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MONTHLY LABOR
REVIEW
Volume 132, Number 10
October 2009
Part-time workers: some key differences between primary and secondary earners
The proportion of part-time workers who are primary wage earners has grown steadily
over the past three decades
H. Luke Shaefer
3
Manhattan’s financial sector and the 2005–07 employment dynamic
16
The parenting of infants: a time-use study
33
Unemployment insurance recipients and nonrecipients in the CPS
44
A first-time look at county-level Business Employment Dynamics data offers new
insights into Manhattan employment growth during the 2005-07 period
Solidelle F. Wasser, Bruce J. Bergman, and Michael L. Dolfman
Data from the American Time Use Survey help to determine whether parents
of infants spend their time differently than parents of older children
Robert Drago
Current Population Survey data show that rates of applications for and receipts of UI
benefits differ substantially by workers’ reasons for unemployment
Wayne Vroman
Departments
Labor month in review
Book review
Précis
Current labor statistics
2
54
56
57
Editor-in-Chief: Michael D. Levi Executive Editor: William Parks II Managing Editor: Terry L. Schau Editors: Brian I. Baker,
Casey P. Homan Book Review Editor: James Titkemeyer Design and Layout: Catherine D. Bowman, Edith W. Peters Cover
Design: Bruce Boyd Contributor: Eugene P. Coyle
Labor Month In Review
The October Review
In its official employment measures,
the Bureau of Labor Statistics usually defines part-time workers to be
those who work less than 35 hours
per week. BLS further classifies parttime workers into those who work
part time on an involuntary basis
and those who work such hours on
a voluntary basis. In this month’s
lead article, Luke Shaefer, assistant professor at the University of
Michigan’s School of Social Work,
analyzes part-time worker data from
the Current Population Survey (CPS)
with a slightly different approach—
by dividing part-time workers into
primary and secondary wage earners.
Primary wage earners, as the name
implies, are the main source of income for themselves and their family, whereas secondary wage earners
depend on another worker for the
majority of their family’s income. The
author finds, on the basis of the estimates presented in the article, that
the proportion of part-time workers accounted for by primary wage
earners has increased slowly during
the past three decades, and that primary wage earners currently make up
more than 36 percent of all part-time
workers. The article also indicates,
perhaps unexpectedly, that most
part-time primary workers choose
part-time work over full-time hours.
One of the most widely known
and anticipated releases from BLS
each month is the findings from the
survey of employer payrolls, which
provide a snapshot of the number of
net job gains or losses for a particular month. It is notable that underlying these job gains and losses is a
dynamic flow of job-change activity.
One Bureau program that measures
this activity is Business Employment
2
Monthly Labor Review • October 2009
Dynamics (BED). BED data capture
the level of “gross” job-change activity that is behind the net change.
In an article by Solidelle F. Wasser,
formerly from the Bureau’s New
York–New Jersey Regional Office,
and Bruce J. Bergman and Michael
L. Dolfman of the same office, BED
data are used, along with data on net
payroll change, to gauge job activity in Manhattan’s financial sector
during the 2005–07 period. The authors find that, just before the recession beginning in December 2007,
Manhattan enjoyed above-average
employment growth. The authors
also conclude that the latest period of relative employment growth
in Manhattan was caused not by a
higher rate of job creation but by a
slower pace of job loss in contracting
and closing establishments.
Do parents of infants spend their
time differently than parents of older
children? Professor Robert Drago of
The Pennsylvania State University
presents us with this question and
uses data from the Bureau’s American Time Use Survey to help provide an answer. The article also includes a look at the trade-offs that
parents make in order to make more
time for their children, and a look
at variations in the amounts of time
spent on childcare, paid work, and
housework among groups of differing socioeconomic status. The author
finds that parents of infants do in
fact exhibit different patterns of time
use compared with parents of older
children. The analysis also indicates
that fathers have become more involved with infant childcare in recent decades, but that infant childcare is still predominantly provided
by the mother. The paper also finds,
not surprisingly to most parents,
that single mothers of infants not
only provide more childcare relative
to single mothers of older children,
but they also spend more of their
time sleeping. This perhaps suggests
that mothers of infants may experience exhaustion because of frequent
interruptions of sleep at night.
This issue’s concluding article is by
Wayne Vroman, an economist with
the Urban Institute. The article uses
data from unemployment insurance
(UI) supplements to the CPS to understand why less than half of all
unemployed workers in the United
States are compensated by the UI
program. The author finds that most
people who do not file for UI benefits
believe that they are not eligible for
them, but the specific reasons they do
not apply for benefits strongly depend
on their reasons for unemployment.
For example, the paper suggests that,
among people whose temporary jobs
have ended, many do not understand
key elements of UI program coverage
and eligibility requirements.
2008 economic stimulus
tax rebates
How did you use your 2008 economic stimulus tax rebate? According to
a report published this month by
the Bureau’s Consumer Expenditure
Survey program, almost half of us
used this rebate mostly to pay down
debt. Another 30 percent reported
mostly spending the rebate, and another 18 percent saved it. Those with
at least one parent and qualifying
child were more than twice as likely
to have used the rebate to pay off
debt then they were to spend it, and
single parents were much less likely
to save the rebate than families with
a husband, a wife, and children. The
report is available online at www.bls.
gov/cex/taxrebate.htm.
Part-Time Workers
Part-time workers: some key differences
between primary and secondary earners
Data from the Annual Social and Economic Supplement to the CPS
indicate that the proportion of part-time workers who are
primary earners has grown over the past three decades; part-time
primary earners face numerous social welfare challenges,
whereas part-time secondary earners have social welfare outcomes
that compare well with those of full-time workers
H. Luke Shaefer
H. Luke Shaefer is an assistant
professor at the School of Social
Work, University of Michigan,
Ann Arbor, MI. E-mail: lshaefer@
umich.edu
T
he Bureau of Labor Statistics
(BLS) considers part-time workers to be those who “usually work
less than 35 hours per week (at all jobs).”1
Both the BLS and labor economists often classify part-time workers into those
who work less than 35 hours per week for
economic, or involuntary, reasons, such as
slack business conditions or inability to
find a full-time job, and those who work
such hours for noneconomic, or voluntary, reasons, such as competing family
obligations. Although there is some cyclical variation in the relative sizes of these
two groups, a large majority of part-time
workers each year reports voluntary reasons for working part time, even during
economic downturns.
Knowing whether workers prefer parttime hours or work them involuntarily is
important for drawing conclusions about
the part-time workforce. For many outcomes, however, it also may prove analytically useful to divide part-time workers
into primary and secondary wage earners.
For primary wage earners, their job is the
main source of income for themselves and
their family, whereas secondary wage earn-
ers depend on another worker for the majority
of their family’s income. This article uses historical and current data from the March 2008
Annual Social and Economic Supplement to
the Current Population Survey (CPS) to divide
the adult (ages 18 to 64 years) part-time workforce into primary and secondary wage earners.
According to estimates presented here, the proportion of part-time workers who are primary
earners has grown slowly, but steadily, over the
past three decades, so that today they make up
more than 36 percent of all part-time workers,
well above the proportion who work part time
involuntarily. Furthermore, part-time primary
earners appear to make up a distinct group that
is not highly correlated with either voluntary or
involuntary part-time work.
Part-time primary earners appear to face
numerous social welfare challenges, including a high risk of poverty and a risk of going
without health insurance. Part-time secondary
earners, in contrast, have social welfare outcomes that compare well with those of fulltime workers. Thus, findings from this article
suggest that their family’s wage-earning status
may be a key mediating variable affecting the
social welfare outcomes of part-time workers.
Beginning with background information on
Monthly Labor Review • October 2009
Part-Time Workers
research into part-time work, the article continues by
presenting current and historical data on primary and
secondary part-time earners and ends with some conclusions suggesting a path for future research.
Background
According to CPS annual estimates, part-time workers
made up 17 percent of all employed persons 16 years
and older in 2007, about the same percentage as in the
previous few years. BLS estimates show that part-time
workers tend to be younger than full-time workers,
although they are also disproportionately likely to be
older, near or of retirement age. Part-time workers are
concentrated in the service sector, in industries such as
retail, social services, and food services. Women are far
more likely than men to work part time, with roughly
one-quarter of all employed women usually working
part-time hours. Research has shown that part-time
workers are less likely than full-time workers to receive
employer-based benefits, such as health care coverage or
pensions.2 Most studies also find that part-time workers
earn less than comparable full-time workers, although
some research suggests that this is not so for certain
populations, such as highly educated women.3
One important characteristic of part-time workers is
that most of them appear to favor their work arrangement over working full-time hours. The BLS classifies
part-time workers into those who report noneconomic
reasons for working such hours and those who report
economic reasons for doing so. Economic reasons comprise slack work or business conditions, inability to
find full-time work, and seasonal work. Noneconomic
reasons include childcare problems, other family or
personal obligations, and being in school, among other
reasons. Researchers often consider noneconomic reasons to indicate voluntary part-time work, a hypothesis
which assumes that workers choose their employment
arrangement and would not prefer full-time hours.
Economic reasons are often considered to indicate involuntary part-time work, a hypothesis which assumes
that these workers would prefer full-time hours, given
the opportunity to work such hours.4
Table 1 presents 2007 CPS data on workers’ reasons
for working part-time hours. Eighty-eight percent
of those who usually worked part-time hours during
2007—almost 20 million of the 22 million part-time
workers—reported reasons which indicated that they
worked such hours voluntarily. Just 1.2 million parttime workers reported that they could find only a part
Monthly Labor Review • October 2009
Table 1.
Reasons for usually working part-time hours (less
than 35 hours per week), adults 16 years and
older, 2007
[In thousands]
Reasons
Total
employed
Percent
All part-time workers.....................
22,460
Economic reasons:
Slack work or business conditions..
Could find only part-time work ......
Seasonal work . .....................................
1,441
1,210
53
6.42
5.39
.23
19,756
656
87.96
2.92
4,940
853
6,150
21.99
3.80
27.38
2,200
4,956
9.80
22.07
Noneconomic reasons ..........................
Childcare problems . ...........................
Other family or personal
obligations...........................................
Health or medical limitations . .......
In school or training ..........................
Retired or Social Security earnings
limit ......................................................
All other noneconomic reasons ....
100
SOURCE: CPS household data annual averages. Full table available on
the Internet at www.bls.gov/cps/cpsaat20.pdf.
time job, while nearly 5 million reported that they chose parttime hours because of other family or personal obligations.
More than twice as many respondents said that they worked
part time because they were “in school or training” (6.2 million) than reported all of the economic reasons combined (2.7
million). The relative size of the group of part-time involuntary workers fluctuates with economic cycles, growing during economic downturns. Recently, the BLS announced that
this group grew substantially in the final months of 2008.5
In general, though, the group is a small one that has seen no
consistent upward trend beyond cyclical fluctuations in the
past few decades.
Many of the reasons included in the CPS that indicate voluntary part-time work are related to intervening family or
personal factors (for example, childcare problems, other family
or personal obligations, and health and medical limitations).
Therefore, many voluntary part-time workers may choose
such hours because intervening family or life circumstances
rule out full-time hours or at least substantially raise the opportunity cost of full-time work. This situation is sometimes
referred to as “constrained choice.”6 One study, for example,
finds that many mothers of preschool-aged children manage the competing demands of employment and caregiving
by working part-time hours.7 In other circumstances, these
mothers might prefer full-time hours.
An alternative way to think about the part-time workforce is to divide workers into the aforementioned primary
and secondary wage earners. Part-time work originally was
designed to attract married women into the labor market
as secondary wage earners during the 1940s and 1950s.
Before the post-World War II era, virtually all jobs required long hours with rigid arrival and departure times.8
During the postwar era, however, firms faced a declining
supply of unmarried women because of increasing college
enrollment and other factors. In response, firms began
to offer part-time jobs in hopes of appealing to married
women.
Because part-time jobs originally were designed for
married women, most of those jobs did not offer fringe
benefits such as health insurance or pensions, which typically were accessed through a spouse. Thus, part-time employment may continue to work well for secondary earners, for whom such employment originally was designed.
In contrast, part-time employment may not work so well
for primary earners, who might suffer from the lesser income and more limited access to social benefits that these
jobs offer. Part-time primary earners thus may be a relatively vulnerable group in the U.S. labor market that may
or may not overlap entirely with the group working part
time involuntarily, in light of the preceding discussion of
constrained choice.
The remainder of this article offers a method for dividing part-time workers, as defined in the CPS, into primary
and secondary earners and compares the two groups on a
number of labor market and social welfare outcomes.
Data and methods
The CPS, a monthly survey of approximately 60,000 households, is conducted by the U.S. Census Bureau for the BLS
and is a major source of labor market statistics for the
United States. The CPS offers a nationally representative
multistage stratified sample of the noninstitutionalized
U.S. population. Detailed labor market and demographic
data are collected on all adult respondents aged 16 years
and older. The analyses that follow utilize the CPS Annual Social and Economic Supplement, which provides
annualized data for the preceding year on numerous labor
market and social welfare outcomes. Data were extracted
from the Integrated Public Use Microdata Series, into
which CPS data from the Annual Supplement between
1962 and 2007 were integrated and variables were “harmonized” (coded identically) to be consistent over time.9
The analyses were restricted to working-age adults (that
is, adults aged 18 to 64 years), because workers older or
younger than that face unique issues. The 2007 outcomes
of 86,462 respondents who were employed (excluding the
self-employed) were analyzed, of which 12,990 respondents were found to have usually worked part-time hours
during that year. Descriptive results are presented. Regression analyses were utilized to control for competing
factors, such as differences in age and marital status, that
might have caused descriptive differences.10
Identifying primary and secondary wage earners. A parsimonious method was employed to divide workers into
primary and secondary wage earners. The stratified survey
design of the CPS entails that earnings data be collected for
all related family members within all households that are
surveyed. All adult person-year observations were clustered
by family in order to compute a total annual family earned
income for each respondent (the total earned income by
each family member aged 16 years or older). Then, the
annual personal earned income of each individual worker
was divided into the family unit’s annual earned income.
Those respondents with earnings that accounted for 50
percent or more of their family’s earned income were considered primary earners. Those whose earnings accounted
for less than 50 percent of their family’s earned income
were considered secondary earners.
Chart 1 divides the part-time workforce into four
groups: primary wage earners working part time voluntarily, primary wage earners working part time involuntarily, secondary wage earners working part time voluntarily, and secondary wage earners working part time
involuntarily. As the chart shows, primary wage earners
made up 36 percent of all workers who usually worked
part-time hours during 2007, while involuntary part-time
workers made up approximately 20 percent. Interestingly,
involuntary part-time workers split evenly between the
primary and secondary earner groups, suggesting that the
two dichotomies—voluntary-involuntary and primarysecondary—are not interchangeable and should not be
conflated with each other.
Robustness tests suggest that these proportions were not
highly sensitive to the 50-percent decision point for identifying primary earners. When a 55-percent decision rule
was used, primary earners made up 34 percent of part-time
workers in 2007, and when a 45-percent rule was used, they
made up 38 percent. Some researchers might argue that total
family income should be used instead of total family earned
income. Such an approach might exclude workers from the
primary wage earner group who work part time because
they are receiving a pension or have some other sources of
unearned income. When total family income was used in
this way, together with a 50-percent decision rule, primary
part-time workers were found to have made up 26 percent
of all part-time workers in 2007. This result suggests some
sensitivity to the use of earned income as opposed to total
Monthly Labor Review • October 2009
Part-Time Workers
Chart 1. Percentages of part-time workers aged 18–64 years in 2007
Secondary wage earner working
part time involuntarily
(10 percent)
Secondary wage
earner working part
time voluntarily
(54 percent)
Primary wage earner working
part time involuntarily
(10 percent)
Primary wage
earner working part
time voluntarily
(26 percent)
SOURCE: Author’s calculation from the 2008 Current Population Survey Annual Social and Economic Supplement. Data extracted from
IPUMS-CPS (Miriam King, Steven Ruggles, Trent Alexander, Donna Leicach, and Matthew Sobeck, “Integrated Public Use Microdata Series, Current
Population Survey: Version 2.0” [machine-readable database] Minneapolis, Minnesota Population Center [producer and distributor], 2004), on
the Internet at www.ipums.org/cps.
income. Family earned income was chosen for the analysis
presented in this article because using total family income in
some cases would have led to some family units having no
primary wage earners.
Chart 2 offers a historical time series that shows, over
time, the proportion of part-time workers who are primary earners and the proportion who work their hours involuntarily. Both series appear to have some countercyclical
variation: both groups grow in relative size during recessions. Unlike the involuntary part-time group, however,
primary earners appear to be growing slowly, but steadily,
as a proportion of all part-time workers over time: from
roughly 30 percent of the part-time workforce in 1970,
they grew to 36 percent in 2007. As might be expected,
the relative size of the involuntary part-time group is extremely sensitive to economic cycles. However, beyond
that sensitivity, the group appears to exhibit no upward
trend. The proportion of part-time workers who worked
their hours involuntarily in 2007 was almost identical to
what it was in 1974, the first year for which these data
are available. (It is worth noting, though, that the national
unemployment rate in 1974 was 5.6 percent, compared
with 4.6 percent in 2007.)
These figures lead to a few important conclusions. First,
Monthly Labor Review • October 2009
working part time involuntarily or voluntarily should not
be conflated with being a primary or secondary wage
earner. These are different groups. The proportion of parttime workers who are primary earners is much larger than
the proportion who work their hours involuntarily, and
involuntary part-time workers split evenly between primary and secondary earners. Further, it appears that the
proportion of part-time workers who are primary earners
is trending upward slowly over time, with some cyclical
variation.
Descriptive results for 2007
Table 2 presents 2007 descriptive means for demographic
characteristics and social welfare outcomes for full-time
workers, part-time primary earners, and part-time secondary earners. In assigning statistical significance, all descriptive statistics are clustered by household to adjust for the
stratified design of the CPS. As expected, part-time workers are, on average, both younger and more likely to be
women than are full-time workers. Within the part-time
employed, though, primary earners are older, on average,
with a mean age of 39 years, compared with 33 years for
secondary earners, and are somewhat less likely to be wom-
Chart 2. Part-time workers aged 18–64 years in the United States, 1970–2007
Percent
Percent
40.0
40.0
Primary wage earners
35.0
35.0
30.0
30.0
Wage earners working part time involuntarily
25.0
25.0
20.0
20.0
15.0
15.0
10.0
1970
1974
1978
1982
1986
1990
1994
1998
2002
2006
10.0
SOURCE: Author’s calculation from the 2008 Current Population Survey Annual Social and Economic Supplement. Data extracted from
IPUMS-CPS (Miriam King, Steven Ruggles, Trent Alexander, Donna Leicach, and Matthew Sobeck, “Integrated Public Use Microdata Series, Current
Population Survey: Version 2.0” [machine-readable database] Minneapolis, Minnesota Population Center [producer and distributor], 2004), on
the Internet at www.ipums.org/cps.
en (65 percent instead of 72 percent). There are some slight
differences by race and ethnicity among the three groups.
First, part-time workers in both subgroups are slightly less
likely to be of Hispanic origin than are full-time workers. Second, secondary earners are disproportionately more
likely to be White and non-Hispanic than are workers in
the other two groups. Third, part-time primary earners
are more likely to be Black than are full-time workers and
considerably more likely to be Black than are part-time
secondary earners. Finally, less than one-third of part-time
primary earners were married, and, surprisingly, a larger
proportion of full-time workers were married (58 percent)
than were part-time secondary earners (51 percent).11
Differences in educational attainment are slight among
the three groups. Sixty-one percent of full-time workers in
2007 had some college education, and the figures for parttime primary earners and part-time secondary earners were
60 percent and 63 percent, respectively. Roughly 10 percent of
part-time workers in both groups had less than a high school
degree, while the same was true of 8 percent of full-time
workers. Part-time workers in their early twenties were far
more likely to be enrolled in school than were their full-time
counterparts. Among respondents between the ages of 18 and
24 years, 1 in 5 full-time workers were enrolled in school in
2007, while more than 50 percent of part-time primary earners were enrolled. Even higher was the proportion of parttime secondary earners in school, with more than two-thirds
of those between 18 and 24 years enrolled in 2007.
With regard to the social welfare outcomes presented in
table 2, full-time workers and part-time secondary earners in 2007 look quite similar to each other. The proportions of respondents in these two groups living in poverty
were virtually identical, at roughly 4 percent. (The 2007
Federal poverty line was $16,530 for a family of three.)
About the same proportion of both groups received public
welfare benefits during the year. (Included in this variable
are benefits from cash assistance, food stamps, and public
housing.) The two groups went without health insurance
at similar rates as well: roughly 16 percent of full-time
workers were uninsured in 2007, while about 18 percent of
part-time secondary earners were uninsured. Table 2 also
reports on family pension coverage. This variable indicates
whether one or more members of the respondent’s family
were covered by a work-based pension program. To create the variable, CPS respondents again were clustered by
family unit to determine whether respondents had some
work-based pension coverage in their family—through
themselves, a spouse, or another family member. Among
Monthly Labor Review • October 2009
Part-Time Workers
time primary earners lived below the
Federal poverty line during 2007, and
close to half of all part-time primary
Part-time
primary
Part-time
earners lived below 150 percent of the
Characteristic
Full-time
earner
secondary earner
poverty line. Nearly a third of part-time
1
2
Age ..........................................................
40.0
38.8
33.3
primary earners were uninsured during
1
2
Woman . .................................................
44.1
65.4
72.4
2007, and almost 18 percent of all part3
2
time primary earners participated in a
66.9
66.1
73.9
White ......................................................
1
2
public welfare program. Just 22 percent
Black . .....................................................
12.5
15.3
8.3
2
2
of part-time primary earners lived in
Hispanic origin ...................................
14.5
12.6
11.9
Other race..............................................
6.1
6.1
5.8
families in which at least one member
2
2
Citizen . ...................................................
90.3
91.2
93.3
was covered by a work-based pension
1
2
program; the 22-percent figure was
Married . ................................................
57.6
29.9
51.1
more than 40 percentage points less
Education
than that of either of the other refer1
Less than 12 years ..............................
8.0
10.7
10.1
ence groups. All of the outcomes de2
12 years ..................................................
31.7
29.2
28.5
scribed are statistically significant and
More than 12 years ............................
61.2
60.1
62.5
substantially different from those faced
Income level
by full-time workers and part-time sec1
Below the Federal poverty line4 ...
3.6
29.0
4.3
ondary wage earners.
Below 150 percent of the Federal
4
1
Perhaps surprisingly, table 3 highlights
poverty line .....................................
9.2
47.5
10.1
1
2
Family pension coverage . ..............
62.9
21.8
66.6
the fact that, on some key social welfare
1
2
Uninsured .............................................
15.8
31.8
17.8
outcomes, part-time primary earners
1
Public welfare participation ...........
4.0
17.5
3.5
fared worse than nonworking adults in
1
Lives in a metropolitan area ...........
85.8
83.6
85.4
2007. While 41 percent of nonworkers
Region
were under 150 percent of the Federal
3
Northeast ..............................................
18.2
16.6
19.6
poverty line, almost 48 percent of part2
Midwest .................................................
22.4
24.4
27.0
time primary earners also were. Further,
1
2
South ......................................................
36.6
33.1
29.1
nonworkers were less likely to go without
3
West ........................................................
22.9
25.9
24.3
health insurance and more likely to have
2
1
68.9
Student (respondents, 18–24) .......
20.2
56.5
family pension coverage than were partObservations . ......................................
73,472
4,476
8,514
time primary earners. Finally, part-time
1
nomic Supplement. Data extracted from
Statistically significantly different from fullprimary earners appeared slightly more
IPUMS-CPS (Miriam King, Steven Ruggles, Trent
time mean at p < 0.05 and from part-time secondlikely than nonworkers to access public
Alexander, Donna Leicach, and Matthew Soary earner mean at p < 0.05.
welfare programs. Some of these differ2
beck , “Integrated Public Use Microdata SeStatistically significantly different from fullries, Current Population Survey: Version 2.0” ences are driven by differences in marital
time mean at p < 0.05.
3
[machine-readable database] Minneapolis,
Statistically significantly different from partstatus: whereas 48 percent of nonworking
Minnesota Population Center [producer and
time secondary earner mean at p < 0.05.
adults were married in 2007, the same
4
distributor], 2004), on the Internet at www.
The Federal poverty line is officially desigwas true of only 30 percent of part-time
ipums.org/cps. Standard errors are clustered
nated as $16,530 for a family of three.
by household to adjust for the survey’s stratiSOURCE: Author’s calculation from the 2008
primary earners. However, even when
fied design.
Current Population Survey Annual Social and Ecothese social welfare outcome estimates
are restricted to unmarried individuals in
both groups, results for the two groups prove to be similar
full-time workers, 63 percent had work-based pension to each other. In sum, part-time primary earners appeared
coverage in their family, while about 67 percent of part- to face numerous social welfare challenges—more so than
did full-time workers, part-time secondary workers, and, in
time secondary earners did.
Part-time primary earners appear to have substantial some cases, nonworking adults.
and statistically significant differences in their social welfare outcomes, compared with both full-time workers and Labor market outcomes. Table 4 reports on numerous
part-time secondary earners. Almost 30 percent of part- labor market outcomes. Both part-time primary and
Table 2.
Demographic and social welfare characteristics of U.S. workers aged
18–64 years, mean values, 2007
Monthly Labor Review • October 2009
Table 3.
Social welfare characteristics of part-time primary
wage earners and nonworkers aged 18–64 years,
mean values, 2007
Characteristic
Part-time primary
earners
Nonworking adults
Below Federal poverty
line1 ....................................
29.0
Below 150 percent of
Federal poverty line1 ...
47.5
2
Family pension coverage..
21.8
2
Uninsured ...........................
31.8
2
Public welfare participation . ..............................
Married . ...............................
17.5
29.9
2
Observations . ....................
4,476
28.9
41.0
31.0
25.5
15.4
48.0
2
28,300
The Federal poverty line is officially desginated as $16,530 for a
family of three.
2
Statistically significantly different from part-time primary earner
mean at p< 0.05.
SOURCE: Author’s calculation from the 2008 Current Population
Survey Annual Social and Economic Supplement. Data extracted
from IPUMS-CPS (Miriam King, Steven Ruggles, Trent Alexander, Donna
Leicach, and Matthew Sobeck, “Integrated Public Use Microdata Series,
Current Population Survey: Version 2.0” [machine-readable database]
Minneapolis, Minnesota Population Center [producer and distributor],
2004), on the Internet at www.ipums.org/cps. Standard errors are
clustered by household to adjust for the survey’s stratified design.
1
part-time secondary earners were about half as likely
as full-time workers to be represented by a union. Both
groups were similarly likely to be covered by a workbased pension program through their jobs, with about
1 in 5 enjoying such coverage. In contrast, more than
half of full-time workers had pension benefits. Thus, the
67-percent rate of family pension coverage enjoyed by
part-time secondary earners (see table 2) were a result
of benefits obtained through another family member. As
for employer-based health insurance coverage, table 4
suggests that part-time primary earners are nearly twice
as likely than secondary earners to have an employer pay
for some or all of their health insurance, even though
they are far less likely than secondary earners to have any
health insurance at all. This may be because part-time
primary earners have a higher takeup rate for employer-based insurance that is offered to them, given that
part-time secondary earners appear likely to be covered
through another family member.
The two groups of part-time workers were similarly concentrated in the service sector, as measured
by both industry and occupation, with the highest
concentration in education, health, and social services,
followed next by arts, entertainment, accommodations,
and food service, and then by retail trade. Secondary
earners were slightly more likely to be in retail trade
or in a sales or related occupation than were primary
earners. Finally, roughly 44 percent in both groups of
part-time workers worked for a firm with 100 or fewer
employees, while 34 percent of full-time workers did
the same. Fully a third of part-time workers in both
groups worked for a firm with fewer than 25 workers,
compared with 20 percent of full-time workers (not
shown in table 4).
Are the poor social welfare outcomes of part-time
primary earners related to their marginal attachment to
the labor force? Within the part-time workforce, primary
earners worked, on average, about 2 additional hours per
week, and 1.6 additional weeks per year, compared with
secondary earners. Also, primary earners appear to have
made substantially more per year, with an average annual
income of just under $20,000, compared with $12,500
for secondary earners. Dividing average annual earned
income by average annual work hours12 yields an approximate hourly rate of $18.98 for primary earners and
$13.46 for secondary earners (compared with $22.06 for
full-time workers). These results suggest that primary
earners worked more hours, and made more per hour, on
average, than did secondary earners.
Other factors
It is possible that the differences in social welfare outcomes presented in table 2 are driven by demographic differences beyond being a part-time primary or secondary
wage earner. Part-time workers, for example, are younger,
on average, than full-time workers, so the results shown in
the table may be driven by that demographic variable or
other competing factors. In an effort to address this possibility, three probit regression models are reported in tables
5 and 6, to build on the descriptive estimates presented
earlier. Parameter estimates are converted to average marginal effects and therefore can be interpreted similarly to
output from linear probability models. These probit models will provide some evidence as to whether controlling
for other demographic and environmental-related factors
narrows the descriptive disparities in outcomes faced by
part-time primary earners, compared with part-time secondary earners and the main reference group of full-time
workers.
The dependent variables in tables 5 and 6 are dummy
variables for the social welfare outcomes discussed in table
2. A set of mutually exclusive variables for work arrangeMonthly Labor Review • October 2009
Part-Time Workers
Table 4.
Job characteristics of U.S. workers aged 18–64 years, mean values,
2007
Characteristic, and industry
and occupation
Full-time
Part-time primary
earner
Annual earned income . ......................
Weekly work hours................................
Weeks worked in 2007 ........................
$47,034
42.9
49.7
Employer paid for insurance .............
Union member . .....................................
Received a pension . .............................
Worked for a small firm (100 or
fewer employees)...............................
62.2
15.5
52.8
1
34.4
2
1.1
7.6
13.5
3.0
10.4
4.9
2.7
.11
4.2
2
3.7
2
1.1
1
15.9
4.1
1.6
Industry
Utilities.......................................................
Construction ...........................................
Manufacturing .......................................
Wholesale trade .....................................
Retail trade................................................
Transportation and warehousing . ..
Information .............................................
Finance, insurance, and real estate..
Professional, scientific, and
technical services ..............................
Education, health, and social
services .........................................................
Arts, entertainment,
accommodations, and food
service . ..................................................
Public administration ..........................
Other . ........................................................
$19,856
1
23.4
1
44.7
1
Part-time
secondary earner
$12,477
2
21.5
2
43.1
2
26.4
2
7.6
2
18.9
2
44.1
2
2
1
7.4
2
9.9
2
20.9
2
10.6
2
13.8
2
8.8
2
17.4
44.7
.11
2.5
2
2.8
2
1.3
19.3
2
3.0
2.2
2
2
3.6
2
3.7
8.3
2
7.1
30.8
2
23.9
2
5.75
2.2
29.6
26.1
2.0
.8
1.6
.7
Occupation
Management, and business and
financial operations ..........................
14.7
Professional and related .....................
Food preparation and serving . ........
Personal care and service ...................
Other service . .........................................
Sales and related ...................................
Office and admininstrative
support..................................................
Construction ...........................................
Production and transportation ........
Other . ........................................................
21.5
4.1
2.0
7.7
9.5
Observations............................................
73,472
14.2
6.6
14.2
5.6
4.8
4.3
2
20.5
14.0
2
6.6
1
12.1
1
13.3
2
20.2
15.2
2
6.2
8.6
2
16.7
2
2
13.5
1
3.8
2
10.0
2
1.7
2
3
4,476
17.7
2
1.6
2
8.0
2
1.5
8,514
1
Statistically significantly different from full-time mean at p < 0.05 and from part-time
secondary earner mean at p < 0.05.
2
Statistically significantly different from full-time mean at p < 0.05.
3
Statistically significantly different from part-time secondary earner mean at p < 0.05.
SOURCE: Author’s calculation from the 2008 Current Population Survey Annual Social
and Economic Supplement. Data extracted from IPUMS-CPS (Miriam King, Steven Ruggles, Trent
Alexander, Donna Leicach, and Matthew Sobeck, “Integrated Public Use Microdata Series, Current
Population Survey: Version 2.0” [machine-readable database] Minneapolis, Minnesota Population
Center [producer and distributor], 2004), on the Internet at www.ipums.org/cps. Standard errors
are clustered by household to adjust for the survey’s stratified design.
10
Monthly Labor Review • October 2009
ment is included for (1) full-time
work, (2) part-time primary earners,
and (3) part-time secondary earners,
with full-time work as the referent. Demographic control variables
include sex, age (and age squared),
race and ethnicity, and marital status. A dummy variable is included
if the worker is between the ages
of 18 and 24 years and is enrolled
as a student. State dummy variables
are included, as is an indicator for
metropolitan or rural residence. All
models are clustered by household,
to correct for overly narrow standard errors that may result from the
stratified sample design.
Other job characteristics are
included in model 2 for each dependent variable, for each of the
outcomes (in poverty, uninsured,
family pension coverage), in the
form of variables for detailed industry and occupation. These variables might be more easily thought
of as outcome measures instead of
independent variables; however, because of the specific aims of the regressions, it makes analytic sense to
include them as independent variables in alternative models in order
to see the extent to which they affect the results for part-time workers. Further, including them exerts
a downward bias on the results for
the variables used to identify parttime workers. Including other job
characteristics in an effort to generate a conservative estimate of the
impact of work-related characteristics on access to benefits is common
in the literature.13
The results shown in table 5
suggest that other factors may account for some, but not many, of
the differences in poverty rates and
health insurance coverage separating part-time primary earners from
full-time workers and part-time
secondary earners. The descriptive
Table 5.
Probit regression results (marginal effects) for social welfare
outcomes for U.S. workers aged 18-64 years, 2007
In poverty
Variable
Full time
Part time × primary
earner...................................
Model 1
0.187
1
Model 2
0.152
1
(.00674)
Part time × secondary
earner . ........................................
Age ...........................................
Age squared ..........................
Man
Woman . ..................................
–.000477
(.00182)
.000473
(.000322)
1
–.00002
(.00000402)
1
.00868
(.000926)
White non-Hispanic
Black . .......................................
Education less than
12 years
12 years ...................................
More than 12 years .............
–.0233
(.00114)
1
–.0665
(.00251)
1
Married, spouse present
Married, spouse absent . ...
Widowed ................................
Single, never married . .......
Metro area resident ............
Industry: utilities
Construction .........................
Manufacturing .....................
Wholesale trade ...................
Retail trade ............................
Transportation and
warehousing .....................
Information . .....................
See notes at end of table.
–.0180
(.00103)
1
–.0434
(.00220)
1
–.00783
(.00148)
1
–.00858
(.00154)
–
–
–
–
–
–
–
–
–
0.103
1
(.00688)
.0161
(.0457)
–.00112
(.000754)
–.0000112
(.00000919)
–.00346
(.00243)
1
.0460
(.00489)
1
.145
(.00554)
1
.0774
(.00722)
.0448
(.00478)
1
.126
(.00529)
1
.0769
(.00714)
1
–.0800
(.00325)
1
–.195
(.00491)
1
.0243
(.00551)
1
.0510
(.00559)
1
.0296
(.00254)
1
.0315
(.00771)
1
.0195
(.00169)
1
–
–
.0387
(.00511)
1
–.00275
(.000785)
.00000122
(.00000954)
1
–.0235
(.00214)
1
1
–.0630
(.00320)
1
–.129
(.00472)
1
.184
(.0145)
1
.158
(.0114)
1
.141
(.00576)
1
.152
(.0159)
1
.137
(.00443)
1
–.00813
(.00180)
1
–.00997
(.00173)
1
Model 2
(.00733)
.0214
(.00227)
1
.0217
(.00211)
1
.0118
(.00263)
.0332
(.00659)
1
.0650
(.00651)
1
.0370
(.00288)
1
.0409
(.00884)
1
.0250
(.00195)
Divorced .................................
0.136
1
1
1
Separated ...............................
In school (aged 18–24
years) ....................................
–.00471
(.00136)
1
.000810
(.000283)
1
–.00002
(.00000355)
1
.00849
(.000967)
1
.0256
(.00254)
1
.0286
(.00247)
1
.0142
(.00298)
Other races ............................
Model 1
(.00627)
1
Hispanic ..................................
Uninsured
.158
(.0138)
1
.136
(.0109)
1
.124
(.00552)
1
.133
(.0155)
1
.123
(.00426)
1
1
–.0805
(.00333)
1
–.0199
(.00397)
1
1
–.0151
(.00248)
.000409
(.00371)
1
–.0107
(.00215)
1
–.0123
(.00209)
–
–
–
–
–
–
–
–
1
–.00266
(.00294)
1
–.0101
–
–
–
1
–.0772
(.00300)
1
–.0201
(.00384)
–.0561
(.00899)
1
.0512
(.0111)
1
–.0387
(.00667)
1
–.0290
(.00828)
.00800
(.00869)
–.0119
(.00844)
results presented in table 2 suggest
that part-time primary wage earners
are about 25 percentage points more
likely to be living in poverty than
are full-time workers. With other
factors controlled, the probit results
suggest that this gap falls to between
15 percentage points and 19 percentage points. Further, the probit results
indicate that part-time secondary
earners are no more likely to experience poverty than are full-time workers, and in model 2 they are actually
slightly, but statistically significantly,
less likely to experience poverty than
are full-time workers. All these results
suggest that, with numerous factors
controlled, part-time primary earners
are still far more likely to experience
poverty than are full-time workers or
part-time secondary workers, and the
latter two groups experience similar
levels of risk.
The results for models with a dependent variable of having no health
insurance again show that the output
does not differ dramatically from the
descriptive results. Part-time primary
earners are descriptively 16 percentage points more likely to go uninsured
than are full-time workers. With
other factors controlled, probit results
indicate that this gap falls slightly, to
between 10 percentage points and 14
percentage points. The models suggest that part-time secondary earners
are slightly more likely (between 2
percentage points and 4 percentage
points) to go uninsured than are fulltime workers, but are far less likely to
go uninsured than their primary-earner counterparts. Finally, table 6 suggests that the other factors included in
the model appear to have a negligible
impact on the disparities in family
pension coverage experienced by parttime primary earners relative to fulltime workers and part-time secondary
earners. The part-time primary-earner
variable is associated with more than
Monthly Labor Review • October 2009 11
Part-Time Workers
Table 5.
Continued—Probit regression results (marginal effects) for social
welfare outcomes for U.S. workers aged 18–64 years, 2007
Variable
Finance, insurance, and
real estate...........................
Professional, scientific, and
technical services..............
Education, health, and
social services ...................
Arts, entertainment,
accommodations, and
food service .......................
Public administration ........
Other . ......................................
Occupation:
management, and
business and financial
operations
Professional and related ...
Food preparation and
serving . ...............................
Personal care and
service .................................
Other service . .......................
Sales and related .................
Office and administrative
support ...............................
Construction .........................
Production and
transportation ........................
Other . ......................................
In Poverty
Model 1
–
–
–
–
Uninsured
Model 2
–0.00879
(.00291)
–
–
–.00680
(.00274)
–
–
.00257
(.00358)
–
–
–.00476
(.00288)
.00367
(.00358
1
–.0166
(.00148)
–
–
–
–
–
–
1
1
–
–
–
–
–
–
–
–
Model 1
3
Model 2
–0.0169
(.00964)
3
–.0300
(.00752)
1
.0311
(.00983)
1
–.0312
(.00737)
1
.0437
(.00998)
1
–.0776
(.00491)
1
–
–
1
.0119
(.00315)
–
–
.00502
(.00522)
–
–
1
.0588
(.00668)
–
–
1
–
–
–
–
–
–
1
.0568
(.00729)
1
.0646
(.00884)
1
.0450
(.00588)
–
–
–
–
–
–
1
–
–
–
–
1
.0215
(.00385)
1
.0372
(.00767)
–
–
–
–
1
–
–
–
–
1
.0479
(.00584)
1
.0331
(.00638)
–
–
–
–
1
.116
(.00842)
.114
(.00962)
.138
(.0121)
1
.0784
(.00757)
1
.0388
(.00582)
1
.120
(.0111)
.0931
(.00744)
.0690
(.00886)
1
State fixed effects
Pseudo R2 ...............................
Observations . .......................
1
1
2
.23
86,462
.25
86,462
.18
86,462
.21
86,462
Statistically significantly at p < 0.01.
Statistically significantly p < 0.05.
Statistically significantly at p < 0.1.
NOTE: Boldface entries are referents. Standard errors are in parentheses. Dash indicates
variable not regressed in model 1.
SOURCE: Author’s calculation from the 2008 Current Population Survey Annual Social and
Economic Supplement. Data extracted from the Integrated Public Use Microdata Series of the CPS
(Miriam King, Steven Ruggles, Trent Alexander, Donna Leicach, and Matthew Sobeck, “Integrated
Public Use Microdata Series, Current Population Survey: Version 2.0” [machine-readable database]
Minneapolis, Minnesota Population Center [producer and distributor], 2004), on the Internet at www.
ipums.org/cps. Standard errors are clustered by household to adjust for the survey’s stratified design.
12
Monthly Labor Review • October 2009
a 40-percentage-point reduction in the
probability of being in a family with
some work-based pension coverage, relative to the other two groups.
THE STANDARD PRACTICE of
dividing part-time workers into voluntary and involuntary groups offers
important information about the labor
market. The size of the group working
part time involuntarily is a good indicator of the health of the labor market.
However, results presented here suggest
that it is important not to conflate reasons for working part time voluntarily
or involuntarily with being a primary or
secondary earner. Evidence presented
in this article indicates that part-time
secondary earners fare quite well on
the social welfare outcomes examined.
They are no more likely to be in poverty
than are full-time workers, they are only
slightly more likely to go uninsured
than are full-time workers, and they are
actually more likely to live in a family
in which one or more members is covered in a work-based pension program.
On the whole, part-time work seems
to work relatively well for secondary
earners, the group for which such jobs
originally were designed.
In contrast, part-time primary wage
earners appear to face some serious social welfare challenges, with high rates
of poverty and a high risk of going uninsured. This is despite the fact that, on
average, part-time primary earners appear to have a stronger attachment to
the labor force than secondary earners
have, in that the primary earners work
more hours per year, at a somewhat
higher pay rate. Thus, these social welfare challenges are not the result of a
marginal attachment to the labor force.
Instead, they seem to result from differences in family composition. Probit
regression results suggest that other factors controlled for in the model do not
account for the descriptive differences in
social welfare outcomes.
Table 6.
Probit regression results (marginal effects) for family pension coverage for U.S. workers aged 18–64 years, 2007
Family pension coverage
Variable
Model 1
Model 2
Full time
Part time × primary earner
–0.414
(.00725)
1
.0308
(.00660)
!
.0639
(.00655)
.0115
(.00128)
1
1
Age ..............................................
Man
.00820
(.00130)
1
–.0000849
(.0000153)
1
Woman . .....................................
–.0000561
(.0000154)
1
.00707
(.00289)
.0207
(.00355)
2
1
White, non-Hispanic
Black . ..........................................
–.0536
(.00747)
1
–.168
(.00730)
1
–.0897
(.00955)
1
1
Hispanic .....................................
1
Other races ...............................
1
–.0558
(.00760)
–.155
(.00738)
–.0888
(.00966)
Education, less than
12 years
12 years ......................................
1
.164
(.00685)
1
More than 12 years ................
1
.292
(.00731)
1
.137
(.00702)
.211
(.00778)
Married, spouse present
Married, spouse absent . ......
Separated ..................................
Industry: utilities
Construction............................
Manufacturing .......................
Part time × secondary
earner .....................................
Age squared .............................
–0.397
(.00772)
1
Variable
–.235
(.0158)
1
–.198
(.0127)
1
–.157
(.00653)
1
–.162
(.0165)
1
–.138
(.00587)
1
1
1
Divorced ....................................
1
Widowed ...................................
1
Single, never married . ..........
1
–.220
(.0162)
–.181
(.0130)
–.144
(.00660)
–.147
(.0168)
–.125
(.00591)
In school (aged 18–24 years) ..
1
.116
(.00926)
1
Metro area resident................
.00922
(.00648)
3
.124
(.00914)
.0125
(.00657)
Wholesale trade......................
Retail trade ..............................
Transportation and
warehousing ..............................
Information .............................
Finance, insurance, and real
estate ......................................
Professional, scientific, and
technical services ...............
Education, health, and social
services . .................................
Arts, entertainment,
accommodations, and
food service ..............................
Public administration ..........
Other . ........................................
Family pension coverage
Model 1
–
–
–
–
–
Model 2
0.202
1
(.0157)
–.0668
(.0158)
1
.0833
1
–
–
–
1
(.0127)
.0487
(.0157)
–
–
–
–
.0166
(.0139)
1
.0808
(.0139)
–
–
1
–
–
1
.0520
(.0162)
.0584
(.0139)
–
–
1
–.0444
(.0145)
–
–
–
–
.0868
(.0130)
1
–.0758
(.0146)
1
–
1
–
(.0102)
.229
–
–
.00736
(.00697)
Occupation: management,
and business and
financial operataions
Professional scientific and
related . ..................................
Food preparation and
serving ....................................
–
–
1
Personal care and service ...
–
–
1
Other service . .........................
–
–
1
Sales and related ...................
–
–
1
–
–
1
Office and admininistrative
support .....................................
–.136
(.00913)
–.110
(.0111)
–.169
(.0133)
–.113
(.00884)
–.0405
(0.00732)
See notes at end of table.
Monthly Labor Review • October 2009 13
Part-Time Workers
Table 6.
Continued—Probit regression results (marginal effects) for family pension coverage for U.S. workers aged
18–64 years, 2007
Family pension coverage
Family pension coverage
Variable
Variable
Model 1
Construction..........................
–
Model 2
–0.0877
1
Other.........................................
–
(.0125)
Sate fixed effects
–
–.115
Pseudo R2................................
(.00846)
Observations
Production and
transportation...................
–
Model 1
1
Statistically significant at p < 0.01.
Statistically significant at p < 0.05.
3
Statistically significant at p < 0.1.
NOTE: Boldface entries are referents. Standard errors are in parentheses. Dash indicates variable not regressed in model 1.
SOURCE: Author’s calculation from the 2008 Current Population Survey
1
2
Historical evidence reported in this article shows that
part-time primary earners have been growing slowly, but
steadily, as a proportion of all part-time workers over
the past few decades, with some cyclical variation. Perhaps surprisingly, most part-time primary earners choose
part-time over full-time hours, and some do so for the
advantages that those hours can provide, despite their
restrictions on access to social benefits and their effects
on social welfare outcomes. These workers may be trading access to social benefits for increased flexibility, among
other things. However, the individual preferences that
lead workers to select part-time employment are not necessarily the result of free personal choice among equally
plausible alternatives. Most voluntary part-time workers
Model 2
–0.0650
1
(.0106)
.12
.15
86,462
86,462
Annual Social and Economic Supplement. Data extracted from the Integrated Public Use Microdata Series of the CPS (Miriam King, Steven Ruggles,
Trent Alexander, Donna Leicach, and Matthew Sobek, “Integrated Public Use
Microdata Series, Current Population Survey: Version 2.0” [machine-readable
database] (Minneapolis, Minnesota Population Center [producer and distributor], 2004), on the Internet at www.ipums.org/cps. Standard errors are
clustered by household to adjust for the survey’s stratified design.
choose part-time hours because of competing demands
such as school, childcare, or other family responsibilities.
If they did not have these responsibilities, it is unclear
whether they would choose part- or full-time hours.
Given the differences in these key social welfare outcomes faced by primary and secondary earners, research
and policies aimed at the part-time workforce as a whole
may prove inefficient. At least on the outcomes examined
herein, part-time secondary wage earners fare comparably
to workers with full-time hours. Thus, it makes more sense
to target research and social benefits toward those who
need them more, namely, part-time primary wage earners,
than toward either all part-time workers or the relatively
more well off part-time secondary wage earners.
Notes
ACKNOWLEDGMENTS: The author thanks Julia Henly, Sheldon Danziger,
Susan Lambert, Harold Pollack, and Matt Rutledge for helpful comments,
and Mario Simonelli for research assistance.
1
Handbook of Methods (Bureau of Labor Statistics, 1997), p. 1.
2
See Rebecca M. Blank, “Are Part-Time Jobs Bad Jobs?” in G.
Burtless, ed., A Future of Lousy Jobs? (Washington, DC, Brookings Institution, 1990), pp. 123–64; Christopher Tilly, Half a Job: Bad and Good
Part-Time Jobs in a Changing Labor Market (Philadelphia: Temple
University Press, 1996); and Arne L. Kalleberg, Barbara F. Reskin, and
Ken Hudson, “Bad Jobs in America: Standard and Nonstandard Employment Relations and Job Quality in the United States,” American
Sociological Review, April 2000, pp. 256–78.
3
Rebecca M. Blank, “Contingent Work in a Changing Labor
14 Monthly Labor Review • October 2009
Market,” in Richard B. Freeman and Peter Gottschalk, eds., Generating
Jobs: How to Increase Demand for Less-Skilled Workers (New York: Russell Sage Foundation, 1998), pp. 258–94.
Ibid.; see also Thomas Nardone, “Part-Time Employment: Reasons, Demographics, and Trends,” Journal of Labor Research, summer
1995, pp. 275–92.
4
5
See “Involuntary Part-Time Work on the Rise,” in Issues in Labor Statistics, Summary 08-08 (Bureau of Labor Statistics, December
2008).
Janet Walsh, “Myths and Counter-Myths: An Analysis of PartTime Female Employees and Their Orientations to Work and Working Hours,” Work, Employment & Society, June 1999, pp. 179–203.
6
7
Karen Fox Folk and Andrea H. Bellar, “Part-Time Work and
Child Care Choices for Mothers of Preschool Children,” Journal of
Marriage and Family, February 1993, pp. 146–57.
Dora L. Costa, “From Mill Town to Board Room: The Rise of
Women’s Paid Labor,” Journal of Economic Perspectives, fall 2000, pp. 10122; Jeremy Atack and Fred Bateman, “How Long Was the Workday in
1880?” Journal of Economic History, vol. 52, no. 1, 1992, pp. 129–60.
8
Miriam King, Steven Ruggles, Trent Alexander, Donna Leicach,
and Matthew Sobek, “Integrated Public Use Microdata Series, Current Population Survey: Version 2.0” [machine-readable database]
(Minneapolis, Minnesota Population Center [producer and distributor], 2004), on the Internet at www.cps.ipums.org/cps (visited June
1, 2009).
9
When a dichotomous outcome variable is used, probit or logistic
regression models are preferable to linear probability models because
probit models explicitly model the outcome as a probability and avoid
problems of heteroskedasticity. Probit results in this article are linearized by conversion into marginal effects with the use of Stata software’s
dprobit routine. Hence, probit results can be interpreted similarly to
results from linear probability models, while not suffering from the
same problems of bias.
10
11
Note that, with data from the Annual Social and Economic
Supplement, time-varying characteristics such as marital status and
union membership pertain to the year the interview was conducted
(2008 in this study) and may not be applicable during the reference
period for annualized outcomes (2007 in this study). For example, if,
during the interview in 2008, a respondent indicated that he or she was
a member of a union, then the part-time job that the respondent held
during the previous year may not have been the same job at which the
respondent was a union member.
That is, mean annual earned income ÷ (mean weekly work hours
× mean weeks worked).
12
13
Kalleberg, Reskin, and Hudson, “Bad Jobs in America”; Anne
E. Polivka, “Contingent and alternative work arrangements, defined,”
Monthly Labor Review, October 1996, pp. 3–9; and Anne E. Polivka,
Sharon R. Cohany, and Steven Hipple, “Definition, Composition, and
Economic Consequences of the Nonstandard Workforce,” in Françoise
Carré, Marianne A. Ferber, Lonnie Golden, and Stephen A. Herzenberg, eds., Nonstandard Work: The Nature and Challenges of Changing
Employment Arrangements (Champaign, IL, Industrial Relations Research Association, 2000), pp. 41–94.
Monthly Labor Review • October 2009 15
Manhattan Employment Dynamics
Manhattan’s financial sector
and the 2005–07 employment dynamic
Despite a reduced level of job activity, as reflected by gross
gains and losses, Manhattan enjoyed above-average growth
just prior to the recession beginning in December 2007;
the financial sector, characterized by a deceleration in job creation
along with strong wage escalation, provides a unique vantage point
for examining the dynamics of employment growth at the local level
Solidelle F. Wasser,
Bruce J. Bergman,
and
Michael L. Dolfman
Solidelle F. Wasser is an
economist formerly in
the New York-New Jersey
Information Office, Bureau
of Labor Statistics; Bruce
J. Bergman is a labor
economist in the same
office; and Michael L.
Dolfman is the New YorkNew Jersey Information
Office Regional
Commissioner. E-mail:
bergman.bruce@bls.gov or
dolfman.michael@bls.gov
16
T
he New York metropolitan area, accounting for nearly $1.1 trillion dollars,
or 9 percent of the Nation’s gross domestic product, ranks as “the largest metropolitan area economy.”1 At the core of that economy is New York County, otherwise known
as Manhattan. To a large degree, the financial
activities industry has powered the Manhattan
economic engine. This article takes a new look
at what distinguished both that industry and
Manhattan in light of newly released Business
Employment Dynamics (BED) data from the
Bureau of Labor Statistics (BLS).
BED data offer a different perspective on the
labor market, measuring the summation of
gross job gains and losses at the establishment
level. This approach is in contrast to the periodic release of other BLS employment numbers, which the Agency refers to as payroll
data. With those data, the difference obtained
between two periods is the net change, a static
measure, such as –100,000. By contrast, the
dynamic captured by BED statistics is the level
of job change activity behind the net change:
how did the economy end up with a net job
loss of 100,000? BED data measure how many
jobs were created by establishment openings
Monthly Labor Review • October 2009
and expansions, in addition to how many jobs
were destroyed by establishment closings and
contractions.2
In other words, BED gross job gains and
gross job losses attest to the volume of activity in labor market demand, and the numbers
help explain payroll employment change, an
outcome of that activity. The study of Manhattan employment presented in this article analyzes both of these aspects: gross activity and
net payroll change. Taken together, these two
elements enable us to gauge excess job reallocation,3 and this information adds a unique
dimension to economists’ understanding of local employment trends.
In the course of the period for which BED
data are available, namely, 1992–2008, the U.S.
economy experienced two recessions.4 Prior to
the 2001 recession, the high point in the payroll job count occurred in the fourth quarter
of 2000 in both the Nation and Manhattan.
Although the timing of the economic recovery differed, the United States and Manhattan
shared a post-2001 employment crest in the
fourth quarter of 2007.
Manhattan employment never quite rebounded as high as it did during the earlier peak, and
on the surface, it may have appeared that the events of 2001
inflicted permanent damage to the economy. Nevertheless,
despite great loss, the pace of employment growth, as measured by BLS payroll data, grew to finally exceed that of the
Nation during the 3-year period prior to the December
2007 peak. Paradoxically, BED data show that this event
occurred at a time of diminished job creation—that is, noticeably fewer job gains. So, what differentiated the periods
leading to the last two employment peaks?
Part of the answer to this question lies with structural
changes that occurred in Manhattan’s base industries—information, financial activities, and professional and business services—shortly after 2001.5 This study narrows the
perspective to the Manhattan financial sector, an industry
characterized by a deceleration in job creation along with
extraordinary wage escalation. The unique vantage point
of that perspective yields a better understanding of the
mechanics of employment demand.
After summarizing Manhattan job creation and destruction between 1992 and 2007, the article focuses on
job flows into and out of financial activities, contrasting
the period prior to the 2007 employment peak with the
one prior to the 2000 peak. Next, the discussion goes
on to frame the BED job change data in the context of
payroll data from the Quarterly Census of Employment
and Wages (QCEW), highlighting those characteristics
which may have factored into the job flow patterns of
the financial sector. Finally, the article examines the
relationship between job activity and wage change in
Manhattan.
The analysis indicates that Manhattan’s payroll growth
prior to the 2007 recession was attributable largely to a
slower rate of job destruction, as opposed to a higher rate
of job creation. Despite slowing rates of job creation, the
interplay of job reallocation and relatively high wages may
have contributed to above-average growth in wages and
employment in the financial sector.
Job flows in Manhattan, 1992–2007
The components of BED job activity—gross job gains and
gross job losses—are measured by a longitudinal database
derived from the QCEW, a census of employer reports required by State unemployment insurance laws that cover
96.2 percent of wage and salary workers. Gross job gains
include increased employment from business expansions
and openings.6 Gross job losses cover employment decreases caused by business contractions and closings.7
This article uses both seasonally adjusted and unadjusted
quarterly BED data, along with over-the-year averages.8
Quarterly data from the BED program and employment
data from the QCEW refer to the fourth quarter, unless
otherwise noted. This selection of quarterly data was intended to highlight the periods that reflected peak employment in two business cycles––the fourth quarters of
2000 and 2007, respectively––occurring within the timeframe covered by the available data. The selection of the
fourth quarter also reflects the predominance of autumn
in Manhattan hiring patterns. (See the appendix.)
What BED data teach us is that employment change represents an equilibrium of substantial activity. During the
period of this study, a typical quarter in Manhattan yielded
more than 100,000 gross job gains, with 4 out of 5 originating at expanding establishments. At the same time, the
Manhattan workforce generally experienced a comparable
magnitude of job loss, with about the same proportion of
destroyed jobs involving contracting (instead of closing)
businesses.9 The difference between these measures––the
net employment change––varied each quarter, usually
amounting to less than 50,000. (See chart 1.)
Gross job gains each quarter ranged from 100,000 to
158,400 (seasonally adjusted) over the 1992–2007 period,
while there were between 93,400 and 179,300 gross job
losses each quarter. The largest net employment decline
that occurred in any quarter in Manhattan was –58,000,
during the fourth quarter of 2001, and the largest net
gain, 28,800, occurred during the third quarter of 2000.
The fewest job losses occurred during the quarters leading
to the 2007 recession: Manhattan job losses were fewer
than 100,000 in 7 of the 12 quarters ending in December
2007.
The changing gain-loss balance highlights different
employment turning points in the U.S. and Manhattan
job markets. Nationally, gross employment gains peaked
in the first quarter of 2000 and began to slow relative to
levels from the 1998–99 period, lending credence to the
observation in the job flow literature that BED data are
useful harbingers of business cycle turns. By the start of
the 2001 recession, job gains in the Nation fell about 5
percent from the peak, as job losses rose 6 percent during
the same period. (A similar pattern of declining gains preceded the next recession: gross job gains slowed to relatively low levels in 2007, but gains still exceeded losses in
3 of the 4 quarters .)
Job creation in Manhattan, however, continued to increase during the national slowdown. Up until the first
quarter of 2001, Manhattan gross job gains outpaced losses, which also were rising (in absolute terms). It was only
in the fourth quarter of 2001, capturing the economic effects of the 9/11 attack,10 that the gross job loss (179,254)
Monthly Labor Review • October 2009
17
Manhattan Employment Dynamics
Chart 1.
Total employment change, Manhattan, seasonally adjusted, 1992–2007
Thousands
of jobs
Thousands
of jobs
200
160
200
120
120
80
80
40
40
Net change
0
0
–40
–40
–80
–80
Jobs destroyed (net losses)
–120
–120
–160
–160
–200
1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
became severe and lasting. The net change, –58,000 jobs,
was followed for several years by relatively subdued activity, which, compared with U.S. job activity, substantiates
the finding that 9/11 aggravated the effect of the economic downturn in Manhattan.
By the third quarter of 2003, net job change in the United States had turned positive, after which it remained that
way until 2007. Although job gain activity in the Nation
returned to levels similar to those existing prior to 2001,
quarterly gross job gains in Manhattan tended to be below earlier levels: between 93,000 and 118,000 jobs were
gained, compared with between 105,000 and 158,000
during the 1997–2000 period. Despite the decline in jobs
gained, Manhattan’s net change (as a percentage of average employment) exceeded that of the Nation in every
quarter from 2006 through 2007.
Where the jobs changed
In Manhattan, the greatest share of job changes, about
22 percent to 25 percent of all gross gains and losses, occurred in professional and business services, a supersector
that employs about 1 out of every 4 private-sector workers. (This supersector also experienced the greatest share
18
160
Jobs created (gross gains)
Monthly Labor Review • October 2009
–200
of job changes at the national level, where it accounted
for about 16 percent of the private sector.) Typically,
many other Manhattan industries’ shares of total activity also were close to their proportions of total employment: construction, manufacturing, wholesale trade, and
education and health services. Retail trade, along with
leisure and hospitality, industries characterized by high
turnover and seasonal employment, had shares of gains
and losses that exceeded their employment shares. In
contrast, financial activities and information had smaller
shares of both.
Though smaller, the share of gross job gains and losses
that occurred in financial activities was nevertheless considerable. Financial activities’ share of job reallocation was
higher in Manhattan than in the Nation, a large difference accounted for by the relative importance of finance
in Manhattan. Financial activities’ shares of each of the
components of total reallocation tended to trend in tandem. This behavior is consistent with the frequently noted
phenomenon that, contrary to expectations, job gains and
losses tend to increase and diminish simultaneously. The
sector accounted for an average of 15.1 percent of gains
and an average of 15.7 percent of losses over the years examined, indicating that, in Manhattan, financial activities’
share of total reallocation was somewhat stable (with the
exception of the early 1990s and of 2001 and its aftermath, when losses accelerated). In the Nation, financial
activities accounted for an average of just 5.8 percent of
both losses and gains during those years.
The “great moderation” at the local level
A decline in job activity at the national and State levels
during 1992–2008 has been documented extensively elsewhere.11 The Manhattan data exhibit a similar pattern: all
job flow components declined from earlier levels, and the
level of activity approaching the most recent employment
peak in the fourth quarter of 2007 did not match activity levels from the earlier peak in the fourth quarter of
2000.
The activity slowdown affected most sectors. Gross job
gains in professional and business services were consistently above 30,000 per quarter from 1996 until 2001.
Reflecting the aftereffect of both the recession and the
9/11 attack, net employment fell during 7 of the 8 quarters of 2001 and 2002. Activity in the professional and
business services sector remained subdued (below earlier
levels) throughout the period leading to 2007.
Gains and losses in the information sector also exhibited
a secular decline, having dropped by half since 2000. Education and health services, by contrast, tended to show a
persistent pattern of both gains and losses even through
the downturn. Only in one year, 1999, were there consecutive quarterly net losses. The national pattern exhibited
even stronger job performance: not even a single quarter
posted a net loss.
Like the Manhattan base industries,12 the declining
sectors—manufacturing, transportation and warehousing, and wholesale trade—exhibited decreased job activity. Manufacturing decreased steadily in both gains
and losses to the point that the sector’s total activity
was about one-third of what it had been in the late
1990s.13
Financial activities
The decline in job reallocation also was evident in the financial activities sector. Chart 2 shows that, after spiking
in late 2001, Manhattan job losses “settled down” to levels
lower than what they had been earlier, and gains moderated. The chart represents gains and losses as a moving
average, indexed to the average gain and loss level for the
Chart
Chart2.2. Gross job gains and losses in financial activities, Manhattan, four-quarter averages as a percent
of series average, seasonally adjusted, 1993–2008
Average
Average
180
Losses
180
160
160
140
140
120
Gains
120
100
100
80
80
60
60
40
40
20
20
0
0
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Monthly Labor Review • October 2009
19
Manhattan Employment Dynamics
period of the study. What emerges is a consistently higher
level of gains compared with losses, despite both series
being at levels that were below the U.S. average. The chart
also shows how losses started to increase in 2007.
A comparable view of financial activities on the national
level, excluding Manhattan, yields a sharp contrast. As
chart 3 shows, losses started to build in the rest of the
United States in the third quarter of 2005, and the index
of losses exceeded gains shortly thereafter.
Although financial activities accounted for a major amount
of Manhattan job activity, if we factor in employment and
if we express gains and losses as rates,14 it is evident that the
sector had relatively less activity than other Manhattan sectors, as well as a declining amount of activity over time. The
average quarterly rate of private-sector job loss in Manhattan
prior to 2001 ranged from 6.6 percent to 7.3 percent. (See
table 1.) After 2001, rates of job loss ranged from 5.2 percent to 7.1 percent, with all but one year below 6.4 percent.
A similar trend of declining losses appears in the financial
activities data: before 2001, losses averaged 4.0 percent to
5.9 percent; after 2001, losses ranged from 3.8 percent to 6.2
percent, with only one year (2002) above 4.8 percent. Financial activities had lower rates of gross job loss during all 15
years for which four-quarter averages are available.
An examination of average gross gain rates yields a cor-
responding conclusion: job creation in financial activities
tended to be below average during the same period and
declined over time. As indicated in table 2, Manhattan
financial activities experienced a decline in fourth-quarter
job gain rates, from 5.2 percent in 2002 to 4.2 percent in
2007. During that period, the national rate of job gains
declined from 6.1 percent to 5.3 percent.15 Table 1 shows
that, in Manhattan, financial activities had a lower rate of
gross gains and losses during most years. Construction,
manufacturing, retail trade, information, professional and
business services, and wholesale trade all had higher gain
and loss rates. (On a national basis, financial activities also
tended to have a lower rate of job reallocation.)
The exception to this pattern was 2002: still reeling from
the 2001 terrorist attack, financial activities lost jobs in
2002 at a higher rate in Manhattan (6.2 percent) than in
the United States (5.9 percent). This situation was unlike
that of most years, when Manhattan’s rates tended to be
below national averages for both private industry and financial activities. Table 2 shows that average rates for job
gains and job losses declined between 2002 and 2007 in
both Manhattan and the Nation, but the decline in losses,
particularly within financial activities, was much sharper
at the local level. By 2007, the average rate of job losses
in the supersector dropped to 3.8 percent in Manhattan,
Chart
Chart3.2. Gross job gains and losses in financial activities, United States less Manhattan, four-quarter averages
as a percent of series average, seasonally adjusted, 1993–2008
Average
Average
140
140
Gains
120
120
100
100
Losses
80
80
60
60
40
40
20
20
0
20
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Monthly Labor Review • October 2009
0
Table 1. Rates of gross job change in Manhattan, four-quarter averages, not seasonally adjusted
Type of
Professional
Private
Retail
Financial
Construction Manufacturing
Information and business Wholesale
change and
industry
trade
activities
trade
year
services
Gross losses
1993................................
1994................................
1995................................
1996................................
1997................................
1998................................
1999................................
2000................................
2001................................
2002................................
2003................................
2004................................
2005................................
2006................................
2007................................
7.1
6.6
6.8
6.9
6.6
6.8
7.3
6.9
8.4
7.1
6.3
6.2
5.7
5.4
5.2
11.6
11.8
13.2
13.0
11.0
9.6
11.7
10.2
12.1
11.5
11.1
11.0
10.3
8.9
8.5
11.5
10.8
11.2
11.5
10.7
11.8
12.9
11.9
12.7
10.6
9.6
9.0
8.4
8.5
7.5
8.7
8.9
8.7
8.7
8.9
8.8
9.4
9.2
9.9
8.0
7.7
7.7
6.9
6.8
6.8
5.9
4.0
5.0
4.8
4.5
4.7
5.0
4.9
6.7
6.2
4.8
4.7
4.2
4.3
3.8
5.9
6.6
7.3
6.9
5.7
6.7
5.9
6.2
9.7
8.3
5.7
5.8
4.2
4.8
4.1
7.0
7.2
7.0
7.2
6.8
6.5
7.2
7.0
9.6
7.6
6.6
6.6
5.8
5.2
5.3
Gross gains
1993................................
1994................................
1995................................
1996................................
1997................................
1998................................
1999................................
2000................................
2001................................
2002................................
2003................................
2004................................
2005................................
2006................................
2007................................
7.3
7.0
7.0
7.6
7.3
7.5
7.9
8.0
6.5
6.5
6.0
6.4
6.2
6.1
5.9
14.5
12.8
14.1
13.1
12.1
13.0
13.0
12.3
9.6
9.0
9.5
10.4
10.8
10.3
10.9
10.4
10.2
10.1
10.4
10.3
9.9
11.9
9.6
8.2
7.7
7.6
8.0
6.7
6.2
6.5
9.3
9.3
9.2
10.0
8.9
9.9
10.8
10.0
7.5
8.3
7.0
8.4
7.9
7.4
7.7
6.2
4.2
4.4
4.7
5.0
5.1
5.2
5.3
4.9
5.2
4.3
4.7
4.9
4.8
4.2
6.3
6.5
7.2
7.5
6.8
7.1
7.1
8.6
6.9
5.8
4.1
4.9
4.7
4.7
4.8
7.3 7.3
8.0
7.4
7.4
7.6
8.8
7.6
8.1
7.5
8.1
8.0
8.3
8.8
8.6
8.6
6.4
6.8
6.6
6.6
6.3
6.5
6.9
6.1
6.4
6.5
6.0
6.0
6.1
5.8
Table 2. Gross job flows measured by average rates,
not seasonally adjusted, Manhattan and United
States, 2002–07
Gross job gains
Gross job losses
Manhattan or
United States,
and year
Private
Financial
Private
Financial
(ending
industry
activities industry activities
December)
Manhattan
2002..........................
6.5
5.2
2003..........................
6.0
4.3
2004..........................
6.4
4.7
2005..........................
6.2
4.9
2006..........................
6.1
4.8
2007..........................
5.9
4.2
United States
7.1
6.3
6.2
5.7
5.4
5.2
6.2
4.8
4.7
4.2
4.3
3.8
2002..........................
2003..........................
2004..........................
2005..........................
2006..........................
2007..........................
7.4
7.0
6.7
6.6
6.5
6.5
5.9
5.4
5.6
5.4
5.4
5.6
7.2
7.0
7.2
7.1
6.8
6.7
6.1
5.6
5.9
5.9
5.5
5.3
8.2
7.7
7.5
7.9
7.1
8.7
8.3
9.0
8.9
7.2
6.7
6.6
6.6
6.5
5.9
whereas it was 5.6 percent in the Nation as a whole, having risen from 5.4 percent in 2005.
The preceding rate data indicate that the latest period of
net employment growth was not due to a higher rate of
job creation; rather, the Manhattan “advantage” was due
to slower destruction. A slowdown in job creation was accompanied, and compensated for, by a more pronounced
slowdown in job destruction. Table 3 shows that this slowdown in job losses, relative to the Nation’s losses, was most
apparent in the declining rate of jobs lost at contracting
firms. In 2002, job losses in contracting establishments
were 4.4 percent of average employment in the Nation; by
2005, the rate had fallen to 4.0 percent nationally and 3.1
percent in Manhattan. From that point, it began to inch
up in the United States, but in Manhattan the rate edged
down even further, to 3.0 percent in 2007.
Chart 4 contrasts rising levels of activity in the runup
to 2001 with activity leading to the 2007 recession. In financial activities, the 2000 high point in employment was
Monthly Labor Review • October 2009
21
Manhattan Employment Dynamics
Table 3. Gross job flows measured by average rates,
financial activities, not seasonally adjusted,
Manhattan and United States, 2002–07
Manhattan or
United States,
and year
(ending
December)
Employment distribution and growth
Expansions Contractions Openings Closings
Manhattan
2002........................
2003........................
2004........................
2005........................
2006........................
2007........................
3.8
3.0
3.6
3.9
3.8
3.4
4.5
3.5
3.6
3.1
3.2
3.0
1.4
1.3
1.2
1.1
1.1
.8
1.7
1.3
1.1
1.1
1.1
.8
4.6
4.4
4.5
4.5
4.3
4.1
4.4
4.2
4.2
4.0
4.2
4.3
1.5
1.2
1.3
1.4
1.2
1.2
1.6
1.3
1.4
1.4
1.2
1.3
United States
2002........................
2003........................
2004........................
2005........................
2006........................
2007........................
preceded by an increase in both expansions and contractions. In Manhattan and in the United States, an upswing
in contractions occurred among rates of employment loss
in contracting firms about eight quarters prior to the 2000
employment peak. During the eight quarters prior to the
2007 peak, however, the upswing occurred nationally, but
not in Manhattan. This difference reinforces the dichotomy evident in charts 2 and 3, and it tells us that the
positive net change––the employment “growth” in Manhattan––was more closely explained by contractions and
closings than by job gains.
Putting the BED data in context
Just as the job flow data add a dynamic dimension to other
employment data, QCEW data offer an insight into county-level employment characteristics. A key feature of the
Manhattan economy, evidenced by the QCEW numbers, has
been its continuous adaptation. Over the past three decades,
Manhattan’s economy was characterized by a relative flatness of the employment trend. (See chart 5.) More telling
than total changes in employment, however, are the shifts in
employment that have occurred, the result being reflected in
a persistent modernization of the county’s industry mix.
For example, in Manhattan, about 80,000 jobs were lost
in two declining industries––manufacturing and wholesale trade––between 1992 and 2007; over the same period, employment in professional and business services
increased by 137,000. This type of adaptability has con22
tributed to the county’s ability to retain much of its industrial importance.
Monthly Labor Review • October 2009
The 2001 recession and terrorist attack had a profound
effect on those Manhattan industries which had weakening employment shares, such as manufacturing, wholesale
trade, and financial activities. As table 4 shows, during the
8 years prior to the 2000 employment peak, employment
in financial activities grew by just 5 percent, compared
with 19 percent throughout Manhattan private industry.
The national rate of job growth in the financial sector, also
shown in table 4, was 3 times that in Manhattan. The attacks on the World Trade Center on September 11, 2001,
affected more than the 194,000 jobs in finance, insurance,
and real estate that were located within the immediate vicinity. The local adjustment after the shock was severe: as
the following tabulation of 12-month percent changes in
employment shows, in the 12 months ending in December 2002 Manhattan private industry contracted by 2.2
percent while employment in financial activities dropped
by 6.2 percent and financial activities employment edged
up by 0.6 percent nationally:
Year
Private
industry
Financial
activities
Manhattan:
2002 ...........................
2003 ...........................
2004 . .........................
2005............................
2006 ...........................
2007 ...........................
–2.2
–.7
.9
2.4
2.5
3.2
–6.2
–2.7
.5
3.0
2.8
2.4
United States:
2002............................
2003 . .........................
2004 . .........................
2005 ...........................
2006 . .........................
2007 . .........................
–.4
.0
1.9
1.9
1.7
.7
.6
1.2
1.4
2.2
.8
–1.4
In a short amount of time, the pace of net job growth
in Manhattan accelerated to surpass that of the Nation.
From 2004 to 2007, the 3 years prior to the December
2007 peak, the 12-month rate of job growth in private industry in Manhattan was 2.4 percent or more, while in the
United States it was between 0.7 percent and 1.9 percent.
Private-industry growth slowed nationally in 2007, but
in Manhattan it topped 3 percent. The contrast was even
more striking in financial activities, whose employment
growth started slowing in 2006. In 2007, the credit crisis
Chart 4.
Average rates of job change in financial activities, 0–24 quarters prior to employment peak,
various measures, 2000 and 2007, not seasonally adjusted
Manhattan
United States
Percent
Percent
8.0
8.0
Gross gains
8.0
7.0
7.0
7.0
6.0
6.0
6.0
5.0
5.0
4.0
4.0
6.0
6.0
8.0
Gross gains
2000
7.0
6.0
2007
2000
5.0
2007
4.0
24
6.0
20
16
12
8
4
0
Expansions
5.0
2000
4.0
3.0
2007
2.0
24
2.0
20
16
12
8
4
0
Openings
1.5
2007
1.0
5.0
24
20
16
12
5.0
4.0
4.0
3.0
3.0
2.0
2.0
24
2.0
2.0
1.5
1.5
1.0
1.0
0.5
0.5
0.0
0.0
4
0
4.0
6.0
Expansions
5.0
8
2000
5.0
2007
4.0
3.0
20
Openings
16
12
8
4
0
2.0
2000
2.0
1.5
2007
1.0
2000
0.5
0.0
24
0
20
16
12
8
4
Number of quarters prior to employment peak
0.5
24
0
20
16
12
8
4
Number of quarters prior to employment peak
Monthly Labor Review • October 2009
0.0
23
Manhattan Employment Dynamics
Chart 4.
Continued—Average rates of job change in financial activities, 0–24 quarters prior to employment
peak, various measures, 2000 and 2007, not seasonally adjusted
Manhattan
United States
Percent
7.0
Gross losses
7.0
2007
6.0
2000
5.0
4.0
3.0
24
20
5.0
16
12
8
4
0
Contractions
7.0
6.0
6.0
5.0
5.0
4.0
4.0
3.0
3.0
5.0
5.0
Percent
7.0
Gross losses
2000
6.0
2007
5.0
4.0
24
20
16
12
8
4
0
3.0
5.0
Contractions
2000
2007
4.0
3.0
2.0
2000
24
3.0
20
16
12
8
4
0
Closings
2.5
2.0
2000
1.5
1.0
2007
0.5
0.0
24
20
16
12
8
4
Number of quarters prior to employment peak
24
Monthly Labor Review • October 2009
0
4.0
4.0
3.0
3.0
2.0
2.0
3.0
3.0
2.5
2.5
2.0
2.0
1.5
1.5
1.0
1.0
0.5
0.5
0.0
0.0
2007
4.0
3.0
24
20
16
12
8
4
0
2.0
3.0
Closings
2.5
2000
2.0
1.5
2007
1.0
0.5
24
20
16
12
8
4
Number of quarters prior to employment peak
0
0.0
Chart 5. Index of total nonfarm employment, Manhattan and United States, annual averages, 1978–2007
Index
(1978 = 100)
Index
(1978 = 100)
160
160
140
140
United States
120
120
100
100
80
Manhattan
80
60
60
40
40
20
20
0
1978
0
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
SOURCE: Bureau of Labor Statistics, Quarterly Census of Employment and Wages.
and the housing slowdown took a much greater toll nationally than it did on Wall Street: while the Nation shed
1.4 percent of its financial activities jobs, employment in
Manhattan continued to grow at a rate of 2.4 percent.
The wage picture
Beyond employment, a key to understanding the Manhattan economy is the distribution and growth of wages. Manhattan’s adaptation to economic and technological developments has translated largely into gains in average wages, as
opposed to employment. From 1992 to 2007, total wages
in the private sector advanced 2.4 percent in Manhattan,
about 5 percentage points less than they did in the Nation;
local employment growth lagged that of the United States
by almost 10 percentage points. The net result was a faster
rate of average wage growth in Manhattan.
The structure of wages helps explain this phenomenon.
With the largest percentage share of total payroll wages
in the Nation (18.9 percent), professional and business
services accounted for an even higher share of the wage
bill in Manhattan (26.3 percent). Nevertheless, the largest share (39.6 percent) of Manhattan wages stemmed
from financial activities.
The dominance of the Manhattan wage picture by financial activities contrasts sharply with the picture for
the Nation, where the sector accounted for only about 10
percent of payroll wages. Despite strong employment and
wage shifts among the other sectors in Manhattan, financial activities maintained approximately the same share of
total private-sector wages throughout the 16-year period
of this study.
Payroll data show that, although employment in financial activities never returned to its 2000 peak—or even to
its 1992 levels—average weekly wages in the supersector
compared favorably not only with other supersectors within Manhattan, but also with those of the Nation as a whole.
In both 1992 and 2007, one financial activities industry—
securities, commodities contracts, and investments—had
the highest fourth-quarter average weekly wage among all
service-providing subsectors in Manhattan.
As regards wage growth, weekly wages in the financial
activities sector grew by 50 percent, topping wage growth
in all the other private-industry sectors, between 1992
and 2000. Wage growth in the sector accelerated in the
years that followed, and by 2007 average wages in ManMonthly Labor Review • October 2009
25
Manhattan Employment Dynamics
hattan’s financial activities sector were more than double
what they were in 1992. Nationally, weekly wages grew 85
percent during the same period.
Distinguishing characteristics
The QCEW payroll data reveal important features of the
Manhattan financial activities sector that may factor into
any changes in job flow activity that occur in the county.
In Manhattan, a greater proportion of employment exists
in larger establishments and in higher paying financial industries. QCEW data indicate that the average establishment size in the Nation has declined over time, from 13.9
in 1993 to 12.8 in 2008.16 The average establishment size in
financial activities in the United States also declined, from
11.1 in 1993 to 9.2 in 2008. In contrast, the average establishment size in Manhattan was 16.0, and that of the finan-
cial activities sector was 22.9 in 1993 and 20.1 in 2008.
A key distinction between financial activities in Manhattan and in the United States is in the proportion of establishments that employ at least 50 or more employees.17
That size category accounted for 2.4 percent of financial
activities establishments, and 48.4 percent of the sector’s
workers, nationwide. In Manhattan, 9.7 percent of the establishments employed at least 50 workers, and their share
of employment, as table 5 shows, was 70.1 percent. The
significance of the relation between employment size, on
the one hand, and gains and losses, on the other, will be
explored subsequently.
National data from the QCEW indicate that the largest
establishments tended to have above-average weekly wages. In the private sector, large establishments (those with
at least 250 employees) had average weekly wages that
were higher than the average for all sizes every year from
Table 4. Fourth-quarter employment and wages, Manhattan and United States, 2000 and 2007
[In percent of total]
Manhattan or United States,
and industry sector
Average monthly
employment (thousands)
2000
2007
Employment change,
percent
1992–2000
1992–2007
Total wages (millions of
dollars)
2000
2007
Change in average
weekly wages, percent
1992–2000
1992–2007
Manhattan
Total private industry...............
Construction.....................................
Manufacturing.................................
Wholesale trade...............................
Retail trade........................................
Information.......................................
Financial activities..........................
Professional and business
services............................................
Educational and health
services...........................................
Leisure and hospitality..................
Other services, except
public administration.................
1,983.2
1.9
3.4
4.6
7.1
8.6
20.6
1,952.6
1.8
1.9
4.2
7.7
7.0
19.6
19.0
51.8
–31.8
–7.8
27.9
31.1
5.0
17.2
46.7
–62.7
–17.3
37.1
4.8
–1.4
40,628.8
1.7
2.2
4.6
3.3
8.2
39.6
52,132.7
1.7
1.4
4.1
3.5
7.0
39.4
32.5
29.2
33.2
22.0
21.4
20.6
50.6
72.8
78.7
101.2
57.4
55.8
64.5
104.9
25.4
25.3
40.8
38.5
26.3
26.7
31.5
74.3
12.6
9.6
15.0
11.2
22.8
39.8
44.2
60.0
6.5
4.4
7.8
4.9
19.8
32.2
56.9
63.6
4.3
4.6
18.5
24.4
1.9
2.3
29.0
87.3
111,343.3
6.1
15.5
5.2
14.2
3.3
6.8
114,917.0
6.6
12.0
5.2
13.9
2.6
7.0
23.2
45.2
2.8
17.1
18.8
38.1
15.7
27.1
62.2
–18.0
22.0
19.7
12.7
23.3
1,044,811.9
6.6
18.4
7.2
8.6
5.2
10.0
1,346,643.2
7.3
14.3
7.3
8.0
4.0
10.9
31.3
34.6
30.7
35.8
26.7
46.2
39.8
63.8
70.9
64.1
70.4
50.3
78.2
84.5
15.2
15.7
52.7
63.3
18.9
20.2
33.1
71.8
13.1
10.6
15.4
11.5
24.2
25.3
51.0
40.6
11.8
4.6
14.4
4.9
18.4
33.3
52.9
63.7
3.7
3.9
19.5
28.3
2.3
2.4
30.2
62.4
United States
Total private industry............
Construction....................................
Manufacturing................................
Wholesale trade..............................
Retail trade.......................................
Information......................................
Financial activities.........................
Professional and business
services...........................................
Educational and health
services...........................................
Leisure and hospitality.................
Other services, except public
administration..............................
SOURCE:
26
Bureau of Labor Statistics, Quarterly Census of Employment and Wages.
Monthly Labor Review • October 2009
Table 5. Employment, by size of establishment, Manhattan and
United States, March 2008
Number of
All
Percent
employees
industries
share
Manhattan
All sizes.................
2,374,109
100.0
Fewer than 5.............
110,536
4.7
5 to 9..........................
118,093
5.0
10 to 19......................
157,811
6.6
20 to 49......................
257,007
10.8
50 to 99......................
211,376
8.9
100 to 249.................
281,609
11.9
250 to 499.................
198,288
8.4
500 to 999.................
188,326
7.9
1,000 or more...........
851,063
35.8
50 or more.................
1,730,662
72.9
United States
All sizes................. 112,664,943
100.0
Fewer than 5.............
7,726,877
6.9
5 to 9..........................
9,317,085
8.3
10 to 19......................
12,711,584
11.3
20 to 49......................
19,590,711
17.4
50 to 99......................
15,201,036
13.5
100 to 249.................
18,771,468
16.7
250 to 499.................
10,489,713
9.3
500 to 999.................
7,357,375
6.5
1,000 or more...........
11,499,094
10.2
50 or more.................
63,318,686
56.2
Financial
activities
Percent
share
377,464
16,018
21,958
31,658
43,183
100.0
4.2
5.8
8.4
11.4
33,424
46,535
37,518
30,457
116,713
8.9
12.3
9.9
8.1
30.9
264,647
70.1
8,004,315
880,417
1,013,595
1,059,301
1,176,519
100.0
11.0
12.7
13.2
14.7
799,091
930,318
632,478
630,484
882,112
10.0
11.6
7.9
7.9
11.0
3,874,483
48.4
SOURCES: U.S. data are from the Bureau of Labor Statistics, Quarterly
Census of Employment and Wages; unpublished Manhattan data are from
the New York State Department of Labor.
2001 to 2008. In financial activities, this also was true for
establishments with 100 to 249 workers. (See table 6.)
Data from the QCEW also show how the industrial
composition of financial activities differs in Manhattan
from that in the United States. In 1992, securities, commodity contracts, and other financial investments and related activities, the financial activities subsector with the
highest average weekly wage, accounted for 37 percent of
the sector’s employment, and almost two-thirds of its total wages, in Manhattan. In stark contrast, nationally the
subsector accounted for 7.7 percent of financial activities
employment and 23.1 percent of the sector’s wages. Other
subsectors, such as credit intermediation and related activities (including banking), insurance, and real estate, had
greater shares of employment and wages nationally than
they did in Manhattan.
In Manhattan, as in the Nation, the securities subsector
had increasing shares of employment and wages in 2000
compared with 1992. The following tabulation shows that,
in 2007, the securities industry held a large share of financial activities’ employment and wages in Manhattan:
Year and measure
Manhattan
Securities industries’ percent
of all financial activities, 1992:
Establishments ................
20.7
Employment.....................
37.0
Total wages.......................
64.3
Average weekly wage .......... $3,510
Securities industries’ percent
of all financial activities, 2000:
Establishments ................
24.1
Employment ....................
46.8
Total wages ......................
72.0
Average weekly wage........... $4,670
Securities industries’ percent
of all financial activities, 2007:
Establishments .................
26.4
Employment ....................
47.6
Total wages ......................
72.6
Average weekly wage........... $6,296
Rest of
United States
5.9
5.9
15.3
$1,761
8.9
9.0
22.2
$2,336
10.1
8.9
22.9
$3,232
Table 6. Average weekly wages, by size of establishment,
United States, 2001–08
All
Year
sizes
50
to
99
100
to
249
250
to
499
500
to
999
1,000
or
more
Total private
industry
2001..................
2002..................
2003..................
2004..................
2005..................
2006..................
2007..................
20081................
$720
719
728
758
777
848
892
912
$663
667
676
703
717
778
813
838
$710
719
733
762
776
847
892
910
$792
799
802
850
880
962
1,010
1,035
$870
889
920
961
991
1,080
1,153
1,200
$1,104
1,073
1,080
1,154
1,187
1,339
1,439
1,454
1,348
1,272
1,265
1,414
1,482
1,686
1,895
1,898
1,306
1,307
1,302
1,497
1,559
1,694
1,884
1,981
1,496
1,444
1,467
1,690
1,718
1,917
2,251
2,202
1,692
1,569
1,489
1,697
1,876
2,131
2,282
2,397
1,504
1,494
1,575
1,685
1,800
1,924
2,199
2,207
2,639
2,186
2,080
2,567
2,803
3,666
4,350
4,033
Financial
activities
2001..................
2002..................
2003..................
2004..................
2005..................
2006..................
2007..................
20081................
Preliminary.
SOURCE: Bureau of Labor Statistics, Quarterly Census of Employment
and Wages.
1
Monthly Labor Review • October 2009
27
Manhattan Employment Dynamics
Fully 47.6 percent of the Manhattan supersector was employed in securities in 2007, earning 72.6 percent of the
total financial activities wage bill. In contrast, the securities industry shares remained unchanged in the rest of the
Nation from 2000 to 2007, at about 9 percent of employment and 22 percent of total wages.
Thus, the QCEW data show not only the economic importance of the financial activities supersector in Manhattan, but other important features that distinguish it
there from its importance in the Nation, and those characteristics could help explain job flow trends. At the onset of the period studied, the Manhattan finance industry
already had a pay advantage, partly related to its size and
industry makeup. Over time, employment became even
more concentrated into the higher paying finance industries, which already accounted for a far greater share of
financial activities in Manhattan compared with the rest
of the Nation.
Explaining job flow trends
With the backdrop afforded by the QCEW data, we can
better understand the churning in jobs added and lost
each quarter. Much theorization has centered about the
cause of the churning: job activity may be attributed to
establishments that are adjusting payrolls in response
to productivity changes, business competition, external
shocks, seasonal changes, or the business cycle. From this
perspective, jobs are reallocated to a more efficient structure on the basis of employer decisions.
That Manhattan has maintained a pay advantage for private
industry as a whole, and for financial activities in particular,
might suggest that Manhattan has attained an efficient allocation of labor. At the same time, as a corporate and metropolitan center, the county accommodates business establishments that tend to be larger, and better positioned financially,
than average, and these characteristics may have had implications for employment growth and business turnover.
The above-average size of Manhattan businesses may
partly explain the reduced level of activity over time.
About 60 percent of job activity in the Nation involves
firms18 with fewer than 100 employees. Beyond this fact,
additional BLS research indicates that a dropoff in job activity, observed nationally, was more pronounced among
establishments that changed employment by more than
20 employees. It may be presumed that most of the establishments in this category are larger. Thus, given the larger
establishments characteristic of the Manhattan economy,
one might expect a decline in activity to be more pronounced at the local level.
28
Monthly Labor Review • October 2009
Table 7. Fourth-quarter rate of net change in employment
compared with excess reallocation rates, not
seasonally adjusted, Manhattan and United States,
1992–2007
Manhattan
United States
Year
Excess
Excess
Rate of net
Rate of net
reallocation
change
change reallocation
rate
rate
Total private
industry
1992...................
1993...................
1994...................
1995...................
1996...................
1997...................
1998...................
1999...................
2000...................
2001...................
2002...................
2003...................
2004...................
2005...................
2006...................
2007...................
1.2
2.4
2.3
2.8
3.2
3.0
3.1
3.8
3.0
.0
2.2
2.5
2.7
3.1
3.1
3.3
11.6
10.6
10.8
10.8
11.2
10.6
10.0
11.0
11.2
14.6
10.0
8.8
9.2
7.8
7.8
7.6
0.2
.6
.5
.3
.8
.7
.8
1.0
.4
–.8
–.2
.4
.6
.5
.4
.3
15.0
14.6
14.8
15.2
14.6
15.2
14.2
14.0
14.4
14.0
13.8
13.2
13.0
13.0
12.8
12.8
1992..................
–.6
7.6
.4
1993..................
1.6
5.6
1.0
1994..................
–.1
7.0
–.4
1995..................
.3
8.0
.7
1996..................
.7
8.8
1.1
1997..................
.9
7.0
1.3
1998..................
.0
8.6
1.2
1999..................
1.5
8.4
.8
2000..................
1.2
8.0
1.0
2001..................
–4.5
8.0
.3
2002..................
.0
8.2
.9
2003..................
.7
6.4
.1
2004..................
1.5
5.6
.7
2005..................
1.7
5.6
.8
2006..................
1.1
6.0
.4
2007..................
.7
6.0
–.2
10.4
9.8
10.8
10.6
10.2
11.0
11.6
11.0
10.6
11.2
9.8
10.2
10.0
9.6
9.8
10.2
Financial
activities
Expectations, however, do not explain why a slowdown
in job activity occurred. For that, we may look to excess
reallocation, the “extra” gain and loss activity above and
beyond the net change. A net job loss of 100,000 could
be caused by gross losses amounting to 250,000 and gross
gains totaling 150,000. Or it could reflect 500,000 gross
losses and 400,000 gross gains. In the former example,
excess reallocation equals 300,000 jobs (gross gains and
gross losses that cancel each other out); in the latter example, excess reallocation amounts to 800,000 jobs, ob-
viously much more activity.
Excess reallocation, then, is essentially the number of establishment payroll-level changes that do not show up in
reported industry payroll counts. Table 7 shows that total
private-industry rates of excess reallocation were lower, on
average, in Manhattan than in the Nation. Financial activities’ excess reallocation rates were even lower than those
of private industry. The table contrasts the slowdown in
Manhattan excess reallocation compared with U.S. excess
reallocation, together with an increasingly higher (net)
growth rate in Manhattan.
Some have theorized that job reallocation increases during recessions and decreases during expansions.19 More
specifically, countercyclical movements in job reallocation rates are initiated by sharp increases in job destruction prior to, and during, recessions. Evidence (based on
manufacturing data at a time when the secular trend was
downward) pointed to job creation continuing at a steadier rate than job destruction, even during recessions, and
the researchers concluded that job reallocation could lead
to recessions.
BED data for Manhattan, however, do not confirm that
pattern. Excess reallocation is not countercyclical for financial activities or the other base industries. Other re-
search20 finds rising volatility among publicly traded firms,
but that privately held firms have become less volatile and
dominate the overall trend.
BED data do illustrate a close relation between excess reallocation and total wages in Manhattan financial activities. Chart 6 shows a coincident rise in excess reallocation
with first-quarter wages in financial activities, centering
in the quarter of bonus payments characteristic of this supersector. The pattern, also reflecting the seasonal nature
of the data, holds almost to the end of the series, even
as excess reallocation activity slows. A somewhat different pattern is revealed by the less turbulent fourth-quarter
data, as depicted in Chart 7.
In the fourth quarter, excess reallocation appears to lead
the wage change up to 2002. After that, there is a break
in the connections between the series, and excess reallocation drops well below its previous average.
This trend in excess reallocation coincided with both an
acceleration in total wages that followed the fourth quarter of 2002 and an increasing concentration of employment in securities, perhaps suggesting that the objectives
of job reallocation were realized. The accelerating rise in
average weekly wages with relatively low job creation in
Manhattan financial activities that occurred starting in
Chart 6. Excess reallocation and total wages,1 each as a percent of series average,2 financial activities,
Manhattan, 1992–2008
Average
Average
350
300
Wages
Excess
300
250
Linear (wages)
Linear (excess)
250
200
200
150
150
100
100
50
50
0
1
2
350
1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
0
Total wages were adjusted for inflation by the New York-New Jersey Consumer Price Index (1982–84 = 100).
Series average (= 100) from third quarter of 1992 to second quarter of 2008, not seasonally adjusted.
Monthly Labor Review • October 2009
29
Manhattan Employment Dynamics
Chart 7. Fourth-quarter excess reallocation and total wages,1 each as a percent of series average,2
financial activities, Manhattan, 1992–2007
Average
Average
140
140
Excess
120
120
100
80
80
60
60
40
40
20
20
0
1992
1
2
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
0
Total wages were adjusted for inflation by the New York-New Jersey Consumer Price Index (1982–84 = 100).
Series average (= 100) from third quarter of 1992 to second quarter of 2008, not seasonally adjusted.
2004 might suggest that a more optimal level of job allocation had been reached. What will be particularly telling
is what happened, and what will be happening, after the
2007 recession, now that the financial sector is facing new
challenges.
Additional research is needed to explore excess reallocation and its explanatory value. A closer look at the activity
patterns, as well as the establishment size and turnover,
of industries in various sectors can be further analyzed to
explain shifts in establishments, employment, and wages.
Articles on BED data have been written by scholars who
have had access to detailed data at the establishment level.
Many have noted the heterogeneity of the data even at that
level. Even without establishment-level detail, however,
there is evidence that reallocation has contributed to a
different industry mix within the Manhattan supersector
from that of the rest of the country. The redistribution of
industries within the supersector may explain divergences
between Manhattan and the Nation, particularly in the
post-2001 recession.
BUSINESS EMPLOYMENT DYNAMICS DATA shed light on
conflicting patterns evident in BLS payroll data. Gross employment flow activity—gains and losses of jobs—provides
30
100
Wages
Monthly Labor Review • October 2009
another dimension to understanding differences in growth.
In the years prior to the latest recession, Manhattan had a
reduced level of activity and still outperformed the Nation.
The adaptation of financial activities, an industry with deep
roots in Manhattan’s past, has been accompanied by patterns of excess reallocation and wage change distinct from
those of the Nation. From the labor market experiences in
the aftermath of September 11, it is clear that the adaptability of local economies’ core industries is a critical ingredient of the eventual recovery of those economies.21
Although the Manhattan experience tends to reflect the
national pattern of a secular decline in the magnitude of
job flows, the BED data reveal an important fact: the latest
period of relative employment growth in Manhattan was
due, not to a higher rate of job creation, but to a slower
pace of job loss in contracting and closing establishments,
and a substantial part of this effect occurred in the financial sector.
BED data also reveal differences in the timing of job gains
and losses, and these differences are of particular interest
as regards the runup to the latest recession. As early as
the third quarter of 2006, the national figures prefigured
the downturn to come, while a different story emerged in
Manhattan. That story is related to excess job reallocation,
a previously unexplored aspect of understanding job flows
and, consequently, shifts in wages.
BED data illuminate Manhattan business patterns and
shed light on growth and job flow activity. What appears
as a paradox—reduced activity and increased growth—
may be a reflection of the unique character of financial
activities, a sector that has continuously adapted to contemporaneous business activity, and this adaptation has
made Manhattan a driving force for the much larger socioeconomic area.
Notes
Acknowledgment: The authors would like to thank Emily A. Harcum, a marketing specialist in the Division of Information Services,
Office of Publications and Special Studies, Bureau of Labor Statistics,
for her invaluable assistance.
1
See Sharon D. Panek, Frank T. Baumgardner, and Matthew J. McCormick, “Introducing New Measures of the Metropolitan Economy,”
Survey of Current Business, November 2007, pp. 79–114, especially p.
79.
National and State data currently are published quarterly by naics
supersector and size of firm. Future expansions of available data will
include greater industry and geographic detail.
2
3
Job reallocation, an indicator of how much job activity is occurring,
is equal to the sum of gross job gains and gross job losses. Excess job
reallocation, describing the amount of activity above and beyond the
net change, is equal to job reallocation minus the absolute value of the
net employment change.
The National Bureau of Economic Research designates recessions
as periods of significant decline in economic activity throughout the
U.S. economy. The determination of when a recession begins and ends
is based on a number of indicators, such as production, income, and employment. No comparable official date exists, however, for timing the
economic decline (and recovery) at the local level. A comparison involving solely employment shows that, compared with the United States,
New York City suffered a larger and more protracted percentage decline
in employment during both the 1991 and 2001 recessions.
4
See Michael L. Dolfman, Solidelle F. Wasser, and Kevin Skelly,
“Structural changes in Manhattan’s post-9/11 economy,” Monthly Labor Review, October 2006, pp. 58–79.
5
6
Increased employment from establishment openings comes from
seasonal reopenings and other situations, in addition to establishment
births. Representing about 60 percent of openings, births are new businesses that report employment for the very first time or that report
positive employment after four consecutive quarters of zero employment. (See Akbar Sadhegi, “The births and deaths of business establishments in the United States,” Monthly Labor Review, December
2008, pp. 3–18.)
7
Reduced employment associated with closing establishments
comes in part from temporary shutdowns of seasonal units. Deaths,
which account for about 60 percent of closing establishments, are businesses that disappear by reporting no employment for four consecutive
quarters.
8
qcew data are not seasonally adjusted, necessitating over-the-year
analysis. For a discussion about interpreting annual compared with quarterly changes in bed data, see James R. Spletzer and Joshua C. Pinkston,
“Annual measures of gross job gains and gross job losses,” Monthly Labor
Review, November 2004, pp. 3–13. (See also Akbar Sadeghi, James R.
Spletzer, and David M. Talan, “Business employment dynamics: annual
tabulations,” Monthly Labor Review, May 2009, pp. 45–56.)
9
See Sadeghi, Spletzer, and Talan, “Business employment dynamics.” The authors illustrate how seasonal variation and employment
patterns are less visible in the annual data. For example, when national
gross job gains are measured on a quarterly basis, 81 percent of the
gains are found to be due to expanding establishments. On an annual
basis, the number is 69 percent.
10
See Dolfman, Wasser, and Skelly, “Structural changes in Manhattan.”
See Sheryl L. Konigsberg, James R. Spletzer, and David M. Talan,
“Business employment dynamics: tabulations by size of employment
change,” Monthly Labor Review, April 2009, pp. 19–29.
11
12
The base industries of the county, as indicated by location quotients of employment (measures of how the local distribution of industry employment differs from the national distribution) are financial
activities, information, and professional and business services.
13
The decline in manufacturing was characterized by a very high
rate of employment lost to closings (60 percent), as opposed to that
lost to existing businesses contracting. (Interestingly, the proportion of
employment gained from openings, 41 percent, was higher in manufacturing than in any other sector.)
14
Computing an activity measure as a rate involves expressing the
measure as the result of the count divided by an average of beginningperiod employment to ending-period employment.
15
In addition to the number of gross job gains dropping to low levels
nationally, establishment births as a percentage of total establishments
exceeded establishment deaths each quarter from the first quarter of
2002 through the fourth quarter of 2006. Prior to the December 2007
peak, the birthrate declined from representing 3.27 percent of all establishments in the third quarter of 2005 to 2.89 percent.
16
Authors’ tabulations using aggregate qcew establishment and employment counts.
17
The qcew program tabulates data by establishment size class for
the first quarter of each year. The size class of each establishment is
determined by the March employment level. Each establishment of
a multiestablishment firm is tabulated separately into the appropriate
size class; the total employment level of the reporting multiestablishment firm, however, is not used in the size tabulation.
18
Establishments are used in the tabulation of the bed statistics by
industry, and firms are used in the tabulation of the bed size class statistics. Among bed data are data on the magnitude of job losses on an
establishment basis; for example, it has been found that approximately
one-third of gross job gains and gross job losses originate from establishments that change employment by 20 or more jobs. Also, one–third
of gross job gains and gross job losses originate from a large number
of establishments that have changed their employment level by 1 to 4
employees.
Monthly Labor Review • October 2009
31
Manhattan Employment Dynamics
19
See Scott Schuh and Robert Triest, “Job Reallocation and the
Business Cycle: New Facts for an Old Debate,” in Beyond Shocks: What
Causes Business Cycles? Proceedings from the Federal Reserve Bank of
Boston Conference Series no. 42, 1998.
20
See Steven J. Davis, R. Jason Faberman, John Haltiwanger, Ron S.
Jarmin, and Javier Miranda, “Business Volatility, Job Destruction, and
Unemployment,” Discussion Papers, ces 08–26 (U.S. Census Bureau,
Center for Economic Studies, August 2008).
21
For a discussion of the importance of core industries in a particular economic downturn, see Michael L. Dolfman, Solidelle Fortier
Wasser, and Bruce Bergman, “The effects of Hurricane Katrina on the
New Orleans economy,” Monthly Labor Review, June 2007, pp. 3–18.
APPENDIX: The seasonality of job movement in Manhattan
A close examination of BED data confirms an aspect of city
life long celebrated in fiction and song: the quickening of bigcity life known as the “fall season” is grounded in a pickup in
hiring activity. Data from the BED show this strong seasonal
pattern. Both the United States and New York County
(Manhattan) tend to exhibit seasonal patterns in net changes
between gains and losses produced by industry expansion and
contraction and the opening and closing of places of business.
Winter and summer patterns are characterized by negative
changes, in contrast to positive changes in spring and fall. As
the following tabulation shows, it is the dominance of the fall
changes in Manhattan that separates economic activity there
from the national pattern:
BED net change (rate)
Quarter
United
ending in—
Manhattan
States
32
March:
Average .............................
Maximum .........................
Minimum .........................
2.0
–1.0
–3.3
–1.8
–1.2
–2.5
June:
Average .............................
Maximum .........................
Minimum .........................
1.0
1.9
–.7
3.0
3.8
1.9
September:
Average .............................
Maximum .........................
Minimum .........................
–.7
.4
–3.5
–.1
.8
–1.6
December:
Average .............................
Maximum .........................
Minimum .........................
2.6
3.8
.0
.4
1.0
–.8
Monthly Labor Review • October 2009
Despite Manhattan’s reputation as an international emporium,
increases in retail trade are far less important in explaining the
fourth-quarter increases there than they are nationwide. In the
Nation, retail trade and education are typical sectors which
experienced gains in the fourth quarter that offset heavy losses
in construction and in leisure and hospitality. In Manhattan, by
contrast, few losses occurred at all in the fourth quarter. Small
losses in manufacturing were offset by small gains in wholesale
trade, and construction was flat. No other sector lost jobs.
Contrary to the national pattern, in Manhattan professional
and business services accounted for about one-fourth of all job
gains, while retail trade also added about one-fourth to the total,
followed by leisure and hospitality at 21 percent. Net changes
in professional and business services tended to result primarily
from a drop in contracting businesses and closings, while retail
trade and leisure changes reflected an increase in expansions.
One might suggest that these expansions were a reaction to
demand coming from base-industry employees, whose high
wages appeared to be less threatened by contractions in the
fourth quarter.1
Note to the appendix
1
This pattern of demand and its consequent effect on employment was
noted in Michael L. Dolfman, Solidelle F. Wasser, and Kevin Skelly, “Structural
changes in Manhattan’s post-9/11 economy,” Monthly Labor Review, October
2006, pp. 58–79.
Parenting of Infants
The parenting of infants: a time-use
study
Data from the American Time Use Survey show that parents of infants spend
far more time on childcare relative to parents of older children; women spend
more time engaging in childcare than men, parents obtain time for childcare
from various sources, and time use diverges across lines of socioeconomic status
Robert Drago
Robert Drago is a professor
of labor studies and women’s
studies at The Pennsylvania
State University. E-mail:
drago@psu.edu
D
o parents of infants spend their
time differently than parents
of older children? Although an
extensive body of research concerns time
use among parents, no previous study
has directly answered this question. Data
from the initial 5 years of the American
Time Use Survey (ATUS) allow for an
investigation of the topic. The analysis in
this article provides answers to a series of
questions regarding the quantity of time
that “coupled” women, coupled men, and
single women allocate to childcare; the
trade-offs that are made in order to generate time for childcare; and variations
among groups of differing socioeconomic
status (SES) in time spent on childcare, on
housework, and at work.
The first question is whether parents
devote more time to infants relative to
older children. In general, one would
expect the answer to be yes. Initially, infants generally require more from their
caregivers. Few newborns sleep through
the night, and they need frequent feeding, changing of diapers, rocking, and so
forth. Further, infant care is often viewed
as more important or valuable to parents
and to society than care for older children.
This is evident in the paid maternity leave
systems that allow mothers to devote
themselves to infant care in most nations.1
The scarcity of paid maternity leave may help
explain why coupled mothers of newborns in
the United States are often pressured to leave
the labor force, or “opt out,” to spend more
time on childcare.2 However, fathers do not
appear to fit this pattern. Overall, fathers have
increased the amount of time they allocate to
childcare in recent decades,3 but earlier studies provide mixed results in answering the
question of whether fathers devote more or
less time to younger children than to older
children.4
The second question concerns the “time financing” of childcare, that is, the reallocation
of time spent on other activities to generate
additional time for children. Implicit in debates regarding opting out is the possibility
that the reduction of time spent working for
pay is a major source of childcare time—that
is, time during which one is engaged in childcare—for new mothers with husbands or partners. An analysis of time financing can discern
whether mothers of infants commonly pull
their time from other sources—such as leisure or sleep. For coupled men especially, the
sources of childcare time are pertinent given
the historical pattern of new fathers increasing
the amount of time they devote to employment.5 If fathers of infants are found to spend
more time on both employment and childcare,
where does that time come from? For single
mothers, the task of raising an infant alone
Monthly Labor Review • October 2009 33
Parenting of Infants
may involve difficult choices, particularly when the
mother is employed; this article may help to shed light
on how those choices are made.
The third (and last) question is the following:
how are childcare time, time allocated to housework,
and working time—that is, time spent working for
pay—related to SES? Socioeconomic status is linked
to financial and social resources, as well as to expectations regarding behavior; as a result, there are reasons
to expect that allocation of time will differ by SES. For
example, families of high SES have greater financial resources to purchase services ranging from housework
to precooked meals and childcare. These purchases
may free up time for work or leisure, and they can
function to ameliorate the compromise between paid
work and childcare time that usually must be made.
It is also possible that norms have developed among
high-SES people regarding work and parenting. Some
research suggests that an “ideal worker” norm leads
men and women of high SES to work long hours, regardless of parental status, and other research suggests
that a norm of “intensive mothering” has emerged
among these same families.6 If high levels of primary
childcare time are accepted as an indicator of intensive
parenting, then an analysis of the relationships among
primary childcare time, working time, and SES can reveal whether high-SES mothers (and fathers) tend to
engage in intensive parenting, work long hours, or do
both. The other end of the SES spectrum is characterized by poverty. The welfare-to-work legislation of
1996 makes an analysis of poor families more relevant
because the legislation provides incentives for low-income single mothers of infants to gain and maintain
employment. Indeed, by 2003, when ATUS data collection began, a total of 20 States had imposed work
requirements on the mothers of infants who applied
for welfare.7 These requirements may have generated
reductions in the quantity of time parents have allocated to childcare as single mothers have striven to
expand paid working time.
Data
The ATUS was first administered in 2003; survey data
spanning 5 years are available and have been pooled for
this article.8 The ATUS sample is drawn from Current
Population Survey (CPS) respondents, and data from
the two surveys can be matched. The ATUS is administered approximately 2 to 4 months after the CPS,
and data are collected every day of the year except for
34
Monthly Labor Review • October 2009
a few holidays. Because of the delay between the administration of the CPS and that of the ATUS, for this article variables
are constructed from the ATUS whenever possible. The ATUS
response rate hovers around 53 percent, a rate similar to that of
other single-day time-diary studies administered over the telephone.9 The main survey instrument is a 24-hour “diary.” Individuals provide information, beginning at 4 a.m. “yesterday,” on
“what [they] were doing” during the following 24 hours. They
document the activities they did, where they were at the time,
and whom they were with. For cases in which people were doing more than one activity at the same time, they generally are
asked to document the activity that could be considered the
primary activity.
In the 2003–07 ATUS data, there are 2,612 households with
parents of infants under the age of 1 year at the time of survey
administration and 20,428 households with parents of dependent children aged 1 or older but below the age of 13. Thirteen
years old is the cutoff because data on childcare as a secondary
activity are not available for children at or above that age. Children may be biological offspring of the parent, may be stepchildren, may have been adopted, or may have a foster relationship
with the parent, and they must live in the household at least 50
percent of the time for the parent to be included in the sample.
Any household with one or more parents of both an infant and
an older child is counted as a household with infants and not as
a household with older children. There is no way to distinguish
between the quantity of time that a parent with both an infant
and child aged 1–12 spent with the infant and the quantity of
time the parent spent with the older child.
In 80 cases, an infant was residing in the household but the
respondent was not the infant’s parent and was instead the parent of one or more other children in the household; these cases
are retained in the sample but reclassified as involving parents
of older children since these parents may not have been responsible for infant care. Also, only 29 single fathers of infants
are found in the sample. Because of the small size of that group,
they are ignored in the analysis that follows.
There are reasons to be concerned about days when the
parent has no contact with the child. For coupled parents,
such days might occur relatively frequently when the other
parent takes responsibility for the child. But for single mothers who do not have another primary caregiver, the inclusion of days with no contact would not help researchers to
understand how single parents make time for their children.
Only four cases exist in which single mothers of infants had
no contact with their infants on the diary day; in 277 cases,
a single mother of one or more children aged 1–12 had no
contact with any of her children. For consistency all 281 observations are excluded from the analysis. As seems reasonable for understanding childcare arrangements, unmarried
partners are classified as coupled, as are spouses living in
the household.10
The sample of parents of infants comprises 1,007
partnered men, 1,227 partnered women, and 265 single
women. In regard to parents of older children, data are
available for 7,687 coupled fathers, 8,851 coupled mothers, and 3,097 single mothers. The data are weighted for
all of the analyses that follow in this article.11
Childcare time
Primary childcare time is the quantity of time that survey
respondents spent primarily doing activities that involved
care for their own dependent child or children. Time spent
caring for adults or other children is excluded. Although
the ATUS does not include a question concerning secondary activities in the main body of the survey, it does have
a supplementary question regarding the times when and
activities during which a child is “in [one’s] care,” which is
intended to mean either that the child is physically present or that the adult is otherwise able to monitor the child
and respond if necessary. The inclusion of this measure of
secondary care allows for a broader indicator of childcare
time and yields time estimates that are much higher than
those obtained from the collection of general data on secondary activities.12 Secondary childcare data are collected
only for parents with children under the age of 13, and, as
with primary childcare time, only time spent caring for
one’s own children is counted. Figures exclude time during which the child was sleeping. Sometimes, of course,
parents have an infant sleep in their bed in order that they
can be available for emergencies or breastfeeding while
the infant sleeps at night. If one views this type of sleeping
arrangement as a form of childcare, then childcare time
for parents of infants could be considered to be underestiTable 1.
mated.13 Secondary childcare time and primary childcare
time are mutually exclusive over the course of the 24-hour
reference day, so the estimates are summed to create a
measure of total childcare time.
It is reasonable to interpret primary childcare time as
involving more energy or greater concentration than secondary childcare time; thus, the amount of time during
which a parent is engaged primarily in childcare can be
taken as an indicator of the extent of “intensive parenting.”
In addition, childcare time can be interpreted as requiring
a greater expenditure of energy, a higher level of responsibility, or both if a partner or spouse is not present during
the activity. For example, a mother may be feeding a child
while the father helps with food preparation or cleanup;
even if the father does not help in the kitchen, he may be
available to answer the telephone or to call a doctor in
the event of an emergency. In circumstances such as these,
either the workload or level of responsibility involved in
childcare is lessened by the presence of a partner or spouse.
A measure of total solo childcare time is defined as total
childcare time minus primary and secondary childcare
time during which a partner or spouse is present.14 (Total
solo childcare time is composed of primary solo childcare
time and secondary solo childcare time.)
Total childcare, primary childcare, and total solo childcare figures are provided in table 1. These figures cover
coupled fathers, coupled mothers, and single mothers. The
data allow for comparisons between parents of infants
and parents of older children, and between weekdays and
weekends. Coupled fathers with infants spent about twice
as much time on primary childcare and around an hour
longer on total childcare as compared with coupled fathers
with children aged 1–12. Not surprisingly, coupled fathers
devoted more time to both primary and total childcare on
weekends, with about 4 additional hours on the average
Hours and minutes of childcare, parents of infants and of older children, 2003–07
Coupled fathers
Type of childcare and day
With youngest
With youngest
child under age 1 child aged 1–12
Total childcare, weekdays.....................
5:01
4:13
Total childcare, weekend days............
9:31
8:23
Primary childcare, weekdays...............
1:25
0:53
Primary childcare, weekend days......
1:52
1:02
Total solo childcare, weekdays...........
2:06
2:08
Total solo childcare , weekend days...
3:11
3:19
Sample size, weekdays......................
Sample size, weekend days.............
489
518
3,748
3,939
Coupled mothers
Single mothers
With youngest
child under age 1
With youngest
child aged 1–12
With youngest
With youngest
child under age 1 child aged 1–12
11:05
11:58
3:53
3:19
8:08
5:50
7:53
10:31
1:58
1:26
5:47
5:29
8:56
11:12
3:13
2:46
8:56
11:12
6:51
9:50
1:42
1:18
6:51
9:50
617
610
4,352
4,499
116
149
1,563
1,534
SOURCE: Weighted ATUS data.
Monthly Labor Review • October 2009 35
Parenting of Infants
weekend day for total childcare in comparison with the
average weekday. The total solo childcare figures, however,
reveal that most fathers’ childcare occurred with a spouse
or partner present. Indeed, on weekend days, over 6 hours
out of a total of 9.5 hours of total childcare time were
spent with a spouse or partner present.
On both weekdays and weekends, coupled mothers
with infants were engaged in primary childcare for almost
twice as long as coupled mothers with children aged 1–12.
Also in comparison with coupled mothers with older children, coupled mothers of infants spent over 3 more hours
on weekdays in total childcare time and around an hour
and a half longer on weekend days. Their total solo childcare time was over 2 hours longer on weekdays but was
only slightly longer on weekend days.15
Reviewing the figures for coupled mothers of infants
and coupled fathers of infants reveals an obvious difference
in trend between the sexes. Taking coupled fathers’ childcare time as a percentage of the sum of coupled fathers’ and
coupled mothers’ childcare time yields a high of 44.3 percent for total childcare time on weekends and a low of 20.5
percent for total solo childcare time on weekdays. There is
no evidence of reciprocal agreements between coupled parents. Because more fathers than mothers work outside the
home and it is more common to work on weekdays than on
weekends, reciprocity would require that, in general, fathers
take the lead on weekend childcare and mothers shoulder
more of the burden during the week. However, none of the
evidence fits; on the basis of any of the three measures—
primary childcare time, total childcare time, or total solo
childcare time—coupled mothers perform at least 1 additional hour of childcare on weekend days.
As is the case with coupled mothers, single mothers’
parenting of infants is associated with more childcare
than their parenting of older children. This is true for all
of the three aforementioned measures of childcare time
and for both weekdays and weekend days. Compared with
coupled mothers of infants, single mothers allocate less
time to primary childcare and total childcare. Differences
range from a low of 33 minutes for primary childcare time
on weekends to over 2 hours for total childcare time on
weekends. The fact that coupled mothers allocate more
time to childcare than single mothers could imply that
the spouses and partners of coupled mothers serve as a
resource—whether by working and earning money or by
helping around the house or with errands—freeing up additional time for the mothers to engage in childcare; it
also could mean that single mothers are more reliant on
childcare provided by a babysitter, a nanny, a relative, or
a friend. By contrast, the pattern is reversed in regard to
36
Monthly Labor Review • October 2009
solo childcare: the amount of time spent by single mothers
is greater than that spent by coupled mothers of infants.
Concerning total solo childcare, there is a 48-minute difference between single mothers and coupled mothers on
weekdays and a difference of over 5 hours on weekend
days. If one chooses to consider the quantity of total solo
childcare time that a person spends to be the best indicator of effort or responsibility, then single mothers’ larger
amount of total solo childcare time suggests that they bear
a heavier burden than coupled mothers.
Regarding statistical testing for differences across parents of infants and of older children, note that parents of
infants are considered to be those whose youngest child is
younger than 1 year old. This means that many parents of
infants also have older children present in the household.
Table 2 displays results of regressions of the three childcare time measures against variables for both the presence
of an infant and the presence of two or more children
(one, both, or none of whom may be infants). As reported
in the table, in all but 2 of the 18 relevant regressions the
estimated effect of an infant is positive and the t-statistic
is significant at the 1-percent level; the t-statistic is not
significant for two groups only: coupled fathers engaging in solo childcare on weekdays and those doing so on
weekends. In 11 of the regressions, the presence of two or
more children also is associated with significantly elevated
levels of childcare time. For every group of parents with
infants except for coupled fathers engaging in solo childcare time on weekdays and those doing so on weekends,
the estimated addition to childcare time for an infant is
at least twice as large as the effect of having two or more
children.16
Allocating time to primary childcare
The allocation of time to primary childcare is studied by
comparing broad categories of time use across coupled
mothers, coupled fathers, and single mothers of infants
and of older children. Although parents of infants could
be compared with nonparents, doing so would not facilitate an understanding of whether parenting patterns
diverge when an infant is involved. The ATUS has 17 timeuse categories, with sleep and primary childcare serving
as subcategories. To simplify table 3, care for one or more
children from outside the household is combined with
care for any adult. In addition, professional and personal
care services, household services, and government services
and civic obligations are combined into one category and
labeled as “use of services”; socializing, relaxing, and leisure are combined with sports, exercise, and recreation
pay—but that difference is not significant.
Coupled mothers with infants spent around
2 more hours per day on primary childcare
Coupled
Coupled
Single
than did coupled mothers with children
fathers
mothers
mothers
aged 1–12. Coupled mothers with infants
Type of childcare and day
Two or
Two or
Two or
spent almost 1 fewer hour per day working
Infant
more
Infant
more
Infant more
for pay, 16 fewer minutes engaging in sports
effect children effect children effect children
effect
effect
effect
and leisure time, and also less time—but not
as much less—on personal care, travel, spiri1
1
1
1
Total childcare, weekdays.................... 147.7
–4.5
199.4
65.4
123.1
45.2
1
1
1
1
tual and volunteer activities, and education. In
Total childcare, weekend days........... 171.9
28.4
88.8
26.0
80.6
12.3
1
1
1
1
Primary childcare, weekdays.............. 131.6
4.1
117.5
4.3
89.3
25.4
contrast to coupled fathers, an examination of
1
1
2
Primary childcare, weekend days.... 150.7
3.9
112.9
6.2
85.6
15.6
1
1
1
1
the official ATUS time-use categories reveals
Total solo childcare, weekdays..........
–2.4
0.4
147.5
66.1
123.1
45.2
1
2
1
1
Total solo childcare, weekend days..
–4.0
29.4
24.8
38.7
80.6
12.3
that the sports and leisure result is due to significantly less time devoted to sports, exercise,
Sample size, weekdays..................
4,235
4,967
1,677
Sample size, weekend days........
4,455
5,107
1,681
and recreation, and not to spending less time
with socializing, relaxing and leisure activities.
1
Statistically significant at p<.01.
Like the coupled fathers of infants, coupled
2
Statistically significant at p<.05.
mothers of infants—in comparison with their
NOTE: The results are from linear regressions with minutes of childcare as the dependent
variable, and with dummy variables for the presence of an infant and the presence of at least
counterparts with older children—spent sigtwo dependent children in the household.
nificantly less time doing volunteer activities
SOURCE: Weighted ATUS data.
but not significantly less time engaged in religious or spiritual activities.
The time-financing analysis suggests that around half
to make the “sports and leisure” category; and volunteer of the additional childcare time that coupled mothers
activities are combined with religious and spiritual activi- with infants spent in comparison with coupled mothers of
ties. In total, there are 14 types of primary activities that older children was generated by spending less time workappear in the table.
ing for pay. To look more closely at the effects of opting
The table reports time-use statistics for parents of in- out per se, primary childcare time is regressed against usual
fants as compared with parents of older children, with weekly working hours for the subsamples of parents of
significant differences taken from the results of linear re- infants. The advantage of using figures for usual weekly
gressions for the effect of an infant on the relevant time hours is that they yield working time estimates for emcategory for each gender-family group. The regressions ployed respondents across both working and nonworking
also control for the presence of two or more dependent days, whereas time-diary figures on working hours are
children in the household. Coupled fathers with infants only available for working days. The coefficients can be
devoted 36 more minutes to primary childcare than did used to simulate the number of additional weekly minutes
fathers with older children, additional time which appears of primary childcare time produced by a 1-hour reducto have come primarily from spending around 13 fewer tion in weekly working time. The 1-hour reduction is esminutes per day on housework and 14 fewer minutes on timated to add 8 additional minutes of primary childcare
sports and leisure activities. Fathers of infants also spent for coupled fathers, with an identical figure of 8 minutes
less time—not as much less, but still significantly less— for coupled mothers. These figures are almost certainly
on personal care and on spiritual activities and volunteer subject to selection biases to the extent that mothers and
work. An examination of the ATUS time-use categories fathers choose work and childcare hours simultaneously,
behind these results reveals that, in comparison with with those holding a relative preference for childcare percoupled fathers of older children, coupled fathers of in- forming more childcare and less paid work and, by the
fants spent significantly less time engaging in socializing, same token, those with a relative preference for employrelaxing, and leisure activities as well as significantly less ment performing less childcare and more paid work. The
time volunteering, without allocating a significantly dif- results nonetheless echo the conclusion from historical
ferent amount of time to sports, exercise, and recreation or data that the entry of mothers into the labor force had
to spiritual and religious activities. It appears that fathers only small effects on primary childcare time.17
with infants spent 18 fewer minutes per day working for
These data also, however, leave a puzzle regarding why
Table 2. Results from regressions of childcare measures against variables for
presence of infant and for presence of two or more children, 2003–07
Monthly Labor Review • October 2009 37
Parenting of Infants
Table 3.
Hours and minutes of primary activities, parents of infants and of older children, 2003–07
Coupled fathers
Type of activity
With youngest
child under age 1
With youngest
child aged 1–12
Coupled mothers
With youngest
child under age 1
With youngest
child aged 1–12
Primary childcare ...............................
Sleep..........................................................
Personal care.........................................
Housework.............................................
Care for others......................................
Work..........................................................
Education................................................
Consumer purchases.........................
1
1:32
8:10
2
0:32
1
1:07
0:07
5:22
0:08
0:22
0:56
8:08
0:35
1:20
0:07
5:40
0:05
0:19
1
3:44
8:29
1
0:38
2:35
0:08
1
1:55
2
0:05
0:32
1:49
8:29
0:44
2:44
0:07
2:51
0:10
0:35
Use of services......................................
Eating and drinking............................
Sports and leisure................................
Spiritual and volunteer ....................
Telephone calls.....................................
Traveling..................................................
0:05
1:09
2
3:37
1
0:11
0:01
1:25
0:04
1:08
3:51
0:16
0:02
1:25
0:07
1:01
1
3:13
1
0:11
0:05
1
1:08
0:06
1:03
3:29
0:19
0:05
1:19
Sample size........................................
1,007
7,687
1,227
8,851
Statistically significant at p<.01.
Statistically significant at p<.05.
NOTE: Significance tests are conducted by use of linear regressions with an
1
Single mothers
With youngest
With youngest
child under age 1 child aged 1–12
3:04
9:34
2
0:43
2
1:40
1
0:02
1
2:19
0:21
0:30
1:35
8:50
0:50
1:59
0:08
3:22
0:17
0:28
0:08
0:44
3:38
1
0:05
0:06
1
0:58
0:08
0:52
3:43
0:12
0:08
1:18
265
3,097
1
1
2
infant dummy variable, and they control for having at least two children.
2
there would be any pressure on mothers of infants to opt
out. An answer is provided by regressing total childcare
time and total solo childcare time against usual weekly
working hours among parents of infants. Relevant regressions suggest that for coupled fathers, a 1-hour reduction
in weekly work hours results in 11 additional minutes of
total solo childcare and 22 additional minutes of total
childcare. For coupled mothers, the analyses imply that
the same reduction in weekly work hours results in 35 additional minutes of total solo childcare and 42 additional
minutes of total childcare. By implication, the motivation
for new mothers to opt out might be attributed to how
much value they ascribe to secondary childcare time.
Single mothers of infants spent 90 more minutes on primary childcare than did single mothers of older children.
That time came primarily from spending significantly less
time doing paid work. Single mothers of infants spent approximately 1 fewer hour working, and they also spent less
time on travel, spiritual and volunteer activities, eating and
drinking, personal care, and care for adults and other children. As with the coupled mothers, note that the amount
by which the working time of single mothers with infants
is less than the working time of single mothers with older
children is smaller than the amount by which the primary
childcare time of single mothers is greater than the primary childcare time of single mothers with older children.
As was the case for both coupled fathers and mothers,
the lesser quantity of time that single women with infants
38
Monthly Labor Review • October 2009
SOURCE: Weighted ATUS data.
spent doing spiritual and volunteer activities can be traced
primarily to spending less time volunteering. The greater
quantity of time spent caring for others among single
mothers of older children might, at least in some cases,
flow from networks of care constructed by single mothers
such that they receive childcare from other family members at some times and reciprocate by providing childcare
to them at other times.18
As with the coupled mothers, single mothers’ childcare
time is regressed against usual weekly working time to
simulate the additional weekly minutes of childcare generated by a 1-hour reduction in weekly work hours, again
with a restriction of the sample to parents of infants. The
1-hour reduction in working time is associated with only
a 5-minute increase in primary childcare time, but with
a 35-minute expansion of total and total solo childcare.
Again, the results suggest that trade-offs between work
and childcare concern secondary childcare more than primary childcare.
Perhaps surprisingly, single mothers of infants devoted
44 more minutes to sleep than single mothers of children
aged 1–12. It is possible that the additional sleep is related
to the exhaustion associated with being the lone care provider for an infant. But it is also possible that at least some
of this additional sleep occurs with the single mothers in
the same beds as their infants; it is possible that, on some
days, some of the mothers remain in bed longer in order to
avoid waking the infant, go to sleep earlier, or nap at other
times during the day with the infant. “Cosleeping” makes
particular sense for single mothers because usually there
is no one else already present in bed at night. The ATUS
provides no information on with whom respondents sleep
or on childcare time while the child is asleep, so no direct
information is available. However, a proxy for exhaustion
can be constructed.
An indicator of exhaustion is calculated as the number
of times that parents end a sleep episode between midnight and 4 a.m. and begin a new sleep episode prior to 4
a.m., after excluding respondents performing shiftwork.19
Among the parents of infants, coupled fathers averaged
0.12 interruption from 12 a.m. to 4 a.m., coupled mothers 0.33, and single mothers 0.22. By way of comparison,
coupled fathers with older children reported an average of
0.07 sleep interruption, with comparable figures of 0.09
for coupled mothers and 0.08 for single mothers. For
the parents of infants experiencing sleep interruptions,
the mean time spent awake is 36.3 minutes for coupled
fathers, 35.1 minutes for coupled mothers, and 36.8 minutes for single mothers. Mothers devoted well over half of
this time to childcare: coupled mothers spent 73.2 percent (25.7 minutes) and single mothers spent 81.8 percent
(30.1 minutes) of the time awake on childcare, compared
with coupled fathers, who spent 54.0 percent (19.6 minutes) of the time on childcare.
These figures provide some reason to believe that parents of infants are often exhausted. Further, the interruptions affected coupled and single mothers far more often
than coupled fathers. However, the figures do not provide
a complete explanation for the elevated amount of sleeping time reported by single mothers of infants: relative
to coupled mothers of infants; the single mothers indeed
spent more time on childcare when awakened in the middle of the night, but they woke less frequently.
SES and childcare, paid work, and housework
The final analysis of this article divides the parents of
infants into three subgroups—high, middle, and low
SES—and compares these subgroups’ levels of childcare,
housework, and working time. Typically, SES is measured
using a variable or combination of variables related to education, income or wealth, and occupation. For example, an
individual with a college or university degree, with high
income, and with a managerial or professional occupation
would be classified as high SES, whereas an individual living in poverty would be considered to be of low SES.20
Occupation is ignored in the present analysis because the
resources associated with high SES arguably allow some
mothers to opt out of employment, in which case they
may not report an occupation and would be misclassified
as a result. Instead, the combination of family income of
at least $60,000 per year and the respondent holding a
bachelor’s degree serves as a proxy for high SES. In this
article, the low-SES group is defined by family income
of less than $15,000 for coupled parents and of less than
$12,500 for single mothers.21 Because the income data are
categorical, there is no obvious way to correct for inflation
across survey years.
SES is related to many aspects of an individual’s life,
and the parents of infants are no exception. For example,
SES is closely connected to marital status. The unweighted
sample size for this analysis includes only six single mothers reporting high SES, so this group is necessarily ignored
for the analysis. Further, only 6.4 percent of coupled fathers and 8.6 percent of coupled mothers were living in
poverty, whereas over 50 percent of single mothers were
living in poverty. Because so few coupled fathers were living in poverty, that group also is ignored below. Given
that high-SES parents tend to delay childbearing, it is
also not surprising that among coupled parents of infants,
Table 4. Selected characteristics of parents of high, [middle],
and (low) socioeconomic status, 2003–07
Characteristic
Coupled
fathers
Coupled
mothers
Mean number of children
1.95
[2.05]
–
1
Percent employed..................
1
98.1
[94.4]
–
1
Mean age (in years)...............
1
Manager/professional,
percent...................................
34.7
[31.5]
–
80.9
[24.6]
–
1
Sample size.........................
314
[548]
(59)
1
Statistically significant at p<.01.
2
Statistically significant at p<.05.
Single
mothers
1.00
[2.21]
(2.18)
–
[2.22]
(2.59)
68.9
[46.0]
(37.8)
–
[66.4]
1
(38.4)
32.5
[28.5]
1
(25.6)
–
[24.3]
[24.4]
56.4
[16.4]
1
(4.6)
–
[6.4]
2
(2.3)
363
[661]
(96)
6
[107]
(121)
1
1
NOTE: Significance tests for robust t-statistics in linear regressions with
dummy variables for high- and low-SES groups. Dash indicates datum not
reported because of small sample size.
SOURCE: Weighted ATUS data.
Monthly Labor Review • October 2009 39
Parenting of Infants
people of high SES were almost 7 years older on average
than their counterparts living in poverty. (See table 4.)
Further, even though occupation was not used to indicate SES, high-SES parents disproportionately fill managerial and professional occupations: 80.9 percent of the
coupled fathers and 56.4 percent of the coupled mothers
were working in these occupations. Significantly less than
10 percent of poor coupled mothers and fathers or single
mothers held such positions. Consistent with the “ideal
worker” norm that appears to affect high-SES individuals, high-SES coupled fathers and coupled mothers were
significantly more likely to be employed; for example,
high-SES coupled mothers of infants were almost twice as
likely to be employed as their low-SES counterparts (68.9
percent compared with 37.8 percent, respectively).
Table 5 provides information on the three indicators of
childcare time, on housework, and on working time. There
are data for working time on the reference day—including
both people with jobs and those without—as well as data
on usual weekly work hours. The sample is broken down
by gender-family status and by SES, and is restricted to
parents of infants. Tests for differences use ordinary least
squares regressions, with various time measures serving
as the dependent variables and dummy variables for high
and low SES as the independent variables.
With regard to coupled parents and primary childcare, fathers of high SES recorded significantly more time
for primary childcare, reporting an additional half-hour
relative to the middle group. Coupled mothers exhibit the
same pattern and significant differences: those of high SES
reported 41 more minutes of primary childcare time than
did those of middle SES, and those of middle SES reported
over 69 more minutes than the low-SES group. These differences in primary childcare time between groups of fathers and among groups of mothers are consistent with
the norm of intensive mothering among high-SES mothers and also consistent with the hypothesis of intensive
parenting among high-SES fathers. Total childcare time
figures yield a similar pattern for coupled fathers, although
the differences are not significant. Total childcare time for
coupled mothers was lower for the low- and high-SES
groups than for the middle group, by around a half-hour.
Most high-SES mothers do not have as much time to devote to their children as other mothers, but they tend to
spend that time more intensively—as suggested by significantly higher levels of primary childcare time—than
other mothers. The pattern of total solo childcare among
mothers mirrors that of total childcare.
“Housework time” spent by coupled fathers was longer
for those of high SES than for those of middle SES, but
40
Monthly Labor Review • October 2009
the difference is not significant. High-SES coupled mothers
recorded significantly lower levels of housework than other
mothers. Less time spent doing housework can be expected
to mean that someone was paid to do the work or that some
of these tasks were done by a partner or spouse.
Time-diary figures for coupled fathers’ working time
yield no statistically significant differences between fathers of high SES and fathers of middle SES, though the
high-SES fathers reported a few additional minutes of
working time. Reports of usual weekly work hours reveal
statistically significant differences in the expected direction: high-SES fathers of infants worked over 3.5 hours
per week longer than their counterparts of middle SES.
Both the diary figures and the weekly reports suggest that
high-SES coupled mothers of infants tend to work longer
hours than other mothers of infants. In sum, the results for
couples are consistent with pressures on high-SES parents
both to be active parents and to work long hours. Mothers
in this group generate at least part of their childcare time
through reductions in housework. Nonetheless, the results
Table 5. Hours and minutes of childcare, housework, and paid
work; means for high, [middle], and (low) SES, 2003–07
Coupled
fathers
Coupled
mothers
Single
mothers
2:01
[1:31]
–
4:19
[3:38]
1
(2:29)
–
[2:59]
(3:13)
Total childcare..................................
6:59
[6:22]
11:05
[11:32]
(11:00)
–
[8:42]
2
(10:42)
Total solo childcare........................
2
7:29
[7:44]
2
(6:29)
–
[8:42]
2
(10:42)
Housework........................................
1:17
[1:12]
–
2
2:09
[2:47]
(2:49)
[1:34]
(1:55)
–
Working time on diary day........
5:19
[5:16]
–
2
2:23
[1:41]
(1:48)
–
[2:35]
(1:50)
23:12
[13:54]
(11:12)
–
[19:48]
1
(11:30)
363
[661]
(96)
6
[107]
(121)
Activity
Primary childcare............................
1
2:57
[2:22]
–
Usual weekly working time.......
Sample size.................................
1
2
45:48
[42:12]
–
1
314
[548]
(59)
1
1
Statistically significant at p<.01.
Statistically significant at p<.05.
NOTE: Significance tests are conducted by use of linear regressions with
dummy variables for high- and low-SES groups. Dash indicates datum not
reported because of small sample size.
SOURCE: Weighted ATUS data.
fit the hypothesis that high-SES mothers are often caught
between extreme expectations regarding their careers on
one hand and childrearing on the other.
For single mothers, living in poverty is associated with
2 more hours of total childcare time and 2 more hours
of total solo childcare time in comparison with being of
middle SES. That difference cannot be accounted for by a
divergence in housework time, since single mothers living in poverty also reported elevated levels of housework
(although the difference is not significant). Lower levels
of working time seem to be a contributing factor. Daily
working time was an insignificant 45 minutes shorter, but
usual weekly work hours were a significant 8 hours shorter
for those living in poverty.
This result (8 fewer hours of working time) fits the findings reported in the previous section regarding coupled
mothers of infants spending less time doing paid work
and more time caring for children than coupled mothers
of older children and, similarly, single mothers of infants
spending less time doing paid work and more time caring for children than single mothers of older children. The
difference between coupled mothers and single mothers is
that less working time is closely associated with poverty
for single mothers but not for coupled mothers. Table 5
reveals significantly lower weekly work hours for poor
single mothers of infants but not for poor coupled mothers of infants. Looked at differently, the simple correlation
between poverty status and usual weekly hours is –0.105
for coupled mothers, but –0.312 (a figure with a larger
absolute value) for single mothers.
THE ANALYSIS IN THIS ARTICLE SUPPORTS THE
GENERAL CLAIM that parents of infants exhibit divergent patterns of time use compared with the parents of older
children, confirming that infants are given distinct treatment.
Relative to mothers of older children, both coupled and
single mothers of infants devoted at least an additional hour
per day to childcare, whether measured by primary childcare
or total childcare time. In comparison with coupled mothers
of older children, coupled mothers of infants recorded over
3 additional hours per day of total childcare on weekdays. In
addition, coupled fathers with infants devoted more time to
childcare than coupled fathers with children aged 1–12, although the differences in primary childcare and total childcare are smaller than they are for coupled mothers, ranging
from a low of 33 additional minutes of primary childcare on
weekdays to a high of 68 additional minutes of total childcare on weekends. These findings suggest that, on the whole,
fathers have become more involved with infants in recent
decades; however, childcare is still marked by substantial in-
equality between the amount of time spent by men and the
amount spent by women.
Total solo childcare time spent by single mothers of infants is around an hour longer than that spent by coupled
mothers on weekdays, and over 5 hours longer on weekend
days. These differences highlight the difficulties involved in
parenting an infant alone. However, it is important to note
that the solo childcare figures exclude time that parents
spent caring for children together, and that time also appears to be valuable to families and to society.
The parents of infants financed the additional time they
need for childcare—that is, as compared with the parents
of older children—using a variety of mechanisms. Coupled
fathers and mothers of infants, as well as single mothers
of infants, all tended to spend less time on personal care
and volunteer activities. The coupled fathers spent less time
with housework and sports and leisure as well to free up
time for primary childcare. Employment played a more
significant role for coupled and single mothers; each group
significantly scaled back working time and, perhaps relatedly, travel time.
Surprisingly, single mothers of infants not only provided more childcare relative to their counterparts with
older children, but also reported an additional 44 minutes
of sleep. Indirect indicators suggest that both coupled and
single mothers may experience exhaustion that is, in part,
due to frequent interruptions of sleep at night when infants
are present. However, single mothers were interrupted less
frequently than coupled mothers, so this hypothesis is inconclusive. It is also possible that the expanded sleeping
time of single mothers is related to sleeping in the same
bed as one’s child as a form of childcare, although this
practice cannot be identified with the ATUS data.
Among the parents of infants, spending one fewer hour
at work is associated with only minor increases in primary
childcare time, regardless of the sex of the parent or the
presence of a partner. Working one fewer hour is associated
with much larger increases in total childcare and total solo
childcare time: an additional 22 minutes of total childcare
for coupled fathers, 42 minutes for coupled mothers, and
35 minutes for single mothers. These findings suggest that
pressures on coupled mothers of infants to opt out of employment are related to the value of time during which a
child is “in [one’s] care” more so than to primary childcare
time. Nonetheless, it is important to note that most of the
high-SES coupled mothers were employed and that they
worked longer hours in comparison with any other group
of coupled or single mothers. Contrary to media depictions,22 coupled mothers of high SES do not appear to be
leading an “opt-out revolution.”
Monthly Labor Review • October 2009 41
Parenting of Infants
Time-use patterns diverge across lines of socioeconomic status among the parents of infants. High-SES coupled
fathers, who tend to have the greatest financial resources,
spent roughly 30 percent more time on primary childcare
relative to their counterparts of middle SES, while highSES coupled mothers spent almost twice as much time engaging in primary childcare as their poor counterparts did.
Again, these findings are consistent with the existence of
a norm of intensive mothering among high-SES mothers
that has partially evolved to a norm of intensive parenting,
cutting across the gender line. A large part of the additional primary childcare time that high-SES parents spent
appears to have been obtained by reducing “in [one’s]
care” time. The high-SES fathers tended to spend more
time doing housework than middle-SES fathers, while the
high-SES mothers engaged in less housework than other
mothers. High-SES parents of infants exhibited long work
hours, particularly in terms of usual weekly hours.
The same pressures to opt out that appear to confront
many coupled mothers also appear to affect many single
mothers. In both cases, reductions in work hours may provide the most direct route to an expansion of childcare
time during the first year of a child’s life. There is, however,
a crucial difference between single mothers and coupled
mothers. Single mothers with reduced or zero work hours
indeed devoted more time to childcare, but the price was
a substantially greater risk of poverty for themselves and
their children.
Notes
ACKNOWLEDGMENTS: The author thanks Ya-Ning Lee for research assistance, and Laurie Bonjo, Nancy Folbre, Elizabeth Handwerker, Jennifer Hook, Heather Joshi, Anne Polivka, Jay Stewart, and
Mark Wooden for helpful comments.
1
See Jody Heymann, Alison Earle, and Jeffrey Hayes, The Work,
Family, and Equity Index: How Does the United States Measure Up?
(Montreal, QC, The Institute for Health and Social Policy, 2007), on
the Internet at www.mcgill.ca/files/ihsp/WFEI2007.pdf (visited
Nov. 14, 2008).
2
See Michael Baker and Kevin Milligan, “How Does Job-Protected Maternity Leave Affect Mothers’ Employment?” Journal of Labor
Economics, October 2008, pp. 655–91.
3
See Suzanne M. Bianchi, John P. Robinson, and Mellisa A. Milkie, Changing Rhythms of American Family Life (New York, Russell Sage
Foundation, 2006), p. 63.
For an example of an article which finds that levels of fathers’
involvement increase as children age, see Jeffrey J. Wood and Rena
L. Repetti, “What gets dad involved? A longitudinal study of change
in parental child caregiving involvement,” Journal of Family Psychology,
March 2004, pp. 237–49. However, W.J. Yeung, J.F. Sandberg, P.E. Davis-Kean, and S.L. Hofferth, “Children’s Time with Fathers in Intact
Families,” Journal of Marriage and Family, February 2001, pp. 136–54,
find fathers devoting more time to children aged zero to two years.
4
For example, Daniel S. Hamermesh, Workdays, Workhours, and
Work Schedules (Kalamazoo, Mich., Upjohn Institute, 1996), p. 29;
finds men working 1.85 percent more days per week and 3.43 percent
more hours per day when they have children under the age of 3 years,
in comparison with when they do not have children younger than 3.
Bianchi and others, Changing Rhythms, p. 47, find fathers with infants
working around 0.8 more hour per week relative to fathers whose children are all over the age of 6 years.
5
6
For information on long hours and the ideal worker norm, see
Joan Williams, Unbending Gender (New York, Oxford University Press,
2000); or Robert Drago, Striking a Balance (Boston, Dollars and Sense,
2007). For information on the norm of intensive mothering, see Sharon
Hays, The Cultural Contradictions of Motherhood (New Haven, Conn.,
Yale University Press, 1996).
42
Monthly Labor Review • October 2009
7
See Jane Waldfogel, What Children Need (Cambridge, Mass.,
Harvard University Press, 2006).
8
Much of the information in this section is drawn from the American Time Use Survey User’s Guide (U.S. Census Bureau and U.S. Bureau
of Labor Statistics, 2008).
9
30.
For example, see Bianchi and others, Changing Rythms, pp. 27–
A check of the 2006 data for married and unmarried partners
reveals only one male same-sex couple and no female same-sex couples
who also were parents of infants, so the distinction between same-sex
couples and opposite-sex couples is ignored in this article.
10
11
The weights correct for demographic characteristics including
race/ethnicity and income, and for the oversampling of weekend days
in the survey. The relevant weights are TU06FWGT for the 2003–05
samples and TUFINLWGT for the 2006 and 2007 data.
12
See Mary Dorinda Allard, Suzanne Bianchi, Jay Stewart, and
Vanessa R. Wight, “Comparing childcare measures in the ATUS and
earlier time-diary studies,” Monthly Labor Review, May 2007, pp.
27–36.
13
Respondents’ sleep time is excluded from ATUS estimates of
“child in care” time because respondents themselves were inconsistent
in reporting child-in-care time from when they were asleep. The exclusion remedies this inconsistency.
14
The total solo childcare measure does not exclude time when
grandparents or other family or friends are present.
15
When contemplating the validity of the ATUS data, it is reassuring to discover that, across weekdays and weekends, most coupled
mothers’ total childcare time minus their total solo childcare time was
approximately equal to the quantity of time that the respective fathers
reported engaging in childcare in conjunction with their partner. In a
parallel, most coupled fathers’ total childcare time minus their total solo
childcare time was approximately equal to the quantity of time that the
respective mothers reported engaging in childcare in conjunction with
their partner. This is particularly impressive given that the samples of
coupled fathers and mothers are independently collected.
16
Surprisingly, there are no obvious efficiency gains in terms of
childcare time for parenting both infants and other children simulta-
neously. If there were, then adding interaction terms for parents of one
or more infants and parents of at least two children to the regressions
would yield negative effects. Yet the addition of the interaction terms
yields only one significant effect in the 18 regressions: coupled mothers
of infants and of other children devote an additional 53 minutes to solo
childcare on weekdays. (Results are available from the author.) Further
analysis suggests this additional time may come from reductions in
work hours; regressing usual work hours against the same independent
variables for coupled mothers reveals significantly lower weekly work
hours when both an infant and other children are present, with the
divergence estimated to be 4.2 hours per week.
17
See Suzanne M. Bianchi, “Maternal Employment and Time
with Children: Dramatic Change or Surprising Continuity?” Demography, November 2000, pp. 401–14.
18
For examples of such networks, see Anita I. Garey, Weaving Work
and Motherhood (Temple University Press, Philadelphia, 1999), pp.
89–102.
19
As is standard, respondents classified as performing shiftwork
are those who report a majority of working time on the diary day outside of the hours between 8 a.m. and 4 p.m.
For more information see, for example, John Iceland and Rima
Wilkes, “Does Socioeconomic Status Matter? Race, Class, and Residential Segregation,” Social Problems, May 2006, pp. 248–73.
20
21
The ATUS-CPS family income data are placed into the following
categories: less than $10,000, $10,000 to $12,499, $12,500 to $14,999,
and $15,000 to $19,999. For the year 2007, the U.S. Census Bureau
defines poverty for a single parent with one child to be associated with
household income of less than $14,291, and poverty for a couple with
one child to be associated with household income of less than $16,689.
Although one could use the $15,000 cutoff for single mothers, the
$12,500 figure serves to make poverty groups more comparable across
the single and couple samples, given that the income needs of couples
should be greater. However, changing the single-mother poverty cutoff
to $15,000 or raising the middle-class income cutoff from $60,000 to
$75,000 leaves the general pattern of results unchanged. See the U.S.
Census Bureau, “Poverty Thresholds 2007,” at www.census.gov/hhes/
www/poverty/threshld/thresh07.html (visited Oct. 9, 2009).
See Pamela Stone, Opting Out? Why Women Really Quit Careers
and Head Home (Berkeley, Calif., University of California Press, 2007),
pp. 3–4.
22
Monthly Labor Review • October 2009 43
Unemployment Insurance Benefits
Unemployment insurance recipients
and nonrecipients in the CPS
Data from unemployment insurance supplements to the Current Population
Survey show that the percentages of unemployed people who applied
for and received UI benefits vary by reason for unemployment; the data
also reveal that most people who did not file for benefits believed
they were not eligible for them
Wayne Vroman
Wayne Vroman is a PhD
economist at the Urban
Institute. E-mail:
wvroman@urban.org
44
T
he unemployment insurance (UI)
program in the United States consistently compensates less than
half of all unemployed workers. The low UI
recipiency rate1 could reflect such diverse
factors as accurate worker perceptions of
ineligibility in certain State programs in
which eligibility is for the most part limited to people who have lost their job, poor
understanding of program eligibility rules
among eligible people, or voluntary decisions among the unemployed not to apply.
Distinguishing among the various possible
explanations is important in assessing the
effectiveness of the UI program.
Each month, the U.S. Census Bureau
conducts the Current Population Survey
(CPS), which is a survey of a nationally
representative sample of U.S. households.
In 4 of the past 30 years, a supplement to
the CPS has queried unemployed people
about applications for and receipt of UI
benefits.2 Although the supplement was
administered multiple times in three of the
four years, annual estimates were calculated
for each of the years; thus, this article refers
to “the supplement of 2005,” for example,
to refer to all the UI supplement data collected during multiple months throughout
Monthly Labor Review • October 2009
the year. Unlike UI administrative data, which
pertain just to applicants and recipients, the data
from the CPS supplements also cover unemployed nonapplicants and nonrecipients. Three
of the four UI supplements posed questions to
the unemployed about their reasons for not filing for or not receiving UI benefits. Responses
to these “reason” questions are helpful for understanding why UI recipiency rates are so low.
This article summarizes findings from the most
recent UI supplement in the CPS, which was
conducted during 2005. Selected results from
the three earlier supplements—of 1976, 1989,
and 1993—also are noted. In addition, the
article draws from a project report published
this year by the Employment and Training
Administration.3
Two principal findings are suggested by
the CPS data. (1) In regard to UI benefits, application rates and recipiency rates vary systematically according to people’s reasons for
unemployment. For example, “job leavers”
often perceive they are ineligible because of
the circumstances of their job separation (they
may have quit their job, for example), whereas
labor force reentrants commonly believe their
lack of recent work experience makes them ineligible. People on temporary layoff frequently
do not apply for benefits because they expect
to be recalled soon. Additionally, factors such as age,
duration of unemployment, and State of residence
also are correlated with the decision to apply or not
to apply for benefits. (2) The most common reason for
not applying for UI benefits is the belief that one is
not eligible for them; the fact that this belief is fairly
widespread is the primary cause of the low overall UI
benefit recipiency rate.
The 2005 UI supplement
In 2005 the CPS unemployment insurance supplement
was administered in four separate months ( January, May,
July, and November) to unemployed people in outgoing
rotation groups, which are groups of individuals who are
in their 4th or 16th month as part of the sample. The
eight supplemental questions were administered at the
same time as the regular survey questions. The supplemental questions asked about application for UI benefits
since the last job, receipt of UI benefits—whether the person had received benefits anytime since the last job and
whether the person had received benefits anytime during
the previous week—the main reason for not applying
for or not receiving benefits, exhaustion of benefits, and
union membership.4
The supplemental sample had 3,033 unemployed
persons. The Census Bureau developed weights for this
sample in order that it be representative of annual unemployment in 2005. Usable responses to the application and recipiency questions were obtained from 2,849
persons. Most of the analysis in this article is based
upon these persons.
Summary of application and recipiency rates
In 2005, 34.8 percent of the unemployed applied for
UI benefits, a figure that closely approximates the corresponding statistic in the UI program data.5 Table 1
displays data on applications for UI benefits, showing
the percentage of unemployed people who applied
for benefits in 2005 by sex, age, reason for unemployment, and duration of unemployment. Each entry in
the table shows the percentage of unemployed people
who applied for UI benefits since leaving their last
job. Applicants are included in the data regardless of
whether or not they actually were qualified to apply
for UI benefits.
For each of the four variables included in table 1, the
patterns of UI application rates match those found in UI
program data. Application rates rise sharply with age:
the rate is 14.0 percent of women and 13.1 percent of men
aged 16–24, as compared with 46.7 percent of women and 49.6
percent of men 45 and older. The overall application rates of
men and women were quite similar—33.5 percent for women
and 35.9 percent for men.6 Among job leavers and “reentrants,”
women were slightly more likely to apply than men.
“Job losers” (that is, people who have lost their jobs) were
about three times more likely to file for benefits than job leavers
or reentrants. They were also, on the whole, considerably more
likely to be eligible for benefits than jobs leavers or reentrants.
As shown in table 1, the application rate for job losers was 50.7
percent, compared with 18.7 percent for job leavers and 15.4
percent for reentrants. Since the UI program is intended mainly
to compensate those who lose jobs through no fault of their
own, the fact that job losers have a much higher application
rate than job leavers and reentrants is to be expected. However,
the low overall application rate among job losers (roughly 50
percent) raises questions.
It should also be noted that application rates and recipiency
rates vary widely across geographic areas. The aforementioned
Employment and Training Administration report from this
year examines State-level variation and finds that patterns in
UI program data are extremely similar in the CPS supplement
data. Application rates are highest in the States of the Northeast, of the upper Midwest and along the west coast. Application rates are below average throughout the southern and
Rocky Mountain States.
People who are unemployed because their temporary jobs
ended now constitute a sizeable segment of U.S. unemployment. Since 1994, the CPS has identified this group of people
within the total unemployment pool. The 2005 CPS supplement
is the first supplement to identify and study the phenomenon
of workers who are unemployed because their temporary jobs
ended. There were approximately 756,000 of these workers, or
21 percent of all job losers, in the weighted data from the 2005
supplement. By comparison, the total number of job leavers
was approximately 797,000.
Because individuals who are unemployed following the
end of a temporary job are like other job losers in that their
unemployment is due to an employer-initiated job separation,
it is important to learn about their experiences in applying for
and receiving UI benefits. The 2005 supplement indicated that
people from this group were less likely to apply for benefits
than job losers on temporary layoff or other job losers. The
application rate of workers unemployed after a temporary job
was 28.8 percent, compared with 44.2 percent for people on
temporary layoff and 62.6 percent among other job losers.
However, similar to the application rate of other unemployed
groups, the application rate of those unemployed following
a temporary job increases with age and duration of unemMonthly Labor Review • October 2009
45
Unemployment Insurance Benefits
Table 1.
UI benefits application rates by sex, age, reason for unemployment, and duration of unemployment, 2005
[In percent]
Unemployment
duration,
in weeks
Women
16–24
25–44
Men
45 or older
Total
16–24
Total
25–44
45 or older
Total
Job losers
0 to 2..............................
3 to 4..............................
5 to 10............................
11 to 26.........................
27 or more....................
7.1
32.8
34.1
40.7
(1)
29.4
33.7
48.2
71.0
50.4
28.7
53.9
55.9
75.7
72.8
22.9
40.8
48.2
68.1
60.9
14.7
37.5
51.2
20.6
53.4
36.5
45.8
50.0
66.7
58.9
40.7
48.9
61.1
72.7
60.7
32.0
45.5
54.1
58.4
59.3
28.3
43.4
51.6
62.4
59.9
Total...............................
27.6
50.0
60.5
50.1
29.2
53.7
58.6
51.0
50.7
0 to 2..............................
3 to 4..............................
5 to 10............................
11 to 26.........................
27 or more....................
0.0
17.6
(1)
9.5
(1)
0.0
17.7
9.9
32.9
(1)
(1)
(1)
35.1
30.1
(1)
4.8
23.0
20.0
25.0
40.7
3.6
0.0
(1)
20.8
(1)
14.8
17.0
10.5
28.8
11.0
(1)
(1)
(1)
39.8
24.3
7.8
18.3
8.0
27.5
18.6
6.3
20.9
13.6
26.2
28.5
Total...............................
7.4
19.5
36.8
21.1
8.6
17.3
29.1
16.2
18.7
Job leavers
Reentrants
0 to 2..............................
3 to 4..............................
5 to 10............................
11 to 26.........................
27 or more....................
6.1
9.4
6.8
7.7
15.9
3.8
26.3
16.7
31.7
28.1
6.3
1.3
40.0
25.1
32.2
5.4
13.5
18.7
22.2
26.6
3.2
10.4
0.0
0.0
4.1
(1)
18.9
32.4
13.4
26.3
(1)
(1)
6.7
27.0
36.3
4.4
11.7
7.2
9.9
23.6
5.1
12.8
13.6
16.8
25.2
Total...............................
8.5
23.8
24.5
18.1
3.2
21.8
23.6
12.1
15.4
All unemployed
0 to 2..............................
3 to 4..............................
5 to 10............................
11 to 26.........................
27 or more....................
5.4
17.7
16.1
17.7
16.5
15.7
28.3
33.4
51.4
40.1
22.2
40.6
47.8
54.3
56.7
13.2
27.7
33.6
44.1
43.7
7.7
16.6
15.6
11.1
20.8
30.0
37.7
43.7
52.5
44.7
34.4
47.4
45.9
59.3
51.9
21.6
32.9
35.4
41.0
44.1
17.6
30.3
34.6
42.5
44.0
Total...............................
14.0
36.4
46.7
33.5
13.1
43.3
49.6
35.9
34.8
1
Application rate not shown because the cell has fewer than 10
unemployed persons.
NOTE: All cells show percentages that are based on weighted
ployment. More discussion of their experiences with UI
appears later in this article.
In summary, data from the 2005 UI supplement show
that only about one-third of the unemployed applied for
UI benefits during that year. Among job leavers and labor
force reentrants, applicants represented less than 20 percent
of the unemployed. Even among job losers, the group most
likely to file for benefits, the overall application rate was
only about 50 percent. The low rate of UI benefit recipiency
in the United States is mainly a reflection of a low overall
application rate.
Not all people who apply for UI benefits receive a payment. Table 2 summarizes information on the receipt of
UI benefits among all unemployed people (whether or not
46
Monthly Labor Review • October 2009
data measured in thousands of persons.
SOURCE: Supplements to the CPS conducted in January, May, July,
and November 2005.
they applied for UI benefits) since their last job ended.
The statistics are calculated by sex, age, reason for unemployment, and duration of unemployment. As expected, in
most cases UI recipiency increases with age within “reason
for unemployment” groups, and it also tends to increase
with unemployment duration. Overall, about one-fourth
(23.9 percent) of unemployed people reported receipt of
UI benefits in 2005. This rate is about three-quarters of
the recipiency rate in the UI program data. According to
the CPS supplement, the average recipiency rate was 35.6
percent for job losers, 8.8 percent for job leavers, and 10.9
percent for reentrants.
Lags in the process of applying for and receiving benefits
cause the percentages of recipients to be especially low in
Table 2.
UI benefits recipiency rates among all unemployed people, by sex, age, reason for unemployment, and duration of
unemployment, 2005
[In percent]
Unemployment
duration,
in weeks
Women
16–24
25–44
Men
45 or older
Total
16–24
25–44
45 or older
Total
Total
Job losers
0 to 2......................
3 to 4......................
5 to 10....................
11 to 26.................
27 or more............
0.0
5.1
14.3
16.1
(1)
8.1
15.2
35.9
59.2
38.8
16.5
37.6
53.2
71.2
57.3
8.7
21.0
37.8
58.0
47.9
0.8
17.0
30.1
14.3
53.4
14.3
21.3
32.8
53.0
44.7
14.1
21.1
46.2
55.2
55.6
10.5
20.8
37.5
45.1
50.8
9.8
20.9
37.5
50.1
49.4
Total.......................
9.4
35.7
50.6
37.0
16.9
36.0
41.7
34.8
35.6
0 to 2......................
3 to 4......................
5 to 10....................
11 to 26.................
27 or more............
.0
.0
(1)
7.9
(1)
.0
8.3
.0
28.2
(1)
(1)
(1)
8.6
15.3
(1)
.0
9.0
3.6
17.6
23.1
.0
.0
(1)
7.3
(1)
.0
.0
8.9
2.7
11.0
(1)
(1)
(1)
17.1
24.3
.0
7.3
7.4
7.2
18.6
.0
8.3
5.7
12.8
20.7
Total.......................
2.2
10.8
17.1
10.1
4.0
3.8
21.2
7.4
8.8
.0
3.3
.0
.0
4.1
(1)
3.7
32.4
12.1
13.0
(1)
(1)
5.8
27.0
35.8
2.0
3.2
7.0
9.6
17.8
3.1
8.0
9.3
12.6
18.0
1.1
14.3
23.2
9.0
10.9
Job leavers
Reentrants
0 to 2......................
3 to 4......................
5 to 10....................
11 to 26.................
27 or more............
3.1
5.7
3.8
6.0
13.5
3.3
25.7
5.9
21.2
20.2
6.3
1.3
29.9
16.3
18.5
3.7
11.4
11
15
18.1
Total.......................
5.7
16.5
16.4
12.3
All unemployed
0 to 2......................
3 to 4......................
5 to 10....................
11 to 26.................
1.6
4.7
7.4
9.3
5.0
17.2
21.9
40.8
11.9
27.9
39.3
47.0
5.4
15.5
23.6
35.3
0.3
6.7
9.2
6.8
11.6
15.7
30.5
39.9
.9
22.0
35.2
45.8
6.9
14.2
25.2
30.8
6.2
14.9
24.4
32.9
27 or more............
Total.......................
14.8
6.3
28.8
7.1
42.0
36.2
32.3
23.6
20.8
7.1
32.0
28.1
48.3
36.6
37.1
24.3
35.0
23.9
1
Recipiency rate not shown because the cell has fewer than 10 unemployed persons.
NOTE: All cells show percentages that are based on weighted data
the category of 0- to 2-weeks’ unemployment duration.
Whereas the overall application rate for this category is
17.6 percent (table 1), the overall recipiency rate is 6.2
percent (table 2), about one-third of the application rate.
In contrast, the overall recipiency rate in the category for
the longest duration of unemployment—more than 27
weeks—was 35.0 percent, roughly four-fifths of the application rate of the same group (44.0 percent). Denials
of benefits account for most of the difference between the
application rate and the recipiency rate of those with a
long duration of unemployment. However, the 1-week
waiting period and lags in administrative decisionmaking also contribute to low recipiency among people with a
short duration of unemployment.
It should be noted that the contrast between the re-
measured in thousands of people.
SOURCE: Supplements to the CPS conducted in January, May, July, and
November 2005.
cipiency rates in table 2 and the application rates in table
1 was greatest among job leavers (8.8 percent in table 2
compared with 18.7 percent in table 1). This wider gap between the application rate and the recipiency rate among
job leavers is to be expected since administrative determinations regarding the issue of quitting a job result in
denials more than 70 percent of the time.7
Receipt of benefits in four CPS supplements
As previously indicated, the 2005 UI supplement was the
fourth supplement undertaken during the past 30 years.
(The other three supplements were in 1976, 1989, and
1993.) Conditions in the labor market during the four
years in which the supplement was conducted varied from
Monthly Labor Review • October 2009
47
Unemployment Insurance Benefits
one year to another. The highest unemployment rate was
in May 1976 (7.4 percent in seasonally adjusted data); the
annual unemployment rate in 1993 also was high, at 6.9
percent. In contrast, the unemployment rates in 1989 and
2005 were much lower and quite similar to one another:
5.3 percent in 1989 and 5.1 percent in 2005.
The four years also differed in the availability of UI benefits. In 1989 and 2005, the only benefits available were
from the regular UI program—the State-financed 26week program. In contrast, extended benefits were available in 1993 under Extended Unemployment Compensation, a temporary, federally financed program for people
who had exhausted their benefits.8 During 1993, regular
UI benefits of $21.5 billion were paid, while the Extended
Unemployment Compensation program paid an additional $11.8 billion (or 55 percent of regular benefits).
In May 1976, benefits were available from an even
wider array of UI programs. In addition to the regular
UI program, there were three other programs: (1) the
Federal-State Extended Benefit program; (2) the Federal Supplemental Benefits program, a temporary Federal
benefit program like the one enacted in June 2008; and (3)
the Supplemental Unemployment Assistance program,
a unique, one-time program active from 1975 to 1978.9
Thus, opportunities for individuals to receive UI benefits
were present under four different UI programs active in
May 1976.
Table 3 summarizes benefit recipiency rates among
people who applied for UI benefits, as measured in the four
CPS supplements. The table presents recipiency rates along
four dimensions: sex, reason for unemployment, duration of
unemployment, and year. Across the four supplements, on
the whole recipiency was highest in 1976, second highest in
1993, and lowest in 1989 and 2005. This recipiency pattern
closely follows the pattern of unemployment rates and that
of benefit availability across the four years. The similarity of
recipiency rates in 1989 and 2005 is noteworthy, because
only regular UI was available in those years and the unemployment rates of the two years were similar (5.3 percent in
1989 and 5.1 percent in 2005).
As expected, recipiency was consistently highest among
job losers and people with long spells of unemployment.
Across the rows in table 3, recipiency generally increases
as the duration of unemployment becomes longer. Also,
with just a single exception, in comparing the average recipiency rates for each of the four years with one another
for each category of applicant, the recipiency rate is highest in 1976 and lowest in 1989 or 2005.10
Another clear pattern in table 3 is the comparatively
high recipiency rates among job leavers and reentrants in
48
Monthly Labor Review • October 2009
Table 3.
[In percent]
UI benefits recipiency rates among people who
applied for benefits, by sex, reason for unemployment, and duration of unemployment, in 1976,
1989, 1993, and 2005
Unemployment duration, in weeks
Year
1–2
3–4
1976..............
1989..............
1993..............
2005..............
32.4
7.4
13.9
8.7
44.4
32.7
28.3
21.0
1976..............
1989..............
1993..............
2005..............
28.7
10.0
7.5
10.5
42.1
26.8
27.3
20.8
5–10
11–26
27 or
more
Total
Job losers - Women 16 or older
61.9
47.2
47.2
37.8
71.7
54.4
61.0
58.0
81.6
56.0
71.6
47.9
63.6
39.2
49.8
37.0
Job losers - Men 16 or older
65.3
49.2
60.0
37.5
77.1
54.8
62.2
45.1
76.7
53.0
65.6
50.8
63.9
39.6
51.1
34.8
Job leavers - Women 16 or older
1976..............
1989.............
1993..............
2005..............
16.7
1.0
0.6
0.0
6.5
7.5
2.1
9.0
1976..............
1989..............
1993..............
2005..............
3.3
0.7
3.2
0.0
13.2
4.6
14.4
7.3
1976..............
1989..............
1993..............
2005..............
10.0
3.0
5.3
3.7
10.9
9.1
6.1
11.4
1976..............
1989..............
1993..............
2005..............
10.5
2.5
1.5
2.0
19.0
8.5
5.4
3.2
13.0
8.4
0.7
3.6
53.6
13.8
29.8
17.6
67.5
2.1
(1)
23.1
31.0
6.2
11.0
10.1
Job leavers - Men 16 or older
28.9
11.7
1.8
7.4
52.9
10.6
23.5
7.2
58.3
11.6
37.4
18.6
31.8
6.2
15.3
7.4
Reentrants - Women 16 or older
19.8
10.4
11.7
11.0
13.6
10.7
13.5
15.0
29.9
18.2
21.5
18.1
14.6
8.5
10.4
12.3
Reentrants - Men 16 or older
24.6
10.7
17.7
7.0
33.3
4.5
24.3
9.6
33.3
23.0
13.9
17.8
25.1
8.4
12.2
9.0
Datum did not meet BLS publication criteria.
NOTE: The recipiency rates for job losers, job leavers, and
reentrants combined were as follows: 1976 = 0.483, 1989 = 0.242, 1993 =
0.351 and 2005 = 0.240.
SOURCE: Unemployment insurance supplements to the CPS
conducted in 1976, 1989, 1993, and 2005.
1
1976 in comparison with later years. This is to be expected,
since three other programs besides regular UI were active
in May 1976. Particularly important was the presence of
the Supplemental Unemployment Assistance program in
1976, which used less stringent eligibility criteria than the
regular UI program.11
Reasons for not applying for benefits
The 2005 UI supplement and the supplements of 1989 and
1993 asked questions that sought to identify reasons for
not applying for and for not receiving benefits. Because
nonapplicants do not have direct contact with the UI program, UI administrative data cannot inform researchers
about the motivations that underlie decisions to remain
outside the UI program. The CPS supplements identified
several potential reasons for not applying.
Table 4 summarizes responses to the question about not
applying for benefits. Four main kinds of reasons are identified in the rows, along with the catchall category of “other
reasons.” The four broad reasons are the following: (1) belief
that one is ineligible (this belief could be either well founded
or not well founded), (2) attitude/understanding/barrier to
UI benefits, (3) job expected/became employed, and (4) not
looking (e.g., retired, ill, or disabled). The first two broad reasons are divided into more detailed categories, also referred to
in this article as “detailed reasons.” Respondents were asked
to choose one broad reason and one detailed reason as their
primary rationale for not applying for UI benefits.
The two data columns in table 4 display estimated counts
and percentages of nonapplicants in the broad and detailed
categories. Note that even with the variety of reasons identified, more than one-tenth (11.4 percent) of people did not
provide a reason for not applying that could be categorized.
Through refinements of the questions and interviewer
training, this “other reasons” problem has been reduced in
successive CPS supplements: the percentage of people in the
“other reasons” category went from 28.5 percent in 1989 to
22.5 percent in 1993 and then to 11.4 percent in 2005.
The most important reason for not applying in 2005 was
the belief that one is ineligible for benefits. Of the estimated
4.368 million nonapplicants, 2.269 million (or 51.9 percent)
stated they believed they were not eligible for benefits; 1.207
million said they had not worked long enough to be eligible,
and 601,000 gave a reason for ineligibility related to the circumstances of their separation from their job.
The other broad categories of reasons for not applying
all accounted for less than 20 percent of nonapplicants.
The broad category of attitude/understanding/barrier to UI
benefits accounted for 17.8 percent of the total, but each of
its subcategories accounted for 5.0 percent or less of nonapplicants. Note the varied motivations within this broad
grouping. Some did not need the money or did not want the
hassle, and some viewed UI negatively. Others did not know
about the program, did not know how to file for benefits, or
faced a barrier (the most common of which was being told,
mainly by their employer, that they were not eligible).
Of the people represented in table 4, note that about
594,000 (or 13.6 percent) indicated they expected a job
soon or were employed. That is, there was no reason to
file for benefits because they expected to be working in
the near future. The fourth broad category—“not looking
for a job”—accounted for only 5.3 percent of the total responses. The responses in this category are appropriate to
people not actively seeking work.
The reasons for not applying for benefits differ systematically according to the person’s reason for unemployment.
Table 5 is similar to table 4 in that it organizes people by
their reasons for not applying for UI benefits. The data in
table 5, however, do not include people with “other reasons”
for not applying, so each statistic refers to people who gave
a definitive reason for not applying. Unlike table 4, table
5 organizes people by their reasons for unemployment in
order to show what percent of each group of unemployed
people cited which reason for not applying.
Note in column 1 that the belief that one is ineligible
for UI benefits accounted for 58.6 percent of all the people
who cited one of the four broad reasons for not applying
for UI benefits. In each of the reason-for-unemployment
groups the belief that one is ineligible accounted for at
least 50 percent of nonapplicants except for job losers on
temporary layoff (column 3), 33.7 percent of whom believed they were ineligible.
Two other statistics related to UI eligibility also are noteworthy in table 5. First, 6.9 percent of “other job losers” had
previously exhausted UI benefits. This group includes many
displaced workers, who are known to experience long spells
of unemployment. Their long unemployment spells imply
that many did not have sufficient recent earnings to requalify
for UI benefits following the exhaustion of their benefits. Second, 17.2 percent of people who were unemployed because a
temporary job ended reported that their work was not covered by UI. This is highly questionable, because temporary
employees work mainly as wage and salary workers and UI
coverage among wage and salary workers exceeds 98 percent.
The fact that the percentage is as high as 17.2 suggests that
many temporary workers do not understand that their jobs
fall within the umbrella of UI-covered employment or may
have other reasons for not applying for UI benefits.
Note also that job leavers generally had different reasons for believing themselves to be ineligible for benefits
than did labor force reentrants. Over 40 percent of job
leavers gave a reason for ineligibility related to their manner of job separation, while nearly 40 percent of reentrants
indicated they had “insufficient past work,” that is, that
they had not worked long enough at the job to be eligible
for UI benefits. Nearly 65 percent of both job leavers and
reentrants gave reasons for not applying for benefits that
were related to ineligibility.
As one would expect, job losers on temporary layoff
was the unemployment group most likely not to apply for
Monthly Labor Review • October 2009
49
Unemployment Insurance Benefits
suggest it is those people whose temporary
jobs have ended. This group had a high percentage of people stating that their work
Number
Percent of
was not covered by UI, 17.2 percent, and a
of persons,
all
Reason for not applying
high percentage who did not know about
in
unemployed
thousands
people
UI or how to file for benefits, 8.9 percent.
These two statistics sum to roughly oneBelief that one is ineligible............................................................................
2,269
51.9
quarter of all people in this group who did
Work not covered by UI.............................................................................
303
6.9
Insufficient past work................................................................................
1,207
27.6
not apply for UI benefits. Since this group
Job separation reason (quit or misconduct).....................................
601
13.8
also had a much lower application rate
Any other reason concerning eligibility, other than previous
exhaustion of benefits............................................................................
35
0.8
than the two other categories of job losers
Previous exhaustion of benefits............................................................
123
2.8
(as discussed earlier), it appears that many
Attitude/understanding/barrier to UI benefits. .........................................
778
17.8
Do not need the money or do not want the hassle.......................
220
5.0
people whose temporary jobs have ended
Negative attitude about UI................................................................................
78
1.8
do not fully understand how their previ Do not know about UI/do not know how to file.............................
212
4.9
ous work is related to UI eligibility.
Barrier to filing (e.g., language or transportation)..........................
52
1.2
Told not eligible...........................................................................................
175
4.0
To summarize, three comments about
Plan to file soon...........................................................................................
42
1.0
nonapplicants seem appropriate: (1) The
Job expected/became employed..............................................................
594
13.6
Not looking for a job (e.g., retired, ill, or disabled)...............................
231
5.3
most common reason for not applying for
Other reasons....................................................................................................
496
11.4
UI benefits is a perception of ineligibility.
Just didn’t/don’t know why....................................................................
107
2.4
All other reasons.........................................................................................
389
8.9
(Over half of all non-applicants gave this
Total.....................................................................................................................
4,368
100.0
reason for not filing). (2) The reasons for
not filing vary systematically according to
SOURCE: Weighted counts are based on 1,832 persons who were identified as unemployed
and who did not apply for UI benefits.
the reason for unemployment. Reentrants
are most likely to state they had insufficient
past work, whereas job leavers were most likely to give a
benefits because of an expectation of being reemployed reason for not filing that was related to the circumstances
soon. The percentage of temporarily laid-off workers giv- of the job separation. Job losers on temporary layoff were
ing this reason is 39.6, more than twice the percentage for most likely to state that they expected to have a job soon.
(3) People whose temporary jobs had ended appeared to
any other detailed reason-for-unemployment group.
Among people who were not looking for a job, 10.3 have the least-developed understanding of the UI program
percent were in the reentrant category, more than in any and how to apply for benefits.
other reason-for-unemployment category. The reentrants
to the labor force who were not looking for a new job Reasons for not receiving benefits
likely viewed themselves as focused more on personal and
family activities than on the labor market and paid em- Not all people who apply for UI benefits receive payments.
ployment. The second-highest percentage of people who The 2005 CPS supplement asked about receipt of benefits
were not looking for a new job was the percentage of job since the person’s last job and within the previous week.
About 3 in 10 who applied for UI in 2005 had not received
losers on temporary layoff (4.6 percent).
Another noteworthy finding is the percentages of job a payment by the time of their interview.12 As would be
losers who reported they were told that they were not expected, the supplement found that most people who
eligible for UI benefits—4.7 percent of job losers on tem- had not received benefits either had been denied benefits
porary layoff, 8.7 percent of other job losers, and 6.7 per- because they were found ineligible or were still waiting for
cent of people whose temporary jobs ended. Knowledge their applications to be processed. Nearly half (48.0 perabout the UI program and how to file for benefits seems cent) gave a reason related to UI eligibility. In descending
especially low among the latter two groups. Among those order of importance, the four most common reasons that
whose temporary jobs ended, 9.1 percent indicated they workers gave for denial of benefits were the following: (1)
did not file because they did not need the money or want insufficient past work, (2) job separation reasons (quits or
misconduct), (3) other administrative disqualifications,
the hassle.
If any single group of unemployed is especially ill in- and (4) previous exhaustion of benefits. More than 40 performed about the UI program, the percentages in table 5 cent of nonrecipients either were waiting approval of an
Table 4.
50
Reasons for not applying for UI benefits in 2005
Monthly Labor Review • October 2009
Table 5.
Percentages of people who did not apply for UI benefits and gave a classifiable reason why not, by
reason for unemployment and reason for not applying, 2005
Reason for not applying
All reasons for
Job losers on
Job loser total
unemployment
temporary
=[3]+[4]+[5]
=[2]+[6]+[7]
layoff
Other job
losers
Temporary
job ended
Job leavers
Reentrants
[1]
[2]
[3]
[4]
[5]
[6]
[7]
Belief that one is ineligible..........................
Work not covered by UI ............................
Insufficient past work.................................
Job separation reason (quit or
misconduct)...................................................
Any other reason concerning
eligibility, other than previous
exhaustion of benefits............................
Previous exhaustion of benefits.............
Attitude/understanding/barrier to UI
benefits...........................................................
Do not need the money or do not
want the hassle.........................................
Negative attitude about UI.........................
Do not know about UI/do not
know how to file.......................................
Barrier to filing (e.g., language or
transportation)...........................................
Told not eligible.......................................
Plan to file soon.......................................
Job expected/became employed.............
Not looking (e.g., retired, ill, or disabled).....
58.6
7.8
31.2
50.1
11.6
26.3
33.7
11.5
17.3
60.6
7.4
31.3
52.8
17.2
28.9
64.6
1.3
19.1
64.4
6.6
39.6
15.5
7.3
3.0
12.2
5.0
43.1
14.0
.9
3.2
1.3
3.7
.6
1.3
2.8
6.9
.0
1.7
.0
1.1
.9
3.4
20.1
26.1
22.1
25.4
31.1
14.2
16.5
5.7
2.0
6.0
2.7
10.3
2.7
.5
2.6
9.1
2.9
5.3
1.9
5.5
1.4
5.5
6.9
2.8
8.4
8.9
3.7
4.8
1.3
4.5
1.1
15.3
6.0
1.2
6.9
2.4
21.1
2.7
.6
4.7
1.0
39.6
4.6
1.3
8.7
3.9
12.4
1.7
1.6
6.7
1.9
13.8
2.2
1.0
1.7
.6
19.3
1.9
1.6
3.2
.0
8.8
10.3
Total....................................................................
100.0
100.0
100.0
100.0
100.0
100.0
100.0
SOURCE: Weighted counts are based on 1,336 persons who were identified and unemployed and who gave reasons for not applying for UI benefits.
application or had already had their applications approved
and were waiting to receive their first payment of benefits.
Among people who had received benefits since their
last job, a sizeable percentage (40.1 percent) had not received benefits in the previous week. More than 80 percent of those who had not received benefits during the
previous week reported they had exhausted their eligibility prior to the past week. Every reason other than the
exhaustion of benefits accounted for less than 4 percent
of the people who had received benefits since their last
job but had not received benefits in the last week. Considering both nonreceipt of benefits since the last job and
nonreceipt during the past week, the explanations given
were straightforward and presented no major surprises.
Nonreceipt mainly resulted from ineligibility (especially
because of the exhaustion of benefits) and from delays in
the processing of applications.
Analysis of microdata
Unemployed respondents in the 2005 UI supplement provide a sample of 2,859 complete microrecords. The determinants of applications for benefits and receipt of benefits
(both measured as 0–1 variables) were examined with a
series of multiple regressions.13 The regressions used sets of
dummy (0–1) variables to capture the effects of individual
explanatory factors such as age, sex and duration of unemployment. Because applications for and receipt of benefits
vary widely according to people’s reasons for unemployment, the regressions were fitted separately for each of five
“reason” groups.
A consistent finding of the analysis was that age and
unemployment duration were the most consistently significant factors in explaining both applications for benefits and the receipt of benefits. The regressions were least
successful in explaining the applications for benefits and
receipt of benefits among job leavers and people whose
temporary jobs had ended. The best explanations were for
the behavior of those on temporary layoff and those in the
“other job losers” category. The regressions revealed substantial differences in application rates across regions. The
regressions were also able to determine that delays in the
processing of applications were much shorter for “other
job losers” than for people on temporary layoff.
The regression analysis was only a preliminary investigation, but it highlights the importance of several idenMonthly Labor Review • October 2009
51
Unemployment Insurance Benefits
tifiable influences on UI applications and the receipt of
benefits. The findings all mirrored the tabular summaries
like those displayed in tables 1–3. Additional analysis of
the microdata is warranted.
THE UI SUPPLEMENT IN THE 2005 CPS PROVIDES
fairly recent data on applications for and the receipt of
UI benefits. Tabular summaries and regression analysis of
microdata have found a number of important statistical
regularities. Perhaps the most important finding from
these data is that most people who do not file for UI benefits believe they are not eligible for benefits. The specific
reason for not applying, however, depends strongly upon
the person’s reason for unemployment. At least among
people whose temporary jobs ended, the data suggest
that many of them do not understand key elements of UI
program coverage and eligibility. More analysis of similar
microdata would help improve researchers’ understanding
of why so few unemployed people apply for and receive
UI benefits.
Notes
Acknowledgments: The author thanks Jake Benus, Wayne Gordon, Janet
Javar and Steve Wandner for commenting on earlier drafts of this article.
1
The recipiency rate is the ratio of weekly UI beneficiaries to
weekly total unemployment. Among the 21 high-income countries
that are members of the Organization for Economic Cooperation
and Development, the median UI recipiency rate during the 2000–04
timespan was 0.875; during the same period, recipiency in the United
States averaged 0.391, less than half the median of the 21 countries’
rates. Of these countries, only Greece and Japan had lower recipiency
rates than the United States.
2
Three papers that summarize the first three CPS supplements from
1976, 1989, and 1993 are the following: Carl Rosenfeld, “Job search of
the unemployed, May 1976,” Monthly Labor Review, November 1977,
pp. 39–43; Wayne Vroman, “The Decline in Unemployment Insurance
Claims Activity in the 1980s,” Unemployment Insurance Occasional
Paper 91–2, (Washington, DC, U.S. Department of Labor, Employment
and Training Administration, 1991); and Stephen Wandner and Andrew
Stettner, “Why are many jobless workers not applying for benefits?”
Monthly Labor Review, June 2000), pp. 21–32.
3
See Wayne Vroman, “An Analysis of Unemployment Insurance
Non-Filers: 2005 CPS Supplement Results,” Occasional Paper 2009–7,
(Washington, DC, U.S. Department of Labor, Employment and
Training Administration, 2009).
4
The eight questions are shown in the appendix of this article.
5
According to the UI program data, applicants for unemployment
insurance (collectively referred to as “insured unemployment”) were
34.4 percent of total unemployment in 2005.
52
Monthly Labor Review • October 2009
6
In UI program data for 2005, the difference between the sexes was
slightly larger. The insured-employment-to-uninsured-employment
ratio was 0.324 for women and 0.366 for men.
7
UI program data on nonmonetary decisions involving voluntary
quits in 2005 indicate a denial rate of 0.73.
8
Some form of temporary Federal benefit program has been enacted
in every recession since 1958. Federal-State Extended Benefits also
were paid in 1993 in Oregon, Puerto Rico, and Washington State.
The Supplemental Unemployment Assistance program paid
benefits to people regardless of their eligibility for regular UI. Usually,
emergency and extended benefit programs pay benefits only to people
who have already exhausted their entitlement to regular UI benefits.
The Supplemental Unemployment Assistance program served many
individuals with low and/or intermittent earnings histories and employees
of nonprofit organizations and the government who were not covered by
UI at the time.
9
The only exception to this generalization is women reentrants.
In this category, the 2005 average of 12.3 percent is only marginally
higher than the 1993 average of 10.4 percent.
10
11
Eligibility was extended to people who previously had worked
in noncovered sectors and to some who did not satisfy other eligibility
criteria for the regular UI program.
12
In UI program data for 2005, the ratio of first payments to new
initial claims is 0.757.
13
The regression analysis is discussed in Section 7 and Appendix B
of Vroman, “An Analysis of Unemployment Insurance Non-Filers.”
APPENDIX:
Questions in the 2005 UI supplement in the CPS
As noted in the text, the supplement questions were administered mainly to unemployed people in outgoing rotation groups
during the months of January, May, July, and November in 2005. The eight questions are listed below. Details that relate to
skip patterns for the questions, the selection of people to be interviewed, and other instructions to the CPS interviewers are
available from the Census Bureau, which has prepared documentation for potential users of data on UI benefits.
Question 1. Have you (or her/his name) applied for unemployment benefits since (your/her/his)
last job?
Question 2. Have you (or her/his name) received any unemployment benefits since (your/her/his)
last job?
Question 3. Did you (or her/his name) receive unemployment benefits last week?
Question 5. There are a variety of reasons why people
might not apply for unemployment benefits.
What are the reasons (you have/name has) not
applied for unemployment benefits since (your/
her/his) last job?
Question 6. Why didn’t (you/name) believe (you were/she
was/he was) eligible for unemployment benefits?
Question 4a. Why didn’t you (or her/his name) receive
any unemployment benefits last week?
Question 7. Of the reasons you just mentioned, (read the list
of reasons), what is the main reason (you/name)
did not apply?
Question 4b. Why haven’t you (or hasn’t her/his name)
received any unemployment benefits since (your/
her/his/) last job?
Question 8. Were you (Was name) a union member or
covered by a union contract on (your/his/her)
last job?
Monthly Labor Review • October 2009
53
Book Review
Is it time to apply the
brakes?
Managing Without Growth: Slower
by Design, Not Disaster. By Peter A.
Victor, Northampton, MA, Edward
Elgar Publishing, 2008, 260 pp.,
$31.50/paperback.
Managing Without Growth is one of
a number of recent books focused on
economic growth as a policy issue. Its
author, Peter A. Victor, is a professor
of Economics at York University in
Toronto, Canada, who has worked on
environmental issues as an academic
consultant and public servant for over
30 years. Victor grounds his book in
quantitative information on employment, GDP, poverty, and forecasts of
global warming. Its distinguishing
feature is econometric modeling of
the macro economy assuming slow or
no growth.
Concerns about the consequences
of a rapidly growing world population and finite resources first came
to prominence with the publication
of An Essay on the Principle of Population by Thomas Malthus in 1798.
The publication in 1972 of The Limits
to Growth by Donella H. Meadows,
Dennis L. Meadows, Jorgen Randers,
and William W. Behrens III, reexamined the exponential growth in the
demands placed upon the earth and
the linear growth in the earth’s capacity to absorb it, looking at 5 variables:
(1) world population (2) industrialization (3) pollution (4) food production and (5) resource depletion. The
book made no specific predictions,
but rather gave indications of tendencies that would occur given specific behavior. It is only natural that
a conflict would develop between the
conclusions drawn about the book by
environmentalists and intellectuals on
54
Monthly Labor Review • October 2009
the one hand (in favor of protecting
the earth) and business and government officials on the other (in favor
of developing the earth), especially
in their view of the effects of pricing
mechanisms on the environment. In
Managing Without Growth, this conflict is revisited in its entirety, and
Victor’s review of the literature is rich
and generous to all sides.
Three chapters of Victor’s book
cover “sources, sinks, and services.”
“Sources” is the Malthusian issue of
running out of material, with Peak Oil
replacing food as the focus. “Services”
are what Nature does to preserve the
globe. “Sinks” are where the wastes of
the economy go. Per Victor, concern
about runaway climate change caused
by Green House Gas (GHG) emissions pinpoints sinks as a most pressing problem for humanity.
Sinks are confronted in the quantitative section on scale in Chapter 7.
Victor uses data on population and
GDP growth to examine how rapidly
carbon intensity—the multiplicative
of carbon per unit of energy and energy per unit of GDP—must decline
to achieve the 60 percent reduction in
CO2 emissions over 50 years, which
the Intergovernmental Panel on Climate Change (IPCC 2007) set as a
target to protect against runaway climate change. Victor reports on the
relatively slow rate of improvement
in carbon intensity world-wide in
the years 1972–2002. Since 2002, of
course, a new focus on development
and deployment of clean energy
technology has occurred, which may
speed gains. But Victor’s calculations
show that, if carbon intensity doesn’t
significantly improve, slower economic growth in the developed world
will be a necessity to reduce emissions
of Green House Gases.
Using diverse scenarios based on
Canadian data and an econometric
model called LowGrow, Victor projects whether slow or zero growth in
a modern economy (from 2005 to
2035) is even possible. LowGrow is
ambitious and solid work. It raises the
discussion of crashing the economy
to an analytical plane, but it must be
viewed as a beginning. Methods to
adjust an economy’s rate of growth
have been known and employed for
decades. Monetary and fiscal policy
do just that, after all; for example, the
Federal Reserve, if concerned about
inflation, can slow economic activity
to a zero or negative rate of growth.
One critical economic variable, investment, illustrates part of the problem. Victor has an equation to generate the annual value for investment, I,
in LowGrow, but no theory of investment. His value for I is a function of
three things—the interest rate, GDP,
and the rate of corporate profits, each
lagged one year. For private investment, however, the value of assets and
the decision about investing in additional assets depend on expectations
about the future, specifically on an
estimate of cash flows from the assets. Projections of asset value will be
lower if expected growth is reduced.
This leads, in turn, to reduced investment by business. Ultimately a shift
in the balance among worker-owned,
government, and business investment
would be likely. The model disappoints by implying a future economy
much like today’s, but simply with
slow or zero growth. The changes
sure to be required by all parties are
scarcely touched; what is clear is that
the no-growth economy would be
profoundly different from today’s
economy. For the necessary revolution in consumer culture, Victor relies on individuals choosing “voluntary simplicity.” He concludes that it
is possible to have full employment,
eliminate poverty, and reduce GHG
emissions in an economy with slow
or no economic growth by 2035, but
only if we act quickly.
The final chapter focuses on policies
to achieve and then manage with slow
or no growth. Since people tend to
resist rules and taxes impacting their
lives, the proscriptive rules and taxes
listed leads to Victor’s remark that,
“The dilemma for policy makers is
that the scope of the change required
for managing without growth is so
great that no democratically elected
government could implement the
requisite policies without the broadbased consent of the electorate.” As
an incentive to change, Victor recommends reducing the work week, an
idea that has proven popular across
the world. Demands by labor and
others for shorter hours have often
been successful in the past, and it is a
policy recommendation which shows
up in almost every discussion of reducing growth.
One must keep in mind when read-
ing this book that Victor is a selfdescribed ecological economist with
a focus on environmental issues.
Having said that, Managing Without
Growth is a strong contribution to
the discussion of economic growth,
especially in the quantitative analysis
that runs through the book and in the
author’s full command of the many
dimensions of the literature.
—Eugene P. Coyle, Ph.D.
Eugene P. Coyle & Associates
Berkeley, California
Monthly Labor Review • October 2009
55
Précis
A beautiful city means
productive workers
What are the qualities that draw you
to a city? Is it the sunny skies or the
snowy slopes? Maybe it is a thriving
restaurant scene or an emerging arts
culture. For years economists and
policymakers alike have analyzed the
relationship between leisure amenities and the attraction of people and
jobs to certain cities, hoping to unlock
the key to urban growth and development. Economist Gerald Carlino has
an intriguing new take on the subject
in his article “Beautiful City,” published in the third quarter 2009 edition of the Federal Reserve Bank of
Philadelphia’s Business Review.
In a 2008 study conducted with his
research partner Albert Saiz, Carlino found a positive correlation between the number of leisure tourists
who visited a city in the 1990s and
the growth of both employment and
population during the same period.
The study shows that leisure amenities—such as historic districts, architectural beauty, and variety in cultural
and recreational opportunities—are
important for an area’s growth, even
after the researchers controlled for
56
Monthly Labor Review • October 2009
a city’s proximity to a coast and for
a city’s climate, which are two advantages that cannot be reproduced.
For example, in the 1990s population growth was about 2.2 percentage points higher and employment
growth was 2.6 percentage points
higher in a city with twice as many
tourists as another city. Carlino and
Saiz also found evidence of acceleration in house-price appreciation and
rent growth in cities with more tourists. A city with twice as many tourists as another city has a 2-percentage-point higher house price appreciation and a 1.3-percentage-point
higher rent growth.
Citing many shortcomings in the
quality-of-life approach to assessing
a city’s potential, Carlino and Saiz
use “a more encompassing measure of
the demand for urban amenities that
stems from a revealed preference for
these amenities as represented by the
number of leisure tourists who visit
a metropolitan area.” The qualities
that attract tourists to an area—culture, ambiance, architecture, pleasant public spaces, scenic beauty, and
so forth—attract households to cities when they decide to make these
places their permanent homes.
Carlino and Saiz believe that the
association between leisure amenities
and growth may occur because such
amenities disproportionately attract
more productive workers. A city with
twice the level of tourists as another
city has a 0.3-percentage-point increase in the growth rate of the share
of the population with at least a college education.
While past studies have focused
mainly on the relationship between
city growth and business agglomeration economies, Carlino notes that,
with technological advances in communication and transportation, businesses have more freedom than ever
before to choose their locations. He
implies that businesses today decide
where to locate on the basis of where
their workers choose to live.
But why are leisure-related amenities associated with economic
growth? Carlino suggests that “beautiful cities” are attractive to high-skill
workers—and it is especially these
workers who are known to stimulate
both employment and population
growth. Highly educated individuals
are highly productive workers who,
in turn, enhance the productivity of
their coworkers.
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 region,
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 ........................................................ 113
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......................................................... 126
52. Annual data: Employment status of the civilian
working-age population, 10 countries........................... 127
53. Annual indexes of productivity and related measures,
17 economies................................................................ 128
Injury and Illness data
54. Annual data: Occupational injury and illness..................... 130
55. Fatal occupational injuries by event or exposure ................ 132
Monthly Labor Review • October 2009 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 • October 2009
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 International 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
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
January–June period. The historical season-
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
4 weeks. Persons who did not look for work
ally 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,
managerial, and supervisory positions. Those
Monthly Labor Review • October 2009
59
Current Labor Statistics
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 • October 2009
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
American Industry Classification System
Monthly Labor Review • October 2009
61
Current Labor Statistics
(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
(OMB) defines metropolitan areas for use
62
Monthly Labor Review • October 2009
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 Em-
ployment 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 combined to represent one of ten intermediate
aggregations, such as professional and related
occupations, or one of five higher level aggreMonthly Labor Review • October 2009
63
Current Labor Statistics
gations, 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
in the private nonfarm economy was published beginning in 1975. Changes in total
compensation cost—wages and salaries and
64
Monthly Labor Review • October 2009
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 esti-
mated 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.
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, allowMonthly Labor Review • October 2009
65
Current Labor Statistics
ances, 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 family 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
66
Monthly Labor Review • October 2009
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 organization 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 definitions 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
job seekers. 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
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.
Monthly Labor Review • October 2009
67
Current Labor Statistics
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, Singapore, 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,
manufacturing 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
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 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 pub68
Monthly Labor Review • October 2009
lishes 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, Singapore, 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 Divi-
sion of International Labor Comparison 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 • October 2009
69
Current Labor Statistics: Comparative Indicators
1. Labor market indicators
Selected indicators
2007
2007
2008
II
III
2008
IV
I
II
2009
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:
66.0
63.0
4.6
4.7
11.6
3.6
4.5
9.4
3.6
66.0
62.2
5.8
6.1
14.4
4.8
5.4
11.2
4.4
66.0
63.0
4.5
4.6
11.5
3.5
4.4
9.0
3.6
65.9
62.9
4.7
4.8
11.8
3.6
4.6
9.7
3.7
66.0
62.8
4.8
4.9
12.1
3.7
4.7
9.9
3.8
66.0
62.8
4.9
5.1
12.7
3.9
4.8
10.1
3.9
66.1
62.5
5.4
5.6
13.5
4.2
5.1
11.1
4.1
66.1
62.1
6.0
6.5
14.9
5.1
5.6
11.9
4.5
65.9
61.3
6.9
7.5
16.5
6.0
6.1
11.6
5.2
65.6
60.3
8.1
8.8
18.0
7.4
7.2
12.9
6.2
65.8
59.7
9.2
10.4
20.0
8.8
8.0
14.4
6.9
1
Total nonfarm…………………….................................................... 137,598
Total private....................................................................... 115,380
137,066
114,566
137,645
115,400
137,652
115,389
138,152
115,783
137,814
115,373
137,356
114,834
136,732
114,197
135,074
112,542
133,000
110,457
131,692
109,138
22,233
Manufacturing………….………………..………………………… 13,879
21,419
13,431
22,289
13,889
22,099
13,796
22,043
13,777
21,800
13,643
21,507
13,505
21,247
13,322
20,532
12,902
19,520
12,296
18,815
11,854
Service-providing ……………………………………………….………….. 115,366
115,646
115,356
115,553
116,109
116,014
115,849
115,485
114,542
113,480
112,877
Goods-producing ……………………………………………….…………..
Average hours:
Total private........................................…………..........................
Manufacturing………...……………………………………………
Overtime……..………….………………...………………………
33.9
41.2
4.2
33.6
40.8
3.7
33.9
41.3
4.3
33.8
41.3
4.1
33.8
41.2
4.1
33.8
41.2
4.0
33.6
40.9
3.8
33.6
40.5
3.5
33.3
39.9
2.9
33.1
39.4
2.6
33.0
39.5
2.8
Civilian nonfarm ……………………………….…………………………….……
3.3
2.6
.8
1.0
.6
.8
.7
.8
.3
.4
.4
Private nonfarm……………...............………...............................
3.0
2.4
.9
.8
.6
.9
.7
.6
.2
.4
.3
2.4
2.4
1.0
.5
.6
1.0
.7
.4
.3
.4
.3
3.2
2.5
.9
.9
.6
.9
.7
.6
.3
.4
.3
4.1
3.0
.6
1.8
.7
.5
.5
1.7
.3
.6
.5
2.0
3.2
2.8
2.4
1.2
.9
.5
.8
.7
.6
.8
.9
.8
.7
.7
.6
.6
.2
1.0
.3
.6
.2
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
Quarterly data seasonally adjusted.
2
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.
70
Monthly Labor Review • October 2009
4
Excludes Federal and private household workers.
5
Goods-producing industries include mining, construction, and manufacturing. Serviceproviding industries include all other private sector industries.
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
2007
2008
2007
II
2008
III
IV
I
II
2009
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
3.0
2.6
2.4
0.8
.9
1.0
.8
0.6
.6
0.8
.9
0.7
.7
0.8
.6
0.3
.2
0.4
.4
0.4
.3
3.4
3.3
2.7
2.6
.7
.8
1.0
.9
.7
.6
.8
.9
.7
.7
.8
.6
.3
.3
.4
.4
.4
.3
2.8
3.8
1.5
.1
.7
1.7
2.5
0
-3.9
1.2
1.4
3.9
4.5
1.8
4.1
12.1
6.3
7.4
2.8
10.5
21.5
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
2.8
3.4
.7
5.0
14.5
4.2
5.2
.6
6.9
14.9
-.1
-.4
1.0
.7
-15.6
-7.4
-10.0
1.9
-13.6
-32.1
.1
.1
-.1
-2.0
-7.4
3.1
4.3
.0
2.7
13.1
1.8
1.8
1.9
1.8
3.5
2.8
5.5
5.5
1.6
2.0
.2
-.1
3.1
3.1
.3
-.1
.8
.8
.2
.3
6.3
6.4
1.0
1.9
2.8
-1.1
5.3
-2.7
6.9
3.2
-1.4
-6.0
-
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
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
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.
5
Output per hour of all employees.
3. Alternative measures of wage and compensation changes
Quarterly change
Components
2008
II
Four quarters ending—
2009
III
IV
I
2008
II
II
III
2009
IV
I
II
1
Average hourly compensation:
All persons, business sector..........................................................
All persons, nonfarm business sector...........................................
Employment Cost Index—compensation:
4.5
4.5
2.6
2.9
-2.5
-2.4
0.1
.2
2.6
2.7
2.9
3.1
2.5
2.6
1.5
1.5
1.1
1.3
.7
.7
.8
.7
.5
.8
.6
.7
.6
1.7
.3
.2
.6
.2
.3
.4
.4
1.0
.3
.6
.4
.3
.6
.2
.5
3.1
3.0
2.7
3.0
3.5
2.9
2.8
2.9
2.8
3.4
2.6
2.4
2.8
2.4
3.0
2.1
1.9
3.0
1.8
3.1
1.8
1.5
2.9
1.2
3.2
.7
.7
1.1
.7
.5
.8
.6
.7
.6
1.8
.3
.3
.7
.2
.3
.4
.4
.6
.4
.5
.4
.3
.7
.2
.5
3.2
3.1
2.9
3.2
3.4
3.1
2.9
2.9
3.0
3.5
2.7
2.6
3.2
2.5
3.1
2.2
2.0
3.1
1.9
3.0
1.8
1.6
2.7
1.4
3.0
2
3
Civilian nonfarm ……….………………………………………….…………..…
Private nonfarm….......................................................................
Union…………..........................................................................
Nonunion…………....................................................................
State and local government….....................................................
Employment Cost Index—wages and salaries:
3
1.6
1.3
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 • October 2009 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
2008
Annual average
2007
2008
Aug.
Sept.
Oct.
2009
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
July
Aug.
TOTAL
Civilian noninstitutional
1
population ……………………. 231,867
Civilian labor force.............. 153,124
66.0
Participation rate...........
Employed........................ 146,047
Employment-pop63.0
ulation ratio 2……………
7,078
Unemployed...................
4.6
Unemployment rate.....
Not in the labor force........ 78,743
233,788 234,107 234,360 234,612 234,828 235,035 234,739 234,913 235,086 235,271 235,452 235,655 235,870 236,087
154,287 154,823 154,621 154,878 154,620 154,447 153,716 154,214 154,048 154,731 155,081 154,926 154,504 154,577
66.0
66.1
66.0
66.0
65.8
65.7
65.5
65.6
65.5
65.8
65.9
65.7
65.5
65.5
145,362 145,273 145,029 144,657 144,144 143,338 142,099 141,748 140,887 141,007 140,570 140,196 140,041 139,649
62.2
8,924
5.8
79,501
62.1
9,550
6.2
79,284
61.9
9,592
6.2
79,739
61.7
10,221
6.6
79,734
61.4
10,476
6.8
80,208
61.0
11,108
7.2
80,588
60.5
11,616
7.6
81,023
60.3
12,467
8.1
80,699
59.9
13,161
8.5
81,038
59.9
13,724
8.9
80,541
59.7
14,511
9.4
80,371
59.5
14,729
9.5
80,729
59.4
14,462
9.4
81,366
59.2
14,928
9.7
81,509
Men, 20 years and over
Civilian noninstitutional
1
population ……………………. 103,555
Civilian labor force.............. 78,596
75.9
Participation rate...........
Employed........................ 75,337
Employment-pop72.8
ulation ratio 2……………
3,259
Unemployed...................
4.1
Unemployment rate.....
Not in the labor force……… 24,959
104,453 104,613 104,741 104,869 104,978 105,083 104,902 104,999 105,095 105,196 105,299 105,412 105,530 105,651
79,047
79,308
79,392
79,380
79,335
78,998
78,585
78,687
78,578
79,081
79,395
79,291
79,045
79,231
75.7
75.8
75.8
75.7
75.6
75.2
74.9
74.9
74.8
75.2
75.4
75.2
74.9
75.0
74,750
74,737
74,503
74,292
74,045
73,285
72,613
72,293
71,655
71,678
71,593
71,387
71,319
71,204
71.6
4,297
5.4
25,406
71.4
4,572
5.8
25,305
71.1
4,889
6.2
25,349
70.8
5,088
6.4
25,489
70.5
5,290
6.7
25,643
69.7
5,714
7.2
26,085
69.2
5,972
7.6
26,318
68.9
6,394
8.1
26,312
68.2
6,923
8.8
26,516
68.1
7,403
9.4
26,115
68.0
7,802
9.8
25,904
67.7
7,904
10.0
26,121
67.6
7,726
9.8
26,485
67.4
8,027
10.1
26,420
Women, 20 years and over
Civilian noninstitutional
1
population ……………………. 111,330
Civilian labor force.............. 67,516
60.6
Participation rate...........
Employed........................ 64,799
Employment-pop58.2
ulation ratio 2……………
2,718
Unemployed...................
4.0
Unemployment rate.....
Not in the labor force……… 43,814
112,260 112,401 112,518 112,633 112,731 112,825 112,738 112,824 112,908 112,999 113,089 113,189 113,296 113,405
68,382
68,666
68,385
68,700
68,753
68,891
68,584
68,917
68,977
69,148
69,112
69,060
68,985
68,923
60.9
61.1
60.8
61.0
61.0
61.1
60.8
61.1
61.1
61.2
61.1
61.0
60.9
60.8
65,039
65,003
65,008
64,975
64,902
64,860
64,298
64,271
64,148
64,226
63,895
63,810
63,789
63,662
57.9
3,342
4.9
43,878
57.8
3,662
5.3
43,736
57.8
3,377
4.9
44,133
57.7
3,725
5.4
43,933
57.6
3,851
5.6
43,978
57.5
4,031
5.9
43,935
57.0
4,286
6.2
44,154
57.0
4,646
6.7
43,907
56.8
4,828
7.0
43,931
56.8
4,922
7.1
43,850
56.5
5,217
7.5
43,976
56.4
5,249
7.6
44,130
56.3
5,196
7.5
44,311
56.1
5,261
7.6
44,481
17,075
6,858
40.2
5,573
17,092
6,849
40.1
5,533
17,101
6,844
40.0
5,518
17,110
6,799
39.7
5,390
17,118
6,531
38.2
5,196
17,126
6,557
38.3
5,194
17,098
6,547
38.3
5,188
17,090
6,610
38.7
5,184
17,083
6,493
38.0
5,083
17,076
6,501
38.1
5,103
17,064
6,573
38.5
5,082
17,053
6,575
38.6
4,999
17,044
6,474
38.0
4,933
17,031
6,423
37.7
4,783
32.6
1,285
18.7
10,218
32.4
1,316
19.2
10,243
32.3
1,326
19.4
10,257
31.5
1,408
20.7
10,311
30.4
1,335
20.4
10,587
30.3
1,363
20.8
10,568
30.3
1,359
20.8
10,551
30.3
1,427
21.6
10,480
29.8
1,410
21.7
10,590
29.9
1,398
21.5
10,575
29.8
1,491
22.7
10,491
29.3
1,576
24.0
10,478
28.9
1,541
23.8
10,570
28.1
1,640
25.5
10,608
Both sexes, 16 to 19 years
Civilian noninstitutional
1
population ……………………. 16,982
7,012
Civilian labor force..............
41.3
Participation rate...........
5,911
Employed........................
Employment-pop34.8
ulation ratio 2……………
1,101
Unemployed...................
15.7
Unemployment rate.....
Not in the labor force……… 9,970
White3
Civilian noninstitutional
1
population ……………………. 188,253
Civilian labor force.............. 124,935
66.4
Participation rate...........
Employed........................ 119,792
Employment-pop63.6
ulation ratio 2……………
5,143
Unemployed...................
4.1
Unemployment rate.....
Not in the labor force……… 63,319
189,540 189,747 189,916 190,085 190,221 190,351 190,225 190,331 190,436 190,552 190,667 190,801 190,944 191,086
125,635 125,987 125,844 126,298 126,029 125,634 125,312 125,703 125,599 126,110 126,423 126,199 125,997 126,118
66.3
66.4
66.3
66.4
66.3
66.0
65.9
66.0
66.0
66.2
66.3
66.1
66.0
66.0
119,126 119,082 118,964 118,722 118,226 117,357 116,692 116,481 115,693 115,977 115,561 115,202 115,123 114,922
62.8
6,509
5.2
63,905
62.8
6,904
5.5
63,761
62.6
6,880
5.5
64,072
62.5
7,577
6.0
63,787
62.2
7,803
6.2
64,193
61.7
8,277
6.6
64,718
61.3
8,621
6.9
64,913
61.2
9,222
7.3
64,628
60.8
9,906
7.9
64,837
60.9
10,133
8.0
64,441
60.6
10,862
8.6
64,244
60.4
10,997
8.7
64,601
60.3
10,874
8.6
64,947
60.1
11,197
8.9
64,968
27,843
17,740
63.7
15,953
27,896
17,949
64.3
16,026
27,939
17,733
63.5
15,709
27,982
17,768
63.5
15,762
28,021
17,708
63.2
15,703
28,059
17,796
63.4
15,674
28,052
17,791
63.4
15,546
28,085
17,703
63.0
15,336
28,118
17,542
62.4
15,212
28,153
17,816
63.3
15,142
28,184
17,737
62.9
15,095
28,217
17,700
62.7
15,103
28,252
17,684
62.6
15,111
28,290
17,584
62.2
14,929
57.3
1,788
10.1
10,103
57.4
1,923
10.7
9,947
56.2
2,024
11.4
10,206
56.3
2,006
11.3
10,214
56.0
2,005
11.3
10,313
55.9
2,122
11.9
10,263
55.4
2,245
12.6
10,261
54.6
2,368
13.4
10,382
54.1
2,330
13.3
10,576
53.8
2,673
15.0
10,337
53.6
2,642
14.9
10,446
53.5
2,597
14.7
10,517
53.5
2,573
14.5
10,568
52.8
2,655
15.1
10,706
Black or African American3
Civilian noninstitutional
1
population ……………………. 27,485
Civilian labor force.............. 17,496
63.7
Participation rate...........
Employed........................ 16,051
Employment-pop58.4
ulation ratio 2……………
1,445
Unemployed...................
8.3
Unemployment rate.....
Not in the labor force……… 9,989
See footnotes at end of table.
72
Monthly Labor Review • October 2009
4. Continued—Employment status of the population, by sex, age, race, and Hispanic origin, monthly data seasonally adjusted
[Numbers in thousands]
Employment status
2008
Annual average
2007
2008
Aug.
32,141
22,024
68.5
20,346
32,273
22,201
68.8
20,404
63.3
1,678
7.6
10,116
63.2
1,797
8.1
10,072
Sept.
2009
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
July
Aug.
32,369
22,259
68.8
20,506
32,465
22,187
68.3
20,232
32,558
22,074
67.8
20,168
32,649
22,134
67.8
20,096
32,417
21,931
67.7
19,800
32,501
22,100
68.0
19,684
32,585
22,175
68.1
19,640
32,671
22,376
68.5
19,854
32,753
22,438
68.5
19,595
32,839
22,347
68.1
19,623
32,926
22,526
68.4
19,745
33,017
22,341
67.7
19,433
63.4
1,752
7.9
10,111
62.3
1,955
8.8
10,278
61.9
1,906
8.6
10,484
61.6
2,038
9.2
10,515
61.1
2,132
9.7
10,486
60.6
2,416
10.9
10,401
60.3
2,536
11.4
10,410
60.8
2,521
11.3
10,295
59.8
2,843
12.7
10,315
59.8
2,724
12.2
10,491
60.0
2,781
12.3
10,400
58.9
2,908
13.0
10,675
Hispanic or Latino
ethnicity
Civilian noninstitutional
1
population ……………………. 31,383
Civilian labor force.............. 21,602
68.8
Participation rate...........
Employed........................ 20,382
Employment-pop64.9
ulation ratio 2……………
1,220
Unemployed...................
5.6
Unemployment rate.....
Not in the labor force ………… 9,781
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
2007
2008
2008
Aug.
Sept.
Oct.
2009
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
July
Aug.
Characteristic
Employed, 16 years and older.. 146,047 145,362 145,273 145,029 144,657 144,144 143,338 142,099 141,748 140,887 141,007 140,570 140,196 140,041 139,649
Men....................................... 78,254
77,486
77,484
77,249
76,938
76,577
75,847
75,092
74,777
74,053
74,116
74,033
73,777
73,703
73,519
Women............................…… 67,792
67,876
67,789
67,780
67,720
67,567
67,491
67,007
66,970
66,834
66,890
66,537
66,419
66,339
66,131
Married men, spouse
46,314
45,860
45,804
45,887
45,787
45,610
45,182
44,712
44,502
44,470
44,469
44,255
44,294
43,992
43,943
35,832
35,869
35,994
35,864
35,590
35,649
35,632
35,375
35,563
35,481
35,444
35,391
35,464
35,377
35,199
4,401
5,875
5,879
6,292
6,848
7,323
8,038
7,839
8,626
9,049
8,910
9,084
8,989
8,798
9,076
2,877
4,169
4,240
4,418
4,953
5,399
6,020
5,766
6,443
6,857
6,699
6,794
6,783
6,849
6,941
1,210
1,389
1,412
1,514
1,514
1,585
1,617
1,667
1,764
1,839
1,810
1,922
1,980
1,835
2,044
reasons……………………… 19,756
19,343
19,690
19,275
19,083
18,886
18,922
18,864
18,855
18,833
19,065
18,872
18,718
19,018
18,814
4,317
5,773
5,802
6,167
6,742
7,209
7,932
7,705
8,543
8,942
8,826
8,928
8,845
8,647
8,945
2,827
4,097
4,171
4,279
4,889
5,304
5,938
5,660
6,390
6,773
6,650
6,681
6,699
6,733
6,844
1,199
1,380
1,385
1,541
1,499
1,579
1,619
1,658
1,760
1,850
1,802
1,909
1,969
1,776
2,020
reasons.................………… 19,419
19,005
19,269
18,930
18,808
18,635
18,642
18,567
18,562
18,493
18,661
18,502
18,358
18,621
18,436
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 • October 2009 73
Current Labor Statistics: Labor Force Data
6. Selected unemployment indicators, monthly data seasonally adjusted
[Unemployment rates]
Annual average
Selected categories
2007
2008
2008
2009
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
July
Aug.
Characteristic
Total, 16 years and older............................
Both sexes, 16 to 19 years.....................
Men, 20 years and older.........................
Women, 20 years and older...................
4.6
15.7
4.1
4.0
5.8
18.7
5.4
4.9
6.2
19.2
5.8
5.3
6.2
19.4
6.2
4.9
6.6
20.7
6.4
5.4
6.8
20.4
6.7
5.6
7.2
20.8
7.2
5.9
7.6
20.8
7.6
6.2
8.1
21.6
8.1
6.7
8.5
21.7
8.8
7.0
8.9
21.5
9.4
7.1
9.4
22.7
9.8
7.5
9.5
24.0
10.0
7.6
9.4
23.8
9.8
7.5
9.7
25.5
10.1
7.6
White, total 1………………………………
4.1
13.9
15.7
12.1
3.7
3.6
5.2
16.8
19.1
14.4
4.9
4.4
5.5
17.3
19.5
15.0
5.1
4.7
5.5
17.5
19.7
15.2
5.5
4.2
6.0
18.6
22.6
14.4
5.8
4.9
6.2
18.4
21.4
15.3
6.1
5.1
6.6
18.7
21.4
16.0
6.5
5.5
6.9
18.4
21.8
14.8
6.8
5.8
7.3
19.1
22.2
16.0
7.4
6.1
7.9
20.0
23.3
16.7
8.0
6.5
8.0
19.7
22.5
16.9
8.5
6.4
8.6
20.3
24.4
16.0
9.0
6.9
8.7
21.4
23.9
18.9
9.2
6.8
8.6
22.2
25.8
18.5
9.1
6.8
8.9
24.1
27.9
20.1
9.3
6.9
8.3
29.4
33.8
25.3
7.9
6.7
10.1
31.2
35.9
26.8
10.2
8.1
10.7
29.3
29.8
28.9
10.6
9.1
11.4
29.8
32.9
26.7
11.9
9.3
11.3
32.9
37.2
27.8
11.8
8.9
11.3
32.2
42.0
23.2
12.1
9.0
11.9
33.7
35.2
32.2
13.4
8.9
12.6
36.5
44.0
29.8
14.1
9.2
13.4
38.8
45.6
32.1
14.9
9.9
13.3
32.5
41.2
25.2
15.4
9.9
15.0
34.7
42.1
27.2
17.2
11.5
14.9
39.4
46.1
34.0
16.8
11.2
14.7
37.9
44.4
32.4
16.4
11.3
14.5
35.7
39.2
32.5
15.8
11.7
15.1
34.7
46.0
24.7
17.0
11.9
5.6
2.5
2.8
4.6
4.9
7.6
3.4
3.6
5.8
5.5
8.1
3.7
3.7
6.3
5.7
7.9
3.9
3.5
6.3
5.9
8.8
4.1
4.2
6.8
5.7
8.6
4.2
4.3
7.0
5.8
9.2
4.4
4.5
7.5
5.9
9.7
5.0
4.7
8.0
5.9
10.9
5.5
5.1
8.6
5.8
11.4
5.8
5.4
9.2
5.9
11.3
6.3
5.5
9.6
6.1
12.7
6.8
5.7
10.2
6.0
12.2
6.9
5.6
10.3
5.9
12.3
6.9
5.5
10.1
6.0
13.0
7.1
5.4
10.5
6.3
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................
7.1
9.0
9.7
9.8
10.4
10.6
10.9
12.0
12.6
13.3
14.8
15.5
15.5
15.4
15.6
Some college or associate degree………..
4.4
3.6
5.7
4.6
5.8
5.0
6.3
5.1
6.5
5.3
6.9
5.5
7.7
5.6
8.0
6.2
8.3
7.0
9.0
7.2
9.3
7.4
10.0
7.7
9.8
8.0
9.4
7.9
9.7
8.2
Bachelor's degree and higher 4…………….
2.0
2.6
2.7
2.6
3.1
3.2
3.7
3.8
4.1
4.3
4.4
4.8
4.7
4.7
4.7
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
2007
2,542
2,232
2,303
1,061
1,243
16.8
8.5
2008
2,932
2,804
3,188
1,427
1,761
17.9
9.4
2008
Aug.
3,242
2,874
3,447
1,568
1,878
17.6
9.3
Sept.
2,864
3,083
3,662
1,621
2,041
18.7
10.3
Oct.
3,108
3,055
4,109
1,834
2,275
19.8
10.6
2009
Nov.
3,255
3,141
3,964
1,757
2,207
18.9
10.0
Dec.
3,267
3,398
4,517
1,927
2,591
19.7
10.6
NOTE: Beginning in January 2003, data reflect revised population controls used in the household survey.
74
Monthly Labor Review • October 2009
Jan.
3,658
3,519
4,634
1,987
2,647
19.8
10.3
Feb.
3,404
3,969
5,264
2,347
2,917
19.8
11.0
Mar.
3,371
4,041
5,715
2,534
3,182
20.1
11.2
Apr.
3,346
3,982
6,211
2,531
3,680
21.4
12.5
May
3,275
4,321
7,002
3,054
3,948
22.5
14.9
June
3,204
4,066
7,833
3,452
4,381
24.5
17.9
July
3,233
3,557
7,880
2,916
4,965
25.1
15.7
Aug.
3,026
4,120
7,816
2,828
4,988
24.9
15.4
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
2007
2008
2008
Aug.
Sept.
Oct.
2009
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
July
Aug.
3,515
976
2,539
793
2,142
627
4,789
1,176
3,614
896
2,472
766
4,994
1,279
3,715
999
2,678
829
5,348
1,396
3,952
982
2,587
822
5,811
1,367
4,443
946
2,650
825
6,156
1,413
4,744
940
2,655
760
6,471
1,524
4,946
1,007
2,777
829
6,980
1,441
5,539
917
2,751
780
7,696
1,488
6,208
820
2,834
1,005
8,243
1,557
6,686
887
2,974
868
8,814
1,625
7,189
890
3,087
900
9,546
1,832
7,714
910
3,180
956
9,649
1,762
7,886
822
3,335
947
9,560
1,680
7,880
885
3,312
967
9,818
1,718
8,100
829
3,307
1,085
49.7
13.8
35.9
11.2
30.3
8.9
53.7
13.2
40.5
10.0
27.7
8.6
52.6
13.5
39.1
10.5
28.2
8.7
54.9
14.3
40.6
10.1
26.6
8.4
56.8
13.4
43.4
9.2
25.9
8.1
58.6
13.4
45.1
8.9
25.3
7.2
58.4
13.8
44.6
9.1
25.1
7.5
61.1
12.6
48.5
8.0
24.1
6.8
62.3
12.0
50.2
6.6
22.9
8.1
63.5
12.0
51.5
6.8
22.9
6.7
64.4
11.9
52.5
6.5
22.5
6.6
65.4
12.6
52.9
6.2
21.8
6.6
65.4
11.9
53.5
5.6
22.6
6.4
64.9
11.4
53.5
6.0
22.5
6.6
65.3
11.4
53.9
5.5
22.0
7.2
3.2
.6
1.7
.5
3.5
.6
1.7
.5
3.8
.6
1.7
.5
4.0
.6
1.7
.5
4.2
.7
1.8
.5
4.5
.6
1.8
.5
5.0
.5
1.8
.7
5.4
.6
1.9
.6
5.7
.6
2.0
.6
6.2
.6
2.1
.6
6.2
.5
2.2
.6
6.2
.6
2.1
.6
6.4
.5
2.1
.7
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
2.3
3.1
Job losers 1…………………….…
.5
.6
Job leavers...............................
1.4
1.6
Reentrants................................
.4
.5
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
2008
2007
2008
Aug.
Sept.
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
15.7
17.5
14.5
8.2
3.6
3.7
3.1
5.8
12.8
18.7
22.1
16.8
10.2
4.6
4.8
3.8
6.2
13.3
19.2
22.2
17.4
10.7
5.0
5.2
4.1
6.2
13.4
19.4
21.7
17.8
10.8
5.0
5.3
4.2
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................
4.7
11.6
17.6
19.4
16.5
8.9
3.6
3.7
3.2
6.1
14.4
21.2
25.2
19.0
11.4
4.8
5.0
3.9
6.4
14.6
21.1
24.5
19.0
11.7
5.1
5.3
4.3
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…………
4.5
9.4
13.8
15.7
12.5
7.3
3.6
3.8
5.4
11.2
16.2
19.1
14.3
8.8
4.4
4.6
3.0
3.7
1
Oct.
2009
Nov.
Dec.
Jan.
6.6
13.8
20.7
23.1
18.4
10.6
5.3
5.5
4.6
6.8
13.9
20.4
24.1
18.3
11.1
5.6
5.8
4.8
7.2
14.7
20.8
24.1
19.1
12.1
6.0
6.3
4.9
7.6
14.8
20.8
21.4
20.2
12.1
6.4
6.7
5.2
8.1
15.5
21.6
22.9
21.0
12.9
6.9
7.2
5.6
8.5
16.3
21.7
23.7
20.9
14.0
7.2
7.6
6.2
8.9
16.7
21.5
23.0
21.3
14.7
7.5
7.8
6.4
May
9.4
17.3
22.7
23.4
22.9
15.0
8.1
8.4
6.7
June
9.5
17.8
24.0
25.1
23.7
15.2
8.2
8.5
7.0
July
9.4
17.8
23.8
25.4
23.0
15.3
8.1
8.4
6.7
Aug.
9.7
18.2
25.5
26.4
25.0
15.1
8.3
8.7
6.8
6.8
14.8
21.4
23.2
20.4
11.9
5.5
5.8
4.5
7.2
16.5
24.7
27.3
21.7
12.9
5.6
5.8
4.7
7.4
16.1
24.0
28.8
21.2
12.9
5.9
6.1
5.1
7.9
16.9
23.3
27.0
21.5
14.2
6.4
6.7
5.1
8.3
17.1
24.4
26.5
22.8
14.1
6.9
7.3
5.3
8.8
17.6
24.9
26.5
24.7
14.6
7.5
7.9
6.0
9.5
19.3
25.7
28.2
24.6
16.7
7.9
8.3
6.3
10.0
19.8
25.6
26.3
25.3
17.5
8.3
8.8
6.7
10.5
20.2
26.7
26.1
27.8
17.5
9.0
9.5
7.0
10.6
19.8
26.2
25.8
26.9
17.2
9.2
9.5
7.7
10.5
20.0
27.0
27.7
27.0
17.1
9.0
9.5
7.4
10.9
20.7
29.8
29.8
29.8
16.8
9.5
10.0
7.5
5.9
12.0
17.3
20.1
15.6
9.5
4.9
5.1
5.5
11.9
17.3
20.3
14.9
9.4
4.4
4.6
5.9
10.7
16.5
19.2
14.7
8.1
5.1
5.2
6.1
11.5
16.7
19.7
15.1
9.2
5.2
5.4
6.4
12.4
18.2
21.2
16.6
9.8
5.4
5.7
6.7
12.2
17.1
16.2
17.5
10.0
5.8
6.0
7.3
13.3
18.3
19.8
17.0
10.9
6.2
6.4
7.5
13.1
17.8
19.4
17.2
11.0
6.5
6.7
7.6
13.3
17.4
19.9
17.1
11.5
6.6
6.7
8.0
14.2
18.6
20.7
17.5
12.2
7.0
7.2
8.3
15.7
21.8
24.4
20.4
12.8
7.0
7.2
8.1
15.5
20.5
23.2
18.8
13.3
6.9
7.1
8.2
15.6
21.1
22.9
19.9
13.2
7.0
7.2
4.5
3.9
4.3
4.3
4.3
5.4
5.3
5.8
5.4
5.8
6.4
7.1
6.7
Data are not seasonally adjusted.
NOTE: Beginning in January 2003, data reflect revised population controls used in the household survey.
Monthly Labor Review • October 2009 75
Current Labor Statistics: Labor Force Data
10. Unemployment rates by State, seasonally adjusted
June
July
2008
State
July
2009p
2009p
June
July
2008
State
July
2009p
2009p
Alabama............................…………………
Alaska........................................................
Arizona............................……………………
Arkansas....................................................
California............................…………………
5.1
6.7
5.7
5.0
7.3
10.1
8.3
8.7
7.2
11.6
10.2
8.2
9.2
7.4
11.9
Missouri………………………………………
Montana.....................................................
Nebraska............................…………………
Nevada......................................................
New Hampshire............................…………
6.1
4.5
3.3
6.7
3.8
9.3
6.4
5.0
11.9
6.8
9.3
6.7
5.0
12.5
6.8
Colorado....................................................
Connecticut............................………………
Delaware...................................................
District of Columbia............................……
Florida........................................................
4.9
5.8
4.8
7.0
6.3
7.6
7.9
8.4
10.9
10.7
7.8
7.8
8.1
10.6
10.8
New Jersey................................................
New Mexico............................………………
New York...................................................
North Carolina............................……………
North Dakota.............................................
5.5
4.2
5.4
6.3
3.3
9.2
6.8
8.7
11.0
4.2
9.3
7.0
8.6
10.9
4.2
Georgia............................…………………
Hawaii........................................................
Idaho............................………………………
Illinois.........................................................
Indiana............................……………………
6.2
4.0
5.0
6.7
6.0
10.1
7.3
8.4
10.3
10.7
10.3
7.0
8.8
10.4
10.6
Ohio............................………………………
Oklahoma..................................................
Oregon............................……………………
Pennsylvania.............................................
Rhode Island............................……………
6.7
3.9
6.3
5.4
7.9
11.1
6.4
12.0
8.4
12.4
11.2
6.6
11.8
8.5
12.7
Iowa............................………………………
Kansas.......................................................
Kentucky............................…………………
Louisiana...................................................
Maine............................……………………
4.1
4.3
6.5
4.4
5.4
6.2
7.0
10.9
6.8
8.6
6.5
7.5
11.1
7.4
8.5
South Carolina............................…………
South Dakota.............................................
Tennessee............................………………
Texas.........................................................
Utah............................………………………
6.9
3.0
6.6
4.9
3.4
12.1
5.0
10.8
7.5
5.7
11.7
4.9
10.7
7.9
6.0
Maryland............................…………………
Massachusetts...........................................
Michigan............................…………………
Minnesota..................................................
Mississippi............................………………
4.4
5.2
8.3
5.4
7.3
7.2
8.6
15.2
8.4
9.1
7.2
8.8
15.0
8.1
9.7
Vermont............................…………………
Virginia.......................................................
Washington............................………………
West Virginia.............................................
Wisconsin............................………………
Wyoming....................................................
4.6
4.0
5.3
4.2
4.6
3.3
7.3
7.1
9.2
9.1
9.0
5.9
6.8
6.9
8.9
8.9
9.0
6.5
p
= preliminary
11. Employment of workers on nonfarm payrolls by State, seasonally adjusted
State
July
2008
June
2009p
July
2009p
State
July
2008
July
2009p
Alabama............................………… 2,161,527 2,127,390 2,108,750
Alaska.............................................
357,440
359,320
358,054
Arizona............................…………… 3,146,036 3,145,412 3,153,879
Arkansas........................................ 1,370,777 1,367,119 1,361,928
California............................………… 18,405,284 18,501,485 18,458,451
Missouri……………………………… 3,010,020
Montana.........................................
506,482
Nebraska............................…………
994,572
Nevada........................................... 1,374,762
New Hampshire............................…
738,531
2,995,945
499,170
984,400
1,400,378
738,496
3,003,321
499,049
980,794
1,400,331
740,208
Colorado......................................... 2,730,874
Connecticut............................……… 1,877,881
Delaware........................................
442,689
District of Columbia........................
333,035
Florida............................................ 9,240,335
2,700,034
1,878,610
437,327
328,293
9,202,891
2,690,935
1,884,593
433,983
329,606
9,207,857
New Jersey.....................................
New Mexico............................……
New York........................................
North Carolina............................…
North Dakota..................................
4,497,826
959,044
9,691,152
4,536,387
370,205
4,550,492
954,480
9,775,221
4,554,663
365,321
4,561,769
953,279
9,741,365
4,535,411
364,159
Georgia............................………… 4,845,555
Hawaii.............................................
654,853
Idaho............................……………
755,550
Illinois............................................. 6,694,696
Indiana............................…………… 3,234,314
4,765,522
645,319
749,417
6,652,588
3,213,243
4,764,573
645,433
754,591
6,646,220
3,158,473
Ohio............................………………
Oklahoma.......................................
Oregon............................……………
Pennsylvania..................................
Rhode Island............................……
5,979,879
1,749,922
1,961,165
6,396,148
568,056
5,973,139
1,777,563
1,978,460
6,439,939
569,948
5,951,729
1,778,175
1,972,457
6,389,316
573,584
Iowa............................………………
Kansas...........................................
Kentucky............................…………
Louisiana........................................
Maine............................……………
1,676,005
1,496,103
2,044,027
2,073,979
707,466
1,682,357
1,522,093
2,077,602
2,067,340
701,842
1,677,863
1,530,471
2,069,566
2,066,449
700,478
South Carolina............................… 2,154,794 2,195,408 2,182,993
South Dakota..................................
444,601
446,854
447,037
Tennessee............................……… 3,041,094 3,038,221 3,022,089
Texas.............................................. 11,708,438 11,972,833 12,017,910
Utah............................……………… 1,383,701 1,371,556 1,368,519
Maryland............................…………
Massachusetts...............................
Michigan............................…………
Minnesota.......................................
Mississippi............................………
2,998,410
3,425,606
4,927,360
2,933,841
1,316,676
2,953,280
3,420,398
4,869,232
2,956,917
1,296,899
2,956,023
3,440,444
4,857,097
2,964,399
1,291,409
Vermont............................…………
354,799
Virginia........................................... 4,123,932
Washington............................……… 3,476,183
West Virginia..................................
804,769
Wisconsin............................……… 3,077,959
Wyoming........................................
293,377
NOTE: Some data in this table may differ from data published elsewhere because of the continual updating of the database.
p
76
June
2009p
= preliminary
Monthly Labor Review • October 2009
359,460
4,157,365
3,563,389
790,341
3,092,772
290,799
360,235
4,148,781
3,556,136
788,662
3,081,545
291,256
12. Employment of workers on nonfarm payrolls by industry, monthly data seasonally adjusted
[In thousands]
Industry
Annual average
2007
TOTAL NONFARM................. 137,598
TOTAL PRIVATE........................ 115,380
2008
2008
Aug.
Sept.
Oct.
2009
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
Julyp
Aug.p
137,066 137,053 136,732 136,352 135,755 135,074 134,333 133,652 133,000 132,481 132,178 131,715 131,411 131,210
114,566 114,497 114,197 113,813 113,212 112,542 111,793 111,105 110,457 109,865 109,573 109,182 108,936 108,754
22,233
21,419
21,351
21,247
21,063
20,814
20,532
20,127
19,832
19,520
19,253
19,041
18,829
18,713
18,581
724
60.1
663.8
146.2
223.4
Mining, except oil and gas 1……
77.2
Coal mining……………………
Support activities for mining……
294.3
7,630
Construction................................
Construction of buildings........... 1,774.2
Heavy and civil engineering…… 1,005.4
Speciality trade contractors....... 4,850.2
Manufacturing.............................. 13,879
9,975
Production workers................
8,808
Durable goods...........................
6,250
Production workers................
515.3
Wood products..........................
500.5
Nonmetallic mineral products
455.8
Primary metals..........................
Fabricated metal products......... 1,562.8
1,187.1
Machinery……….....................
Computer and electronic
774
57.0
717.0
161.6
227.7
80.6
327.7
7,215
1,659.3
970.2
4,585.3
13,431
9,649
8,476
5,986
459.6
468.1
443.3
1,528.3
1,185.6
787
56.1
730.6
164.7
230.0
81.7
335.9
7,177
1,647.5
966.1
4,563.1
13,387
9,608
8,439
5,948
451.9
464.5
440.8
1,530.6
1,187.5
794
56.5
737.7
166.3
230.2
82.5
341.2
7,131
1,625.0
960.2
4,545.4
13,322
9,543
8,392
5,898
446.4
460.2
441.1
1,519.4
1,183.1
794
56.6
737.7
166.5
230.5
83.1
340.7
7,066
1,609.9
952.6
4,503.9
13,203
9,425
8,300
5,805
438.8
458.2
438.6
1,505.0
1,179.3
793
56.6
736.8
167.4
230.7
84.3
338.7
6,939
1,588.4
942.5
4,408.5
13,082
9,322
8,216
5,741
429.8
450.1
429.8
1,486.3
1,162.7
789
55.7
733.3
169.4
229.2
84.5
334.7
6,841
1,572.9
933.2
4,335.2
12,902
9,174
8,085
5,633
416.2
441.2
419.6
1,461.5
1,150.2
781
55.2
725.3
167.7
227.9
84.9
329.7
6,706
1,536.9
926.6
4,242.2
12,640
8,946
7,881
5,458
403.9
434.3
409.3
1,425.3
1,126.0
771
54.5
716.4
167.8
225.7
84.1
322.9
6,593
1,509.5
919.0
4,164.4
12,468
8,804
7,753
5,352
390.4
425.8
395.2
1,399.0
1,100.8
754
51.9
701.9
166.9
222.8
83.3
312.2
6,470
1,481.5
907.2
4,081.4
12,296
8,654
7,620
5,239
388.4
417.0
386.4
1,370.3
1,070.5
740
51.4
689.0
167.0
220.4
82.4
301.6
6,367
1,461.7
885.5
4,019.6
12,146
8,532
7,490
5,130
382.4
415.5
376.2
1,344.1
1,051.4
731
51.3
679.6
168.1
219.4
81.4
292.1
6,310
1,451.2
876.1
3,983.1
12,000
8,409
7,372
5,034
373.5
410.7
367.8
1,325.9
1,032.0
721
51.4
669.3
166.9
217.4
80.3
285.0
6,231
1,433.4
862.1
3,935.9
11,877
8,316
7,271
4,957
367.1
406.1
360.3
1,308.8
1,016.3
715
51.1
663.8
165.5
215.6
79.0
282.7
6,162
1,415.1
854.4
3,892.4
11,836
8,301
7,248
4,957
364.3
405.5
358.8
1,295.1
1,003.2
709
51.3
657.3
165.4
215.4
79.3
276.5
6,102
1,408.9
848.3
3,844.7
11,770
8,258
7,193
4,916
362.1
403.4
357.5
1,286.8
997.9
products 1……………………… 1,272.5
Computer and peripheral
1,247.6
1,248.3
1,246.5
1,239.8
1,233.3
1,223.7
1,212.9
1,196.9
1,187.1
1,171.1
1,156.1
1,142.4
1,134.5
1,125.2
GOODS-PRODUCING………………
Natural resources and
mining…………..……….......……
Logging....................................
Mining..........................................
Oil and gas extraction……………
equipment..............................
Communications equipment…
186.2
128.1
182.8
129.0
182.6
129.1
182.8
129.2
182.4
128.6
181.8
129.5
180.0
129.1
180.3
129.6
175.5
129.0
173.5
128.5
167.8
127.8
164.2
127.4
162.7
126.5
162.4
126.3
160.4
125.4
Semiconductors and
electronic components..........
Electronic instruments……….
447.5
443.2
432.4
441.6
432.3
442.6
431.0
442.5
428.4
440.2
423.2
438.8
417.4
437.5
410.5
433.8
403.3
431.9
397.6
430.9
389.2
431.1
382.8
427.2
375.6
424.4
371.0
422.2
367.9
419.7
Electrical equipment and
appliances...............................
Transportation equipment.........
429.4
1,711.9
424.9
1,606.5
425.5
1,584.5
422.6
1,572.6
421.3
1,531.3
417.5
1,532.5
412.0
1,501.8
406.1
1,423.5
399.1
1,423.7
389.7
1,400.4
382.0
1,365.9
378.4
1,335.3
377.0
1,309.6
374.0
1,339.0
372.9
1,320.8
Furniture and related
products.....……………………… 531.1
Miscellaneous manufacturing
641.7
Nondurable goods.....................
5,071
Production workers................
3,725
Food manufacturing.................. 1,484.1
481.0
630.8
4,955
3,663
1,484.8
475.7
630.1
4,948
3,660
1,482.7
470.3
629.4
4,930
3,645
1,484.3
458.8
628.5
4,903
3,620
1,484.7
449.6
624.2
4,866
3,581
1,489.0
440.6
618.4
4,817
3,541
1,477.6
428.6
611.0
4,759
3,488
1,470.7
417.4
604.5
4,715
3,452
1,467.2
408.8
601.1
4,676
3,415
1,464.4
401.0
600.4
4,656
3,402
1,474.9
394.4
597.4
4,628
3,375
1,471.7
388.1
595.1
4,606
3,359
1,473.8
382.7
590.9
4,588
3,344
1,473.9
378.4
588.2
4,577
3,342
1,475.5
Beverages and tobacco
products…………………………
Textile mills………………………
Textile product mills...................
Apparel………………………….
Leather and allied products.......
Paper and paper products.........
198.2
169.7
157.7
214.6
33.8
458.2
199.0
151.0
147.5
198.4
33.6
445.8
199.2
149.5
145.2
200.4
34.5
444.7
199.3
147.5
145.5
197.3
34.3
441.9
197.2
145.6
144.5
192.8
33.9
439.7
196.4
140.6
143.5
187.1
32.6
437.1
195.8
136.8
141.2
183.5
32.6
433.4
194.2
133.6
137.4
178.9
32.4
427.3
191.3
130.0
134.2
176.3
31.9
422.5
191.6
128.2
129.3
173.8
31.7
418.3
190.9
127.3
127.5
169.9
31.7
415.1
190.5
126.1
127.0
170.2
31.5
410.5
190.0
124.5
126.7
165.8
30.8
409.1
189.4
122.5
125.9
166.7
31.3
407.2
189.9
122.4
125.6
165.1
30.6
406.0
Printing and related support
activities…………………………
Petroleum and coal products.....
Chemicals..................................
Plastics and rubber products..
622.1
114.5
860.9
757.2
594.1
117.1
849.8
734.2
591.5
118.0
847.3
734.7
587.6
117.9
844.3
729.7
582.3
117.8
843.4
721.1
574.1
117.2
842.6
705.9
567.0
116.9
837.1
694.9
558.1
114.2
832.7
679.7
549.2
114.6
828.2
669.3
541.5
114.5
823.4
659.0
534.4
114.6
818.9
651.1
529.6
114.5
814.9
641.4
522.8
114.5
811.0
637.1
518.4
114.3
807.4
631.3
514.6
114.3
804.4
629.0
SERVICE-PROVIDING...................
115,366
115,646 115,702 115,485 115,289 114,941 114,542 114,206 113,820 113,480 113,228 113,137 112,886 112,698 112,629
PRIVATE SERVICEPROVIDING……………………… 93,147
Trade, transportation,
and utilities................................
Wholesale trade.........................
Durable goods…………………..
Nondurable goods……………
26,630
6,015.2
3,121.5
2,062.2
93,146
93,146
92,950
92,750
92,398
92,010
91,666
91,273
90,937
90,612
90,532
90,353
90,223
90,173
26,385
5,963.7
3,060.7
2,053.0
26,354
5,954.3
3,052.4
2,049.0
26,257
5,947.2
3,047.2
2,044.1
26,157
5,920.1
3,026.1
2,040.5
26,005
5,890.3
3,004.9
2,033.6
25,843
5,850.7
2,978.6
2,025.1
25,735
5,819.3
2,959.6
2,013.9
25,605
5,773.7
2,926.2
2,006.6
25,479
5,741.3
2,899.4
2,002.5
25,371
5,710.8
2,875.5
1,997.7
25,308
5,695.7
2,861.8
1,996.6
25,258
5,680.3
2,848.1
1,994.0
25,174
5,666.8
2,836.8
1,992.2
25,152
5,654.0
2,827.1
1,987.3
Electronic markets and
agents and brokers……………
831.5
850.1
852.9
855.9
853.5
851.8
847.0
845.8
840.9
839.4
837.6
837.3
838.2
837.8
839.6
Retail trade................................. 15,520.0 15,356.3 15,334.5 15,278.2 15,216.8 15,126.0 15,037.9 14,991.5 14,934.3 14,872.4 14,839.7 14,811.6 14,791.5 14,747.0 14,738.2
Motor vehicles and parts
dealers 1………………………
Automobile dealers..................
1,908.3
1,242.2
1,844.5
1,186.0
1,832.6
1,176.2
1,818.4
1,164.8
1,792.7
1,141.7
1,770.5
1,121.2
1,745.6
1,099.9
1,730.1
1,088.6
1,716.8
1,078.7
1,701.8
1,067.7
1,690.2
1,057.1
1,681.6
1,050.2
1,673.9
1,042.6
1,669.9
1,040.4
1,673.4
1,044.1
Furniture and home
furnishings stores....................
574.6
542.8
542.3
538.4
532.4
522.6
514.2
508.3
499.7
497.7
492.4
486.3
484.7
483.9
480.4
Electronics and appliance
stores.......................................
549.4
549.6
551.0
547.1
545.1
541.5
538.6
535.5
533.7
518.6
518.0
517.0
515.7
513.1
513.5
See notes at end of table.
Monthly Labor Review • October 2009 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
2009
2008
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
July p
Aug. p
1,309.3
2,843.6
1,253.1
2,858.4
1,245.9
2,853.8
1,248.4
2,846.5
1,245.9
2,851.9
1,235.8
2,843.5
1,227.8
2,835.1
1,214.9
2,835.3
1,207.1
2,826.0
1,193.5
2,827.6
1,189.3
2,828.9
1,186.3
2,828.0
1,181.1
2,828.8
1,175.3
2,823.5
1,169.0
2,821.4
993.1
861.5
1,002.4
843.4
999.0
840.9
998.9
834.8
995.9
836.1
989.4
836.9
991.2
834.4
985.7
833.0
986.9
832.1
985.0
830.4
984.2
831.1
984.7
829.0
984.3
829.9
984.1
830.3
983.9
833.5
Clothing and clothing
accessories stores ………………… 1,500.0
1,484.2
1,483.3
1,478.5
1,471.5
1,462.2
1,448.5
1,445.0
1,443.8
1,433.4
1,432.7
1,426.8
1,420.1
1,414.4
1,407.1
Sporting goods, hobby,
656.3
book, and music stores……………
General merchandise stores1……… 3,020.6
Department stores………………… 1,591.5
Miscellaneous store retailers………
865.4
Nonstore retailers…………………… 437.9
646.7
3,047.1
1,557.0
847.8
436.3
645.8
3,058.2
1,554.4
845.6
436.1
641.6
3,045.8
1,541.9
844.3
435.5
641.2
3,025.5
1,523.9
845.0
433.6
633.1
3,024.5
1,517.5
838.3
427.7
624.3
3,029.2
1,521.2
825.0
424.0
620.8
3,040.7
1,529.1
819.5
422.7
613.6
3,040.7
1,532.6
815.1
418.8
610.0
3,045.5
1,530.9
810.4
418.5
608.8
3,041.2
1,524.0
805.3
417.6
607.0
3,041.8
1,526.0
805.8
417.3
605.1
3,045.1
1,528.6
804.8
418.0
605.4
3,032.8
1,523.3
797.6
416.7
605.8
3,034.6
1,528.1
799.0
416.6
Transportation and
warehousing................................. 4,540.9
Air transportation…………….……… 491.8
Rail transportation……...…………… 233.7
65.5
Water transportation………...………
Truck transportation………..……… 1,439.2
4,505.0
492.6
229.5
65.2
1,391.1
4,506.0
488.1
228.8
64.9
1,390.3
4,471.3
483.2
227.6
64.5
1,378.1
4,456.9
482.1
229.5
63.9
1,370.3
4,424.4
481.6
229.0
62.6
1,358.0
4,389.9
477.8
226.8
60.3
1,340.8
4,354.4
476.8
227.1
59.7
1,323.3
4,327.0
474.8
224.1
60.9
1,313.9
4,295.5
474.0
220.7
59.6
1,300.3
4,251.7
466.8
217.9
58.1
1,283.2
4,233.5
466.7
214.6
57.2
1,277.4
4,218.4
463.9
212.2
56.5
1,269.5
4,193.9
462.9
212.2
55.7
1,264.6
4,193.6
463.6
213.2
56.2
1,261.3
Building material and garden
supply stores................................
Food and beverage stores.............
Health and personal care
stores………………………………
Gasoline stations……………………
Transit and ground passenger
transportation………...……………
Pipeline transportation………...……
412.1
39.9
418.1
42.0
422.7
42.5
414.4
43.1
413.8
43.3
411.7
43.2
410.1
43.3
408.1
43.1
406.4
43.1
406.2
43.0
401.8
43.0
405.4
42.5
413.0
42.3
407.0
41.8
406.7
42.5
Scenic and sightseeing
transportation…….…………………
28.6
28.0
27.3
27.1
27.1
27.2
27.2
26.9
27.0
27.0
27.2
28.5
27.7
28.7
28.5
584.2
580.7
665.2
553.4
3,032
589.9
575.9
672.8
559.5
2,997
592.1
575.7
673.6
559.3
2,990
589.5
572.9
670.9
560.5
2,986
588.0
570.5
668.4
562.8
2,982
582.2
565.7
663.2
564.0
2,965
579.5
564.6
659.5
564.6
2,940
569.3
563.2
656.9
569.3
2,924
561.0
563.7
652.1
570.0
2,918
554.6
558.5
651.6
570.1
2,905
550.3
556.0
647.4
568.5
2,884
545.6
550.5
645.1
567.5
2,858
537.8
551.5
644.0
567.8
2,845
532.5
547.8
640.7
566.1
2,834
533.9
549.0
638.7
565.7
2,826
Publishing industries, except
Internet…………………...…………
901.2
882.6
879.4
876.6
872.6
863.6
857.8
846.3
836.3
827.8
820.1
808.6
801.8
795.6
787.9
Motion picture and sound
recording industries……...…………
Broadcasting, except Internet.
380.6
325.2
381.6
315.9
380.0
313.8
381.7
313.0
388.7
312.9
385.0
313.1
377.2
308.1
376.7
306.5
389.8
302.5
393.7
299.0
389.5
296.3
381.3
294.2
379.3
291.9
380.3
290.2
382.9
288.6
Internet publishing and
broadcasting………………...………
Telecommunications………….…… 1,030.6
1,021.4
1,023.1
1,021.6
1,014.5
1,010.2
1,004.0
1,001.6
999.5
996.7
989.3
986.4
981.6
978.2
976.0
261.6
133.6
8,146
6,015.2
259.8
133.6
8,141
6,010.6
259.6
133.6
8,115
5,994.3
258.9
134.1
8,088
5,978.7
257.5
135.1
8,043
5,948.7
256.4
136.5
8,010
5,924.0
257.0
135.7
7,954
5,890.4
254.6
134.8
7,898
5,853.9
253.9
134.1
7,857
5,829.5
255.5
133.7
7,811
5,799.6
253.8
133.2
7,784
5,781.6
254.4
135.5
7,751
5,760.5
254.8
135.3
7,737
5,748.0
257.0
134.0
7,712
5,729.8
21.6
22.2
22.3
22.3
22.1
21.5
21.3
21.0
20.9
20.8
20.5
20.3
20.3
20.2
20.3
related activities1………………… 2,866.3
Depository credit
2,735.8
2,724.4
2,722.4
2,706.4
2,692.8
2,680.8
2,665.3
2,648.8
2,635.4
2,619.8
2,613.5
2,604.0
2,602.1
2,592.4
intermediation1…………………… 1,823.5
Commercial banking..…………… 1,351.4
1,819.5
1,359.9
1,818.4
1,360.1
1,814.8
1,359.0
1,811.1
1,356.0
1,806.9
1,352.7
1,804.9
1,351.8
1,798.1
1,346.6
1,790.9
1,340.5
1,783.4
1,334.2
1,778.0
1,329.4
1,774.4
1,327.9
1,772.7
1,324.2
1,770.0
1,323.5
1,767.0
1,321.0
848.6
858.1
861.4
851.4
847.8
842.1
839.9
826.5
814.9
805.8
797.0
791.7
786.4
782.3
780.5
Insurance carriers and
related activities………………...… 2,306.8
2,308.8
2,312.0
2,307.6
2,311.0
2,300.9
2,292.0
2,287.4
2,281.1
2,279.4
2,274.3
2,268.3
2,261.9
2,256.5
2,249.6
88.7
90.3
90.5
90.6
91.4
91.4
90.0
90.2
88.2
88.1
88.0
87.8
87.9
86.9
87.0
Real estate and rental
and leasing………………………..… 2,169.1
Real estate……………………….… 1,500.4
Rental and leasing services………
640.3
2,130.2
1,481.1
620.9
2,130.0
1,482.4
619.4
2,120.6
1,474.5
617.7
2,109.0
1,471.2
609.7
2,093.8
1,461.7
603.8
2,085.8
1,458.2
599.3
2,063.2
1,444.9
589.9
2,043.8
1,432.4
583.2
2,027.0
1,421.9
576.6
2,011.7
1,411.9
571.5
2,002.7
1,405.1
569.2
1,990.6
1,396.3
566.5
1,988.6
1,396.4
564.6
1,981.9
1,392.5
562.1
Support activities for
transportation………………..……
Couriers and messengers……...……
Warehousing and storage…………
Utilities ………………………….……….....
Information…………………...….
ISPs, search portals, and
data processing………..…………
Other information services…………
267.8
126.3
8,301
Financial activities ………………..…
Finance and insurance……………..… 6,132.0
Monetary authorities—
central bank…………………..……
Credit intermediation and
Securities, commodity
contracts, investments……………
Funds, trusts, and other
financial vehicles…………….……
Lessors of nonfinancial
intangible assets………………..…
28.4
28.2
28.2
28.4
28.1
28.3
28.3
28.4
28.2
28.5
28.3
28.4
27.8
27.6
27.3
Professional and business
services…………………………...…
Professional and technical
17,942
17,778
17,727
17,675
17,612
17,488
17,356
17,205
17,029
16,910
16,783
16,756
16,655
16,624
16,605
services1……………………………
Legal services……………..………
7,659.5
1,175.4
7,829.7
1,163.7
7,833.0
1,161.0
7,834.4
1,160.2
7,844.0
1,160.2
7,827.7
1,157.7
7,797.2
1,156.8
7,765.5
1,154.1
7,729.2
1,148.7
7,697.9
1,144.9
7,670.7
1,139.4
7,652.4
1,136.9
7,615.6
1,131.7
7,598.9
1,128.2
7,582.6
1,128.1
Accounting and bookkeeping
services……………………………
935.9
950.1
947.9
945.6
946.4
941.0
933.7
927.5
924.4
929.5
929.3
938.0
936.8
934.8
934.3
Architectural and engineering
services…………………………… 1,432.2
1,444.8
1,447.2
1,441.4
1,437.1
1,428.6
1,419.4
1,411.1
1,394.2
1,377.9
1,364.1
1,350.3
1,335.9
1,324.5
1,320.6
.
See notes at end of table
78
2008
2007
Monthly Labor Review • October 2009
12. Continued—Employment of workers on nonfarm payrolls by industry, monthly data seasonally adjusted
[In thousands]
Industry
Annual average
2008
2009
2007
2008
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
Julyp
Aug.p
1,372.1
1,450.3
1,460.6
1,461.6
1,466.1
1,467.9
1,466.8
1,462.4
1,463.7
1,459.2
1,460.4
1,457.0
1,456.0
1,462.6
1,459.9
952.7
1,008.9
1,011.6
1,021.0
1,022.9
1,024.9
1,020.5
1,025.7
1,021.6
1,016.0
1,016.7
1,017.9
1,015.7
1,014.9
1,015.6
1,866.4
1,894.6
1,895.2
1,887.1
1,882.8
1,882.0
1,872.1
1,871.7
1,862.1
1,852.6
1,840.2
1,829.9
1,823.8
1,819.7
1,818.4
Administrative and waste
services…………………………… 8,416.3
Administrative and support
8,053.7
7,998.6
7,953.2
7,884.8
7,778.3
7,686.3
7,567.5
7,437.8
7,359.4
7,272.3
7,274.0
7,215.2
7,205.8
7,203.9
7,693.5
3,144.4
2,342.6
823.2
7,637.0
3,089.5
2,301.1
814.9
7,591.9
3,049.8
2,264.2
818.1
7,522.0
2,987.7
2,218.9
820.8
7,414.2
2,896.7
2,128.5
823.7
7,324.4
2,829.5
2,055.6
816.0
7,203.1
2,720.5
1,965.7
817.6
7,076.5
2,638.7
1,892.7
805.0
6,999.2
2,567.0
1,835.4
799.1
6,911.7
2,506.4
1,781.5
792.9
6,912.7
2,501.9
1,780.6
790.5
6,854.3
2,470.3
1,750.9
783.8
6,843.7
2,459.5
1,745.2
783.9
6,841.5
2,455.9
1,738.3
781.9
Computer systems design
and related services…………
Management and technical
consulting services……………
Management of companies
and enterprises……..……….....
services 1……………………… 8,061.3
Employment services 1……… 3,545.9
Temporary help services…… 2,597.4
817.4
Business support services……
Services to buildings
and dwellings…………………
1,849.5
1,847.0
1,847.0
1,843.3
1,837.4
1,829.4
1,818.1
1,812.5
1,796.8
1,791.5
1,778.7
1,786.1
1,771.2
1,769.8
1,767.3
Waste management and
remediation services………….
355.0
360.2
361.6
361.3
362.8
364.1
361.9
364.4
361.3
360.2
360.6
361.3
360.9
362.1
362.4
18,322
2,941.4
18,855
3,036.6
18,950
3,083.7
18,957
3,055.1
18,981
3,047.3
19,044
3,066.0
19,080
3,063.1
19,119
3,088.4
19,138
3,083.1
19,158
3,077.9
19,175
3,077.4
19,215
3,077.6
19,248
3,082.0
19,262
3,072.2
19,308
3,076.3
Educational and health
services………………...……….
Educational services…….………
Health care and social
assistance……….……………… 15,380.2 15,818.5 15,865.9 15,901.9 15,934.1 15,977.8 16,017.0 16,030.3 16,054.7 16,080.1 16,097.8 16,137.7 16,166.1 16,190.2 16,231.5
Ambulatory health care
services 1……………………… 5,473.5
Offices of physicians…………… 2,201.6
Outpatient care centers………
512.0
Home health care services……
913.8
Hospitals………………………… 4,515.0
5,660.7
2,265.7
532.5
958.0
4,641.1
5,683.8
2,272.7
537.2
963.4
4,660.7
5,699.5
2,279.0
534.8
966.8
4,668.9
5,706.1
2,283.3
536.6
968.6
4,681.9
5,727.7
2,289.8
536.9
975.6
4,692.4
5,742.6
2,294.5
536.7
980.7
4,703.7
5,753.3
2,300.4
538.0
981.4
4,707.5
5,770.1
2,304.4
538.5
991.0
4,711.3
5,779.8
2,308.0
537.7
996.7
4,715.1
5,794.1
2,310.5
538.7
1,004.5
4,716.7
5,812.9
2,314.6
539.3
1,013.3
4,719.1
5,830.6
2,321.9
543.5
1,016.7
4,718.9
5,842.0
2,329.8
542.0
1,018.2
4,722.4
5,856.3
2,336.1
543.3
1,021.1
4,723.0
3,008.1
1,613.7
2,508.7
859.2
13,459
3,009.9
1,612.6
2,511.5
851.6
13,454
3,007.6
1,608.9
2,525.9
862.5
13,428
3,013.2
1,611.0
2,532.9
862.3
13,395
3,022.3
1,614.5
2,535.4
863.2
13,344
3,029.6
1,617.3
2,541.1
864.3
13,304
3,029.4
1,616.6
2,540.1
862.7
13,268
3,033.6
1,617.9
2,539.7
860.4
13,236
3,041.0
1,621.8
2,544.2
858.2
13,202
3,042.8
1,624.5
2,544.2
853.9
13,168
3,049.1
1,626.8
2,556.6
860.3
13,195
3,056.3
1,628.9
2,560.3
854.3
13,176
3,064.7
1,631.4
2,561.1
845.9
13,177
3,072.8
1,635.9
2,579.4
856.5
13,163
Nursing and residential
care facilities 1………………… 2,958.3
Nursing care facilities………… 1,602.6
Social assistance 1……………… 2,433.4
Child day care services………
850.4
Leisure and hospitality………..
13,427
Arts, entertainment,
and recreation……….…….……
1,969.2
1,969.3
1,964.7
1,955.3
1,952.0
1,944.0
1,947.1
1,943.8
1,936.2
1,928.7
1,900.6
1,901.8
1,885.5
1,897.8
1,892.9
Performing arts and
spectator sports…………………
405.0
406.3
406.2
402.9
402.5
398.8
401.4
405.7
398.6
400.5
392.9
396.8
393.8
400.0
396.3
Museums, historical sites,
zoos, and parks…………………
130.3
131.8
132.1
130.6
129.6
130.6
130.8
130.3
130.9
130.6
130.5
130.9
130.8
130.5
130.5
1,433.9
1,431.2
1,426.4
1,421.8
1,419.9
1,414.6
1,414.9
1,407.8
1,406.7
1,397.6
1,377.2
1,374.1
1,360.9
1,367.3
1,366.1
Amusements, gambling, and
recreation………………………
Accommodations and
food services…………………… 11,457.4 11,489.3 11,489.3 11,472.4 11,442.7 11,399.6 11,356.5 11,323.7 11,299.7 11,273.2 11,267.0 11,293.6 11,290.0 11,278.8 11,270.3
Accommodations………………. 1,866.9
1,857.3 1,843.6 1,841.3 1,827.9 1,812.1 1,794.3 1,768.4 1,754.7 1,732.7 1,723.6 1,728.7 1,721.0 1,715.5 1,713.8
Food services and drinking
places…………………………… 9,590.4
Other services……………………
5,494
Repair and maintenance……… 1,253.4
Personal and laundry services
1,309.7
9,632.0
5,528
1,228.2
1,326.6
9,645.7
5,530
1,220.6
1,331.7
9,631.1
5,532
1,221.2
1,333.9
9,614.8
5,535
1,216.4
1,330.1
9,587.5
5,509
1,204.7
1,323.2
9,562.2
5,477
1,189.9
1,320.9
9,555.3
5,461
1,184.7
1,313.6
9,545.0
5,449
1,177.3
1,312.5
9,540.5
5,426
1,166.3
1,302.4
9,543.4
5,420
1,163.7
1,297.3
9,564.9
5,416
1,158.4
1,293.3
9,569.0
5,420
1,157.8
1,298.4
9,563.3
5,415
1,155.1
1,296.1
9,556.5
5,407
1,155.9
1,295.9
Membership associations and
organizations…………………… 2,931.1
Government..................................
Federal........................................
Federal, except U.S. Postal
Service....................................
U.S. Postal Service………………
State...........................................
Education................................
Other State government..........
Local...........................................
Education................................
Other local government...........
2,973.3
2,977.6
2,977.1
2,988.3
2,980.7
2,965.7
2,963.1
2,958.7
2,956.8
2,958.6
2,964.3
2,963.9
2,963.4
2,955.2
22,218
2,734
22,500
2,764
22,556
2,768
22,535
2,771
22,539
2,775
22,543
2,783
22,532
2,778
22,540
2,793
22,547
2,796
22,543
2,808
22,616
2,876
22,605
2,860
22,533
2,817
22,475
2,826
22,456
2,824
1,964.7
769.1
5,122
2,317.5
2,804.3
14,362
7,986.8
6,375.5
2,016.8
747.5
5,178
2,359.0
2,818.9
14,557
8,075.6
6,481.8
2,027.1
740.6
5,204
2,379.5
2,824.6
14,584
8,084.5
6,499.4
2,034.3
736.5
5,192
2,373.3
2,818.9
14,572
8,075.4
6,496.4
2,043.5
731.9
5,194
2,372.8
2,820.7
14,570
8,071.6
6,498.3
2,052.4
730.1
5,197
2,380.3
2,816.4
14,563
8,067.6
6,495.6
2,057.3
720.9
5,196
2,381.3
2,814.8
14,558
8,060.5
6,497.7
2,065.8
726.9
5,192
2,380.2
2,811.6
14,555
8,070.7
6,484.7
2,071.0
724.9
5,192
2,382.3
2,809.4
14,559
8,076.7
6,482.5
2,086.0
721.7
5,186
2,379.9
2,805.9
14,549
8,078.7
6,469.8
2,154.6
721.0
5,189
2,385.5
2,803.5
14,551
8,081.4
6,469.2
2,150.2
709.5
5,189
2,386.2
2,802.5
14,556
8,078.0
6,478.3
2,111.1
705.9
5,174
2,377.9
2,796.3
14,542
8,070.2
6,471.3
2,120.9
705.4
5,149
2,357.2
2,791.4
14,500
8,015.6
6,484.6
2,127.6
696.0
5,150
2,354.3
2,795.9
14,482
7,998.6
6,483.3
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 • October 2009 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
2007
2008
2008
2009
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
Julyp
Aug.p
33.1
TOTAL PRIVATE…………………………
33.9
33.6
33.7
33.6
33.5
33.4
33.3
33.3
33.3
33.1
33.1
33.1
33.0
33.1
GOODS-PRODUCING………………………
40.6
40.2
40.2
39.9
39.8
39.5
39.4
39.3
39.2
38.9
39.0
39.0
39.0
39.3
39.3
Natural resources and mining……………
45.9
45.1
45.3
44.5
44.7
45.3
44.3
44.2
43.9
43.4
43.0
43.3
43.3
42.9
43.4
Construction…………………………………
39.0
38.5
38.6
38.3
38.3
37.7
38.0
37.9
38.0
37.7
37.5
37.6
37.6
37.8
37.9
Manufacturing…………………….............
Overtime hours..................................
41.2
4.2
40.8
3.7
40.8
3.7
40.5
3.5
40.4
3.5
40.2
3.2
39.9
2.9
39.8
2.9
39.5
2.7
39.4
2.6
39.6
2.7
39.4
2.8
39.5
2.8
39.9
2.9
39.9
2.9
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..............
41.5
4.2
39.4
42.3
42.9
41.6
42.6
40.6
41.2
42.8
39.2
38.9
41.1
3.7
38.6
42.1
42.2
41.3
42.3
41.0
40.9
42.0
38.1
38.9
41.1
3.7
38.8
42.2
42.5
41.1
42.5
41.0
40.8
41.7
37.9
39.4
40.6
3.4
38.4
41.9
41.8
40.9
42.1
40.8
41.0
40.9
37.4
38.7
40.6
3.4
38.1
41.8
41.4
40.8
41.8
40.8
40.4
41.3
37.4
38.9
40.4
3.1
37.6
40.9
40.9
40.8
41.4
41.3
40.2
40.9
37.2
38.5
40.0
2.8
36.8
40.9
40.5
40.3
41.1
40.4
39.7
40.9
37.3
38.3
39.8
2.7
36.9
40.2
40.4
39.7
40.9
40.7
39.4
40.4
37.7
38.4
39.6
2.5
37.1
40.0
40.1
39.5
40.6
40.5
38.9
40.1
37.4
38.2
39.3
2.4
36.9
39.9
40.1
39.0
40.1
39.9
38.8
40.0
37.7
38.2
39.5
2.5
37.0
40.2
40.0
39.2
40.1
40.2
39.6
40.6
37.6
38.3
39.4
2.6
36.9
40.5
40.0
39.2
39.9
40.0
39.3
40.0
37.8
38.0
39.4
2.6
37.4
40.8
39.7
39.3
39.8
40.0
38.8
40.4
37.8
37.9
39.9
2.7
37.7
41.5
40.1
39.4
39.9
40.2
38.9
41.9
37.9
38.3
39.9
2.7
37.7
41.1
40.4
39.5
39.8
40.4
39.0
41.6
37.4
38.4
Nondurable goods..................................
Overtime hours..................................
Food manufacturing............................…
Beverage and tobacco products..........
Textile mills………………………………
Textile product mills……………………
Apparel.................................................
Leather and allied products..................
Paper and paper products………………
40.8
4.1
40.7
40.7
40.3
39.7
37.2
38.2
43.1
40.4
3.7
40.5
38.8
38.7
38.6
36.4
37.5
42.9
40.4
3.8
40.5
38.2
39.5
38.7
36.5
37.5
42.9
40.2
3.6
40.3
38.2
38.9
38.1
35.9
37.5
42.4
40.2
3.6
40.3
38.1
38.4
37.9
36.3
36.9
42.2
39.9
3.4
39.9
37.9
37.7
37.9
36.2
34.4
42.1
39.7
3.1
39.8
36.7
37.0
37.1
36.0
34.7
41.9
39.7
3.2
40.1
37.0
37.1
37.0
36.0
34.0
41.6
39.5
3.0
39.9
37.0
36.4
37.1
35.6
33.3
41.5
39.4
3.0
40.1
36.2
36.3
37.0
36.1
32.8
41.1
39.6
3.1
40.1
35.8
36.9
37.5
36.1
32.4
41.4
39.6
3.2
40.0
36.5
36.8
38.3
36.1
32.0
41.2
39.6
3.2
39.9
35.3
37.8
38.0
35.6
32.0
41.8
39.8
3.3
39.6
35.0
37.6
38.4
36.2
33.3
42.2
39.9
3.3
40.1
35.4
37.5
38.3
35.6
33.6
41.9
Printing and related support
activities.............................................
Petroleum and coal products……………
Chemicals…………………………………
Plastics and rubber products……………
39.1
44.1
41.9
41.3
38.3
44.6
41.5
41.0
38.2
45.6
41.4
41.0
38.3
45.2
41.3
40.7
38.3
45.2
41.5
40.6
38.2
44.4
41.3
40.6
38.0
45.3
41.1
40.0
37.7
45.1
41.1
39.9
37.3
43.8
41.1
39.6
37.5
44.3
40.9
39.4
37.7
43.8
41.0
39.8
37.6
43.4
41.1
39.8
38.1
43.4
41.2
39.8
38.5
43.2
41.6
40.4
38.6
44.2
41.4
40.3
PRIVATE SERVICEPROVIDING………………………………
32.4
32.3
32.4
32.3
32.3
32.2
32.2
32.2
32.1
32.1
32.0
32.0
31.9
32.0
32.0
Trade, transportation, and
utilities.......……………….......................
Wholesale trade........……………….......
Retail trade…………………………………
Transportation and warehousing………
Utilities………………………………………
Information…………………………………
Financial activities…………………………
33.3
38.2
30.2
37.0
42.4
36.5
35.9
33.2
38.2
30.0
36.4
42.7
36.7
35.8
33.2
38.3
30.0
36.4
42.3
36.8
36.1
33.2
38.1
30.1
36.4
42.7
36.9
36.0
33.1
38.2
29.9
36.3
42.5
36.9
35.9
33.0
38.1
29.8
36.1
42.4
37.0
36.1
32.9
37.8
29.7
36.2
42.9
37.0
35.9
32.9
38.1
29.7
36.0
42.6
37.2
36.2
32.8
37.9
29.8
35.7
43.2
36.9
36.2
32.7
37.8
29.7
35.7
42.4
36.7
36.1
32.8
37.8
29.8
35.8
42.3
36.4
36.0
32.9
37.6
29.9
36.0
42.1
36.5
36.0
32.8
37.6
29.8
35.8
41.9
36.4
35.9
32.8
37.4
29.8
36.3
41.9
36.4
35.9
32.8
37.6
29.8
36.3
42.0
36.4
36.1
Professional and business
services……………………………………
Education and health services……………
Leisure and hospitality……………………
Other services……………........................
34.8
32.6
25.5
30.9
34.8
32.5
25.2
30.8
34.9
32.6
25.2
30.9
34.8
32.5
25.2
30.7
34.9
32.5
25.1
30.7
34.9
32.4
25.0
30.7
34.8
32.4
25.0
30.6
34.9
32.4
24.8
30.7
34.8
32.3
25.0
30.6
34.7
32.4
24.8
30.5
34.7
32.3
24.8
30.5
34.7
32.3
24.7
30.5
34.6
32.2
24.7
30.3
34.6
32.2
24.7
30.4
34.7
32.2
24.7
30.4
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 • October 2009
NOTE: See "Notes on the data" for a description of the most recent benchmark
revision.
p = preliminary.
14. Average hourly earnings of production or nonsupervisory workers1 on private nonfarm payrolls, by industry,
monthly data seasonally adjusted
Industry
Annual average
2008
2009
2007
2008
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
Julyp
Aug.p
TOTAL PRIVATE
Current dollars………………………
Constant (1982) dollars……………
$17.43
8.33
$18.08
8.30
$18.18
8.20
$18.21
8.21
$18.28
8.33
$18.34
8.54
$18.40
8.65
$18.43
8.64
$18.46
8.61
$18.50
8.64
$18.50
8.65
$18.53
8.65
$18.54
8.57
$18.59
8.59
$18.66
8.58
GOODS-PRODUCING...............................
18.67
19.33
19.43
19.48
19.56
19.63
19.69
19.72
19.78
19.85
19.82
19.84
19.85
19.92
19.91
20.97
20.95
17.26
16.43
18.20
15.67
22.50
21.87
17.74
16.97
18.70
16.15
23.01
22.02
17.78
17.01
18.74
16.19
23.08
22.09
17.81
17.07
18.74
16.28
23.03
22.17
17.89
17.15
18.84
16.35
23.28
22.28
17.94
17.25
18.91
16.37
23.23
22.41
17.96
17.33
18.94
16.39
23.14
22.43
17.99
17.36
18.99
16.43
23.14
22.42
18.07
17.47
19.09
16.49
23.33
22.59
18.10
17.52
19.17
16.46
23.38
22.55
18.11
17.51
19.18
16.49
23.26
22.59
18.11
17.49
19.23
16.45
23.28
22.58
18.13
17.51
19.22
16.54
23.23
22.60
18.27
17.63
19.44
16.54
23.16
22.61
18.25
17.61
19.38
16.60
PRIVATE SERVICE-PRIVATE SERVICEPROVIDING..........………………..............
17.11
17.77
17.87
17.90
17.97
18.03
18.10
18.14
18.17
18.20
18.21
18.24
18.25
18.30
18.39
Trade,transportation, and
utilities…………………………………....
Wholesale trade....................................
Retail trade...........................................
Transportation and warehousing………
Utilities……………………………………
Information..............................................
Financial activities..................................
15.78
19.59
12.75
17.72
27.88
23.96
19.64
16.16
20.14
12.87
18.41
28.84
24.77
20.27
16.23
20.28
12.92
18.48
28.89
24.95
20.37
16.20
20.20
12.91
18.47
28.86
24.90
20.43
16.23
20.22
12.89
18.58
28.91
24.99
20.43
16.29
20.29
12.93
18.66
28.91
24.94
20.41
16.31
20.31
12.94
18.66
29.16
24.91
20.53
16.36
20.41
12.97
18.72
29.22
24.98
20.53
16.38
20.52
12.96
18.67
29.67
25.09
20.55
16.38
20.59
12.97
18.68
29.31
25.31
20.62
16.38
20.70
12.96
18.62
29.29
25.28
20.64
16.42
20.87
12.97
18.63
29.45
25.41
20.75
16.38
20.79
12.96
18.54
29.44
25.45
20.78
16.41
20.86
12.98
18.58
29.48
25.42
20.75
16.54
20.99
13.10
18.67
29.83
25.62
20.86
Professional and business
services.................................................
20.15
21.19
21.38
21.47
21.63
21.78
21.97
22.04
22.17
22.26
22.26
22.26
22.32
22.42
22.50
Education and health
services.................................................
Leisure and hospitality..........................
Other services.........................................
18.11
10.41
15.42
18.88
10.84
16.08
18.96
10.89
16.17
19.04
10.90
16.20
19.08
10.92
16.24
19.13
10.90
16.29
19.20
10.94
16.29
19.18
10.97
16.30
19.24
10.97
16.25
19.24
10.98
16.23
19.33
10.97
16.22
19.34
10.99
16.24
19.39
11.05
16.24
19.45
11.07
16.29
19.49
11.13
16.35
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 • October 2009 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
2007
TOTAL PRIVATE……………………………… $17.43
Seasonally adjusted…………………….
–
2008
2008
Aug.
Sept.
Oct.
2009
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
Julyp Aug.p
$18.08 $18.10 $18.25 $18.27 $18.40 $18.40 $18.49 $18.57 $18.57 $18.52 $18.47 $18.42 $18.49 $18.60
– 18.18 18.21 18.28 18.34 18.40 18.43 18.46 18.50 18.50 18.53 18.54 18.59 18.66
GOODS-PRODUCING......................................
18.67
19.33
19.53
19.63
19.61
19.65
19.75
19.64
19.64
19.74
19.78
19.83
19.83
19.97
19.99
Natural resources and mining……………..
20.97
22.50
23.06
23.19
22.98
23.31
23.53
23.41
23.19
23.40
23.40
23.10
22.94
23.08
23.05
Construction.…………..................................
20.95
21.87
22.16
22.34
22.28
22.32
22.52
22.32
22.25
22.45
22.44
22.54
22.47
22.68
22.75
Manufacturing…………………………………… 17.26
17.74
17.75
17.84
17.86
17.94
18.06
18.03
18.07
18.09
18.13
18.09
18.12
18.18
18.21
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 ...................
18.20
13.68
16.93
19.66
16.53
17.72
19.94
15.93
23.04
14.32
14.66
18.70
14.20
16.90
20.18
16.99
17.97
21.03
15.78
23.83
14.54
15.19
18.72
14.25
16.85
20.28
17.08
17.97
21.21
15.94
23.88
14.59
15.33
18.80
14.37
16.94
20.36
17.14
18.08
21.23
15.99
24.05
14.54
15.31
18.81
14.44
16.92
20.01
17.18
18.11
21.42
15.83
24.10
14.55
15.33
18.92
14.58
16.85
19.98
17.21
18.18
21.37
15.74
24.37
14.77
15.42
19.06
14.66
16.73
20.05
17.36
18.15
21.44
15.88
24.58
14.92
15.60
18.99
14.69
16.82
19.80
17.24
18.16
21.46
15.81
24.66
14.95
15.66
19.09
14.77
17.03
19.75
17.30
18.17
21.42
15.93
24.69
14.85
15.97
19.17
14.67
17.19
19.69
17.29
18.26
21.71
15.95
24.80
15.02
16.02
19.20
14.72
17.37
19.98
17.41
18.20
21.73
15.99
24.76
15.00
16.07
19.20
14.91
17.25
19.80
17.38
18.36
21.70
16.15
24.85
15.02
16.18
19.22
14.84
17.39
19.90
17.43
18.25
21.67
16.23
24.95
15.11
16.08
19.33
15.03
17.44
20.18
17.47
18.37
21.85
16.39
25.01
15.22
16.18
19.36
15.12
17.46
20.05
17.52
18.36
22.03
16.39
24.79
15.13
16.23
Nondurable goods………………………......
Food manufacturing ...........................……
Beverages and tobacco products .............
15.67
13.55
18.54
16.15
14.00
19.35
16.15
14.02
18.60
16.30
14.15
18.97
16.32
14.10
19.41
16.35
14.17
19.98
16.43
14.26
19.95
16.51
14.34
20.07
16.48
14.30
20.25
16.43
14.24
20.40
16.51
14.27
20.25
16.43
14.26
20.38
16.50
14.34
20.20
16.51
14.34
20.15
16.52
14.44
20.28
13.00
11.78
11.05
12.04
18.44
16.15
25.21
19.55
15.39
13.57
11.73
11.40
12.96
18.88
16.75
27.46
19.49
15.85
13.67
11.78
11.28
12.94
18.81
16.83
27.69
19.53
15.86
13.72
11.81
11.48
12.98
19.04
16.90
28.25
19.77
15.94
13.71
11.62
11.38
13.14
19.11
16.99
28.69
19.67
16.03
13.69
11.59
11.35
13.61
18.89
16.86
28.28
19.77
16.13
13.80
11.72
11.38
13.47
19.11
17.01
28.17
19.72
16.24
13.90
11.59
11.46
14.10
19.27
16.79
29.13
19.89
16.24
13.76
11.53
11.40
14.19
18.99
16.79
29.57
19.96
16.22
13.88
11.34
11.26
14.21
18.90
16.69
29.80
19.93
16.20
13.79
11.34
11.44
14.34
19.29
16.76
29.26
20.02
16.19
13.63
11.34
11.28
13.85
19.09
16.61
29.18
20.16
16.09
13.62
11.56
11.38
14.06
19.29
16.56
29.42
20.18
16.06
13.49
11.18
11.38
13.69
19.45
16.54
29.69
20.35
15.83
13.79
11.37
11.28
13.59
19.06
16.76
29.61
20.27
15.88
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 …………………………………….
17.11
17.77
17.73
17.90
17.94
18.10
18.09
18.23
18.33
18.31
18.24
18.18
18.11
18.16
18.29
Trade, transportation, and
utilities…….……..........................................
Wholesale trade ………………………………
Retail trade ……………………………………
Transportation and warehousing ……………
Utilities ………..…..….………..………………
15.78
19.59
12.75
17.72
27.88
16.16
20.14
12.87
18.41
28.84
16.21
20.23
12.93
18.52
28.64
16.27
20.20
13.01
18.53
28.95
16.24
20.21
12.89
18.55
29.00
16.26
20.41
12.85
18.69
28.96
16.14
20.36
12.74
18.62
29.28
16.37
20.44
12.96
18.68
29.27
16.47
20.65
12.99
18.73
29.70
16.45
20.64
13.02
18.64
29.42
16.42
20.69
13.01
18.58
29.50
16.40
20.78
12.99
18.54
29.50
16.35
20.66
12.96
18.54
29.27
16.39
20.83
12.99
18.64
29.33
16.56
21.04
13.12
18.75
29.56
Information………………………………….....
23.96
24.77
24.87
25.03
25.06
25.03
24.86
25.03
25.12
25.40
25.24
25.41
25.26
25.30
25.66
Financial activities……..………....................
19.64
20.27
20.29
20.42
20.41
20.54
20.50
20.48
20.68
20.67
20.65
20.72
20.66
20.65
20.87
20.15
21.19
21.12
21.31
21.45
21.97
22.01
22.16
22.52
22.52
22.28
22.15
22.11
22.25
22.40
services………………………………………… 18.11
Professional and business
services…………………………………………
Education and health
18.88
18.95
19.08
19.04
19.10
19.23
19.26
19.26
19.23
19.33
19.29
19.32
19.47
19.43
Leisure and hospitality ………………………
10.41
10.84
10.79
10.89
10.93
10.93
11.05
11.03
11.06
11.00
10.99
10.99
10.97
10.96
11.02
Other services…………………......................
15.42
16.08
16.10
16.22
16.17
16.24
16.27
16.34
16.34
16.33
16.27
16.29
16.16
16.17
16.30
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 • October 2009
16. Average weekly earnings of production or nonsupervisory workers1 on private nonfarm payrolls, by industry
Industry
Annual average
2007
TOTAL PRIVATE………………… $590.04
Seasonally adjusted..........
–
GOODS-PRODUCING………………
757.34
Natural resources
and mining………………………..
962.64
2008
2009
2008
Aug.
$607.99 $613.59
–
612.67
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
Julyp
Aug.p
$613.20
611.86
$613.87
612.38
$620.08
612.56
$610.88
612.72
$608.32
613.72
$616.52
614.72
$614.67
612.35
$607.46
612.35
$609.51
613.34
$609.70
611.82
$613.87
615.33
$624.96
617.65
791.09
788.32
782.07
778.15
762.03
758.10
763.94
759.55
773.37
779.32
788.82
795.60
1,013.78 1,051.54 1,041.23 1,038.70 1,072.26 1,040.03 1,020.68 1,008.77 1,003.86
776.60
794.87
994.50
990.99 1,000.18
987.82 1,016.51
816.66
842.36
875.32
869.03
866.69
845.93
840.00
828.07
823.25
837.39
830.28
856.52
858.35
879.98
Manufacturing……………………… 711.56
724.23
727.75
729.66
726.90
726.57
727.82
712.19
708.34
709.13
705.26
710.94
719.36
719.93
730.22
767.56
547.81
711.30
850.84
701.47
759.92
775.01
561.45
726.24
865.96
707.11
763.73
770.80
561.87
725.03
861.23
707.88
764.78
767.45
551.61
719.10
832.42
707.82
760.62
766.26
549.67
692.54
817.18
707.33
758.11
771.93
538.02
677.57
818.04
706.55
755.04
750.11
524.43
654.30
797.94
680.98
740.93
748.33
531.72
657.36
786.05
678.16
735.89
751.46
531.05
673.85
793.51
670.85
730.40
746.88
534.34
694.80
783.22
668.54
720.72
752.64
553.16
700.35
788.04
677.82
727.06
763.03
571.34
721.69
796.00
685.00
724.53
765.47
577.15
742.94
801.15
683.08
723.78
778.27
583.63
740.30
818.04
695.54
728.89
808.80
861.43
869.61
874.68
876.08
891.13
883.33
866.98
863.23
864.06
860.51
863.66
873.30
869.63
885.61
656.46
986.79
645.60
650.35
999.94 1,002.96
660.39
645.86
990.86 1,002.56
642.19
646.32
994.30 1,022.53
621.33
993.80
613.31
990.07
615.67
992.00
615.62
985.45
633.08
631.35
631.02
639.21
991.52 1,015.47 1,017.91 1,043.66
560.84
554.20
566.09
549.61
542.72
546.49
563.98
559.13
547.97
563.25
552.00
566.25
578.71
579.88
576.45
manufacturing..........................
569.99
591.73
608.60
595.56
593.27
593.67
600.60
599.78
603.67
613.57
610.66
614.84
612.65
618.08
631.35
Nondurable goods.......................
639.99
551.32
652.20
566.91
654.08
572.02
663.41
581.57
659.33
575.28
658.91
572.47
657.20
573.25
650.49
569.30
644.37
561.99
644.06
563.90
642.24
555.10
647.34
570.40
656.70
573.60
655.45
569.30
660.80
581.93
755.22
524.40
467.77
411.39
459.50
795.58
750.18
524.93
453.12
415.17
486.49
809.21
716.10
542.70
460.60
410.59
481.37
806.95
720.86
544.68
452.32
409.84
486.75
818.72
729.82
525.09
438.07
411.96
484.87
812.18
767.23
520.22
441.58
414.28
462.74
802.83
726.18
514.74
441.84
410.82
476.84
814.09
728.54
510.13
423.04
407.98
470.94
797.78
741.15
493.98
426.61
403.56
465.43
780.49
730.32
502.46
419.58
407.61
470.35
769.23
706.73
496.44
417.31
409.55
457.45
792.82
754.06
497.50
432.05
408.34
445.97
780.78
719.12
520.28
448.53
407.40
451.33
806.32
705.25
507.22
429.31
414.23
451.77
816.90
726.02
525.40
437.75
402.70
462.06
798.61
632.02
642.50
644.59
655.72
659.21
652.48
654.89
627.95
622.91
627.54
625.15
617.89
625.97
628.52
645.26
CONSTRUCTION
Durable goods……………………
754.77
539.34
Wood products .........................
716.78
Nonmetallic mineral products....
Primary metals…………………… 843.26
687.20
Fabricated metal products.........
Machinery………………………… 754.19
884.98
Computer and electronic
products..................................
Electrical equipment and
appliances...............................
Transportation equipment………
Furniture and related
products…………………………
Miscellaneous
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………………………… 1,112.73
Chemicals………………………… 819.54
1,224.26 1,259.90 1,302.33 1,322.61 1,275.43 1,256.38 1,307.94 1,286.30 1,290.34 1,258.18 1,254.74 1,285.65 1,309.33 1,308.76
808.80
810.50
820.46
814.34
822.43
814.44
811.51
820.36
815.14
816.82
820.51
835.45
844.53
841.21
Plastics and rubber
products…………………………
PRIVATE SERVICEPROVIDING…………....................
Trade, transportation,
and utilities………………………
Wholesale trade......…………......
Retail trade…………………………
635.63
649.04
650.26
655.13
652.42
658.10
657.72
647.98
639.07
636.66
633.03
635.56
644.01
633.20
643.14
554.89
574.31
576.23
578.17
577.67
588.25
578.88
579.71
592.06
587.75
580.03
579.94
577.71
582.94
594.43
526.07
748.94
385.11
535.79
769.91
386.39
541.41
774.81
391.78
543.42
767.60
395.50
535.92
772.02
384.12
536.58
787.83
381.65
531.01
767.57
380.93
530.39
770.59
378.43
538.57
784.70
384.50
537.92
782.26
384.09
535.29
775.88
385.10
537.92
779.25
388.40
536.28
776.82
387.50
542.51
776.96
393.60
551.45
799.52
396.22
Transportation and
warehousing……………………… 654.95
Utilities……………………………… 1,182.65
Information…………………………
670.33
679.68
676.35
671.51
680.32
679.63
663.14
663.04
665.45
655.87
661.88
663.73
678.50
690.00
1,231.19 1,205.74 1,244.85 1,238.30 1,236.59 1,256.11 1,243.98 1,286.01 1,241.52 1,250.80 1,241.95 1,226.41 1,223.06 1,238.56
874.65
908.44
917.70
926.11
924.71
936.12
917.33
921.10
931.95
934.72
911.16
914.76
911.89
920.92
946.85
Financial activities………………… 705.13
726.37
726.38
728.99
728.64
753.82
731.85
735.23
761.02
754.46
739.27
739.70
737.56
737.21
765.93
Professional and
business services………………
700.82
738.25
739.20
739.46
750.75
775.54
761.55
762.30
785.95
785.95
766.43
766.39
767.22
767.63
790.72
Education and………………………
health services…………………… 590.09
614.30
617.77
620.10
616.90
624.57
621.13
622.10
624.02
623.05
620.49
619.21
620.17
628.88
631.48
Leisure and hospitality…………… 265.52
273.27
278.38
272.25
273.25
273.25
270.73
264.72
275.39
272.80
270.35
271.45
274.25
277.29
282.11
Other services……………………… 477.06
494.99
500.71
497.95
496.42
501.82
496.24
498.37
501.64
498.07
494.61
495.22
489.65
493.19
502.04
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.
septTAB16
Monthly Labor Review • October 2009 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:
2005...............................................
52.6
60.1
54.1
58.1
56.8
58.3
58.5
59.2
54.2
55.9
62.7
57.6
2006..............................................
64.9
62.2
63.8
59.8
49.1
51.8
59.2
55.4
55.7
56.3
59.4
60.7
2007..............................................
53.5
55.5
52.4
49.4
55.9
48.3
50.7
46.5
55.9
57.2
59.4
57.9
2008…………………………………
42.1
40.6
44.1
41.1
42.6
36.9
37.6
39.1
34.7
33.0
27.1
20.5
2009…………………………………
22.1
20.8
19.6
21.8
29.3
25.8
30.3
34.9
2005...............................................
51.7
57.2
59.0
59.8
57.9
62.0
60.5
62.9
60.3
55.5
56.3
62.7
2006..............................................
67.7
68.6
65.1
65.1
60.5
58.9
55.5
57.0
55.0
54.4
59.0
64.2
2007..............................................
62.5
54.8
54.2
54.8
54.1
50.4
52.8
48.7
53.3
53.9
58.3
62.5
2008…………………………………
57.7
44.8
40.2
39.7
37.3
33.6
33.6
32.8
34.9
33.2
26.9
20.8
2009…………………………………
18.6
14.2
15.1
15.3
20.3
22.0
22.0
24.2
2005...............................................
55.4
57.9
58.1
57.0
58.3
60.9
63.1
63.3
61.6
59.6
61.4
62.5
2006..............................................
64.6
63.8
67.5
66.2
65.5
66.6
60.3
61.1
57.9
57.9
62.4
59.0
2007..............................................
60.3
57.2
60.5
58.3
55.5
56.5
52.8
52.4
56.6
54.4
56.8
59.0
2008…………………………………
56.6
53.0
50.7
47.4
40.2
33.4
31.0
33.4
30.6
29.0
26.0
24.4
2009…………………………………
21.6
17.2
15.1
15.3
15.9
16.6
15.9
20.1
2005...............................................
60.9
60.9
60.0
59.2
58.3
60.3
61.3
63.3
60.7
59.2
59.8
61.8
2006..............................................
67.2
65.5
65.9
62.9
65.5
66.8
64.8
64.4
66.6
65.9
64.9
66.2
2007..............................................
63.3
59.4
61.1
59.6
59.2
58.3
56.8
57.2
59.4
58.9
58.1
59.6
2008…………………………………
54.4
56.1
52.6
49.1
50.2
47.8
43.7
42.3
38.0
37.8
32.3
28.2
2009…………………………………
24.0
22.0
19.9
18.1
17.5
17.2
16.2
15.7
Over 3-month span:
Over 6-month span:
Over 12-month span:
Manufacturing payrolls, 84 industries
Over 1-month span:
2005...............................................
36.7
46.4
42.2
46.4
40.4
33.7
41.0
43.4
45.8
47.6
44.6
47.0
2006..............................................
57.8
49.4
53.6
47.0
37.3
50.6
49.4
42.2
40.4
42.8
41.0
44.0
2007..............................................
44.6
41.0
30.7
24.7
38.0
32.5
43.4
30.7
39.2
42.8
60.8
48.2
2008…………………………………
30.7
28.9
37.3
32.5
40.4
25.3
25.9
27.7
22.9
18.7
15.1
10.2
2009…………………………………
6.0
9.6
10.8
16.3
11.4
12.0
24.1
28.3
2005...............................................
36.7
43.4
41.0
41.6
35.5
36.1
34.9
36.7
42.2
44.0
38.6
48.8
2006..............................................
56.6
57.2
48.2
48.2
44.6
50.0
43.4
45.2
36.7
33.1
35.5
39.2
2007..............................................
40.4
33.1
33.1
28.9
29.5
30.1
31.9
28.9
30.7
30.7
39.2
51.2
2008…………………………………
48.8
33.7
28.3
29.5
26.5
22.9
19.9
16.9
22.3
21.1
15.1
11.4
2009…………………………………
6.0
3.6
3.6
7.8
8.4
12.0
8.4
12.0
2005...............................................
33.7
39.8
38.0
36.1
35.5
34.9
39.8
36.1
36.1
38.0
36.7
39.8
2006..............................................
45.2
45.2
50.6
48.8
50.6
50.0
45.2
47.0
43.4
42.2
39.8
34.3
2007..............................................
37.3
33.1
29.5
28.9
30.7
34.9
28.9
26.5
29.5
28.3
33.7
38.0
2008…………………………………
34.3
30.1
37.3
35.5
25.3
20.5
17.5
18.1
16.9
13.3
11.4
9.6
2009…………………………………
9.0
4.8
4.8
6.0
4.8
4.8
7.2
8.4
2005...............................................
45.2
44.0
42.2
41.0
36.7
35.5
32.5
34.3
33.1
33.7
33.7
38.0
2006..............................................
44.0
41.0
41.0
39.8
39.8
45.2
42.2
42.8
47.0
48.8
45.8
44.6
2007..............................................
39.8
36.7
37.3
30.7
28.9
29.5
30.7
28.9
33.1
28.9
34.3
35.5
2008…………………………………
27.7
28.9
25.9
25.3
30.7
27.1
24.7
19.3
21.7
21.7
16.9
15.1
2009…………………………………
8.4
4.8
4.8
4.8
6.0
6.0
6.6
4.8
Over 3-month span:
Over 6-month span:
Over 12-month span:
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 • October 2009
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
Feb.
2
Total ………………………………………………
Percent
2009
Mar.
Apr.
2009
May
June
p
July
Feb.
Aug.
Mar.
2.2
Apr.
1.9
May
1.9
June
1.9
p
July
1.9
Aug.
2,973
2,633
2,513
2,523
2,513
2,408
2,387
1.8
1.8
Total private 2…………………………………
2,606
2,269
2,042
2,191
2,163
2,090
2,077
2.3
2.0
1.8
2.0
1.9
1.9
1.9
Construction………………………………
58
51
29
39
56
47
62
0.9
0.8
0.5
0.6
0.9
0.8
1.0
Manufacturing……………………………
141
115
95
105
113
110
125
1.1
0.9
0.8
0.9
0.9
0.9
1.1
Trade, transportation, and utilities………
488
414
332
466
469
393
439
1.9
1.6
1.3
1.8
1.8
1.5
1.7
Professional and business services……
482
428
461
451
445
431
401
2.8
2.5
2.7
2.6
2.6
2.5
2.4
Education and health services…………
589
537
515
530
531
553
514
3.0
2.7
2.6
2.7
2.7
2.8
2.6
Leisure and hospitality……………………
332
289
322
265
276
256
247
2.4
2.1
2.4
2.0
2.1
1.9
1.8
367
353
461
310
322
314
307
1.6
1.5
2.0
1.4
1.4
1.4
1.3
2.0
Industry
Government…………………………………
Region3
Northeast…………………………………
607
583
520
554
609
508
507
2.4
2.3
2.0
2.2
2.4
2.0
South………………………………………
1,109
1,000
942
888
882
870
871
2.2
2.0
1.9
1.8
1.8
1.8
1.8
Midwest……………………………………
563
499
512
512
496
509
507
1.8
1.6
1.7
1.7
1.6
1.7
1.7
West………………………………………
638
556
570
544
561
517
541
2.1
1.8
1.9
1.8
1.9
1.7
1.8
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
Feb.
2
Total ………………………………………………
Percent
2009
Mar.
Apr.
May
2009
June
July
p
Aug.
Feb.
3.2
Mar.
3.1
Apr.
3.1
May
3.0
June
3.0
July
3.2
Aug.p
4,339
4,099
4,117
3,942
3,919
4,228
4,029
3.1
Total private 2…………………………………
4,042
3,799
3,822
3,739
3,654
3,930
3,762
3.6
3.4
3.5
3.4
3.3
3.6
3.5
Construction………………………………
370
343
341
365
277
355
306
5.6
5.3
5.4
5.8
4.5
5.8
5.0
Manufacturing……………………………
257
244
236
206
225
272
249
2.1
2.0
1.9
1.7
1.9
2.3
2.1
Trade, transportation, and utilities………
814
883
888
842
744
819
802
3.2
3.5
3.5
3.3
2.9
3.3
3.2
Professional and business services……
730
668
733
721
644
686
708
4.3
4.0
4.4
4.3
3.9
4.1
4.3
Education and health services…………
527
483
475
473
530
522
541
2.8
2.5
2.5
2.5
2.8
2.7
2.8
Leisure and hospitality……………………
704
693
691
695
695
716
700
5.3
5.3
5.3
5.3
5.3
5.4
5.3
275
271
340
273
262
282
264
1.2
1.2
1.5
1.2
1.2
1.3
1.2
2.9
Industry
Government…………………………………
Region3
Northeast…………………………………
837
696
729
712
735
714
710
3.3
2.8
2.9
2.9
3.0
2.9
South………………………………………
1,566
1,458
1,619
1,423
1,428
1,544
1,517
3.2
3.0
3.4
3.0
3.0
3.3
3.2
Midwest……………………………………
904
943
901
867
839
885
930
3.0
3.1
3.0
2.9
2.8
3.0
3.1
West………………………………………
960
931
949
995
917
1,042
867
3.2
3.1
3.2
3.4
3.1
3.5
2.9
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 • October 2009 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
Feb.
2
Total ………………………………………………
Percent
2009
Mar.
Apr.
May
2009
June
July
p
Aug.
Feb.
3.6
Mar.
3.5
Apr.
May
3.5
3.3
June
p
July
3.3
Aug.
4,833
4,712
4,641
4,356
4,306
4,430
4,265
3.4
3.3
Total private 2…………………………………
4,555
4,434
4,362
4,066
3,939
4,147
3,960
4.1
4.0
4.0
3.7
3.6
3.8
3.6
Construction………………………………
463
463
437
411
355
444
353
7.0
7.2
6.9
6.5
5.7
7.2
5.8
Manufacturing……………………………
424
401
390
367
352
329
318
3.4
3.3
3.2
3.1
3.0
2.8
2.7
Trade, transportation, and utilities………
920
1,001
982
951
816
874
826
3.6
3.9
3.9
3.8
3.2
3.5
3.3
Professional and business services……
951
778
839
771
698
738
721
5.6
4.6
5.0
4.6
4.2
4.4
4.3
Education and health services…………
498
466
462
419
489
500
506
2.6
2.4
2.4
2.2
2.5
2.6
2.6
Leisure and hospitality……………………
731
751
716
684
696
713
718
5.5
5.7
5.4
5.2
5.3
5.4
5.5
271
265
255
288
340
298
291
1.2
1.2
1.1
1.3
1.5
1.3
1.3
3.0
Industry
Government…………………………………
Region3
Northeast…………………………………
783
878
700
774
799
716
743
3.1
3.5
2.8
3.1
3.2
2.9
South………………………………………
1,742
1,741
1,682
1,565
1,535
1,602
1,509
3.6
3.6
3.5
3.3
3.2
3.4
3.2
Midwest……………………………………
1,121
1,085
1,065
1,016
958
958
967
3.7
3.6
3.5
3.4
3.2
3.2
3.2
West………………………………………
1,188
978
1,188
980
1,053
1,181
1,066
4.0
3.3
4.0
3.3
3.6
4.0
3.6
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
Feb.
2
Total ………………………………………………
Percent
2009
Mar.
Apr.
May
2009
June
July
p
Aug.
Feb.
1.4
Mar.
1.4
Apr.
1.3
May
1.4
June
1.4
July
p
Aug.
1,911
1,856
1,777
1,788
1,787
1,778
1,739
1.4
1.3
Total private 2…………………………………
1,831
1,749
1,678
1,682
1,680
1,673
1,639
1.6
1.6
1.5
1.5
1.5
1.5
1.5
Construction………………………………
87
102
74
84
70
68
63
1.3
1.6
1.2
1.3
1.1
1.1
1.0
Manufacturing……………………………
105
81
80
86
93
82
81
.8
.7
.7
.7
.8
.7
.7
Trade, transportation, and utilities………
372
444
385
398
391
415
384
1.5
1.7
1.5
1.6
1.5
1.6
1.5
Professional and business services……
310
278
272
281
257
265
255
1.8
1.6
1.6
1.7
1.5
1.6
1.5
Education and health services…………
258
249
228
249
264
235
245
1.3
1.3
1.2
1.3
1.4
1.2
1.3
Leisure and hospitality……………………
431
433
430
396
429
411
429
3.3
3.3
3.3
3.0
3.3
3.1
3.3
115
107
99
107
111
107
104
.5
.5
.4
.5
.5
.5
.5
Northeast…………………………………
271
273
263
303
279
234
265
1.1
1.1
1.1
1.2
1.1
1.0
1.1
South………………………………………
759
751
691
718
693
724
677
1.6
1.6
1.4
1.5
1.5
1.5
1.4
Midwest……………………………………
468
431
410
397
403
435
372
1.5
1.4
1.4
1.3
1.3
1.5
1.2
West………………………………………
453
408
453
398
434
404
435
1.5
1.4
1.5
1.3
1.5
1.4
1.5
Industry
Government…………………………………
Region3
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 • October 2009
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, fourth quarter 2008.
County by NAICS supersector
Establishments,
fourth quarter
2008
(thousands)
Average weekly wage1
Employment
December
2008
(thousands)
Percent change,
December
2007-082
Fourth
quarter
2008
Percent change,
fourth quarter
2007-082
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 .............................................................................
9,177.5
8,884.3
127.0
881.7
360.0
1,925.3
147.4
862.8
1,537.6
857.4
742.2
1,229.1
293.2
133,870.4
111,752.9
1,802.7
6,636.1
12,891.3
26,316.1
2,948.2
7,853.7
17,366.1
18,304.3
12,957.7
4,445.7
22,117.5
-2.3
-2.9
2.0
-10.2
-6.2
-3.5
-3.4
-3.2
-4.1
2.9
-1.7
-.7
.9
$918
919
996
1,052
1,094
766
1,360
1,390
1,201
872
390
581
914
2.2
2.0
5.1
4.9
1.8
1.1
.1
-.4
3.7
3.7
1.8
2.8
4.0
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 .............................................................................
433.9
430.0
.5
14.0
14.5
53.6
8.8
24.1
42.6
28.1
27.2
201.1
4.0
4,152.9
3,552.8
10.5
136.7
417.6
802.4
207.5
231.8
574.2
500.0
396.1
258.8
600.1
-3.4
-3.8
-2.7
-12.3
-5.9
-5.4
( 4)
-5.7
( 4)
( 4)
-1.6
.5
( 4)
1,075
1,064
1,261
1,138
1,107
833
1,889
1,462
1,306
979
927
454
1,141
1.8
1.1
5.4
4.8
3.8
-.8
(4)
-3.8
(4)
(4)
5.9
1.1
5.6
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 .............................................................................
141.0
139.6
.1
12.4
7.0
27.6
2.6
15.7
29.1
14.0
11.7
14.6
1.4
2,480.0
2,169.2
1.1
82.8
219.9
467.7
56.1
203.7
423.4
386.1
227.5
96.1
310.8
-2.8
-3.3
-5.6
-10.5
-6.5
-4.9
-3.2
-4.3
-4.8
3.1
-2.2
-.1
.8
1,118
1,126
998
1,478
1,119
840
1,487
2,007
1,525
930
440
783
1,058
1.5
1.3
-5.0
6.9
3.0
-.4
-4.3
.7
3.5
1.3
.0
3.2
2.9
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 .............................................................................
118.9
118.6
.0
2.4
3.0
22.0
4.6
19.2
25.5
8.9
11.8
18.0
.3
2,386.4
1,934.3
.2
36.3
33.7
255.2
134.5
369.0
489.1
297.7
224.3
90.2
452.1
-1.3
-1.6
-3.6
.6
-8.3
-3.3
-1.5
-3.9
-2.4
1.6
.8
.7
.0
1,856
2,041
1,594
1,939
1,565
1,294
2,055
4,085
2,173
1,133
889
1,102
1,062
-.6
-.7
4.7
.6
.7
-1.5
-.3
-1.3
.6
6.0
-.7
( 4)
1.6
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 .............................................................................
98.1
97.6
1.6
6.7
4.6
22.5
1.4
10.6
19.6
10.4
7.6
11.9
.5
2,078.1
1,820.6
85.8
156.9
187.7
443.1
32.0
117.9
336.9
224.3
175.2
59.6
257.5
1.0
.9
7.1
.5
2.4
.6
-2.4
-2.7
-.2
3.1
-.6
.4
1.8
1,187
1,215
2,872
1,217
1,468
1,035
1,393
1,517
1,448
958
404
673
988
2.6
2.3
-7.6
7.1
-3.4
4.0
8.2
4.7
3.7
3.2
4.7
3.2
5.2
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 .............................................................................
103.6
102.9
.5
11.0
3.6
22.9
1.7
12.9
23.2
10.3
7.4
7.4
.7
1,741.0
1,512.8
9.0
115.5
120.8
365.7
29.4
140.1
289.2
216.8
176.8
48.4
228.2
-5.8
-6.9
-4.9
-25.3
-8.0
-6.8
-4.1
-4.8
-8.5
5.7
-5.3
-4.9
2.0
892
893
1,026
986
1,217
796
1,098
1,066
989
999
420
613
881
2.1
2.2
20.6
3.4
3.6
.9
3.4
-.4
5.0
2.3
-1.4
2.7
.1
See footnotes at end of table.
Monthly Labor Review • October 2009 87
Current Labor Statistics: Labor Force Data
22. Continued—Quarterly Census of Employment and Wages: 10 largest counties, fourth quarter 2008.
County by NAICS supersector
Establishments,
fourth quarter
2008
(thousands)
December
2008
(thousands)
Percent change,
December
2007-082
Fourth
quarter
2008
Percent change,
fourth quarter
2007-082
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 .............................................................................
102.7
101.3
.2
6.9
5.3
17.2
1.3
10.7
19.1
10.0
7.1
18.0
1.4
1,451.2
1,301.1
4.2
83.3
166.4
272.3
29.0
110.0
258.3
150.8
171.7
49.0
150.1
-4.8
-5.3
-9.0
-14.9
-5.7
-6.9
-3.8
-7.5
-7.6
3.2
-2.2
-.3
-.8
$1,043
1,043
665
1,234
1,226
947
1,423
1,582
1,259
960
406
569
1,044
1.4
1.2
-2.8
4.5
-.2
1.4
4.0
-2.6
6.0
2.3
1.5
-4.2
3.2
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 .............................................................................
68.6
68.1
.6
4.4
3.1
15.2
1.7
8.8
15.1
6.7
5.4
6.6
.5
1,484.4
1,314.7
8.5
80.1
129.8
308.2
47.3
142.9
275.6
153.9
128.5
39.0
169.7
-1.2
-1.6
12.6
( 4)
-5.4
-2.1
-4.2
( 4)
( 4)
3.8
( 4)
-1.2
2.3
1,123
1,141
4,744
1,075
1,224
990
1,524
1,429
1,375
1,059
493
682
984
1.1
1.1
( 4)
(4)
1.1
-4.2
3.6
-1.7
2.4
3.1
(4)
3.6
2.2
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 .............................................................................
100.0
98.8
.8
7.0
3.1
14.2
1.3
9.5
16.3
8.2
6.9
26.9
1.3
1,309.1
1,082.3
9.4
70.4
100.4
218.3
38.6
74.2
210.9
138.3
158.2
58.4
226.8
-3.0
-3.5
-11.4
-14.3
-3.3
-6.3
.6
-5.7
-4.4
4.2
-2.3
2.0
-.4
981
960
577
1,140
1,306
759
1,970
1,171
1,238
953
425
491
1,079
2.0
1.6
.2
5.5
.9
.7
2.3
-1.0
2.0
3.1
3.9
1.7
2.8
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 .............................................................................
77.6
77.0
.4
6.6
2.4
14.9
1.8
6.9
13.7
6.5
6.2
17.6
.5
1,175.3
1,018.2
2.9
63.8
108.8
221.8
81.4
72.4
185.4
129.3
108.6
43.7
157.1
-1.5
-2.0
7.0
-11.6
-3.3
-2.9
6.1
-5.0
-3.3
4.6
-2.5
-.8
1.9
1,130
1,140
1,573
1,197
1,449
955
1,982
1,418
1,378
894
450
631
1,069
4.0
4.0
11.8
6.8
7.0
1.0
3.9
2.6
4.6
3.8
1.6
3.6
4.2
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 .............................................................................
86.8
86.4
.5
6.4
2.6
23.5
1.5
10.2
18.2
9.4
6.0
7.6
.4
1,003.9
851.3
9.6
42.0
41.2
253.4
19.0
67.2
132.2
145.9
104.0
36.2
152.6
-4.2
-4.7
-10.6
-21.4
-11.7
-4.0
-8.1
-7.6
-5.2
2.8
-1.9
-3.3
-1.1
924
907
457
973
818
814
1,266
1,387
1,229
901
514
579
1,017
2.6
2.3
-11.1
5.3
1.0
1.2
5.2
.1
6.6
1.7
.6
6.0
3.7
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
Average weekly wage1
Employment
Totals for the United States do not include data for Puerto Rico or the
Monthly Labor Review • October 2009
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, fourth quarter 2008.
State
Establishments,
fourth quarter
2008
(thousands)
Average weekly wage1
Employment
December
2008
(thousands)
Percent change,
December
2007-08
Fourth
quarter
2008
Percent change,
fourth quarter
2007-08
United States2 ...................................
9,177.5
133,870.4
-2.3
$918
2.2
Alabama ............................................
Alaska ...............................................
Arizona ..............................................
Arkansas ...........................................
California ...........................................
Colorado ...........................................
Connecticut .......................................
Delaware ...........................................
District of Columbia ...........................
Florida ...............................................
121.6
21.4
164.5
86.5
1,370.0
177.1
113.5
29.4
34.4
623.0
1,909.8
303.9
2,557.9
1,168.2
15,288.5
2,295.8
1,688.0
416.8
687.5
7,586.6
-3.1
1.6
-5.1
-1.5
-3.2
-1.5
-1.7
-3.0
.3
-5.3
790
927
848
706
1,042
932
1,164
943
1,570
824
3.5
5.7
2.7
-1.0
.7
.5
1.2
1.9
5.1
1.6
Georgia .............................................
Hawaii ...............................................
Idaho .................................................
Illinois ................................................
Indiana ..............................................
Iowa ..................................................
Kansas ..............................................
Kentucky ...........................................
Louisiana ...........................................
Maine ................................................
276.7
39.3
57.2
371.5
161.4
94.6
87.2
108.4
128.5
51.1
3,970.3
614.7
634.1
5,795.8
2,831.3
1,483.7
1,370.2
1,783.2
1,907.5
595.3
-3.5
-3.5
-3.9
-2.3
-3.4
-1.0
-.2
-2.6
.1
-2.1
853
821
693
985
764
756
769
754
829
735
2.3
3.5
1.0
1.0
2.7
3.1
3.1
3.0
5.9
4.0
Maryland ...........................................
Massachusetts ..................................
Michigan ............................................
Minnesota .........................................
Mississippi .........................................
Missouri .............................................
Montana ............................................
Nebraska ...........................................
Nevada ..............................................
New Hampshire ................................
164.3
215.1
258.2
172.0
71.0
175.7
43.2
60.4
77.5
49.9
2,531.8
3,239.6
3,993.3
2,658.8
1,117.2
2,700.9
433.8
923.1
1,206.5
626.2
-1.9
-1.1
-4.9
-1.9
-2.8
-1.7
-1.5
-.3
-6.5
-2.0
1,010
1,154
903
907
679
842
678
730
862
936
2.4
1.8
3.6
2.6
3.8
7.9
2.9
1.0
-1.1
2.2
New Jersey .......................................
New Mexico ......................................
New York ..........................................
North Carolina ...................................
North Dakota .....................................
Ohio ..................................................
Oklahoma ..........................................
Oregon ..............................................
Pennsylvania .....................................
Rhode Island .....................................
273.7
54.9
585.9
260.1
25.8
293.0
100.8
134.1
344.0
35.9
3,927.7
821.2
8,677.4
4,003.8
354.4
5,167.5
1,559.8
1,676.6
5,645.8
464.3
-2.4
-1.2
-1.0
-3.0
1.9
-3.2
.0
-3.7
-1.3
-3.4
1,123
768
1,169
793
725
816
755
808
897
887
2.8
3.9
1.4
1.9
5.1
2.6
4.9
1.3
2.6
5.7
South Carolina ..................................
South Dakota ....................................
Tennessee ........................................
Texas ................................................
Utah ..................................................
Vermont ............................................
Virginia ..............................................
Washington .......................................
West Virginia .....................................
Wisconsin ..........................................
119.5
30.8
143.1
566.6
88.3
25.1
233.5
222.8
48.9
161.1
1,837.1
395.2
2,695.7
10,510.8
1,215.0
304.4
3,656.8
2,885.0
713.8
2,753.2
-3.5
.4
-3.3
.4
-2.1
-1.7
-1.3
-1.8
-.1
-1.9
731
663
824
933
770
774
953
918
735
793
2.1
2.5
1.4
2.4
1.4
4.3
3.3
3.7
7.1
3.0
Wyoming ...........................................
25.2
284.5
1.5
850
4.3
Puerto Rico .......................................
Virgin Islands ....................................
55.3
3.6
1,028.5
45.5
-2.9
-1.4
528
731
2.3
-.8
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 • October 2009 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)
1998 ..................................................
1999 ..................................................
2000 ..................................................
2001 ..................................................
2002 ..................................................
2003 ..................................................
2004 ..................................................
2005 ..................................................
2006 ..................................................
2007 ..................................................
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
8,971,897
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
135,366,106
$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
6,018,089,108
$31,945
33,340
35,323
36,219
36,764
37,765
39,354
40,677
42,535
44,458
$614
641
679
697
707
726
757
782
818
855
$31,676
33,094
35,077
35,943
36,428
37,401
38,955
40,270
42,124
44,038
$609
636
675
691
701
719
749
774
810
847
$31,762
33,244
35,337
36,157
36,539
37,508
39,134
40,505
42,414
44,362
$611
639
680
695
703
721
753
779
816
853
$33,605
34,681
36,296
37,814
39,212
40,057
41,118
42,249
43,875
45,903
$646
667
698
727
754
770
791
812
844
883
$30,251
31,234
32,387
33,521
34,605
35,669
36,805
37,718
39,179
40,790
$582
601
623
645
665
686
708
725
753
784
$43,688
44,287
46,228
48,940
52,050
54,239
57,782
59,864
62,274
64,871
$840
852
889
941
1,001
1,043
1,111
1,151
1,198
1,248
UI covered
1998 ..................................................
1999 ..................................................
2000 ..................................................
2001 ..................................................
2002 ..................................................
2003 ..................................................
2004 ..................................................
2005 ..................................................
2006 ..................................................
2007 ..................................................
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
8,908,198
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
132,639,806
$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
5,841,231,314
Private industry covered
1998 ..................................................
1999 ..................................................
2000 ..................................................
2001 ..................................................
2002 ..................................................
2003 ..................................................
2004 ..................................................
2005 ..................................................
2006 ..................................................
2007 ..................................................
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
8,681,001
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
114,012,221
$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
5,057,840,759
State government covered
1998 ..................................................
1999 ..................................................
2000 ..................................................
2001 ..................................................
2002 ..................................................
2003 ..................................................
2004 ..................................................
2005 ..................................................
2006 ..................................................
2007 ..................................................
67,347
70,538
65,096
64,583
64,447
64,467
64,544
66,278
66,921
67,381
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
4,611,395
$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
211,677,002
Local government covered
1998 ..................................................
1999 ..................................................
2000 ..................................................
2001 ..................................................
2002 ..................................................
2003 ..................................................
2004 ..................................................
2005 ..................................................
2006 ..................................................
2007 ..................................................
137,902
140,093
141,491
143,989
146,767
149,281
155,043
157,309
158,695
159,816
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
14,016,190
$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
571,713,553
Federal government covered (UCFE)
1998 ..................................................
1999 ..................................................
2000 ..................................................
2001 ..................................................
2002 ..................................................
2003 ..................................................
2004 ..................................................
2005 ..................................................
2006 ..................................................
2007 ..................................................
47,252
49,661
50,256
50,993
50,755
51,753
52,066
52,895
52,916
63,699
NOTE: Data are final. Detail may not add to total due to rounding.
90
Monthly Labor Review • October 2009
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
2,726,300
$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
176,857,794
25. Annual data: Quarterly Census of Employment and Wages, establishment size and employment, private ownership, by
supersector, first quarter 2007
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 ...............................
8,572,894
112,536,714
5,189,837
7,670,620
Natural resources and mining
Establishments, first quarter ..................
Employment, March ...............................
124,002
1,686,694
69,260
111,702
23,451
155,044
15,289
205,780
10,137
304,936
3,250
222,684
1,842
278,952
519
179,598
190
126,338
64
101,660
Construction
Establishments, first quarter ..................
Employment, March ...............................
883,409
7,321,288
580,647
835,748
141,835
929,707
84,679
1,137,104
52,336
1,564,722
15,341
1,046,790
6,807
1,004,689
1,326
443,761
350
232,556
88
126,211
Manufacturing
Establishments, first quarter ..................
Employment, March ...............................
361,070
13,850,738
136,649
238,848
61,845
415,276
54,940
755,931
53,090
1,657,463
25,481
1,785,569
19,333
2,971,836
6,260
2,140,531
2,379
1,613,357
1,093
2,271,927
Trade, transportation, and utilities
Establishments, first quarter ..................
Employment, March ...............................
1,905,750
25,983,275
1,017,012
1,683,738
381,434
2,539,291
248,880
3,335,327
160,549
4,845,527
53,721
3,709,371
34,536
5,140,740
7,315
2,510,273
1,792
1,167,986
511
1,051,022
Information
Establishments, first quarter ..................
Employment, March ...............................
143,094
3,016,454
81,414
113,901
20,986
139,730
16,338
222,710
13,384
411,218
5,609
387,996
3,503
533,877
1,134
392,350
489
335,998
237
478,674
Financial activities
Establishments, first quarter ..................
Employment, March ...............................
863,784
8,146,274
563,670
890,816
155,984
1,029,911
81,849
1,080,148
40,668
1,210,332
12,037
822,627
6,313
945,396
1,863
645,988
939
648,691
461
872,365
Professional and business services
Establishments, first quarter ..................
Employment, March ...............................
1,456,681
17,612,073
989,991
1,375,429
196,645
1,292,744
125,014
1,685,085
83,127
2,520,739
32,388
2,243,595
20,412
3,102,005
5,902
2,012,609
2,263
1,535,591
939
1,844,276
Education and health services
Establishments, first quarter ..................
Employment, March ...............................
812,914
17,331,231
388,773
700,195
179,011
1,189,566
116,031
1,559,689
75,040
2,258,922
27,393
1,908,595
18,815
2,828,678
4,153
1,409,073
1,906
1,319,128
1,792
4,157,385
Leisure and hospitality
Establishments, first quarter ..................
Employment, March ...............................
716,126
12,949,319
275,121
439,080
120,795
815,688
132,408
1,858,394
134,766
4,054,666
39,766
2,648,733
10,681
1,510,212
1,639
551,528
646
438,008
304
633,010
Other services
Establishments, first quarter ..................
Employment, March ...............................
1,119,209
4,402,263
908,792
1,109,065
118,963
776,354
57,419
756,783
25,169
732,313
5,562
379,320
2,731
401,371
457
152,994
95
62,295
21
31,768
1
Includes establishments that reported no workers in March 2007.
2
Includes data for unclassified establishments, not shown separately.
1,407,987
933,910
648,489
220,564
124,980
30,568
9,326,775 12,610,385 19,566,806 15,156,364 18,718,813 10,438,705
11,049
5,510
7,479,948 11,568,298
NOTE: Data are final. Detail may not add to total due to rounding.
Monthly Labor Review • October 2009 91
Current Labor Statistics: Labor Force Data
26. Average annual wages for 2006 and 2007 for all covered workers1 by
metropolitan area
Average annual wages3
Metropolitan area2
2007
Percent
change,
2006-07
Metropolitan areas4 ..............................................................
$44,165
$46,139
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 ...........................................................................
29,842
19,277
38,088
32,335
41,027
36,934
31,329
39,787
30,394
33,574
31,567
20,295
39,499
33,378
42,191
38,191
32,757
41,784
31,988
35,574
5.8
5.3
3.7
3.2
2.8
3.4
4.6
5.0
5.2
6.0
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 .....................................
35,331
42,955
32,184
30,373
47,186
32,724
35,308
32,268
33,485
45,889
37,041
45,237
32,850
31,086
49,427
34,593
36,575
33,406
34,256
48,111
4.8
5.3
2.1
2.3
4.7
5.7
3.6
3.5
2.3
4.8
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 .....................................................................
38,018
30,468
35,638
45,737
36,020
45,177
31,746
36,437
37,245
39,362
39,276
31,554
36,915
46,458
38,254
47,177
32,829
37,691
39,339
40,628
3.3
3.6
3.6
1.6
6.2
4.4
3.4
3.4
5.6
3.2
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 .....................................................................
35,094
39,026
32,618
33,319
33,270
35,048
40,798
32,550
34,024
30,913
35,680
40,682
34,239
34,318
35,372
36,322
42,570
34,118
35,248
32,028
1.7
4.2
5.0
3.0
6.3
3.6
4.3
4.8
3.6
3.6
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 ......................................................
41,359
36,734
56,809
50,944
32,529
37,694
74,890
25,795
32,717
36,950
42,082
37,553
59,817
52,745
33,308
39,506
79,973
27,126
32,705
38,218
1.7
2.2
5.3
3.5
2.4
4.8
6.8
5.2
0.0
3.4
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 ..........................................
32,835
40,548
33,132
37,065
40,115
38,307
38,976
34,422
36,887
35,267
33,132
41,907
34,091
37,658
42,030
41,105
41,059
35,788
38,687
36,954
0.9
3.4
2.9
1.6
4.8
7.3
5.3
4.0
4.9
4.8
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 .................................................
45,732
39,051
35,358
35,306
48,631
31,557
41,447
30,949
33,075
41,325
46,975
40,819
36,522
36,191
50,823
33,207
42,969
32,216
34,666
42,783
2.7
4.5
3.3
2.5
4.5
5.2
3.7
4.1
4.8
3.5
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 .........................................................................
29,797
30,239
38,325
32,207
35,209
32,334
40,107
41,168
35,399
40,586
31,035
32,630
39,745
33,266
36,293
34,511
41,078
42,655
37,186
41,981
4.2
7.9
3.7
3.3
3.1
6.7
2.4
3.6
5.0
3.4
See footnotes at end of table.
92
2006
Monthly Labor Review • October 2009
26. Continued — Average annual wages for 2006 and 2007 for all covered
workers1 by metropolitan area
Average annual wages3
Metropolitan area2
Percent
change,
2006-07
2006
2007
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 .........................
$29,859
47,525
33,266
33,141
28,870
37,559
39,387
34,883
39,375
31,197
$31,373
49,627
34,433
34,086
30,212
39,385
40,223
35,931
41,039
32,196
5.1
4.4
3.5
2.9
4.6
4.9
2.1
3.0
4.2
3.2
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 .........................................................................
48,232
41,358
47,455
31,473
34,571
33,044
33,677
49,314
31,718
30,035
50,180
42,895
49,019
32,367
35,978
34,240
35,202
52,420
32,792
32,419
4.0
3.7
3.3
2.8
4.1
3.6
4.5
6.3
3.4
7.9
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 .......................................................................
32,072
35,878
33,968
29,903
33,213
33,257
36,858
41,296
21,002
33,542
32,701
36,566
34,879
31,354
34,788
34,329
37,182
42,345
22,075
35,264
2.0
1.9
2.7
4.9
4.7
3.2
0.9
2.5
5.1
5.1
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 .................................................................
36,220
31,281
35,734
32,231
39,409
33,610
29,518
33,376
37,940
30,932
38,572
33,216
37,325
34,473
39,310
34,305
30,699
34,664
39,335
31,236
6.5
6.2
4.5
7.0
-0.3
2.1
4.0
3.9
3.7
1.0
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 ...............................................................
34,409
35,641
33,504
29,499
34,573
34,765
32,780
29,331
29,234
33,729
35,613
36,542
35,111
30,979
36,243
36,994
33,564
30,177
30,745
36,221
3.5
2.5
4.8
5.0
4.8
6.4
2.4
2.9
5.2
7.4
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 .........................................
38,056
29,542
35,144
36,677
35,898
32,432
35,471
24,551
34,688
34,621
38,953
31,009
37,066
37,788
37,213
33,703
36,536
26,094
34,971
35,468
2.4
5.0
5.5
3.0
3.7
3.9
3.0
6.3
0.8
2.4
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 .....................................................................
31,148
39,807
31,522
51,282
30,059
31,323
31,416
36,895
39,009
27,684
32,504
41,424
32,718
54,188
30,729
32,364
33,210
37,470
40,748
28,448
4.4
4.1
3.8
5.7
2.2
3.3
5.7
1.6
4.5
2.8
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 ..........................................................................
38,417
50,177
32,648
44,659
31,632
41,307
35,913
38,337
36,836
34,605
41,604
53,494
33,973
45,763
29,878
42,227
37,457
39,387
38,267
35,771
8.3
6.6
4.1
2.5
-5.5
2.2
4.3
2.7
3.9
3.4
See footnotes at end of table.
Monthly Labor Review • October 2009 93
Current Labor Statistics: Labor Force Data
26. Continued — Average annual wages for 2006 and 2007 for all covered
workers1 by metropolitan area
Average annual wages3
Metropolitan area2
2007
Jackson, TN ...........................................................................
Jacksonville, FL .....................................................................
Jacksonville, NC ....................................................................
Janesville, WI ........................................................................
Jefferson City, MO .................................................................
Johnson City, TN ...................................................................
Johnstown, PA .......................................................................
Jonesboro, AR .......................................................................
Joplin, MO .............................................................................
Kalamazoo-Portage, MI .........................................................
$34,477
40,192
25,854
36,732
31,771
31,058
29,972
28,972
30,111
37,099
$35,059
41,437
27,005
36,790
32,903
31,985
31,384
30,378
31,068
38,402
1.7
3.1
4.5
0.2
3.6
3.0
4.7
4.9
3.2
3.5
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 ..........................................................................
32,389
41,320
38,750
31,511
35,100
33,697
37,216
45,808
31,819
35,380
33,340
42,921
40,439
32,915
36,399
35,018
38,386
47,269
32,949
36,419
2.9
3.9
4.4
4.5
3.7
3.9
3.1
3.2
3.6
2.9
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 ............................................................................
38,170
35,883
33,530
36,171
39,890
28,051
29,969
40,139
29,896
29,830
40,684
37,447
34,394
37,043
40,866
29,009
31,422
42,336
30,830
30,617
6.6
4.4
2.6
2.4
2.4
3.4
4.8
5.5
3.1
2.6
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 ........................................................................
31,790
30,776
32,231
37,926
33,790
33,703
36,169
26,766
35,055
35,140
32,876
31,961
33,118
39,290
35,177
34,750
39,305
27,810
36,956
37,101
3.4
3.9
2.8
3.6
4.1
3.1
8.7
3.9
5.4
5.6
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 .......................................................................
48,680
38,673
31,977
33,242
34,126
31,213
40,007
46,659
33,171
20,619
50,480
40,125
32,761
34,412
34,243
33,266
41,201
49,235
33,109
21,326
3.7
3.8
2.5
3.5
0.3
6.6
3.0
5.5
-0.2
3.4
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 .........................................................................
26,712
31,697
40,580
31,147
42,175
31,383
42,625
42,049
46,931
30,652
27,651
32,877
42,339
32,351
43,428
32,570
45,574
43,261
49,542
32,233
3.5
3.7
4.3
3.9
3.0
3.8
6.9
2.9
5.6
5.2
Mobile, AL ..............................................................................
Modesto, CA ..........................................................................
Monroe, LA ............................................................................
Monroe, MI ............................................................................
Montgomery, AL ....................................................................
Morgantown, WV ...................................................................
Morristown, TN ......................................................................
Mount Vernon-Anacortes, WA ...............................................
Muncie, IN .............................................................................
Muskegon-Norton Shores, MI ................................................
36,126
35,468
30,618
40,938
35,383
32,608
31,914
32,851
30,691
33,949
36,890
36,739
31,992
41,636
36,223
35,241
32,806
34,620
31,326
34,982
2.1
3.6
4.5
1.7
2.4
8.1
2.8
5.4
2.1
3.0
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 ...............................................................................
27,905
41,788
39,320
41,003
44,892
42,434
61,388
36,967
43,184
31,330
28,576
44,171
41,300
42,728
47,039
43,255
65,685
38,140
45,463
31,623
2.4
5.7
5.0
4.2
4.8
1.9
7.0
3.2
5.3
0.9
See footnotes at end of table.
94
Percent
change,
2006-07
2006
Monthly Labor Review • October 2009
26. Continued — Average annual wages for 2006 and 2007 for all covered
workers1 by metropolitan area
Average annual wages3
Metropolitan area2
Percent
change,
2006-07
2006
2007
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 ...................................
$31,801
37,144
32,890
35,846
37,787
38,139
37,776
39,538
32,491
45,467
$32,452
41,758
34,067
37,192
39,678
39,273
38,633
41,014
33,593
47,669
2.0
12.4
3.6
3.8
5.0
3.0
2.3
3.7
3.4
4.8
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 ........................................................................
39,778
33,341
32,213
36,287
33,530
42,283
48,647
42,220
32,115
40,759
40,975
33,950
33,547
39,131
34,165
43,470
50,611
43,697
33,094
42,910
3.0
1.8
4.1
7.8
1.9
2.8
4.0
3.5
3.0
5.3
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 ....................................................................
36,707
28,418
20,266
36,979
42,607
34,408
39,528
30,625
39,428
32,308
38,075
29,268
21,019
38,497
44,335
36,375
40,793
32,048
40,674
34,141
3.7
3.0
3.7
4.1
4.1
5.7
3.2
4.6
3.2
5.7
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 .................................
30,941
32,370
39,002
41,205
29,920
38,048
33,307
39,537
42,495
36,668
32,552
32,833
40,746
42,801
31,119
39,945
34,953
41,365
44,530
37,846
5.2
1.4
4.5
3.9
4.0
5.0
4.9
4.6
4.8
3.2
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 ......................................................................
33,912
42,941
39,481
37,424
31,556
34,850
44,552
37,747
33,018
28,034
35,419
44,786
40,752
38,304
32,527
33,041
46,385
37,507
33,996
29,052
4.4
4.3
3.2
2.4
3.1
-5.2
4.1
-0.6
3.0
3.6
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 .......................................................................
31,253
41,354
32,764
37,974
33,223
38,630
30,168
36,763
45,784
33,526
31,828
42,873
33,986
39,419
34,833
40,935
30,920
38,274
47,657
33,471
1.8
3.7
3.7
3.8
4.8
6.0
2.5
4.1
4.1
-0.2
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 ............................................
61,343
19,498
76,608
24,812
35,146
40,326
40,776
35,320
41,533
35,751
64,559
19,777
82,038
25,939
36,740
41,967
41,540
37,395
42,824
36,424
5.2
1.4
7.1
4.5
4.5
4.1
1.9
5.9
3.1
1.9
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 ....................................................................
35,684
32,813
49,455
35,908
34,166
33,678
31,826
34,542
35,089
37,077
36,695
34,205
51,924
37,049
35,672
34,892
33,025
36,056
36,266
37,967
2.8
4.2
5.0
3.2
4.4
3.6
3.8
4.4
3.4
2.4
See footnotes at end of table.
Monthly Labor Review • October 2009 95
Current Labor Statistics: Labor Force Data
26. Continued — Average annual wages for 2006 and 2007 for all covered
workers1 by metropolitan area
Average annual wages3
Metropolitan area2
2007
Spokane, WA .........................................................................
Springfield, IL .........................................................................
Springfield, MA ......................................................................
Springfield, MO ......................................................................
Springfield, OH ......................................................................
State College, PA ..................................................................
Stockton, CA ..........................................................................
Sumter, SC ............................................................................
Syracuse, NY .........................................................................
Tallahassee, FL .....................................................................
$34,016
40,679
37,962
30,786
31,844
35,392
36,426
29,294
38,081
35,018
$35,539
42,420
39,487
31,868
32,017
36,797
37,906
30,267
39,620
36,543
4.5
4.3
4.0
3.5
0.5
4.0
4.1
3.3
4.0
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 ................................................................................
38,016
31,341
32,545
37,039
34,806
54,274
37,119
37,637
35,613
36,173
39,215
32,349
34,079
38,538
36,109
56,645
38,524
38,942
36,737
37,184
3.2
3.2
4.7
4.0
3.7
4.4
3.8
3.5
3.2
2.8
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 ...............................................................
32,457
26,794
40,225
33,823
36,642
37,749
36,071
29,772
33,450
38,087
33,916
27,842
42,932
35,901
38,317
39,408
37,734
30,968
34,679
39,220
4.5
3.9
6.7
6.1
4.6
4.4
4.6
4.0
3.7
3.0
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 ......................................................................
58,057
34,329
34,438
31,416
28,340
30,620
38,763
30,785
31,431
32,948
60,711
35,899
35,710
32,893
29,475
31,169
39,662
32,320
32,506
34,239
4.6
4.6
3.7
4.7
4.0
1.8
2.3
5.0
3.4
3.9
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 ...............................................................................
34,895
37,712
42,726
28,401
19,001
37,226
33,852
33,642
28,369
36,016
38,921
44,652
29,743
19,380
38,469
34,698
35,058
30,147
3.2
3.2
4.5
4.7
2.0
3.3
2.5
4.2
6.3
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,
2006-07
2006
Monthly Labor Review • October 2009
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
19981
Civilian noninstitutional population...........
Civilian labor force............................……
Labor force participation rate...............
Employed............................…………
Employment-population ratio..........
Unemployed............................………
Unemployment rate........................
Not in the labor force............................…
1
205,220
137,673
67.1
131,463
64.1
6,210
4.5
67,547
19991
207,753
139,368
67.1
133,488
64.3
5,880
4.2
68,385
20001
20011
2002
2003
2004
2005
2006
2007
2008
212,577
142,583
67.1
136,891
64.4
5,692
4.0
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
6.0
74,658
223,357
147,401
66.0
139,252
62.3
8,149
5.5
75,956
226,082
149,320
66.0
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
66.0
146,047
63.0
7,078
4.6
78,743
233,788
154,287
66.0
145,362
62.2
8,924
5.8
79,501
Not strictly comparable with prior years.
28. Annual data: Employment levels by industry
[In thousands]
Industry
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
Total private employment............................…
106,021
108,686
110,995
110,708
108,828
108,416
109,814
111,899
114,113
115,420
114,792
Total nonfarm employment……………………
Goods-producing............................…………
Natural resources and mining.................
Construction............................……………
Manufacturing............................…………
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
136,086
22,531
684
7,691
14,155
137,623
22,221
723
7,614
13,884
137,248
21,404
774
7,175
13,455
Private service-providing..........................
Trade, transportation, and utilities..........
Wholesale trade............................………
Retail trade............................…………
Transportation and warehousing.........
Utilities............................………………
Information............................……………
Financial activities............................……
Professional and business services……
Education and health services…………
Leisure and hospitality……………………
Other services……………………………
81,667
25,186
5,795
14,609
4,168
613
3,218
7,462
15,147
14,446
11,232
4,976
84,221
25,771
5,893
14,970
4,300
609
3,419
7,648
15,957
14,798
11,543
5,087
86,346
26,225
5,933
15,280
4,410
601
3,630
7,687
16,666
15,109
11,862
5,168
86,834
25,983
5,773
15,239
4,372
599
3,629
7,808
16,476
15,645
12,036
5,258
86,271
25,497
5,652
15,025
4,224
596
3,395
7,847
15,976
16,199
11,986
5,372
86,600
25,287
5,608
14,917
4,185
577
3,188
7,977
15,987
16,588
12,173
5,401
87,932
25,533
5,663
15,058
4,249
564
3,118
8,031
16,394
16,953
12,493
5,409
89,709
25,959
5,764
15,280
4,361
554
3,061
8,153
16,954
17,372
12,816
5,395
91,582
26,276
5,905
15,353
4,470
549
3,038
8,328
17,566
17,826
13,110
5,438
93,199
26,608
6,028
15,491
4,536
553
3,029
8,308
17,962
18,327
13,474
5,491
93,387
26,332
6,012
15,265
4,495
560
2,987
8,192
17,863
18,878
13,615
5,520
19,909
20,307
20,790
21,118
21,513
21,583
21,621
21,804
21,974
22,203
22,457
Government……………………………………
Monthly Labor Review • October 2009 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
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
Private sector:
Average weekly hours.......……................................
Average hourly earnings (in dollars).........................
Average weekly earnings (in dollars)........................
34.5
13.01
448.56
34.3
13.49
463.15
34.3
14.02
481.01
34.0
14.54
493.79
33.9
14.97
506.75
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
17.42
589.72
33.6
18.05
606.84
Goods-producing:
Average weekly hours.............................................
Average hourly earnings (in dollars).......................
Average weekly earnings (in dollars)......................
40.8
14.23
580.99
40.8
14.71
599.99
40.7
15.27
621.86
39.9
15.78
630.01
39.9
16.33
651.61
39.8
16.80
669.13
40.0
17.19
688.13
40.1
17.60
705.31
40.5
18.02
730.16
40.6
18.67
757.06
40.2
19.31
775.28
44.9
16.20
727.28
44.2
16.33
721.74
44.4
16.55
734.92
44.6
17.00
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
19.90
907.95
45.9
20.96
961.78
45.0
22.42
1008.27
Average weekly hours............................................
Average hourly earnings (in dollars)......................
Average weekly earnings (in dollars).....................
Manufacturing:
38.8
16.23
629.75
39.0
16.80
655.11
39.2
17.48
685.78
38.7
18.00
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
39.0
20.02
781.21
39.0
20.95
816.06
38.5
21.86
841.46
Average weekly hours............................................
Average hourly earnings (in dollars)......................
Average weekly earnings (in dollars).....................
Private service-providing:
41.4
13.45
557.09
41.4
13.85
573.25
41.3
14.32
590.77
40.3
14.76
595.19
40.5
15.29
618.75
40.4
15.74
635.99
40.8
16.14
658.49
40.7
16.56
673.33
41.1
16.81
691.02
41.2
17.26
711.36
40.8
17.72
723.51
Average weekly hours..………................................
Average hourly earnings (in dollars).......................
Average weekly earnings (in dollars)......................
32.8
12.61
413.50
32.7
13.09
427.98
32.7
13.62
445.74
32.5
14.18
461.08
32.5
14.59
473.80
32.3
14.99
484.68
32.3
15.29
494.22
32.4
15.74
509.58
32.5
16.42
532.78
32.4
17.10
554.78
32.3
17.73
572.96
Trade, transportation, and utilities:
Average weekly hours.............................................
Average hourly earnings (in dollars).......................
Average weekly earnings (in dollars)......................
Wholesale trade:
34.2
12.39
423.30
33.9
12.82
434.31
33.8
13.31
449.88
33.5
13.70
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
15.39
514.34
33.3
15.79
526.38
33.2
16.19
537.00
Average weekly hours.........................................
Average hourly earnings (in dollars)...................
Average weekly earnings (in dollars)..................
Retail trade:
38.6
15.07
582.21
38.6
15.62
602.77
38.8
16.28
631.40
38.4
16.77
643.45
38.0
16.98
644.38
37.9
17.36
657.29
37.8
17.65
667.09
37.7
18.16
685.00
38.0
18.91
718.63
38.2
19.59
748.90
38.2
20.13
769.74
Average weekly hours.........................................
Average hourly earnings (in dollars)...................
Average weekly earnings (in dollars)..................
30.9
10.05
582.21
30.8
10.45
602.77
30.7
10.86
631.40
30.7
11.29
643.45
30.9
11.67
644.38
30.9
11.90
657.29
30.7
12.08
667.09
30.6
12.36
685.00
30.5
12.57
718.63
30.2
12.76
748.90
30.0
12.90
769.74
Transportation and warehousing:
Average weekly hours.........................................
Average hourly earnings (in dollars)...................
Average weekly earnings (in dollars)..................
38.7
14.12
546.86
37.6
14.55
547.97
37.4
15.05
562.31
36.7
15.33
562.70
36.8
15.76
579.75
36.8
16.25
598.41
37.2
16.52
614.82
37.0
16.70
618.58
36.9
17.28
636.97
36.9
17.73
654.83
36.4
18.39
669.44
Utilities:
Average weekly hours.........................................
Average hourly earnings (in dollars)...................
Average weekly earnings (in dollars)..................
42.0
21.48
902.94
42.0
22.03
924.59
42.0
22.75
955.66
41.4
23.58
977.18
40.9
23.96
979.09
41.1
24.77
1017.27
40.9
25.61
1048.44
41.1
26.68
1095.90
41.4
27.40
1135.34
42.4
27.87
1182.17
42.6
28.84
1230.08
Information:
Average weekly hours.........................................
Average hourly earnings (in dollars)...................
Average weekly earnings (in dollars)..................
Financial activities:
36.6
17.67
646.34
36.7
18.40
675.47
36.8
19.07
700.86
36.9
19.80
730.88
36.5
20.20
737.77
36.2
21.01
760.45
36.3
21.40
777.25
36.5
22.06
805.08
36.6
23.23
850.42
36.5
23.94
873.63
36.7
24.74
907.02
Average weekly hours.........................................
Average hourly earnings (in dollars)...................
Average weekly earnings (in dollars)..................
36.0
13.93
500.98
35.8
14.47
517.57
35.9
14.98
537.37
35.8
15.59
557.92
35.6
16.17
575.54
35.5
17.14
609.08
35.5
17.52
622.87
35.9
17.95
644.99
35.7
18.80
672.21
35.9
19.64
705.29
35.9
20.28
727.38
Professional and business services:
Average weekly hours.........................................
Average hourly earnings (in dollars)...................
Average weekly earnings (in dollars)..................
34.3
14.27
490.00
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
19.13
662.27
34.8
20.13
700.15
34.8
21.15
736.55
Education and health services:
Average weekly hours.........................................
Average hourly earnings (in dollars)...................
Average weekly earnings (in dollars)..................
32.2
13.00
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
564.94
32.6
18.11
590.18
32.5
18.78
611.03
26.2
7.67
200.82
26.1
7.96
208.05
26.1
8.32
217.20
25.8
8.57
220.73
25.8
8.81
227.17
25.6
9.00
230.42
25.7
9.15
234.86
25.7
9.38
241.36
25.7
9.75
250.34
25.5
10.41
265.45
25.2
10.83
272.97
32.6
11.79
384.25
32.5
12.26
398.77
32.5
12.73
413.41
32.3
13.27
428.64
32.0
13.72
439.76
31.4
13.84
434.41
31.0
13.98
433.04
30.9
14.34
443.37
30.9
14.77
456.50
30.9
15.42
476.80
30.8
15.86
488.22
Natural resources and mining
Average weekly hours............................................
Average hourly earnings (in dollars)......................
Average weekly earnings (in dollars).....................
Construction:
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)..................
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 • October 2009
30. Employment Cost Index, compensation,1 by occupation and industry group
[December 2005 = 100]
2007
Series
June
Sept.
2008
Dec.
Mar.
June
2009
Sept.
Dec.
Mar.
Percent change
June
3 months
ended
12 months
ended
June 2009
2
Civilian workers ……….…….........…………………………………….…
105.0
106.1
106.7
107.6
108.3
109.2
109.5
109.9
110.3
0.4
1.8
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…………………………
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
110.1
109.7
110.4
108.2
106.0
109.5
110.4
109.8
110.7
108.3
105.5
110.0
110.9
110.0
111.3
108.4
104.3
110.8
111.1
110.1
111.6
108.7
104.5
111.3
.2
.1
.3
.3
.2
.5
1.9
1.1
2.4
.9
-1.5
2.5
Natural resources, construction, and maintenance…………
Construction and extraction………………………………
Installation, maintenance, and repair……………………
Production, transportation, and material moving……………
Production……………………………………………………
Transportation and material moving………………………
Service occupations……………………………………………
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
109.3
110.3
108.0
106.9
105.9
108.1
110.2
109.8
110.8
108.6
107.2
106.2
108.4
110.6
110.1
111.0
109.1
108.0
107.2
108.9
111.5
110.7
111.6
109.5
108.5
107.7
109.5
111.9
.5
.5
.4
.5
.5
.6
.4
2.1
1.8
2.3
2.2
2.3
2.1
2.6
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…………………
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
107.3
105.6
109.5
110.8
110.4
110.2
109.0
111.1
111.1
107.5
105.9
109.8
111.1
110.8
110.8
109.6
111.3
111.4
108.0
106.5
110.3
111.7
111.7
111.7
110.3
111.8
111.9
108.2
106.7
110.6
112.2
112.2
112.3
110.8
112.1
112.1
.2
.2
.3
.4
.4
.5
.5
.3
.2
1.3
1.5
1.9
2.7
2.4
2.8
2.4
2.9
3.0
106.6
108.0
109.1
109.7
110.1
111.6
112.0
113.0
113.8
.7
3.4
104.9
105.7
106.3
107.3
108.0
108.7
108.9
109.3
109.6
.3
1.5
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……………………………………………
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
109.6
109.3
109.9
107.9
106.0
109.2
109.0
110.3
107.4
106.6
105.8
107.7
109.4
109.9
109.5
110.3
107.9
105.5
109.6
109.6
110.8
108.1
106.9
106.1
107.9
109.8
110.4
109.6
111.0
107.9
104.3
110.5
109.9
110.9
108.6
107.7
107.1
108.4
110.7
110.5
109.7
111.1
108.3
104.5
110.9
110.3
111.5
108.9
108.1
107.6
108.9
110.9
.1
.1
.1
.4
.2
.4
.4
.5
.3
.4
.5
.5
.2
1.5
.9
1.9
.7
-1.6
2.2
1.8
1.6
2.2
2.0
2.3
1.6
2.0
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………..
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
107.2
106.7
106.7
109.8
105.8
107.5
106.6
107.1
110.4
106.2
107.9
106.8
107.3
110.4
107.0
108.2
106.7
107.4
110.9
107.5
.3
-.1
.1
.5
.5
1.3
.1
1.0
1.7
2.1
Construction…………………………………………………
Manufacturing…………………………………………………
Management, professional, and related…………………
Sales and office……………………………………………
Natural resources, construction, and maintenance……
Production, transportation, and material moving……..
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
110.6
105.6
105.4
106.7
105.3
105.5
110.9
105.9
105.4
107.0
106.0
105.8
110.9
106.5
105.7
107.3
106.6
106.7
111.2
106.7
105.7
107.1
107.1
107.2
.3
.2
.0
-.2
.5
.5
1.0
1.5
.5
.9
2.5
2.1
Service-providing industries…………………………………
Management, professional, and related……………………
Sales and office………………………………………………
Natural resources, construction, and maintenance………
Production, transportation, and material moving………..
Service occupations…………………………………………
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
109.1
110.2
108.0
107.8
107.6
109.5
109.4
110.6
108.0
108.4
107.8
109.8
109.8
111.1
108.0
109.0
108.5
110.7
110.1
111.2
108.4
109.5
109.0
111.0
.3
.1
.4
.5
.5
.3
1.5
1.7
.6
2.1
1.9
2.1
Trade, transportation, and utilities…………………………
104.2
104.7
105.5
106.1
107.3
107.6
107.5
107.8
108.1
.3
.7
3
Public administration ………………………………………
Private industry workers………………………………………
See footnotes at end of table.
Monthly Labor Review • October 2009 99
Current Labor Statistics: Compensation & Industrial Relations
30. Continued—Employment Cost Index, compensation,1 by occupation and industry group
[December 2005 = 100]
2007
Series
June
Sept.
2008
Dec.
Mar.
June
2009
Sept.
Dec.
Mar.
Percent change
June
3 months
ended
12 months
ended
June 2009
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……………
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
107.1
108.2
106.8
108.1
107.2
107.4
107.6
106.4
110.8
110.3
111.4
110.1
110.1
110.6
111.4
109.9
106.8
108.1
106.9
108.9
107.4
107.1
107.2
106.6
111.6
110.6
111.3
110.5
110.7
111.4
112.1
109.9
107.1
108.3
107.4
109.6
107.7
106.8
106.9
106.6
111.9
111.5
111.9
111.5
111.5
112.2
113.0
110.8
106.9
108.8
107.9
110.9
107.5
107.9
108.1
106.9
111.9
111.9
112.0
111.9
112.0
112.0
112.6
110.8
-0.2
.5
.5
1.2
-.2
1.0
1.1
.3
.0
.4
.1
.4
.4
-.2
-.4
.0
-0.3
1.1
1.4
2.6
1.2
.6
.4
1.1
1.8
2.3
2.7
2.3
2.7
2.5
2.4
1.3
105.7
107.6
108.4
108.9
109.4
111.3
111.6
112.3
112.9
.5
3.2
Workers by occupational group
Management, professional, and related………………………
Professional and related……………………………………
Sales and office…………………………………………………
Office and administrative support…………………………
Service occupations……………………………………………
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
111.3
111.1
111.0
111.4
111.9
111.6
111.4
111.3
111.8
112.4
112.0
111.9
112.4
112.8
113.4
112.6
112.4
113.0
113.3
114.0
.5
.4
.5
.4
.5
3.0
3.0
3.4
3.2
3.6
Workers by industry
Education and health services………………………………
Education services………………………………………
Schools…………………………………………………
Elementary and secondary schools………………
Health care and social assistance………………………
Hospitals…………………………………………………
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
111.2
111.0
111.0
111.1
112.7
110.8
111.5
111.2
111.2
111.4
113.2
111.3
111.9
111.8
111.8
112.0
113.3
112.4
112.4
112.1
112.1
112.2
114.8
113.5
.4
.3
.3
.2
1.3
1.0
3.0
3.0
3.0
3.1
3.3
3.5
106.6
108.0
109.1
109.7
110.1
111.6
112.0
113.0
113.8
.7
3.4
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 • October 2009
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]
2007
Series
June
Sept.
2008
Dec.
Mar.
June
2009
Sept.
Dec.
Mar.
Percent change
June
3 months
ended
12 months
ended
June 2009
1
Civilian workers ……….…….........…………………………………….…
105.0
106.0
106.7
107.6
108.4
109.3
109.6
110.0
110.4
0.4
1.8
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…………………………
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
110.1
109.8
110.3
108.1
106.3
109.3
110.5
110.1
110.7
108.1
105.6
109.8
111.0
110.4
111.2
108.1
104.3
110.6
111.2
110.5
111.5
108.6
104.7
111.2
.2
.1
.3
.5
.4
.5
2.0
1.4
2.3
.8
-1.8
2.5
Natural resources, construction, and maintenance…………
Construction and extraction………………………………
Installation, maintenance, and repair……………………
Production, transportation, and material moving……………
Production……………………………………………………
Transportation and material moving………………………
Service occupations……………………………………………
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
109.9
110.7
108.8
107.7
107.2
108.2
109.9
110.6
111.3
109.6
108.0
107.5
108.5
110.3
110.7
111.4
110.0
108.5
108.2
108.8
111.2
111.2
111.8
110.5
109.0
108.7
109.5
111.6
.5
.4
.5
.5
.5
.6
.4
2.0
1.7
2.5
2.0
2.1
2.1
2.7
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…………………
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
108.6
107.4
109.4
110.2
110.4
110.5
109.1
110.0
109.9
109.0
107.7
109.7
110.5
110.9
111.3
109.7
110.2
110.1
109.2
108.1
110.2
111.0
111.7
112.0
110.3
110.5
110.4
109.5
108.4
110.5
111.4
112.2
112.6
110.9
110.7
110.5
.3
.3
.3
.4
.4
.5
.5
.2
.1
1.4
1.6
1.8
2.5
2.4
2.9
2.6
2.6
2.8
105.2
106.4
107.4
108.2
108.6
109.9
110.4
111.3
112.3
.9
3.4
105.1
106.0
106.6
107.6
108.4
109.1
109.4
109.8
110.1
.3
1.6
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……………………………………………
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
110.1
109.7
110.4
108.0
106.4
109.2
109.8
110.8
108.5
107.5
107.2
108.0
109.7
110.5
110.0
110.9
108.0
105.7
109.7
110.5
111.5
109.3
107.8
107.4
108.3
110.1
111.1
110.3
111.6
107.9
104.3
110.6
110.6
111.4
109.7
108.3
108.1
108.5
111.0
111.1
110.3
111.8
108.3
104.7
111.1
111.0
111.7
110.2
108.8
108.5
109.2
111.2
.0
.0
.2
.4
.4
.5
.4
.3
.5
.5
.4
.6
.2
1.6
1.2
2.1
.6
-1.8
2.4
1.8
1.5
2.4
1.9
2.0
1.7
2.2
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………..
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
108.6
108.7
107.6
110.5
107.3
109.0
108.8
107.9
111.3
107.6
109.2
109.3
108.1
111.1
108.0
109.5
109.3
108.3
111.4
108.5
.3
.0
.2
.3
.5
1.4
.8
1.0
1.6
1.8
Construction…………………………………………………
Manufacturing…………………………………………………
Management, professional, and related…………………
Sales and office……………………………………………
Natural resources, construction, and maintenance……
Production, transportation, and material moving……..
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
110.6
107.4
107.6
107.6
108.1
107.1
111.1
107.7
107.8
108.1
109.0
107.3
111.2
108.1
108.4
108.2
108.8
107.7
111.4
108.4
108.5
108.2
109.2
108.2
.2
.3
.1
.0
.4
.5
1.3
1.6
1.2
1.2
2.0
1.8
Service-providing industries…………………………………
Management, professional, and related……………………
Sales and office………………………………………………
Natural resources, construction, and maintenance………
Production, transportation, and material moving………..
Service occupations…………………………………………
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
109.3
110.3
108.0
108.6
107.8
109.7
109.6
110.8
108.0
109.3
108.1
110.1
110.0
111.4
107.9
109.9
108.6
111.0
110.3
111.5
108.3
110.5
109.3
111.3
.3
.1
.4
.5
.6
.3
1.6
1.9
.6
2.3
2.1
2.3
Trade, transportation, and utilities…………………………
104.3
104.6
105.5
105.9
107.2
107.5
107.4
107.8
108.2
.4
.9
2
Public administration ………………………………………
Private industry workers………………………………………
Monthly Labor Review • October 2009 101
Current Labor Statistics: Compensation & Industrial Relations
31. Continued—Employment Cost Index, wages and salaries, by occupation and industry group
[December 2005 = 100]
2007
Series
June
Sept.
2008
Dec.
Mar.
June
2009
Sept.
Dec.
Mar.
Percent change
June
3 months
ended
12 months
ended
June 2009
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……………
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
106.8
108.1
106.7
109.3
107.3
107.7
108.2
105.3
111.0
110.2
110.8
110.1
110.3
111.4
111.9
110.4
106.4
108.1
106.9
109.6
107.5
107.2
107.6
105.7
111.9
110.6
110.8
110.6
111.1
112.3
112.8
110.4
106.8
108.3
107.2
111.0
107.8
106.8
107.1
105.6
112.3
111.4
111.1
111.5
111.8
113.1
113.7
111.4
106.5
108.9
107.9
112.0
108.1
107.9
108.5
105.8
112.2
111.8
111.2
111.9
112.3
112.8
113.2
111.4
-0.3
.6
.7
.9
.3
1.0
1.3
.2
-.1
.4
.1
.4
.4
-.3
-.4
.0
-0.7
1.2
1.8
2.5
1.7
.2
.1
1.1
2.0
2.4
2.4
2.3
2.8
2.6
2.5
1.4
104.6
106.4
107.1
107.7
108.2
110.1
110.4
110.9
111.5
.5
3.0
Workers by occupational group
Management, professional, and related………………………
Professional and related……………………………………
Sales and office…………………………………………………
Office and administrative support…………………………
Service occupations……………………………………………
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
110.1
110.1
109.3
109.7
110.4
110.4
110.3
109.7
110.1
110.9
110.7
110.6
110.5
111.0
112.0
111.2
111.1
111.2
111.6
112.7
.5
.5
.6
.5
.6
2.8
2.8
3.1
3.0
3.8
Workers by industry
Education and health services………………………………
Education services………………………………………
Schools…………………………………………………
Elementary and secondary schools………………
Health care and social assistance………………………
Hospitals…………………………………………………
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
110.2
109.9
109.9
109.8
112.8
111.4
110.5
110.1
110.1
110.1
113.4
112.1
110.7
110.4
110.4
110.3
113.1
112.8
111.1
110.7
110.7
110.5
114.8
114.0
.4
.3
.3
.2
1.5
1.1
2.8
2.8
2.8
2.8
3.4
3.4
105.2
106.4
107.4
108.2
108.6
109.9
110.4
111.3
112.3
.9
3.4
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 • October 2009
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]
2007
Series
June
Sept.
2008
Dec.
Mar.
June
2009
Sept.
Dec.
Mar.
Percent change
June
3 months
ended
12 months
ended
June 2009
Civilian workers………………………………………………….
105.1
106.1
106.8
107.6
108.1
108.9
109.1
109.7
110.0
0.3
1.8
Private industry workers………………………………………… 104.3
105.0
105.6
106.5
107.0
107.5
107.7
108.2
108.4
.2
1.3
Workers by occupational group
Management, professional, and related………………………
Sales and office…………………………………………………
Natural resources, construction, and maintenance…………
Production, transportation, and material moving……………
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
108.5
107.6
107.5
104.8
108.5
107.8
107.7
105.1
108.8
108.0
108.2
106.4
108.8
108.1
108.8
106.8
.0
.1
.6
.4
.8
1.0
1.7
2.2
Service occupations……………………………………………
105.1
106.0
106.7
107.6
108.5
108.7
108.8
109.7
110.0
.3
1.4
Goods-producing………………………………………………
102.2
Manufacturing………………………………………………… 101.0
Service-providing……………………………………………… 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
104.6
102.3
108.7
104.7
102.5
108.9
105.4
103.5
109.3
105.7
103.6
109.5
.3
.1
.2
1.2
1.4
1.3
110.3
111.0
111.4
111.8
113.9
114.2
115.2
115.8
.5
3.6
Workers by industry
State and local government workers…………………………
108.0
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 • October 2009 103
Current Labor Statistics: Compensation & Industrial Relations
33. Employment Cost Index, private industry workers by bargaining status and region
[December 2005 = 100]
2007
Series
June
Sept.
2008
Dec.
Mar.
June
2009
Sept.
Dec.
Mar.
Percent change
June
3 months
ended
12 months
ended
June 2009
COMPENSATION
Workers by bargaining status1
Union…………………………………………………………………
Goods-producing…………………………………………………
Manufacturing…………………………………………………
Service-providing…………………………………………………
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
107.4
106.2
102.1
108.3
108.0
106.9
102.8
108.8
109.1
108.0
104.4
109.9
109.8
108.9
104.8
110.6
0.6
.8
.4
.6
2.9
3.1
3.0
2.9
Nonunion……………………………………………………………
Goods-producing…………………………………………………
Manufacturing…………………………………………………
Service-providing…………………………………………………
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
108.9
107.6
106.6
109.2
109.1
107.7
106.8
109.4
109.4
107.9
107.1
109.8
109.6
108.0
107.3
110.0
.2
.1
.2
.2
1.2
.8
1.0
1.3
Workers by region1
Northeast……………………………………………………………
South…………………………………………………………………
Midwest………………………………………………………………
West…………………………………………………………………
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
108.7
109.1
107.4
109.3
109.5
109.3
107.6
109.4
109.8
109.8
107.9
109.9
110.2
110.1
108.1
110.1
.4
.3
.2
.2
1.9
1.5
1.0
1.6
Workers by bargaining status1
Union…………………………………………………………………
Goods-producing…………………………………………………
Manufacturing…………………………………………………
Service-providing…………………………………………………
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
107.4
107.1
104.9
107.7
108.1
107.7
105.5
108.3
108.8
108.2
106.0
109.2
109.6
108.8
106.4
110.1
.7
.6
.4
.8
2.7
2.3
1.9
3.0
Nonunion……………………………………………………………
Goods-producing…………………………………………………
Manufacturing…………………………………………………
Service-providing…………………………………………………
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
109.4
109.0
108.0
109.4
109.6
109.3
108.2
109.7
110.0
109.5
108.6
110.1
110.2
109.7
108.9
110.3
.2
.2
.3
.2
1.4
1.2
1.5
1.4
Workers by region1
Northeast……………………………………………………………
South…………………………………………………………………
Midwest………………………………………………………………
West…………………………………………………………………
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
108.7
109.8
107.9
109.9
109.6
110.0
108.0
110.1
109.9
110.4
108.4
110.5
110.3
110.7
108.6
110.8
.4
.3
.2
.3
1.9
1.5
1.0
1.7
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 • October 2009
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
Take-up rate (all workers) 3……………………………………
-
-
85
85
84
20
21
22
21
21
23
24
25
23
-
-
-
-
-
29
19
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 • October 2009 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 • October 2009
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 • October 2009 107
Current Labor Statistics: Compensation & Industrial Relations
35. National Compensation Survey: Health insurance benefits in private industry
by access, participation, and selected series, 2003-2007
Series
Year
2003
2004
2005
2007 1
2006
Medical insurance
Percentage of workers with access
All workers…………………………………………………………………………
2
White-collar occupations ………………………………………………………
Management, professional, and related …………………………………
Sales and office………………………………………………………………
Blue-collar occupations 2………………………………………………………
Natural resources, construction, and maintenance………………………
60
69
70
71
65
76
77
77
71
-
-
-
-
-
85
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
45
53
53
52
52
50
59
58
57
-
-
-
-
-
67
48
Percentage of workers participating
All workers…………………………………………………………………………
White-collar occupations 2 ………………………………………………………
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
40
46
46
46
46
47
53
54
53
-
-
-
-
-
62
47
3
Take-up rate (all workers) ………………………………………………………
Dental
Percentage of workers with access
All workers…………………………………………………………………………
2
White-collar occupations ………………………………………………………
Management, professional, and related …………………………………
Sales and office………………………………………………………………
Blue-collar occupations 2………………………………………………………
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 • October 2009
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 • October 2009 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
2007
Number of stoppages:
Beginning in period.............................
In effect during period…......................
2008
2008
Aug.
Sept.
2009
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
Aug.p
July
21
23
15
16
2
2
2
2
1
2
0
1
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
2
1
1
Workers involved:
Beginning in period (in thousands)…..
In effect during period (in thousands)…
189.2
220.9
72.2
136.8
7.0
7.0
28.2
28.2
6.0
33.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
2.5
2.5
1.5
4.0
1.9
1.9
Days idle:
Number (in thousands)…....................
1264.8
1954.1
100.6
469.8
600.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
30.0
43.5
5.7
0.01
0.01
0
0.02
0.02
0
0
0
0
0
0
0
0
0
0
1
Percent of estimated working time …
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
Oct.
Monthly Labor Review • October 2009
worked is found in "Total economy measures of strike idleness,"
October 1968, pp. 54–56.
NOTE:
p = preliminary.
Monthly Labor Review ,
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
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…................................
2009
2008
2007
2008
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
July
Aug.
207.342
621.106
203.300
202.916
201.245
222.107
195.616
215.303
644.951
214.225
214.106
214.125
244.853
204.653
219.086
656.284
216.419
216.422
217.259
250.080
207.488
218.783
655.376
217.672
217.696
218.629
250.924
209.937
216.573
648.758
218.705
218.738
219.660
252.832
210.706
212.425
636.332
218.752
218.749
219.086
252.723
209.602
210.228
629.751
218.839
218.805
218.683
253.063
208.890
211.143
632.491
219.729
219.675
219.744
254.445
208.616
212.193
635.637
219.333
219.205
218.389
254.187
207.963
212.709
637.182
218.794
218.600
217.110
253.698
206.348
213.240
638.771
218.364
218.162
215.783
252.709
205.699
213.856
640.616
218.076
217.826
215.088
252.714
203.789
215.693
646.121
218.030
217.740
214.824
253.008
204.031
215.351
645.096
217.608
217.257
213.815
253.391
201.743
215.834
646.544
217.701
217.350
213.722
252.382
202.911
1
Dairy and related products ……….………………………… 194.770 210.396 214.748 213.533 212.733 213.102 210.838 209.632 204.537 199.687 197.124 196.055 194.197 193.118 192.381
Fruits and vegetables…............................................. 262.628 278.932 283.296 285.986 285.484 283.677 281.706 282.601 278.721 274.759 274.297 274.006 272.608 270.940 267.309
Nonalcoholic beverages and beverage
materials….............................................................. 153.432
Other foods at home…............................................... 173.275
Sugar and sweets…................................................. 176.772
Fats and oils…......................................................... 172.921
Other foods…........................................................... 188.244
1,2
Other miscellaneous foods ……….………………… 115.105
1
Food away from home ……….………………………………… 206.659
1,2
Other food away from home ……….…………………… 144.068
Alcoholic beverages….................................................. 207.026
Housing.......................................................................... 209.586
Shelter...............…....................................................... 240.611
Rent of primary residence…...................................... 234.679
160.045
184.166
186.577
196.751
198.103
160.055
186.991
187.813
203.059
200.961
161.499
187.944
189.929
206.274
201.388
163.727
189.348
190.515
208.300
202.993
163.015
189.301
191.756
205.806
203.058
162.750
190.203
193.312
206.710
203.902
164.882
192.492
197.429
206.886
206.343
164.213
192.404
196.676
205.359
206.621
165.656
192.234
197.137
204.776
206.367
162.889
191.352
197.301
200.464
205.734
162.803
191.144
196.403
200.679
205.587
162.571
191.328
197.009
201.127
205.654
162.069
190.967
195.126
201.031
205.544
162.953
191.317
195.430
200.578
206.064
119.924 121.033 121.144 122.699 123.543 123.791 124.012 122.580 122.402 122.883 122.838 122.224 121.990 121.892
215.769
150.640
214.484
216.264
246.666
243.271
217.063
151.133
215.094
219.148
247.985
244.181
218.225
152.040
216.055
218.184
247.737
244.926
219.290
153.544
216.972
217.383
247.844
245.855
220.043
153.978
217.492
216.467
247.463
246.681
220.684
154.062
217.975
216.073
247.085
247.278
221.319
153.402
219.113
216.928
248.292
247.974
221.968
154.726
219.682
217.180
248.878
248.305
222.216
154.414
219.999
217.374
249.597
248.639
222.905
155.099
219.671
217.126
249.855
248.899
223.023
155.099
220.005
216.971
249.779
249.069
223.163
155.841
220.477
218.071
250.243
249.092
223.345
156.570
220.850
218.085
250.310
248.994
223.675
156.697
220.946
217.827
250.248
249.029
Lodging away from home………………………………142.813 143.664 149.146 143.597 141.140 133.555 129.157 133.559 135.809 137.715 137.700 135.680 138.318 139.424 137.454
3
Owners' equivalent rent of primary residence ………. 246.235 252.426 252.957 253.493 253.902 254.669 254.875 255.500 255.779 256.321 256.622 256.875 256.981 256.872 257.155
1,2
Tenants' and household insurance ……….…………… 117.004
Fuels and utilities…................................................... 200.632
Fuels...............…...................................................... 181.744
Fuel oil and other fuels…....................................... 251.453
Gas (piped) and electricity….................................. 186.262
Household furnishings and operations…................... 126.875
Apparel .......................................................................... 118.998
Men's and boys' apparel…......................................... 112.368
Women's and girls' apparel….................................... 110.296
118.843
220.018
200.808
334.405
202.212
127.800
118.907
113.032
107.460
118.562
235.650
217.455
367.794
218.656
128.013
116.376
110.180
104.211
119.944
228.450
209.501
349.164
210.950
128.584
121.168
112.720
111.774
119.916
221.199
201.176
318.667
203.503
128.789
122.243
115.067
111.833
120.232
216.285
195.599
281.869
199.435
128.554
121.262
114.239
110.588
120.019
215.184
194.335
256.209
199.487
128.535
117.078
110.767
105.456
120.402
215.232
194.149
247.163
199.791
128.761
114.764
110.797
100.638
120.683
213.520
192.168
242.264
197.886
129.170
118.825
115.202
105.777
120.737
210.501
188.736
230.837
194.752
129.669
122.545
117.748
111.079
120.675
207.175
184.903
228.107
190.686
129.654
123.208
117.195
111.871
120.728
206.358
183.783
225.164
189.619
129.644
121.751
117.146
109.460
121.083
212.677
190.647
232.638
196.754
129.623
118.799
112.849
106.455
121.298
212.961
190.534
230.192
196.767
129.267
115.620
109.744
101.688
121.830
212.661
189.735
237.521
195.475
128.304
117.130
110.835
103.991
1
113.762
124.157
195.549
191.039
109.558
121.982
206.739
201.779
113.494
124.907
203.861
199.153
116.158
126.442
192.709
187.976
116.010
126.788
173.644
168.527
112.568
124.093
164.628
159.411
112.321
122.363
166.738
161.788
113.544
124.301
169.542
164.871
115.548
126.707
169.647
165.023
117.084
128.057
171.987
167.516
114.142
127.519
175.997
171.757
113.915
125.515
183.735
179.649
111.022
124.405
182.798
178.330
113.673
125.292
184.386
179.987
2
New and used motor vehicles ……….…………………… 94.303 93.291
New vehicles…........................................................ 136.254 134.194
1
Used cars and trucks ……….……………………………… 135.747 133.951
Motor fuel…............................................................... 239.070 279.652
Gasoline (all types)…............................................... 237.959 277.457
Motor vehicle parts and equipment…........................ 121.583 128.747
Motor vehicle maintenance and repair…................... 222.963 233.859
Public transportation...............….................................. 230.002 250.549
Medical care................................................................... 351.054 364.065
Medical care commodities...............…......................... 289.999 296.045
Medical care services...............…................................ 369.302 384.943
Professional services…............................................. 300.792 310.968
Hospital and related services…................................. 498.922 533.953
2
Recreation ……….………………………………………….……… 111.443 113.254
1,2
Video and audio ……….……………………………………… 102.949 102.632
2
Education and communication ……….……………………… 119.577 123.631
93.260
133.404
135.405
323.822
321.511
130.327
236.125
268.487
364.477
295.003
385.990
312.396
535.501
113.786
102.546
124.653
92.480
132.399
132.916
315.078
313.535
131.048
237.121
261.318
365.036
295.461
386.579
312.527
537.728
114.032
102.706
125.505
92.071
132.264
129.733
268.537
266.382
131.917
238.227
252.323
365.746
295.791
387.440
312.914
540.853
114.169
102.193
125.686
91.618
132.359
126.869
187.189
184.235
132.947
239.048
243.385
366.613
297.317
387.992
313.328
543.183
114.078
101.831
125.758
91.408
132.308
125.883
149.132
146.102
133.077
239.356
237.638
367.133
298.361
388.267
313.886
543.585
113.674
101.629
125.921
91.831
133.273
124.863
156.604
154.488
133.414
241.076
234.394
369.830
299.998
391.365
315.603
551.305
113.822
101.347
126.151
92.224
134.186
122.837
167.395
166.118
134.108
241.689
231.529
372.405
302.184
394.047
316.992
558.373
114.461
101.704
126.190
92.109
134.611
121.061
168.404
167.826
134.484
242.118
230.735
373.189
302.908
394.837
317.460
560.995
114.625
102.000
126.187
92.381
134.863
121.213
177.272
176.704
134.640
242.649
229.827
374.170
303.979
395.753
317.661
564.785
114.261
102.300
126.273
92.701
135.162
122.650
193.609
193.727
134.347
242.488
228.878
375.026
304.697
396.648
319.333
564.112
114.264
101.947
126.467
93.020
135.719
124.323
225.021
225.526
134.270
242.683
232.540
375.093
304.683
396.750
319.652
564.406
114.643
101.871
126.519
93.413
136.055
125.061
217.860
217.945
133.729
243.031
238.932
375.739
304.229
397.868
320.076
568.315
114.619
101.614
126.914
93.126
134.080
128.028
225.089
225.179
133.531
243.494
238.997
376.537
305.797
398.303
320.252
570.150
114.755
101.474
128.128
Infants' and toddlers' apparel ……….………………………113.948
Footwear…................................................................ 122.374
Transportation................................................................ 184.682
Private transportation...............…................................ 180.778
2
Education ……….………………………………………….………171.388 181.277 183.184 186.148 186.669 186.733 186.916 187.175 187.256 187.298 187.416 187.853 188.179 189.184 193.161
Educational books and supplies…........................... 420.418 450.187 458.989 462.787 463.825 462.694 464.544 468.432 469.996 472.185 472.507 472.588 476.974 481.768 490.102
Tuition, other school fees, and child care…............. 494.079 522.098 527.230 536.082 537.606 537.906 538.309 538.765 538.878 538.813 539.149 540.498 541.119 543.810 555.402
1,2
Communication ……….……………………………………… 83.367 84.185 84.701 84.524 84.535 84.601 84.737 84.928 84.945 84.922 84.985 85.049 84.975 85.056 84.913
1,2
Information and information processing ……….…… 80.720 81.352 81.815 81.635 81.652 81.723 81.886 82.030 82.052 82.022 82.090 82.038 81.909 81.991 81.835
1,2
Telephone services ……….…………………………… 98.247 100.451 101.301 101.311 101.407 101.538 101.688 101.880 101.895 101.991 102.072 102.267 102.182 102.643 102.674
Information and information processing
1,4
other than telephone services ……….…………… 10.597
10.061
10.012
9.901
9.874
9.867
9.906
9.919
9.926
9.872
9.881
9.775
9.731
9.604
9.499
Personal computers and peripheral
1,2
equipment ……….……………………………………108.411 94.944 92.921 90.797 89.945 88.984 88.529 88.522 87.696 86.213 85.714 84.366 83.476 80.838 78.576
Other goods and services.............................................. 333.328 345.381 346.990 348.166 349.276 349.040 349.220 350.259 351.223 361.156 370.606 369.901 370.595 372.894 372.699
Tobacco and smoking products...............…................ 554.184 588.682 597.361 597.581 599.744 599.820 602.644 607.403 611.549 679.078 742.443 740.311 746.283 762.907 763.634
1
Personal care ……….………………………………………….…195.622 201.279 201.623 202.486 203.107 202.921 202.774 203.080 203.391 204.117 204.896 204.578 204.503 204.571 204.352
1
Personal care products ……….…………………………… 158.285 159.290 159.252 159.643 159.826 161.000 161.397 162.588 162.508 162.696 163.777 163.051 162.301 162.887 162.476
1
Personal care services ……….…………………………… 216.559 223.669 224.151 224.614 225.564 226.197 226.281 225.734 225.895 227.982 227.913 227.607 227.572 227.325 227.580
See footnotes at end of table.
Monthly Labor Review • October 2009 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]
Series
Annual average
2007
2008
Aug.
Sept.
2008
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
2009
Apr. May
June
July
Aug.
Miscellaneous personal services...............….... 324.984 338.921 341.053 343.431 343.131 340.174 339.698 340.608 341.188 341.570 342.641 343.051 344.232 344.367 345.137
Commodity and service group:
Commodities...........…............................................ 167.509 174.764 179.148 179.117 175.257 167.673 163.582 164.360 165.891 166.645 167.816 169.060 171.593 170.483 171.081
Food and beverages….........................................
Commodities less food and beverages….............
Nondurables less food and beverages…............
Apparel ….........................................................
203.300
147.515
182.526
118.998
214.225
153.034
196.192
118.907
216.419
158.179
207.284
116.376
217.672
157.621
206.919
121.168
218.705
151.874
195.127
122.243
218.752
141.397
173.346
121.262
218.839
135.720
161.681
117.078
219.729
136.427
162.938
114.764
219.333
138.702
167.560
118.825
218.794
139.962
170.200
122.545
218.364
141.753
173.855
123.208
218.076
143.587
177.480
121.751
218.030
147.099
184.581
118.799
217.608
145.742
181.755
115.620
217.701
146.528
184.366
117.130
Non durables less food, beverages,
and apparel…................................................. 226.224 248.809 268.740 265.100 244.935 209.569 192.948 196.490 201.554 203.557 209.177 216.090 229.692 227.038 230.396
Durables….......................................................... 112.473 110.877 110.779 110.077 109.677 109.191 108.811 109.025 109.221 109.264 109.404 109.650 109.983 109.924 109.129
Services….............................................................. 246.848 255.498 258.638 258.059 257.559 256.967 256.731 257.780 258.328 258.597 258.466 258.433 259.544 259.992 260.355
3
Rent of shelter ……….…………………………………… 250.813 257.152 258.547 258.255 258.368 257.961 257.567 258.830 259.440 260.197 260.469 260.388 260.869 260.935 260.858
Transportation services….................................... 233.731 244.074 248.806 248.047 247.762 247.030 246.287 247.006 248.114 247.912 248.696 248.628 249.194 251.184 252.234
Other services….................................................. 285.559 295.780 297.923 299.598 299.923 299.996 300.067 300.614 301.471 302.024 301.668 302.132 303.000 303.761 305.890
Special indexes:
All items less food…............................................ 208.098 215.528 219.552 218.991 216.250 211.421 208.855 209.777 211.076 211.775 212.464 213.236 215.389 215.069 215.617
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…....................................
196.639
200.080
149.720
184.012
223.411
193.468
205.453
207.777
155.310
197.297
244.443
205.901
210.264
211.653
160.341
207.769
262.470
212.882
209.936
211.321
159.825
207.483
259.278
213.274
206.776
209.021
154.250
196.442
241.183
207.435
201.075
204.721
144.055
175.979
209.344
195.773
198.127
202.442
138.536
165.032
194.403
189.557
198.936
203.281
139.258
166.282
197.704
190.649
200.184
204.265
141.491
170.665
202.323
192.943
200.626
204.766
142.728
173.167
204.159
194.105
201.271
205.275
144.464
176.587
209.195
195.864
202.171
205.876
146.261
180.017
215.459
197.673
204.578
207.764
149.697
186.726
227.768
201.461
204.069
207.388
148.386
184.090
225.410
199.746
204.776
207.855
149.155
186.552
228.446
201.191
260.764
236.847
207.723
208.925
210.729
140.053
241.018
253.058
273.000
244.987
236.666
214.751
215.572
140.246
284.352
261.017
278.606
248.198
266.283
215.873
216.476
139.785
328.240
262.867
277.615
247.563
258.020
216.397
216.862
140.528
318.918
262.980
276.297
246.997
231.561
216.695
217.023
140.659
272.921
263.156
275.425
246.351
189.938
216.417
216.690
140.236
193.395
262.901
275.370
246.090
171.158
215.930
216.100
139.228
155.745
262.636
276.227
247.013
174.622
216.586
216.719
139.111
162.395
263.759
276.739
247.439
178.741
217.325
217.685
140.270
172.428
264.547
276.407
247.675
177.454
218.033
218.639
141.662
172.787
265.147
275.752
247.490
179.704
218.388
219.143
142.489
181.102
265.399
275.777
247.406
186.909
218.323
219.128
142.360
196.528
265.466
277.777
248.557
205.408
218.440
219.283
141.990
226.881
265.993
278.747
248.963
201.938
218.421
219.350
141.463
219.922
266.484
279.697
249.316
204.971
218.642
219.596
141.310
227.204
267.008
CONSUMER PRICE INDEX FOR URBAN
WAGE EARNERS AND CLERICAL WORKERS
All items.................................................................... 202.767 211.053 215.247 214.935 212.182 207.296 204.813 205.700 206.708 207.218 207.925 208.774 210.972 210.526 211.156
All items (1967 = 100)............................................... 603.982 628.661
Food and beverages................................................ 202.531 213.546
Food..................….................................................. 202.134 213.376
Food at home….................................................... 200.273 213.017
Cereals and bakery products….......................... 222.409 245.472
Meats, poultry, fish, and eggs…......................... 195.193 204.255
641.155
215.850
215.812
216.214
250.842
207.211
640.226
217.098
217.090
217.594
251.448
209.515
632.025
218.141
218.120
218.600
253.561
210.314
617.472
218.178
218.114
217.956
253.498
209.297
610.075
218.269
218.155
217.498
253.759
208.639
612.719
219.123
218.998
218.485
255.055
208.161
615.719
218.645
218.449
217.111
254.775
207.656
617.239
218.119
217.855
215.922
254.395
206.094
619.344
217.653
217.376
214.654
253.556
205.527
621.875
217.308
216.975
213.876
253.430
203.409
628.422
217.258
216.890
213.657
253.701
203.503
627.093
216.805
216.384
212.628
253.969
201.261
628.970
216.957
216.539
212.623
252.932
202.483
1
Dairy and related products ……….…………………… 194.474 209.773 214.139 212.841 211.808 212.184 209.922 208.530 203.023 198.048 195.714 194.694 192.898 191.783 191.048
Fruits and vegetables…...................................... 260.484 276.759 282.171 284.612 283.549 281.279 278.835 279.906 275.884 271.727 271.771 271.530 270.653 269.316 265.730
Nonalcoholic beverages and beverage
materials…....................................................... 152.786
Other foods at home….......................................
172.630
Sugar and sweets…......................................... 175.323
Fats and oils….................................................. 173.640
Other foods…................................................... 188.405
1,2
Other miscellaneous foods ……….…………… 115.356
159.324 159.024 160.850 163.265 162.472 162.280 164.514 163.821 165.437 162.464 162.468 162.167 161.650 162.433
183.637
185.494
197.512
198.303
120.348
186.458
186.860
203.721
201.119
121.443
187.467
188.914
207.069
201.632
121.589
188.806
189.574
208.973
203.138
123.026
188.685
190.501
206.870
203.126
123.837
189.527
192.120
207.439
203.937
124.144
191.782
195.867
207.400
206.490
124.477
191.620
195.395
206.185
206.547
122.994
191.594
196.015
205.693
206.468
122.837
190.650
195.858
201.474
205.820
123.112
190.401
194.928
201.470
205.641
123.126
190.657
195.773
202.004
205.759
122.537
190.235
194.005
201.666
205.549
122.119
190.704
194.511
201.199
206.210
122.217
1
Food away from home ……….…………………………… 206.412 215.613 217.002 218.147 219.219 220.107 220.847 221.497 222.101 222.336 222.957 223.082 223.186 223.408 223.789
1,2
Other food away from home ……….……………… 143.462 149.731 150.301 151.321 152.910 153.464 153.646 153.397 154.520 154.054 154.414 154.409 155.091 156.904 156.769
Alcoholic beverages…........................................... 207.097 214.579 214.931 215.728 216.953 217.626 218.445 219.458 220.029 220.500 220.243 220.729 221.179 221.517 221.618
Housing.................................................................... 204.795 211.839 214.743 213.954 213.156 212.591 212.452 213.078 213.192 213.213 212.885 212.881 214.034 214.029 213.824
Shelter...............…................................................ 232.998 239.128 240.038 240.163 240.517 240.740 240.752 241.651 242.051 242.605 242.857 242.941 243.238 243.248 243.279
Rent of primary residence…............................... 233.806 242.196 243.010 243.741 244.624 245.425 246.026 246.696 246.991 247.285 247.517 247.710 247.691 247.573 247.601
2
Lodging away from home ……….…………………… 142.339 143.164 148.368 142.591 140.763 133.747 129.982 134.235 136.255 138.008 138.008 136.113 139.246 140.873 138.543
3
Owners' equivalent rent of primary residence … 223.175 228.758 229.219 229.670 230.028 230.743 230.926 231.503 231.746 232.235 232.503 232.739 232.837 232.723 232.977
1,2
Tenants' and household insurance ……….…… 117.366
Fuels and utilities…...........................................
198.863
Fuels...............….............................................. 179.031
Fuel oil and other fuels…................................ 251.121
Gas (piped) and electricity….......................... 184.357
Household furnishings and operations…............ 122.477
Apparel ................................................................... 118.518
Men's and boys' apparel…................................. 112.224
Women's and girls' apparel…............................. 110.202
119.136 118.894 120.279 120.258 120.589 120.360 120.715 120.960 121.099 121.084 121.160 121.529 121.765 122.254
217.883
197.537
331.784
200.265
123.635
118.735
113.490
107.489
233.373
213.807
363.535
216.557
123.944
116.214
110.513
104.584
226.709
206.544
345.907
209.442
124.500
120.990
112.973
112.304
219.325
198.191
317.012
201.651
124.719
121.957
115.495
111.880
214.700
193.000
283.747
197.507
124.466
121.149
114.651
110.612
213.861
192.050
260.185
197.545
124.314
117.006
111.232
105.413
213.882
191.852
251.976
197.703
124.454
114.969
111.879
100.751
212.353
190.110
246.781
196.040
124.865
118.766
116.332
105.538
209.400
186.809
236.237
192.922
125.337
122.162
118.735
110.380
205.840
182.795
232.068
188.735
125.458
122.709
117.834
110.990
205.270
181.977
229.019
187.982
125.589
121.364
117.687
108.637
211.929
189.108
235.869
195.445
125.526
118.547
113.416
105.676
212.276
189.082
233.018
195.547
125.160
115.516
110.558
101.289
211.808
188.125
239.435
194.211
124.219
117.095
111.629
103.727
1
Infants' and toddlers' apparel ……….……………… 116.278 116.266 111.593 115.764 118.496 118.611 115.003 114.775 116.001 117.944 119.873 116.912 116.645 113.744 116.482
Footwear…......................................................... 122.062 124.102 122.026 124.873 126.352 126.689 124.152 122.753 124.494 126.858 128.312 127.802 126.150 125.046 125.880
Transportation.......................................................... 184.344 195.692 207.796 204.785 192.198 170.870 160.914 163.215 165.976 165.978 168.539 173.055 181.730 180.419 182.541
Private transportation...............…......................... 181.496 192.492 204.348 201.476 188.871 167.301 157.272 159.719 162.645 162.659 165.299 169.957 178.734 177.197 179.368
2
New and used motor vehicles ……….……………… 93.300
112
Monthly Labor Review • October 2009
92.146
92.287
91.305
90.530
89.783
89.482
89.774
89.728
89.418
89.620
90.039
90.588
90.973
91.129
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
Series
2007
2008
2008
Aug.
Sept.
2009
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
July
Aug.
New vehicles…............................................ 137.415 135.338 134.540 133.504 133.351 133.380 133.317 134.490 135.248 135.744 135.911 136.113 136.800 137.082 135.130
1
Used cars and trucks ……….…………………… 136.586
Motor fuel…................................................... 239.900
Gasoline (all types)….................................. 238.879
Motor vehicle parts and equipment…............ 121.356
Motor vehicle maintenance and repair…....... 225.535
Public transportation...............…..................... 228.531
Medical care.......................................................
Medical care commodities...............…............
Medical care services...............…...................
Professional services….................................
Hospital and related services….....................
350.882
282.558
370.111
303.169
493.740
134.731
280.817
278.728
128.776
236.353
247.865
136.186
325.116
322.930
130.228
238.583
264.755
133.669
316.717
315.324
131.072
239.571
258.142
130.444
269.639
267.580
132.088
240.688
249.168
127.540
187.770
184.855
133.125
241.509
240.496
126.526
149.650
146.644
133.295
241.855
235.199
125.485
157.265
155.204
133.645
243.594
232.422
123.443
168.028
166.831
134.264
244.219
229.404
121.669
169.060
168.574
134.485
244.650
229.034
121.850
177.982
177.510
134.614
245.180
228.525
123.339
194.339
194.569
134.439
245.036
227.522
125.056
225.876
226.515
134.273
245.129
230.926
125.817
218.560
218.757
133.787
245.421
236.963
128.781
225.797
226.007
133.587
245.871
237.029
364.208
287.970
386.317
313.446
530.193
364.652
286.880
387.420
314.893
532.065
365.250
287.397
388.036
314.977
534.394
366.000
287.725
388.947
315.458
537.382
366.800
289.046
389.493
315.825
539.864
367.301
290.080
389.744
316.435
540.101
370.001
291.710
392.831
318.110
547.655
372.630
293.917
395.563
319.663
554.390
373.541
294.728
396.489
320.231
557.167
374.599
295.699
397.553
320.407
561.516
375.420
296.431
398.387
322.043
560.906
375.479
296.369
398.497
322.346
561.337
376.161
295.871
399.677
322.759
565.448
377.007
297.379
400.204
322.964
567.545
2
Recreation ……….……………………………………… 108.572 110.143 110.698 110.904 110.947 110.826 110.487 110.630 111.257 111.436 111.182 111.152 111.471 111.416 111.453
1,2
Video and audio ……….……………………………102.559 102.654 102.643 102.819 102.267 101.974 101.810 101.488 101.857 102.153 102.516 102.214 102.193 101.982 101.867
2
Education and communication ……….…………… 116.301 119.827 120.809 121.439 121.569 121.636 121.819 122.025 122.092 122.087 122.152 122.293 122.333 122.699 123.579
2
Education ……….………………………………………169.280 178.892 180.819 183.613 184.091 184.115 184.352 184.642 184.765 184.824 184.892 185.291 185.626 186.596 190.222
Educational books and supplies….............. 423.730 452.880 461.104 465.570 466.885 465.576 467.179 471.061 473.012 474.880 474.950 475.213 480.024 485.218 493.615
Tuition, other school fees, and child care… 477.589 504.163 509.241 517.389 518.726 518.938 519.500 519.987 520.159 520.146 520.348 521.550 522.076 524.523 534.825
1,2
86.807 87.369 87.224 87.226 87.300 87.444 87.599 87.640 87.615 87.671 87.712 87.652 87.780 87.667
……….…………………………… 85.782
Communication
1,2
… 83.928
84.828
……….… 11.062
10.567
Information and information processing
85.355
85.208
85.214
85.292
85.454
85.581
85.624
85.595
85.655
85.624
85.524
85.653
85.532
1,2
Telephone services ……….………………… 98.373 100.502 101.339 101.350 101.436 101.564 101.720 101.876 101.890 101.977 102.048 102.231 102.153 102.587 102.613
Information and information processing
other than telephone services
1,4
10.525
10.414
10.375
10.367
10.406
10.418
10.442
10.378
10.385
10.271
10.238
10.113
10.012
Personal computers and peripheral
1,2
equipment ……….……………………… 108.164 94.863 92.931 90.722 89.690 88.631 88.176 88.178 87.622 86.004 85.406 84.017 83.278 80.736 78.480
Other goods and services.................................. 344.004 357.906 360.102 361.125 362.354 362.550 362.986 364.333 365.522 380.208 394.902 394.061 395.052 398.448 398.228
Tobacco and smoking products...............….... 555.502 591.100 599.823 600.293 602.533 602.881 605.662 610.503 615.012 682.115 747.906 746.009 752.078 768.005 768.483
1
Personal care ……….………………………………… 193.590 199.170 199.501 200.284 200.930 201.036 200.918 201.209 201.426 202.099 203.010 202.631 202.406 202.490 202.221
1
Personal care products ……….………………… 158.268 159.410 159.345 159.730 159.914 160.994 161.295 162.683 162.543 162.516 163.911 163.119 162.165 162.767 162.415
1
Personal care services ……….………………… 216.823 223.978 224.464 224.910 225.800 226.433 226.578 225.951 226.088 228.201 228.119 227.829 227.800 227.512 227.751
Miscellaneous personal services...............… 326.100 340.533 342.974 345.175 344.622 342.853 342.530 343.022 343.443 344.021 345.016 345.326 346.411 346.525 347.402
Commodity and service group:
Commodities...........….......................................
Food and beverages…....................................
Commodities less food and beverages…........
Nondurables less food and beverages…......
Apparel …...................................................
169.554
202.531
150.865
189.507
118.518
177.618
213.546
157.481
205.279
118.735
182.846
215.850
163.761
218.454
116.214
182.647
217.098
162.971
217.828
120.990
177.906
218.141
155.982
203.762
121.957
168.926
218.178
143.544
178.209
121.149
164.233
218.269
137.015
164.879
117.006
165.151
219.123
137.932
166.694
114.969
166.673
218.645
140.235
171.698
118.766
167.514
218.119
141.615
174.838
122.162
169.005
217.653
143.871
179.415
122.709
170.532
217.308
146.125
183.813
121.364
173.662
217.258
150.477
192.478
118.547
172.493
216.805
149.046
189.436
115.516
173.379
216.957
150.209
192.365
117.095
Nondurables less food, beverages,
and apparel…............................................ 237.858 263.756 287.124 283.056 259.204 217.500 198.108 202.400 208.255 211.287 218.502 226.621 242.726 239.626 243.461
Durables….................................................... 112.640 111.217 111.357 110.451 109.782 109.038 108.576 108.689 108.592 108.413 108.596 108.933 109.430 109.432 109.039
Services…......................................................... 241.696 250.272 253.304 252.861 252.369 252.144 252.176 253.033 253.456 253.591 253.403 253.482 254.624 255.003 255.342
3
Rent of shelter ……….……………………………… 224.617 230.555 231.445 231.541 231.885 232.096 232.112 232.981 233.365 233.903 234.148 234.229 234.511 234.515 234.537
Transporatation services…............................ 233.420 242.563 246.041 245.722 246.003 246.126 245.881 246.931 248.029 247.862 248.809 248.795 249.312 250.811 251.880
Other services…............................................. 275.218 284.319 286.389 287.792 287.898 288.082 288.227 288.627 289.432 290.043 289.738 290.116 290.845 291.573 293.266
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
2
3
Not seasonally adjusted.
Indexes on a December 1997 = 100 base.
Indexes on a December 1982 = 100 base.
202.698
193.940
196.564
152.875
190.698
234.201
196.772
210.452
203.102
204.626
159.538
206.047
258.423
210.333
214.950
208.544
208.900
165.689
218.562
279.753
218.473
214.361
208.068
208.563
164.937
218.010
276.112
218.725
210.949
204.149
205.726
158.132
204.734
254.473
211.680
205.214
197.342
200.707
145.985
180.533
216.516
198.009
202.292
193.918
198.153
139.620
167.933
198.909
190.910
203.186
194.811
198.978
140.543
169.708
202.906
192.284
204.465
196.052
199.928
142.809
174.484
208.291
194.740
205.167
196.551
200.421
144.172
177.487
211.094
196.174
206.081
197.432
201.112
146.371
181.815
217.649
198.408
207.148
198.571
201.955
148.589
186.012
225.091
200.601
209.744
201.488
204.200
152.856
194.254
239.808
205.219
209.308
200.871
203.723
151.466
191.387
237.011
203.377
210.021
201.726
204.341
152.606
194.170
240.515
205.017
230.876
232.195
208.066
203.002
203.554
140.612
241.257
247.888
241.567
240.275
237.414
208.719
208.147
141.084
284.270
255.598
246.834
243.354
267.624
209.718
208.857
140.802
328.310
257.072
245.787
242.868
259.864
210.325
209.329
141.428
319.507
257.411
244.331
242.316
232.106
210.649
209.511
141.375
272.894
257.774
243.599
242.058
188.375
210.541
209.383
140.793
192.494
258.008
243.646
242.079
168.726
210.168
208.925
139.731
154.744
258.039
244.376
242.819
172.463
210.707
209.404
139.614
161.781
258.976
244.791
243.128
177.033
211.279
210.203
140.554
171.978
259.643
244.413
243.223
175.947
211.989
211.178
142.077
172.563
260.158
243.718
242.980
178.485
212.472
211.857
143.237
181.021
260.439
243.784
243.022
186.321
212.462
211.926
143.170
196.706
260.615
245.833
244.196
205.662
212.552
212.051
142.943
227.444
261.014
246.622
244.531
201.967
212.505
212.097
142.526
220.264
261.425
247.308
244.857
205.144
212.823
212.449
142.634
227.506
261.960
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 • October 2009 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-
2009
ule1
U.S. city average……………………………………………
Mar.
Apr.
May
Urban Wage Earners
2009
June
July
Aug.
Mar.
Apr.
May
June
July
Aug.
M
212.709 213.240 213.856 215.693 215.351 215.834 207.218 207.925 208.774 210.972 210.526 211.156
Northeast urban……….………………………………………….………
M
227.309 227.840 228.136 229.930 230.154 230.883 223.626 224.252 224.748 226.695 226.714 227.598
Size A—More than 1,500,000...........................................
M
229.749 230.400 230.611 232.058 232.416 233.314 224.597 225.214 225.657 227.337 227.550 228.472
M
134.411 134.547 134.857 136.488 136.417 136.598 134.558 134.951 135.329 136.888 136.626 137.109
M
202.021 202.327 203.195 205.350 204.814 205.632 196.453 196.933 197.971 200.487 199.824 200.723
M
203.240 203.463 204.443 206.308 205.656 206.591 196.855 197.192 198.271 200.356 199.611 200.710
M
129.334 129.604 129.967 131.640 131.366 131.748 128.468 128.968 129.524 131.554 131.096 131.481
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
197.267 197.644 198.911 201.157 200.908 201.823 194.393 194.651 196.047 198.674 198.455 199.404
South urban…….…..............................................................
M
206.001 206.657 207.265 209.343 208.819 209.000 201.737 202.619 203.500 205.968 205.415 205.867
Size A—More than 1,500,000...........................................
M
208.529 208.934 209.235 211.390 211.034 211.436 205.066 205.733 206.271 208.909 208.492 208.995
M
130.873 131.370 131.777 133.056 132.736 132.729 128.686 129.309 129.885 131.382 131.063 131.302
3
Size B/C—50,000 to 1,500,000 ……….…………………………
Size D—Nonmetropolitan (less than 50,000)………….....
M
206.927 207.898 209.563 211.815 210.491 210.899 205.744 206.921 208.989 211.721 210.341 211.088
West urban…….…...............................................................
M
217.357 217.910 218.567 219.865 219.484 219.884 210.661 211.386 212.263 213.973 213.541 213.988
Size A—More than 1,500,000...........................................
M
221.124 221.790 222.659 223.908 223.498 224.072 212.965 213.646 214.734 216.395 215.955 216.539
M
131.775 131.912 131.990 132.952 132.774 132.756 130.674 131.103 131.389 132.517 132.314 132.407
M
M
M
194.750 195.207 195.745 197.214 196.987 197.614 192.327 192.861 193.597 195.414 195.096 195.796
131.230 131.557 131.876 133.220 132.975 133.069 129.833 130.361 130.847 132.384 132.069 132.341
204.672 205.421 206.717 208.543 207.784 208.369 201.485 202.351 203.883 206.327 205.504 206.271
Chicago–Gary–Kenosha, IL–IN–WI…………………………..
Los Angeles–Riverside–Orange County, CA……….…………
M
M
207.462 207.886 209.809 211.010 210.906 211.441 200.218 200.607 202.464 203.691 203.554 204.246
221.376 221.693 222.522 223.906 224.010 224.507 213.013 213.405 214.446 216.145 216.128 216.628
New York, NY–Northern NJ–Long Island, NY–NJ–CT–PA…
M
235.067 235.582 235.975 237.172 237.600 238.282 229.064 229.639 230.307 231.916 232.177 232.841
Boston–Brockton–Nashua, MA–NH–ME–CT……….…………
1
232.155
– 231.891
– 233.018
– 231.884
– 231.420
– 232.535
–
Cleveland–Akron, OH……………………………………………
1
199.457
– 200.196
– 200.558
– 190.107
– 191.297
– 191.494
–
Dallas–Ft Worth, TX…….………………………………………
1
200.039
– 199.311
– 200.663
– 200.770
– 200.955
– 203.075
–
Washington–Baltimore, DC–MD–VA–WV ……….……………
Atlanta, GA……………………..…………………………………
1
138.620
– 139.311
– 140.810
– 137.539
– 138.510
– 140.434
–
2
– 199.210
– 203.585
– 203.351
– 197.676
– 202.632
– 202.276
Detroit–Ann Arbor–Flint, MI……………………………………
2
– 202.373
– 204.537
– 204.673
– 197.239
– 199.977
– 200.169
Houston–Galveston–Brazoria, TX………………………………
2
– 189.701
– 192.325
– 191.687
– 186.970
– 189.979
– 189.503
Miami–Ft. Lauderdale, FL……………...………………………
2
– 220.740
– 221.485
– 221.306
– 217.900
– 219.091
– 219.000
Philadelphia–Wilmington–Atlantic City, PA–NJ–DE–MD……
2
– 221.686
– 223.810
– 226.039
– 220.732
– 223.361
– 225.481
San Francisco–Oakland–San Jose, CA…….…………………
2
– 223.854
– 225.692
– 225.801
– 218.587
– 220.996
– 221.279
Seattle–Tacoma–Bremerton, WA………………...……………
2
– 225.918
– 227.257
– 227.138
– 220.208
– 221.993
– 221.873
3
Size B/C—50,000 to 1,500,000 ……….…………………………
Size classes:
5
A
3
B/C
D…………….…………......................................................
Selected local areas 6
7
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.
2 Regions defined as the four Census regions.
3 Indexes on a December 1996 = 100 base.
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
1
114
Monthly Labor Review • October 2009
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.
7 Indexes on a November 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.
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............................……………………
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
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
215.303
3.8
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
214.225
5.4
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
216.264
3.2
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
118.907
-0.1
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
195.549
5.9
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
364.065
3.7
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
345.381
3.6
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
211.053
4.1
Monthly Labor Review • October 2009 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
2007
2008
2008
Aug.
Sept.
Oct.
2009
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
Mayp Junep Julyp Aug.p
166.6
173.5
167.0
177.1
186.3
178.3
182.2
193.2
181.3
182.2
193.0
181.5
177.4
185.5
180.7
172.0
178.2
179.8
168.8
173.7
177.7
170.4
175.8
177.7
169.9
175.2
175.0
169.1
174.2
173.8
170.3
176.0
175.9
170.8
176.8
173.9
174.1
181.3
176.0
172.6
179.6
173.4
174.3
181.8
173.9
excluding foods.....................................
Nondurable goods less food.................
Durable goods......................................
Capital equipment...................................
175.6
191.7
138.3
149.5
189.1
210.5
141.2
153.8
197.5
223.9
140.2
153.9
197.2
223.4
140.3
154.3
187.0
205.4
144.8
157.0
177.0
190.6
144.2
156.9
171.5
182.1
144.4
157.2
174.4
186.5
144.3
157.4
174.5
186.6
144.3
157.2
173.5
185.2
144.1
156.9
175.2
187.7
144.4
156.8
176.9
190.5
144.1
156.3
182.2
198.0
144.7
156.6
180.7
196.5
143.3
156.0
183.5
200.6
143.7
156.4
Intermediate materials,
supplies, and components........…………
170.7
188.3
199.4
198.6
189.0
179.2
171.6
171.4
169.7
168.0
168.6
168.7
172.6
172.4
174.9
162.4
161.4
184.0
189.8
136.3
177.2
180.4
214.3
203.3
140.3
188.7
187.5
238.6
218.9
141.9
186.7
185.2
234.7
214.5
142.4
180.3
179.4
222.4
202.2
142.5
171.1
175.5
200.6
190.0
142.3
163.7
170.8
185.0
178.6
141.9
162.7
167.3
186.8
172.8
141.7
161.0
164.3
185.6
168.2
141.5
159.5
163.2
182.3
165.8
141.3
158.9
164.2
182.6
163.2
140.8
158.2
166.1
180.9
162.0
140.6
160.7
166.1
189.2
162.9
140.6
161.4
163.4
191.8
163.7
140.6
163.7
164.0
195.7
169.0
140.9
for construction.........................................
Processed fuels and lubricants...................
Containers..................................................
Supplies......................................................
192.5
173.9
180.3
161.7
205.4
206.2
191.8
173.8
212.9
225.2
195.0
178.9
214.0
224.5
198.4
179.0
212.2
193.9
199.1
177.0
210.2
168.7
199.0
175.3
207.9
151.2
198.1
173.4
207.0
153.4
200.8
172.9
204.8
150.7
199.5
172.3
204.2
146.5
198.4
171.9
203.2
151.4
197.6
172.0
202.2
153.9
195.5
172.2
202.2
167.0
195.4
172.8
201.7
165.2
194.5
172.2
201.6
172.6
193.3
172.1
Crude materials for further
processing.......................…………………
Foodstuffs and feedstuffs...........................
Crude nonfood materials............................
207.1
146.7
246.3
251.8
163.4
313.9
274.6
170.6
350.0
254.2
167.6
314.2
212.0
147.9
253.9
183.3
144.2
203.2
172.6
135.5
191.6
170.2
136.1
186.5
160.7
133.3
171.5
160.1
131.0
172.6
163.9
136.5
174.6
172.5
140.8
186.3
180.8
141.2
201.5
172.8
133.2
194.3
178.0
129.8
207.2
Special groupings:
Finished goods, excluding foods................
Finished energy goods...............................
Finished goods less energy........................
Finished consumer goods less energy.......
Finished goods less food and energy.........
166.2
156.3
162.8
168.7
161.7
176.6
178.7
169.8
176.9
167.2
182.2
198.6
170.8
178.3
167.4
182.1
197.0
171.2
178.7
167.9
176.3
167.8
173.1
180.2
170.8
169.6
144.1
172.7
179.7
170.6
166.1
130.6
172.3
179.0
170.8
168.0
136.4
172.7
179.4
171.3
168.0
136.3
172.1
178.6
171.3
167.2
133.2
171.9
178.5
171.4
168.3
137.2
172.4
179.2
171.4
169.3
141.6
171.7
178.5
171.1
172.8
153.1
172.4
179.5
171.5
171.7
150.5
171.5
178.3
171.0
173.6
156.6
171.8
178.6
171.2
and energy................................................
Consumer nondurable goods less food
170.0
176.4
176.6
177.2
180.2
180.0
180.1
180.7
181.0
181.4
181.5
181.3
181.8
181.4
181.5
and energy..............................................
197.0
206.8
208.5
209.7
210.7
210.9
211.0
212.4
212.9
214.0
213.8
213.8
214.1
214.8
214.7
171.5
154.4
174.6
167.6
188.7
181.6
208.1
180.9
199.7
194.3
231.3
188.9
199.1
190.0
227.5
188.8
189.5
179.9
197.4
184.5
179.4
174.7
167.3
179.8
171.8
167.9
147.7
175.3
171.8
165.8
152.2
174.0
170.1
164.6
149.3
172.7
168.4
163.5
144.1
171.9
168.9
164.5
149.5
171.2
168.8
167.3
151.4
170.9
172.8
169.6
167.8
171.6
172.8
166.4
166.4
171.7
175.5
166.8
174.9
172.6
and energy................................................
168.4
180.9
188.7
188.8
184.8
180.2
175.9
174.6
173.4
172.6
171.8
171.2
171.7
172.2
173.2
Crude energy materials..............................
Crude materials less energy.......................
Crude nonfood materials less energy.........
232.8
182.6
282.6
309.4
205.4
324.4
339.1
222.3
374.2
303.7
211.7
337.5
244.4
182.0
276.7
194.9
167.6
224.8
181.1
159.8
221.3
173.0
161.2
225.2
152.1
158.8
224.9
153.3
156.4
222.9
155.0
161.2
224.4
166.4
167.2
235.4
184.1
168.7
240.9
172.5
163.5
247.6
184.2
163.8
262.0
Finished consumer goods
Materials and components
for manufacturing......................................
Materials for food manufacturing..............
Materials for nondurable manufacturing...
Materials for durable manufacturing.........
Components for manufacturing................
Materials and components
Finished consumer goods less food
Intermediate materials less foods
and feeds..................................................
Intermediate foods and feeds.....................
Intermediate energy goods.........................
Intermediate goods less energy..................
Intermediate materials less foods
p = preliminary.
116
Monthly Labor Review • October 2009
42. Producer Price Indexes for the net output of major industry groups
[December 2003 = 100, unless otherwise indicated]
NAICS
Industry
2008
Aug.
Sept.
Oct.
2009
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May p Junep Julyp Aug.p
Total mining industries (December 1984=100).............................
Oil and gas extraction (December 1985=100) .............................
Mining, except oil and gas……………………………………………
Mining support activities………………………………………………
299.2
383.6
190.4
177.1
273.4
341.2
188.9
177.6
223.3
259.4
184.1
179.3
184.9
199.5
174.7
179.9
174.8
184.1
173.0
177.0
173.4
180.3
178.4
174.0
159.0
154.1
184.7
172.0
159.1
154.1
186.1
168.7
160.5
157.0
187.9
162.9
168.3
170.1
188.9
159.5
181.0
191.7
189.6
154.3
175.0
183.3
188.2
150.1
187.0
201.7
188.5
154.9
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
182.6
180.5
114.8
114.2
102.5
154.1
109.1
124.5
110.0
382.2
182.9
179.2
115.2
114.9
102.7
154.8
109.1
126.6
110.4
382.6
176.8
176.4
116.1
114.9
103.0
154.6
107.6
127.3
110.3
300.0
169.4
173.4
116.0
114.7
103.2
154.3
106.7
127.2
110.2
221.4
164.1
171.1
116.3
113.5
103.2
154.3
106.2
127.0
110.3
167.0
164.7
170.1
117.6
113.4
103.5
154.3
105.0
126.7
110.2
178.6
163.9
168.7
119.2
113.0
103.5
154.7
104.0
126.0
109.6
176.4
162.9
167.6
120.3
112.3
103.5
154.7
103.2
125.5
109.6
168.0
164.2
168.6
119.6
112.1
103.5
153.9
102.8
124.5
109.4
186.2
165.6
170.4
119.3
112.2
103.8
153.4
102.3
123.1
109.3
205.2
168.5
171.4
119.5
112.4
103.5
153.6
102.1
122.3
109.0
238.4
167.2
169.7
119.7
112.3
103.6
153.5
103.2
122.0
108.5
227.0
169.4
169.8
119.9
112.0
103.6
154.3
103.5
121.4
108.1
250.4
325
326
(December 1984=100)………………………………….…………
Chemical manufacturing (December 1984=100)…………………… 238.2
165.2
Plastics and rubber products manufacturing
240.4
166.9
239.3
167.8
234.5
166.9
229.7
165.0
226.7
163.4
225.1
161.6
224.6
161.2
223.6
160.9
222.9
160.4
223.3
159.8
224.9
160.3
223.9
160.8
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
233.5
178.8
118.3
92.7
129.3
106.5
173.5
228.9
179.6
118.8
92.7
129.8
106.6
174.3
214.9
179.6
119.4
92.7
129.4
110.4
175.1
199.9
179.3
119.9
92.6
127.3
110.0
175.3
185.6
178.5
120.0
92.4
126.9
110.1
175.7
177.6
178.9
120.5
92.5
126.8
110.0
176.1
173.3
177.7
120.4
92.4
126.8
109.9
177.0
169.5
177.0
120.4
92.4
127.3
109.4
176.8
164.7
175.5
120.3
92.3
127.9
109.3
176.7
162.2
174.7
120.3
92.5
128.3
108.9
176.5
163.7
174.3
120.2
92.3
128.4
109.5
177.0
164.3
173.5
120.5
92.4
128.4
108.6
177.1
173.2
173.5
120.4
92.4
129.4
109.0
177.0
339
Miscellaneous manufacturing………………………………………… 110.5
110.4
110.6
110.4
110.8
111.4
111.4
111.6
111.7
111.5
111.5
111.7
111.6
117.5
122.0
111.0
133.3
72.7
162.4
117.6
121.1
110.8
134.0
81.7
150.6
116.8
121.0
108.9
134.6
76.8
148.7
118.5
120.8
108.1
136.4
76.3
154.1
117.1
120.6
107.8
136.4
77.7
155.2
116.9
120.8
107.8
136.0
68.9
150.9
118.4
121.0
103.7
136.0
71.0
153.9
118.0
120.8
105.4
136.3
63.1
156.1
119.0
121.4
104.9
138.7
59.7
148.0
118.3
123.7
104.6
137.4
59.2
142.5
119.3
121.9
103.0
136.5
69.6
140.0
118.2
120.2
104.3
135.4
75.7
148.4
118.1
119.5
105.2
138.0
62.9
145.6
Air transportation (December 1992=100)…………………………… 213.0
Water transportation…………………………………………………… 133.7
Postal service (June 1989=100)……………………………………… 180.5
208.6
135.1
180.5
209.3
135.0
180.5
203.8
130.6
180.5
198.5
128.0
180.5
198.4
122.4
180.5
190.5
118.5
181.6
187.6
117.7
181.6
187.2
115.2
181.6
176.1
117.5
186.8
177.0
110.6
186.8
184.5
113.4
186.8
188.1
113.4
186.8
140.8
136.0
133.4
133.1
133.9
132.9
130.4
128.1
126.9
129.1
131.8
131.8
123.6
106.9
126.3
163.2
119.7
118.7
123.7
107.6
126.5
163.0
119.8
118.9
124.0
107.7
127.3
164.9
120.6
119.1
124.3
107.7
127.3
164.9
120.6
119.2
124.2
107.8
127.4
165.3
120.7
119.2
125.6
108.3
127.2
166.5
122.0
120.3
125.6
108.7
127.6
166.8
122.2
120.3
125.9
108.9
127.7
167.0
122.3
120.5
125.9
108.8
127.7
166.9
122.6
121.4
125.7
108.8
127.3
166.9
122.7
121.5
125.9
108.7
127.7
167.1
123.1
121.1
126.6
108.9
127.6
167.2
123.5
120.8
126.8
108.9
127.7
167.5
123.9
121.6
111.1
105.5
101.5
101.0
120.2
112.7
104.4
109.3
135.0
161.5
115.5
110.2
107.0
101.5
101.1
120.5
111.7
103.8
108.6
131.3
162.6
115.4
110.9
112.0
101.2
101.3
117.7
111.5
103.1
109.2
128.2
163.2
115.6
111.1
111.5
101.2
101.3
115.8
111.7
103.0
108.2
126.9
163.2
115.0
110.7
109.3
101.4
101.3
115.2
112.8
102.8
109.8
123.7
163.2
115.7
111.9
107.9
101.2
101.0
113.5
111.0
101.6
109.9
128.3
164.8
115.3
111.9
108.1
101.1
100.9
111.7
109.0
101.6
108.6
133.0
165.5
115.2
111.6
107.5
101.1
100.9
109.2
109.5
101.6
109.9
133.1
166.0
115.3
111.7
105.5
100.8
100.9
109.1
108.8
101.9
109.2
135.1
166.2
115.3
111.7
107.1
101.8
100.9
111.8
109.0
101.9
109.7
134.6
166.1
115.3
111.8
107.4
101.2
101.0
110.9
109.4
101.9
108.9
138.1
166.2
115.3
111.2
103.4
101.3
101.0
109.5
109.4
102.0
109.0
142.5
166.2
115.3
111.4
101.2
101.8
101.0
110.0
110.0
102.0
108.7
142.5
166.4
115.2
141.6
106.3
123.4
98.8
109.3
113.3
150.9
141.6
106.3
123.1
101.4
109.4
114.0
146.9
141.8
106.3
123.6
101.4
109.4
113.0
145.6
141.8
106.3
124.1
101.4
109.4
113.3
144.3
141.9
106.3
124.2
101.4
109.1
111.3
141.6
142.9
105.6
123.8
101.4
109.6
112.2
140.6
142.9
105.4
124.0
101.8
109.7
113.3
139.9
142.8
105.3
123.6
102.2
109.8
114.9
141.3
143.0
105.3
123.9
100.2
109.7
115.0
141.5
142.9
105.4
123.3
99.7
109.6
115.8
143.8
142.9
105.2
123.8
100.2
109.7
115.0
144.6
142.9
105.3
123.2
100.3
109.9
116.5
150.5
142.9
105.3
123.4
100.5
110.2
116.8
148.3
211
212
213
311
312
313
315
316
321
322
323
324
(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…………………………………………………………………… 145.7
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 • October 2009 117
Current Labor Statistics: Price Data
43. Annual data: Producer Price Indexes, by stage of processing
[1982 = 100]
Index
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
Finished goods
Total...............................................................................
Foods............................…………………………….……
Energy............……………………………………….….…
Other…...............................………………………….……
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
96.7
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
167.0
156.3
161.7
177.1
178.3
178.7
167.2
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
170.7
161.4
174.6
168.4
188.3
180.4
208.1
180.9
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
207.1
146.7
232.8
238.7
251.8
163.4
309.4
308.5
Intermediate materials, supplies, and
components
Total...............................................................................
Foods............……………………………………….….…
Energy…...............................………………………….…
Other.................…………...………..........………….……
Crude materials for further processing
Total...............................................................................
Foods............................…………………………….……
Energy............……………………………………….….…
Other…...............................………………………….……
44. U.S. export price indexes by end-use category
[2000 = 100]
Category
2008
Aug.
Sept.
Oct.
2009
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
July
Aug.
ALL COMMODITIES……………....................................
125.9
124.9
122.3
118.4
115.8
116.6
116.3
115.5
116.1
116.6
117.8
117.4
118.2
Foods, feeds, and beverages……………...……………
Agricultural foods, feeds, and beverages….............
Nonagricultural (fish, beverages) food products……
189.6
194.7
145.7
190.4
195.6
145.5
175.0
178.3
147.8
164.8
166.9
148.3
155.1
156.6
143.5
165.4
167.6
147.9
162.1
164.1
145.7
156.7
158.3
144.4
162.8
165.0
145.3
167.3
170.3
141.4
174.8
178.6
141.5
165.0
167.6
143.1
164.7
167.3
142.8
Industrial supplies and materials……………...………… 174.0
118
169.4
161.8
148.2
139.6
139.0
137.9
136.5
136.9
137.7
140.4
140.5
143.6
Agricultural industrial supplies and materials…........
160.9
157.4
148.5
134.2
126.1
125.6
126.2
122.9
123.6
130.2
131.0
134.9
138.5
Fuels and lubricants…...............................…………
275.8
267.2
239.2
193.4
166.8
165.8
156.2
146.9
156.9
160.2
175.2
166.0
181.4
Nonagricultural supplies and materials,
excluding fuel and building materials…………...…
Selected building materials…...............................…
165.3
115.2
160.8
115.4
155.5
116.6
145.6
115.6
138.8
115.1
138.2
115.5
138.2
115.3
138.2
114.0
137.1
113.5
137.3
112.5
138.5
113.0
139.8
112.9
141.1
113.8
Capital goods……………...…………………………….… 101.9
Electric and electrical generating equipment…........ 109.2
Nonelectrical machinery…...............................……… 94.1
101.8
109.5
93.9
101.7
109.7
93.6
101.6
109.2
93.5
101.5
109.0
93.3
102.1
107.3
93.7
102.3
106.7
94.0
102.3
106.8
93.8
102.8
106.8
94.3
103.0
107.0
94.4
103.1
107.2
94.4
103.4
107.1
94.7
103.5
107.2
94.8
Automotive vehicles, parts, and engines……………...
107.8
107.9
108.2
108.1
108.0
108.4
108.1
108.2
108.1
108.1
108.0
107.8
107.9
Consumer goods, excluding automotive……………... 109.0
Nondurables, manufactured…...............................… 109.6
Durables, manufactured…………...………..........…… 107.2
109.3
109.0
108.7
109.9
108.9
109.9
109.1
107.4
109.8
109.0
107.2
109.7
109.2
108.8
109.7
109.3
109.0
109.8
108.5
107.1
109.9
107.5
107.2
107.6
107.9
107.8
107.9
108.4
108.5
108.1
108.9
108.6
109.5
109.1
109.1
109.6
Agricultural commodities……………...…………………
Nonagricultural commodities……………...……………
188.3
120.4
172.5
118.7
160.6
115.4
150.8
113.2
159.7
113.5
157.0
113.3
151.6
112.9
157.2
113.1
162.8
113.4
169.7
114.1
161.3
114.3
161.7
115.1
Monthly Labor Review • October 2009
188.2
121.5
45. U.S. import price indexes by end-use category
[2000 = 100]
Category
2008
Aug.
Sept.
Oct.
2009
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
July
Aug.
ALL COMMODITIES……………....................................
143.0
137.8
129.6
120.0
114.5
113.0
113.0
113.6
114.8
116.8
120.0
119.2
121.1
Foods, feeds, and beverages……………...……………
Agricultural foods, feeds, and beverages….............
Nonagricultural (fish, beverages) food products……
150.4
167.9
110.9
147.9
165.1
109.1
146.0
162.8
108.0
139.5
154.4
105.8
142.3
159.4
103.8
142.3
159.0
104.5
137.8
153.0
103.4
137.0
151.3
104.8
138.9
154.3
104.1
139.2
155.0
103.6
139.8
155.5
104.4
138.2
153.2
104.2
140.0
155.7
104.4
Industrial supplies and materials……………...………… 270.7
248.9
213.5
174.6
150.4
143.7
144.9
149.3
154.3
163.0
177.3
174.3
182.3
Fuels and lubricants…...............................…………
Petroleum and petroleum products…………...……
392.0
419.5
346.3
371.5
274.1
288.9
197.8
201.6
153.9
150.8
146.6
143.8
150.5
151.6
162.3
168.5
174.4
185.5
191.5
206.1
222.1
241.5
215.9
235.4
231.3
253.6
Paper and paper base stocks…...............................
119.7
119.9
116.4
115.1
113.2
110.3
108.8
106.6
104.6
103.3
101.8
99.0
98.6
Materials associated with nondurable
supplies and materials…...............................………
Selected building materials…...............................…
Unfinished metals associated with durable goods…
Nonmetals associated with durable goods…...........
159.6
122.1
270.3
111.8
162.4
122.7
255.4
111.4
160.2
120.4
236.7
110.9
155.0
118.8
209.3
110.4
148.5
118.1
185.7
109.0
138.8
117.2
176.5
107.1
137.1
116.5
175.9
106.2
136.7
116.2
171.6
105.2
135.3
115.2
171.1
104.3
139.2
114.5
172.8
103.4
137.5
116.0
178.3
103.0
132.3
118.2
184.7
102.8
133.4
119.5
190.2
103.2
Capital goods……………...…………………………….… 93.4
Electric and electrical generating equipment…........
113.0
Nonelectrical machinery…...............................……… 88.3
93.3
112.9
88.2
93.3
112.3
88.1
92.9
111.8
87.7
92.7
111.4
87.5
92.7
111.1
87.5
92.3
110.3
87.2
91.8
109.4
86.6
91.9
109.1
86.8
91.9
109.8
86.7
91.9
110.0
86.5
91.9
110.3
86.5
91.9
110.3
86.5
Automotive vehicles, parts, and engines……………...
108.3
108.1
108.3
107.9
107.8
108.0
107.9
107.7
107.7
107.9
108.0
108.2
108.4
Consumer goods, excluding automotive……………...
Nondurables, manufactured…...............................…
Durables, manufactured…………...………..........……
Nonmanufactured consumer goods…………...………
105.2
108.4
101.7
106.6
105.1
108.2
101.8
106.6
105.1
108.1
101.8
105.9
104.6
108.0
101.1
103.2
104.4
108.2
100.7
103.6
104.4
108.9
100.1
102.7
104.4
108.9
100.0
104.4
103.9
108.4
99.8
101.2
104.1
108.3
100.0
102.7
104.2
108.1
100.5
101.3
104.3
108.1
100.6
101.4
104.0
107.8
100.5
101.5
103.9
107.8
100.4
100.9
46. U.S. international price Indexes for selected categories of services
[2000 = 100, unless indicated otherwise]
Category
2007
June
Sept.
2008
Dec.
Mar.
June
2009
Sept.
Dec.
Mar.
June
Import air freight……………...........................................
Export air freight……………...……………………………
132.3
117.0
134.2
119.8
141.8
127.1
144.4
132.0
158.7
140.8
157.1
144.3
138.5
135.0
132.9
124.1
133.9
117.4
Import air passenger fares (Dec. 2006 = 100)……………
Export air passenger fares (Dec. 2006 = 100)…............
144.6
147.3
140.2
154.6
135.3
155.7
131.3
156.4
171.6
171.4
161.3
171.9
157.3
164.6
134.9
141.7
147.3
135.9
Monthly Labor Review • October 2009 119
Current Labor Statistics: Productivity Data
47. Indexes of productivity, hourly compensation, and unit costs, quarterly data seasonally adjusted
[1992 = 100]
2006
Item
II
2007
III
IV
I
138.7
169.1
120.3
121.9
136.7
127.4
138.0
169.7
119.7
123.0
137.3
128.3
138.7
173.3
122.5
124.9
135.1
128.7
139.0
175.2
122.7
126.0
136.7
130.0
137.7
168.0
119.6
122.0
139.0
128.3
137.0
168.6
118.9
123.0
139.5
129.1
137.8
172.3
121.8
125.0
136.9
129.3
142.1
159.4
113.4
114.0
112.2
118.9
175.8
134.4
119.6
143.4
159.8
112.7
113.5
111.4
119.1
191.4
138.7
120.6
172.5
148.8
105.9
86.3
174.4
149.4
105.4
85.7
II
2008
III
IV
I
140.2
176.5
122.4
125.9
139.4
130.9
142.1
177.8
122.6
125.1
141.9
131.4
142.6
179.6
122.1
125.9
141.9
131.9
142.7
180.3
121.2
126.3
141.7
132.1
138.2
174.2
122.1
126.0
138.2
130.5
139.2
175.1
121.4
125.8
140.9
131.4
141.1
176.3
121.5
125.0
143.3
131.7
141.8
178.5
121.3
125.9
143.0
132.2
143.6
162.5
114.9
115.3
113.2
120.9
175.8
135.9
120.8
143.5
164.2
115.0
116.8
114.4
123.1
171.2
136.2
121.8
144.5
165.2
114.6
117.2
114.4
124.9
171.8
137.7
122.2
144.1
166.2
114.5
118.6
115.3
127.4
155.6
135.1
122.0
175.3
153.0
108.2
87.3
176.9
156.1
109.3
88.2
178.2
156.1
108.2
87.6
180.1
156.1
107.6
86.7
II
2009
III
IV
I
II
143.8
181.0
120.4
125.9
143.8
132.5
143.9
183.0
119.9
127.2
145.4
134.0
144.2
184.2
123.3
127.7
143.6
133.6
144.3
183.0
123.3
126.9
146.9
134.3
146.5
183.1
122.9
125.0
149.9
134.3
141.7
179.2
120.5
126.4
142.5
132.3
142.8
179.8
119.6
125.9
144.9
132.9
142.8
181.8
119.1
127.3
146.6
134.4
143.1
183.1
122.6
128.0
145.3
134.3
143.2
182.0
122.6
127.1
149.2
135.2
145.5
182.1
122.2
125.2
152.3
135.1
145.9
168.3
114.4
118.7
115.3
127.9
149.9
133.9
121.6
145.0
168.6
113.4
119.8
116.3
129.1
133.0
130.2
121.0
147.4
169.7
112.9
118.9
115.1
129.2
134.7
130.7
120.4
148.6
171.8
112.5
119.4
115.6
129.8
145.3
134.0
121.8
148.0
173.7
116.3
121.8
117.3
134.1
129.5
132.8
122.5
145.8
172.6
116.2
123.8
118.4
138.6
127.1
135.5
124.1
–
–
–
–
–
–
–
–
–
181.6
158.6
107.8
87.3
182.8
158.6
106.6
86.8
181.6
159.7
106.2
87.9
180.3
161.4
105.7
89.5
178.1
166.0
111.2
93.2
177.0
166.9
112.4
94.3
179.2
169.3
113.7
94.5
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 • October 2009
48. Annual indexes of multifactor productivity and related measures, selected years
[2000 = 100, unless otherwise indicated]
Item
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
Private business
Productivity:
Output per hour of all persons......……………..............
90.0
Output per unit of capital services……………………… 105.3
Multifactor productivity……………………………………
95.3
Output…...............................………………………….……
82.8
91.7
105.3
96.2
87.2
94.3
103.8
97.4
91.5
97.2
102.3
98.8
96.2
100.0
100.0
100.0
100.0
102.8
96.0
100.4
100.5
107.1
94.7
102.5
102.0
111.2
95.5
105.4
105.2
114.5
97.2
108.2
109.7
116.6
98.1
109.7
113.6
117.6
98.4
110.3
117.1
119.5
97.7
110.7
119.5
122.7
95.6
112.0
120.4
90.8
78.7
86.9
85.5
94.4
82.9
90.7
87.1
96.5
88.2
93.9
90.9
98.8
94.1
97.4
95.0
100.0
100.0
100.0
100.0
98.2
104.6
100.0
107.0
96.2
107.7
99.5
113.1
95.8
110.2
99.9
116.5
96.9
112.9
101.4
117.8
98.8
115.8
103.6
118.9
101.2
119.1
106.2
119.6
102.3
122.3
108.0
122.3
100.3
125.9
107.6
128.3
Productivity:
Output per hour of all persons........……………………… 90.5
Output per unit of capital services……………………… 106.1
95.8
Multifactor productivity……………………………………
Output…...............................………………………….……
82.8
92.0
105.8
96.5
87.2
94.5
104.2
97.7
91.5
97.3
102.6
99.0
96.3
100.0
100.0
100.0
100.0
102.7
96.0
100.4
100.5
107.1
94.5
102.5
102.1
111.1
95.2
105.2
105.2
114.2
96.9
108.0
109.6
116.1
97.7
109.3
113.5
117.2
97.9
109.9
117.1
118.9
97.0
110.1
119.4
122.3
95.1
111.4
120.4
90.4
78.1
86.5
85.3
94.0
82.4
90.4
86.9
96.3
87.8
93.7
90.7
98.8
93.9
97.3
94.8
100.0
100.0
100.0
100.0
98.4
104.7
100.2
107.0
96.4
107.9
99.6
113.2
96.0
110.5
100.0
116.7
97.1
113.1
101.5
117.8
99.1
116.1
103.8
118.9
101.6
119.6
106.6
119.7
102.8
123.1
108.4
122.6
100.9
126.7
108.1
128.8
Productivity:
Output per hour of all persons...…………………………
Output per unit of capital services………………………
Multifactor productivity……………………………………
Output…...............................………………………….……
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…………...………...
100.4
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 • October 2009 121
Current Labor Statistics: Productivity Data
49. Annual indexes of productivity, hourly compensation, unit costs, and prices, selected years
[1992 = 100]
Item
1963
1973
1983
1993
2000
2001
2002
2003
2004
2005
2006
2007
2008
Business
Output per hour of all persons........................................
Compensation per hour…………………………….………
Real compensation per hour………………………………
Unit labor costs…...............................……………………
Unit nonlabor payments…………...………..........………
Implicit price deflator………………………………………
55.0
15.6
66.6
28.4
26.6
27.7
73.4
28.9
85.1
39.4
37.5
38.7
83.0
66.3
90.5
79.8
76.3
78.5
100.4
102.2
99.8
101.8
102.6
102.1
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
157.0
119.0
118.5
124.6
120.8
134.8
163.2
119.7
121.0
130.5
124.6
136.1
169.4
120.3
124.5
134.8
128.3
138.2
176.5
121.9
127.7
137.7
131.4
141.9
182.8
121.6
128.8
142.1
133.8
57.8
16.1
68.7
27.8
26.3
27.3
75.3
29.1
85.5
38.6
35.3
37.4
84.5
66.6
91.1
78.9
76.1
77.9
100.4
102.0
99.5
101.6
103.1
102.1
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
156.0
118.2
118.5
125.5
121.1
133.9
162.1
118.9
121.1
132.1
125.1
135.1
168.3
119.5
124.5
136.8
129.1
137.0
175.2
121.0
127.9
138.4
131.7
140.9
181.7
120.8
129.0
143.3
134.2
62.6
17.9
76.4
27.2
28.6
23.4
57.3
32.5
29.9
74.8
31.0
91.2
39.9
41.4
35.7
54.9
40.8
41.2
85.7
68.9
94.2
80.7
80.4
81.6
91.2
84.2
81.7
100.3
101.8
99.3
101.0
101.4
99.9
114.1
103.7
102.2
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
139.7
154.0
116.8
110.0
110.3
109.3
144.8
118.8
113.1
143.4
159.6
117.1
111.7
111.3
112.7
163.0
126.2
116.3
146.0
165.4
117.5
113.6
113.3
114.6
183.5
133.0
119.9
147.1
172.2
118.9
117.4
117.1
118.3
167.3
131.4
121.9
151.2
178.9
119.0
119.1
118.3
121.3
149.9
129.0
121.9
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
102.6
102.0
99.6
99.5
101.1
100.6
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
164.0
161.5
122.5
98.5
110.2
106.4
171.9
164.5
120.7
95.7
122.2
113.5
173.7
171.2
121.6
98.6
126.6
117.4
179.2
177.4
122.5
99.0
–
–
180.7
184.7
122.8
102.2
–
–
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 • October 2009
50. Annual indexes of output per hour for selected NAICS industries
[1997=100]
NAICS
Industry
Mining
21
211
2111
212
2121
2122
2123
213
2131
Mining………………………………………………….
Oil and gas extraction…………………………………
Oil and gas extraction…………………………………
Mining, except oil and gas……………………………
Coal mining…………………………………………….
Metal ore mining…………………………………………
Nonmetallic mineral mining and quarrying…………
Support activities for mining……………………………
Support activities for mining……………………………
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………
1987
1992
1997
2000
2001
2002
2003
2004
2005
2006
2007
2008
85.3
80.1
80.1
69.3
57.8
71.0
88.0
79.4
79.4
95.0
81.6
81.6
86.8
75.0
91.2
96.4
90.7
90.7
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
111.0
119.4
119.4
106.3
115.8
121.5
96.1
100.9
100.9
109.1
121.6
121.6
109.0
114.3
132.2
99.4
110.4
110.4
113.5
123.8
123.8
110.7
111.7
138.2
103.6
103.5
103.5
116.0
130.1
130.1
113.8
113.4
142.2
108.3
136.3
136.3
106.8
111.7
111.7
116.2
113.4
137.1
114.3
170.3
170.3
96.0
107.8
107.8
114.2
107.8
129.9
118.4
144.9
144.9
87.3
100.4
100.4
111.0
99.8
123.1
120.0
147.0
147.0
81.7
97.0
97.0
105.2
101.0
104.2
109.8
156.8
156.8
-
65.6
67.8
74.5
76.1
100.0
100.0
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
119.1
113.3
119.7
-
94.1
83.6
81.1
87.6
92.4
97.7
90.5
91.1
89.2
91.9
100.0
100.0
100.0
100.0
100.0
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
95.2
101.8
117.8
97.1
97.6
100.0
100.0
100.0
100.0
100.0
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
91.3
94.9
77.8
81.9
80.2
100.0
100.0
100.0
100.0
100.0
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
81.4
83.5
92.9
92.7
91.8
100.0
100.0
100.0
100.0
100.0
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
164.1
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
76.8
93.3
72.9
98.6
78.5
100.0
100.0
100.0
100.0
100.0
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
84.7
83.9
94.7
100.8
85.8
100.0
100.0
100.0
100.0
100.0
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
114.3
103.0
90.6
87.9
94.0
100.0
100.0
100.0
100.0
100.0
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
101.7
101.7
78.4
78.4
86.9
100.0
100.0
100.0
100.0
100.0
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
89.3
90.2
80.4
82.1
87.5
89.6
100.0
100.0
100.0
100.0
100.0
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
85.0
85.8
89.3
90.8
84.7
100.0
100.0
100.0
100.0
100.0
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
Nonmetallic mineral products…………………………
Clay products and refractories…………………………
87.6
86.9
90.8
92.0
100.0
100.0
102.5
102.9
100.0
98.4
104.6
99.7
111.2
103.5
108.7
109.2
115.3
114.6
114.6
111.9
-
-
Utilities
Manufacturing
Monthly Labor Review • October 2009 123
Current Labor Statistics: Productivity Data
50. Continued - Annual indexes of output per hour for selected NAICS industries
[1997=100]
NAICS
124
Industry
1987
1992
1997
2000
2001
2002
2003
2004
2005
2006
2007
2008
3272
3273
3274
3279
331
Glass and glass products………………………………
Cement and concrete products………………………
Lime and gypsum products……………………………
Other nonmetallic mineral products…………………
Primary metals…………………………………………
82.4
93.6
88.2
83.0
81.0
83.9
96.2
89.3
90.3
88.2
100.0
100.0
100.0
100.0
100.0
108.1
101.6
98.5
96.6
101.3
102.9
98.0
101.8
98.6
101.0
107.5
102.4
99.0
106.9
115.2
115.3
108.3
107.1
113.6
118.2
113.8
102.8
104.7
110.6
132.0
123.1
106.5
119.3
118.9
135.5
132.9
103.1
116.5
116.3
134.3
-
-
3311
3312
3313
3314
3315
Iron and steel mills and ferroalloy production………
Steel products from purchased steel…………………
Alumina and aluminum production……………………
Other nonferrous metal production……………………
Foundries…………………………………………………
64.8
79.7
90.5
96.8
81.4
74.7
90.1
95.8
99.7
86.4
100.0
100.0
100.0
100.0
100.0
106.0
96.4
96.6
102.3
103.6
104.4
97.9
96.2
99.5
107.4
125.1
96.8
124.5
107.6
116.7
130.4
93.9
126.8
120.6
116.3
164.9
88.6
137.3
123.1
123.9
163.1
90.8
154.4
122.3
128.6
163.5
86.1
151.7
115.7
131.8
-
-
332
3321
3322
3323
3324
Fabricated metal products……………………………
Forging and stamping…………………………………
Cutlery and handtools…………………………………
Architectural and structural metals……………………
Boilers, tanks, and shipping containers………………
87.3
85.4
86.3
88.7
86.0
91.9
92.2
87.4
92.7
95.4
100.0
100.0
100.0
100.0
100.0
104.8
121.1
105.9
100.6
94.2
104.8
120.7
110.3
101.6
94.4
110.9
125.0
113.4
106.0
98.9
114.4
133.1
113.2
108.8
101.6
113.4
142.0
107.6
105.4
93.6
116.9
147.6
114.1
109.2
95.7
119.7
152.7
116.6
113.5
96.6
-
-
3325
3326
3327
3328
3329
Hardware…………………………………………………
Spring and wire products………………………………
Machine shops and threaded products………………
Coating, engraving, and heat treating metals………
Other fabricated metal products………………………
88.7
82.2
76.9
75.5
91.0
87.3
90.8
87.4
86.6
90.4
100.0
100.0
100.0
100.0
100.0
114.3
112.6
108.2
105.5
99.9
113.5
111.9
108.8
107.3
96.7
115.5
125.7
114.8
116.1
106.5
125.4
135.3
115.7
118.3
111.6
126.0
133.8
114.6
125.3
111.2
131.8
143.2
116.3
136.5
112.5
131.1
140.6
117.1
135.5
117.7
-
-
333
3331
3332
3333
3334
Machinery………………………………………………
Agriculture, construction, and mining machinery……
Industrial machinery……………………………………
Commercial and service industry machinery…………
HVAC and commercial refrigeration equipment……
82.3
74.6
75.1
87.0
84.0
86.7
79.0
79.9
100.4
91.5
100.0
100.0
100.0
100.0
100.0
111.5
100.3
130.0
101.3
107.9
109.0
100.3
105.8
94.5
110.8
116.6
103.7
117.6
97.8
118.6
125.2
116.1
117.0
104.7
130.0
127.0
125.4
126.5
106.5
132.8
134.1
129.4
122.4
115.1
137.1
137.4
129.1
135.3
122.3
133.4
-
-
3335
3336
3339
334
3341
Metalworking machinery………………………………
Turbine and power transmission equipment…………
Other general purpose machinery……………………
Computer and electronic products……………………
Computer and peripheral equipment…………………
85.1
80.2
83.5
28.4
11.0
89.2
80.9
85.4
43.3
21.4
100.0
100.0
100.0
100.0
100.0
106.1
114.9
113.7
181.8
235.0
103.3
126.9
110.5
181.4
252.2
112.7
130.7
117.9
188.0
297.4
115.2
143.0
128.1
217.2
373.4
117.1
126.4
127.1
244.3
415.1
127.3
132.5
138.4
259.6
543.3
128.3
128.5
143.8
282.2
715.7
-
-
3342
3343
3344
3345
3346
Communications equipment……………………………
Audio and video equipment……………………………
Semiconductors and electronic components…………
Electronic instruments…………………………………
Magnetic media manufacturing and reproduction……
39.8
61.7
17.0
70.2
85.7
60.6
93.6
29.9
85.9
90.9
100.0
100.0
100.0
100.0
100.0
164.1
126.3
232.2
116.7
105.8
152.9
128.4
230.0
119.3
99.8
128.2
150.1
263.1
118.1
110.4
143.1
171.0
321.6
125.3
126.1
148.4
239.3
360.0
145.4
142.6
143.7
230.2
381.6
146.6
142.1
178.2
240.7
380.4
150.6
137.7
-
-
335
3351
3352
3353
3359
Electrical equipment and appliances…………………
Electric lighting equipment……………………………
Household appliances…………………………………
Electrical equipment……………………………………
Other electrical equipment and components…………
75.5
91.1
73.3
68.7
78.8
82.2
94.1
82.1
79.0
82.2
100.0
100.0
100.0
100.0
100.0
111.5
102.0
117.2
99.4
119.7
111.4
106.7
124.6
101.0
113.1
113.3
112.4
132.3
101.8
114.0
117.2
111.4
146.7
103.4
116.2
123.3
122.7
159.6
110.8
115.6
130.0
130.3
164.5
118.5
121.6
129.4
136.7
173.2
118.1
115.7
-
-
336
3361
3362
3363
3364
Transportation equipment………………………………
Motor vehicles……………………………………………
Motor vehicle bodies and trailers………………………
Motor vehicle parts………………………………………
Aerospace products and parts…………………………
81.6
75.4
85.0
78.7
87.2
88.0
90.8
88.4
82.3
96.5
100.0
100.0
100.0
100.0
100.0
109.4
109.7
98.8
112.3
103.4
113.6
110.0
88.7
114.8
115.7
127.4
126.0
105.4
130.5
118.6
137.5
140.7
109.8
137.0
119.0
134.9
142.1
110.7
138.0
113.2
140.9
148.4
114.2
144.1
125.0
142.4
163.8
110.9
143.7
117.9
-
-
3365
3366
3369
337
3371
Railroad rolling stock……………………………………
Ship and boat building…………………………………
Other transportation equipment………………………
Furniture and related products…………………………
Household and institutional furniture…………………
55.6
95.5
73.7
84.8
85.2
81.7
99.4
89.5
89.5
92.5
100.0
100.0
100.0
100.0
100.0
118.5
121.9
132.4
101.4
101.9
126.1
121.5
140.2
103.4
105.5
146.1
131.0
150.9
112.6
111.8
139.8
133.9
163.0
117.0
114.7
131.5
138.7
168.3
118.4
113.6
137.3
131.7
184.1
125.0
120.8
148.0
127.3
197.8
127.8
124.0
-
-
3372
3379
339
3391
3399
Office furniture and fixtures……………………………
Other furniture related products………………………
Miscellaneous manufacturing…………………………
Medical equipment and supplies………………………
Other miscellaneous manufacturing…………………
85.8
86.3
81.1
76.3
85.4
86.4
87.6
90.0
89.2
90.3
100.0
100.0
100.0
100.0
100.0
100.2
99.5
114.7
115.5
113.6
98.0
105.0
116.6
120.7
111.8
115.9
110.2
124.2
129.1
118.0
125.2
110.0
132.7
138.9
124.7
130.7
121.3
134.9
139.5
128.6
134.9
128.3
144.6
148.5
137.8
134.4
130.8
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
86.5
75.4
84.1
95.4
110.4
47.1
100.0
100.0
100.0
100.0
100.0
100.0
116.4
124.9
116.7
112.4
107.7
181.9
117.6
128.8
120.1
110.6
116.6
217.8
123.1
140.0
133.4
115.8
123.9
264.7
127.4
146.4
137.6
123.8
133.0
298.9
134.2
161.1
143.5
129.9
139.3
352.5
134.7
166.4
146.7
127.0
140.1
399.9
136.6
172.0
159.3
130.9
134.9
442.5
136.5
170.5
152.2
121.9
128.1
477.7
136.1
171.2
140.5
102.4
126.6
521.4
4235
4236
4237
4238
Metals and minerals…………………………………… 101.7
Electric goods…………………………………………… 42.8
Hardware and plumbing………………………………
82.2
Machinery and supplies………………………………
74.1
108.0
56.0
94.1
80.7
100.0
100.0
100.0
100.0
93.9
152.7
103.6
105.4
94.4
147.5
100.4
102.7
96.3
159.4
102.4
100.2
97.5
165.7
103.8
103.2
106.3
194.1
107.1
112.2
103.5
202.9
103.5
117.2
99.1
218.9
103.9
120.0
91.6
229.8
98.9
115.7
83.8
235.9
91.7
123.2
Wholesale trade
Monthly Labor Review • October 2009
50. Continued - Annual indexes of output per hour for selected NAICS industries
[1997=100]
NAICS
Industry
1987
1992
1997
2000
2001
2002
2003
2004
2005
2006
2007
2008
4239
424
4241
4242
4243
Miscellaneous durable goods…………………………
Nondurable goods………………………………………
Paper and paper products……………………………
Druggists' goods…………………………………………
Apparel and piece goods………………………………
89.8
91.0
85.6
70.7
86.3
108.5
101.8
96.4
88.5
96.1
100.0
100.0
100.0
100.0
100.0
114.4
105.0
100.8
85.8
108.8
117.0
105.0
104.5
84.8
115.2
124.7
105.7
116.4
89.7
122.8
119.8
110.4
119.6
100.1
125.9
134.4
113.5
130.7
105.7
131.0
133.4
113.9
141.4
112.0
140.9
120.6
111.9
136.4
109.1
141.2
117.0
111.0
144.9
101.6
139.4
120.3
110.5
132.5
108.8
145.8
4244
4245
4246
4247
4248
Grocery and related products…………………………
Farm product raw materials……………………………
Chemicals………………………………………………
Petroleum………………………………………………
Alcoholic beverages……………………………………
87.9
81.6
90.4
84.4
99.3
104.5
83.2
105.2
113.5
104.2
100.0
100.0
100.0
100.0
100.0
102.3
105.2
87.9
138.0
108.5
101.8
102.2
85.3
140.5
106.5
98.5
98.2
89.0
153.5
106.8
104.8
98.3
92.1
151.0
108.0
104.0
109.3
91.1
163.0
103.2
103.1
111.4
86.8
151.4
104.1
102.9
118.3
82.8
147.0
107.6
105.6
117.7
82.5
141.2
107.7
101.9
119.8
83.2
143.6
103.2
4249
425
4251
Miscellaneous nondurable goods……………………
Electronic markets and agents and brokers…………
Electronic markets and agents and brokers…………
111.2
64.3
64.3
98.1
84.5
84.5
100.0
100.0
100.0
114.7
120.1
120.1
111.8
110.7
110.7
106.1
109.8
109.8
109.8
104.6
104.6
120.5
98.2
98.2
123.5
87.3
87.3
120.3
92.4
92.4
115.6
100.3
100.3
107.7
97.7
97.7
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
85.2
88.1
89.6
84.8
82.8
100.0
100.0
100.0
100.0
100.0
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
134.7
115.5
146.7
129.0
125.4
142.9
116.5
150.7
130.7
128.0
144.7
113.7
148.0
119.1
116.2
147.1
109.2
442
4421
4422
443
4431
Furniture and home furnishings stores………………
Furniture stores…………………………………………
Home furnishings stores………………………………
Electronics and appliance stores………………………
Electronics and appliance stores………………………
75.2
77.3
71.5
38.0
38.0
86.3
91.2
79.5
56.4
56.4
100.0
100.0
100.0
100.0
100.0
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
161.1
369.2
369.2
156.5
149.9
165.9
414.0
414.0
165.6
154.2
180.7
469.5
469.5
166.1
152.2
184.1
544.0
544.0
444
4441
4442
445
4451
Building material and garden supply stores…………
Building material and supplies dealers………………
Lawn and garden equipment and supplies stores…
Food and beverage stores……………………………
Grocery stores…………………………………………
75.8
77.6
66.9
110.9
111.1
81.6
82.8
75.1
106.7
106.9
100.0
100.0
100.0
100.0
100.0
113.2
115.0
103.1
101.0
101.0
116.8
116.6
118.4
103.8
103.3
120.8
121.3
118.3
104.7
104.8
127.0
127.4
125.7
107.2
106.7
134.4
133.9
140.1
112.8
112.2
134.5
134.9
132.2
117.9
116.8
137.6
137.7
138.0
120.6
118.3
141.1
138.8
160.9
123.8
120.6
142.2
135.9
194.5
121.5
118.9
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
111.8
94.5
89.9
89.9
87.8
100.0
100.0
100.0
100.0
100.0
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
125.0
139.8
133.8
133.8
124.4
138.1
145.9
138.9
138.9
123.8
147.5
155.3
137.8
137.8
126.9
135.5
147.7
138.3
138.3
126.1
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
87.8
75.7
78.9
75.0
63.1
100.0
100.0
100.0
100.0
100.0
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
124.4
147.5
152.8
132.1
138.8
123.8
161.2
167.8
145.5
147.3
126.9
173.8
183.6
142.3
159.3
126.1
179.4
196.2
140.6
144.7
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
87.5
86.4
86.3
86.6
83.0
91.5
100.0
100.0
100.0
100.0
100.0
121.1
129.4
105.8
120.2
106.0
127.1
134.5
113.0
124.8
103.6
127.6
136.0
111.6
129.1
102.1
131.5
141.1
113.7
136.9
106.5
151.1
166.0
123.6
140.7
109.7
163.6
179.6
134.0
145.1
111.2
170.0
190.6
132.3
149.9
113.7
167.4
186.4
132.5
150.6
106.4
172.7
192.8
135.9
149.5
99.3
4529
453
4531
4532
4533
Other general merchandise stores……………………
Miscellaneous store retailers…………………………
Florists………………………………………………….
Office supplies, stationery and gift stores……………
Used merchandise stores………………………………
54.6
65.1
77.6
61.4
64.5
69.7
73.7
83.7
74.4
81.7
100.0
100.0
100.0
100.0
100.0
147.6
114.1
115.2
127.3
116.5
165.2
112.6
102.7
132.3
121.9
179.1
119.1
113.8
141.5
142.0
189.5
126.1
108.9
153.9
149.7
191.7
130.8
103.4
172.8
152.6
198.2
139.1
123.4
182.4
156.7
203.9
153.0
142.8
202.5
167.0
215.4
159.4
134.4
214.8
187.3
220.6
163.0
159.9
208.6
211.1
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
71.2
61.1
50.2
92.7
78.9
100.0
100.0
100.0
100.0
100.0
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
91.2
135.0
99.9
195.5
243.6
102.3
127.0
96.9
215.5
273.0
110.5
130.3
101.4
220.9
290.2
114.7
120.0
112.3
255.7
341.7
127.4
129.4
116.1
277.5
375.8
129.9
134.9
114.4
281.8
362.8
146.8
134.3
481
482111
48412
48421
491
4911
Air transportation………………………………………
78.0
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
81.3
82.3
97.8
112.5
95.2
95.2
100.0
100.0
100.0
100.0
100.0
100.0
97.7
114.3
101.9
94.8
105.5
105.5
92.5
121.9
103.2
84.0
106.3
106.3
101.7
131.9
107.0
81.6
106.4
106.4
112.1
138.5
110.7
86.2
107.8
107.8
126.3
141.4
110.7
88.6
110.0
110.0
135.9
136.3
113.3
88.5
111.2
111.2
142.9
144.2
113.3
88.9
111.3
111.3
145.4
137.7
115.3
93.2
112.0
112.0
-
492
493
4931
49311
49312
Couriers and messengers……………………………… 148.3
Warehousing and storage………………………………
Warehousing and storage………………………………
General warehousing and storage……………………
Refrigerated warehousing and storage………………
-
155.8
76.2
76.2
61.2
93.0
100.0
100.0
100.0
100.0
100.0
128.8
109.3
109.3
115.8
95.4
132.6
115.3
115.3
126.3
85.4
143.2
122.1
122.1
136.1
87.2
146.4
124.8
124.8
138.9
92.2
138.5
122.5
122.5
130.9
99.3
136.5
123.5
123.5
132.0
88.8
140.3
119.4
119.4
130.1
80.4
132.5
115.5
115.5
124.2
85.1
-
Retail trade
Transportation and warehousing
Monthly Labor Review • October 2009 125
Current Labor Statistics: Productivity Data
50. Continued - Annual indexes of output per hour for selected NAICS industries
[1997=100]
NAICS
Industry
1987
1992
Information
1997
2000
2001
2002
2003
2004
2005
2006
2007
2008
511
5111
5112
51213
515
Publishing industries, except internet………………… 64.1
Newspaper, book, and directory publishers………… 105.0
Software publishers……………………………………
10.2
Motion picture and video exhibition…………………… 90.7
Broadcasting, except internet…………………………
99.5
73.2
96.0
43.1
104.0
102.9
100.0
100.0
100.0
100.0
100.0
117.1
107.7
119.2
106.5
103.6
116.6
105.8
117.4
101.6
99.2
117.2
104.7
122.1
99.8
104.0
126.4
109.6
138.1
100.4
107.9
130.7
106.7
160.6
103.6
112.5
136.7
107.9
173.5
102.4
116.1
144.3
112.2
178.7
107.3
123.1
150.1
114.1
184.6
110.6
132.8
-
5151
5152
5171
5172
5175
Radio and television broadcasting……………………
98.1
Cable and other subscription programming………… 105.6
Wired telecommunications carriers…………………… 56.9
Wireless telecommunications carriers………………
75.6
Cable and other program distribution………………… 105.2
104.3
96.4
72.1
74.4
96.1
100.0
100.0
100.0
100.0
100.0
92.1
141.2
122.7
152.8
91.6
89.6
128.1
116.7
191.9
87.7
95.1
129.8
124.1
217.9
95.0
94.6
146.0
130.5
242.6
101.3
96.6
158.7
131.9
292.4
113.8
99.0
163.7
138.3
381.9
110.5
106.8
168.1
142.4
431.6
110.7
110.8
192.5
142.2
456.5
123.8
-
52211
Commercial banking……………………………………
73.6
83.9
100.0
104.8
102.4
106.9
111.7
117.8
119.3
122.7
123.8
-
92.7
60.3
77.0
104.8
66.9
102.2
100.0
100.0
100.0
112.3
121.8
134.9
111.1
113.5
133.3
114.6
114.0
130.3
121.1
116.3
148.5
118.2
137.7
154.5
109.8
147.1
144.2
111.4
168.9
176.2
130.1
173.8
223.0
-
82.9
90.0
90.2
95.9
98.1
87.5
100.6
97.3
112.7
96.3
100.0
100.0
100.0
100.0
100.0
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
104.2
99.9
118.3
107.8
133.4
93.1
103.7
119.8
112.3
132.9
93.6
103.2
118.9
113.1
134.1
98.8
117.4
124.5
110.0
139.1
104.5
-
89.3
75.1
92.4
92.1
100.0
100.0
100.0
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
116.0
179.2
120.7
123.8
183.4
116.1
132.8
190.6
122.3
-
-
-
100.0
100.0
100.0
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
137.8
125.8
154.1
139.7
127.3
156.8
136.0
130.0
138.9
-
Finance and insurance
Real estate and rental and leasing
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…………………………………………
111.9
106.0
95.8
104.6
100.0
100.0
106.0
93.4
93.0
94.3
106.5
96.4
113.2
102.4
101.4
107.9
109.9
106.5
97.7
102.6
103.2
122.8
-
72
721
7211
722
7221
7222
7223
7224
Accommodation and food services…………………… 93.1
Accommodation…………………………………………
85.8
Traveler accommodation………………………………
84.8
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
98.4
90.7
90.2
101.2
97.6
102.8
100.8
119.1
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
105.8
110.3
111.2
103.5
103.0
102.0
115.0
100.6
104.7
107.9
108.4
103.8
103.6
102.5
115.3
97.6
105.7
112.0
112.2
104.4
104.4
102.7
114.9
102.9
107.3
113.1
113.2
106.3
104.2
105.4
117.6
118.6
109.0
119.2
119.4
107.0
104.8
106.8
118.0
112.2
108.6
114.3
114.9
107.9
105.2
107.4
119.2
120.6
108.7
110.8
110.9
109.1
105.5
109.1
117.9
134.2
107.9
109.0
109.0
108.7
104.1
109.2
119.6
137.6
107.9
104.6
105.8
121.8
143.3
8111
81142
81211
81221
8123
81292
Automotive repair and maintenance…………………
85.9
Reupholstery and furniture repair……………………
105.3
Hair, nail, and skin care services……………………… 83.5
Funeral homes and funeral services………………… 103.7
Drycleaning and laundry services……………………
97.1
Photofinishing…………………………………………… 95.8
90.1
107.5
86.5
106.1
95.8
111.8
100.0
100.0
100.0
100.0
100.0
100.0
109.4
105.5
108.2
94.8
107.6
73.8
108.9
105.0
114.6
91.8
110.9
81.2
103.7
102.0
110.4
94.6
112.5
100.5
104.1
97.2
119.7
95.7
103.8
100.5
112.0
99.8
125.0
92.9
110.6
102.0
112.1
101.4
130.0
93.1
121.1
112.4
111.4
100.0
129.8
99.5
119.7
111.3
110.4
105.8
134.5
97.0
114.6
110.2
-
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.
51. Unemployment rates adjusted to U.S. concepts, 10 countries, seasonally adjusted
[Percent]
2007
Country
2007
2008
I
II
2008
III
IV
I
II
2009
III
IV
I
II
United States………
4.6
5.8
4.5
4.5
4.7
4.8
4.9
5.4
6.0
6.9
8.1
9.2
Canada………………
5.3
5.3
5.4
5.2
5.2
5.2
5.2
5.3
5.3
5.6
6.7
7.5
Australia……………
4.4
4.2
4.5
4.3
4.3
4.4
4.0
4.2
4.2
4.5
5.3
5.7
Japan…………………
3.9
4.0
4.0
3.8
3.8
3.9
3.9
4.1
4.1
4.1
4.5
5.3
France………………
8.1
7.5
8.6
8.2
8.1
7.7
7.2
7.4
7.5
8.0
8.7
9.3
Germany……………
8.7
7.5
9.2
8.8
8.6
8.2
7.8
7.6
7.4
7.4
7.7
8.0
Italy…………………
6.2
6.8
6.2
6.1
6.3
6.4
6.6
6.8
6.9
7.1
7.3
7.4
Netherlands…………
3.2
2.8
3.6
3.2
3.0
3.0
2.9
2.8
2.6
2.8
3.1
3.3
Sweden………………
6.2
6.2
6.3
6.1
5.8
5.8
5.7
5.8
5.9
6.5
7.4
8.2
United Kingdom……
5.4
5.7
5.5
5.4
5.3
5.2
5.3
5.4
5.9
6.3
7.0
7.8
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. For further qualifications and historical annual
data, see the BLS report International Comparisons of Annual Labor Force
Statistics, Adjusted to U.S. Concepts, 10 Countries (on the internet at
http://www.bls.gov/ilc/flscomparelf.htm).
126
Monthly Labor Review • October 2009
For monthly unemployment rates, as well as the quarterly and annual rates
published in this table, see the BLS report International Unemployment Rates
and Employment Indexes, Seasonally Adjusted (on the Internet at
http://www.bls.gov/ilc/intl_unemployment_rates_monthly.htm).
Unemployment rates may differ between the two reports mentioned, because the
former is updated annually, whereas the latter is updated monthly and reflects the
most recent revisions in source data.
52. Annual data: employment status of the working-age population, adjusted to U.S. concepts, 10 countries
[Numbers in thousands]
Employment status and country
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
139,368
15,403
9,414
67,090
25,705
39,375
23,176
7,881
4,429
28,786
142,583
15,637
9,590
66,990
25,951
39,302
23,361
8,052
4,490
28,962
143,734
15,891
9,746
66,860
26,217
39,459
23,524
8,199
4,530
29,092
144,863
16,366
9,901
66,240
26,448
39,413
23,728
8,345
4,545
29,343
146,510
16,733
10,085
66,010
26,624
39,276
24,020
8,379
4,565
29,565
147,401
16,955
10,213
65,770
26,758
39,711
24,084
8,439
4,579
29,802
149,320
17,108
10,529
65,850
26,926
40,760
24,179
8,459
4,700
30,137
151,428
17,351
10,771
65,960
27,169
41,250
24,395
8,541
4,752
30,598
153,124
17,696
11,021
66,080
27,305
41,416
24,459
8,686
4,827
30,778
154,287
17,987
11,254
65,900
27,541
41,623
24,829
8,780
4,887
31,125
67.1
65.4
64.3
62.8
55.6
57.7
47.7
61.8
62.8
62.4
67.1
65.9
64.0
62.4
56.2
56.9
47.9
62.5
62.7
62.8
67.1
66.0
64.4
62.0
56.3
56.7
48.1
63.4
63.7
62.8
66.8
66.1
64.4
61.6
56.4
56.7
48.3
64.0
63.7
62.7
66.6
67.1
64.3
60.8
56.4
56.4
48.5
64.7
63.9
62.9
66.2
67.7
64.6
60.3
56.3
56.0
49.1
64.6
63.9
62.9
66.0
67.7
64.6
60.0
56.2
56.4
49.1
64.8
63.6
63.0
66.0
67.4
65.4
60.0
56.1
57.6
48.7
64.7
64.9
63.1
66.2
67.4
65.8
60.0
56.3
58.2
48.9
65.1
65.0
63.5
66.0
67.7
66.2
60.0
56.2
58.4
48.6
65.9
65.4
63.4
66.0
67.9
66.6
59.8
56.3
58.6
49.0
66.3
65.2
63.6
Employed
United States……………………………………………… 131,463
Canada……………………………………………………
13,973
Australia……………………………………………………
8,618
Japan………………………………………………………
64,450
France……………………………………………………… 22,597
Germany…………………………………………………… 36,059
Italy…………………………………………………………
20,370
Netherlands………………………………………………
7,408
Sweden……………………………………………………
4,036
United Kingdom…………………………………………… 26,684
133,488
14,331
8,762
63,920
23,080
36,042
20,617
7,605
4,116
27,058
136,891
14,681
8,989
63,790
23,689
36,236
20,973
7,813
4,230
27,375
136,933
14,866
9,088
63,460
24,146
36,350
21,359
8,014
4,303
27,604
136,485
15,223
9,271
62,650
24,316
36,018
21,666
8,114
4,311
27,815
137,736
15,586
9,485
62,510
24,325
35,615
21,972
8,069
4,301
28,077
139,252
15,861
9,662
62,640
24,346
35,604
22,124
8,052
4,279
28,380
141,730
16,080
9,998
62,910
24,497
36,185
22,290
8,056
4,334
28,674
144,427
16,393
10,255
63,210
24,737
36,978
22,721
8,205
4,416
28,928
146,047
16,767
10,539
63,510
25,088
37,815
22,953
8,408
4,530
29,127
145,362
17,025
10,777
63,250
25,474
38,480
23,137
8,537
4,582
29,343
Civilian labor force
United States……………………………………………… 137,673
Canada……………………………………………………
15,135
Australia……………………………………………………
9,339
Japan………………………………………………………
67,240
France……………………………………………………… 25,277
Germany…………………………………………………… 39,752
23,004
Italy…………………………………………………………
Netherlands………………………………………………
7,744
Sweden……………………………………………………
4,403
United Kingdom…………………………………………… 28,474
Participation rate1
United States………………………………………………
Canada……………………………………………………
Australia……………………………………………………
Japan………………………………………………………
France………………………………………………………
Germany……………………………………………………
Italy…………………………………………………………
Netherlands………………………………………………
Sweden……………………………………………………
United Kingdom……………………………………………
Employment-population ratio 2
United States………………………………………………
Canada……………………………………………………
Australia……………………………………………………
Japan………………………………………………………
France………………………………………………………
Germany……………………………………………………
I l
Italy…………………………………………………………
Netherlands………………………………………………
Sweden……………………………………………………
United Kingdom……………………………………………
64.1
60.4
59.3
60.2
49.7
52.3
42 2
42.2
59.1
57.6
58.5
64.3
61.3
59.6
59.4
50.4
52.1
42.6
42 6
60.3
58.3
59.0
64.4
62.0
60.3
59.0
51.4
52.2
43.2
43 2
61.5
60.1
59.4
63.7
61.9
60.0
58.4
51.9
52.2
43.8
43 8
62.6
60.5
59.5
62.7
62.4
60.2
57.5
51.8
51.5
44.3
44 3
62.9
60.6
59.6
62.3
63.1
60.8
57.1
51.5
50.8
44.9
44 9
62.2
60.2
59.8
62.3
63.3
61.1
57.1
51.1
50.6
45.1
45 1
61.8
59.5
60.0
62.7
63.4
62.1
57.3
51.1
51.2
44.9
44 9
61.6
59.9
60.0
63.1
63.6
62.6
57.5
51.2
52.2
45.5
45 5
62.5
60.4
60.1
63.0
64.2
63.3
57.6
51.6
53.3
45.6
45 6
63.7
61.3
60.0
62.2
64.2
63.8
57.4
52.1
54.2
45.6
45 6
64.5
61.1
59.9
Unemployed
United States………………………………………………
Canada……………………………………………………
Australia……………………………………………………
Japan………………………………………………………
France………………………………………………………
Germany……………………………………………………
Italy…………………………………………………………
Netherlands………………………………………………
Sweden……………………………………………………
United Kingdom……………………………………………
6,210
1,162
721
2,790
2,680
3,693
2,634
337
368
1,791
5,880
1,072
652
3,170
2,625
3,333
2,559
277
313
1,728
5,692
956
602
3,200
2,262
3,065
2,388
239
260
1,587
6,801
1,026
658
3,400
2,071
3,110
2,164
186
227
1,489
8,378
1,143
630
3,590
2,132
3,396
2,062
231
234
1,528
8,774
1,147
599
3,500
2,299
3,661
2,048
310
264
1,488
8,149
1,093
551
3,130
2,412
4,107
1,960
387
300
1,423
7,591
1,028
531
2,940
2,429
4,575
1,889
402
367
1,463
7,001
958
516
2,750
2,432
4,272
1,673
336
336
1,670
7,078
929
482
2,570
2,217
3,601
1,506
278
298
1,652
8,924
962
477
2,650
2,067
3,140
1,692
243
305
1,783
4.5
7.7
7.7
4.1
10.6
9.3
11.5
4.4
8.4
6.3
4.2
7.0
6.9
4.7
10.2
8.5
11.0
3.5
7.1
6.0
4.0
6.1
6.3
4.8
8.7
7.8
10.2
3.0
5.8
5.5
4.7
6.5
6.8
5.1
7.9
7.9
9.2
2.3
5.0
5.1
5.8
7.0
6.4
5.4
8.1
8.6
8.7
2.8
5.1
5.2
6.0
6.9
5.9
5.3
8.6
9.3
8.5
3.7
5.8
5.0
5.5
6.4
5.4
4.8
9.0
10.3
8.1
4.6
6.6
4.8
5.1
6.0
5.0
4.5
9.0
11.2
7.8
4.8
7.8
4.9
4.6
5.5
4.8
4.2
9.0
10.4
6.9
3.9
7.1
5.5
4.6
5.3
4.4
3.9
8.1
8.7
6.2
3.2
6.2
5.4
5.8
5.3
4.2
4.0
7.5
7.5
6.8
2.8
6.2
5.7
Unemployment rate3
United States………………………………………………
Canada……………………………………………………
Australia……………………………………………………
Japan………………………………………………………
France………………………………………………………
Germany……………………………………………………
Italy…………………………………………………………
Netherlands………………………………………………
Sweden……………………………………………………
United Kingdom……………………………………………
report International Comparisons of Annual Labor Force Statistics, Adjusted to U.S.
Concepts, 10 Countries (on the internet at http://www.bls.gov/ilc/flscomparelf.htm).
Unemployment rates may differ from those in the BLS report International Unemployment
Rates and Employment Indexes, Seasonally Adjusted (on the Internet at
NOTE: There are breaks in series for the United States (1999, 2000, 2003, 2004), Australia http://www.bls.gov/ilc/intl_unemployment_rates_monthly.htm), because the former is
(2001), France (2003), Germany (1999, 2005), the Netherlands (2000, 2003), and Sweden updated annually, whereas the latter is updated monthly and reflects the most recent
revisions in source data.
(2005). For further qualifications and historical annual data, see the BLS
Labor force as a percent of the working-age population.
Employment as a percent of the working-age population.
3 Unemployment as a percent of the labor force.
1
2
Monthly Labor Review • October 2009 127
Current Labor Statistics: International Comparisons
53. Annual indexes of manufacturing productivity and related measures, 17 economies
[2002 = 100]
Measure and economy
1980
1990
1994
1995
1996
1997
1998
1999
2000
2001
2003
2004
2005
2006
2007
2008
Output per hour
United States………………………
Canada………………………….……
Australia…………………….………
Japan…………………………………
Korea, Rep. of………………………
Singapore……………………………
Taiwan………………………………
Belgium…………………………...…
Denmark……………………………
France………………………………
Germany………………………...……
Italy……………………………...……
Netherlands…………………...……
Norway………………………………
Spain………………………………..
Sweden……………………………..
United Kingdom……………….……
41.6
55.2
59.0
47.9
–
–
29.3
49.9
66.1
42.9
54.5
56.8
48.0
70.1
57.9
41.3
46.3
56.9
70.7
74.1
70.9
34.6
51.0
53.6
73.9
79.3
63.6
69.8
78.1
68.3
87.8
80.0
50.9
72.8
65.8
82.4
80.0
78.2
49.4
66.9
62.8
82.3
90.8
72.4
79.3
89.8
79.0
89.2
90.2
62.7
83.5
68.3
83.3
79.0
83.4
54.3
71.3
67.4
86.0
90.8
75.2
80.6
94.2
82.1
88.1
93.3
66.6
82.1
71.0
83.0
81.3
87.2
59.7
74.7
72.5
87.3
87.8
75.5
82.9
94.6
83.9
90.8
92.2
68.8
81.4
74.0
86.7
83.0
90.3
67.3
77.1
75.5
92.7
94.8
79.9
87.7
96.5
84.1
91.0
93.1
75.1
82.9
79.1
90.9
87.0
91.2
75.0
83.1
79.1
93.9
94.3
84.1
88.1
95.2
86.6
88.7
94.7
79.6
83.7
83.1
94.8
88.3
93.6
83.5
91.5
84.0
93.3
95.8
87.8
90.2
95.9
90.1
91.7
96.4
86.9
87.8
89.5
100.5
93.6
98.5
90.6
97.7
88.3
96.8
99.2
94.0
96.5
100.9
96.6
94.6
97.4
92.8
93.7
90.4
98.4
95.9
96.5
90.1
91.8
92.2
97.0
99.4
95.9
99.0
101.2
97.1
97.2
99.6
90.1
97.0
106.4
100.4
101.8
106.8
106.8
103.7
102.6
102.9
104.2
104.5
103.6
97.9
102.1
108.7
102.5
108.1
104.2
112.9
101.6
103.1
114.3
117.8
110.0
107.1
108.1
110.2
107.3
107.5
99.3
109.0
115.1
104.4
119.7
110.8
115.1
105.0
103.8
121.7
130.8
112.0
114.8
111.0
113.7
112.3
113.5
100.8
113.9
119.1
106.4
127.1
115.5
120.5
107.3
104.8
122.9
146.8
114.7
122.5
115.1
119.0
114.9
123.1
102.6
118.2
116.7
108.5
139.0
119.8
126.2
110.2
106.8
127.2
157.9
110.3
133.5
120.2
119.4
116.3
129.3
103.1
121.4
116.4
111.1
139.7
123.8
127.8
107.3
105.9
127.0
159.9
103.1
132.8
120.8
114.1
115.4
129.2
99.6
119.7
117.2
110.1
134.6
124.2
Output
United States…………………..……
Canada………………………………
Australia………………………………
Japan…………………………………
Korea, Rep. of………………………
Singapore……………………………
Taiwan………………………………
Belgium………………………………
Denmark……………………………
France………………………………
Germany……………………………
Italy……………………………………
49.6
55.2
70.3
61.9
13.4
–
30.2
67.5
77.3
69.5
81.3
71.1
66.2
68.7
81.5
98.9
41.3
51.2
60.5
87.2
85.5
81.5
94.5
88.2
75.7
73.1
85.4
97.5
54.9
68.5
71.1
87.5
90.3
80.9
90.9
91.4
79.1
76.5
84.9
101.7
61.3
75.4
75.0
89.9
94.7
83.8
90.1
95.7
82.1
77.5
87.6
105.6
65.3
77.4
78.9
90.2
90.3
83.6
88.2
95.2
87.1
82.3
89.6
108.2
68.4
80.8
83.5
94.5
97.7
87.5
92.0
96.6
92.9
86.5
92.1
102.5
63.0
80.2
86.1
96.1
98.5
91.7
93.1
97.5
96.9
93.7
91.9
102.1
76.8
90.6
92.4
96.4
99.4
94.8
94.0
97.3
103.0
103.2
96.3
107.4
89.8
104.4
99.2
100.7
102.9
99.1
100.4
101.4
97.3
99.2
95.4
101.6
92.0
92.2
91.8
100.8
103.0
100.1
102.1
101.1
101.1
99.4
101.7
105.3
105.4
102.9
105.3
98.6
97.2
101.9
100.7
97.3
106.8
101.4
101.8
111.4
115.9
117.2
115.6
102.2
98.8
102.8
104.3
98.0
107.7
103.0
101.4
117.2
123.1
128.3
123.6
102.0
99.3
105.2
107.8
97.8
113.6
102.6
100.5
121.3
133.0
143.6
132.5
104.9
103.4
104.9
115.6
101.1
116.9
101.6
103.7
125.7
142.5
152.2
146.3
107.6
107.2
105.7
122.7
103.1
113.7
95.9
105.4
121.4
146.9
145.9
144.7
107.1
105.2
103.2
123.5
98.4
Netherlands………………………… 59.3
Norway……………………………… 95.1
Spain……………………………….. 58.8
Sweden……………………………… 46.8
United Kingdom…………………… 78.5
Total hours
United States……………………… 119.4
Canada……………………………… 100.0
Australia……………………………… 119.1
Japan………………………………… 129.3
–
Korea, Rep. of………………………
Singapore…………………………… –
Taiwan……………………………… 102.9
Belgium……………………………… 135.3
Denmark…………………………… 117.0
France……………………………… 161.9
Germany…………………………… 149.3
Italy…………………………………… 125.1
Netherlands………………………… 123.6
77.0
91.4
73.7
56.1
94.9
82.0
94.1
73.2
59.7
95.6
85.1
94.6
76.0
67.5
97.1
86.3
98.4
77.9
69.7
97.9
87.5
102.7
82.9
75.1
99.6
90.5
101.9
87.9
81.3
100.3
93.8
101.8
92.9
89.0
101.3
100.1
101.3
97.0
96.3
103.6
99.9
100.5
100.1
94.1
102.2
98.9
103.3
101.2
104.9
99.7
102.3
109.2
101.9
114.5
101.9
104.3
114.1
103.1
119.8
101.7
107.9
117.5
105.0
129.2
103.4
111.3
123.6
106.0
132.2
104.0
110.6
127.3
103.8
127.6
101.0
116.5
97.2
110.0
139.6
119.2
100.5
113.0
117.9
107.8
128.2
135.3
113.0
112.7
115.1
88.8
106.7
124.7
111.1
102.4
113.3
106.3
99.5
111.8
114.5
101.8
103.9
115.9
91.8
107.4
122.0
113.0
105.7
111.2
104.5
104.3
111.3
111.7
101.6
103.7
115.7
93.4
107.7
121.0
109.3
103.7
108.9
103.4
102.9
110.7
106.4
100.7
102.9
117.7
94.9
108.0
119.9
101.7
104.8
110.6
101.9
103.1
109.4
104.9
100.1
104.0
117.4
95.2
105.9
112.5
84.0
96.5
108.8
102.3
104.5
109.0
105.8
102.5
104.5
116.6
98.9
104.1
109.1
92.0
99.0
110.1
103.4
103.7
108.0
104.2
101.5
104.1
115.1
102.7
102.9
109.0
99.1
106.8
112.4
104.0
103.7
105.4
104.0
100.5
103.6
107.6
100.8
99.5
105.3
102.0
100.5
99.6
104.0
103.7
104.4
103.1
99.9
103.0
95.1
99.0
99.9
98.6
98.7
99.3
102.7
95.8
93.3
97.5
97.3
99.4
96.8
94.6
99.8
98.7
97.5
98.3
106.5
107.9
94.5
89.6
95.8
97.1
98.7
93.9
93.6
98.1
97.7
96.3
94.1
114.6
107.7
91.9
87.3
93.7
95.0
97.0
91.6
94.3
95.6
95.9
98.6
90.6
125.2
108.2
91.1
86.9
91.3
93.9
98.6
91.3
92.6
92.2
97.1
98.8
90.2
137.9
109.6
89.5
89.8
90.8
94.9
100.0
91.7
89.0
89.3
99.6
95.7
91.9
141.5
109.0
88.6
92.2
89.4
95.6
98.9
92.4
105.5
81.1
95.1
114.5
107.3
81.4
101.3
118.2
108.4
84.5
101.3
120.3
112.8
89.0
100.1
120.1
115.0
92.8
102.2
119.8
111.0
96.4
102.4
115.4
107.1
99.7
103.8
110.6
103.4
100.5
104.3
105.4
95.1
98.8
97.0
95.7
94.9
97.6
95.7
92.0
95.8
96.8
94.2
88.1
100.7
96.8
93.0
86.3
106.2
95.4
94.6
84.0
108.6
94.3
94.8
81.3
72.2
79.8
69.8
89.4
46.5
77.5
76.4
80.9
77.7
77.6
77.1
78.0
75.0
66.2
83.8
68.0
70.9
73.4
81.7
74.1
92.4
56.4
81.0
82.7
83.2
79.3
79.9
81.2
82.5
77.0
69.2
87.4
71.7
72.1
74.6
82.9
77.5
93.2
65.7
87.0
88.2
84.7
82.5
81.4
85.1
87.0
78.4
72.1
89.5
77.3
71.9
76.5
84.9
79.6
96.4
71.4
90.9
90.8
87.9
85.4
83.8
86.7
91.1
80.5
75.3
91.6
81.4
75.1
81.2
89.3
82.9
98.8
77.7
96.1
94.2
89.2
87.6
84.4
88.0
89.4
83.9
79.7
92.3
84.6
80.7
84.8
91.2
86.2
98.6
78.2
87.9
95.9
90.4
89.8
87.1
90.0
91.7
86.7
84.2
92.1
87.2
85.4
91.3
94.2
90.0
98.0
85.2
90.2
97.6
92.0
91.6
91.8
94.7
94.1
90.9
89.0
93.5
90.6
90.6
94.8
96.8
95.7
99.3
89.0
97.3
103.7
95.9
95.9
94.2
97.6
97.2
94.8
94.4
97.2
94.9
94.7
108.0
104.0
103.9
97.8
105.5
100.6
101.0
103.4
106.8
102.3
102.2
103.8
104.0
104.1
105.0
104.5
104.9
108.9
107.7
109.4
98.8
120.6
97.9
102.1
106.2
110.9
105.5
102.8
107.4
108.4
107.5
108.7
107.3
109.6
112.5
112.4
116.3
99.6
139.7
96.8
105.7
109.4
117.2
109.4
104.1
110.8
110.0
112.6
113.9
111.0
115.9
114.7
115.8
124.2
98.5
153.9
95.0
108.9
113.3
122.9
113.7
108.4
113.0
113.1
119.5
118.9
114.2
121.7
119.6
119.9
130.7
98.3
163.8
94.3
112.4
119.3
126.1
116.8
110.3
115.5
116.7
125.2
124.8
119.7
125.7
123.2
122.5
134.2
100.1
167.1
94.7
113.8
122.8
130.5
120.3
113.0
118.5
120.5
132.2
130.8
123.3
128.8
Norway……………………………… 135.6
104.1
Spain……………………………….. 101.6
92.1
Sweden……………………………… 113.2
110.2
United Kingdom…………………… 169.8
130.4
Hourly compensation
(national currency basis)
United States……………………… 38.2
62.1
Canada……………………………… 36.3
68.3
Australia……………………………… –
61.7
Japan………………………………… 50.4
77.4
Korea, Rep. of………………………
–
23.7
Singapore…………………………… –
56.2
Taiwan……………………………… 20.4
58.6
Belgium……………………………… 40.2
69.0
Denmark…………………………… 32.6
68.6
France……………………………… 28.2
64.2
Germany…………………………… 35.8
59.7
Italy…………………………………… 19.6
61.3
Netherlands………………………… 41.1
61.9
58.5
Norway……………………………… 24.7
Spain……………………………….. 20.7
59.0
Sweden……………………………… 25.4
59.9
Kingdom……………………
24.5
60.6
128United
Monthly
Labor Review • October
2009
See notes at end of table.
augTab54a
53. Continued– Annual indexes of manufacturing productivity and related measures, 17 economies
Measure and economy
1980
1990
1994
1995
1996
1997
1998
1999
2000
2001
2003
2004
2005
2006
2007
2008
Unit labor costs
(national currency basis)
United States……………………… 92.0
Canada……………………………… 65.8
Australia……………………………… –
Japan………………………………… 105.4
Korea, Rep. of……………………… 37.0
Singapore…………………………… –
Taiwan……………………………… 69.5
Belgium……………………………… 80.6
Denmark…………………………… 49.4
France……………………………… 65.6
Germany…………………………… 65.7
Italy…………………………………… 34.5
Netherlands………………………… 85.6
Norway……………………………… 35.3
Spain……………………………….. 35.7
Sweden……………………………… 61.6
United Kingdom…………………… 52.9
109.3
96.7
83.2
109.2
68.5
110.3
109.3
93.3
86.4
101.0
85.5
78.6
90.5
66.6
73.7
117.7
83.3
109.8
96.8
87.2
114.3
94.1
115.9
121.6
98.2
85.6
107.1
97.2
86.8
95.0
74.2
92.8
108.4
84.9
107.5
98.0
93.7
110.8
104.0
113.6
122.7
96.7
87.3
106.1
100.8
87.7
93.8
78.5
93.6
107.6
87.9
105.2
100.0
95.3
106.9
110.0
116.5
121.6
97.1
94.0
107.8
102.7
92.0
93.5
79.4
97.0
112.3
88.3
103.4
97.9
96.0
106.8
106.1
117.9
120.4
94.8
90.0
104.8
98.9
94.4
95.7
82.7
98.4
108.4
90.5
102.6
98.3
95.3
108.3
103.6
115.7
119.1
95.0
92.9
100.4
99.9
94.0
96.9
89.9
97.4
106.3
96.4
102.0
96.2
97.6
105.4
93.7
96.0
114.2
97.0
93.7
99.3
99.7
95.6
96.2
91.8
95.6
100.4
97.3
102.1
93.7
96.2
99.5
94.1
92.3
110.5
95.1
92.3
97.6
98.1
93.2
94.1
94.1
96.0
97.6
96.7
104.8
98.4
99.8
102.9
98.8
106.0
112.4
98.9
96.5
98.3
98.6
96.1
97.7
97.0
97.6
105.3
97.6
101.5
103.6
102.1
91.6
98.8
97.1
98.5
100.5
102.5
97.9
98.7
106.0
101.8
95.8
102.5
96.7
100.7
96.4
106.1
106.0
86.4
102.3
88.9
95.3
98.2
100.6
98.3
95.7
108.1
99.5
93.4
104.1
89.7
98.9
97.7
107.0
112.1
81.8
106.8
86.5
92.0
98.6
103.0
97.4
91.7
110.0
96.6
94.5
107.0
87.3
100.4
95.1
108.0
118.5
80.1
104.8
82.8
88.9
98.5
103.3
98.9
88.0
110.2
95.7
102.4
109.5
82.2
101.6
94.8
108.9
122.3
77.3
103.7
85.5
84.2
99.3
105.6
100.4
85.3
112.1
96.2
107.5
112.3
85.6
101.5
96.4
114.1
126.7
78.8
104.5
91.9
85.7
101.7
114.4
104.3
87.5
119.0
100.7
112.8
118.8
91.6
103.7
Unit labor costs
(U.S. dollar basis)
United States……………………… 92.0
Canada……………………………… 88.4
Australia……………………………… –
Japan………………………………… 58.2
Korea, Rep. of……………………… 76.2
Singapore…………………………… –
Taiwan……………………………… 66.6
Belgium……………………………… 117.6
Denmark…………………………… 69.1
France……………………………… 107.8
Germany…………………………… 74.7
Italy…………………………………… 82.6
Netherlands………………………… 100.4
Norway……………………………… 57.0
Spain……………………………….. 87.6
Sweden……………………………… 141.5
United Kingdom…………………… 81.9
109.3
130.1
119.5
94.3
120.5
109.0
140.3
119.2
110.1
128.7
109.4
134.3
115.9
85.0
127.3
193.1
98.9
109.8
111.3
117.3
140.1
145.7
135.9
158.7
125.4
106.2
134.1
124.0
110.4
121.7
83.9
122.1
136.7
86.5
107.5
112.1
127.7
147.7
168.2
143.5
159.9
140.1
123.0
147.7
145.6
110.2
136.3
98.9
132.2
146.5
92.3
105.2
115.1
137.2
123.0
170.9
147.9
152.9
133.8
127.8
146.2
141.2
122.1
129.3
98.1
134.8
162.8
91.8
103.4
111.1
131.3
110.4
139.9
142.1
144.5
112.9
107.4
124.5
117.9
113.5
114.2
93.2
118.1
137.9
98.6
102.6
104.0
110.2
103.6
92.5
123.9
122.6
111.6
109.3
118.0
117.4
110.8
113.8
95.0
114.8
130.0
106.4
102.0
101.7
115.9
116.1
98.4
101.5
122.1
109.3
105.8
111.9
112.4
107.7
108.4
93.9
107.7
117.9
104.7
102.1
99.1
102.9
115.6
104.0
95.9
122.1
92.8
89.9
95.3
95.8
91.0
91.9
85.2
93.8
103.5
97.6
104.8
99.8
94.9
106.0
95.6
105.9
114.8
93.7
91.4
93.1
93.3
91.0
92.5
86.1
92.4
99.0
93.5
101.5
116.1
122.5
98.9
103.6
99.7
98.9
120.3
122.9
117.2
118.2
126.9
121.9
108.0
122.7
116.3
109.5
96.4
128.0
143.6
100.1
111.7
94.2
98.6
129.2
132.5
129.4
125.9
142.2
130.8
110.6
136.9
118.7
120.6
97.7
138.7
157.2
93.0
130.4
93.1
98.9
129.8
135.5
128.3
120.8
144.8
127.2
117.2
140.9
113.7
121.6
95.1
149.5
164.2
86.3
137.3
93.4
94.4
130.8
137.1
131.5
117.0
146.5
127.2
127.6
145.6
108.4
124.6
94.8
159.3
188.8
82.2
139.6
101.6
88.5
144.0
153.1
145.6
123.7
162.5
139.5
146.6
162.9
123.3
135.2
96.4
168.1
199.0
95.5
119.0
116.4
93.9
158.4
177.3
162.4
136.3
185.4
156.8
159.8
185.1
135.2
128.0
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.
augTAB54B
Monthly Labor Review • October 2009 129
Current Labor Statistics: Injury and Illness Data
1
54. Occupational injury and illness rates by industry, United States
Incidence rates per 100 full-time workers
Industry and type of case 2
1989
1
1990
1991
1992
1993
4
1994
4
1995
4
1996
4
1997
4
3
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
–
–
–
–
–
–
–
–
–
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
–
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:
Total cases ............................………………………….
Lost workday cases.....................................................
Lost workdays........………...........................................
Lumber and wood products:
See footnotes at end of table.
130
Monthly Labor Review • October 2009
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:
NOTE: Dash indicates data not available.
Monthly Labor Review • October 2009 131
Current Labor Statistics: Injury and Illness Data
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.
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Monthly Labor Review • October 2009
COMPENSATION AND WORKING CONDITIONS
U.S. BUREAU OF LABOR STATISTICS
The Employment Cost Index and the Impact on Medicare Reimbursements
by Jeffrey L. Schildkraut
Bureau of Labor Statistics
Originally Posted: October 26, 2009
The Employment Cost Index (ECI) is a major source of data used by the Centers for Medicare and Medicaid Services to
determine the annual adjustment to Medicare reimbursements for health care service providers. This article provides a
measurement of the impact that recent ECI data had on Medicare payment adjustments.
Since the mid-1980s, the Bureau of Labor Statistics Employment Cost Index (ECI), a measure of the rate of change in
employer costs for wages and benefits, has been a major factor in determining the annual adjustment to Medicare
reimbursements for health care service providers. ECI data are used in determining Medicare payment adjustments for six
provider categories, which, as table 1 shows, resulted in an estimated $4.8 billion reimbursement increase for 2008.
Table 1. Estimated increase in payment resulting from ECI based adjustments, 1999 and 2008
Payment provider category
CMS Price Index
Millions of dollars
1999
2008
Hospital inpatient and acute care
PPS Hospital Input Index
$2,100
$2,835
Hospital outpatient
PPS Hospital Input Index
211
465
Hospice
PPS Hospital Input Index
62
237
Skilled Nursing Facility Input Index
290
460
Home Health Input Price Index
273
393
Medicare Economic Index
310
414
$3,246
$4,804
Skilled nursing facility
Home healthcare
Physicians
Total
The U.S. Department of Health and Human Services, Centers for Medicare and Medicaid Services (CMS), administers the
Medicare program, which establishes health care coverage for approximately 45 million beneficiaries.1 CMS issues
reimbursement guidelines and, under Medicares Prospective Payment Systems (PPS), determines reimbursement rates,
subject to approval by Congress, for Medicare-covered goods and services to approximately 1.4 million health care providers
annually.2
While the ECI is one of several data sources used to determine reimbursement rates, CMS does not report to what extent the
ECI ultimately affects the annual reimbursement rate adjustment. In the October 2002 issue of the Monthly Labor Review,
Bureau economists Albert E. Schwenk and William J. Wiatrowski estimated the ECIs impact on the annual adjustment to
Medicare reimbursement rates for 1999 and discussed the relationship between the two programs.3 This article is an update
of the Schwenk-Wiatrowski article, providing a measurement of the impact that recent ECI data have on Medicare payment
adjustments.
ECI data are used in the process to determine the allowable increase in payments in 6 of 16 Medicare payment provider
categories under Medicares Prospective Payment Systems (PPS). The six categories are hospital inpatient and acute care;
hospital outpatient; skilled nursing facilities; hospice; home health care organizations; and physicians. In total, these 6
components accounted for about 59 percent of Medicare expenditures.4
To estimate the impact of the ECI on the resulting CMS reimbursement rate adjustments for each provider category, start
with the CMS projected reimbursement levels, and then multiply the ECI related price index component weights by the
calculated 12-month percent change. Then sum these changes over all components to get the percent change in Medicare
payments due to the ECI. (For more information on the use of ECI components, see “The Employment Cost Index and the
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U.S. BUREAU OF LABOR STATISTICS
Impact on Medicare Reimbursements.”5 ) The percent change in Medicare payments due to the ECI is then multiplied by the
annual CMS Medicare reimbursement estimate for that payment provider category to determine the increase resulting from
the change in the ECI. For example, the estimated ECI impact on the hospital impatient and acute care category is based on
CMS Medicare reimbursement level of $126 billion6; applying the ECI related PPS Hospital Input Index weight of 69.7
percent to the various December 2008 ECI 12-month component changes determines a total payment provider category
change of 2.25 percent. Overall, the total estimated increase in hospital inpatient and acute care payments based on the
December 2008 ECI is approximately $2.8 billion (2.25 percent of $126 billion).7
The PPS designates the level of payment for Medicare-covered services on the basis of the diagnosis and geographic
location of care. Changes in reimbursement rates are primarily based on CMS estimates of changes in expenditure levels for
a set of goods and services, also known as a “market basket.” Increases are based on input price indexes for each
component of the market basket and are developed to estimate cost changes for various Medicare provider categories. CMS
price indexes typically encompass numerous inputs, including changes in compensation costs for various industries, such as
hospitals. ECI data are used for many of these compensation changes, including, for example, the following:
• ECI data account for about 70 percent of the PPS Hospital Price Index, which is used to determine allowable
increases in payments for hospital charges. Thus, a 1-percent increase in the ECI would result in a 0.7-percent
increase in hospital payments. In 2007, Medicare hospital inpatient and acute care payment reimbursements totaled
nearly $126 billion.8 The estimated 2.25-percent change in Medicare payments due to ECI (based on the December
2008 ECI) would result in over $2.8 billion in increases in annual hospital payment reimbursements.
• ECI data account for about 68 percent of the Skilled Nursing Facility Input Index, which is used to determine allowable
increases in payments for charges for skilled nursing facilities. Medicare reimbursed skilled nursing facilities more than
$22 billion in skilled nursing charges in 2007. The estimated 2.02-percent change in Medicare payments due to ECI
(based on December 2008 ECI) would result in a $460 million increase in annual skilled nursing payment
reimbursements.
• ECI data account for about 85 percent of the Home Health Input Price Index, which is used to determine allowable
increases in reimbursements for charges for home health care. Medicare reimbursed home health care providers
more than $15 billion in home health care charges in 2007. The estimated 2.50-percent change in Medicare payments
due to ECI (based on December 2008 ECI) would result in a $393 million increase in annual home health care
payment reimbursements.
• ECI data account for over 28 percent of the Medicare Economic Index, which is used to determine allowable increases
in payments for physician services. Medicare reimbursed physicians more than $58 billion in physician services in
2007. The estimated 0.71-percent change in Medicare payments due to ECI (based on December 2008 ECI) would
result in a $414 million increase in physician payment reimbursements.
Table 1 indicates that the approximate annual adjustment in Medicare reimbursements in 2008 due to increases in the ECI
totaled about $4.8 billion. Annual adjustments attributable to ECI increases in 1999 Medicare payments totaled $3.2 billion.
Estimated payments in hospital inpatient and acute care attributable to the ECI increased from $2.1 billion in 1999 to over
$2.8 billion in 2008, based on December 2008 ECI data. Note that estimates of the annual ECI impact can vary from year to
year. For example, using December 2007 ECI data, the hospital inpatient and acute care category would have estimated
reimbursement increases of approximately $3.0 billion.
The National Compensation Survey (NCS) provides annual updates on the impact of the ECI on Medicare reimbursements.9
CMS reimbursement estimates are based on the Presidents budget and current CMS market basket components and
weights. CMS may make adjustments to components in the six input indexes that could alter the ECI overall impact on one or
more payment provider categories. NCS will provide additional details on the annual ECI impact summary to identify
important changes resulting from market basket updates.
Jeffrey L. Schildkraut
Economist, Division of Compensation and Data Estimation, Office of Compensation and Working Conditions, Bureau of Labor
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COMPENSATION AND WORKING CONDITIONS
U.S. BUREAU OF LABOR STATISTICS
Statistics.
Telephone: (202) 691-6274; E-mail: Schildkraut_J@bls.gov.
Notes
1 See The Henry J. Kaiser Family Foundation, statehealthfacts.org, on the Internet at http://www.statehealthfacts.org/comparemaptable.jsp?
ind=290&cat=6&sub=74&yr=63&typ=1&sort=a.
2 Medicare Payment Advisory Commission, A Data Book: Healthcare Spending and the Medicare Program, June 2008, chart 1-14, p. 16.
3 Albert E. Schwenk and William J. Wiatrowski, “Using the Employment Cost Index to adjust Medicare payments,” Monthly Labor Review,
October 2002, pp. 20-27, on the Internet at http://www.bls.gov/opub/mlr/2002/10/art3full.pdf.
4 See Medicare Payment Advisory Commission, A Data Book: Healthcare Spending and the Medicare Program, June 2008, chart 1-9, p. 11.
An estimate of 59 percent is determined by dividing the total 2007 CMS Medicare reimbursements of all 6 categories by the total of all
Medicare spending in 2007, and then multiplying the result by 100 to express in terms of a percentage. The total for 2007 CMS Medicare
reimbursements for the 6 categories is $254 billion; total 2007 Medicare spending is $428 Billion; multiplied by 100 equals 59 percent. Note
that the total Medicare spending in 2007 ($428 Billion) includes about $51 Billion (or 12 percent of total) in reimbursements for Medicare Part
D, which is a prescription drug plan. For more information, see the Medicare Web site at http://www.medicare.gov/pdphome.asp.
5 “The Employment Cost Index and the Impact on Medicare Reimbursements” is available on the BLS Web site at http://www.bls.gov/ncs/ect/.
6 Centers for Medicare and Medicaid Services, Office of the Actuary, unpublished reimbursement estimates for 2007.
7 ECI data can be found on the Employment Cost Trends page of the BLS Web site at http://www.bls.gov/ncs/ect/.
8 Centers for Medicare and Medicaid Services, Office of the Actuary, unpublished reimbursement estimates for 2007.
9 “The Employment Cost Index and the Impact on Medicare Reimbursements” was first published in 2008. The latest version is available on
the BLS Web site at http://www.bls.gov/ncs/ect/.
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