.6
Health and personal care stores……………………
84.0
Health and personal care stores……………………
84.0
Gasoline stations……………………………………… 83.9
100.0
100.0
100.0
100.0
100.0
100.5
104.6
104.0
104.0
106.7
96.4
99.1
107.1
107.1
110.7
98.5
105.7
112.2
112.2
107.7
108.2
107.1
116.2
116.2
112.9
105.3
110.1
122.9
122.9
125.1
112.2
117.0
129.5
129.5
119.9
120.3
127.8
134.3
134.3
122.2
125.3
139.8
133.4
133.4
124.7
139.4
146.1
139.3
139.3
124.9
145.4
156.8
139.0
139.0
129.3
4471
448
4481
4482
4483
Gasoline stations………………………………………
Clothing and clothing accessories stores……………
Clothing stores…………………………………………
Shoe stores……………………………………………
Jewelry, luggage, and leather goods stores………
83.9
66.3
67.1
65.3
64.5
100.0
100.0
100.0
100.0
100.0
106.7
106.3
108.7
94.2
108.7
110.7
114.0
114.2
104.9
122.5
107.7
123.5
125.0
110.0
130.5
112.9
126.4
130.3
111.5
123.9
125.1
131.3
136.0
125.2
118.7
119.9
138.9
141.8
132.5
132.9
122.2
139.1
140.9
124.8
144.3
124.7
147.6
153.0
132.0
138.9
124.9
162.4
169.4
145.1
148.3
129.3
176.6
186.9
141.6
162.9
451
4511
4512
452
4521
Sporting goods, hobby, book, and music stores……
Sporting goods and musical instrument stores……
Book, periodical, and music stores…………………
General merchandise stores…………………………
Department stores……………………………………
74.9
73.2
78.9
73.5
87.2
100.0
100.0
100.0
100.0
100.0
107.9
111.5
101.0
105.3
100.4
114.0
119.8
103.2
113.4
104.5
121.1
129.4
105.8
120.2
106.2
127.1
134.5
113.0
124.8
103.8
127.6
136.0
111.6
129.1
102.0
131.5
141.1
113.7
136.9
106.8
151.1
166.0
123.6
140.7
109.0
163.5
179.3
134.3
145.0
110.0
170.5
191.4
132.4
149.8
112.7
167.8
189.2
128.3
152.5
107.0
4529
453
4531
4532
4533
Other general merchandise stores…………………
Miscellaneous store retailers…………………………
Florists…………………………………………………
Office supplies, stationery and gift stores……………
Used merchandise stores……………………………
54.8
65.1
77.6
61.4
64.5
100.0
100.0
100.0
100.0
100.0
114.7
108.9
102.3
111.5
119.1
131.0
111.3
116.2
119.2
113.4
147.3
114.1
115.2
127.3
116.5
164.7
112.6
102.7
132.3
121.9
179.3
119.1
113.8
141.5
142.0
188.8
126.1
108.9
153.9
149.7
192.9
130.8
103.4
172.8
152.6
199.8
139.2
123.7
182.4
156.6
204.8
155.0
145.1
204.8
167.6
219.3
160.8
132.9
224.5
182.0
4539
454
4541
4542
4543
Other miscellaneous store retailers…………………
Nonstore retailers………………………………………
Electronic shopping and mail-order houses…………
Vending machine operators…………………………
Direct selling establishments…………………………
68.3
50.7
39.4
95.5
70.8
100.0
100.0
100.0
100.0
100.0
105.3
114.3
120.2
106.3
101.9
103.0
128.9
142.6
105.4
104.3
104.4
152.2
160.2
111.1
122.5
96.9
163.6
179.6
95.7
127.9
94.4
182.1
212.7
91.3
135.1
99.9
195.5
243.6
102.3
127.0
96.9
215.5
273.0
110.5
130.3
101.6
220.6
290.1
114.4
119.6
114.0
261.9
355.9
125.7
127.5
115.4
290.8
397.2
132.4
138.4
481
482111
48412
48421
491
4911
Air transportation………………………………………
81.1
Line-haul railroads……………………………………
58.9
General freight trucking, long-distance……………… 85.7
Used household and office goods moving………… 106.7
U.S. Postal service……………………………………
90.9
U.S. Postal service……………………………………
90.9
100.0
100.0
100.0
100.0
100.0
100.0
97.6
102.1
99.4
91.0
101.6
101.6
98.2
105.5
99.1
96.1
102.8
102.8
98.1
114.3
101.9
94.8
105.5
105.5
91.9
121.9
103.2
84.0
106.3
106.3
102.1
131.9
107.0
81.6
106.4
106.4
112.8
142.0
110.7
86.2
107.8
107.8
126.9
146.4
110.7
88.6
110.0
110.0
135.5
138.4
113.2
88.3
111.2
111.2
142.5
142.8
112.3
87.0
111.3
111.3
-
492
493
4931
49311
49312
Couriers and messengers…………………………… 148.3
Warehousing and storage……………………………
Warehousing and storage……………………………
General warehousing and storage…………………
Refrigerated warehousing and storage………………
-
100.0
100.0
100.0
100.0
100.0
112.6
106.4
106.4
112.1
97.9
117.6
107.7
107.7
112.9
103.4
122.0
109.3
109.3
115.8
95.4
123.4
115.3
115.3
126.3
85.4
131.1
122.1
122.1
136.1
87.2
134.0
124.8
124.8
138.9
92.3
126.8
122.5
122.5
131.0
99.3
125.1
124.9
124.9
132.2
97.5
128.6
122.3
122.3
127.9
88.5
-
100.0
116.1
116.3
117.1
116.6
117.2
126.4
130.7
136.5
142.7
-
4241
4242
4243
4244
4245
Paper and paper products……………………………
Druggists' goods………………………………………
Apparel and piece goods……………………………
Grocery and related products…………………………
Farm product raw materials…………………………
511
Retail trade
Transportation and warehousing
Information
Publishing industries, except internet
64.1
Monthly Labor Review • September 2008 125
Current Labor Statistics: Productivity Data
50. Continued - Annual indexes of output per hour for selected NAICS industries
[1997=100]
NAICS
1987
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
5111
5112
51213
515
5151
5152
Newspaper, book, and directory publishers………… 105.0
Software publishers…………………………………… 10.2
90.7
Motion picture and video exhibition…………………
Broadcasting, except internet………………………… 99.5
Radio and television broadcasting…………………… 98.1
Cable and other subscription programming………… 105.6
Industry
100.0
100.0
100.0
100.0
100.0
100.0
103.9
134.8
99.8
100.8
91.5
136.2
104.1
129.2
101.8
102.9
92.6
139.1
107.7
119.2
106.5
103.6
92.1
141.2
105.8
117.4
101.6
99.2
89.6
128.1
104.7
122.1
99.8
104.0
95.1
129.8
109.5
138.1
100.4
107.9
94.6
146.0
106.6
160.6
103.6
112.5
96.6
158.7
107.6
173.7
102.4
117.7
100.9
164.6
110.8
177.0
105.7
125.5
109.5
169.9
-
5171
5172
5175
Wired telecommunications carriers…………………
56.9
Wireless telecommunications carriers………………
75.6
Cable and other program distribution……………… 105.2
100.0
100.0
100.0
107.7
110.5
97.1
116.7
145.2
95.8
122.7
152.8
91.6
116.7
191.9
87.7
124.1
217.9
95.0
130.5
242.6
101.3
131.7
292.2
113.8
138.2
381.9
110.6
146.2
435.9
110.6
-
52211
Commercial banking…………………………………
72.8
100.0
97.0
99.8
102.7
99.6
102.1
103.6
108.4
108.5
114.2
-
92.7
60.3
77.0
100.0
100.0
100.0
100.1
115.4
113.2
112.2
120.9
129.4
112.3
121.7
134.9
111.1
113.5
133.3
114.6
114.0
130.3
121.1
115.8
148.5
118.2
136.6
154.5
110.2
145.1
144.2
111.8
162.2
176.4
-
82.9
90.0
90.2
95.9
98.1
100.0
100.0
100.0
100.0
100.0
107.6
111.4
98.2
89.2
124.8
105.8
106.8
98.0
97.9
109.8
100.9
107.6
102.0
107.5
108.9
94.4
111.0
100.1
106.9
102.2
111.4
107.6
100.5
113.1
97.6
110.0
112.6
100.5
121.1
104.1
99.9
118.3
107.8
133.5
93.0
103.6
120.8
115.4
131.5
93.5
99.7
119.1
116.2
132.8
95.3
-
89.3
75.1
100.0
100.0
100.0
86.8
111.4
95.3
93.2
115.5
98.6
89.8
119.4
101.0
99.6
115.2
102.1
116.8
127.6
105.6
115.4
147.2
118.8
119.8
167.2
116.6
115.9
182.4
121.5
122.9
189.9
115.6
-
-
100.0
100.0
100.0
118.8
117.2
121.4
124.7
121.4
129.7
131.9
127.4
139.9
135.3
127.7
148.3
137.6
123.1
163.3
140.8
128.6
160.0
140.8
130.7
153.5
137.9
126.0
154.0
140.1
128.2
156.3
-
Finance and insurance
Real estate and rental and leasing
2007
532111
53212
53223
Passenger car rental…………………………………
Truck, trailer, and RV rental and leasing……………
Video tape and disc rental……………………………
541213
54131
54133
54181
541921
Tax preparation services………………………………
Architectural services…………………………………
Engineering services…………………………………
Advertising agencies…………………………………
Photography studios, portrait…………………………
56131
56151
56172
Employment placement agencies……………………
Travel agencies………………………………………
Janitorial services………………………………………
6215
621511
621512
Medical and diagnostic laboratories…………………
Medical laboratories……………………………………
Diagnostic imaging centers……………………………
71311
71395
Amusement and theme parks………………………
Bowling centers………………………………………
112.0
106.0
100.0
100.0
110.5
89.9
105.2
89.4
106.0
93.4
93.0
94.3
106.5
96.4
113.2
102.4
101.4
107.9
109.9
106.1
97.7
110.6
-
7211
722
7221
7222
7223
7224
Traveler accommodation……………………………… 85.1
Food services and drinking places…………………
96.0
Full-service restaurants………………………………
92.1
Limited-service eating places………………………… 96.5
Special food services…………………………………
89.9
Drinking places, alcoholic beverages……………… 136.7
100.0
100.0
100.0
100.0
100.0
100.0
100.1
101.0
100.9
101.2
100.6
99.7
105.6
100.9
100.8
100.4
105.2
98.8
111.8
103.5
103.0
102.0
115.0
100.6
107.6
103.8
103.6
102.5
115.3
97.6
112.1
104.4
104.4
102.7
114.9
102.9
114.4
106.3
104.2
105.4
117.6
118.6
120.4
107.0
104.8
106.8
118.0
112.2
115.0
107.9
105.2
107.5
119.2
121.6
111.8
109.7
106.0
109.8
118.7
135.7
109.2
105.1
108.6
120.2
145.2
8111
81211
81221
8123
81292
Automotive repair and maintenance………………… 85.9
Hair, nail, and skin care services……………………
83.5
Funeral homes and funeral services………………… 103.7
Drycleaning and laundry services…………………… 97.1
Photofinishing…………………………………………
95.8
100.0
100.0
100.0
100.0
100.0
103.6
108.6
106.8
100.1
69.3
106.1
108.6
103.3
105.0
76.3
109.4
108.2
94.8
107.6
73.8
108.9
114.6
91.8
110.9
81.2
103.7
110.4
94.6
112.5
100.5
104.1
119.7
95.7
103.8
100.5
112.0
125.0
92.9
110.6
102.0
111.9
129.9
93.2
120.5
112.4
112.8
122.3
99.7
119.6
114.4
-
Professional and technical services
Administrative and waste services
Health care and social assistance
Arts, entertainment, and recreation
Accommodation and food services
Other services
NOTE: Dash indicates data are not available.
126
Monthly Labor Review • September 2008
51. Unemployment rates, approximating U.S. concepts, 10 countries, seasonally adjusted
[Percent]
2006
Country
2006
2007
I
II
2007
III
IV
I
II
2008
III
IV
I
United States………
4.6
4.6
4.7
4.7
4.7
4.4
4.5
4.5
4.7
4.8
Canada………………
5.5
5.3
5.7
5.4
5.6
5.4
5.4
5.3
5.2
5.2
5.2
Australia……………
4.8
4.4
5.0
4.9
4.7
4.5
4.5
4.3
4.3
4.3
4.1
Japan…………………
4.2
3.9
4.2
4.2
4.2
4.1
4.0
3.8
3.8
3.9
3.9
France………………
9.5
8.6
9.8
9.7
9.5
9.2
9.0
8.8
8.5
8.2
8.1
Germany……………
10.4
8.7
11.1
10.6
10.1
9.6
9.3
8.9
8.5
8.2
7.7
Italy…………………
6.9
6.1
7.3
6.9
6.7
6.4
6.3
6.1
6.0
6.0
-
Netherlands…………
3.9
3.2
4.3
3.9
3.8
3.8
3.6
3.2
3.0
3.0
-
Sweden………………
7.0
6.1
7.3
7.3
6.7
6.5
6.4
6.1
5.8
5.9
5.8
United Kingdom……
5.5
5.4
5.3
5.5
5.6
5.5
5.5
5.4
5.4
5.2
-
NOTE: Dash indicates data not available.
Quarterly figures for France, Germany, Italy, and the Netherlands are
calculated by applying annual adjustment factors to current published data
and therefore should be viewed as less precise indicators of unemployment
under U.S. concepts than the annual figures. Quarterly figures for Sweden
are BLS seasonally adjusted estimates derived from Swedish not
seasonally adjusted data.
For further qualifications and historical annual data, see the BLS report
Comparative Civilian Labor Force Statistics, 10 Countries (on the
4.9
Internet at http://www.bls.gov/fls/flscomparelf.htm ).
For monthly
unemployment rates, as well as the quarterly and annual rates published in
this table, see the BLS report Unemployment rates in 10 countries, civilian
labor force basis, approximating U.S. concepts, seasonally adjusted (on the
Internet at http://www.bls.gov/fls/flsjec.pdf ). Unemployment rates may
differ between the two reports mentioned, because the former is updated
semi-annually, whereas the latter is updated monthly and reflects the most
recent revisions in source data.
Monthly Labor Review • September 2008 127
Current Labor Statistics: International Comparisons
52. Annual data: employment status of the working-age population, approximating U.S. concepts, 10 countries
[Numbers in thousands]
Employment status and country
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
137,673
15,135
9,339
67,240
25,434
39,752
23,004
7,744
4,401
28,474
139,368
15,403
9,414
67,090
25,791
39,375
23,176
7,881
4,423
28,777
142,583
15,637
9,590
66,990
26,099
39,302
23,361
8,052
4,482
28,952
143,734
15,891
9,744
66,860
26,393
39,459
23,524
8,199
4,522
29,085
144,863
16,366
9,893
66,240
26,646
39,413
23,728
8,345
4,537
29,337
146,510
16,733
10,079
66,010
26,851
39,276
24,020
8,379
4,557
29,559
147,401
16,955
10,221
65,770
26,937
39,711
24,084
8,439
4,571
29,791
149,320
17,108
10,506
65,850
27,092
40,760
24,179
8,459
4,694
30,126
151,428
17,351
10,699
65,960
27,322
41,250
24,395
8,541
4,748
30,586
153,124
17,696
10,948
66,080
27,509
24,459
8,686
4,823
30,774
67.1
65.1
64.3
63.2
55.6
57.3
47.3
61.1
63.2
62.5
67.1
65.4
64.3
62.8
56.0
57.7
47.7
61.8
62.8
62.5
67.1
65.9
64.0
62.4
56.3
56.9
47.9
62.5
62.7
62.8
67.1
66.0
64.4
62.0
56.6
56.7
48.1
63.4
63.7
62.9
66.8
66.1
64.4
61.6
56.7
56.7
48.3
64.0
63.6
62.7
66.6
67.1
64.3
60.8
56.8
56.4
48.5
64.7
63.9
62.9
66.2
67.7
64.6
60.3
56.8
56.0
49.1
64.6
63.8
63.0
66.0
67.7
64.6
60.0
56.6
56.4
49.1
64.8
63.6
63.0
66.0
67.4
65.3
60.0
56.5
57.6
48.7
64.7
64.8
63.1
66.2
67.4
65.6
60.0
56.6
58.2
48.9
65.1
65.0
63.5
66.0
67.7
66.0
60.0
56.7
48.6
65.9
65.3
63.4
United States……………………………………………… 129,558
Canada……………………………………………………
13,637
Australia……………………………………………………
8,444
Japan………………………………………………………
64,900
France……………………………………………………
22,176
Germany…………………………………………………
35,508
Italy………………………………………………………… 20,169
Netherlands………………………………………………
7,189
Sweden……………………………………………………
3,969
United Kingdom…………………………………………
26,413
131,463
13,973
8,618
64,450
22,597
36,059
20,370
7,408
4,033
26,686
133,488
14,331
8,762
63,920
23,080
36,042
20,617
7,605
4,110
27,051
136,891
14,681
8,989
63,790
23,714
36,236
20,973
7,813
4,222
27,368
136,933
14,866
9,086
63,460
24,167
36,350
21,359
8,014
4,295
27,599
136,485
15,223
9,264
62,650
24,312
36,018
21,666
8,114
4,303
27,813
137,736
15,586
9,480
62,510
24,373
35,615
21,972
8,069
4,293
28,075
139,252
15,861
9,668
62,640
24,354
35,604
22,124
8,052
4,271
28,372
141,730
16,080
9,975
62,910
24,493
36,185
22,290
8,056
4,334
28,665
144,427
16,393
10,186
63,210
24,717
36,978
22,721
8,205
4,416
28,917
146,047
16,767
10,470
63,510
25,135
22,953
8,408
4,530
29,120
63.8
59.6
59.0
61.0
49.1
51.6
41.9
57.7
56.8
58.2
64.1
60.4
59.3
60.2
49.7
52.3
42.2
59.1
57.6
58.5
64.3
61.3
59.6
59.4
50.4
52.1
42.6
60.3
58.3
59.1
64.4
62.0
60.3
59.0
51.4
52.2
43.2
61.5
60.0
59.4
63.7
61.9
60.0
58.4
51.9
52.2
43.8
62.6
60.4
59.5
62.7
62.4
60.2
57.5
51.8
51.5
44.3
62.9
60.6
59.6
62.3
63.1
60.7
57.1
51.5
50.8
44.9
62.2
60.1
59.8
62.3
63.3
61.1
57.1
51.1
50.6
45.1
61.8
59.4
60.0
62.7
63.4
62.0
57.3
51.1
51.2
44.9
61.6
59.9
60.1
63.1
63.6
62.5
57.5
51.2
52.2
45.5
62.5
60.4
60.1
63.0
64.2
63.1
57.6
51.8
45.6
63.8
61.3
60.0
6,739
1,248
759
2,300
2,940
3,907
2,584
423
445
1,987
6,210
1,162
721
2,790
2,837
3,693
2,634
337
368
1,788
5,880
1,072
652
3,170
2,711
3,333
2,559
277
313
1,726
5,692
956
602
3,200
2,385
3,065
2,388
239
260
1,584
6,801
1,026
658
3,400
2,226
3,110
2,164
186
227
1,486
8,378
1,143
629
3,590
2,334
3,396
2,062
231
234
1,524
8,774
1,147
599
3,500
2,478
3,661
2,048
310
264
1,484
8,149
1,093
553
3,130
2,583
4,107
1,960
387
300
1,419
7,591
1,028
531
2,940
2,599
4,575
1,889
402
361
1,462
7,001
958
512
2,750
2,605
4,272
1,673
336
332
1,669
7,078
929
478
2,570
2,374
1,506
278
293
1,654
4.9
8.4
8.3
3.4
11.7
9.9
11.4
5.6
10.1
7.0
4.5
7.7
7.7
4.1
11.2
9.3
11.5
4.4
8.4
6.3
4.2
7.0
6.9
4.7
10.5
8.5
11.0
3.5
7.1
6.0
4.0
6.1
6.3
4.8
9.1
7.8
10.2
3.0
5.8
5.5
4.7
6.5
6.8
5.1
8.4
7.9
9.2
2.3
5.0
5.1
5.8
7.0
6.4
5.4
8.8
8.6
8.7
2.8
5.2
5.2
6.0
6.9
5.9
5.3
9.2
9.3
8.5
3.7
5.8
5.0
5.5
6.4
5.4
4.8
9.6
10.3
8.1
4.6
6.6
4.8
5.1
6.0
5.1
4.5
9.6
11.2
7.8
4.8
7.7
4.9
4.6
5.5
4.8
4.2
9.5
10.4
6.9
3.9
7.0
5.5
4.6
5.3
4.4
3.9
8.6
8.7
6.2
3.2
6.1
5.4
Civilian labor force
United States……………………………………………… 136,297
Canada……………………………………………………
14,884
Australia……………………………………………………
9,204
Japan………………………………………………………
67,200
France……………………………………………………
25,116
Germany…………………………………………………
39,415
Italy………………………………………………………… 22,753
Netherlands………………………………………………
7,612
Sweden……………………………………………………
4,414
United Kingdom…………………………………………
28,401
Participation rate1
United States………………………………………………
Canada……………………………………………………
Australia……………………………………………………
Japan………………………………………………………
France……………………………………………………
Germany…………………………………………………
Italy…………………………………………………………
Netherlands………………………………………………
Sweden……………………………………………………
United Kingdom…………………………………………
Employed
Employment-population ratio2
United States………………………………………………
Canada……………………………………………………
Australia……………………………………………………
Japan………………………………………………………
France……………………………………………………
Germany…………………………………………………
Italy…………………………………………………………
Netherlands………………………………………………
Sweden……………………………………………………
United Kingdom…………………………………………
Unemployed
United States………………………………………………
Canada……………………………………………………
Australia……………………………………………………
Japan………………………………………………………
France……………………………………………………
Germany…………………………………………………
Italy…………………………………………………………
Netherlands………………………………………………
Sweden……………………………………………………
United Kingdom…………………………………………
Unemployment rate
United States………………………………………………
Canada……………………………………………………
Australia……………………………………………………
Japan………………………………………………………
France……………………………………………………
Germany…………………………………………………
Italy…………………………………………………………
Netherlands………………………………………………
Sweden……………………………………………………
United Kingdom…………………………………………
1
Labor force as a percent of the working-age population.
2
Employment as a percent of the working-age population.
NOTE: Dash indicates data not available.
There are breaks in series for the United States (1998, 1999, 2000, 2003, 2004), Australia
(2001), Germany (1999, 2005), the Netherlands (2000), and Sweden (2005). For further
qualifications and historical annual data, see the BLS report Comparative
128
Monthly Labor Review • September 2008
Civilian
Labor
Force
Statistics,
10
Countries
(on
the
Internet
at
http://www.bls.gov/fls/flscomparelf.htm). Unemployment rates may differ from those
in the BLS report Unemployment rates in 10 countries, civilian labor force basis,
approximating U.S. concepts, seasonally adjusted
(on the Internet at
http://www.bls.gov/fls/flsjec.pdf), because the former is updated semi-annually,
whereas the latter is updated monthly and reflects the most recent revisions in source
data.
53. Annual indexes of manufacturing productivity and related measures, 16 economies
[1996 = 100]
Measure and economy
1980
1990
1993
1994
1995
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Output per hour
United States………………………
Canada………………………….……
Australia…………………….………
Japan…………………………………
Korea, Rep. of………………………
Taiwan………………………………
Belgium…………………………...…
Denmark……………………………
France………………………………
Germany………………………...……
Italy……………………………...……
Netherlands…………………...……
Norway………………………………
Spain………………………………..
Sweden……………………………..
United Kingdom……………….……
58.6
66.5
72.6
54.8
–
40.4
57.2
75.3
56.9
67.1
60.1
58.7
77.3
62.8
60.0
55.9
80.1
85.2
91.1
81.3
58.0
73.9
84.7
90.3
84.2
86.1
82.5
81.4
96.8
86.8
73.9
87.8
88.1
94.0
96.2
87.6
75.9
83.4
89.6
92.0
90.0
89.1
87.2
86.2
98.3
94.9
82.6
100.1
92.7
99.3
98.7
89.0
82.8
86.6
94.4
103.4
95.9
95.8
94.9
94.1
98.3
97.8
91.1
102.7
96.2
100.5
97.2
95.6
90.9
93.0
98.6
103.4
99.7
97.3
99.5
97.9
97.1
101.2
96.8
101.0
104.2
104.5
102.2
103.5
112.8
104.1
109.8
108.0
105.9
105.9
102.0
100.3
100.2
101.0
109.1
102.0
111.5
109.6
107.3
104.5
125.7
109.2
111.2
107.4
111.4
106.3
100.6
103.2
97.7
102.7
115.6
102.9
117.1
114.2
109.0
107.3
139.8
116.0
110.2
109.1
116.2
108.9
101.4
107.4
101.1
104.5
126.2
107.8
126.1
121.1
115.2
113.0
151.7
122.2
114.1
113.0
124.5
116.5
106.7
115.2
104.2
105.6
134.8
115.2
127.4
118.5
117.9
110.6
150.6
127.7
115.3
113.2
127.0
119.5
107.0
115.7
107.1
108.0
131.0
119.4
140.9
120.5
123.2
114.7
165.3
139.2
119.1
113.9
132.4
120.7
105.7
119.2
110.2
108.4
145.3
122.4
149.8
121.1
125.5
122.5
176.8
143.6
122.0
118.7
138.4
125.0
103.5
121.7
119.7
111.1
157.1
128.2
159.0
123.1
127.2
131.0
197.2
150.9
127.6
125.5
142.2
129.7
105.0
129.9
126.8
113.2
173.9
136.0
162.4
127.8
128.1
139.6
212.1
162.3
131.5
126.9
148.7
134.6
106.4
135.8
131.2
115.4
184.7
140.2
165.9
127.7
129.4
142.2
233.5
173.9
134.4
133.4
154.6
144.1
105.9
140.2
135.0
117.7
195.6
147.0
172.7
130.4
133.4
146.2
253.9
189.0
137.3
134.3
158.5
151.3
105.4
144.0
134.7
122.2
197.3
150.8
Output
United States…………………..……
Canada………………………………
Australia………………………………
Japan…………………………………
Korea, Rep. of………………………
Taiwan………………………………
Belgium………………………………
Denmark……………………………
France………………………………
Germany……………………………
Italy……………………………………
Netherlands…………………………
Norway………………………………
Spain………………………………..
Sweden………………………………
United Kingdom……………………
60.5
71.2
80.2
59.0
20.5
38.2
74.8
85.6
83.2
92.3
74.7
70.5
96.7
75.5
67.1
80.3
80.7
88.7
93.1
94.3
63.2
76.7
96.6
94.7
97.5
107.2
92.6
89.2
92.9
94.6
80.4
96.9
85.7
87.7
92.7
93.5
75.5
85.0
92.8
90.3
93.8
99.9
89.9
90.2
93.2
92.4
74.1
93.4
92.2
94.4
97.5
92.1
84.1
90.1
97.0
100.0
96.8
103.1
95.9
95.0
95.7
94.0
85.5
97.8
96.4
98.7
96.9
95.9
94.0
95.0
99.6
104.8
100.3
102.1
100.5
98.6
96.1
97.6
96.8
99.3
106.1
106.3
102.3
102.5
104.9
105.7
108.2
108.2
104.7
104.4
101.5
101.4
104.3
106.4
107.8
101.8
113.2
111.7
105.2
97.1
96.6
109.1
110.1
109.1
109.7
105.6
102.4
104.8
103.6
112.9
116.7
102.4
118.1
121.0
105.0
96.7
117.6
117.1
110.2
110.0
113.4
106.6
102.2
108.7
103.5
119.3
127.6
103.4
125.5
133.1
109.9
101.8
137.6
125.7
114.9
113.9
118.6
113.9
106.5
116.0
102.9
124.6
138.1
105.8
118.5
128.0
108.9
96.2
140.6
116.4
114.9
114.0
119.8
115.8
106.2
115.8
102.2
128.6
134.9
104.5
121.8
129.0
114.2
94.7
151.2
126.7
114.0
110.7
119.7
113.4
105.0
115.9
101.6
128.4
143.4
101.7
123.2
128.3
116.2
99.8
159.6
133.5
112.5
107.6
121.9
114.2
102.2
114.6
105.0
130.0
150.4
101.9
130.1
131.4
116.3
105.6
177.3
146.5
116.6
109.3
123.0
118.3
103.0
118.5
111.0
130.9
164.2
104.0
131.4
133.5
115.8
111.1
189.8
156.7
116.3
105.9
125.9
120.0
102.5
120.9
115.9
132.4
171.8
102.8
135.2
132.2
114.7
115.8
205.9
168.4
119.4
111.7
127.2
127.0
103.7
124.1
123.9
134.8
180.6
104.4
138.3
130.8
118.6
119.0
219.3
185.8
122.4
116.2
128.8
135.0
104.8
128.1
129.3
138.6
185.2
105.0
Total hours
United States……………………… 103.3
Canada……………………………… 107.0
Australia……………………………… 110.5
Japan………………………………… 107.6
Korea, Rep. of………………………
–
Taiwan……………………………… 94.5
Belgium……………………………… 130.9
Denmark…………………………… 113.7
France……………………………… 146.3
Germany…………………………… 137.4
Italy…………………………………… 124.3
Netherlands………………………… 120.1
Norway……………………………… 125.1
Spain……………………………….. 120.3
Sweden……………………………… 111.8
United Kingdom…………………… 143.8
100.7
104.1
102.2
115.9
109.0
103.7
114.1
104.8
115.8
124.6
112.2
109.6
96.0
109.0
108.8
110.4
97.3
93.3
96.4
106.7
99.5
101.9
103.5
98.1
104.1
112.1
103.1
104.6
94.8
97.4
89.7
93.3
99.5
95.1
98.7
103.5
101.6
104.0
102.8
96.7
101.0
107.6
101.1
100.9
97.3
96.1
93.9
95.2
100.2
98.3
99.7
100.4
103.3
102.2
101.0
101.4
100.6
105.0
100.9
100.7
99.0
96.4
100.0
98.3
101.8
101.6
100.1
99.1
93.0
101.6
98.6
100.2
98.9
98.6
99.5
101.0
104.1
105.4
98.8
99.8
101.5
101.9
98.1
92.9
76.8
99.9
98.9
101.5
98.5
99.4
101.8
101.5
106.1
109.9
100.9
99.6
100.9
105.9
96.3
90.2
84.1
101.0
100.0
100.8
97.6
97.9
100.8
101.2
102.4
114.1
101.1
95.9
99.6
109.9
95.4
90.1
90.7
102.9
100.6
100.8
95.3
97.7
99.9
100.7
98.8
118.0
102.4
91.8
93.0
107.9
92.3
87.0
93.3
91.1
99.6
100.7
94.3
96.9
99.3
100.1
95.4
119.0
103.0
87.5
86.5
107.1
92.7
82.6
91.5
91.1
95.7
97.2
90.4
94.0
99.3
97.2
92.3
118.4
98.7
83.1
82.2
105.9
92.6
81.4
90.2
92.9
92.2
90.7
88.1
91.4
98.8
94.1
87.7
117.0
95.7
79.5
81.8
106.7
91.4
80.6
89.9
97.1
91.4
87.1
86.5
91.2
98.1
91.2
87.5
115.6
94.4
76.5
80.9
104.4
90.4
79.6
89.5
96.5
88.5
83.5
84.7
89.2
96.4
89.0
88.4
114.7
93.0
73.3
81.5
103.5
88.7
81.5
88.2
96.8
88.9
83.7
82.3
88.1
97.9
88.5
91.8
114.6
92.4
71.0
80.1
100.3
88.9
81.4
86.4
98.3
89.2
86.5
81.2
89.2
99.4
88.9
96.0
113.4
93.9
69.6
82.7
82.4
79.5
83.0
36.1
66.5
81.4
83.1
78.9
72.3
70.5
79.0
81.2
65.9
77.4
82.8
93.3
93.5
89.3
94.1
61.6
82.6
94.8
90.9
91.8
86.7
85.1
91.7
89.2
90.3
85.8
96.2
96.3
96.2
90.4
96.0
70.8
86.6
95.5
94.1
95.3
90.6
89.6
95.7
91.9
93.6
88.0
98.6
98.1
98.5
95.7
99.2
85.9
93.8
98.2
96.0
98.1
95.5
94.9
98.3
96.0
97.6
92.8
100.3
102.6
102.4
103.0
103.3
108.7
103.1
103.8
103.4
102.9
102.0
104.7
102.3
104.5
102.4
105.4
104.4
108.6
107.7
107.3
105.9
118.4
107.0
105.3
106.1
103.7
103.4
102.8
106.7
110.6
103.2
109.4
112.3
112.9
110.0
111.7
105.7
119.0
108.9
106.7
108.8
107.0
105.8
105.4
110.5
116.9
102.9
112.8
118.9
123.2
113.6
116.3
105.1
127.1
111.0
108.6
110.9
112.8
111.3
108.1
116.1
123.5
104.5
117.2
126.2
126.1
116.7
123.6
106.5
131.1
118.1
114.3
116.2
115.8
114.7
111.8
121.4
130.9
108.7
122.8
131.8
135.2
120.6
129.3
107.2
144.4
114.4
119.3
121.2
122.8
117.5
115.0
128.4
138.8
111.8
129.4
139.1
144.7
125.5
134.5
104.9
151.5
116.3
122.8
129.4
125.7
120.2
119.3
133.5
144.5
117.4
135.2
146.1
147.7
129.1
141.6
105.9
173.0
118.2
125.4
134.4
129.7
120.9
123.4
139.0
149.2
121.5
138.9
153.7
150.5
135.4
150.7
106.8
186.8
122.8
129.8
143.6
134.4
122.4
127.4
141.1
156.2
127.3
143.6
159.7
156.7
138.0
160.3
105.3
202.9
125.2
132.5
148.0
140.9
127.5
129.9
145.0
165.1
132.7
147.7
171.0
162.2
143.2
169.9
105.0
218.6
127.2
136.0
150.5
145.0
129.7
132.7
149.3
172.9
139.2
152.9
175.3
Hourly compensation
(national currency basis)
United States………………………
Canada………………………………
Australia………………………………
Japan…………………………………
Korea, Rep. of………………………
Taiwan………………………………
Belgium………………………………
Denmark……………………………
France………………………………
Germany……………………………
Italy……………………………………
Netherlands…………………………
Norway………………………………
Spain………………………………..
Sweden………………………………
United Kingdom……………………
See notes at end of table.
51.2
43.8
–
53.7
–
23.1
47.5
39.5
34.6
43.3
22.6
52.4
34.3
23.1
32.9
33.4
Monthly Labor Review • September 2008 129
Current Labor Statistics: International Comparisons
53. Continued– Annual indexes of manufacturing productivity and related measures, 16 economies
Measure and economy
1980
1990
1993
1994
1995
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Unit labor costs
(national currency basis)
United States………………………
Canada………………………………
Australia………………………………
Japan…………………………………
Korea, Rep. of………………………
Taiwan………………………………
Belgium………………………………
Denmark……………………………
France………………………………
Germany……………………………
Italy……………………………………
Netherlands…………………………
Norway………………………………
Spain………………………………..
Sweden………………………………
United Kingdom……………………
87.4
65.9
–
98.0
33.6
57.1
83.0
52.5
60.9
64.5
37.6
89.4
44.4
36.8
54.9
59.8
103.3
96.7
87.3
102.1
62.3
89.9
96.1
91.9
93.7
84.0
85.4
97.0
83.9
76.0
104.8
94.3
106.0
99.5
92.8
107.5
81.2
99.1
105.7
98.9
102.0
97.3
97.5
106.4
90.7
95.1
103.9
96.1
103.9
96.9
91.5
107.9
85.5
100.0
101.2
91.0
99.4
94.6
94.4
101.7
93.4
95.7
96.6
96.0
102.0
98.0
98.4
103.8
94.5
100.9
99.6
92.9
98.5
98.2
95.3
100.4
98.9
96.5
95.8
99.4
98.5
98.0
100.7
99.8
96.4
99.0
94.5
95.7
97.2
96.3
102.7
102.0
104.2
101.4
96.6
102.4
97.4
98.3
100.0
101.3
94.2
97.9
94.7
98.8
93.1
97.3
102.2
103.3
113.2
100.4
94.7
109.2
96.4
96.3
102.4
98.6
85.1
93.9
96.9
99.7
92.1
97.1
104.0
102.8
115.7
98.5
89.4
110.3
97.7
93.8
100.9
93.0
83.8
90.9
95.1
98.1
90.6
95.5
101.4
100.8
118.5
99.0
86.9
109.5
99.0
98.5
104.8
96.2
87.0
92.5
99.1
102.7
91.2
96.0
104.5
104.9
122.2
100.6
93.8
110.4
96.0
100.0
105.0
93.5
87.3
82.2
100.2
106.4
92.8
97.4
108.7
107.7
126.0
103.1
89.1
113.7
96.6
103.6
107.1
85.6
85.7
81.0
100.6
109.0
90.8
96.1
115.3
109.7
120.7
105.6
86.1
113.9
92.9
104.9
111.3
80.8
87.8
78.4
98.3
107.0
91.2
93.2
117.6
107.0
117.6
107.3
79.9
113.0
92.6
106.0
117.6
76.5
88.1
75.7
98.7
113.1
90.4
91.0
119.8
103.9
119.1
110.3
77.8
113.9
94.4
108.1
123.9
74.0
86.9
72.0
98.6
110.9
91.2
88.5
122.6
103.5
122.3
112.7
75.5
116.3
93.9
109.8
127.4
71.8
86.1
67.3
99.1
112.1
91.5
85.7
125.8
103.6
128.3
113.9
77.5
116.2
Unit labor costs
(U.S. dollar basis)
United States………………………
Canada………………………………
Australia………………………………
Japan…………………………………
Korea, Rep. of………………………
Taiwan………………………………
Belgium………………………………
Denmark……………………………
France………………………………
Germany……………………………
Italy……………………………………
Netherlands…………………………
Norway………………………………
Spain………………………………..
Sweden………………………………
United Kingdom……………………
87.4
76.8
–
47.0
44.6
43.6
87.9
54.1
73.7
53.4
67.7
75.8
58.1
65.0
87.0
89.1
103.3
113.1
87.1
76.6
70.5
91.8
89.1
86.2
88.0
78.2
110.0
89.8
86.6
94.4
118.7
107.8
106.0
105.2
80.6
105.2
81.1
103.0
94.7
88.4
92.1
88.5
95.6
96.6
82.6
94.5
89.4
92.5
103.9
96.7
85.5
114.8
85.3
103.8
93.7
83.1
91.7
87.8
90.4
94.3
85.5
90.5
84.0
94.3
102.0
97.4
93.1
120.2
98.4
104.6
104.7
96.2
101.0
103.2
90.2
105.6
100.8
98.0
90.0
100.5
98.5
96.5
95.7
89.7
81.9
94.5
81.7
84.0
85.2
83.5
93.0
88.1
95.0
87.6
84.7
107.4
97.4
90.4
80.4
84.1
54.1
80.2
80.8
85.5
80.7
83.2
90.8
87.8
96.8
85.1
79.8
116.0
96.4
88.4
84.5
94.3
57.6
79.8
79.2
82.7
76.5
79.6
88.2
83.8
95.7
79.9
72.5
114.3
97.7
86.1
75.0
93.9
59.6
79.9
67.4
70.3
65.2
67.8
74.6
71.2
86.9
69.6
63.6
106.4
99.0
86.7
69.2
86.1
54.2
75.1
68.1
71.5
63.7
66.1
74.5
71.9
87.8
68.6
60.8
101.9
96.0
86.9
72.9
81.2
56.2
65.4
72.7
78.2
68.4
70.8
81.9
77.9
101.9
74.2
61.4
109.5
96.6
100.9
89.3
80.3
57.9
64.6
87.4
96.1
80.2
83.7
104.0
95.0
110.1
91.1
71.5
119.3
92.9
109.9
104.7
81.3
61.7
64.5
93.9
103.7
88.5
89.2
116.5
101.8
112.7
101.6
72.9
132.7
92.6
119.3
114.6
75.6
69.3
64.7
94.3
109.5
87.8
87.1
118.8
98.9
119.4
104.5
69.8
132.9
94.4
130.0
119.3
69.2
73.3
60.8
95.1
108.3
89.3
85.5
122.7
99.5
123.2
107.8
68.7
137.4
93.9
139.5
136.6
66.3
74.6
56.3
104.3
119.5
97.8
90.5
137.5
108.7
141.6
118.9
77.0
149.1
NOTE: Data for Germany for years before 1993 are for the former West Germany. Data for 1993 onward are for unified Germany. Dash indicates data not available.
130
Monthly Labor Review • September 2008
54. Occupational injury and illness rates by industry, 1 United States
Industry and type of case
Incidence rates per 100 full-time workers 3
2
1989
1
1990
1991
1992
1993
4
1994
4
1995
4
1996
4
1997
4
1998
4
1999
4
2000
4
2001
4
5
PRIVATE SECTOR
8.6
4.0
78.7
8.8
4.1
84.0
8.4
3.9
86.5
8.9
3.9
93.8
8.5
3.8
–
8.4
3.8
–
8.1
3.6
–
7.4
3.4
–
7.1
3.3
–
6.7
3.1
–
6.3
3.0
–
6.1
3.0
–
5.7
2.8
–
Agriculture, forestry, and fishing
Total cases ............................………………………….
Lost workday cases.....................................................
Lost workdays........………...........................................
10.9
5.7
100.9
11.6
5.9
112.2
10.8
5.4
108.3
11.6
5.4
126.9
11.2
5.0
–
10.0
4.7
–
9.7
4.3
–
8.7
3.9
–
8.4
4.1
–
7.9
3.9
–
7.3
3.4
–
7.1
3.6
–
7.3
3.6
–
Mining
Total cases ............................………………………….
Lost workday cases.....................................................
Lost workdays........………...........................................
8.5
4.8
137.2
8.3
5.0
119.5
7.4
4.5
129.6
7.3
4.1
204.7
6.8
3.9
–
6.3
3.9
–
6.2
3.9
–
5.4
3.2
–
5.9
3.7
–
4.9
2.9
–
4.4
2.7
–
4.7
3.0
–
4.0
2.4
–
Construction
Total cases ............................………………………….
Lost workday cases.....................................................
Lost workdays........………...........................................
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
–
9.9
4.5
–
9.5
4.4
–
8.8
4.0
–
8.6
4.2
–
8.3
4.1
–
7.9
4.0
–
General building contractors:
Total cases ............................………………………….
Lost workday cases.....................................................
Lost workdays........………...........................................
13.9
6.5
137.3
13.4
6.4
137.6
12.0
5.5
132.0
12.2
5.4
142.7
11.5
5.1
–
10.9
5.1
–
9.8
4.4
–
9.0
4.0
–
8.5
3.7
–
8.4
3.9
–
8.0
3.7
–
7.8
3.9
–
6.9
3.5
–
Heavy construction, except building:
Total cases ............................………………………….
Lost workday cases.....................................................
Lost workdays........………...........................................
13.8
6.5
147.1
13.8
6.3
144.6
12.8
6.0
160.1
12.1
5.4
165.8
11.1
5.1
–
10.2
5.0
–
9.9
4.8
–
9.0
4.3
–
8.7
4.3
–
8.2
4.1
–
7.8
3.8
–
7.6
3.7
–
7.8
4.0
–
Special trades contractors:
Total cases ............................………………………….
Lost workday cases.....................................................
Lost workdays........………...........................................
14.6
6.9
144.9
14.7
6.9
153.1
13.5
6.3
151.3
13.8
6.1
168.3
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
–
Manufacturing
Total cases ............................………………………….
Lost workday cases.....................................................
13.1
5.8
13.2
5.8
12.7
5.6
12.5
5.4
12.1
5.3
12.2
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
Lost workdays........………...........................................
113.0
120.7
121.5
124.6
–
–
–
–
–
–
–
–
–
Total cases ............................………………………….
Lost workday cases.....................................................
Lost workdays........………...........................................
14.1
6.0
116.5
14.2
6.0
123.3
13.6
5.7
122.9
13.4
5.5
126.7
13.1
5.4
–
13.5
5.7
–
12.8
5.6
–
11.6
5.1
–
11.3
5.1
–
10.7
5.0
–
10.1
4.8
–
–
–
–
8.8
4.3
–
Lumber and wood products:
Total cases ............................…………………………
Lost workday cases..................................................
Lost workdays........………........................................
18.4
9.4
177.5
18.1
8.8
172.5
16.8
8.3
172.0
16.3
7.6
165.8
15.9
7.6
–
15.7
7.7
–
14.9
7.0
–
14.2
6.8
–
13.5
6.5
–
13.2
6.8
–
13.0
6.7
–
12.1
6.1
–
10.6
5.5
–
Furniture and fixtures:
Total cases ............................…………………………
Lost workday cases..................................................
Lost workdays........………........................................
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
5.7
–
11.5
5.9
–
11.2
5.9
–
11.0
5.7
–
Stone, clay, and glass products:
Total cases ............................…………………………
Lost workday cases..................................................
Lost workdays........………........................................
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
5.5
–
10.1
5.1
–
Primary metal industries:
Total cases ............................…………………………
Lost workday cases..................................................
Lost workdays........………........................................
18.7
8.1
168.3
19.0
8.1
180.2
17.7
7.4
169.1
17.5
7.1
175.5
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
6.3
–
12.6
6.3
–
10.7
5.3
11.1
Fabricated metal products:
Total cases ............................…………………………
Lost workday cases..................................................
Lost workdays........………........................................
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
–
Industrial machinery and equipment:
Total cases ............................…………………………
Lost workday cases..................................................
Lost workdays........………........................................
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
–
Electronic and other electrical equipment:
Total cases ............................…………………………
Lost workday cases..................................................
Lost workdays........………........................................
9.1
3.9
77.5
9.1
3.8
79.4
8.6
3.7
83.0
8.4
3.6
81.2
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
2.8
–
5.7
2.9
–
5.0
2.5
–
Transportation equipment:
Total cases ............................…………………………
Lost workday cases..................................................
Lost workdays........………........................................
17.7
6.8
138.6
17.8
6.9
153.7
18.3
7.0
166.1
18.7
7.1
186.6
18.5
7.1
–
19.6
7.8
–
18.6
7.9
–
16.3
7.0
–
15.4
6.6
–
14.6
6.6
–
13.7
6.4
–
13.7
6.3
–
12.6
6.0
–
Instruments and related products:
Total cases ............................…………………………
Lost workday cases..................................................
Lost workdays........………........................................
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
–
Miscellaneous manufacturing industries:
Total cases ............................…………………………
Lost workday cases..................................................
Lost workdays........………........................................
11.1
5.1
97.6
11.3
5.1
113.1
11.3
5.1
104.0
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
–
Total cases ............................………………………….
Lost workday cases.....................................................
Lost workdays........………...........................................
5
Durable goods:
See footnotes at end of table.
Monthly Labor Review • September 2008 131
Current Labor Statistics: Injury and Illness Data
54. Continued—Occupational injury and illness rates by industry,1 United States
Industry and type of case2
Incidence rates per 100 workers 3
1989
1
1990
1991
1993 4 1994 4 1995 4 1996 4 1997 4 1998 4 1999 4 2000 4 2001 4
1992
Nondurable goods:
Total cases ............................…………………………..…
Lost workday cases.........................................................
Lost workdays........………...............................................
11.6
5.5
107.8
11.7
5.6
116.9
11.5
5.5
119.7
11.3
5.3
121.8
10.7
5.0
–
10.5
5.1
–
9.9
4.9
–
9.2
4.6
–
8.8
4.4
–
8.2
4.3
7.8
4.2
–
7.8
4.2
–
6.8
3.8
–
Food and kindred products:
Total cases ............................…………………………..
Lost workday cases......................................................
Lost workdays........………............................................
18.5
9.3
174.7
20.0
9.9
202.6
19.5
9.9
207.2
18.8
9.5
211.9
17.6
8.9
–
17.1
9.2
–
16.3
8.7
–
15.0
8.0
–
14.5
8.0
–
13.6
7.5
12.7
7.3
–
12.4
7.3
–
10.9
6.3
–
Tobacco products:
Total cases ............................…………………………..
Lost workday cases......................................................
Lost workdays........………............................................
8.7
3.4
64.2
7.7
3.2
62.3
6.4
2.8
52.0
6.0
2.4
42.9
5.8
2.3
–
5.3
2.4
–
5.6
2.6
–
6.7
2.8
–
5.9
2.7
–
6.4
3.4
-
5.5
2.2
–
6.2
3.1
–
6.7
4.2
–
Textile mill products:
Total cases ............................…………………………..
Lost workday cases......................................................
Lost workdays........………............................................
10.3
4.2
81.4
9.6
4.0
85.1
10.1
4.4
88.3
9.9
4.2
87.1
9.7
4.1
–
8.7
4.0
–
8.2
4.1
–
7.8
3.6
–
6.7
3.1
–
7.4
3.4
–
6.4
3.2
–
6.0
3.2
–
5.2
2.7
–
Apparel and other textile products:
Total cases ............................…………………………..
Lost workday cases......................................................
Lost workdays........………............................................
8.6
3.8
80.5
8.8
3.9
92.1
9.2
4.2
99.9
9.5
4.0
104.6
9.0
3.8
–
8.9
3.9
–
8.2
3.6
–
7.4
3.3
–
7.0
3.1
–
6.2
2.6
-
5.8
2.8
–
6.1
3.0
–
5.0
2.4
–
Paper and allied products:
Total cases ............................…………………………..
Lost workday cases......................................................
Lost workdays........………............................................
12.7
5.8
132.9
12.1
5.5
124.8
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
3.8
–
7.3
3.7
–
7.1
3.7
–
7.0
3.7
–
6.5
3.4
–
6.0
3.2
–
Printing and publishing:
Total cases ............................…………………………..
Lost workday cases......................................................
Lost workdays........………............................................
6.9
3.3
63.8
6.9
3.3
69.8
6.7
3.2
74.5
7.3
3.2
74.8
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
–
5.1
2.6
–
4.6
2.4
–
Chemicals and allied products:
Total cases ............................…………………………..
Lost workday cases......................................................
Lost workdays........………............................................
7.0
3.2
63.4
6.5
3.1
61.6
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
–
4.2
2.2
–
4.0
2.1
–
Petroleum and coal products:
Total cases ............................…………………………..
Lost workday cases......................................................
Lost workdays........………............................................
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
–
3.7
1.9
–
2.9
1.4
–
Rubber and miscellaneous plastics products:
Total cases ............................…………………………..
Lost workday cases......................................................
Lost workdays........………............................................
16.2
8.0
147.2
16.2
7.8
151.3
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
5.8
–
10.1
5.5
–
10.7
5.8
–
8.7
4.8
–
Leather and leather products:
Total cases ............................…………………………..
Lost workday cases......................................................
Lost workdays........………............................................
13.6
6.5
130.4
12.1
5.9
152.3
12.5
5.9
140.8
12.1
5.4
128.5
12.1
5.5
–
12.0
5.3
–
11.4
4.8
–
10.7
4.5
–
10.6
4.3
–
9.8
4.5
–
10.3
5.0
–
9.0
4.3
–
8.7
4.4
–
Transportation and public utilities
Total cases ............................…………………………..…
Lost workday cases.........................................................
Lost workdays........………...............................................
9.2
5.3
121.5
9.6
5.5
134.1
9.3
5.4
140.0
9.1
5.1
144.0
9.5
5.4
–
9.3
5.5
–
9.1
5.2
–
8.7
5.1
–
8.2
4.8
–
7.3
4.3
–
7.3
4.4
–
6.9
4.3
–
6.9
4.3
–
Wholesale and retail trade
Total cases ............................…………………………..…
Lost workday cases.........................................................
Lost workdays........………...............................................
8.0
3.6
63.5
7.9
3.5
65.6
7.6
3.4
72.0
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
–
Wholesale trade:
Total cases ............................…………………………..…
Lost workday cases.........................................................
Lost workdays........………...............................................
7.7
4.0
71.9
7.4
3.7
71.5
7.2
3.7
79.2
7.6
3.6
82.4
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
–
5.3
2.8
–
Retail trade:
Total cases ............................…………………………..…
Lost workday cases.........................................................
Lost workdays........………...............................................
8.1
3.4
60.0
8.1
3.4
63.2
7.7
3.3
69.1
8.7
3.4
79.2
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
–
Finance, insurance, and real estate
Total cases ............................…………………………..…
Lost workday cases.........................................................
Lost workdays........………...............................................
2.0
.9
17.6
2.4
1.1
27.3
2.4
1.1
24.1
2.9
1.2
32.9
2.9
1.2
–
2.7
1.1
–
2.6
1.0
–
2.4
.9
–
2.2
.9
–
.7
.5
–
1.8
.8
–
1.9
.8
–
1.8
.7
–
Services
Total cases ............................…………………………..…
Lost workday cases.........................................................
Lost workdays........………...............................................
5.5
2.7
51.2
6.0
2.8
56.4
6.2
2.8
60.0
7.1
3.0
68.6
6.7
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
–
-
-
1
Data for 1989 and subsequent years are based on the Standard Industrial Classification Manual, 1987 Edition. For this reason, they are not strictly comparable with data
for the years 1985–88, which were based on the Standard Industrial Classification
Manual, 1972 Edition, 1977 Supplement.
N = number of injuries and illnesses or lost workdays;
EH = total hours worked by all employees during the calendar year; and
200,000 = base for 100 full-time equivalent workers (working 40 hours per week, 50 weeks
per year).
2
Beginning with the 1992 survey, the annual survey measures only nonfatal injuries and
illnesses, while past surveys covered both fatal and nonfatal incidents. To better address
fatalities, a basic element of workplace safety, BLS implemented the Census of Fatal
Occupational Injuries.
4
Beginning with the 1993 survey, lost workday estimates will not be generated. As of 1992,
BLS began generating percent distributions and the median number of days away from work
by industry and for groups of workers sustaining similar work disabilities.
5
Excludes farms with fewer than 11 employees since 1976.
3
The incidence rates represent the number of injuries and illnesses or lost workdays per
100 full-time workers and were calculated as (N/EH) X 200,000, where:
132
Monthly Labor Review • September 2008
NOTE: Dash indicates data not available.
55. Fatal occupational injuries by event or exposure, 1996-2005
20053
1996-2000
(average)
2001-2005
(average)2
All events ...............................................................
6,094
5,704
5,734
100
Transportation incidents ................................................
Highway ........................................................................
Collision between vehicles, mobile equipment .........
Moving in same direction ......................................
Moving in opposite directions, oncoming ..............
Moving in intersection ...........................................
Vehicle struck stationary object or equipment on
side of road .............................................................
Noncollision ...............................................................
Jack-knifed or overturned--no collision .................
Nonhighway (farm, industrial premises) ........................
Noncollision accident ................................................
Overturned ............................................................
Worker struck by vehicle, mobile equipment ................
Worker struck by vehicle, mobile equipment in
roadway ..................................................................
Worker struck by vehicle, mobile equipment in
parking lot or non-road area ....................................
Water vehicle ................................................................
Aircraft ...........................................................................
2,608
1,408
685
117
247
151
2,451
1,394
686
151
254
137
2,493
1,437
718
175
265
134
43
25
13
3
5
2
264
372
298
378
321
212
376
310
335
274
335
277
175
369
345
318
273
340
281
182
391
6
6
5
6
5
3
7
129
136
140
2
171
105
263
166
82
206
176
88
149
3
2
3
Assaults and violent acts ...............................................
Homicides .....................................................................
Shooting ....................................................................
Suicide, self-inflicted injury ............................................
1,015
766
617
216
850
602
465
207
792
567
441
180
14
10
8
3
Contact with objects and equipment ............................
Struck by object ............................................................
Struck by falling object ..............................................
Struck by rolling, sliding objects on floor or ground
level .........................................................................
Caught in or compressed by equipment or objects .......
Caught in running equipment or machinery ..............
Caught in or crushed in collapsing materials ................
1,005
567
364
952
560
345
1,005
607
385
18
11
7
77
293
157
128
89
256
128
118
94
278
121
109
2
5
2
2
Falls ..................................................................................
Fall to lower level ..........................................................
Fall from ladder .........................................................
Fall from roof .............................................................
Fall to lower level, n.e.c. ...........................................
714
636
106
153
117
763
669
125
154
123
770
664
129
160
117
13
12
2
3
2
Exposure to harmful substances or environments .....
Contact with electric current ..........................................
Contact with overhead power lines ...........................
Exposure to caustic, noxious, or allergenic substances
Oxygen deficiency .........................................................
535
290
132
112
92
498
265
118
114
74
501
251
112
136
59
9
4
2
2
1
Fires and explosions ......................................................
Fires--unintended or uncontrolled .................................
Explosion ......................................................................
196
103
92
174
95
78
159
93
65
3
2
1
Event or exposure1
Number
Percent
1 Based on the 1992 BLS Occupational Injury and Illness Classification Manual.
2 Excludes fatalities from the Sept. 11, 2001, terrorist attacks.
3 The BLS news release of August 10, 2006, reported a total of 5,702 fatal work injuries for calendar year
2005. Since then, an additional 32 job-related fatalities were identified, bringing the total job-related fatality
count for 2005 to 5,734.
NOTE: Totals for all years are revised and final. Totals for major categories may include subcategories not
shown separately. Dashes indicate no data reported or data that do not meet publication criteria. N.e.c. means
"not elsewhere classified."
SOURCE: U.S. Department of Labor, Bureau of Labor Statistics, in cooperation with State, New York City,
District of Columbia, and Federal agencies, Census of Fatal Occupational Injuries.
Monthly Labor Review • September 2008 133
COMPENSATION AND WORKING CONDITIONS
U.S. BUREAU OF LABOR STATISTICS
BLS Introduces New Employment Cost Indexes for 14 Metropolitan Areas
by Albert E. Schwenk
Bureau of Labor Statistics
Originally Posted: September 24, 2008
This article presents a first look at new estimates from the National Compensation Survey (NCS): Employment Cost Index
(ECI) 12-month change in total compensation and in wages and salaries for private industry for 14 selected metropolitan
areas. The article also provides a description of how the areas were selected and an overview of what the data show.
For the year ended June 2008, BLS reported that across the Nation the cost of compensation (wages, salaries, and benefits)
had risen 3.0 percent in private industry.1 Among 14 selected metropolitan areas, however, the increases ranged from 1.5
percent in Detroit to 4.4 percent in Philadelphia.
The ECI is a Principal Federal Economic Indicator of the economy of the United States.2 National estimates on wage and
salary trends in private industry were developed in the early 1970s to provide an index of the change in the cost of labor as a
factor of production.3 In an effort to make the index more useful, BLS increased the number of published series over time,
broadening the scope of ECI national estimates in the early 1980s to include State and local government and all civilian
workers as well as estimates of benefits and total compensation.4 The ECI also expanded its industry detail in serviceproducing industries such as hospitals and nursing homes in the 1980s. In addition, in March 2006, when the ECI switched to
the North American Industry Classification System (NAICS) and the Standard Occupational Classification (SOC) system,
BLS began publishing employment cost data for new industry and occupational categories.5
From the beginning, BLS has sought to provide ECI data users with greater geographic detail than the national estimates.
Data for the four geographic regions defined by the Census Bureau--Northeast, South, Midwest, and West--have been
published since the 1970s. In 2006, at the same time that it switched to NAICS and SOC, the ECI expanded geographic
detail to include nine census divisions within the census regions.6 Still, users of ECI data requested even greater geographic
detail. In response, BLS has explored the possibility of publishing measures of change in labor costs for specific Metropolitan
Statistical Areas (MSAs) or Consolidated Statistical Areas (CSAs).7
Selection Of Areas To Publish
As a starting point, using employment data from the 2000 Census of Population, the NCS identified the largest metropolitan
areas in the United States. The next step in the selection process was to determine whether data for each of these areas met
BLS publication standards, based on a review of sample sizes, standard errors,8 and historical data on rates of change in
total compensation and in wages and salaries.
After this review, it was determined that estimates for the 12-month changes in compensation and in wages and salaries
would be published for the following 14 areas: Atlanta-Sandy Springs-Gainesville, GA-AL CSA; Boston-WorcesterManchester, MA-NH CSA; Chicago-Naperville-Michigan City, IL-IN-WI CSA; Dallas-Forth Worth, TX CSA; Detroit-WarrenFlint, MI CSA; Houston-Baytown-Huntsville, TX CSA; Los Angeles-Long Beach-Riverside, CA CSA; Miami-Fort LauderdalePompano Beach, FL MSA; Minneapolis-St. Paul-St. Cloud, MN-WI CSA; New York-Newark-Bridgeport, NY-NJ-CT-PA CSA;
Philadelphia-Camden-Vineland, PA-NJ-DE-MD CSA; Phoenix-Mesa-Scottsdale, AZ MSA; San Jose-San Francisco-Oakland,
CA CSA; and Washington-Baltimore-Northern Virginia, DC-MD-VA-WV CSA.9 (In this article, shortened titles are used to
refer to particular metropolitan areas, but in all cases the full CSA or MSA is intended.)
Weighting Data For ECI Locality Estimates
The estimates of locality ECI 12-month changes were constructed in essentially the same manner as are the national ECI
series of 12-month changes.10 Like the national series, the locality ECI series use fixed employment weights. The fixed
industry-occupation employment weights used to construct each localitys 12-month change estimates were based on
Page 1
COMPENSATION AND WORKING CONDITIONS
U.S. BUREAU OF LABOR STATISTICS
employment for the locality, rather than on national total employment. Because the relative weight of each industryoccupation cell used to estimate rates of change in total compensation and wages and salaries differs across areas, variation
among localities in rates of wage or compensation change reflects both differences in industry and occupation composition of
the work force and differences in rates of change for a fixed market basket of labor services.11
Review Of The Estimates
Table 1 shows 12-month changes in total compensation costs by quarter for the United States as a whole and for the
selected 14 metropolitan areas, as well as the associated standard errors for total compensation; table 2 shows the same for
the cost of wages and salaries.
Table 1. Employment Cost Index, private industry workers, compensation, United States and selected metropolitan
areas (Not seasonally adjusted)
Compensation
Metropolitan area and year
12-month percent changes for period
ended-Mar.
June
Sep.
12-month standard errors for period ended--
Dec.
Mar.
June
Sep.
Dec.
United States
2006
2.6
2.8
3.0
3.2
(-)
(-)
(-)
0.2
2007
3.2
3.1
3.1
3.0
0.2
0.2
0.2
0.2
2008
3.2
3.0
(-)
(-)
0.2
0.2
(-)
(-)
Atlanta-Sandy Springs-Gainesville, GA-AL CSA
2006
(-)
(-)
(-)
2.5
(-)
(-)
(-)
0.6
2007
3.7
4.0
3.6
3.3
0.5
0.3
0.3
0.3
3.1
1.9
(-)
(-)
0.3
0.5
(-)
(-)
2008
Boston-Worcester-Manchester, MA-NH CSA
2006
(-)
(-)
(-)
3.6
(-)
(-)
(-)
0.8
2007
3.5
3.5
3.8
3.2
0.7
0.6
0.6
0.6
2008
3.0
2.5
(-)
(-)
0.7
0.2
(-)
(-)
Chicago-Naperville-Michigan City, IL-IN-WI CSA
2006
(-)
(-)
(-)
3.6
(-)
(-)
(-)
0.6
2007
2.9
2.6
2.3
2.5
0.5
0.6
0.5
0.5
2008
2.9
3.4
(-)
(-)
0.5
0.3
(-)
(-)
Dallas-Fort Worth, TX CSA
2006
(-)
(-)
(-)
3.1
(-)
(-)
(-)
0.7
2007
3.3
2.6
2.3
2.6
0.6
0.5
0.2
0.4
2008
3.3
2.7
(-)
(-)
0.4
0.4
(-)
(-)
2006
(-)
(-)
(-)
1.8
(-)
(-)
(-)
0.5
2007
2.0
1.7
1.2
0.9
0.4
0.5
0.4
0.4
2008
2.2
1.5
(-)
(-)
0.3
0.3
(-)
(-)
Detroit-Warren-Flint, MI CSA
Houston-Baytown-Huntsville, TX CSA
2006
(-)
(-)
(-)
3.8
(-)
(-)
(-)
0.3
2007
3.1
3.0
3.3
2.6
0.3
0.3
0.7
0.7
2008
2.9
2.4
(-)
(-)
0.5
0.2
(-)
(-)
Dashes indicate no data available.
Page 2
COMPENSATION AND WORKING CONDITIONS
U.S. BUREAU OF LABOR STATISTICS
Compensation
Metropolitan area and year
12-month percent changes for period ended-Mar.
June
Sep.
12-month standard errors for period ended--
Dec.
Mar.
June
Sep.
Dec.
Los Angeles-Long Beach-Riverside, CA CSA
2006
(-)
(-)
(-)
3.1
(-)
(-)
(-)
0.4
2007
3.8
3.8
3.9
3.6
0.3
0.3
0.5
0.6
2008
3.5
2.6
(-)
(-)
0.7
0.6
(-)
(-)
2006
(-)
(-)
(-)
5.7
(-)
(-)
(-)
0.3
2007
5.8
5.5
3.7
3.8
0.3
0.6
0.4
0.6
2008
4.4
3.2
(-)
(-)
0.3
0.5
(-)
(-)
Miami-Fort Lauderdale-Pompano Beach, FL MSA
Minneapolis-St.Paul-St.Cloud, MN-WI CSA
2006
(-)
(-)
(-)
1.0
(-)
(-)
(-)
0.2
2007
2.5
2.1
2.3
2.3
0.3
0.3
0.3
0.3
2008
2.5
2.5
(-)
(-)
0.3
0.2
(-)
(-)
2006
(-)
(-)
(-)
3.3
(-)
(-)
(-)
0.4
2007
3.2
3.4
3.4
3.5
0.2
0.3
0.3
0.3
2008
3.2
3.0
(-)
(-)
0.5
0.4
(-)
(-)
New York-Newark-Bridgeport, NY-NJ-CT-PA CSA
Philadelphia-Camden-Vineland, PA-NJ-DE-MD CSA
2006
(-)
(-)
(-)
4.2
(-)
(-)
(-)
0.3
2007
3.0
3.0
3.1
3.0
0.3
0.3
0.4
0.4
2008
3.8
4.4
(-)
(-)
0.3
0.8
(-)
(-)
Phoenix-Mesa-Scottsdale, AZ MSA
2006
(-)
(-)
(-)
1.7
(-)
(-)
(-)
1.5
2007
4.7
3.8
4.0
3.6
1.9
0.5
0.8
1.4
2008
0.5
3.6
(-)
(-)
1.7
0.8
(-)
(-)
San Jose-San Francisco-Oakland, CA CSA
2006
(-)
(-)
(-)
4.6
(-)
(-)
(-)
0.4
2007
4.7
3.2
3.4
3.8
0.4
0.7
0.5
0.7
2008
3.7
3.6
(-)
(-)
0.5
0.3
(-)
(-)
Washington-Baltimore-Northern Virginia, DC-MD-VA-WV CSA
2006
(-)
(-)
(-)
3.8
(-)
(-)
(-)
0.3
2007
3.4
3.6
3.2
2.7
0.3
0.3
0.2
0.3
2008
3.1
2.7
(-)
(-)
0.3
0.5
(-)
(-)
Dashes indicate no data available.
Page 3
COMPENSATION AND WORKING CONDITIONS
U.S. BUREAU OF LABOR STATISTICS
Table 2. Employment Cost Index, private industry workers, wages and salaries, United States and selected
metropolitan areas (Not seasonally adjusted)
Wages and salaries
Metropolitan area and year
12-month percent changes for period ended-Mar.
June
Sep.
12-month standard errors for period ended--
Dec.
Mar.
June
Sep.
Dec.
United States
2006
2.4
2.8
3.0
3.2
(-)
(-)
(-)
0.1
2007
3.6
3.3
3.4
3.3
0.2
0.2
0.2
0.2
2008
3.2
3.1
(-)
(-)
0.2
0.2
(-)
(-)
Atlanta-Sandy Springs-Gainesville, GA-AL CSA
2006
(-)
(-)
(-)
3.0
(-)
(-)
(-)
0.6
2007
3.3
3.6
3.2
2.7
0.5
0.2
0.4
0.5
2008
2.8
2.0
(-)
(-)
0.3
0.4
(-)
(-)
Boston-Worcester-Manchester, MA-NH CSA
2006
(-)
(-)
(-)
4.0
(-)
(-)
(-)
0.4
2007
3.8
3.8
4.0
3.6
0.5
0.6
0.7
0.7
3.2
2.7
(-)
(-)
0.8
0.2
(-)
(-)
2008
Chicago-Naperville-Michigan City, IL-IN-WI CSA
2006
(-)
(-)
(-)
2.6
(-)
(-)
(-)
0.6
2007
3.8
3.0
3.1
3.6
0.5
0.9
0.6
0.7
2008
2.8
3.5
(-)
(-)
0.7
0.2
(-)
(-)
2006
(-)
(-)
(-)
3.3
(-)
(-)
(-)
0.6
2007
3.6
2.9
2.1
2.4
0.3
0.3
0.3
0.4
2008
3.0
2.5
(-)
(-)
0.4
0.5
(-)
(-)
Dallas-Fort Worth, TX CSA
Detroit-Warren-Flint, MI CSA
2006
(-)
(-)
(-)
1.5
(-)
(-)
(-)
0.5
2007
2.6
2.3
1.9
1.0
0.3
0.2
0.3
0.3
2008
1.6
1.8
(-)
(-)
0.3
0.2
(-)
(-)
2006
(-)
(-)
(-)
3.8
(-)
(-)
(-)
0.4
2007
3.3
3.6
4.2
3.2
0.5
0.3
0.7
0.4
3.6
2.6
(-)
(-)
0.4
0.4
(-)
(-)
Houston-Baytown-Huntsville, TX CSA
2008
Los Angeles-Long Beach-Riverside, CA CSA
2006
(-)
(-)
(-)
3.8
(-)
(-)
(-)
0.3
2007
4.2
3.6
4.3
3.7
0.2
0.3
0.5
0.7
2008
3.0
2.5
(-)
(-)
0.9
0.8
(-)
(-)
Miami-Fort Lauderdale-Pompano Beach, FL MSA
2006
(-)
(-)
(-)
5.6
(-)
(-)
(-)
0.4
2007
6.0
5.6
3.5
3.1
0.4
0.7
0.5
0.5
3.8
4.6
(-)
(-)
0.2
0.6
(-)
(-)
(-)
(-)
(-)
0.2
2008
Minneapolis-St.Paul-St.Cloud, MN-WI CSA
2006
(-)
(-)
(-)
Dashes indicate no data available.
Page 4
1.1
COMPENSATION AND WORKING CONDITIONS
U.S. BUREAU OF LABOR STATISTICS
Wages and salaries
Metropolitan area and year
12-month percent changes for period ended-Mar.
2007
3.4
2008
1.7
June
Sep.
Dec.
12-month standard errors for period ended-Mar.
June
Sep.
Dec.
2.5
2.3
2.1
0.4
0.3
0.2
0.3
2.3
(-)
(-)
0.3
0.3
(-)
(-)
New York-Newark-Bridgeport, NY-NJ-CT-PA CSA
2006
(-)
(-)
(-)
3.2
(-)
(-)
(-)
0.5
2007
3.2
3.3
3.1
3.5
0.2
0.4
0.4
0.5
2008
3.0
3.0
(-)
(-)
0.4
0.3
(-)
(-)
Philadelphia-Camden-Vineland, PA-NJ-DE-MD CSA
2006
(-)
(-)
(-)
3.8
(-)
(-)
(-)
0.4
2007
3.5
3.6
3.8
3.5
0.3
0.3
0.4
0.4
2008
3.7
4.6
(-)
(-)
0.3
1.0
(-)
(-)
Phoenix-Mesa-Scottsdale, AZ MSA
2006
(-)
(-)
(-)
1.5
(-)
(-)
(-)
1.7
2007
5.2
3.6
4.2
3.6
2.2
0.5
1.1
1.9
2008
-0.2
3.7
(-)
(-)
2.1
0.8
(-)
(-)
San Jose-San Francisco-Oakland, CA CSA
2006
(-)
(-)
(-)
4.2
(-)
(-)
(-)
0.7
2007
5.1
3.3
3.9
4.5
0.5
0.8
0.5
0.7
2008
3.5
3.6
(-)
(-)
0.5
0.4
(-)
(-)
2006
(-)
(-)
(-)
3.9
(-)
(-)
(-)
0.3
2007
3.4
3.8
3.5
2.8
0.3
0.3
0.2
0.2
2008
3.1
2.7
(-)
(-)
0.3
0.5
(-)
(-)
Washington-Baltimore-Northern Virginia, DC-MD-VA-WV CSA
Dashes indicate no data available.
Several things are evident from these two tables. First, for most areas, both total compensation and wage and salary percent
changes vary more from period to period than they do for the Nation as a whole. Second, the standard errors for the Nation
as a whole are consistently lower than for any particular area. The lower standard errors probably reflect the larger sample
size. Those smaller standard errors may also help explain the smaller variability from period to period in the rates of change
for the Nation as a whole. By area, the largest standard errors for both total compensation and wages and salaries are from
the Phoenix metropolitan area, due largely to the impact of incentive workers in the area--when such workers are excluded,
the standard errors drop sharply. (Incentive workers are those whose wages are at least partially based on productivity
payments such as piece rates, commissions, and production bonuses.)
Table 3 presents average annual percent changes in total compensation costs and in wages and salaries over the entire
period from December 2005 to June 2008, sorted in descending order of the size of the compensation cost change.
Table 3. Average annual percent changes in total compensation costs and in wages and salaries, December 2005-June
2008
Metropolitan area
Total compensation costs
Wages and salaries
Miami-Fort Lauderdale-Pompano Beach, FL
4.5
4.8
San Jose-San Francisco-Oakland, CA
4.2
4.2
Page 5
COMPENSATION AND WORKING CONDITIONS
U.S. BUREAU OF LABOR STATISTICS
Metropolitan area
Total compensation costs
Wages and salaries
Philadelphia-Camden-Vineland, PA-NJ-DE-MD
3.8
3.8
Washington-Baltimore-Northern Virginia, DC-MD-VA-WV
3.4
3.4
New York-Newark-Bridgeport, NY-NJ-CT-PA
3.4
3.3
Phoenix-Mesa-Scottsdale, AZ
3.2
3.0
Chicago-Naperville-Michigan City, IL-IN-WI
3.1
3.1
Houston-Baytown-Huntsville, TX
3.1
3.4
Los Angeles-Long Beach-Riverside, CA
3.1
3.4
United States
3.1
3.3
Boston-Worcester-Manchester, MA-NH
3.1
3.4
Dallas-Forth Worth, TX
2.8
2.8
Atlanta-Sandy Springs-Gainesville, GA-AL
2.6
2.7
Minneapolis-St. Paul-St. Cloud, MN-WI
2.0
2.0
Detroit-Warren-Flint, MI
1.5
1.7
The magnitude of the changes during particular time periods depends on a number of factors, including initial total
compensation cost levels, industry and occupational composition of the work force, and economic conditions. As table 3
shows, the largest average annual percent increases in total compensation costs were in Miami, San Jose-San Francisco,
and Philadelphia. This relationship holds for wages and salaries as well as for total compensation costs. In contrast, the
smallest increases were in Dallas, Atlanta, Minneapolis, and Detroit. These areas also had the smallest wage and salary
increases.
Table 4 shows percent changes in total compensation costs and in wages and salaries for the United States as a whole and
for 14 metropolitan areas for three periods: December 2005 to December 2006, December 2006 to December 2007, and
December 2007 to June 2008.
Table 4. Measures of change in total compensation cost and wage and salary changes over selected time periods, for
the United States and by geographic region, industry division, and locality.
Percent change over selected time periods
Area
Total compensation cost
Wages and salaries
Dec. 2005Dec. 2006
Dec. 2006Dec. 2007
Dec. 2007June 2008
Dec. 2005Dec. 2006
Dec. 2006Dec. 2007
Dec. 2007June 2008
United States
3.2
3.0
1.6
3.2
3.3
1.7
Northeast
3.3
3.4
1.2
3.1
3.4
1.5
3.1
2.9
0.9
3.1
3.1
1.2
3.6
3.2
0.9
4.0
3.6
1.0
3.3
3.7
1.4
3.1
3.5
1.6
New York-Newark-Bridgeport,
NY-NJ-CT-PA
3.3
3.5
1.6
3.2
3.5
1.6
Philadelphia-Camden-Vineland,
PA-NJ-DE-MD
4.2
3.0
2.3
3.8
3.5
2.2
3.5
3.1
1.7
3.6
3.3
2.0
3.8
3.4
1.7
3.9
3.5
1.9
New England
Boston-Worcester-Manchester,
MA-NH
Middle Atlantic
South
South Atlantic
Page 6
COMPENSATION AND WORKING CONDITIONS
U.S. BUREAU OF LABOR STATISTICS
Percent change over selected time periods
Area
Total compensation cost
Wages and salaries
Dec. 2005Dec. 2006
Dec. 2006Dec. 2007
Dec. 2007June 2008
Dec. 2005Dec. 2006
Dec. 2006Dec. 2007
Dec. 2007June 2008
Washington-BaltimoreNorthern Virginia, DC-MD-VAWV
3.8
2.7
2.0
3.9
2.8
1.8
Atlanta-Sandy SpringsGainesville, GA-AL
2.5
3.3
0.8
3.0
2.7
0.9
Miami-Fort LauderdalePompano Beach, FL
5.7
3.8
1.6
5.6
3.1
3.3
East South Central
2.3
3.0
1.7
3.1
3.1
1.5
West South Central
3.4
2.6
2.0
3.4
3.1
2.1
Dallas-Forth Worth, TX
3.1
2.6
1.3
3.3
2.4
1.3
Houston-Baytown-Huntsville,
TX
3.8
2.6
1.4
3.8
3.2
1.6
2.8
2.4
1.6
2.6
2.9
1.8
2.8
2.1
1.4
2.5
2.7
1.6
Detroit-Warren-Flint, MI
1.8
0.9
1.2
1.5
1.0
1.7
Chicago-Naperville-Michigan
City, IL-IN-WI
3.6
2.5
1.8
2.6
3.6
1.5
2.7
3.1
2.4
2.7
3.5
2.4
1.0
2.3
1.6
1.1
2.1
1.7
3.0
3.4
1.8
3.2
3.7
1.8
3.1
4.3
1.8
3.2
4.5
1.9
1.7
3.6
2.8
1.5
3.6
2.5
Midwest
East North Central
West North Central
Minneapolis-St. Paul-St. Cloud,
MN-WI
West
Mountain
Phoenix-Mesa-Scottsdale, AZ
Pacific
3.0
3.0
1.9
3.3
3.4
1.7
Los Angeles-Long BeachRiverside, CA
3.1
3.6
1.1
3.8
3.7
1.0
San Jose-San FranciscoOakland, CA
4.6
3.8
2.1
4.2
4.5
1.7
To provide some perspective, table 4 also shows data for the four census regions and nine census divisions.12 The estimates
by census region and census division are of course affected by total compensation cost changes in metropolitan areas
located within those regions and divisions. In general, the larger the proportion of region or division employment accounted
for by an area, the greater impact that area will have on region or division estimates.
As table 4 shows, estimates by area were generally consistent with the estimates for the associated census divisions and
geographic regions. One strong exception to the general pattern is Minneapolis, a metropolitan area in which both wage and
salary and total compensation cost increases were substantially lower than the increase for the West North Central region of
which it is a part.
Information on the future publication of locality employment cost data will be announced in the next ECI news release,
scheduled for 8:30 a.m., EDT, October 31, 2008; the news release will be posted on the Internet at www.bls.gov/ncs/ect.
Albert E. Schwenk
Senior Labor Economist, Division of Compensation Data Estimation, Office of Compensation and Working Conditions, Bureau of
Labor Statistics.
Telephone: (202) 691-6203; E-mail: Schwenk.Albert@bls.gov.
Page 7
COMPENSATION AND WORKING CONDITIONS
U.S. BUREAU OF LABOR STATISTICS
Notes
1 In the ECI, total compensation includes wages and salaries plus the employer cost for 18 individual employee benefits. The following kinds of
benefits are covered by the ECI: paid leave, such as vacations, holidays, sick leave, and personal leave; supplemental pay, such as premium
pay for work in addition to the regular work schedule (overtime, weekends, and holidays), shift differentials, and nonproduction bonuses (such
as year-end, referral, and attendance bonuses); insurance benefits, such as life, health, short-term disability, and long-term disability
insurance; retirement and savings benefits (defined benefit and defined contribution plans); and legally required benefits (Social Security,
Medicare, Federal and State unemployment insurance, and workers compensation).
2 For more on the Principal Federal Economic Indicators, see Federal Register, Sept. 25, 1985, available on the Internet at http://
www.bea.gov/about/pdf/federalregister09251985.pdf.
3 For a more complete description of the ECI, see John W. Ruser, "Employment Cost Index: What is it?," Monthly Labor Review, September
2001, pp. 3-16; available on the Internet at http://www.bls.gov/opub/mlr/2001/09/art1full.pdf.
4 In the National Compensation Survey (NCS), the civilian sector includes workers in private industry and in State and local government. This
excludes Federal government, agricultural, and household workers.
5 For more on the history of the ECI since it was introduced in December 1975, see Fehmida Sleemi, "Employment Cost Index publication
plans," Monthly Labor Review, April 2006, pp. 6-11; available on the Internet at http://www.bls.gov/opub/mlr/2006/04/art2full.pdf.
6 The New England and Middle Atlantic divisions are in the Northeast region; the South Atlantic, East South Central, and West South Central
divisions are in the South region; East North Central and West North Central divisions are in the Midwest region; and the Mountain and Pacific
divisions are in the West. The census divisions comprise the States as follows: the New England division consists of Connecticut, Maine,
Massachusetts, New Hampshire, Rhode Island, and Vermont; the Middle Atlantic division consists of New Jersey, New York, and
Pennsylvania; the South Atlantic division consists of Delaware, the District of Columbia, Florida, Georgia, Maryland, North Carolina, South
Carolina, Virginia, and West Virginia; the East South Central division consists of Alabama, Kentucky, Mississippi, and Tennessee; the West
South Central: division consists of Arkansas, Louisiana, Oklahoma, and Texas; the East North Central division consists of Illinois, Indiana,
Michigan, Ohio, and Wisconsin; the West North Central division consists of Iowa, Kansas, Minnesota, Missouri, Nebraska, North Dakota, and
South Dakota; the Mountain division consists of Arizona, Colorado, Idaho, Montana, Nevada, New Mexico, Utah, and Wyoming; and the
Pacific division consists of Alaska, California, Hawaii, Oregon, and Washington. Metropolitan areas are sometimes located in more than one
State, and some of those States are located in different census divisions, in which case parts of a metropolitan area may be assigned to more
than one census division.
7 Experimental data for these new series were published in Michael K. Lettau and Christopher J. Guciardo, "Experimental Estimates of
Compensation Levels and Trends for Workers in the 15 Largest Metropolitan Areas, 2004-05," Compensation and Working Conditions Online,
September 17, 2007, on the Internet at http://www.bls.gov/opub/cwc/cm20070912ar01p1.htm. The present article presents data only on
compensation cost trends by metropolitan area, not compensation cost levels.
8 For a discussion of standard errors for the ECI, see Karen OConor and William Wong, "Measuring the Precision of the Employment Cost
Index," Monthly Labor Review, March 1989, pp. 29-36, on the Internet at http://www.bls.gov/opub/mlr/1989/03/rpt1full.pdf.
9 Note that some of these areas are Consolidated Statistical Areas (CSAs) and others are Metropolitan Statistical Areas (MSAs). The NCS is
in its second year of a 6-year transition from a sample of areas based on the December 1993 Office of Management and Budget (OMB) area
definitions to a new sample of areas based on the December 2003 area definitions. The NCS is phasing in new metropolitan and micropolitan
areas as defined by OMB and county clusters defined specifically for the NCS; at the same time, some areas under the December 1993 OMB
definitions are being phased out of the sample. For more information on metropolitan area definitions, visit the U.S. Census Bureaus
Metropolitan and Micropolitan Statistical Areas page on the Internet at http://www.census.gov/population/www/metroareas/metrodef.html.
10 For a more complete description of how the estimates for the ECI and other NCS products are computed, see "National Compensation
Measures," BLS Handbook of Methods, ch. 8, on the Internet at http://www.bls.gov/opub/hom/homch8_a.htm.
11 Note that in estimating compensation cost changes by census region and census division, fixed weights are not used. Rather, the fixed
employment weights by industry and occupation are reallocated among the census region and division series each quarter based on the
current ECI sample. For a discussion of the alternative ways of constructing ECIs, see Donald G. Wood, "Estimation procedures for the
Employment Cost Index," Monthly Labor Review, May 1982, pp. 40-42, on the Internet at http://www.bls.gov/opub/mlr/1982/05/rpt3full.pdf.
12 As noted previously, the regions and census divisions are defined by State, while metropolitan areas often span more than one State. For
table 4, the metropolitan areas were organized with the region or census division where most of its employment was found.
U.S. Bureau of Labor Statistics | Division of Information and Marketing Services, PSB Suite 2850, 2 Massachusetts Avenue, NE Washington, DC
20212-0001 | www.bls.gov/OPUB | Telephone: 1-202-691-5200 | Contact Us
Page 8
COMPENSATION AND WORKING CONDITIONS
U.S. BUREAU OF LABOR STATISTICS
Major Union Mergers, Alliances, and Disaffiliations, 1995-2007
by Elizabeth A. Ashack
Bureau of Labor Statistics
Originally Posted: September 24, 2008
U.S. labor unions have made moves toward maintaining their membership base through mergers that are still occurring,
although at a slower pace than in past decades.
Over the period from 1995 to 2007, union membership in the United States declined by about 4.2 percent, from
approximately 16.4 million members to 15.7 million members.1 During the same period, the level of employment rose by
about 17 percent--from 117 million in 1995 to 138 million in 2007.2 As a result, the percentage of U.S. workers represented
by unions has declined, as well as the absolute number of union workers. These declines in membership have prompted
union organizations to consider union mergers as a strategy for improving their bargaining power.3 This article summarizes
the union mergers, alliances, and disaffiliations that have occurred since 1995.4
Types Of Mergers
Over the years, the American Federation of Labor and Congress of Industrial Organizations (AFL-CIO) has encouraged and
actively promoted mergers, stressing that mergers should involve unions representing workers in the same or related
industries in order to build union power and conserve resources, while at the same time benefiting from the increased
economy of scale.5 For this article, union mergers are grouped into three types:
• Mergers occurring among unions already affiliated with the AFL-CIO
• An independent union merging with an AFL-CIO union, and
• Two or more independent unions merging
The AFL-CIO has also maintained that union mergers must be voluntary and subject to the democratic processes of the
unions involved.
Mergers
From 1995 to 2007, there were 31 union mergers in the United States.6 Twenty-two of these mergers were among AFL-CIO
affiliates, 6 occurred between the AFL-CIO and independent unions, and 3 mergers were among two or more independent
unions. In terms of membership, the largest merger occurred in 2005, when the Paper, Allied-Industrial, Chemical and
Energy Workers International Union (PACE) merged with the United Steelworkers of America (USWA). The merger
increased the size of the USWA to 860,000 members, making it the largest industrial union in the United States. In 2004,
another merger of two major unions took place, uniting the Union of Needletrades, Industrial and Textile Employees (UNITE)
and the Hotel Employees and Restaurant Employees International Union (HERE), forming UNITE HERE, which has a
combined membership of 440,000 workers. (See exhibit.)
Disaffiliations And Strategic Alliances
During the 1995-2007 period, there were nine major union disaffiliations (splits) from the AFL-CIO. The first major union
disaffiliation occurred in 2001, when the United Brotherhood of Carpenters (UBC) severed its relationship with the AFL-CIO.
Then, in 2003, the International Union of Journeymen, Horseshoers, and Allied Trades disaffiliated with the AFL-CIO. In
2005, six of the largest unions joined with the United Brotherhood of Carpenters (UBC) in disaffiliating with the AFL-CIO and
created a strategic alliance called the Change to Win Federation.7 The six disaffiliated unions were the United Food and
Commercial Workers Union (UFCW), the International Brotherhood of Teamsters (IBT), the Laborers International Union
(LIUNA), UNITE HERE, the United Farm Workers (UFW), and the Service Employees International Union (SEIU). The
Page 1
COMPENSATION AND WORKING CONDITIONS
U.S. BUREAU OF LABOR STATISTICS
Change to Win Federation states that it is conducting campaigns to increase union membership in each of the affiliated
unions core industries in order to rebuild worker power and unite millions in the growth industries of the 21st century.8
In 2006, the International Union of Operating Engineers (IUOE) disaffiliated from the AFL-CIO's Building and Construction
Trades Department (BCTD) and joined with the following unions to form a strategic alliance called the National Construction
Alliance (NCA)9: the Laborers International Union of North America (LIUNA), the United Brotherhood of Carpenters (UBC),
International Association of Bridge, Structural, Ornamental, and Reinforcing Iron Workers (BSOIW), and the International
Union of Bricklayers and Allied Craftworkers (BAC). The NCA represents more than 1.8 million union workers.
Another notable alliance that formed during the 1995-2007 period is the Merchant Officers Labor Alliance (MOLA), an
agreement reached in 2007 between the International Organization of Masters, Mates, and Pilots and the Marine Engineers
Beneficial Association (MEBA).10 Similarly, in 2005, the Communication Workers of America (CWA) and the International
Brotherhood of Teamsters (IBT) formed a joint alliance of passenger service workers at U.S. Airways.
Union Merger Activity, 1956-2007
The table that follows summarizes the three types of mergers and their yearly distribution for the period from 1956--the year
following the merger of the American Federation of Labor (AFL) and the Congress of Industrial Organizations (CIO)--to 2007.
The table shows that 48 mergers occurred during the two decades following the AFL-CIO amalgamation (1956-75),
averaging about 2.4 a year. The next decade (1976-85) marked the busiest activity period with 45 mergers, or about 4.5 a
year. Merger activity slowed down slightly from 1986 to 1994, with a total of 40 mergers or an average of 4.4 per year. During
the most recent period (1995-2007), there were only 31 mergers or about 2.4 per year. In the recent period, the highest level
of union merger activity occurred in 2003, when there were 6 mergers; the lowest number occurred in 1997, when there was
1 merger.
Table. Union mergers, 1956–2007
Year
Total: 1956-2007
Total mergers
AFL-CIO only
AFL-CIO and independent
Independent only
164
92
57
15
2007
2
0
2
0
2006
2
2
0
0
2005
2
2
0
0
2004
2
2
0
0
2003
6
3
0
3
2002
2
0
2
0
2001
2
1
1
0
2000
4
4
0
0
1999
2
2
0
0
1998
2
2
0
0
1997
1
1
0
0
1996
2
1
1
0
1995
2
2
0
0
1994
5
4
1
0
1993
7
2
3
2
1992
5
3
2
0
1991
5
2
3
0
1990
1
0
1
0
1989
5
4
1
0
Page 2
COMPENSATION AND WORKING CONDITIONS
U.S. BUREAU OF LABOR STATISTICS
Year
Total mergers
AFL-CIO only
AFL-CIO and independent
Independent only
1988
4
3
1
0
1987
3
1
2
0
1986
5
3
2
0
1985
6
2
3
1
1984
5
2
3
0
1983
5
2
3
0
1982
6
3
3
0
1981
3
2
1
0
1980
6
4
1
1
1979
5
3
2
0
1978
3
2
1
0
1977
3
2
0
1
1976
3
2
1
0
1975
3
1
1
1
1974
1
1
0
0
1973
2
1
1
0
1972
5
3
2
0
1971
3
2
1
0
1970
1
0
1
0
1969
6
2
4
0
1968
4
3
0
1
1967
1
0
1
0
1966
1
0
0
1
1965
1
1
0
0
1964
1
0
1
0
1963
0
0
0
0
1962
3
0
1
2
1961
3
2
1
0
1960
4
1
2
1
1959
3
2
1
0
1958
1
1
0
0
1957
2
1
0
1
1956
3
3
0
0
Exhibit. Chronology of major union mergers, 1995-2007
1995
The United Rubber Workers Union (URW) merged into the United Steelworkers of America (USWA). With the merger, the URW
added approximately 94,000 members to the rolls of the USWA, bringing the total membership of the combined union to more than
700,000.
The International Ladies Garment Workers Union and the Amalgamated Clothing and Textile Workers Union merged to become the
Union of Needletrades, Industrial and Textile Employees (UNITE).
1996
The Independent Federation of Flight Attendants representing 5,400 Trans World Airline attendants merged with the 40,000
member Association of Flight Attendants.
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International Chemical Workers Union merged with The United Food and Commercial Workers Union (UFCW) bringing 40,000
members that became the International Chemical Workers Union Council of the UFCW.
1997
The Newspaper Guild merged with the Communication Workers of America (CWA).
1998
The United Paperworkers International Union (UPIU) merged with the Oil, Chemical and Atomic Workers International Union. The
new 330,000-member union is known as the Paper, Allied-Industrial, Chemical and Energy Workers International Union (PACE).
The United Representatives Guild, Inc., and the Production Service and Sales District Council both merged with the United Food
and Commercial Workers Union (UFCW).
1999
The Bakery, Confectionery and Tobacco Workers Union merged with the American Federation of Grain Millers, becoming the
Bakery, Confectionery, Tobacco Workers and Grain Millers Union (BCTGM).
The 11,000-member Laundry and Dry Cleaning International Union affiliated with the Service Employees International Union (SEIU),
which has about 1.3 million members.
2000
The Textile Processors Union affiliated with the United Food and Commercial Workers Union (UFCW).
The local unions representing 7,200 members of the Textile Processors merged with the Union of Needletrades Industrial and
Textile Employees (UNITE).
The International Union of Electronic, Electrical, Salaried, Machine and Furniture Workers (IUE) merged into the Communications
Workers of America (CWA).
The Chicago Truck Drivers Union, with 5,000 members, affiliated with International Brotherhood of Teamsters (IBT).
2001
The Independent Association of Continental Pilots merged with the Air Line Pilots Association (ALPA), with 7,000 Continental pilots
joining 58,000 ALPA pilots.
The United Transportation Union (UTU) merged with the Brotherhood of Locomotive Engineers (BLE). The merged union was
named the United Transportation Union-Brotherhood of Locomotive Engineers (UTU-BLE).
2002
The Independent FedEx Pilots Association, with 4,200 member pilots, merged with the Air Line Pilots Association (ALPA). In 2002,
prior to the merger, ALPA represented 69,200 pilots at 43 different airlines.
The Independent Baton Rouge Oil and Chemical Workers Union (OCAW) merged into the Paper, Allied-Industrial, Chemical and
Energy Workers International Union (PACE).
2003
The American Flint Glass Workers, with 12,500 members, merged with the United Steelworkers of America (USWA).
The 35,000-member United Service Workers (USW) disaffiliated from the Transportation Communications International Union and
merged with the International Union of Journeymen Horseshoers and Allied Trades.
The 10,000-member Independent National Public Employees Union (NPEU) also merged with the International Union of
Journeymen Horseshoers and Allied Trades.
The 10,000-member Independent National Organization of Industrial Trade Unions (NOITU) merged with the International Union of
Journeymen Horseshoers and Allied Trades.
The Association of Flight Attendants merged into the Communications Workers of America (CWA). The CWA previously had
700,000 members, and the AFA added another 33,881 members.
The Brotherhood of Locomotive Engineers (BLE) in the United States and Canada merged with the International Brotherhood of
Teamsters (IBT), bringing rail employees into the Teamsters for the first time.
2004
The Union of Needletrades, Industrial and Textile Employees (UNITE) and the Hotel Employees and Restaurant Employees
International Union (HERE) merged to become UNITE HERE, a new union of 440,000 members.
The Brotherhood of Maintenance of Way Employees merged with International Brotherhood of Teamsters (IBT).
2005
The Graphic Communications International Union merged with International Brotherhood of Teamsters (IBT). The GCIU has 60,000
members in the United States.
The United Steel Workers of America (USWA) and Paper, Allied-Industrial, Chemical and Energy Workers International Union
(PACE) merged to create an 860,000-member union called USWA. The USWA is now the largest industrial union in the United
States.
2006
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The Professional Flight Attendants Association (PFAA) affiliated with the Transport Workers Union (TWU). At the time, PFAA
represented 9,500 Northwest Airlines employees, and TWU represented 135,000 workers.
New York State United Teachers, a 525,000-member affiliate of the American Federation of Teachers (AFT), merged with the
National Educational Association/New York. The new combined union is known as New York State Teachers NEA/AFT, with
560,000 members.
2007
The Independent Steelworkers Union (ISU) merged with the United Steelworkers of America (USWA).
The International Organization of Masters, Mates and Pilots and the Marine Engineers Beneficial Association united to form the
Merchant Officers Labor Alliance.
Elizabeth A. Ashack Economist, Division of Compensation Data Analysis and Planning, Office of Compensation and Working
Conditions, Bureau of Labor Statistics. Telephone: (202) 691-5178; E-mail: Ashack.Elizabeth@bls.gov.
Notes
1 See Union Members in 2007, USDL 08-0092 (U.S. Department of Labor), January 25, 2008, on the Internet at http://www.bls.gov/
news.release/archives/union2_01252008.pdf; and Union Members in 1995, USDL 96-41, February 9, 1996, on the Internet at http://
www.bls.gov/news.release/History/union2_020996.txt.
2 Employment data from the BLS Current Employment Statistics (CES) survey. For more information, visit the CES home page at http://
www.bls.gov/ces/.
3 A Plan to Help Workers Win: Uniting Our Power to Build a Stronger, Growing Labor Movement, Resolution 1 (AFL-CIO Executive Council),
p. 5; available on the Internet at: http://www.aflcio.org/aboutus/thisistheaflcio/convention/2005/upload/res1.pdf (visited April 15, 2008).
4 For more information on union mergers during the previous 10-year period, see Lisa Williamson, "Union mergers: 1985-94 update," Monthly
Labor Review, February 1995, pp. 18-25; available on the Internet at http://www.bls.gov/opub/mlr/1995/02/art2full.pdf.
5 A Plan to Help Workers Win: Uniting Our Power to Build a Stronger, Growing Labor Movement, Resolution 1 (AFL-CIO Executive Council),
p. 1.
6 Daily Labor Report archives, 1995-2007 (Bureau of National Affairs), on the Internet at http://www.bna.com. (visited March 18, 2008).
7 "Uniting for the American Dream," Resolution (Change to Win: The American Dream for Americas Workers), available on the Internet at
http://www.changetowin.org/fileadmin/pdf/convention-2007-resolution-american_dream.pdf (visited August 12, 2008). For more information,
visit the Change to Win website at http://www.changetowin.org/.
8 Ibid., 2007.
9 For more information on the National Construction Alliance (NCA), visit the organizations website at http://www.ncabuild.org/.
10 More information on the formation of the Merchant Officers Labor Alliance can be found in the "Whats New?" section of the International
Organization of Masters, Mates, and Pilots website, on the Internet at www.bridgedeck.org. A copy of the agreement between the Masters,
Mates, and Pilots and the Marine Engineers Beneficial Association can be found at http://www.bridgedeck.org/WhatsNew/MOLA.pdf.
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