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MONTHLY LABOR
REVIEW
Volume 132, Number 5
May 2009
International comparisons of hours worked: an assessment of the statistics
A study of 13 countries reveals inherent biases in data sources used to measure hours
worked; thus, these data remain useful for broad, but not detailed, comparisons
Susan E. Fleck
3
Job openings and hires decline in 2008
32
Business employment dynamics: annual tabulations
45
Comparing Workers’ Compensation claims with establishments’ responses to the SOII
57
Downward trends in job openings, hires, and quits, and upward trends in layoffs and discharges
characterize labor demand during 2008
Katherine Klemmer
Annual data, released for the first time, allow for comparisons between BED statistics and
statistics from other agencies
Akbar Sadeghi, James R. Spletzer, and David M. Talan
Comparing elements of the WC database with data from the SOII is a useful way to
determine which types of injuries and illnesses the SOII is most likely to undercount
Nicole Nestoriak and Brooks Pierce
Departments
Labor month in review
Book review
Précis
Current labor statistics
2
65
66
67
Editor-in-Chief: Michael D. Levi Executive Editor: William Parks II Managing Editor: Terry Schau Editors: Brian I. Baker,
Richard M. Devens, Casey P. Homan Book Review Editor: James Titkemeyer Design and Layout: Catherine D. Bowman, Edith W.
Peters Cover Design: Keith Tapscott Contributor: David A. Penn
Labor Month In Review
The May Review
Our lead article this month assesses
the sources and quality of international statistics on hours worked. As with
any effort at international comparison,
much work has to be done to standardize concepts, measures, and sources as
much as possible for the comparisons
to be meaningful. As the author Susan
E. Fleck notes, “Measuring and comparing how many hours people spend
at work across countries is not an exact
science, despite recent improvements
in methodology and data coverage.”
But, in an era of ever-increasing global
markets and trade, it is an invaluable
exercise to undertake. The article describes and contrasts data for 13 developed economies as far back as 1980.
It particularly emphasizes differences
in hours-worked data collected from
surveys of businesses and households
and those gathered from administrative sources.
2008 was not a good year overall
for employment trends in the U.S. labor market. As Katherine Klemmer
discusses in her article, job openings
and hires both declined in 2008. This
downward trend, coupled with an upward trend in layoffs and discharges,
should not be surprising in light of the
rise in unemployment and decline in
employment that have characterized
the recession which began at the end
of 2007. The author summarizes developments in openings and hires for
the nation as a whole, for regions, and
by industry.
The Bureau’s Business Employment
Dynamics (BED) program has become
an increasingly watched data source for
quarterly insight on the U.S. economy.
Three BLS economists—Akbar Sadeghi, James R. Spletzer, and David M.
Talan—present new time series from
the BED program of annual gross job
Monthly Labor Review • May 2009
gains and gross job losses. Their article
provides a detailed explanation of how
these new series have been created and
the unique value added by their availability. They present comparisons of
the new series with the quarterly BED
statistics and with similar statistics
from the U.S. Census Bureau.
There has been a great deal of research and discussion about how workplace injuries and illnesses are measured
and whether the current program conducted by the Bureau of Labor Statistics, which collects and tabulates employer reports, is fully accurate. Nicole
Nestoriak and Brooks Pierce describe a
recent study that compared case records
from the BLS program with information from Workers’ Compensation
claims databases. They present some
additional findings by analyzing a subset of the data used in the recent study.
Their goal is to extend the aggregate
results reported by the other authors in
order to shed light on the types of cases
the BLS survey may undercount.
BLS news releases
Among the various methods of data
dissemination, the news release format has been used by BLS for a very
long time. The national office of BLS
routinely publishes about 170 or so
news releases per year, with many
others issued by the regional offices.
Some are produced monthly, some
quarterly, some annually, and some
irregularly. Releases typically contain
data published for the first time. They
include descriptive and analytical text
about the figures, technical information about data sources, methods, and
so on, and tables containing data at
detailed levels, cross-tabulated by different variables.
It has been quite some time since
the Bureau assessed how it uses the
news release format and how effective
the format is. Starting in the summer
of 2008, BLS began such as assessment. It elicited feedback from interested parties in a number of ways:
conducting focus groups with journalists, requesting comments from the
BLS Data Users Advisory Committee, setting up an evaluation by BLS
cognitive psychologists who assist the
agency evaluating the clarity of some
of its public communications, and
having internal reviews conducted by
the Bureau’s program and publications offices.
As a result of this review process,
BLS has decided to produce news
releases that focus with greater clarity on the most important analytical
points and succinctly provide recent
and historical context relevant to each
analytical story. Starting in the summer
of 2009, BLS will begin to introduce
these changes to the news releases that
contain data designated as Principal
Federal Economic Indicators (PFEIs).
The monthly Employment Situation
and Consumer Price Index releases are
two examples of such news releases.
The formats of the text sections of the
news releases also will become more
standardized. There will be no change
in the data published, only in the textual discussion of the data.
In the future, BLS intends to expand
the review process to include its other
(non-PFEI) news releases and, as a result, may implement similar changes to
those releases. Timelines for that phase
of the news release review process have
not yet been established.
Information on the news release review process can be found on the BLS
Web site at www.bls.gov/bls/changes_to_text_sections_of_nrs.htm. This
page will be updated as more information about the process becomes
available.
Comparisons of Hours Worked
International comparisons of hours
worked: an assessment of the statistics
A study of 13 countries reveals that measures of hours worked
based on administrative sources are relatively low while measures
based on establishment and labor force surveys are relatively high;
thus, although ever improving, these measures cannot yet be taken
at face value and are useful only for broad comparisons
Susan E. Fleck
Susan E. Fleck is Chief, Division of Major Sector Productivity, Office of Productivity
and Technology, Bureau of
Labor Statistics. This article
was prepared when she was
a supervisor in the Division
of International Labor Comparisons. E-mail: fleck.susan@
bls.gov
P
ublic commentators, the press, and
governments are interested in the
hours people work. Work hours underpin productivity measures. The number
of hours individuals work stimulates debate
on the quality of life in an international
context: do some societies live to work
while others work to live? The differences
in hours worked between countries fuels discussion of economic growth, employment,
and unemployment. Any comparative measure between countries, however, depends on
a standardization of concepts, sources, and
methods. Measuring and comparing how
many hours people spend at work across
countries is not an exact science, despite
recent improvements in methodology and
data coverage.
The recommendation from the International Labor Organization (ILO) is to
use actual hours worked, including annual
hours actually worked, as the basis for international comparisons. The recommendation to include annual hours actually
worked was part of an updated ILO resolution regarding the measurement of working
time that was adopted at the International
Conference of Labor Statisticians held in
the fall of 2008. Background research on
working time and hours worked carried out
by international statistical organizations
and national statistical agencies to prepare for
the conference has contributed to a rich debate
on hours worked.
This article benefits from the recent exchange
of ideas leading up to the 2008 Conference and
looks at two data sets on hours worked. The
better known of the two is the Organization
for Economic Cooperation and Development
(OECD) data set on average annual hours actually worked, for all employed persons, for 30
countries, published in the annual OECD Employment Outlook.1 The second data set is the
Bureau of Labor Statistics (BLS) underlying
hours and employment data in the annual report, “Gross Domestic Product per Employed
Person,” which presents an international comparison of gross domestic product (GDP) per
hour worked for 13 countries. The OECD data
set provides an explicit measure of average annual hours worked, while the BLS data set publishes total employment and hours, from which
a series for average annual hours worked can be
derived. Both hours-worked data series complement output and productivity data published by
the respective organizations.
Whereas data users tend to look at the
number of average hours worked per year
when making comparisons between countries,
both BLS and OECD caution that such comparisons are prone to error and that the data
series best describe changes over time. This
Monthly Labor Review • May 2009
Comparisons of Hours Worked
article provides some context and explanations for the
data user on why these comparisons are fraught with difficulty. It considers how concepts, sources, and methods
used to construct hours-worked data series affect analyses of data levels and trends. The differences between the
BLS and OECD data sets discussed here highlight a major
theme of the article, namely, that the estimate of average annual hours actually worked per employed person is
just that—an estimate—and it may vary with the sources
and methods used. Nonetheless, trends are similar. Finally,
the article explains why small differences in hours worked
between countries have little meaning, whereas large differences are more likely to be meaningful.
The countries studied are the United States, Canada,
Japan, South Korea, and nine European countries: Belgium, Denmark, France, Germany, the Netherlands, Norway, Spain, Sweden, and the United Kingdom. Both BLS
and OECD data sets depend on a variety of data sources
and concepts used to measure and estimate hours worked.
The 13 countries considered here represent a wide variety of developed economies. Additional data used in this
article come from special studies by the OECD and the
ILO, as well as from studies by researchers and national
statistical agencies. When time series are used, data begin
with 1980 where available. For both data sets, pre-1991
data for Germany are estimated.
The analysis begins with an explanation of various concepts and sources underpinning hours worked and of their
uses and limitations in preparing data series on average annual hours actually worked. This explanation establishes the
framework for discussing methods of estimation of average
annual hours actually worked and for describing the BLS
and OECD data sets, including breaks in series. The levels
and trends for each country are compared with the use of a
rank von Neumann test, to show how trends can be similar,
although levels differ. With this background, the historic
trends in the two data series are compared over a quartercentury whenever data are available. Furthermore, changes
in the labor market that influence hours worked, such as
an expansion of part-time and women’s employment, also
will be examined. A short overview of changes in laws and
norms helps put the trends in context. Comparisons are
made between sources for the same country and between
countries using similar methodologies. Comparisons between Japan and the United States and between Norway
and Sweden highlight discrepancies in levels due to differences in sources and methods. The comparisons are intended to provide the data user with a better understanding
of the interplay among concepts, sources, and methods and
how they affect the comparisons.
Monthly Labor Review • May 2009
There are a number of explanatory factors underlying
the differences in hours worked across countries, such as
institutional, legal, and policy differences. Only institutional and legal factors specific to the regulation of normal
hours of work will be addressed in this article; the other
factors are beyond the scope of the analysis. Furthermore,
with the recent passage of the revised ILO resolution on
working time, the concepts underlying hours worked have
expanded to provide more detail. This study was prepared
before the 2008 ILO resolution on working time was finalized and took effect; thus, the concepts presented are
based on the original ILO resolution.
Hours of work: concepts and sources
Concepts. Resolutions passed by the tripartite meeting
of the International Conference of Labor Statisticians
establish recommendations for countries to develop data
with enough similarities to be suitable for international
comparisons. The October 1962 ILO “Resolution concerning statistics of hours of work” provides guidance on
concepts and measurement relating to hours of work and
on a basic framework for collecting and analyzing data on
hours. The resolution establishes three concepts of hours
of work: “normal hours of work,” “hours actually worked,”
and “hours paid.”2 Another concept often used in data collection is “usual hours of work.” Note that “hours worked”
refers to measured, or actual, hours, whereas “hours of
work” refers to scheduled, or planned, hours.
The box on page 5 lists the components of working
time, based on the 1962 resolution. Items 1 through 6
comprise one or more of the hours concepts mentioned in
this article. Items 7 and 8 are generally accepted as hours
not at work.
Normal hours of work are the maximum number of hours
worked beyond which an employer must pay an overtime
premium. This concept is partially addressed in item 1 in
the box. Normal hours may be fixed by legislation or established by collective-bargaining agreements, depending
on the country, industry, and occupation. The vast majority
of countries in the world have a normal workweek of 40 or
more hours. In the United States, the normal workweek
is 40 hours. In Europe, the normal workweek is usually
less than 40 hours and ranges widely by industry or occupation both within and between countries. For example,
earlier this decade, the normal workweek was 29 hours
for Volkswagen production workers in Germany, but now
it is 33 hours; in France, the normal workweek has been
35 hours for almost all employees for the past 10 years;
and in the Netherlands, the normal workweek can be as
Components of working time
1. Hours actually worked during normal periods of
work.
2. Time worked in addition to hours worked during normal periods of work and generally paid at higher
rates than normal rates (overtime).
chinery, and accidents, or time spent at the workplace
during which no work is done, but for which payment is
made under a guaranteed employment contract.
5. Time corresponding to short rest periods at the
workplace, including tea and coffee breaks.
3. Time spent at the workplace on work such as
preparation of the workplace, repairs and maintenance,
preparation and cleaning of tools, and preparation of
receipts, timesheets, and reports.
6. Hours paid for, but not worked, such as paid annual leave, paid public holidays, and paid sick leave.
4. Time spent at the workplace waiting or standing
by for such reasons as lack of work, breakdown of ma-
8. Time spent on travel from home to work and from
work to home.
many as 60 hours for some workers for short periods.3
Some people call normal hours of work “hypothetical,” in
that they measure the ideal work schedule, not the observable work schedule. On a practical level, employers often
arrange work schedules to keep employees’ hours at or
below the normal-hour threshold, in order to avoid paying overtime wage rates. Data sources for normal hours
of work are derived from the aforementioned legislation
and collective-bargaining agreements and cover predominantly employees.
The concept of hours actually worked encompasses all
hours spent working, including overtime hours and excluding absences; these are items 1 through 5 in the box.4 The
concept excludes items 6 through 8—that is, hours paid
but not worked, such as paid leave, paid public holidays,
and paid sick leave, as well as meal breaks and commuting time. As part-time work has become more prevalent,
workers’ hours are less than the normal workweek, but
are still counted in item 1. Although not explicitly stated
in the resolution, hours actually worked are commonly
counted as both paid and unpaid hours at work. Data on
hours actually worked are collected from household-based
surveys, such as labor force surveys and time-use surveys;
establishment surveys report data using other hours concepts, which can be adjusted to an actual-hours concept.
Hours actually worked usually are reported on a person
basis (but can be adjusted to a jobs basis), account for the
total hours individuals work on all jobs in a given reference period, and generally include both persons working
7. Meal breaks.
part time and persons working full time. Yearly estimates
usually are calculated to reflect a full-year worker (that is,
someone who works throughout the year).
The hours paid concept is described in the 1962 resolution,
but is not identified as a concept amenable to international
comparison. Hours paid generally include items 1 through
5 in the accompanying box and exclude unpaid overtime.
Hours paid also include item 6: holidays, vacation, and sick
leave. Depending on the terms of the employment contract,
items 7 and 8—meal breaks and commuting time—also
may be included in the hours-paid concept. Wide variations across countries persist regarding how workers are
paid for holidays and nonwork time, particularly sick leave.
These differences are the primary reason that international
comparisons of hours paid are not made.
Usual hours of work are not addressed in the 1962 ILO
resolution on hours, but are included in the 2008 resolution. Usual hours of work are hours that are typical of a
certain length of time, such as a day, a week, or a month.5
The concept encompasses the same components as hours
actually worked, but refers only to regularly scheduled
hours. Data on usual hours of work commonly refer to
the usual work schedule during a week or month and are
most commonly collected from household surveys. Some
establishment surveys collect data on contractual hours,
which are usual hours of work expected to be fulfilled under individual employment agreements. These contractual
hours are analogous to normal hours under collective-bargaining agreements.6
Monthly Labor Review • May 2009
Comparisons of Hours Worked
Sources of hours data. A number of sources are used to
capture the hours concepts described in the previous section. For each hours concept, certain sources of data are
preferred over others because they provide a better measure of the concept. In the context of creating a comparable
international measure of average annual hours worked,
each source has its benefits and drawbacks. The chief issues to address in determining the best concept and source
of hours to use in estimating average annual hours worked
are (1) how well the data collected capture the concept of
hours actually worked and (2) what additional data sources have to be used to create the annual estimate, because
of either measurement issues or coverage issues. The main
concern is whether the source covers detailed industries,
all types of workers, and the total economy.
1. Administrative data sources. Data on normal hours of
work are available through administrative data sources.
The primary purpose of such data often is to manage
programs, not to collect statistics. Administrative data are
collected by social programs, ministries, or local, regional,
and national governments. In addition to covering legislation or collective-bargaining agreements on normal hours,
administrative data may cover the use of public services
(such as registering in employment offices or being paid
sick leave), labor code enforcement, or tax collection. Administrative data also provide information on hours not
worked, particularly in countries where paid leave is centrally administered, such as Sweden and Norway.
The advantage of an administrative source for data on
normal hours is its potentially wide population coverage
in those countries with large numbers of employees working under collective-bargaining agreements. European
countries have high rates of union coverage and, in some
cases, have passed legislation that extends the benefits
agreed upon in collective-bargaining contracts to workers who are not union members.7 These countries collect
large amounts of data in administrative databases because
they have active social programs and wide-ranging labor
regulations. Still, administrative data from collective-bargaining agreements, though a common source of data on
normal hours for different occupations, industries, and regions, are not the only source: establishment surveys, such
as those conducted in France, also may provide information on normal hours of work.
Of course, there are limitations on administrative data
as a source of information on hours. First, the wide range
of administrative data on job or labor conditions that
provides information on normal hours may exclude some
workers, such as part-time workers, workers not covered
Monthly Labor Review • May 2009
by collective-bargaining agreements, and the self-employed. For example, in France, small and medium-sized
businesses together account for one-fourth of employees,
but those employees are not subject to the general limitation of a normal 1,600-hour work year. Thus, if normal
hours were to be the basis of an annual measure of hours
actually worked for all employed, the additional hours
worked by employees in small and medium-sized businesses would be excluded.8 Also, administrative data are
collected by job and not by person, so additional information would be required to account for multiple jobholders
if hours worked were to be estimated by person.
Because of limitations on concepts and data sources
of normal hours, estimates of annual hours worked based
on these sources are likely to be undercounted. Normal
hours do not provide a total-economy measure of hours
worked without adjustments that expand coverage to
all employed persons and all industries. The nature of
the data sources—collective-bargaining agreements and
other sources of regulated normal hours—guarantees
that overtime hours worked are not counted. Thus, estimates of hours actually worked will be biased downwards. As an example, some countries covered in the BLS
and OECD data sets base their measure of average annual
hours worked on normal hours and deduct all paid annual
leave and allowable sick leave. This estimation technique
undercounts hours.
2. Survey-based data. Survey-based data have an advantage over administrative data covering normal hours
of work, in that surveys provide reports of hours actually
worked by individuals and count persons employed or jobs.
Data are reported from either individuals or businesses on
their actual labor market behavior, not on their expected
behavior. Labor force surveys collect data on weekly or
daily actual or usual hours worked (or both). Establishment surveys generally collect either weekly or monthly
hours data on an hours-paid concept. Advantages and
limitations exist with the data provided by each of these
types of surveys.
a. Household surveys. Data on actual or usual hours
worked are collected from household surveys such as labor
force surveys and time-use surveys, the latter being more
irregular and with a smaller sample size. Data on hours
actually worked and usual hours of work are reported on
an employed-person basis and account for the total hours
individuals, including both full- and part-time workers,
work on all jobs in the reference period.
The two major advantages of labor force survey data
are the ability to report hours actually worked, including
paid and unpaid overtime, and the broad coverage of the
employed. The concept of hours actually worked captures
the variability and irregularity of the number of hours a
person works and does not work in a given week or other
period, and it can account for shortened workweeks, overtime hours, holidays, sick leave, and vacation. Of course,
the concept of usual hours of work also captures paid and
unpaid overtime, as long as the overtime hours are a regular part of the work schedule. The problem is that usual
hours of work do not fluctuate as much as hours actually
worked and do not capture that variability, because they
exclude irregular hours not worked, irregular overtime,
and short-time work (temporary reductions in the regular
workweek). Regarding coverage of the employed, the nature of a labor force survey is to reach into all households
with all types of workers. Thus, labor force surveys provide
coverage of the self-employed and unpaid family workers,
both of whom are excluded in data on normal hours of
work.
There are a couple of limitations, however, to using labor
force survey data for comparisons of hours worked. First,
data collection that is not ongoing (that is, discontinuous
data collection) can affect the accuracy of data on both
hours actually worked and hours not worked. Because of
this problem, European Union member countries recently
have moved toward ongoing data collection; hence, their
estimates of average annual hours actually worked are
based on 52 weeks of the year. But most other developed
countries collect data on a discontinuous, albeit regular,
basis. By its nature, discontinuous data collection, such as
one week a month or one week a quarter, does not account
for unexpected irregularities in hours worked and hours
not worked—for example, hours not worked on holidays,
in bad weather, or because of school closings. Adjustments
are made to account for hours not worked, but these adjustments themselves are variable across countries, within
a country, and across years, as well as by region or even occupation and industry. It is likely that, as labor force surveys in the European Union and elsewhere expand coverage to all months of the year and all weeks of a month, and
as questions and data collection on hours actually worked
and hours not worked become more precise, some of these
inconsistencies will diminish.
A second common concern regarding labor force surveys
is the issue of reliability. Labor force surveys depend on
respondent recall and proxy responses; accordingly, survey
respondents often do not reliably report their own hours
worked and hours not worked, because they are relying on
faulty memory, and neither do proxy respondents report
such hours reliably, because they lack information about
the intended respondent. In essence, in a labor force survey
hours actually worked are not observed, but are reported,
and people can forget the hours they actually worked.
Nonetheless, past concerns over respondent error in
labor force surveys seem to be less of a problem than
previously thought.9 The advent of time-use surveys has
led to research that sheds light on comparisons between
short-term recall of hours worked and longer term recall
used in household surveys. For example, comparisons between the 1998 Canadian Labor Force Survey and Time
Use Survey found that, overall, average numbers of hours
worked are similar between the two surveys.10 One U.S.
study showed that time-use survey responses accurately
reflect hours worked when the data are collected in or
near the reference period, but that hours are reported at a
level 5 percent lower when data are collected during later
weeks.11 Concerns remain over proxy responses.
Finally, a more theoretical concern regarding the use of
hours data from labor force surveys in productivity comparisons is the need to convert the data from a national
economy concept to a domestic economy concept consistent with national accounts measures.12 In small countries,
such as Belgium, where residents cross national borders
to work, employment data from the household, or labor
force, survey may not be a corresponding measure of those
employed in a country’s production of output, thus affecting the corresponding hours measure.
b. Establishment surveys. Data on hours paid are collected from establishment surveys. The purpose of such
surveys is to collect data on hours, earnings, number of
employees, compensation, and other labor characteristics
of firms and their workers. Establishment surveys have at
least three advantages. First, the data are deemed reliable,
because they are extracted from payroll information and
are considered more precise than data based on individual
recall.13 Second, industry coverage and classification also
are deemed reliable. This is because establishment survey
data often are collected at a detailed industry level, generally complement national accounts output data, and thus
also complement industry productivity analysis. Finally, in
some countries, such as the United States, establishment
survey sample frames are much larger and cover far more
workers than labor force surveys can cover.
The limitations on establishment survey data for hours
measures are at least fourfold. First, the concept of hours
paid typically does not report hours actually worked.
Rather, it includes hours paid and worked, such as the
regular workweek and paid overtime; and hours paid, but
Monthly Labor Review • May 2009
Comparisons of Hours Worked
not worked, such as paid vacation, sick leave, and maternity leave. Second, both the practice and reporting of
the collection of data on hours paid differ widely across
countries, making comparisons difficult. In some countries, such as Norway, benefits for sick leave or maternity
leave are paid by a government or a union, so the hourspaid data from establishment survey sources exclude these
benefits; in other countries, such as the United States, paid
sick leave is a benefit offered by many employers, so it is
counted as hours paid. It is difficult to account for these
differences in creating comparative measures of hours
paid between countries. Third, survey coverage is limited
to employees, and only to certain types of employees. Historically, establishment survey data have been collected on
production workers and have excluded supervisory, temporary, or part-time employees. Only in the recent past
have establishment surveys expanded their coverage to
include supervisory employees. Needless to say, data on
self-employed and unpaid family workers must be found
to complement establishment survey data on employees.
Fourth, in establishment surveys, industry coverage, although complementary to data found in national accounts,
may not be representative of all industries. The focus of
data collection by establishment surveys always has been
the manufacturing sector, although countries have been
expanding coverage to include the service sector.
Without adjustment, hours-paid data from establishment surveys do not provide a total-economy measure of
hours actually worked that covers all employed persons in
all industries. Depending on the adjustment, the estimate
may over- or underestimate hours actually worked: on the
one hand, hours-paid data that are not adjusted for paid
leave will overstate the estimate of hours actually worked;
on the other hand, hours-paid data that are adjusted to
the hours-worked concept by means of administrative or
legislative leave data may understate hours worked if the
adjustment assumes that employees take all leave that is
offered them.
These concepts and sources of hours worked are the
building blocks for the analysis in the next section, which
addresses issues related to constructing a series of average
annual hours actually worked and examines two data sets
from the BLS and the OECD.
tive quality-of-life indicator, they are best measured over
a year, to reflect vacation time and other absences from
work. Second, demand has grown for measures of annual
hours in order to estimate an economy’s total productivity.
Average annual hours actually worked per capita provides
a broad measure of labor utilization, broken down into
three components in a recent OECD study: the “intensive,”
or individual, component of average annual hours actually
worked per employed person, the “extensive,” or economywide, component of the employment-population ratio,
and a demographic factor.14 Unless otherwise stated, the
rest of this article considers instead the narrower, “intensive,” measure of average annual hours actually worked per
employed person—that is, the hours of labor that workers
actually put in on the job.
In 2003, the 17th general report by the International
Conference of Labor Statisticians highlighted the need to
revise existing international recommendations on “hours
actually worked during short as well as longer reference
periods” and suggested that such measures “be broadened to cover all persons in employment, including the
self-employed, by extending the content of each of the
defining categories of working time to include all work
situations, such as irregular, seasonal, work at home, and
unpaid work.”15 Furthermore, the report suggests “the development of an international definition of annual hours
of work that allows for alternative estimation procedures
that take into account variations in the type and range of
national statistics of working time.”16
This section looks at the methodologies used to prepare
measures of average annual hours actually worked per employed person and the data sets underlying the published
measures. The analysis begins with an overview of the
concepts and sources used in the BLS and OECD data sets,
followed by a comparison of differences in the estimates
of average annual hours actually worked per employed
person in each data set, for each of the 13 countries examined. A statistical test comparing trends between the two
data sets shows that the trends diverge for only 3 of the
13 countries examined: the United States, France, and the
Netherlands. The analysis undertaken supports the perspective of the statistical organizations that hours data are
best analyzed as trends and not as levels.
Estimating and comparing hours actually worked
Data sources and country methodology. As countries move
toward adopting a national accounts framework to measure labor input, or hours worked, concepts across countries
are becoming more consistent. It is the source of data and
the methodology used, rather than the concepts employed,
that are at the heart of the comparability issue.
In recent years, statistical reporting and measurement
have focused on how to create comparable series of average annual hours actually worked. The reasons are twofold. First, if hours worked are to be used as a compara
Monthly Labor Review • May 2009
As Gerard Ypma and Bart van Ark attest in their
2006 analysis of the OECD/Eurostat country survey on
employment and hours for national accounts, a country’s
data sources and data priorities determine the methodology that the country uses to prepare an estimate of hours,
employment, and, eventually, average annual hours actually
worked per employed person. The direct method of estimation is based on sources that capture hours actually worked,
whereas the component method is used to convert normal,
paid, or usual hours worked to an hours-actually-worked
concept.17
Exhibits 1 and 2 together provide a snapshot of the BLS
and OECD data sets through 2006, the concept of hours,
the sources of hours and employment, and—where information was available—the adjustments to concepts made
for each data set.18 Ypma and van Ark’s analysis gives detail
where information is lacking. The general term “national
accounts concept of hours worked” refers to the 1993 System of National Accounts measure of labor inputs, which in
turn refers to the ILO resolution on hours actually worked.19
Individual countries may adopt measures that include any
number of original sources and related concepts of hours
and employment, and, as necessary, may subsequently adjust them to expand coverage to all employed persons, to
convert measures of paid, normal, or usual hours to hours
actually worked, or to include industrial sectors that are
otherwise excluded from a survey.20
An important detail of the two tables is the unit of measure of hours. Whether that unit of measure—that is, the average annual hours actually worked—is applied per employed
person, per job, or on the basis of full-time equivalents—creates differences between levels of data. Because one person
can hold more than one job, the average hours worked per
employed person will be greater than the average hours
worked per job. The concept of full-time equivalent workers consolidates hours worked by part-time workers into a
measure of hours that approximates the hours worked by
a full-time employed person working a normal workweek.
Average annual hours actually worked per full-time equivalent worker will be greater than average annual hours actually worked per employed person. Average annual hours actually worked per employee are estimated when data for the
self-employed are not available or are difficult to integrate
into the calculations. Average annual hours actually worked
per employee are generally lower than those per employed
person, because the self-employed work longer hours than
employees. This comparison of two data sets highlights how
results differ, even for the same country, if a different source
of data or unit of measure is used. Eight of the 13 countries
have major differences in their data sources or methods.
data set. In the face of continued interest in broad
measures of productivity based on hours worked, a 2007
BLS report began to publish international comparisons of
GDP per hour worked, as well as GDP per employed person.21 The underlying data on total hours and total employment are collected from national sources, where available.
The report covers 16 countries, but data on hours worked
cover only 13 of the 16, all 13 of which are discussed in
this article. Efforts are being made to extend coverage to
Australia as well. Data for Germany have a break in 1991;
data for earlier years are estimates based on the former
West Germany’s hours and employment. Other breaks in
series include a 1997 break for Canada due to changes in
classification. The years covered for Japan and the Netherlands begin at 1996 and 1995, respectively.
Sources and concepts of data on hours are available in
detail only for some countries. The BLS report publishes
an aggregate, rather than average, measure of annual hours
worked. The underlying source data used to calculate average annual hours actually worked in the BLS data set
are most commonly total-hours-worked measures, available from national accounts, and total employment measures, usually estimated from national labor force surveys
or available from national accounts. Data series for three
countries—Japan, South Korea, and Belgium—are published
as average hours worked. Japan and Belgium publish average
annual hours worked in the national accounts and OECD
productivity database, respectively.22 South Korea’s average
annual hours worked are calculated from average weekly
hours worked, based on the labor force survey. Four other
countries’ hours-worked data are derived partially from labor
force surveys. For the United Kingdom, total hours are based
on labor force survey data whereas total employment comes
from national accounts. For the United States, Canada, and
the Netherlands, labor force surveys are the source of total
employment data, adjusted, where necessary, to account for
the Armed Forces. Total hours data for the United States and
Canada are based on establishment and labor force surveys.
The source of data for the remaining countries is total hours
worked and employment based on national accounts.
Of the countries included in the BLS series, the average hours worked are on an employed-person basis for
all but Japan, Norway, Spain, and the United Kingdom.
Data on hours worked for Japan refer to employees and
exclude the self-employed. Data for Norway are on a fulltime equivalent basis, and data for Spain and the United
Kingdom are on a jobs basis.
BLS
OECD data set.
Once a year, the OECD Employment Outlook
publishes data on average annual hours actually worked per
Monthly Labor Review • May 2009
Comparisons of Hours Worked
Exhibit 1.
Country
BLS concepts, sources, and methods, 13 countries
Primary
Other
Primary
Other
Hours
source of
sources
source
sources
Beginning Breaks in
concept
data on
of data on
of data on
of data on
year
used in
series
total hours total hours
total
total
1
source
data
worked
worked
employment empoyment
United States
1950
None
Establishment Labor force
survey
survey
Methodology
used to create Unit of
average annual measure
hours actually
worked
Hours paid, Labor force
Data on
Divide total
with
survey
Armed Forces hours by total
adjustment
employment
to hours
worked
Per
employed
person
Canada 1961
1997,
Labor force Establishment National
Labor force
No more
Divide total
Per
NAICS
survey
survey
accounts
survey
known
hours by total employed
sources
employment
person
Japan 1996
None
National
No more
National
No informa- No informa- No information
Per
accounts
known
accounts
tion available tion available
available
employee
sources
South Korea 1980
None
Labor force
survey
Belgium 1970
None
Administra
tive data
No more
known
sources
Average
No informa- No informa- Average weekly
Per
hours worked, tion available tion available hours × 52
employed
by week
person
No more
National
No informa- No informa- No informaknown
accounts
tion available tion available tion available
sources
Per
employed
person
Denmark 1966
None
National
AdministraNational
National
accounts
tive data
accounts,
accounts
based on
normal hours
No more
known
sources
Divide total
hours by total
employment
France 1970
None
National
accounts
No more
National
National
known
accounts
accounts
sources
No more
known
sources
Divide total
hours by total
employment
Per
employed
person
Netherlands 1995
None
National
accounts
No more
known
sources
Volume of
Labor force
Data on
Divide total
person-hours
survey
Armed Forces hours by total
worked
employment
Per
employed
person
Germany 1960
1991
National
accounts
No more
National
National
known
accounts
accounts
sources
No more
known
sources
Divide total
hours by total
employment
Per
employed
person
Per
employed
person
Norway 1970
None
National
No more
Man-hours
National
No more
accounts
known
accounts
known
sources
sources
Divide total
Full-time
man-hours
equivalent
worked by total
employment
Spain 1979
None
National
accounts
No more No informaNational
known
tion available
accounts
sources
No more
known
sources
Divide total
hours by total
jobs
Per job
Sweden 1980
None
National
accounts
No more No informaNational
known
tion available
accounts
sources
No more
known
sources
Divide total
hours by total
employment
Per
employed
person
No more No informaNational
known
tion available
accounts
sources
No more
known
sources
Divide total
hours by total
jobs
Per job
United
Kingdom 1971
None
Labor force
survey
1
10
The national accounts concept of hours worked is hours actually worked, unless otherwise noted.
Monthly Labor Review • May 2009
Exhibit 2.
Country
OECD concepts, sources, and methods, 13 countries
Primary
Other
Primary
Other
Hours
source of
sources
source
sources
Beginning Breaks in
concept
data on
of data on
of data on
of data on
year
used in
series
total hours total hours
total
total
1
source data employment empoyment
worked
worked
Methodology
used to create
Unit of
average annual measure
hours actually
worked
United States
1950
None
Establishment Labor force Hours paid, Establishment Labor force (Total hours/
Per
survey
survey
with adjustsurvey
survey
total
employed
employment) ×
ment to
person
multiple
hours worked
jobholder rate
Canada 1961
1997,
Labor force Establishment National
No informa- No informa- Direct measure
Per job
NAICS
survey
survey
accounts
tion available tion available of average actual
hours worked,
with
adjustments for
weeks not covered
and holidays
Japan 1970
None
Establishment Labor force
Hours
Establishment Labor force
OECD
Per job
survey
survey
worked
survey
survey
estimates
South Korea 1980
None
National
No other
National
National
No more
OECD
Per
accounts
known
accounts
accounts,
known
estimates
employed
based on
sources
based on
sources
person
labor force
labor force
survey
survey
Belgium 1983
None
Labor force Administrative Usual hours No informa- No informaOECD
survey
data
worked
tion available tion available
estimate,
accounting for
underreporting
of time not
worked and
public holidays
Per
employed
person
Denmark 1970
None
National Administrative National
National
accounts
data
accounts
accounts
Per
employed
person
No more
OECD
known
estimates
sources
France 1970
None
Administrative Establishment National
No informa- No informa
data
and labor
accounts,
tion available tion available
force surveys
based on
hours offered
French
national
accounts
Per
employed
person
Germany 1991
1991 data Administrative Labor force
National
No informa- No informa
series begin
data
survey
accounts,
tion available tion available
based on
normal hours
German
national
accounts
Per
employed
person
Netherlands 1987
2002, 2003, Labor force Administrative Usual hours No informa- No informaOECD
OECD
survey
data
worked
tion available tion available
estimate,
estimates
accounting for
underreporting
of time not
worked and
public holidays
Per
employed
person
Monthly Labor Review • May 2009 11
Comparisons of Hours Worked
Exhibit 2.
Country
Continued—OECD concepts, sources, and methods, 13 countries
Primary
Other
Primary
Other
Hours
source of
sources
source
sources
Beginning Breaks in
concept
data on
of data on
of data on
of data on
year
used in
series
total hours total hours
total
total
1
source data employment empoyment
worked
worked
Norway 1962
None
Establishment Labor force
National
No informa- No informa
survey
survey and
accounts
tion available tion available
administrative
data
Methodology
used to create
Unit of
average annual measure
hours actually
worked
Norwegian
national
accounts
Full-time
equivalents
Spain 1977
1987,
Labor force Establishment Actual and No informa- No informachange in
survey
survey
usual hours tion available tion available
survey
worked
Spanish
statistical
institute
Full-time
equivalents
Sweden 1950
1996,
Labor force Establishment National
No informa- No informachange in
survey
survey
accounts
tion available tion available
data source
Swedish
national
accounts
Per
employed
person
Average hours
actually
worked × 52
Per
employed
person
United
Kingdom 1970
1
1984, 1992, Labor force
change in
survey
data source;
1994,
include
Northern
Ireland;
1995,
change in
method
No more Actual hours Labor force
known
worked
survey
sources
The national accounts concept of hours worked is hours actually worked, unless otherwise noted.
employed person. The data are based on the OECD productivity database. Data on hours worked are converted, where
necessary and possible, to employed persons from jobs.
Some data for the Employment Outlook hours series are based
on sources that differ from the productivity database. The
OECD data set covers 30 countries and provides estimates of
average annual hours actually worked per employed person
(that is, all those employed, including the self-employed and
unpaid family workers) and per employee (that is, excluding
the self-employed and unpaid family workers).23 The years
covered for Belgium and the Netherlands begin at 1983 and
1987, respectively.
Compared with the BLS data set, the OECD data set
provides slightly more metadata, because the organization
collects and processes a questionnaire on national accounts
from national statistical agencies of member countries. The
hours concept used with the OECD data set is consistent
with national accounts for 7 of the 13 countries in the data
set. (See exhibit 2.) The countries for which data sources
are derived not solely from national accounts include the
12
No more
known
sources
Monthly Labor Review • May 2009
United States, Japan, Belgium, the Netherlands, Spain, and
the United Kingdom. For the United States, both hours and
employment are taken from the BLS major sector productivity measures. Data for Japan are measured primarily by an
establishment survey and are OECD estimates. Estimates of
average annual hours actually worked for Belgium and the
Netherlands are developed from the European Union labor
force survey, using usual hours of work and adjusting for
hours not worked. Data for Spain are based on hours actually worked, as well as usual hours of work for those deemed
not at work in the labor force survey. The data for the United
Kingdom are based completely on the labor force survey, but
are compatible with national accounts concepts.
More information on the OECD data set is available
from Ypma and van Ark’s analysis of 2004 hours-worked
data based on the OECD/European Union national accounts questionnaire.24 South Korea and the United Kingdom are the only two countries for which the dara source
is solely the labor force survey. The United States, Canada,
and Japan are categorized as using primarily survey (both
labor force and establishment) data and not administrative data. The third category is split between the countries
that use survey data more than administrative data—such
as Norway, Spain, and Sweden—and those which use primarily administrative data, supplemented by labor force and
establishment survey data—such as Denmark, France, and
Germany. For Belgium and the Netherlands, OECD prepares an estimate of average hours actually worked based
on the labor force survey.
Comparison across BLS and OECD data sets. The next section
compares the data on average annual hours actually worked
per employed person between the BLS and OECD data
sets.25 In preparation for that analysis, note that differences
in data arise because of differences in sources, concepts,
coverage, and units of measure. For Denmark, France for
1990–2002, Germany for 1991 onward, Norway, and Sweden, data sources in each data set are the same. For Canada,
Japan, South Korea, Denmark, and the Netherlands, average hours are higher in the BLS data set than in the OECD
data set. For France in earlier years, and for Belgium and
Spain, the OECD estimates are higher than the BLS estimates. For the United States, Germany in earlier years, and
the United Kingdom, average annual hours worked are not
consistently higher or lower in either data set.
The differences between the data sets for the United
States and Japan are difficult to pinpoint, given that coverage, sources, and methodology differ between data sets for
both countries. Differences in units of measure affect the
different levels among the data sets for Canada, Spain, and
the United Kingdom. For Belgium, South Korea, and the
Netherlands, the contrast between the BLS and OECD data
sets for each country is due to the source of the data: administrative or survey based; the administrative-data adjustment
for time not worked affects comparisons for two of the three
countries, and the use of normal hours affects the third.
The country-by-country comparison to be presented
highlights how data sources, measurement methods, and
units of measure matter. The differences can be categorized as follows:
• Administrative sources reporting normal hours of
work result in lower estimates of average annual
hours actually worked than do data from surveys.
• Among surveys, data that are primarily from establishment surveys using usual hours or paid hours worked
produce lower estimates than do data that are primarily
from labor force surveys; data from labor force surveys
may overstate hours reported, due to proxy reporting.
• Adjustments to exclude hours not worked may over-
estimate time not worked and lower estimates of
hours worked.
• Units of measurement can affect the levels of hours
worked that are reported.
1. More similar than different: Denmark, France, Germany,
Norway, and Sweden. The Nordic countries covered, as
well as Germany, and France for some years, use the same
data source in both the BLS and OECD data sets and differ
only slightly or not at all across years. For Denmark, average
annual hours actually worked for both data sets are from the
country’s national accounts and run parallel to each other.
In 1980, average annual hours per employed person were
about 1,650 for both data sets; by 2006, they had fallen to
1,577 (OECD) and 1,608 (BLS). (See chart 1, top panel.)
The 30-hour difference between data sources is likely due
to differences in rounding or method of calculation.
For France, the source for both data sets is the French
national accounts. From 1980 to 1989, differences are not
large, averaging about 2 to 4 days a year for any given year.
(See chart 1, middle panel.) The two data sets yield identical results for 1990–2002 and diverge only minimally for
2003–06. The BLS methodology of linking data from different sources with similar concepts for the period before
1990 creates slight differences between the two data sets.
For Germany, both data sets use that country’s national
accounts from 1991 forward. The data sources are identical, and so are the series on average annual hours actually
worked. Hours worked in 2006 were among the lowest that
year of all the countries studied. The 1,436 average annual
hours worked is the equivalent of working 36-hour weeks
only 9 months of the year. (See chart 1, bottom panel.)
For both Norway and Sweden, national accounts data
were used to prepare estimates of hours worked for both data
sets. Nonetheless, the sources of the two countries’ data—administrative sources and the labor force survey—create the
appearance that there are large differences in the Norwegian
and Swedish labor markets when hours measures are compared. In Norway, hours worked were listed as 1,580 in 1980
and had fallen to 1,400 by 2006. (See chart 2, top panel.) In
Sweden, hours worked were near 1,500 in 1980 and 1981;
peaked in 1999; returned to 1,580, an increase equivalent to
2 weeks of work, by 2002; and mostly held steady since then,
coming in at 1,583 in 2006. (See chart 2, bottom panel.)
This difference between Sweden and Norway will be examined more carefully in the next section.
2. United States and Japan: countervailing differences. The
data sets differ for the United States and Japan. The differences, however, are so varied that it is difficult to pinMonthly Labor Review • May 2009 13
Comparisons of Hours Worked
Chart 1.
Average annual hours actually worked, all employed persons, Denmark, France, and Germany,
1980–2006
Hours
worked
1,700
Hours
worked
1,700
Denmark
1,650
1,650
1,600
1,600
BLS
1,550
1,550
OECD
1,500
1,500
1,450
1,450
1,400
1980
Hours
worked
1,900
1,850
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
1,400
Hours
worked
1,900
France
1,850
1,800
1,800
OECD
1,750
1,750
1,700
1,700
1,650
1,650
1,600
1,600
BLS
1,550
1,550
1,500
1,500
1,450
1,450
1,400
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
Hours
worked
1,400
2006
Hours
worked
1,800
1,800
Germany
1,750
1,750
1,700
1,700
OECD
BLS
1,650
1,650
1,600
1,600
1,550
1,550
1,500
1,500
1,450
1,450
1,400
1980
1982
1984
14 Monthly Labor Review • May 2009
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
1,400
2006
Chart 2.
Average annual hours actually worked, all employed persons, Norway and Sweden, 1980–2006
Hours
worked
Hours
worked
1,600
1,600
Norway
1,550
1,550
BLS, OECD1
1,500
1,500
1,450
1,450
1,400
1,400
1,350
1,350
1,300
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
Hours
worked
2006
1,300
Hours
worked
1,700
1,700
Sweden
1,650
BLS, OECD1
1,650
1,600
1,600
1,550
1,550
1,500
1,500
1,450
1,450
1,400
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
1,400
1
For Norway, BLS and OECD data are identical for every year except 1989 and 1999, for which they differ by 1 hour. For Sweden, BLS and OECD
data are identical.
Monthly Labor Review • May 2009 15
Comparisons of Hours Worked
point how they might produce differences in time trends.
U.S. estimates of hours are produced by the BLS Division
of Major Sector Productivity and are based on hourspaid data from an establishment survey on production
workers, adjusted to an hours-worked measure by means
of the labor cost index and further adjusted to account
for industries and categories of workers not otherwise included, as well as self-employed and unpaid family workers, based on the U.S. Current Population Survey.26 The
estimates cover the total economy. The OECD uses aggregate employment data based on the same methodology
to create a data series of average annual hours actually
worked and then adjusts from a jobs to an employedperson basis. The BLS, by contrast, uses employment data
from the national labor force survey, adjusted to include
military employment. The differences between the levels
of hours published in the OECD and BLS data sets reflect
the historically different trends in U.S. employment as
measured by establishment and labor force surveys. The
overall difference between the two data sets lies in the
source of employment data and the underlying differences between the two surveys.27
In the case of Japan, the OECD series on average hours
actually worked is estimated from Japan’s establishment
survey for employees and includes labor force survey data
on the self-employed. The BLS data set is based on the
national accounts data for employees from 1997 onward.
Using the categories of differences outlined earlier, labor
force survey data are expected to produce higher rates
than national accounts data based on administrative or
establishment survey data. But for Japan, the OECD hours
series based on the labor force survey is lower, on average, than the BLS hours series based on national accounts.
Further complicating matters is the fact that hours for all
the employed would be expected to be lower than hours
for employees, given the nature of self-employment.
However, that expectation is not borne out in the case of
the two data sets on Japan: the employee data from the
national accounts trend higher than the OECD data on all
employed persons from the labor force. Only in the case
of units of measure does the direction of the difference
hold. Data on hours worked are on a per-job basis for the
OECD and a per-person basis for BLS. This is the only one
of three differences that explains why hours-worked data
are higher for the BLS data set. Chart 3 shows the average
annual hours actually worked by all employed persons, for
the United States and Japan.
3. Canada, Spain, and the United Kingdom: units of measure matter. In these three countries, the unit of measure,
16 Monthly Labor Review • May 2009
among other things, drives the differences between the
data sets. For Canada, the BLS data series is based on a
measure of hours per employed person, whereas the OECD
data series is based on a measure of hours per job. All
other things being equal, average hours actually worked
per employed person are higher than average hours actually worked per job. Also for Canada, the two data sets
use the same source for hours-worked data, but different
sources for employment data. The source of OECD data is
the Canadian national accounts, which combine establishment and labor force survey data; by contrast, the source
of BLS data is an employment series for employed persons
from the labor force survey. The BLS figure is higher for
all years, partly because of the difference in sources and
partly because the unit of measurement is employed persons rather than jobs.
For Spain, the BLS hours series draws from national
accounts data based partially on the country’s labor force
survey and reported on a per-job basis. The OECD data
set uses a data series estimated by the national statistical
institute, is based on actual and usual hours from the labor force survey, and adopts a full-time-equivalent unit of
measure. These differences create two nearly parallel data
series, with the BLS series, on the per-job basis, at a lower
level than the OECD series. Together, the source and the
unit of measure for Spain explain why the BLS data set
shows lower levels than the OECD data set.
For the United Kingdom, the BLS and OECD data sets
each use that country’s labor force survey data on hours actually worked. The source of data on average hours worked
per person is the same, but the source of data on employment differs. The BLS data source for employment is a national accounts data series of aggregate jobs that combines
data from both establishment and labor force surveys. The
employment source for the OECD data series is solely the
labor force survey, measured on an employed-person basis.
Without more detailed information on the national accounts methodology, it is difficult to determine the extent
to which the establishment survey data may affect the
hours-worked measure. The unit of measure does explain
the difference in the two trends: the trend is lower for the
BLS series, which is based on jobs, than it is for the OECD
series, which is based on employed persons. Chart 4 shows
the average annual hours actually worked by all employed
persons, for Canada, Spain, and the United Kingdom.
4. Belgium, South Korea, and the Netherlands: normal hours
and time not worked. The inclusion of normal hours based
on administrative data to estimate time worked and to adjust for time not worked also drives differences between
Chart 3.
Average annual hours actually worked, all employed persons, United States and Japan, 1980–2006
Hours
worked
Hours
worked
1,900
1,900
United States
BLS
1,880
1,880
OECD
1,860
1,860
1,840
1,840
1,820
1,820
1,800
1,800
1,780
1,780
1,760
1,760
1,740
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
1,740
Hours
worked
Hours
worked
2,200
2006
2,200
Japan
2,100
2,100
OECD
2,000
2,000
1,900
1,900
BLS
1,800
1,800
1,700
1,700
1,600
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
1,600
Monthly Labor Review • May 2009 17
Comparisons of Hours Worked
Chart 4.
Average annual hours actually worked, all employed persons, Canada, Spain, and United Kingdom,
1980–2006
Hours
worked
1,840
1,820
Hours
worked
1,840
Canada
BLS
1,820
1,800
1,800
1,780
1,780
1,760
1,760
1,740
1,740
OECD
1,720
1,720
1,700
1,700
1,680
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
1,680
Hours
worked
Hours
worked
2,200
2006
2,200
Spain
2,000
2,000
OECD
1,800
1,600
1,800
1,600
BLS
1,400
1,400
1,200
1,200
1,000
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
Hours
worked
1,850
1,000
2006
Hours
worked
1,850
United Kingdom
OECD
1,800
1,800
1,750
1,750
1,700
1,700
BLS
1,650
1,650
1,600
1,600
1,550
1980
1982
1984
18 Monthly Labor Review • May 2009
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
1,550
2006
data sets. The BLS and OECD data sets show different
time trends for Belgium, South Korea, and the Netherlands. Upon analysis, the BLS data series based on normal
hours present a lower trend in hours worked, as in the
case of Belgium. For South Korea and the Netherlands,
the OECD adjustments to time not worked, using normal
or administrative data, create an hours-worked series that
averages 1½ to 3 weeks less than the BLS series for both
countries (except South Korea in earlier years).
For Belgium, BLS uses the average-hours-worked series
from the OECD productivity database, which differs from
the OECD data set based on the Employment Outlook.
These data for Belgium are based on administrative data,
according to Ypma and van Ark.28 The OECD data set, by
contrast, uses the labor force survey to create an estimate
of hours worked. The tendency of administrative data to
produce lower estimates, by undercounting overtime and
overestimating leave time taken, explains the lower numbers in the BLS data set for Belgium’s hours relative to the
numbers in the OECD data.
In the case of South Korea, the OECD and BLS data series both use the labor force survey as their primary source
of data. On the one hand, the OECD estimates for South
Korea are based on that nation’s labor force survey and include an adjustment downward to aggregate hours worked
in the year, in order to account for time not worked, before
dividing by employment. On the other hand, the BLS estimates for South Korea are based on published data on
average weekly hours worked for persons at work. The average is multiplied by 52 to create a yearly average, and no
adjustments are made for time not worked. The OECD’s
additional adjustment for time not worked contributes to
a lower estimate of average annual hours actually worked
compared with the BLS estimate, even though the OECD
unit of measure takes account of all those who are employed, as opposed to the BLS employee measure.
For the Netherlands, aggregate hours data for the BLS
data set are based on the Dutch national accounts hoursworked data series and employment is from the labor
force survey, adjusted to include the Armed Forces. The
OECD data set’s estimate of average annual hours actually worked is based on the labor force survey’s figure for
usual hours of work and includes adjustments to time not
worked. The different sources provide different data series.
For 2006, OECD reports 1,391 average annual hours actually worked—about 2½ person-weeks less than the BLS
series figure. One would expect that labor force survey
data would produce a higher average-hours-worked series. However, if OECD’s adjustments to time not worked
overestimate the hours not worked, then the number of
hours worked will be underestimated. This would explain
the fact that data from the BLS hours-worked series yield
higher numbers than do data from the OECD series based
on the labor force survey. Chart 5 shows the average annual hours actually worked by all employed persons, for
Belgium, South Korea, and the Netherlands.
Both the BLS and the OECD suggest that the data
user compare the trends over time between countries.
A rank von Neumann test comparing the differences in
level data between the BLS and OECD data sets for each
country determined that the trends are similar for 10
of the 13 countries examined in this article. That is, the
only 3 countries that show a significant probability of
having experienced a random degree of change between
data sets over time were the United States, France, and
the Netherlands. Thus, for these 3 countries, there is a
variability in the rankings which implies that the two
sets of data are not drawn from the same population,
which in this case would be represented by the data
source. The test results for the other countries show that
the rankings of the differences between the levels are not
different from each other, indicating that the associated
data sets exhibit “trendlike” features. This statistical test
provides evidence that, for the majority of the countries
examined, the comparison made of trends over time is
consistent and useful, even when different sources or
methods are used.
Comparison of hours worked and working time
The concept of hours worked, as addressed in this article,
is a purely quantitative measure of the number of hours an
individual spends at work. Working time, by contrast, is a
broader concept that encompasses quality-of-worklife issues,
including the scheduling of hours of work, such as overtime,
split-shifts, and “just-in-time” flexible work schedules; night
work and weekend work; and part-time work.
A cross-country comparison of hours worked for the
13 countries examined in this article, using the OECD
data set, reflects a number of institutional changes in both
working time and hours worked. Historically, the United
States pioneered reductions in working time well in advance of other industrial nations, although Western Europe caught up by the 1980s.29 Since then, a number of
changes in the structure of the labor market have contributed further to a reduction in working time. First, normal
hours of work have declined in many developed countries
because of changes in laws and collective-bargaining
agreements. Second, women have increasingly joined the
labor force and work, on average, fewer hours than men.
Monthly Labor Review • May 2009 19
Comparisons of Hours Worked
Chart 5.
Average annual hours actually worked, all employed persons, Belgium, South Korea, and the
Netherlands, 1980–2006
Hours
worked
Hours
worked
1,850
1,850
Belgium
1,800
1,800
1,750
1,750
1,700
1,700
OECD
1,650
1,650
1,600
1,600
BLS
1,550
1,550
1,500
1,500
1,450
1,450
1,400
1,400
1,350
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
Hours
worked
Hours
worked
3,000
2,900
1,350
2006
3,000
South Korea
2,900
2,800
2,800
BLS
2,700
2,700
OECD
2,600
2,600
2,500
2,500
2,400
2,400
2,300
2,300
2,200
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
Hours
worked
1,600
1,550
2,200
Hours
worked
1,600
Netherlands
1,550
BLS
1,500
1,450
1,500
1,450
OECD
1,400
1,400
1,350
1,350
1,300
1,300
1,250
20
2006
1980
1982
1984
Monthly Labor Review • May 2009
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
1,250
Finally, part-time hours worked in the growing service
sector mitigate the overtime work pattern in the relatively
smaller manufacturing sector. Each of these labor market
conditions merits discussion.
A 2004 OECD report on working time analyzes the
broader measure of labor utilization—average annual
hours actually worked per capita—showing that these
hours have barely declined over the past three decades,
even as average annual hours actually worked per employed
person fell significantly.30 The large decline in average annual hours worked per worker was offset by increases in
both the employment rate (or employment-population
ratio) and the share of the population that is of working
age. The employment rate has risen as more women join
the workforce and as older workers stay in their jobs rather than retire. Both women and older workers are more
likely to work fewer hours in a full-time job or become
part of the growing ranks of part-time workers.
A 10-year snapshot with available data of the employment-population ratio, part-time employment rate, and
women’s labor force participation rate reflects, to a lesser
degree, the 30-year trend just described. (See table 1.) In 9
of the 13 countries examined, there were small increases in
the employment-population ratio. ( Japan and South Korea
saw a small decline and Spain experienced a large increase.)
The part-time employment rate grew from a low point in
South Korea and Spain; it fell in the United States and
Sweden, and it remained steady in Canada, Japan, France,
Norway, and the United Kingdom. The part-time employment rate rose in the remaining countries. Dutch policy
and legislation provide strong incentives for part-time emTable
Table 1.
1.
ployment, which are reflected in the fact that more than
a third of workers are employed part time in the Netherlands. The women’s labor force participation rate inched
up in all of the countries studied, except for Japan, where it
fell, and the Netherlands and Spain, where it rose dramatically. Nearly a tenth of women in the latter two countries
joined the labor force over the 10 years examined.
In both the OECD and BLS data series, 1980–2006
trends in average annual hours actually worked per employed person broadly reflect the institutional norms and
laws relating to working time in each of the 13 countries
discussed. This section next addresses some of the significant institutional and legislative changes that have occurred in the past 26 years in these countries.31
Countries with high working time. Of the countries examined, the United States, Canada, Japan, South Korea—
and the United Kingdom and Italy until recently—share
some or all of the following characteristics in their labor
market institutions and laws:
• a normal workweek of 40 hours or more
• no limit on maximum hours of work allowed per
week
• vacation time subject to tenure in job
• wage or leave penalties for absence from work
• limited or no legal entitlement to vacation time.
The United States and Japan impose no legal limit on the
maximum number of hours worked per week. Regarding
paid time off, business practice in the United States varies
Three important international labor market indicators, 1996 and 2006
EmploymentPart-time
Women’s labor
population ratio
employment rate
force participation rate
Country
1996
2006
1996
2006
1996
2006
United States................................................................................. 63.2 63.1
14.7
13.3 59.3 59.4
Canada............................................................................................. 59.1 63.6
19.4
18.5 57.3 62.1
Japan ............................................................................................... 60.9 57.5
21.8
24.5 49.3 47.9
South Korea................................................................................... 59.4 58.9 4.7
9.7 48.9 50.6
Belgium........................................................................................... 45.1 48.8
14.9
19.3 44.0 45.9
Denmark......................................................................................... 60.3 62.8
16.9
18.1 58.4 60.8
France.............................................................................................. 49.1 51.2
14.2
13.3 48.6 51.1
Germany......................................................................................... 52.0 52.2
15.2
21.9 47.4 51.2
Netherlands................................................................................... 56.2 62.5
29.7 35.5 49.5 57.8
Norway............................................................................................ 60.2 62.6
21.2
21.1 57.2 60.3
Spain ............................................................................................... 38.9 52.3 7.6
11.1 37.2 47.0
Sweden............................................................................................ 57.6 60.4
14.8
13.4 59.4 60.8
United Kingdom.......................................................................... 57.3 60.1
23.6
23.4 53.8 56.7
Monthly Labor Review • May 2009 21
Comparisons of Hours Worked
South Korea’s long hours worked
South Koreans work longer hours per week than
workers in many other OECD countries, despite national legislation that phased in the 40-hour workweek by 2004. The 2007 South Korean labor force
survey reports that nearly 60 percent of all employed
persons who were at work when the survey was taken
actually worked 45 hours or more a week, whereas less
than 30 percent worked a 36- to 44-hour workweek.
Less than 15 percent of part-time employed persons
who were at work when the survey was taken worked
35 or fewer hours a week.
widely, with some businesses granting leave only after a
year’s tenure, others increasing the number of leave days
with job tenure, and about a fourth providing no paid
leave at all. Japanese and South Korean labor laws differ
from business practice. Businesses are supposed to pay for
overtime and to promote leave for employees. In practice,
however, workers usually take vacation hours when sick,
because sick leave is often unpaid. In some cases, employers penalize workers’ absences by deducting or not providing bonus pay or vacation time.32 Canada, the United
Kingdom, South Korea, and Japan require statutory paid
vacation time for full-time employees, while there is no
requirement in U.S. law to provide vacation time, either
paid or unpaid. Of the six countries with high working
time, only the United Kingdom and Italy require employers to pay part-time or temporary employees for their annual leave. The European countries are set apart by the
fact that they recently adopted the European Union’s
mandates on working-time restrictions.33
Between 1988 and 1997, Japanese laws reduced normal
hours of work from 48 to 40 hours per week; between 1997
and 2004, South Korea followed suit. (See box, this page.)
There have been few changes in labor laws in the remaining four countries during the past 25 years. In the 1990s,
the United Kingdom and Italy complied with the European Union regulations to limit working hours in 2002 and
2003, respectively.
Countries with low working time. Conditions in Belgium,
Denmark, France, Germany, the Netherlands, Norway, and
Sweden differ from those of the high-working-time countries just described. The aforementioned recent changes
to labor laws in the United Kingdom and Italy now place
22
Monthly Labor Review • May 2009
these two countries in the low-working-time category.
These countries share some or all of the following characteristics in their labor market institutions and laws:
• a legal or collectively bargained workweek of less
than 40 hours
• a limit on the maximum number of hours worked
during the week and a limit on the maximum number of overtime hours worked during the year
• statutory paid vacation time of a minimum of 4
weeks per year for full-time workers and prorated
for part-time employees
• near-universal entitlement to statutory vacation
time
• broad coverage of collective-bargaining agreements
that provide even more generous leave entitlements
than those written into law.
Revised laws regarding normal hours of work have been
implemented throughout Europe as a result of the European Union Directive on Working Time, which was first
introduced in 1993 and most recently revised in 2003.34
These laws (1) limit the hours that employees can work
overtime throughout the year and (2) establish vacation
rights of 4 weeks per year for full-time employees, with
prorated vacations for part-time employees.
Germany, the Netherlands, Norway, and Sweden have
a high share of workers covered by collective-bargaining
agreements; these countries saw reductions in the workweek as a result of changes in those agreements in the late
1980s. The Netherlands passed national legislation in 2000
that allowed employees to choose the number of hours
they want to work. The legislation led to a further growth
in part-time employment, which had begun to grow in the
1980s.35 The trend toward reductions in working time was
complemented by the implementation of the European
Union Working Time Directive in member countries. The
last two of the major European countries to ratify changes
in labor laws to comply with the directive were the United
Kingdom in 2002 and Italy in 2003.
The case of France is unique, because the reduction in
the normal workweek was initiated by laws, not collective-bargaining agreements. A series of laws was passed
beginning in the 1990s to reduce the number of hours in
the normal workweek, with the primary purpose of decreasing high unemployment. The changes began with the
Robien law in 1996, followed by the Aubry laws in 1998
and 2002, effectively reducing the normal workweek from
39 hours to 35 hours.
The trend toward reductions in hours shows signs of
Germany’s “minijobs”
Germany’s “minijobs” escape measurement. A
growing number of people work in such jobs, also
called “one-euro jobs”—positions that have a limit on
the hours that can be worked and that offer wages
on which earnings are not subject to income taxes
and employer taxes are reduced. The program was
intended to create jobs for the unemployed, but employed workers have taken on minijobs as second jobs
because of the tax advantage. In 2004, minijobs accounted for about 12 percent of employment, and 37
percent of minijobs went to people who had another
job. Minijobs are excluded from the administrative
framework of tax collection, so data on the hours
worked at them and the number of jobs they generate
are excluded from hours-worked statistics (personal
communication, Dr. Ulrich Walwei, Bundesagentur
für Arbeit/Institute for Employment Research, Germany, April 2006).
reversing in some countries. French legislation in 2003—
specifically, the Fillon law—excluded small businesses
from the normal maximum workweek limit of 35 hours,
and further revisions in 2007 were intended to provide
greater flexibility in scheduling hours for businesses. In
Germany, since 2003 a number of collective-bargaining
agreements, among them the trend-setting Volkswagen
and IGMetall agreements, have seen an increase in the
length of the regular workweek (which remains under 40
hours) in exchange for job security. The trend of raising the
ceiling on normal hours continues today in contract bargaining, especially in Germany. However, hours-worked
statistics do not necessarily reflect this or any other trend.
(See box, this page.)
Numerous studies of industrial relations in both the
countries with high working time and those with low working time provide detailed information on the institutions,
labor markets, and demographics that reinforce the quarter-century trends seen in the OECD and BLS data series on
average annual hours actually worked per employed person.
Among the findings are high, but declining, hours worked
in Asian countries; little change in hours worked in Anglophone countries, where a large share of workers continues
to work more than normal hours; and falling hours worked
in European countries, because of a reduction in normal
and contractual hours and rising part-time employment.36
Comparison of Japanese and U.S. hours worked
Pinpointing whether one country’s average hours actually
worked are more or less than another’s for a given year or
period is not a precise science. The next two sections look
at the data series for two countries whose labor market
conditions do not seem to be reflected in their data: Japan
and Sweden. Japan’s hours-worked series in both the BLS
and OECD data sets show that the average hours actually
worked by Japanese workers are on a par with those worked
by U.S. workers, defying the many references to that country’s “long-hours culture” that have become commonplace.
On the other end of the spectrum, Sweden’s hours worked
trended upward during the 25-year period studied, quite
unlike the trend in the other 12 countries and, in particular,
quite unlike its neighbor Norway, which has similar labor
practices. An analysis of the data sources used to construct
the various time series, together with a look at alternative sources, provides a further window of understanding
into the challenges of international comparisons of data
on hours worked. The estimates for Japan and Sweden are
compared with those for the United States and Norway,
respectively, and with alternative data sources.
The OECD data series for Japan shows that, for 2006,
annual average hours actually worked were 1,784, a figure
that is 35 hours less than the U.S. estimate of 1,804. (See
chart 6; data before 1996 are not available for the BLS data
set.) Over a quarter century, Japan’s annual average hours
actually worked declined by 42 eight-hour workdays and
the U.S. average fell by less than 2 eight-hour workdays. Is
it possible that U.S. workers now work longer hours than
their Japanese counterparts? Further, how does one explain the common practice of employees working unpaid
overtime in Japan despite recent regulations restricting
overtime hours?37 Finally, what about the culture of long
work hours as exemplified by official recognition of the occupational hazard of death from overwork, a phenomenon
the Japanese call karoshi?38
Some researchers think that the data for Japan undercount unpaid overtime and long hours of work. Evidence on
the incidence of overtime work in Japan, shown repeatedly
in many special surveys on labor conditions, together with a
historical comparison help interpret Japan’s data series. The
incidence and degree of usual overtime in Japan from 1997
through 2007 are given in table 2, which compares ranges
of hours worked by persons who worked at least two-thirds
of the year; these workers represent approximately 80 percent of employed persons.39 In all 3 years shown, 87 percent
or more of these year-round employed persons worked
at least a 35-hour week. However, from 1997, the year in
Monthly Labor Review • May 2009 23
Comparisons of Hours Worked
Chart 6.
Average annual hours actually worked, all employed persons, the United States and Japan,
1980–2006
Hours
worked
Hours
worked
2,200
2,200
2,100
2,100
Japan
2,000
2,000
1,900
1,900
United States
1,800
1,800
1,700
1,700
1,600
1980
1982
1984
1986
1988
1990
1992
which legislation was passed to reduce the normal workweek from 44 to 40 hours, the share of persons who usually
worked 43 or more hours per week shifted slightly upward,
from 57 percent in 1997 to 61 percent in 2002. The percentage fell to 59 percent in 2007. Over the year, a number
of employees do not take vacation time, even though they
are entitled to it. According to one 2005 study, workers
take less than half their vacation for the year, accumulating
an average of 18 untaken vacation days.40
Further evidence of the undercount of hours in the
OECD data set is found in Takeshi Mizunoya’s research.
Mizunoya uses both labor force and establishment surveys
to determine the degree to which different survey sources
for Japanese data matter. His critique of the OECD annualhours-worked data series for underreporting hours worked
in Japan stems from the type of survey that the OECD uses.
Rather than using the establishment survey, as the OECD
does, Mizunoya uses the labor force survey for 3 years during the 1990s to account for unpaid overtime, developing
an estimate of employees’ average annual hours actually
worked.41 Chart 7 compares Mizunoya’s estimates with the
OECD annual-hours-worked data series. The Mizunoya
estimates are greater than the OECD data for each of the
24 Monthly Labor Review • May 2009
1994
1996
1998
2000
2002
2004
1,600
2006
years studied—1990, 1995, and 1999—increasing from a
240-hour to a 270-hour difference over the decade, or the
equivalent of at least 6 weeks more a year. Because, on average, the self-employed work more hours than employees,
the Mizunoya estimate, based on employees, does not fully
compensate for the greater number of hours worked by the
self-employed.
This example from Japan leaves the lesson that understanding labor markets is key to deciphering the differences in data sources and explaining how those differences affect comparisons.
Swedish and Norwegian hours worked
The BLS and OECD data sets for Sweden and Norway are
identical, each using the data prepared by that country’s
national accounts. However, the data series for Sweden
shows that average annual hours actually worked in 2006
were the highest among countries with low working time
and were about 175 hours more than those of Sweden’s
Nordic neighbor Norway. Twenty-five years ago, Sweden’s
hours were lower than Norway’s, but average annual hours
actually worked in 2006 were reported to be 1,583 for
Table 2.
1.
Table
Percent distribution of weekly hours worked by year-round employed persons, Japan, 1997, 2002,
and 2007
2002
2007
1997
Weekly hours worked
All year-round employed persons...................................................... 53,873,000 50,576,100 51,715,100
Less than 15.......................................................................................................
.9
1.0
1.2
15–21.................................................................................................................
1.9
2.4
2.9
22–34................................................................................................................. 6.0 7.1 8.1
35–42................................................................................................................. 34.1
29.0
29.0
43–45.................................................................................................................
15.0
12.5
12.2
46–48.................................................................................................................
15.4
14.5
13.1
49–59.................................................................................................................
15.9
19.5
18.9
60 or more.......................................................................................................
10.6
14.1
14.6
NOTE: Year-round employed persons are those who work more than 200
days per year.
Sweden and 1,407 for Norway. (See chart 8.) Until the
1990s, hours fell in both countries, but Sweden’s hours
worked rose throughout the decade and remain the highest among countries with low hours worked. By contrast,
Norway’s hours worked show a continuously declining
trend. Is it possible that Swedes work 5 weeks more per
year, on average, than Norwegians? This seems unlikely,
for a number of reasons. First, both countries have labor
laws that provide generous statutory paid leave of 5 weeks
a year—1 more week than that mandated by the European
Union Working Time Directive—and full- and part-time
workers are eligible for this leave. Second, Sweden has
11 national holidays compared with Norway’s 9. Finally,
many employees in both countries are covered by collective-bargaining agreements and work less than a 40-hour
workweek.
The similarities in labor conditions belie the fact that
the two countries’ economies experienced different levels
of prosperity in the 1990s. Norway’s oil wealth cushioned it
from the austerity that the Swedish economy had to turn to
in the 1990s. Sweden experienced a strong economic downturn and increasing unemployment, and saw its generous
social policies curbed throughout the decade.42 The increase
in the country’s hours worked in the 1990s is counterintuitive: a weak economy generally contributes to a decline in
hours worked, both individually and across the economy.
The decline in hours worked as of 2000 can be explained
by a number of changes, including continued reductions in
normal hours of work through collective-bargaining agreements in the private sector43 and adverse effects of the expansion of an already generous sick leave policy, leading to
a daily rate of absence from work of 20 percent.44 In light of
these developments, Sweden’s average annual hours actually worked appear suspiciously high.
The Swedish national accounts’ primary source of data on
employment and hours worked is the country’s labor force
SOURCE: Employment Status Survey, Statistics Bureau, Management and
Coordination Agency, Government of Japan.
survey. The Norwegian national accounts data, by contrast,
are based on normal hours of work reported by administrative data sources. Administrative data used by Norway lead
to the lowest estimates of hours actually worked, whereas
labor force surveys, such as those used by Sweden’s national
accounts, produce the highest estimates. These differences
in underlying data sources make it difficult to compare the
two countries’ data series. It is probable that hours actually
worked in each country lie somewhere in between the two
series’ values, but it is highly unlikely that Swedish people
work 4 to 5 more weeks a year than Norwegians do.
Using data from similar sources and creating a simple
methodology of comparison shrinks the differences between the two countries’ hours-worked figures considerably.
and increases their levels as well. Harmonized labor force
survey data on hours actually worked per week for Norway
and Sweden are available for 2006. Because the two countries’ labor force surveys are continuous, one can estimate
average annual hours actually worked by multiplying the
average of hours actually worked per week by 52. The labor
force survey reports higher hours overall for both countries
and diminishes the difference between them. As the following tabulation shows, the difference between Norway’s
and Sweden’s average annual hours actually worked declines
from 4½ weeks to 1½ weeks when comparable data sources
and methodologies are used:
Average annual hours
actually worked per employed person, 2006
Country
National accounts
Norway .........................
1,407
Sweden .........................
1,583
European Union
labor force survey
1,817
1,872
These examples highlight how differences in concepts and
Monthly Labor Review • May 2009 25
Comparisons of Hours Worked
Chart 7.
Average annual hours actually worked per employed person or per employee,1 Japan, 1990, 1995,
and 1999, OECD and Mizunoya data series
Hours
worked
Hours
worked
2,500
2,500
2,000
2,000
1,500
1,500
1,000
1,000
500
500
0
1990
1995
1999
1990
OECD
NOTE:
1995
Mizunoya
1999
0
OECD data are per employed person; Mizunoya data are per employee.
sources can affect estimates of average annual hours actually worked. Despite the problems that are inherent in
making comparisons of levels of annual hours worked per
person, broad trends are often reliable, reflecting real labor
conditions in a country.
Data sources matter
The preceding comparisons between Japan and the United States, on the one hand, and Sweden and Norway, on
the other, are complemented by two studies: one by the
French researchers Mireille Bruyère and Odile Chagny,
and the other by the OECD. Both analyses used usualhours-worked data from labor force surveys to create
estimates of average annual hours actually worked and
made adjustments with other data sources to account for
hours not worked. Both analyses found that, in general,
labor force surveys produce usual-hours-worked estimates that are greater than those based on normal hours
worked, but lower than estimates based on hours actual
worked.
26 Monthly Labor Review • May 2009
Bruyère and Chagny’s labor force survey estimates from
the 1990s showed higher average hours worked for the
same year, compared with the OECD estimates described
in earlier sections, which are based on hours paid and normal hours for the United States, Japan, France, Germany,
and the Netherlands.45 However, the authors’ estimate of
average hours worked for the United Kingdom was lower
than that prepared for the OECD database, which is based
on hours actually worked from the labor force survey.
An OECD special study that used data for 2002 and a
decomposition method produced results similar to those
of Bruyère and Chagny.46 Using usual hours worked and
adjusting for hours not worked, the OECD special study
produced estimates for France and Germany that were
higher, compared with values from the normal-hours-ofwork source of the regular OECD data set. The Dutch data
for both OECD publications should be the same as well,
but differed inexplicably. The U.K. estimate based on the
decomposition method and using normal hours as well as
survey sources was lower than the estimate based on the
actual-hours-worked estimate.
Chart 8.
Average annual hours actually worked, all employed persons, Sweden and Norway, 1980–2006
Hours
worked
Hours
worked
1,700
1,700
Sweden
1,650
1,650
1,600
1,600
1,550
1,550
1,500
1,500
Norway
1,450
1,450
1,400
1,400
1,350
1,350
1,300
1,300
1,250
1980
1982
1984
1986
1988
1990
1992
THE EVIDENCE PRESENTED IN THIS ARTICLE confirms
that biases are inherent in data sources used to measure
hours worked. Data series of average annual hours actually worked based on normal and contractual hours concepts from administrative sources yield low measures of
hours worked, whereas series based on establishment and
labor force surveys provide relatively higher measures. The
highest levels of hours worked are estimated directly from
labor force surveys.
The OECD and BLS data series on average annual hours
actually worked per employed person reflect broad trends
in labor markets. The likelihood that hours worked in Japan are higher than reported, but still falling, is a reasonable conclusion, based on the differences in data sources
and changes in legislation in that country. The OECD data
series showing that U.S. workers work more hours per year,
on average, than their European counterparts appears to
be slightly inflated because of differences in sources and
methods, but the difference is nonetheless real. Flat trends
in hours worked in Anglophone countries reflect those
countries’ work regulations.
The cases of Japan and Sweden highlight how meas-
1994
1996
1998
2000
2002
2004
1,250
2006
ures of hours worked cannot be taken at face value. It is
unlikely that Japanese workers work fewer hours per year
than their U.S. counterparts when a majority of them
have a longer workweek and take fewer days of vacation.
That Swedish workers work considerably more hours than
Norway’s workers also seems doubtful.
The cross-country comparisons of hours worked for both
employees and those who are employed, using the same
method for different countries and different methods for
the same country, also provide a valuable lesson. These comparisons show that concepts, sources, and methods matter
in building comparable hours-worked data series across
countries. Because both survey-based data on hours actually
worked and direct estimation produce high hours-worked
estimates, and normal and contractual hours worked from
administrative data produce low hours-worked estimates, it
is important that any data series be transparent in describing sources and methods used in preparing estimates.
The international comparison of hours-worked data,
like most international comparisons, is subject to the constraint that national statistics are developed primarily to
serve a national purpose. Thus, the best source of hours
Monthly Labor Review • May 2009 27
Comparisons of Hours Worked
available for one country may not be for another. The
English-speaking and Asian OECD countries selected for
study here recently have made improvements in surveybased data to measure overtime and long work hours more
accurately. For example, in 1997, the redesigned Canadian
labor force survey expanded and revised its questions on
hours worked.47 Also, some European countries recently
revised their labor force surveys to get improved coverage of hours not worked. For example, Sweden introduced
questions to expand information on absences from work
in its 2005 labor force survey,48 and in March 2002 France
revised its labor force questionnaire for the European
Union, adding and clarifying questions on average and
contractual hours, reasons for days off, and the reference
period for usual hours worked.49
Improvements in data collection lead to revisions in
estimation methods. Statistics Norway is studying the use
of the now-continuous labor force survey for actual hours,
rather than normal hours, of work—partly because annual average hours based on labor force survey data are
nearly 12 percent higher than hours-worked figures based
on administrative data using the normal-hours-of-work
concept.50 Improvements in the collection and measurement of data on hours in a number of the OECD countries
should lead to improved harmonization of data among
these countries in the future. In the meantime, data on
average annual hours actually worked remain useful for
broad comparisons, but consumers of these data should
take heed: small differences between countries may tell a
misleading story.
Notes
ACKNOWLEDGMENT: The author thanks many people for their support, comments, and suggestions. Special thanks go to BLS economists
Jennifer Raynor, Richard Esposito, and Marie-Claire Sodergren; to
Judy Yang, BLS student trainee in economics; to Constance Sorrentino, for her always helpful guiding eye; and to Pascal Marianna of the
Organization for Economic Cooperation and Development (OECD),
whose ability to provide more detail on the methodology of the OECD
database proved invaluable in producing this article. The article also
benefited from the review of Omar Hardardson of Eurostat and Statistics Iceland; Sophie Lawrence of the International Labor Organization; Paul Swaim of the OECD; and Angus Maddison, Emeritus
Professor, Faculty of Economics, University of Groningen. The ideas
set forth in this article are solely the responsibility of the author and do
not necessarily reflect the views of the Bureau of Labor Statistics.
1
Available on the Internet at www.oecd.org/statistics (visited May 22,
2009).
2
See “Resolution concerning statistics of hours of work, adopted by the
Tenth International Conference of Labor Statisticians (October 1962),” on the
Internet at www.ilo.org/public/english/bureau/stat/download/res/hours.pdf
(visited May 22, 2009).
3
See www.redorbit.com/news/business/675442/vw_workers_agree_
to_33hour_workweek/index.html (visited May 15, 2009); www.iht.com/articles/2006/09/29/business/vw.php (visited May 22, 2009); www.justlanded.
com/english/Netherlands/Tools/Just-Landed-Guide/Jobs/Working-theNetherlands (visited May 22, 2009); and docs.minszw.nl/pdf/135/2007/135_
2007_1_18401.pdf (visited May 22, 2009).
4
The U.S. Current Population Survey calls this concept hours at work.
Ralf Hussmanns, Farhad Mehran, and Vijay Verma, Surveys of economically active population, employment, unemployment and underemployment: An ILO
manual on concepts and methods (Geneva, International Labor Office, 1990), p.
84.
5
6
Normal hours are agreed-upon hours based on collective-bargaining
agreements and legislation, whereas contractual hours constitute a fixed schedule established by individual agreement. Contractual hours are not covered in
this article, given that the concept is not used in the United States and that data
on contractual hours have only recently been considered as a possible source of
data on hours.
7
Jelle Visser, “Union membership statistics in 24 countries,” Monthly Labor Review, January 2006, pp. 38–49; on the Internet at www.bls.gov/opub/
28 Monthly Labor Review • May 2009
mlr/2006/01/art3full.pdf (visited May 15, 2009).
8
The text of the 2003 Fillon Law that documents this exception is at www.
legifrance.gouv.fr/affichTexte.do?cidTexte=LEGITEXT000005635050&date
Texte=20090515 (visited May 15, 2009).
9
Still, concern over proxy and nonresponse error remains. Statistical methods are used to test and correct for these errors.
10
Jean-Pierre Maynard, Lucy Chung, and Deborah Sunter (Statistics Canada), “Measuring hours actually worked,” paper presented at meeting of Paris
Group on Labor Compensation, Lisbon, Portugal, Sept. 29–Oct. 1, 2004.
11
Harley Frazis and Jay Stewart, “What can time-use data tell us about
hours of work?” Monthly Labor Review, December 2004, pp. 3–9.
12
See Gerard Ypma and Bart van Ark, “Employment and Hours Worked in
National Accounts: A Producer’s View on Methods and a User’s View on Applicability,” EU KLEMS working paper no. 10, 2006, on the Internet at www.euklems.
net/pub/no10(online).pdf (visited May 22, 2009). The national economy of a
given country has to do with the production of individuals and national businesses, no matter where they are located, within or outside of that country. The
domestic economy takes into account only production within the borders of the
country.
13
Adriana Mata Greenwood, “The hours that we work: the data we need, the
data we get,” ILO Bulletin of Labor Statistics, 2001–1, on the Internet at www.ilo.
org/public/english/bureau/stat/download/articles/2001-1.pdf (visited May 15,
2009).
14
OECD
Employment Outlook, 2004 (Paris, OECD, 2004), pp. 24–34.
General report, Seventeenth International Conference of Labor Statisticians, November 24–December 3, 2003 (Geneva, International Labor
Organization, 2003), p. 59, on the Internet at www.ilo.org/wcmsp5/groups/
public/---dgreports/---integration/---stat/documents/meetingdocument/
wcms_087585.pdf (visited May 15, 2009).
15
16
Ibid., p. 60. The Paris Group on Labor and Compensation contributed
in great part to the report of the 17th International Conference of Labor
Statisticians. The Paris Group on Labor and Compensation was established
in 1997 in response to an April 1996 recommendation by the U.N. Statistical Commission’s working party on international statistical programs, with the
aim of examining, assessing, and reconciling sources of information used to
measure the labor market and of contributing to improving concepts and their
implementation. In the past 10 years, meetings of this U.N. “City Group” have
addressed topics dealing with measurements of working time and hours worked.
Information on the Paris Group is at the French Statistical Institute (Institut
National des Statistiques et Études Économiques, or INSEE) Web site, www.
insee.fr/en/nom_def_met/colloques/citygroup/citygroup.htm (visited May
22, 2009), and the U.N. Web site, unstats.un.org/unsd/methods/citygroup/
paris.htm (visited May 22, 2009).
17
Ypma and van Ark, “Employment and Hours Worked in National
Accounts.”
18
The data sets use the data sources and adjustments based, respectively, on the
GDP report of June 2007 (on the Internet at www.bls.gov/ilc; visited May 22, 2009)
and on the data prepared for the statistical annex of OECD Employment Outlook, 2007
(Paris, OECD, 2007), on the Internet at www.oecd.org/dataoecd/29/27/38749309.
pdf (visited May 15, 2009). Further details on the national accounts methodology
for some of the countries in the OECD data set also are found in Ypma and van Ark,
“Employment and Hours Worked in National Accounts.”
19
See United Nations Statistics Division, System of National Accounts,
1993, chapter 17, on the Internet at unstats.un.org/unsd/sna1993/tocLev8.
asp?L1=17&L2=2 (visited May 22, 2009).
20
For more details on methods of compiling annual estimates, see Adriana Mata Greenwood, “The hours that we work: the data we need, the data
we get,” ILO Bulletin of Labor Statistics, 2001-1 (Geneva, International Labor
Office, 2001), on the Internet at www.ilo.org/global/What_we_do/Statistics/
lang--en/docName--WCMS_087906/index.htm (visited May 22, 2009); and
“Review of the experimental status of international comparisons of productivity—GDP per hour worked” (United Kingdom, National Statistics Office, Oct. 9,
2002), on the Internet at www.statistics.gov.uk/downloads/theme_economy/
review_of_hourly_ICP.pdf (visited May 22, 2009).
21
Comparative real gross domestic product per capita and per employed person:
16 countries, 1960–2007 (Bureau of Labor Statistics, Office of Productivity and
Technology, July 7, 2008), on the Internet at www.bls.gov/fls/flsgdp.pdf (visited May 22, 2009).
22
The OECD productivity database provides data on average annual hours
actually worked. For Belgium, as well as some other countries, data sources in
that database differ from those in the OECD Employment Outlook database. The
BLS measure for Belgium from the OECD productivity database is based on administrative data.
23
See Table F in the Statistical Annex of OECD Employment Outlook, 2007,
p. 263. Data also are updated annually online at OECD.stat (visited May 22,
2009).
Ypma and van Ark, “Employment and Hours Worked in National Accounts,” pp. 15–16.
24
25
See table A–1 for the underlying data used in the comparison. Data for
this article were the most current at that time, but have since been updated.
26
See “Supplementary Information Used to Calculate Hours Data for Major Sector Productivity and Costs Series” (Bureau of Labor Statistics, Jan. 17,
2007), on the Internet at www.bls.gov/lpc/hoursdatainfo.htm (visited May 22,
2009).
27
Mary Bowler and Teresa Morisi, “Understanding the employment measures from the CPS and CES survey,” Monthly Labor Review, February 2006, pp.
23–38; on the Internet at www.bls.gov/opub/mlr/2006/02/art2full.pdf (visited May 22, 2009).
28
Ypma and van Ark, “Employment and Hours Worked in National
Accounts.”
29
John Owen, “Work-time reduction in the U.S. and Western Europe,”
Monthly Labor Review, December 1988, pp. 41–45, on the Internet at www.bls.
gov/opub/mlr/1988/12/rpt3full.pdf (visited May 22, 2009).
30
OECD
Employment Outlook 2004, pp. 24–34.
For a more complete review of industrial relations in the countries covered, see William K. Roche, Brian Fynes, and Terri Morrissey, “Working time
and employment: A review of international evidence,” International Labor Review, vol. 135, no. 2 (1996), pp. 129–57; Gerhard Bosch, Peter Dawkins, and
François Michon, Times are changing: working time in 14 industrialised countries
(Geneva, International Institute for Labor Studies, 1994); Jon C. Messenger
(ed.), Working Time and Workers’ Preferences in Industrialized Countries, Finding the Balance (New York, Routledge, 2004); Sangheon Lee, “Working-hour
gaps: trends and issues,” in Messenger, Working Time and Workers’ Preferences,
pp. 29–59; and Greg Bamber and Russell Lansbury (eds.), International and
Comparative Employment Relations: A study of industrialised market economies, 3d
31
ed. (St. Leonards, U.K., Allen & Unwin, 1998).
32
See “Restriction on Dismissal, Holidays & Leave” (South Korean Ministry of Labor, Apr. 29, 2009), on the Internet at english.molab.go.kr/english/
Working/Standard_Restriction.jsp (visited May 22, 2009); and Kazuya Ogura,
“Annual paid leave in Japan,” Japan Labor Review, Spring 2004, pp. 100–08, on
the Internet at www.jil.go.jp/english/documents/JLR02_ogura.pdf (visited
May 22, 2009).
33
Prior to 1998, when the United Kingdom began complying with the European Union’s Working Time Directive (discussed in detail shortly), U.K. labor
laws had a higher ceiling on maximum weekly hours. The United Kingdom consistently has had higher average actual and usual weekly hours worked, compared
with its other European neighbors. Despite the legislative changes wrought by
the European Union’s directive, many companies in the United Kingdom use the
“individual opt-out” clause of the directive to loosen restrictions placed on maximum work hours. The limit was 60 hours a week before the country revised the
labor law in 1998; it has since been reduced to 48. (See Catherine Barnard, Simon
Deakin, and Richard Hobbs, “Opting out of the 48-hour week: employer necessity or individual choice? An empirical study of the operation of article 18(1)(b)
of the Working Time Directive in the UK,” Industrial Law Journal, December
2003, pp. 223–52.)
34
“Directive 2003/88/EC of the European Parliament and of the Council
of 4 November 2003 concerning certain aspects of the organisation of working time” (European Union, Nov. 18, 2003), on the Internet at www.lex.unict.
it/eurolabor/en/documentation/dirapprovate/dir(03)-88en.pdf (visited May
15, 2009). Recent information on efforts to revise the 2003 directive are in
Stefan Lücking, “Political agreement reached on working time and temporary
work directives” (Munich, European Industrial Relations Observatory On-line,
Oct. 15, 2008), on the Internet at www.eurofound.europa.eu/eiro/2008/07/
articles/eu0807049i.htm (visited May 15, 2009).
35
See Working Hours (Adjustment) Act—Netherlands (Geneva, International
Labor Organization, June 20, 2002), on the Internet at www.ilo.org/public/
english/employment/gems/eeo/law/nether/l_wa.htm (visited May 15, 2009);
and Sheri Todd, Improving work-life balance—what are other countries doing? The
Netherlands (Ottawa, Labor Program, Human Resources and Skills Development Canada, 2004), on the Internet at www.hrsdc.gc.ca/eng/lp/spila/wlb/
pdf/improving-work-life-balance.pdf (visited May 15, 2009).
36
For a more complete review of trends in industrial relations and hours in
the countries covered herein, see Bamber and Lansbury, International and Comparative Employment Relations; Gerhard Bosch, “Working time tendencies and
emerging issues,” International Labor Review, vol. 138, no. 2 (1999), pp. 131–49;
Bosch, Dawkins, and Michon, Times are changing; Messenger, Working Time and
Workers’ Preferences; Lee, “Working-hour gaps”; Roche, Fynes, and Morrisey,
“Working time and employment”; “Australian social trends, 1999” (Canberra,
Australian Bureau of Statistics, June 24, 1999), and “Australian social trends,
2002” (Canberra, Australian Bureau of Statistics, June 4, 2002), special sections
on employment arrangements, document 4102.0, on the Internet at www.abs.gov.
au/AUSTATS/abs@.nsf/mf/4102.0?opendocument?utm_id=LN (go to “Past and
Future Releases”) (visited May 15, 2009); “Working hours: latest trends and policy
initiatives,” in OECD Employment Outlook, 1998 (Paris, OECD, 1998), pp. 153–88;
“Recent labor market developments and prospects,” in OECD Employment Outlook,
1994 (Paris, OECD, 2004), pp. 17–60; and Sheri Todd, “Improving Work-Life Balance—What Are Other Countries Doing?” (Ottawa, Human Resources and Skills
Development Canada, 2004), on the Internet at www.hrsdc.gc.ca/en/lp/spila/
wlb/pdf/improving-work-life-balance.pdf (visited May 15, 2009).
37
See Yoichi Shimada, “Future of the system of regulations on working hours
for white-collar workers in Japan,” Japanese Journal of Labor Studies, October 2003,
abstract on the Internet at www.jil.go.jp/english/ejournal/2003.html (visited
May 15, 2009); Lee, “Working-hour gaps”; and Kazuya Ogura and Takashi Fujimoto, Empirical Study on Long Working Hours and Unpaid Working Time in Japan
(Tokyo, Japan Institute for Labor Policy and Training, research report no. 22,
March 2005), on the Internet at www.jil.go.jp/english/reports/jilpt_01.html.
38
Death from overwork is an occupational hazard when one dies after
having worked more than 24 continuous hours or 16 hours daily for 7 consecutive days. (See Takeshi Mizunoya, “An International Comparison of Unpaid
Overtime Work Among Industrialized Countries,” originally published in
Japanese in Journal of the Society of Economic Statistics, no. 81, 2001, on the
Internet in English at www.ilo.org/public/english/bureau/stat/download/
articles/2002-3.pdf (visited May 22, 2009).)
Monthly Labor Review • May 2009 29
Comparisons of Hours Worked
39
Data are from the Employment Status Survey, a representative household survey that collects information on type and hours of work.
40
Susumu Noda, “Legal Issues on Long-Term Leave: Conflicting Structure
of Leave Benefits,” Japan Labor Review, summer 2006, pp. 55–73, on the Internet at www.jil.go.jp/english/documents/JLR11_noda.pdf (click on “English”
to view the English-language document) (visited May 22, 2009).
41
Mizunoya, “International Comparison of Unpaid Overtime Work.”
42
One such policy was the special part-time pension scheme that allowed
people to work and, at the same time, draw a pension. The plan was phased out
beginning in 1994 and was eliminated in 2001 (only to be replaced in 2003 by
a similar scheme among state employers). (See Eskil Wadensjö, “Part-time pensions and part-time work in Sweden,” Institute for the Study of Labor Discussion Paper No. 2273 (Bonn, IZA, August 2006), on the Internet at ftp://repec.
iza.org/RePEc/Discussionpaper/dp2273.pdf (visited May 22, 2009).)
43
European industrial relations observatory on-line, “2004 Annual Review
for Sweden,” on the Internet at eurofound.europa.eu/eiro/2005/01/feature/
se0501102f.htm (visited May 22, 2009).
44
David Rae, “How to Reduce Sickness Absences in Sweden: Lessons
from International Experience,” OECD Economics Department Working Paper
No. 442, in Economic Survey of Sweden 2005 (Paris, OECD, 2005).
45
Mireille Bruyère and Odile Chagny, “Comparaisons internationales des
durées du travail.”
30
Monthly Labor Review • May 2009
OECD Employment Outlook, 2004.
Statistics Canada, “Labour Force Survey, Detailed Information for April
2006,” on the Internet at www.statcan.gc.ca/cgi-bin/imdb/p2SV.pl?Function
=getSurvey&SurvId=3701&SurvVer=0&InstaId=13986&InstaVer=67&
DispYear=2006&SDDS=3701&lang=en&db=imdb&adm=8&dis=2 (visited
May 22, 2009).
48
Simon Bolling, “Hours of absence, overtime and hours actually worked,”
paper prepared for the Paris group meeting, Lisbon, September 2004 (Statistics Sweden, 20044), on the Internet at www.insee.fr/en/insee-statistiquepublique/colloques/citygroup/pdf/S-2-Paper_Statistics-Sweden_040916.
pdf (visited May 22, 2009).
49
Stephane Lhermitte, “Measurement of working time: comparison between the new and the former labour force surveys in France,” paper prepared
for the Paris Group Meeting, London, September 2003, on the Internet at
www.insee.fr/en/insee-statistique-publique/colloques/citygroup/pdf/
France-comparison-ALFS-CLFS.pdf (visited May 22, 2009).
46
47
50
See Helge Naesheim, “Statistics on working time, report from Norway,”
paper prepared for the Paris Group meeting, London, September 4–5, 2003 (Statistics Norway, July 2, 2003), on the Internet at www.insee.fr/en/insee-statistiquepublique/colloques/citygroup/pdf/Norway-general.pdf; and “Definition and
measurement of annual hours,” paper prepared for the Paris group meeting, Lisbon,
September 2004 (Statistics Norway, Aug. 28, 2004), on the Internet at www.insee.
fr/en/insee-statistique-publique/colloques/citygroup/pdf/Norway-3-countrypaper.pdf (visited May 22, 2009).
Table A-1.
Year
1980……..
1981……..
1982……..
1983……..
1984……..
1985……..
1986……..
1987……..
1988……..
1989……..
1990……..
1991……..
1992……..
1993……..
1994……..
1995…….
1996……..
1997……..
1998……..
1999……..
2000……..
2001……..
2002……..
2003……..
2004……..
2005……..
2006……..
Average annual hours actually worked, all employed persons, 13 countries, 1980–2006
United States
Canada
OECD
BLS
OECD
BLS
1,819
1,809
1,806
1,825
1,843
1,841
1,833
1,838
1,842
1,855
1,836
1,823
1,826
1,835
1,842
1,849
1,840
1,850
1,852
1,853
1,841
1,819
1,814
1,806
1,809
1,804
1,804
1,824
1,807
1,795
1,804
1,820
1,825
1,806
1,809
1,823
1,837
1,818
1,810
1,802
1,819
1,836
1,855
1,852
1,865
1,879
1,887
1,864
1,841
1,822
1,795
1,797
1,793
1,792
1,802
1,801
1,784
1,780
1,782
1,790
1,789
1,797
1,807
1,801
1,788
1,767
1,759
1,763
1,780
1,775
1,784
1,767
1,767
1,769
1,768
1,762
1,744
1,734
1,752
1,738
1,738
1,807
1,807
1,787
1,784
1,788
1,802
1,799
1,809
1,828
1,822
1,804
1,780
1,779
1,805
1,821
1,810
1,826
1,809
1,804
1,807
1,802
1,793
1,775
1,761
1,779
1,769
1,766
Germany 1
OECD
1980…….........................................
1981..................................................
1982..................................................
1983…….........................................
1984…….........................................
1985..................................................
1986..................................................
1987..................................................
1988..................................................
1989..................................................
1990…….........................................
1991..................................................
1992..................................................
1993…….........................................
1994..................................................
1995..................................................
1996…….........................................
1997…….........................................
1998..................................................
1999..................................................
2000…….........................................
2001…….........................................
2002…….........................................
2003..................................................
2004…….........................................
2005…….........................................
2006…….........................................
1
1,751
1,729
1,718
1,705
1,694
1,671
1,652
1,629
1,624
1,601
1,578
1,548
1,566
1,550
1,547
1,534
1,518
1,509
1,503
1,492
1,473
1,458
1,445
1,439
1,442
1,437
1,436
Japan
OECD
2,121
2,106
2,104
2,095
2,108
2,093
2,097
2,096
2,092
2,070
2,031
1,998
1,965
1,905
1,898
1,884
1,892
1,865
1,842
1,810
1,821
1,809
1,798
1,799
1,787
1,775
1,784
South Korea
Belgium
Denmark
France
BLS
OECD
BLS
OECD
BLS
OECD
BLS
OECD
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
1,924
1,894
1,872
1,851
1,865
1,846
1,832
1,832
1,836
1,823
1,832
2,876
2,892
2,905
2,923
2,919
2,894
2,923
2,892
2,846
2,742
2,688
2,672
2,650
2,667
2,651
2,658
2,648
2,592
2,496
2,502
2,520
2,506
2,465
2,434
2,394
2,354
2,305
2,803
2,787
2,907
2,881
2,865
2,865
2,803
2,881
2,902
2,834
2,798
2,777
2,730
2,740
2,725
2,730
2,720
2,673
2,605
2,621
2,631
2,621
2,590
2,553
2,532
2,501
2,491
–
–
–
1,768
1,793
1,799
1,779
1,763
1,750
1,741
1,754
1,715
1,693
1,646
1,646
1,674
1,646
1,660
1,672
1,581
1,554
1,577
1,579
1,575
1,549
1,565
1,571
1,690
1,667
1,653
1,659
1,630
1,635
1,624
1,635
1,630
1,612
1,601
1,590
1,594
1,552
1,551
1,549
1,547
1,566
1,555
1,545
1,545
1,547
1,548
1,542
1,522
1,534
1,534
1,646
1,617
1,627
1,622
1,615
1,601
1,603
1,568
1,549
1,532
1,518
1,513
1,532
1,531
1,494
1,499
1,495
1,512
1,528
1,539
1,554
1,562
1,556
1,552
1,558
1,574
1,577
1,659
1,632
1,642
1,638
1,633
1,619
1,622
1,587
1,569
1,552
1,539
1,534
1,554
1,555
1,548
1,541
1,531
1,544
1,559
1,568
1,581
1,586
1,578
1,576
1,582
1,597
1,608
1,842
1,808
1,765
1,758
1,746
1,731
1,720
1,716
1,718
1,699
1,702
1,694
1,695
1,682
1,675
1,651
1,655
1,649
1,637
1,630
1,591
1,578
1,536
1,530
1,555
1,559
1,564
Netherlands
BLS
OECD
BLS
1,698
1,683
1,681
1,679
1,672
1,645
1,638
1,631
1,629
1,605
1,567
1,548
1,566
1,550
1,547
1,534
1,518
1,509
1,503
1,492
1,473
1,458
1,445
1,439
1,442
1,437
1,436
–
–
–
–
–
–
–
1,540
1,509
1,497
1,504
1,471
1,447
1,419
1,411
1,391
1,421
1,414
1,400
1,381
1,372
1,372
1,348
1,363
1,362
1,375
1,391
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
1,516
1,524
1,513
1,497
1,492
1,490
1,490
1,472
1,463
1,460
1,448
1,457
Norway
OECD
1,580
1,570
1,559
1,553
1,548
1,542
1,538
1,511
1,513
1,511
1,503
1,500
1,510
1,507
1,505
1,488
1,483
1,478
1,476
1,473
1,455
1,429
1,414
1,399
1,417
1,421
1,407
Spain
Sweden
BLS
1,828
1,790
1,736
1,731
1,720
1,707
1,703
1,702
1,707
1,688
1,702
1,694
1,695
1,682
1,675
1,651
1,655
1,649
1,637
1,630
1,591
1,578
1,536
1,531
1,558
1,550
1,548
United Kingdom
BLS
OECD
BLS
OECD
BLS
OECD
BLS
1,580
1,570
1,559
1,553
1,548
1,542
1,538
1,511
1,513
1,510
1,503
1,500
1,510
1,507
1,505
1,488
1,483
1,478
1,476
1,474
1,455
1,429
1,414
1,399
1,417
1,421
1,407
2,003
1,968
1,946
1,912
1,865
1,855
1,847
1,838
1,835
1,822
1,824
1,833
1,825
1,816
1,816
1,815
1,811
1,813
1,834
1,817
1,815
1,817
1,798
1,800
1,799
1,769
1,764
1,753
1,727
1,727
1,696
1,660
1,643
1,643
1,595
1,600
1,608
1,608
1,600
1,596
1,587
1,584
1,592
1,592
1,602
1,614
1,629
1,653
1,649
1,647
1,632
1,618
1,599
1,594
1,517
1,508
1,523
1,532
1,534
1,538
1,536
1,546
1,566
1,565
1,561
1,548
1,565
1,582
1,621
1,626
1,635
1,639
1,638
1,647
1,625
1,603
1,580
1,562
1,585
1,588
1,583
1,517
1,508
1,523
1,532
1,534
1,538
1,536
1,546
1,566
1,565
1,561
1,548
1,565
1,582
1,621
1,626
1,635
1,639
1,638
1,647
1,625
1,603
1,580
1,562
1,585
1,588
1,583
1,773
1,715
1,730
1,717
1,733
1,766
1,768
1,758
1,798
1,786
1,771
1,767
1,732
1,726
1,740
1,743
1,742
1,740
1,734
1,723
1,711
1,714
1,696
1,677
1,672
1,676
1,669
1,793
1,747
1,743
1,717
1,726
1,735
1,726
1,720
1,732
1,745
1,745
1,726
1,701
1,701
1,692
1,715
1,715
1,715
1,711
1,702
1,686
1,689
1,673
1,665
1,658
1,661
1,656
Data prior to 1991 are for West Germany.
Monthly Labor Review • May 2009 31
JOLTS Annual Story
Job openings and hires
decline in 2008
Downward trends in job openings, hires, and quits
were geographically widespread and affected almost
every industry
Katherine Klemmer
Katherine Klemmer is an
economist in the Division
of Administrative Statistics and Labor Turnover,
Office of Employment
and Unemployment
Statistics, Bureau of
Labor Statistics. Klemmer.
Katherine@bls.gov
32
J
ob openings and hires declined during
2008. The number of job openings, a stock
measure referenced to the last day of the
month, dropped from 4.4 million, seasonally
adjusted, in December 2007 to 3.2 million in
December 2008 after trending down steadily
over the year. Hires, which is a measure of
worker flows, also trended down steadily over
the year. Hires dropped from 5.1 million, seasonally adjusted, in December 2007 to a low
of 4.2 million in November 2008 and then increased to 4.5 million in December 2008. Job
openings and hires also declined in 2007.1
The total separations level which was 5.0
million, seasonally adjusted, in December
2007, fluctuated over the course of the year
reaching a high of 5.2 million in April 2008
and returned to 5.0 million in December 2008.
The level of layoffs and discharges increased
from 1.8 million in December 2007 to 2.4
million in December 2008 and the level of
quits dropped from 2.9 million in December
2007 to 2.1 million in December 2008.
In December 2008, the National Bureau of
Economic Research announced that the current recession had begun in December 2007.2
The downward trend in job openings, hires,
and quits, and the upward trend in layoffs and
discharges are consistent with recessionary
trends in other economic statistics. Recessionary trends are evident in increasing unemployment and declining employment levels. For
example, the unemployment rate, 4.9 percent
in December 2007, climbed to 7.2 by of December 2008.3 Also, since December 2007,
Monthly Labor Review • May 2009
nonfarm employment dropped from 138 million to 135 million for the month of December
2008, a net employment loss of approximately
3 million over the course of 2008.4 Chart 1
shows JOLTS total private job openings compared to CES total private employment levels
since December 2000. The job openings leveled off and began to fall prior to December
2007 when employment levels began to fall.
The Job Openings and Labor Turnover
Survey program (JOLTS) measures job openings, hires, and separations on a monthly basis
by industry and geographic region. The JOLTS
statistics gauge labor demand by collecting
data monthly from a sample of approximately
16,000 nonfarm business establishments and
is aligned monthly with the BLS Current Employment Statistics (CES) program. Published
JOLTS data are available from December 2000
forward. In 2008, JOLTS added seasonally-adjusted arts, entertainment, and recreation series
for all data types and seasonally-adjusted layoffs and discharges for the Total Nonfarm, Total Private, and Government industries. Also,
the entire JOLTS data series was retabulated on
the basis of new methodology concurrent with
the release of the January 2009 preliminary estimates.5 Unless otherwise noted, JOLTS data
used in this report are seasonally adjusted.
National level trends: job openings
The job openings rate at the national level
experienced a downward trend for 2008 and
Chart 1.
JOLTS total private job openings and CES total private employment, seasonally adjusted, December
2000–December 2008
Employment
(in thousands)
Job openings
(in thousands)
117,000
5,000
4,750
116,000
Employment
4,500
115,000
4,250
114,000
4,000
113,000
3,750
112,000
3,500
111,000
Job openings
3,250
110,000
3,000
109,000
2,750
108,000
2,500
107,000
2,250
106,000
2,000
Dec 2000
Dec 2001
Dec 2002
Dec 2003
Dec 2004
Dec 2005
Dec 2006
Dec 2007
105,000
Dec 2008
NOTE: Shaded regions represent recessions as designated by the National Bureau of Economic Research.
reached a low in December 2008 of 2.3 percent. Fewer job
openings mean fewer opportunities for job-seekers to find
employment. An economic expansion is characterized by
a rising number of job openings and falling unemployment while an economic contraction is characterized by
rising unemployment and a falling number of job openings. Chart 2 illustrates the inverse relationship between
job openings and unemployment.6 As the economy began
to weaken prior to the beginning of the current recession,
unemployment climbed while job openings dropped.
The ratio between unemployment and job openings is
an indication of how the number of unemployed persons
per job opening changes over time. The ratio increased
from mid-2006 where it hovered around 1.5 unemployed
persons per job opening to a ratio of approximately 3.5
unemployed persons per job opening in December 2008.7
(See chart 3.)
National level trends: hires
Hires are defined as the total number of additions to the
payroll occurring at any time during the reference month.
In November 2008, hires reached a series low of 4.2
million. The series declined from a high of 5.0 million
in February 2008 to 4.2 million in November 2008 and
then increased in December 2008 to 4.5 million hires. The
downward trend that concluded in November 2008 began
in mid-2006. The annual hires rate dropped to a series low
of 41.2 percent in 2008. (See table 1.)
When comparing hires to total separations, it is indicative of an economic contraction when total separations
exceed hires. For 11 consecutive months, from February 2008 through December 2008, separations exceeded
hires. Prior to that point, hires exceeded separations in 49
of the 53 months from September 2003 through January
2008. None of the four exceptions occurred in consecutive
months. (See chart 4.)
National level trends: total separations
Total separations is defined as the total number of terminations of employment occurring at any time during the
reference month and includes quits, layoffs and discharges, and other separations such as retirements. In 2008,
monthly total separations peaked in April at 5.2 million,
dropped to 4.8 million in July, and then trended upward
Monthly Labor Review • May 2009
33
JOLTS Annual Story
Chart 2.
JOLTS job openings rate and CPS unemployment rate, seasonally adjusted, December 2000–
December 2008
Job openings
rate
Unemployment
rate
4.0
7.5
7.0
3.5
Unemployment rate
6.5
6.0
3.0
5.5
5.0
2.5
4.5
Job openings rate
4.0
2.0
3.5
3.0
1.5
Dec 2000
Dec 2001
Dec 2002
Dec 2003
Dec 2004
Dec 2005
Dec 2006
Dec 2007
Dec 2008
NOTE: Shaded regions represent recessions as designated by the National Bureau of Economic Research.
Chart 3.
Ratio of CPS unemployment to JOLTS job openings, seasonally adjusted, December 2000–December 2008
Unemployed workers
per job opening
Unemployed workers
per job opening
3.5
3.5
3.0
3.0
2.5
2.5
2.0
2.0
1.5
1.5
1.0
1.0
Dec 2000
Dec 2001
Dec 2002
Dec 2003
Dec 2004
Dec 2005
Dec 2006
Dec 2007
NOTE: Shaded regions represent recessions as designated by the National Bureau of Economic Research.
34
Monthly Labor Review • May 2009
Dec 2008
Table 1.
Annual hires rates 1 and levels 2
Rates (percent)
Industry and region
2007
2008
Change
Total...........................................................................
46.1
41.2
– 4.9
Levels (in thousands)
Percent
2007
2008
Change
change
–10.6
63,381
56,496
Percent
change
–6,885
–10.9
–10.2
10.1
– 4.0
–20.9
–22.3
–19.1
–12.2
–14.5
–13.6
Industry
Total private............................................................
Natural resources and mining......................
Construction.......................................................
Manufacturing...................................................
Durable goods................................................
Nondurable goods........................................
Trade, transportation, and utilities.............
Wholesale trade.............................................
Retail trade.......................................................
Transportation, warehousing, and
utilities..........................................................
Information.........................................................
Financial activities.............................................
Finance and insurance.................................
Real estate and rental and leasing..........
Professional and business services.............
Education and health services.....................
Educational services.....................................
Health care and social assistance............
Leisure and hospitality....................................
Arts, entertainment, and recreation.......
Accommodations and food services......
Other services.....................................................
51.0
47.9
63.1
33.3
30.5
38.1
49.6
36.8
58.8
46.1
– 4.9
– 9.6
58,833
52,807
49.4 1.5 3.1 347 382
64.0 .9 1.4 4,811 4,618
27.2
– 6.1
–18.3 4,617 3,651
24.6
– 5.9
–19.3 2,687 2,089
31.5
– 6.6
–17.3 1,930 1,561
44.0
– 5.6
–11.3
13,215
11,602
31.7
– 5.1
–13.9 2,212 1,892
51.3
– 7.5
–12.8 9,121 7,876
–6,026
35
–193
–966
–598
–369
–1,613
–320
–1,245
36.9
32.4
38.0
34.1
49.3
64.0
35.1
30.9
35.9
83.4
83.2
83.4
47.3
36.2
– .7
– 1.9 1,881 1,833
27.2
– 5.2
–16.0 983 814
32.5
– 5.5
–14.5 3,158 2,649
28.3
– 5.8
–17.0 2,089 1,704
44.4
– 4.9
– 9.9 1,070 945
56.9
– 7.1
–11.1
11,475
10,112
34.8
– .3
– .9 6,438 6,553
30.9 .0 .0 910 939
35.5
– .4
– 1.1 5,529 5,616
74.0
– 9.4
–11.3
11,194 9,965
74.8
– 8.4
–10.1 1,639 1,473
73.9
– 9.5
–11.4 9,554 8,492
44.5
– 2.8
– 5.9 2,600 2,462
–48
– 2.6
–169
–17.2
–509
–16.1
–385
–18.4
–125
–11.7
–1,363
–11.9
115 1.8
29 3.2
87 1.6
–1,229
–11.0
–166
–10.1
–1,062
–11.1
–138
– 5.3
Government...........................................................
Federal..................................................................
State and local....................................................
20.5
30.9
19.0
16.4
12.1
17.0
– 4.1
–18.8
– 2.0
–20.0 4,549 3,688
–60.8 844 335
–10.5 3,705 3,351
–861
–509
–354
–18.9
–60.3
– 9.6
–773
–3,514
–1,549
–1,053
– 7.7
–14.4
–10.9
– 7.1
Region 3
Northeast.............................................................
South.....................................................................
Midwest................................................................
West.......................................................................
39.0
49.0
45.4
47.8
36.0
42.1
40.7
44.6
– 3.0
– 6.9
– 4.7
– 3.2
1
The annual hires rate is the number of hires during the entire year as a
percent of annual average employment.
2 The annual hires level is the total number of hires during the entire
year.
3
The States (including the District of Columbia) that comprise the regions
are: Northeast: Connecticut, Maine, Massachusetts, New Hampshire, New
to 5.0 million in December.
The annual total separations rate reached a series low
of 43.3 percent in 2008. The annual total separations rate
is the sum of total separations levels for the 12 months of
the year divided by the annual average employment level
multiplied by 100. This annual rate has declined for the
last three years. However, while annual total separations
rates have decreased over the past three years, the relative
proportion of annual layoffs and discharges within total
– 7.7
–14.1
–10.4
– 6.7
10,010 9,237
24,360
20,846
14,239
12,690
14,774
13,721
Jersey, New York, Pennsylvania, Rhode Island, and Vermont; South: Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia, Kentucky,
Louisiana, Maryland, Mississippi, North Carolina, Oklahoma, South Carolina,
Tennessee, Texas, Virginia, and West Virginia; Midwest: Illinois, Indiana, Iowa,
Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio,
South Dakota, and Wisconsin; West: Alaska, Arizona, California, Colorado,
Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington,
and Wyoming.
separations has increased. Layoffs and discharges rose
from 34 percent of total separations in 2006 (prior to
the current economic downturn) to 41 percent of total
separations in 2008. The quits rate dropped from a high
of 58 percent of total separations in 2006 to 52 percent
of total separations in 2008, while the other separations
rate slipped from 8 percent of total separations in 2006
to 7 percent of total separations in 2008. (See tables 2–5.)
Note the difference between the composition of total
Monthly Labor Review • May 2009
35
JOLTS Annual Story
Table 2. Annual total separations rates 1 and levels 2
Rates (percent)
Levels (in thousands)
Industry and region
Percent
Percent
2007
2008
Change
2007
2008
Change
change
change
Total.................................................................................. 45.1
Industry
43.3
– 1.8
– 4.0
62,104
59,343
–2,761
– 4.4
Total private................................................................ 50.1
48.7
– 1.4
– 2.8
57,860
55,808
–2,052
– 3.5
Natural resources and mining.......................... 43.0
43.2 .2 .5 311 334
23 7.4
Construction........................................................... 65.2
72.7 7.5
11.5 4,971 5,242
271 5.5
Manufacturing....................................................... 35.1
33.3
– 1.8
– 5.1 4,871 4,475
–396
– 8.1
Durable goods..................................................... 32.7
31.8
– .9
– 2.8 2,880 2,695
–185
– 6.4
Nondurable goods............................................. 39.2
35.9
– 3.3
– 8.4 1,988 1,780
–208
–10.5
Trade, transportation, and utilities................. 48.4
47.3
– 1.1
– 2.3
12,889
12,488
–401
– 3.1
Wholesale trade.................................................. 35.3
35.1
– .2
– .6 2,126 2,093
–33
– 1.6
Retail trade............................................................ 57.5
54.9
– 2.6
– 4.5 8,928 8,424
–504
– 5.6
Transportation, warehousing, and
utilities.................................................................. 36.0
38.9 2.9 8.1 1,835 1,970
135 7.4
Information............................................................. 32.9
29.9
– 3.0
– 9.1 999 897
–102
–10.2
Financial activities................................................. 39.3
35.2
– 4.1
–10.4 3,259 2,870
–389
–11.9
Finance and insurance...................................... 35.6
30.9
– 4.7
–13.2 2,181 1,856
–325
–14.9
Real estate and rental and leasing................ 49.7
47.6
– 2.1
– 4.2 1,078 1,013
–65
– 6.0
Professional and business services................. 62.3
60.9
– 1.4
– 2.2
11,183
10,823
–360
– 3.2
Education and health services......................... 32.3
32.1
– .2
– .6 5,911 6,055
144 2.4
Educational services.......................................... 28.9
28.3
– .6
– 2.1 850 858
8 .9
Health care and social assistance.................. 32.9
32.9 .0 .0 5,060 5,199
139 2.7
Leisure and hospitality........................................ 81.5
75.5
– 6.0
– 7.4
10,938
10,158
–780
– 7.1
Arts, entertainment, and recreation............ 81.3
76.6
– 4.7
– 5.8 1,601 1,509
–92
– 5.7
Accommodations and food services........... 81.5
75.3
– 6.2
– 7.6 9,341 8,648
–693
– 7.4
Other services......................................................... 46.0
44.6
– 1.4
– 3.0 2,529 2,467
–62
– 2.5
Government................................................................. 19.1
15.7
– 3.4
–17.8 4,242 3,534
–708
–16.7
Federal...................................................................... 30.2
11.6
–18.6
–61.6 825 322
–503
–61.0
State and local........................................................ 17.6
16.3
– 1.3
– 7.4 3,420 3,210
–210
– 6.1
Region 3
Northeast................................................................. 37.1
38.0 .9 2.4 9,530 9,742
212 2.2
South......................................................................... 48.0
44.2
– 3.8
– 7.9
23,852
21,891
–1,961
– 8.2
Midwest.................................................................... 44.2
41.8
– 2.4
– 5.4
13,862
13,024
–838
– 6.0
West........................................................................... 48.1
47.8
– .3
– .6
14,857
14,686
–171
– 1.2
1
The annual total separations rate is the number of total separations
tions during the entire year.
during
the entire year as a percent of annual average employment.
3 See footnote 3, Table 1.
2
The annual total separations level is the total number of total separa-
separations in 2006, prior to the economic downturn, and
the composition of total separations in 2008, subsequent
to the economic downturn, as shown in chart 5.
With the exception of 2007, the JOLTS total separations series has trended closely with CES employment
annually, increasing and decreasing in a procyclical
manner in conjunction with increases and decreases in
employment levels.8 Total separations are procyclical
with employment in most instances because quits are
also procyclical. In 2007, however, the quits component
36
Monthly Labor Review • May 2009
of total separations decreased while total employment
continued to increase and the layoffs and discharges
component of total separations increased.
Quits. Quits are voluntary separations by employees, excluding retirements. During 2008, quits steadily declined
from a high of 2.9 million in January to a low of 2.1 million in December. The downward trend in quits can be
explained by worker behavior during an economic slowdown. Individuals are less willing to quit their current job
Table 3. Annual quits rates 1 and levels 2
Industry and region
Rates (percent)
Levels (in thousands)
2007
2008
Change
Total.........................................................................
25.5
22.6
– 2.9
Industry
Total private........................................................
Natural resources and mining..................
Construction...................................................
Manufacturing...............................................
Durable goods............................................
Nondurable goods....................................
Trade, transportation, and utilities.........
Wholesale trade..........................................
Retail trade...................................................
Transportation, warehousing, and
utilities.........................................................
Information.....................................................
Financial activities........................................
Finance and insurance.............................
Real estate and rental and leasing.......
Professional and business services........
Education and health services..............
Educational services.................................
Health care and social assistance...........
Leisure and hospitality...............................
Arts, entertainment, and recreation...
Accommodations and food services..
Other services................................................
– 3.1
– 1.1
– 1.8
– 3.7
– 3.6
– 4.2
– 2.8
– 2.7
– 4.1
Percent
2007
2008
Change
change
–11.4
35,103
31,004
–4,099
Percent
change
–11.7
28.7
25.3
24.9
18.1
16.2
21.5
28.7
19.5
35.8
25.6
24.2
23.1
14.4
12.6
17.3
25.9
16.8
31.7
–10.8
33,095
29,344
– 4.3 183 187
– 7.2 1,903 1,664
–20.4 2,512 1,929
–22.2 1,423 1,072
–19.5 1,088 855
– 9.8 7,652 6,824
–13.8 1,170 999
–11.5 5,553 4,861
–3,751
–11.3
4 2.2
–239
–12.6
–583
–23.2
–351
–24.7
–233
–21.4
–828
–10.8
–171
–14.6
–692
–12.5
18.2
19.2
22.8
22.8
23.1
32.3
20.4
14.1
21.6
55.4
32.1
59.4
25.5
19.1 .9 4.9 927 965
15.5
– 3.7
–19.3 581 465
18.8
– 4.0
–17.5 1,896 1,528
17.4
– 5.4
–23.7 1,400 1,047
22.6
– .5
– 2.2 500 481
28.9
– 3.4
–10.5 5,797 5,145
18.7
– 1.7
– 8.3 3,732 3,531
12.7
– 1.4
– 9.9 414 386
19.9
– 1.7
– 7.9 3,315 3,148
49.7
– 5.7
–10.3 7,443 6,685
28.9
– 3.2
–10.0 632 570
53.2
– 6.2
–10.4 6,810 6,115
25.1
– .4
– 1.6 1,400 1,387
38 4.1
–116
–20.0
–368
–19.4
–353
–25.2
–19
– 3.8
–652
–11.2
–201
– 5.4
–28
– 6.8
–167
– 5.0
–758
–10.2
–62
– 9.8
–695
–10.2
–13
– .9
Government.......................................................
9.0 7.4
– 1.6
–17.8 2,008 1,661
Federal...............................................................
10.5 3.8
– 6.7
–63.8 287 105
State and local................................................. 8.8 7.9
– .9
–10.2 1,722 1,555
Region 3
–347
–182
–167
–17.3
–63.4
– 9.7
Northeast..........................................................
18.3
18.0
– .3
– 1.6 4,708 4,616
–92
– 2.0
South..................................................................
29.1
25.0
– 4.1
–14.1
14,478
12,393
–2,085
–14.4
Midwest.............................................................
24.1
21.8
– 2.3
– 9.5 7,552 6,800
–752
–10.0
West....................................................................
27.1
23.4
– 3.7
–13.7 8,366 7,191
–1,175
–14.0
1
3
The annual quits rate is the number of quits during the entire year as a
See footnote 3, Table 1.
percent
of annual average employment.
2
The annual quits level is the total number of quits during the entire
year.
if they believe it will be difficult to find a new job. They
are also less willing to relocate for new jobs.9 In 2008, this
downward trend in quits could be tied to the collapse of
the housing market, high gas prices in the first half of the
year, and economic uncertainty in general.10
In December 2008, the Consumer Confidence IndexTM, a leading indicator, reached a historic low of
38.6,11 down from 90.6 in December 2007. Over time,
the JOLTS quits rate series has trended closely with the
Consumer Confidence Index.12 If consumers are not
confident in the economy, they are less likely to quit
their jobs. (See chart 6.)
Layoffs and Discharges. Layoffs and discharges are involuntary separations initiated by the employer. While there
was some fluctuation in the month-to-month levels during 2008, layoffs and discharges have trended up over the
year. In January 2008, there were 1.8 million layoffs and
discharges. By December 2008, the number of layoffs and
discharges rose to 2.4 million.
Because unemployment insurance claims are usually
filed after job loss, they trend closely with the layoffs and
discharges series. Similar to the upward trend in layoffs
and discharges, unemployment insurance claims rose over
the course of 2008.13 Chart 7 shows that both series reflect
Monthly Labor Review • May 2009
37
JOLTS Annual Story
Table 4. Annual layoffs and discharges rates 1 and levels 2
Rates (percent)
Industry and region
2007
2008
Change
Levels (in thousands)
Percent
2007
2008
Change
change
Total...................................................................................
16.4
17.8 1.4 8.5
Industry
22,539
Percent
change
24,370
1,831 8.1
Total private.................................................................
18.4
20.2 1.8 9.8
21,176
23,146
Natural resources and mining...........................
12.6
15.1 2.5
19.8 91 117
Construction............................................................
37.3
46.4 9.1
24.4 2,848 3,347
Manufacturing........................................................
14.1
16.5 2.4
17.0 1,963 2,217
Durable goods.....................................................
13.7
16.7 3.0
21.9 1,205 1,413
Nondurable goods.............................................
14.9
16.2 1.3 8.7 757 801
Trade, transportation, and utilities..................
13.6
16.3 2.7
19.9 821 973
Retail trade............................................................
17.7
18.9 1.2 6.8 2,753 2,907
Transportation, warehousing, and
utilities................................................................
13.9
16.0 2.1
15.1 707 811
Information..............................................................
10.4
12.2 1.8
17.3 315 365
Financial activities..................................................
13.3
13.5 .2 1.5 1,107
1,100
Finance and insurance...................................... 9.9
10.6 .7 7.1 605 640
Real estate and rental and leasing...............
23.1
21.6
–1.5
– 6.5 500 461
Professional and business services..................
26.4
28.7 2.3 8.7 4,744 5,110
Education and health services.......................... 9.5
11.0 1.5
15.8 1,737 2,069
Educational services..........................................
13.2
14.0 .8 6.1 387 426
Health care and social assistance................. 8.8
10.4 1.6
18.2 1,350 1,644
Leisure and hospitality.........................................
23.6
23.4
– .2
– .8 3,174
3,152
Arts, entertainment, and recreation............
46.2
45.6
– .6
–1.3 910 898
Accommodations and food services...........
19.7
19.6
– .1
– .5 2,262 2,256
Other services..........................................................
16.6
17.7 1.1 6.6 914 977
Government................................................................ 6.1 5.5
– .6
–9.8 1,364 1,227
Federal....................................................................... 8.2 3.9
– 4.3
–52.4 225 109
State and local........................................................ 5.8 5.6
– .2
–3.4 1,137 1,114
1,970 9.3
26
28.6
499
17.5
254
12.9
208
17.3
44 5.8
152
18.5
154 5.6
104
14.7
50
15.9
–7
–.6
35 5.8
–39
–7.8
366 7.7
332
19.1
39
10.1
294
21.8
–22
– .7
–12
–1.3
–6
– .3
63 6.9
–137
–116
–23
–10.0
–51.6
– 2.0
Region 3
Northeast...............................................................
15.6
16.9 1.3 8.3 3,996 4,326
South.......................................................................
15.9
16.5 .6 3.8 7,909 8,162
Midwest.................................................................
16.8
17.0 .2 1.2 5,276 5,302
West.........................................................................
17.3
21.4 4.1
23.7 5,357 6,582
330 8.3
253 3.2
26 .5
1,225
22.9
1
discharges during the entire year.
The annual layoffs and discharges rate is the number of layoffs and dis
charges during the entire year as a percent of annual average employment.
3
2
See footnote 3, Table 1.
The annual layoffs and discharges level is the total number of layoffs and
increases beginning well before the start of the recession.
Regional trends: job openings
Other Separations. Other separations includes separations due to retirement, transfer to other locations of the
same firm, death, and disability. Other separations, not
seasonally adjusted, declined from 334,000 in December
2007 to 289,000 in December 2008. The annual other
separations rate also reached a low in 2008 of 2.9 percent
of annual average employment. This decline in other separations may represent a tendency to forestall retirement
during a recession.
Just as job openings at the national level experienced a
downward trend in 2008, the job openings rates for all
four regions also experienced downward movements in
2008. The Midwest regional job openings rate reached a
low of 1.9 percent in December 2008.
Using Local Area Unemployment Statistics unemployment data, ratios for the number of unemployed persons
per job opening were computed by region.14 The highest
ratio is currently in the Midwest where the number of
38
Monthly Labor Review • May 2009
Table 5. Annual other separations rates1 and levels2
Rates (percent)
Levels (in thousands)
Industry and region
Percent
Percent
2007
2008
Change
2007
2008
Change
change
change
Total............................................................................
3.2 2.9
– 0.3
– 9.4 4,463 3,969
–494
–11.1
Industry
Total private......................................................... 3.1 2.9
– .2
– 6.5 3,591 3,319
–272
– 7.6
Natural resources and mining.................... 4.8 3.6
– 1.2
–25.0 35 28
–7
–20.0
Construction..................................................... 2.9 3.2 .3
10.3 220 233
13 5.9
Manufacturing................................................. 2.8 2.5
– .3
–10.7 393 332
–61
–15.5
Durable goods............................................. 2.9 2.5
– .4
–13.8 252 209
–43
–17.1
Nondurable goods..................................... 2.8 2.5
– .3
–10.7 142 124
–18
–12.7
Trade, transportation, and utilities........... 3.6 3.7 .1 2.8 956 974
18 1.9
Wholesale trade........................................... 2.2 2.0
– .2
– 9.1 134 120
–14
–10.4
Retail trade.................................................... 4.0 4.3 .3 7.5 623 658
35 5.6
Transportation, warehousing, and
utilities..........................................................
3.9 3.9 .0 .0 201 196
–5
– 2.5
Information....................................................... 3.3 2.3
– 1.0
–30.3 100 68
–32
–32.0
Financial activities.......................................... 3.1 3.0
– .1
– 3.2 257 245
–12
– 4.7
Finance and insurance.............................. 2.8 2.9 .1 3.6 174 172
–2
– 1.1
Real estate and rental and leasing........ 3.7 3.4
– .3
– 8.1 80 73
–7
– 8.8
Professional and business services.......... 3.6 3.2
– .4
–11.1 644 568
–76
–11.8
Education and health services................... 2.4 2.4 .0 .0 444 454
10 2.3
Educational services.................................. 1.7 1.6
– .1
– 5.9 50 48
–2
– 4.0
Health care and social assistance.......... 2.6 2.6 .0 .0 395 406
11 2.8
Leisure and hospitality................................. 2.4 2.4 .0 .0 324 322
–2
– .6
Arts, entertainment, and recreation.... 3.0 2.1
– .9
–30.0 59 42
–17
–28.8
Accommodations and food services...
2.3 2.4 .1 4.3 267 278
11 4.1
Other services.................................................. 3.9 1.8
– 2.1
–53.8 217 102
–115
–53.0
Government............................................................ 3.9 2.9
– 1.0
–25.6 872 647
–225
–25.8
Federal...................................................................
11.4 4.0
– 7.4
–64.9 312 110
–202
–64.7
State and local..................................................... 2.9 2.7
– .2
– 6.9 559 538
–21
– 3.8
Region3
Northeast.............................................................. 3.2 3.1
– .1
– 3.1 821 799
–22
– 2.7
South...................................................................... 3.0 2.7
– .3
–10.0 1,475 1,342
–133
– 9.0
Midwest................................................................. 3.3 2.9
– .4
–12.1 1,034 919
–115
–11.1
West........................................................................ 3.7 3.0
– .7
–18.9 1,132 909
–223
–19.7
1
The annual other separations rate is the number of other separations tions during the entire year.
during
the entire year as a percent of annual average employment.
3
See footnote 3, Table 1.
2
The annual other separations level is the total number of other separa-
unemployed per job opening is approaching 4 to 1. All
four regions show a similar trend of an increasing ratio
beginning in mid-2007.
Regional trends: hires
Similar to the trend at the national level, hires have trended
downward at the regional level in 2008. All four regions
have dropped to series low hires rates, seasonally adjusted.
In 2008, after peaking at a hires rate of 4.2 percent in
April, the West region reached a series low of 3.4 percent
in October. The Northeast and Midwest both experienced
slight increases in hires rate in June 2008 at 3.2 and 3.6
percent, respectively, but then the hires rates fell to 2.6
percent in the Northeast and 3.0 percent in the Midwest
by November 2008. The South region showed a steady
decline in hires to a low of 3.2 percent in November 2008
and then increased to 3.4 percent in December.
Regional trends: total separations
Total separations increased in the Northeast and West
regions and decreased in the Midwest and South regions.
From December 2007 to December 2008, separations inMonthly Labor Review • May 2009
39
JOLTS Annual Story
Chart 4.
Difference between monthly hires and separations, seasonally adjusted, December 2000–December
2008
(In thousands)
(In thousands)
600
600
400
400
200
200
0
0
–200
–200
–400
–400
–600
–600
–800
Dec 2000
Dec 2001
Dec 2002
Dec 2003
Dec 2004
Dec 2005
Dec 2006
Dec 2007
–800
Dec 2008
NOTE: Shaded regions represent recessions as designated by the National Bureau of Economic Research.
Chart 5.
Composition of total separations: 2006 and 2008
2006
2008
Layoffs
and
discharges
41%
Layoffs
and
discharges
34%
Quits
52%
Quits
58%
Other
separations
8%
40
Monthly Labor Review • May 2009
Other
separations
7%
Chart 6.
JOLTS quits and the Conference Board Consumer Confidence IndexTM, seasonally adjusted, December
2000–December 2008
Quits
(in thousands)
Consumer Confidence
Index
4,000
140
3,500
120
Quits
3,000
100
2,500
80
2,000
60
1,500
Consumer Confidence Index
1,000
40
20
500
0
0
Dec 2000
Dec 2001
Dec 2002
Dec 2003
Dec 2004
Dec 2005
Dec 2006
Dec 2007
Dec 2008
NOTE: Shaded regions represent recessions as designated by the National Bureau of Economic Research.
Chart 7.
JOLTS layoffs and discharges and initial unemployment insurance claims, seasonally adjusted,
December 2000–December 2008
(In thousands)
(In thousands)
2,700
2,700
2,500
2,500
2,300
2,300
2,100
2,100
Layoffs and discharges
1,900
1,900
1,700
1,700
1,500
1,500
Initial claims
1.300
1.300
1,100
1,100
Dec 2000
Dec 2001
Dec 2002
Dec 2003
Dec 2004
Dec 2005
Dec 2006
Dec 2007
Dec 2008
NOTE: Shaded regions represent recessions as designated by the National Bureau of Economic Research.
Monthly Labor Review • May 2009
41
JOLTS Annual Story
creased in the Northeast from 2.8 percent to 3.2 percent
and in the West from 3.9 percent to 4.0 percent. During
the same time period, total separations in the South decreased from 3.8 percent to 3.7 percent and in the Midwest from 3.6 percent to 3.5 percent.
Relative contributions of the components of total
separations varied by region. Layoffs and discharges in
the West showed the highest annual percentage of total
separations of the four census regions at 44.8 percent in
2008. The South showed the lowest contribution of layoffs
and discharges to total separations at 37.3 percent. Quits
were high in the South at 56.6 percent of that region’s
total separations. The Northeast showed the lowest contribution of quits to total separations of the four Census
regions at 47.4 percent. Other separations were highest in
the Northeast as a percentage of that region’s total separations at 8.2 percent while the South again shows the
lowest contribution at 6.1 percent.
Industry trends in 2008
The overall pattern of declining job openings, declining
hires, increasing layoffs and discharges, and declining
quits and other separations was consistent across most
Chart 8.
industries. For the majority of industries job openings
declined from December 2007 to December 2008. The
following industries reached series lows during 2008 for
their job openings rates, seasonally adjusted: construction
in December 2008; professional and business services in
November 2008; and accommodation and food services
in November 2008.
Hires rates also declined in the majority of industries
over 2008. The following industries dropped to series low
seasonally-adjusted hires rates during 2008: manufacturing in November 2008; retail trade in November 2008;
professional and business services in September 2008; arts,
entertainment, and recreation in November 2008; and accommodation and food services in December 2008.
Typically, average monthly hires exceed average
monthly job openings. This is true in 2008 at the total
nonfarm level. However, there are several industries in
which average monthly job openings exceeded average
monthly hires in 2008 indicating areas where, in spite of
the current recession, demand for some types of labor may
be greater than the supply. These industries include information; finance and insurance; and health care and social
assistance. (See chart 8.)
Total separations rates at the industry level showed a
Monthly hires and job openings rates, annual averages, 2008
Percent
Percent
4.5
4.0
4.5
Average monthly hires Average monthly job openings
3.5
3.5
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
Total nonfarm
Information
Finance and insurance Health care and social
assistance
42
4.0
Monthly Labor Review • May 2009
mix of increases and decreases over the year: construction;
manufacturing; trade, transportation, and utilities; and
professional and business services experienced increasing
seasonally-adjusted total separations numbers over the
course of 2008. The remaining industries experienced seasonally-adjusted declines in total separations during 2008,
with the exception of education and health services, which
remained unchanged. Series lows occurred in the following seasonally-adjusted separations series: arts, entertainment, and recreation; and government. In the remaining
separations series, which are not seasonally adjusted, total
separations increased from December 2007 to December
2008 with the following exceptions: finance and insurance; educational services; and Federal Government.
Industry level layoffs and discharges, which are not seasonally adjusted, have increased over the year in almost all
industries with the exceptions of finance and insurance;
Federal Government; and State and local government
which showed declines. In December 2008, wholesale
trade reached a series high for layoffs and discharges at 2.4
percent of total employment, not seasonally adjusted. In a
number of cases, layoffs and discharges remained stable
until after the summer months when the climb in layoffs
and discharges began.
Quits have declined in all of the seasonally adjusted
industry series from over the year with most industries
dropping to series low quit rates. For the not seasonally
adjusted series, Federal Government quits dropped to a
series low rate of 0.1 percent of total employment in November 2008.
Other separations, which are not seasonally adjusted,
were fairly stable over 2008, trending downward only
slightly in most industries. Notably, mining and logging
showed a 0.3 percent decline from December 2007 to
December 2008 in other separations as did wholesale
trade. Real estate and rental and leasing on the other hand
showed an increase in other separations of 0.4 percent of
total employment.
Leisure and Hospitality. Leisure and hospitality showed
large changes over the course of 2008 in job openings,
hires, and total separations. The job openings rate, seasonally adjusted, declined steadily over the year from 4.1 percent in December 2007 to 2.3 percent in December 2008,
a series low. Hires, seasonally adjusted, declined from a
high of 6.9 percent in February 2008 to a low of 5.3 percent in November 2008. In May, the hires rate increased to
6.7 percent but then resumed the downward trend. Total
separations in the leisure and hospitality industry showed
a downward trend from a high of 6.9 percent in February
2008 to a low of 5.7 percent in December 2008.
In arts, entertainment, and recreation, job openings
dropped slightly by 0.3 percent while hires declined by
1.1 percent, seasonally adjusted, from December 2007 to
December 2008. Quits reached a series low of 1.5 percent
in December 2008, seasonally adjusted. Accommodation
and food services showed a downward trend for 2008
in job openings. Job openings, seasonally adjusted, went
from 4.4 percent in December 2007 to 2.4 percent in
December 2008. Hires for accommodation and food services, seasonally adjusted, trended downward over 2008.
From December 2007 to December 2008, total separations dropped from 6.8 percent to 5.7 percent, seasonally
adjusted.
Durable Goods Manufacturing. The durable goods manufacturing industry experienced declining job openings
and hires, and increasing total separations. An analysis of
the annual data provides another look at the impact of the
recession on the durable goods industry.
On an annual basis, the share of layoffs and discharges
as a percent of total separations showed a larger increase in
durable goods manufacturing from 2007 to 2008 than any
other industry. The contribution of layoffs and discharges
went from 41.8 percent in 2007 to 52.4 percent in 2008,
an increase of 10.6 points. Quits also declined from 49.4
percent contribution to total separations in 2007 to 39.8
percent in 2008, a decrease of 9.6 points. This represents
a larger decline in quits as a portion of total separations
than any other industry as well.
Construction. The construction industry experienced a
drop in job openings rate from 1.8 percent in December 2007 to a low of 0.9 percent in December 2008 while
hires experienced an increase from 5.0 percent in December 2007 to 5.3 percent in December 2008, seasonally
adjusted. Total separations, seasonally adjusted, were up
from 5.4 percent to 6.6 percent for the same time period.
The layoffs and discharges rate, not seasonally adjusted,
experienced a large increase from 3.8 percent in December 2007 to 5.8 percent in December 2008. The increase
in layoffs and discharges in the construction industry can
be explained by the severe problems in the financial and
housing markets during the recession. According to CES
employment figures, national construction employment
went from 7.5 million employees in December 2007 to
6.8 million employees in December 2008, seasonally adjusted.
Monthly Labor Review • May 2009
43
JOLTS Annual Story
Conclusion
The current recession continued to impact labor market
demand in 2008; job openings and hires declined and
layoffs and discharges increased while quits decreased at
the national level. For all four Census regions, job open-
ings declined as did hires. Total separations increased
in the Northeast and remained relatively unchanged in
the remaining regions. At the industry level, declining
job openings, declining hires, increasing layoffs and discharges, and declining quits and other separations were
measured across most industries.
NOTES
1
Zhi Boon, “Job openings, hires, and turnover decrease in 2007,” Monthly
Labor Review (May 2008): 14-23.
National Bureau of Economic Research. Determination of the December
2007 Peak in Economic Activity, December 1, 2008. http://www.nber.org/cycles/dec2008.html (visited Dec. 11, 2008).
2
U.S. Department of Labor. Bureau of Labor Statistics. Data on the unemployment rates are available from Current Population Survey at http://stats.
bls.gov/cps/#news (visited Mar. 18, 2009).
3
U.S. Department of Labor. Bureau of Labor Statistics. Data on the annual
employment levels are available from the Current Employment Statistics at
http://stats.bls.gov/ces/home.htm (visited Mar. 18, 2009).
4
5
U.S. Department of Labor. Bureau of Labor Statistics. Job Openings and
Labor Turnover Survey News Release: Job Openings and Labor Turnover: January 2009, March 10, 2009, http://stats.bls.gov/news.release/archives/jolts_
03102009.htm (visited Mar. 10, 2009).
recent retabulations and methodology updates.
8
U.S. Department of Labor. Bureau of Labor Statistics. Data on the annual employment levels are available from the Current Employment Statistics
at http://stats.bls.gov/ces/home.htm (visited Mar. 18, 2009).
9
Nick Zieminski, “Workers less willing to move or switch jobs,” Reuters, August
1, 2008, http://www.reuters.com/article/reutersEdge/idUSN0143860920080801
(visited Mar. 18, 2009).
10
Ibid.
Sue Kirchhoff, “Consumer confidence hits new low; home values continue to slide,” USA Today, January 27, 2009, http://www.usatoday.com/money/
economy/housing/2009-01-27-case-shiller_N.htm. (visited Mar. 18, 2009).
11
12
Conference Board. Data on the Consumer Confidence Index are available from the Consumer Confidence Survey at http://www.conference-board.
org/economics/consumer.cfm (visited Mar. 18, 2009).
6
“Economic Jolt: Job Openings and Labor Turnover December 2008,” Paper Economy, February 10, 2009, http://paper-money.blogspot.com/2009/02/
economic-jolt-job-openings-and-labor.html#links (visited Mar. 18, 2009).
13
U.S. Department of Labor. Employment and Training Administration.
Data from the Unemployment Insurance Claims are available on the internet at
http://www.dol.gov/opa/media/press/eta/ui/eta20090005.htm (visited Mar.
24, 2009). Monthly claims calculations shown on graph sum the weekly initial
unemployment claims by month.
7
Diane Stafford, “10 million job hunters for 3 million jobs,” Kansas City
Star, December 14, 2008, http://economy.kansascity.com/?q=node/513 (visited Mar. 18, 2009). The article uses JOLTS data dating from before the most
14
U.S. Department of Labor. Bureau of Labor Statistics. Data on the local area unemployment rates are available from the Local Area Unemployment
Statistics program at http://www.bls.gov/lau/ (visited Mar. 18, 2009).
44
Monthly Labor Review • May 2009
Annual BED Data
Business employment dynamics:
annual tabulations
The Business Employment Dynamics program releases quarterly
gross job gain and gross job loss statistics, and this year it is
releasing annual statistics for the first time; the annual data
show over-the-year growth and decline of employment
at the establishment level
Akbar Sadeghi,
James R. Spletzer,
and
David M. Talan
Akbar Sadeghi, James R.
Spletzer, and David M. Talan
are economists in the Office
of Employment and Unemployment Statistics, Bureau
of Labor Statistics. E-mail:
sadeghi.akbar@bls.gov,
spletzer.jim@bls.gov,
talan.david@bls.gov
B
usiness Employment Dynamics (BED)
data from the U.S. Bureau of Labor
Statistics are quarterly statistics that
quantify levels of gross job gains and gross job
losses in the United States. Gross job gains
are defined as the sum of all employment
gains at expanding and opening establishments. Gross job losses are defined as the sum
of all employment losses at contracting and
closing establishments. In the second quarter
of 2008, on a seasonally adjusted basis, 1.8
million establishments expanded or opened,
creating 7.3 million jobs, and 2.0 million establishments contracted or closed, eliminating 7.8 million jobs. The difference between
the 7.3 million gross job gains and the 7.8
million gross job losses is a net employment
loss of 0.5 million jobs (seasonally adjusted).
The gross job gain and gross job loss statistics,
which are substantially larger numbers than
the net employment change, illustrate how
dynamic the U.S. labor market is from quarter
to quarter.
Since their initial release in 2003, BED statistics have become an important component
of the Nation’s statistical infrastructure. BED
data are routinely cited by policymakers, researchers, and the business community, as well
as the popular press. One request that BLS
has heard consistently from users is for the
production of annual gross job gain and loss
statistics, which would enable a comparison
of BED statistics with gross job gain and loss
statistics from the U.S. Census Bureau and
from other countries. The statistics that the
BED program historically has produced cannot be compared with statistics from other
statistical agencies, because the BED statistics
are quarterly and other gross job gain and loss
statistics are annual; four quarters of gross job
gains and losses cannot be summed to create an annual measure of gross job gains and
losses.
This article presents a new BED time series
of annual gross job gain and gross job loss
statistics. The article begins with a detailed
documentation of how BLS has created annual BED statistics, and it discusses the value
added by annual statistics notwithstanding
the availability of quarterly statistics. The
heart of the article is a comparison of the
annual BED statistics with the quarterly BED
statistics and a comparison of the annual BED
statistics with similar statistics from the U.S.
Census Bureau.
Business Employment Dynamics
An overview of quarterly BED data. The BED
program’s quarterly measures of gross job
gains and gross job losses are constructed
from Quarterly Census of Employment and
Wages (QCEW) microdata. These microdata
represent quarterly contribution reports submitted to the States by employers. QCEW
data are a comprehensive and accurate source
of information on employment and wages,
and they provide a near census (98 percent
Monthly Labor Review • May 2009 45
Annual BED Data
complete) of employees on nonfarm payrolls.1 The QCEW
is the sampling frame for BLS establishment-based surveys and is the employment benchmark for the Current
Employment Statistics survey and other BLS establishment-based surveys. In the second quarter of 2008, QCEW
statistics show an employment level of 136.6 million jobs
in 9.1 million establishments in the U.S. economy. BLS
publishes employment and wage data from the QCEW approximately 7 months after the end of each quarter.
All employers subject to State unemployment insurance
laws must submit quarterly contribution reports to the
State employment security agencies. These reports detail
the establishments’ level of employment by month and
their wages by quarter. BED quarterly gross job gain and
gross job loss statistics are tabulated by linking establishment-level microdata from the QCEW across quarters and
then classifying establishments as expanding, opening,
contracting, closing, or not changing their employment
level. Following establishments across time using microdata is a complex and challenging exercise. BLS has developed a multistep process to link business-establishment
microdata over time. This linkage process consists of two
distinct administrative matches based on unique establishment identifiers maintained by the States, a probability-based weighted match, and an analyst review match.
The basic product of the BED program is statistics measuring quarterly gross job gains and gross job losses. BLS
publishes quarterly BED data approximately 8 months after the end of the quarter.2 Seasonally adjusted quarterly
gross job gain and gross job loss statistics are plotted in
chart 1. (The BED time series starts in the third quarter of
1992.) The 2001 recession is immediately evident in the
chart. Both gross job gains and the gross job losses were
climbing at relatively constant rates between 1992 and
1999, and then in 2001 gross job gains dropped substantially and gross job losses climbed dramatically. This shows
that the net employment losses during the 2001 recession
are the result of both falling gross job gains (a slowdown
in the jobs created by establishment expansions and openings) and rising gross job losses (an increase in the jobs
lost from establishment contractions and closings).
changes that reverse themselves in other quarters during
the year. The seasonal variations in establishment-level
employment are accounted for in the quarterly gross job
gain and gross job loss statistics. However, gross job gains
and gross job losses measured on an annual basis—the
first quarter of each year, for example—are not affected
by any seasonal employment variation that occurs during
the year. As such, the annual statistics are arguably better measures of over-the-year growth and decline at the
establishment level.
The second reason to produce annual statistics is related
to the internal structure of the BED program. The BED
program publishes statistics on establishment births and
establishment deaths, and the definitions of births and
deaths differ from the definitions of openings and closings that underlie the statistics that have been published
thus far.3 Businesses are allowed to and often do report
zero employment to the State unemployment insurance
systems for several quarters after they have effectively
closed. This undoubtedly occurs when a business owner
temporarily shuts down the business but anticipates starting it up again when economic conditions improve. By
reporting zero employment and wages on the quarterly
contributions form, the business owner can keep his or
her unemployment insurance account active in preparation for reopening the business. As a result, in any given
quarter one observes many businesses closing, but which
of these businesses will start up again and which will die
cannot be determined for several more quarters. The BED
definition of establishment death requires four consecutive quarters of no positive employment, and implementing this definition requires longitudinally linking five
consecutive quarters of cross-sectional QCEW microdata.
An output derived from this five-quarter linkage is annual
gross job gain and gross job loss statistics.
The third reason for creating annual BED statistics is to
satisfy demands from users of BED data. As stated previously, users want annual BED data in order to compare the
BED gross job gain and gross job loss statistics from BLS
with similar statistics from the U.S. Census Bureau and
from statistical agencies in other countries.
Reasons for creating annual BED statistics. There are three
main reasons that annual measures of gross job gains and
gross job losses should be produced despite the availability of quarterly measures. The first is to enhance people’s
understanding of labor market dynamics. Many establishments are seasonal and exhibit consistent patterns of
growth and decline during the four quarters of the year.
These seasonal expansions and contractions are short-term
The method of constructing annual BED statistics. Creating annual BED statistics from quarterly cross-sectional
QCEW microdata is difficult. The difficulty arises from
trying to follow establishments through mergers, restructurings, and other ownership and administrative changes.
It is important to do this correctly because the quality of
longitudinal statistics hinges upon the ability to accurately
follow establishments across time. Failure to follow an es-
46
Monthly Labor Review • May 2009
Chart 1.
Quarterly gross job gains and gross job losses, third quarter 1992 through second quarter 2008,
seasonally adjusted
Thousands of jobs
Thousands of jobs
9,000
9,000
Quarterly gross job gains
8,000
8,000
6,000
7,000
Quarterly gross job losses
7,000
1992
1993 1994 1995 1996
1997 1998 1999 2000 2001 2002 2003 2004
2005 2006 2007 2008
6,000
Note: The first quarter of each year ends in March, and the first quarter’s endpoint is represented by the year’s long tick mark. The
shorter tick marks represent the endpoints of the second, third, and fourth quarters. The shaded bars denote National Bureau of
Economic Research (NBER)-designated recessions, one running March 2001–November 2001 and the other beginning in December
2007. An endpoint for the more recent recession has yet to be designated.
tablishment through mergers or other corporate restructurings would break a continuous longitudinal linkage
and result in a spurious establishment closing and a concomitant spurious establishment opening. Annual BED
gross job gain and gross job loss statistics must accurately
measure the growth and decline of establishment-level
employment rather than be distorted because of missed
linkages due to changes in establishment identifiers in the
administrative source data.
BLS has thoroughly researched the best way to create annual BED statistics from quarterly QCEW microdata and
has determined that information from all quarters within
the year needs to be used when creating an annual link.4
BLS’ research has shown that the annual gross job gain
and gross job loss statistics would be biased upward by
almost 10 percent if quarterly linkage information from
within the year were not taken into account. This upward
bias would result from establishments that go through
mergers or other corporate restructurings and are incorrectly classified as establishments that have opened and/or
closed during the year. It took a long time to develop the
longitudinal-linkage algorithm that underlies the BED
annual statistics, but the increases in data quality resulting
from the complex new algorithm have made the effort
worthwhile.
Annual tabulations
Basic results. Table 1 presents quarterly and annual tabulations of BED statistics. The statistics in table 1 are not
seasonally adjusted. In the first quarter of 2007 there were
111,994,015 private-sector jobs, and in the first quarter
of 2008 there were 112,130,509 private-sector jobs. The
annual net employment change of approximately 136,000
jobs is the sum of the four seasonally unadjusted quarterly
changes during the year: an increase of 2,932,000 jobs
between the first and second quarters of 2007, a decline
of 738,000 jobs between the second and third quarters,
an increase of 323,000 jobs between the third and fourth
quarters, and a decline of 2,380,000 jobs between the
fourth quarter of 2007 and the first quarter of 2008. (The
statistics do not add precisely because of rounding.) These
quarterly and annual net employment changes are listed
in the final column of table 1.
The annual net employment change of 136,000 jobs in
table 1 is the difference between the annual gross job gains
Monthly Labor Review • May 2009 47
Annual BED Data
Table 1. Quarterly and annual gross job gains and gross job losses, first quarter 2007 through first quarter 2008,
not seasonally adjusted
(in thousands)
Employment
Gross job gains
Gross job losses
Net
Timespan
employment
Gains
Gains
Losses
Losses
change
Beginning Ending
Total
from
from
Total
from
from
quarter
quarter
expansions openings
contractions closings
Quarterly:
2007:Q1 – 2007:Q2.........................
111,994
114,926
9,164
7,533
1,631
6,232
5,002
1,230
2,932
2007:Q2 – 2007:Q3.........................
114,926
114,188
6,620
5,330
1,290
7,358
6,137
1,221
–738
2007:Q3 – 2007:Q4.........................
114,188
114,511
7,648
6,321
1,327
7,325
6,077
1,248
323
2007:Q4 – 2008:Q1.........................
114,511
112,131
6,485
4,984
1,501
8,865
7,108
1,757
–2,380
Quarterly average
Annual:
2007:Q1 – 2008:Q1.........................
111,994
112,131
7,479
6,042
1,437
7,445
6,081
1,364
12,706
8,705
4,001
12,570
8,721
3,849
136
NOTE: Statistics may not add up precisely because of rounding.
and the annual gross job losses. Looking at the bottom
row of table 1, one can see that between the first quarter
of 2007 and the first quarter of 2008, employment in expanding establishments grew by 8.7 million jobs and employment in opening establishments grew by 4.0 million
jobs. The number of annual gross job gains was 12.7 million. Employment in contracting establishments declined
by 8.7 million jobs, and closing establishments accounted
for a loss of 3.8 million jobs. The level of annual gross job
losses was 12.6 million jobs. The difference between the
12.7 million jobs gained and 12.6 million jobs lost is the
net employment change of 136,000 jobs.
The annual gross job gain and loss statistics in table 1
are higher in magnitude than the quarterly gross job gain
and loss statistics from any quarter within the year. The
quarterly gross job gains, on a non-seasonally adjusted
basis, range from 6.5 million to 9.2 million during the
first quarter 2007 to first quarter 2008 period. The average
level of quarterly gross job gains is 7.5 million jobs, which
is substantially less than the annual gross job gains of 12.7
million jobs. Similarly, the average number of quarterly
gross job losses is 7.4 million, which is less than the annual gross job losses of 12.6 million jobs.
The difference between the annual and the average quarterly gross job gains is more prominent in the statistics on
opening establishments than in the statistics on expanding establishments. When gross job gains are measured
on an average quarterly basis, 81 percent of gross job
gains are found to be due to expanding establishments
(6,042/7,479 in table 1), whereas, when measured on an
annual basis, 69 percent of gross job gains are found to be
due to expanding establishments (8,705/12,706 in table
48
Monthly Labor Review • May 2009
1). Similar computations show that 82 percent of quarterly gross job losses are due to contracting establishments,
whereas 69 percent of annual gross job losses are due to
contracting establishments. This greater importance of
expansions and contractions in the quarterly statistics
relative to the annual statistics is attributable to the transitory and seasonal nature of quarterly establishment-level
employment changes that often reverse themselves during
other quarters of the year.
The transitory nature of quarterly establishment-level
employment changes is also the reason that the sum of
four quarterly gross job gains or losses does not equal annual gross job gains or losses. The sum of the four quarterly gross job gain statistics in table 1 is approximately 30
million, yet this statistic has no clear interpretation.5 The
new BED annual gross job gain and gross job loss statistics
make clear that it is not appropriate to use the sum of the
four quarterly gross job flows statistics as an annual gross
job flows statistic.
Chart 2 compares the time series of quarterly and annual
BED gross job gain and gross job loss statistics. In this
chart, the quarterly statistics are seasonally adjusted but
the annual statistics are not. The quarterly statistics are
identical to those in chart 1 (bearing in mind that charts
1 and 2 have different scales on their vertical axes). The
annual statistics in chart 2 were tabulated by linking business establishments from the first quarter of the reference
year to the first quarter of the previous year.
Consistent with the statistics in table 1, the annual gross
job gains and losses in chart 2 are higher in magnitude
than the quarterly gross job gains and losses. The magnitude of the annual gross job gains is 1.7 times greater,
Chart 2.
Quarterly and annual gross job gains and gross job losses, second quarter 1993 through
second quarter 2008, quarterly data seasonally adjusted and annual data not seasonally adjusted
Thousands of jobs
18,000
Thousands of jobs
18,000
15,000
15,000
12,000
12,000
9,000
Quarterly gross job gains
Annual 1st quarter-to-1st quarter gross job gains
6,000
1993 1994 1995 1996
Quarterly gross job losses
Annual 1st quarter-to-1st quarter
gross job losses
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006
2007 2008
9,000
6,000
Note: The first quarter of each year ends in March, and the first quarter’s endpoint is represented by the year’s long tick mark. The datum for each first quarter-to first quarter year is plotted at the end of the year in question (in March). The shorter tick marks represent the
endpoints of the second, third, and fourth quarters. The shaded bars denote National Bureau of Economic Research (NBER)-designated
recessions, one running March 2001–November 2001 and the other beginning in December 2007. An endpoint for the more recent
recession has yet to be designated.
on average, than the magnitude of the quarterly gross job
gains. Similarly, the magnitude of the annual gross job
losses is 1.7 times greater, on average, than the magnitude
of the quarterly gross job losses. Recall that the difference between gross job gains and gross job losses is net
employment change. The fact that the gap between the
annual gross job gains and losses in chart 2 is often larger
than the gap between the quarterly gross job gains and
losses should not be of concern, because annual first quarter-to-first quarter net employment growth is the sum of
four quarters of net employment growth during the year.
It is important to note the ways in which the quarterly and the annual gross job gains and losses in chart 2
relate to the business cycle. During the 2001 recession,
the difference between the quarterly gross job gain series
and quarterly gross job loss series reaches its peak in the
third quarter of the year. In this quarter, quarterly gross
job losses are estimated to be 8.8 million and quarterly
gross job gains are estimated to be 7.6 million, with a
quarterly net employment decline of 1.2 million jobs. The
annual first quarter-to-first quarter series shows the difference between gross job gains and losses peaking in the
first quarter of 2002. In the first quarter of 2002, the annual gross job losses measure 16.4 million and the annual
gross job gains measure 13.6 million, with an annual net
employment decline of 2.8 million jobs. This difference
in timing should not be surprising: annual gross job gain
and gross job loss statistics measure activity that occurred
during the previous year.
The annual first quarter-to first quarter gross job gains
at expanding and opening establishments and the annual
first quarter-to first quarter gross job losses at contracting and closing establishments are presented in chart
3. When gross job gains and losses are measured annually, expanding establishments account for approximately
two-thirds of jobs gained and contracting establishments
account for approximately two-thirds of jobs lost. Both
expansions and contractions, as well as openings and closings, behave about as one would expect throughout the
business cycle. The net employment change attributable to
expansions and contractions is positive in the 1990s, turns
negative in the early 2000s, and becomes positive again in
the mid-2000s. The net employment change attributable
to openings and closings shows the same pattern, yet the
magnitude of changes in net employment is greater overall in the expanding and contracting establishments than
in the opening and closing establishments.
Annual statistics based on other quarters. The annual BED
statistics presented in table 1 and charts 2–3 are based on
comparisons of establishment-level employment from the
first quarter of one year to the first quarter of the followMonthly Labor Review • May 2009 49
Annual BED Data
Chart 3.
Annual first quarter-to-first quarter gross job gains and gross job losses,1994–2008,
not seasonally adjusted
Thousands of jobs
Thousands of jobs
12,000
12,000
9,000
9,000
6,000
3,000
1994
Job gains from expansions
Job losses from contractions
1995 1996
1997
1998 1999
2000
2001
2002
Job gains from openings
Job losses from closings
2003
2004
2005
2006
2007 2008
6,000
3,000
Note: The first quarter of each year ends in March, and the first quarter’s endpoint is represented by the year’s tick mark. The
datum for each first quarter-to first quarter year is plotted at the end of the year in question (in March). The shaded bars denote
National Bureau of Economic Research (NBER)-designated recessions, one running March 2001–November 2001 and the other beginning in December 2007. An endpoint for the more recent recession has yet to be designated.
ing year. It is possible to calculate annual gross job gains
and gross job losses for all quarters of the year. Chart 4
presents statistics that measure annual gross job gains
and losses from first quarter to first quarter, from second
quarter to second quarter, from third quarter to third
quarter, and from fourth quarter to fourth quarter. These
annual statistics in chart 4 are not seasonally adjusted. The
long-term pattern of the annual gross job gains and losses,
computed for every quarter within the year, appears similar to the pattern of the quarterly statistics in chart 1. The
2001 recession is particularly evident in the annual statistics: the annual gross job gains exceed the annual gross job
losses for all quarters prior to 2001, and then during 2001
the gross job gains fall and the gross job losses rise.
The statistics in chart 4 are not seasonally adjusted, and
a careful look reveals some seasonal properties in the annual gross job gains and losses when they are tabulated
for every quarter of the year. Looking at the 1990s, where
the seasonal pattern is quite evident in chart 4, one can
see that the annual first quarter-to first quarter gross job
gains are somewhat less than the annual gross job gains
tabulated for second quarter-to-second quarter, third
quarter-to-third quarter, and fourth quarter-to-fourth
50
Monthly Labor Review • May 2009
quarter. Similarly, the annual first quarter-to first quarter
gross job losses are somewhat less than the annual gross
job losses tabulated for the other three quarters of the year.
This seasonal pattern is much more evident in chart 5,
which is the same as chart 4 except that it covers only retail trade, which is a very seasonal industry. In retail trade,
annual gross job gains and gross job losses are low when
computed first quarter-to-first quarter and are high when
computed fourth quarter-to-fourth quarter. The resulting
annual net employment change for retail trade, computed
as the difference between the annual gross job gains and
annual gross job losses, exhibits no seasonal pattern.
Annual gross job gains and losses, when tabulated for
every quarter of the year, show a well-defined seasonal
pattern in charts 4 and 5. The key to understanding this
seasonal pattern begins with noting that the annual gross
job gain series and gross job loss series for retail trade in
chart 5 have the same seasonal pattern—both are low in
the first quarter and both are high in the fourth quarter.
This is different from the pattern of the non-seasonally
adjusted quarterly gross job gains and gross job losses for
retail trade, in which the quarterly gross job gains jump in
the fourth quarter as establishments hire for the holiday
Chart 4.
Annual gross job gains and losses; first quarter-to-first quarter, second-to-second, third-to-third,
and fourth-to-fourth; third quarter 1993 through second quarter 2008; not seasonally adjusted
Thousands of jobs
Thousands of jobs
18,000
18,000
Annual gross job gains
15,000
15,000
Annual gross job losses
12,000
9,000
12,000
1993 1994 1995 1996 1997 1998 1999 2000 2001
2002 2003 2004 2005 2006 2007 2008
9,000
Note: The first quarter of each year ends in March, and the first quarter’s endpoint is represented by the year’s long tick mark. Each
datum for each year of measurement is plotted at the end of the year in question. For example, the year from third quarter 1992 to
third quarter 1993 is plotted in September 1993. The shaded bars denote National Bureau of Economic Research (NBER)-designated
recessions, one running March 2001–November 2001 and the other beginning in December 2007. An endpoint for the more recent
recession has yet to be designated.
Chart 5.
Annual gross job gains and losses in retail trade; first quarter-to-first quarter, second-to-second,
third-to-third, and fourth-to-fourth; first quarter 1993 through second quarter 2008;
not seasonally adjusted
Thousands of jobs
2,500
Thousands of jobs
2,500
Annual gross job gains
2,000
1,500
2,000
Annual gross job losses
1,500
1,000
1,000
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Note: The first quarter of each year ends in March, and the first quarter’s endpoint is represented by the year’s long tick mark. Each
datum for each year of measurement is plotted at the end of the year in question. For example, the year from third quarter 1992 to
third quarter 1993 is plotted in September 1993. The shaded bars denote National Bureau of Economic Research (NBER)-designated
recessions, one running March 2001–November 2001 and the other beginning in December 2007. An endpoint for the more recent
recession has yet to be designated.
Monthly Labor Review • May 2009 51
Annual BED Data
season and then the quarterly gross job losses jump in the
first quarter as the temporary holiday employees leave the
retail establishments.
The source of the seasonality in chart 5 can be best explained with a simple example. Assume a simple economy
with three establishments in the retail trade industry. All
three of these establishments have 10 employees in the
first, second, and third quarters, and all three establishments want to have 15 employees in the fourth quarter.
If the first establishment manages to have 15 employees
in the fourth quarter of every year, the annual gross job
gains and gross job losses for this establishment will be
zero whether they are measured from first quarter to first
quarter, second quarter to second quarter, third to third, or
fourth to fourth. Now assume that the second establishment has 14 employees in the fourth quarter of one year
and 16 employees in the fourth quarter of the following
year. The annual gross job gain for this establishment will
be two employees when comparing employment from the
fourth quarter of one year with the fourth quarter of the
next year. To complete the example, assume that the third
establishment has 16 employees in the fourth quarter of
one year and 14 employees in the fourth quarter of the
following year. The annual gross job loss for this establishment will be two employees when comparing employment from the fourth quarter of one year with the fourth
quarter of the next.
In this simple example, industry employment is always
45 employees in the fourth quarter, but a seasonal spike
occurs in the annual fourth quarter-to-fourth quarter
gross job gains and gross job losses. Such a seasonal spike
originates from establishment-level variation in the number of additional workers each establishment hires during
its seasonal peak in employment. This illustration shows
that one should expect annual gross job gain and gross job
loss data to exhibit seasonal spikes when they are tabulated for every quarter of the year.
Comparisons with other annual series
This section of the paper compares the BED annual gross
job gain and loss statistics with the U.S. Census Bureau’s
Business Dynamics Statistics (BDS) data.6 The Census
Bureau released the first BDS data in December 2008.7 The
BDS program uses concepts and definitions that are similar
to those of the BED program, as one can see by reading the
technical documentation for the new BDS data: “The BDS
data measure the net change in employment at the establishment level. These changes come about in one of four
ways. A net increase in employment can come from either
52
Monthly Labor Review • May 2009
opening establishments or expanding establishments. A
net decrease in employment can come from either closing
establishments or contracting establishments. Gross job
gains include the sum of all jobs added at either opening
or expanding establishments. Gross job losses include the
sum of all jobs lost in either closing or contracting establishments. The net change in employment is the difference
between gross job gains and gross job losses.”8
To compare the BED annual gross job gain and loss statistics with the Census Bureau’s BDS data, this article uses
the first quarter-to-first quarter BED data since the BDS
data are tabulated as first quarter-to-first quarter comparisons. The BDS data are available for the years 1977–2005,
whereas the BED annual data are available for the years
1994–2008. Charts 6 and 7 cover the 1994–2005 period,
during which the two series overlap.9
Chart 6 shows gross job gains and gross job losses for the
BED and BDS series. One can immediately see that every
year, the BDS annual gross job gains and gross job losses
are greater in magnitude than those of the BED program.
In the 1994–99 period, the BDS gross job gains are 15
percent higher than the BED gains, and the BDS gross job
losses are 20 percent higher than the BED losses. In the
2002–05 period, the BDS gross job gains are 36 percent
higher than those of the BED program, and the BDS gross
job losses are 27 percent higher than those of the BED
program.
There are three plausible explanations for these differences in magnitude. First, the level of employment in the
BDS data is consistently higher than the level of employment in the BED data, so it would be expected for the BDS
statistics to fluctuate by larger numbers of jobs than do
the BED statistics.10 The BDS data show approximately 5
percent greater employment in the average year, and the
magnitudes of the gross job gains and losses in the BDS
statistics are 15 to 36 percent higher than they are in the
BED statistics. As such, differences in employment levels
can explain only some of the differences in magnitude observed in chart 6.
A second explanation for the higher levels of gross job
gains and gross job losses in the BDS statistics relative to
the BED statistics might be the failure to properly link
data. As noted previously, analysis of the BED statistics
has shown that gross job gain and loss data that do not
take account of linkage information within the year lead
to levels of gross job gains and losses that are about 10
percent higher. However, this hypothesis of missing links
suggests that almost all of the difference between the BDS
and the BED statistics should be in the openings and closings data, with only a small difference in the expansions
Chart 6.
BLS BED and Census BDS annual first quarter-to-first quarter series, 1994–2005, not seasonally adjusted
Gross job gains
Thousands of jobs
Thousands of jobs
22,000
22,000
20,000
20,000
18,000
18,000
Census BDS
16,000
16,000
BLS BED
14,000
14,000
12,000
12,000
10,000
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
10,000
Gross job losses
Thousands of jobs
Thousands of jobs
22,000
22,000
20,000
20,000
18,000
18,000
16,000
16,000
14,000
Census BDS
BLS BED
12,000
10,000
1994
14,000
1995
1996
12,000
1997
1998
1999
2000
2001
2002
2003
2004
10,000
2005
Sources: Data are from the U.S. Census Bureau’s Business Dynamics Statistics (BDS) program and the U.S. Bureau of
Labor Statistics’ Business Employment Dynamics (BED) program.
Monthly Labor Review • May 2009 53
Annual BED Data
Chart 7.
BLS BED and Census BDS annual first quarter-to-first quarter series, 1994–2005, not seasonally adjusted
Gross job gains from expansions and openings
Thousands of jobs
Thousands of jobs
15,000
15,000
10,000
10,000
5,000
5,000
BLS BED expansions
BLS BED
0
1994
1995
1996
1997
openings
1998
1999
Census BDS expansions
Census BDS openings
2000
2001
2002
2003
2004
0
2005
Gross job losses from contractions and closings
Thousands of jobs
Thousands of jobs
15,000
15,000
10,000
10,000
5,000
5,000
BLS BED contractions
BLS BED
0
1994
1995
1996
1997
Census BDS contractions
Census BDS closings
closings
1998
1999
2000
2001
2002
2003
2004
2005
Sources: Data are from the U.S. Census Bureau’s Business Dynamics Statistics (BDS) program and the U.S. Bureau of
Labor Statistics’ Business Employment Dynamics (BED) program.
54
Monthly Labor Review • May 2009
0
and contractions data. As will be shown later, this is not
the case.
A third possible explanation for the difference in magnitudes is fundamental differences in the underlying
source data. It could be that the QCEW microdata used to
create the BED statistics have less year-to-year establishment-level employment variation than do the underlying
cross-sectional microdata used to create the BDS statistics.
Other than linking the BED and BDS microdata and comparing employment changes for matched establishments,
there does not appear to be any simple way to evaluate the
validity of the hypothesis of differences in the underlying
source data.
Several other facts about the BED and BDS data in chart 6
are also apparent in the graphs. Looking at the time series,
one can see that both the BED and the BDS data show a
dramatic temporary increase in gross job losses in the first
quarter 2001 to first quarter 2002 period. However, only
the BED data show a decrease in gross job gains in the first
quarter 2001 to first quarter 2002 period. This difference
is important. Much of our knowledge of the labor market
dynamics during the 2001 recession comes from quarterly
BED data—the net employment decline during the 2001
recession is characterized by rising gross job losses and
falling gross job gains. The annual first quarter-to-first
quarter BED data show the same labor market dynamics
as the quarterly BED data, albeit with an annual rather
than quarterly reference period that makes it difficult to
interpret short-run employment changes. (The 2001 recession was only 8 months in duration, as dated by the
National Bureau of Economic Research.) However, trying
to understand the 2001 recession using only the BDS data
would miss the employment losses attributable to falling
gross job gains.
Chart 7 explores the components of the BED and BDS gross
job gain and gross job loss data. The first graph shows the
employment gains from expansions and openings, and the
second graph shows the employment losses from contractions and closings.11 One can see that the BDS data on gross
job gains from expansions and on gross job gains from openings are greater in magnitude than the corresponding BED
data. One can also see that the BDS data on gross job losses
from contractions and on gross job losses from closings are
greater in magnitude than the corresponding BED data.
The most interesting difference between the BED and the
BDS data in chart 7 is evident in the 2002 values for jobs
gained from openings and jobs lost from closings. The BDS
statistics for both have an upward blip in trend in this year.
The number of jobs created from establishment openings
according to the BDS statistics is 6.8 million in 2001, 8.0
million in 2002, and 6.7 million in 2003. The equivalent BED
numbers are 5.0 million in 2001, 5.0 million in 2002, and
4.6 million in 2003. One possibility is that this difference in
trend results from the processing of the 2002 quinquennial
Economic Census.
QUARTERLY BUSINESS EMPLOYMENT DYNAMICS STATISTICS were initially released in 2003, and the BED pro-
gram has expanded ever since. The program released industry
statistics in 2004, size-class statistics in 2005, State statistics
in 2007, size-of-employment-change statistics in 2008, birth
and death statistics in 2009, and annual statistics in 2009.
Annual statistics respond to needs of BED customers, and
they also enhance people’s understanding of labor market
dynamics. This article has described how annual BED statistics are created, how they compare with quarterly BED statistics, and how they compare with the U.S. Census Bureau’s
BDS statistics.
NOTES
1
This endnote summarizes the data sources and flows underlying the QCEW
data. All employers subject to State unemployment insurance laws are required
to submit quarterly contribution reports detailing their level of employment
by month and wages by quarter to the State employment security agencies.
The raw data require substantial editing and review. In addition, BLS directs
the States to conduct two supplemental surveys that are necessary to yield accurate data at the local level. The first is the Annual Refiling Survey, for which
the States contact nearly 2 million businesses each year to obtain or update
business names, addresses, industry codes, and related contact information. The
second survey is the Multiple Worksite Report, which collects employment and
wage information for each establishment in multiunit firms within the State.
The Multiple Worksite Report covers about 110,000 businesses (1.4 percent
of all firms, 16 percent of all establishments, and 39 percent of employment)
each quarter, allowing for the matching of employment and wage data with
the correct county and industry. After the raw data are augmented by the data
from the Annual Refiling Survey and Multiple Worksite Report and are then
thoroughly edited by the State Labor Market Information staff, the States submit these data and other business identification information to BLS as part of
the QCEW program.
2
For more detail on the construction of the BED data, see James R. Spletzer,
R. Jason Faberman, Akbar Sadeghi, David M. Talan, and Richard L. Clayton,
“Business employment dynamics: new data on gross job gains and losses,”
Monthly Labor Review, April 2004, pp. 29–42.
3
For more detail on the definitions of establishment births and establishment
deaths, see Akbar Sadeghi, “The births and deaths of business establishments
in the United States,” Monthly Labor Review, December 2008, pp. 3–18. BED
Monthly Labor Review • May 2009 55
Annual BED Data
birth and death statistics are available at the BED website at www.bls.gov/bdm
(visited May 21, 2009).
4
Three research papers document this finding. First, see Joshua C. Pinkston
and James R. Spletzer, “Annual Measures of Job Creation and Job Destruction
Created from Quarterly Microdata,” American Statistical Association 2002 Proceedings of the Section on Business and Economic Statistics, pp. 3311–16. Second,
see Joshua C. Pinkston and James R. Spletzer, “Annual measures of gross job
gains and gross job losses,” Monthly Labor Review, November 2004, pp. 3–13.
And third, see Sadeghi, “The births and deaths of business establishments.”
5
For a more complete discussion of the differences between an annual statistic and the sum of four quarterly statistics, see Pinkston and Spletzer, “Annual
measures of gross job gains and gross job losses.”
6
The authors acknowledge and appreciate the comments of Ron Jarmin and
Javier Miranda of the U.S. Census Bureau, who reviewed a prepublication draft
of this article.
7
The press release from the U.S. Census Bureau announcing the BDS data series can be found at www.census.gov/Press-Release/www/releases/archives/
employment_occupations/013012.html (visited April 2, 2009).
8
56
This quote is from www.ces.census.gov/index.php/bds/bds_overview#_
Monthly Labor Review • May 2009
Concepts_and_Methodology (visited April 2, 2009). Note that the BDS
program uses the terms “gross job gains” and “gross job losses” in its technical
documentation, yet it uses the terms “job creation” and “job destruction” in its
downloadable database. This article uses the terms “gross job gains” and “gross
job losses” when comparing BED data with BDS data.
9
The two series have strengths and weaknesses relative to each other. Users
who want data that are more current will need to use the BED data, whereas
users who want a time series dating back to the 1970s will need to use the BDS
data.
10
In the BDS database, the level of employment for the second quarter of 1998
is 106.6 million jobs. This is 4.4 million higher than the BED level of employment for the second quarter of 1998 (as published in Pinkston and Spletzer,
“Annual measures of gross job gains and gross job losses”). The BDS level of
employment is consistently higher than the BED level, and the difference grows
over the 1998–2002 period; the difference is 6.4 million in the first quarter of
2002.
11
The BDS program’s technical documentation focuses on the terms openings
and closings, whereas the downloadable BDS database uses the terms “entries”
and “exits” as well as births and deaths. This article uses the terms openings and
closings.
Workplace Injuries and Illnesses
Comparing Workers’ Compensation claims
with establishments’ responses to the SOII
Comparing elements of the Workers’ Compensation database
with data from the Survey of Occupational Injuries and Illnesses
is a useful way to determine which types of injuries and illnesses
the SOII is most likely to undercount
Nicole Nestoriak
and
Brooks Pierce
Nicole Nestoriak and Brooks
Pierce are economists in the
Office of Compensation and
Working Conditions, Bureau of
Labor Statistics. E-mail: nestoriak.nicole@bls.gov, pierce.
brooks@bls.gov.
T
he Bureau of Labor Statistics’ Survey of Occupational Injuries and
Illnesses (SOII) collects and tabulates employer reports on work-related injuries and illnesses. SOII estimates are the
primary source of information on nonfatal
work-related injuries and illnesses in the
United States.
Recent work comparing SOII microdata with other administrative sources of
work-related injury and illness data, in
particular Workers’ Compensation (WC)
claims databases, concludes that the SOII
substantially undercounts cases. This article focuses on the paper “Capture-Recapture Estimates of Nonfatal Workplace
Injuries and Illnesses” by Leslie I. Boden
and Al Ozonoff, which compares SOII
case records with WC microdata for several States. Their findings indicate that the
SOII detects between 50 percent and 75
percent of cases in the States studied.1
The present article describes the
Boden-Ozonoff study and reports some
additional findings that were obtained
by analyzing a subset of the data that the
Boden-Ozonoff paper used. This new
research extends the aggregate results reported by Boden and Ozonoff in order to
determine which types of cases the SOII
is most likely to undercount. In particular,
the present article focuses on differences in
the SOII capture rate by establishment type, by
time of case filing, and by type of injury.
Methods
The basic method underlying the BodenOzonoff study involves comparing the SOII list
of injury and illness cases with an analogous
list, covering the same workforce, from the
Workers’ Compensation administrative system
to determine to what extent the lists overlap.
Cases in the WC claims microdata that are
not found in the SOII sample are considered
missed by the SOII and form the basis of the
estimated SOII undercount.
Although this method is logically straightforward, it is difficult to carry out. Because
any given injury is processed independently
and represented differently in the two systems, it is not always possible to definitively
link the case’s representation in the SOII with
its representation in the WC data. Further, it
is often difficult to determine whether or not
a reported WC injury or illness case occurred
in an establishment that was within the SOII
sample. Finally, in comparing the SOII and WC
data it is critical to exclude cases outside the
scope of one or the other of the data sources;
otherwise a simple difference in scope will be
misinterpreted as underreporting.2 It is someMonthly Labor Review • May 2009 57
Workplace Injuries and Illnesses
times challenging, however, to determine whether or not
a given case is in scope for WC or the SOII.
Data sources
This section describes the data sources for the article and
describes in particular the aspects of the data relevant to
the matching exercise.
The SOII is an annual establishment survey that most
recently sampled approximately 176,000 establishments
in private industry. Because the SOII is a survey, it does not
give a complete listing of the experiences of every privatesector establishment. Rather, sampled establishments in
effect represent the greater universe of establishments.
Sampling is a valid approach for producing estimates, but
the fact that the SOII is based on a sample rather than
a census does make the matching exercise in Boden and
Ozonoff ’s paper more challenging.
SOII respondents are directed to report from on-site
injury logs maintained as part of the Occupational Safety
and Health Administration’s record-keeping requirements. The record-keeping rules dictate that records be
maintained at an establishment’s physical location; accordingly, BLS samples data at the establishment level
rather than at the firm level.3 Firms with multiple sites
or establishments may have some, none, or all of their establishments sampled in any given year. Data for a given
survey year are reported to BLS in the first half of the year
following the survey year.
For more serious injury or illness cases—those involving at least 1 day away from work beyond the date of
injury or onset of illness—the SOII collects detailed information describing the incident and the affected employee.
The SOII program refers to these cases as “days away from
work” cases. The information that is collected includes the
nature and source of the injury or illness, the part of the
body affected, and the date of the onset of the injury or illness, as well as the employee’s name, date of birth, sex, and
race. These data, as well as information on the employer,
are used to help identify cases for the purposes of matching SOII records with WC administrative records.
The Boden-Ozonoff group obtained permission from
several States to match WC claims microdata with SOII
microdata. Because the SOII data are confidential, all data
analysis was carried out at BLS. And because WC data include confidential information, there were some data to
which BLS did not have access. However, BLS did obtain
permission from one State, Wisconsin, to further analyze
its 1998–2001 WC data. Boden and Ozonoff also made
their intermediate data sets available to BLS, which made
58
Monthly Labor Review • May 2009
this article’s detailed analysis possible.
Workers’ Compensation systems differ from State to
State, but on the whole they have similar features. Most
States mandate coverage of nearly all private-sector workers. WC typically covers almost all medical expenses arising from a work-related injury or illness, it recompenses
portions of lost earnings due to temporary injuries or illnesses if the duration of the injury or illness exceeds a
minimum waiting period, and it provides partial or total
disability payments in the event of permanent injury or
illness. Temporary injury and illness cases in Wisconsin
from 1998 to 2001 were compensable under WC if they
satisfied a 3-day waiting period. An employee generally
has 2 years to report a workplace injury to his or her employer, although most injuries are reported much earlier.
Some traumatic injuries (vision loss, total loss of a hand or
arm, permanent brain injury, etc.) and some occupational
diseases (carpal tunnel syndrome, hearing loss, etc.) have
no time limit for filing a claim.
Under the WC system, cases may be claimed by workers
but disputed by the employer.4 An employer may believe
a given injury is not work related, or the employer may
dispute the degree of disability. In such cases the employee may request that the State office of WC resolve the
dispute via a hearing before an administrative law judge.
Negotiated settlements are possible. The WC data that this
article uses include some contested cases and negotiated
settlements, but they are not identified separately from
the other cases. The Wisconsin WC system reported on
average about 50,000 lost-time claims per year over the
2000–06 period. Of these, about 18 percent (an annual
average of about 9,200 claims) were marked as denials,
as injuries or illnesses that that did not require days away
from work, or as noncompensable cases. About 13.6 percent (6,800) of claims were litigated annually.5
The Boden-Ozonoff study imposes scope restrictions
on each data source; the intent is for every data source to
refer to the same sets of at-risk private-sector employees.
As an example, mining and railroad sector data are excluded because the SOII program does not collect those
data through its normal survey instrument. (Rather, it
relies on administrative files from the Mine Safety and
Health Administration and the Federal Railroad Administration.) As another example, injury and illness cases
in the SOII involving fewer than 3 days away from work
are excluded, as such cases do not meet the Wisconsin
WC system waiting period requirements.6 Perhaps the
most important scope restriction calls for the discarding
of WC cases that arose in establishments which are not
in the SOII sample. To do so accurately requires that one
identify the establishments from the SOII sample in the
WC data, which may be difficult—especially in the case of
multiestablishment firms as described earlier. In general
one expects such scope restrictions to cause some degree
of error beyond the margin of error that would normally
be expected. Some of the numerical results in this article
are consequently subject to some additional error because
of issues of scope caused by data limitations in the BodenOzonoff study.
In the end, there are 4 years of SOII and WC injury and
illness case data available. These data comprise approximately 217,000 distinct cases.7 The SOII and WC case lists
overlap substantially, but not completely: the SOII list covers about 70 percent of all observed SOII and WC cases,
and the WC list covers about 81 percent. In other words,
the Boden-Ozonoff study suggests that the SOII estimates
undercount observed cases by about 30 percent.8
Single-establishment and multiestablishment
firms
Whereas the SOII data come from establishments chosen
for the sample, the WC data tend to reflect reporting by
firms. Consequently, the WC data are not detailed enough
to allow one to consistently determine where within firms
injuries and illnesses have occurred. The issue is a problem
when a firm has multiple establishments of which only
some are sampled by the SOII. Is an injury case apparently
missed by the SOII truly a missed case, or rather is it an injury that occurred at an establishment not in the sample? In
this circumstance there is some ambiguity about whether
to treat the case as one that was misreported to the SOII.
The Boden-Ozonoff study recognizes this issue and
makes a statistical adjustment in the instances in which it
arises. Nevertheless, because the issue is an important one,
it makes sense to show separate results for single-estab-
lishment and multiestablishment firms. The data, when
organized in this way, show that the SOII appears to miss
more cases in multiestablishment firms. This may be due
to an intrinsic difference between single-establishment
and multiestablishment firms, or it may result from the
method used for matching.
Table 1 presents statistics by establishment status. Of
the cases in either the Wisconsin WC data or the SOII
data, roughly 56 percent are in single-establishment firms
and 36 percent are in multiestablishment firms. The remaining 8 percent are of unknown status because there is
not enough information available to label them as either
single-establishment or multiestablishment firms.9
Table 1 shows that the SOII capture rates are higher
when only single-establishment firms are considered:
according to the calculations, the SOII captures 77.5
percent of the estimated cases in this subset of the data.
The SOII’s rate of capture of injuries and illnesses in multiunit establishments is 62.2 percent. In establishments
of unknown status, the capture rate is 52.8 percent. The
data for establishments of unknown status appear to behave—both here and in other tabulations—more like the
multiestablishment than the single-establishment data.
One possible explanation for the differences in capture
rates across establishment types is that the single-establishment firms actually do not report their behavior in
the same way that establishments in multiestablishment
firms do. Note, however, that the WC capture rate is similar across the establishment types. Thus, there appears to
be some particular reporting or measurement effect that
differs by establishment status within the SOII but not
within the WC administrative system.
Another possibility is that the single-establishment
firm subset of the data yields more accurate estimates because the method used to adjust the multiestablishment
results introduces error. For the single-establishment firm
Table 1. Capture propensities by status of establishments, 1998–2001
Total number of cases................................................
Percent of cases captured by the SOII. .................
Percent of cases captured by Workers’ . ..............
Compensation
Single-establishment firms
Establishments within
multiestablishment firms
121,567
77.5
79.7
77,967
62.2
83.3
Establishments within
firms of unknown status
17,798
52.8
84.0
NOTE: The “percent captured” rows show the percentage of observed cases captured by the Survey of Occupational Injuries and Illnesses and by Workers’ Compensation. Data are calculated using Workers’ Compensation cases from single-establishment firms in Wisconsin.
Monthly Labor Review • May 2009 59
Workplace Injuries and Illnesses
subset of the data, it is rarer to encounter ambiguity concerning whether or not a given WC claim case occurred
in an establishment sampled by the SOII. Distinguishing
between these two possibilities is an important topic for
further study.
The remainder of this article focuses on cases involving
single-establishment firms. Although these cases do not
represent the full spectrum of cases, using only data from
single-establishment firms allows one to avoid situations
in which one does not know whether an observed WC case
is within the SOII sample or not. Restricting the sample in
this manner is akin to restricting the scope of the two data
sources in the hope that each data source refers to the
same set of workers and injury and illness cases.
SOII capture propensity by time of WC filing
The timing of the collection of injury and illness data is
another characteristic that differs between WC and the
SOII, and it may explain part of the undercount. The SOII
collects data in the first 6 months of the year following
the year of incidence and only contains cases that are recognized as valid, work-related cases of injuries or illnesses
that occurred during or just after the survey year. Cases
that are not recognized prior to data collection obviously
are not included in the SOII counts. The WC administrative data, however, cover cases that were recorded up to 2
years following the date of incidence.
The extract of the Wisconsin WC data used in this article does not include a list of cases’ filing dates. However,
the WC system assigns case identifiers sequentially, and
the case identifier embeds the year of the filing. From the
case identifier one can therefore generate a year and an
imputed month of filing for cases in the WC system.10 Out
of the 121,567 cases in single-establishment firms that the
SOII captured, 96,884 cases are also in the WC system and
are used in this analysis. The remaining 24,683 are in the
records but not the WC records, and they therefore
will be dropped from the remainder of this analysis as,
by definition, there is no time-of-WC-filing information
available for these cases.
Table 2 shows case counts and the “SOII capture propensity” as functions of the year of the WC filing. SOII’s
“capture propensity” is defined here as the percent of WC
cases that appear in the SOII. A case with a date of injury
in 1998 and a WC system identifier indicating a filing in
2000 would be included in the row “2 years after close of
survey year.” Note that about 12.8 percent of cases are filed
in the year following the survey year. We refer to these as
“1-year-after” data for simplicity. A little over 1 percent of
cases are filed with a greater lag. The final column shows
the SOII capture propensity.
Two broad facts are clear in these data. First, there are
a substantial number of cases filed under the WC program
after the close of the SOII survey year. Second, the SOII
capture propensity is much lower for these particular cases. Together these facts suggest that the WC data include
many cases that are not known to SOII respondents, or
have not been deemed work related, at the time of the
survey response.
Aside from the year of filing, another known fact is
the order in which cases are entered into the WC system.
Cases in the 1-year-after data occur disproportionately
early in the filing sequence. About half of these cases appear to have been filed early in the calendar year following
the SOII survey year. For that half, the SOII capture rate is
fairly high, approximately 60–65 percent. For the other
half of the 1-year-after data, the SOII capture rate is approximately one-third. Thus, the 1-year-after capture rate
of 48.0 in table 2 masks variation within the year.
One reasonable conclusion to make is that about half
of the 1-year-after filings are either: 1. delayed WC filings
from workers in establishments that replied to the SOII
with accurate responses, 2. injury and illness cases that
SOII
Table 2. SOII capture propensity by year of WC filing, 1998–2001
Year of WC case filing
Same year as survey year............................................
1 year after close of survey year...............................
2 years after close of survey year.............................
3 years after close of survey year.............................
Number of cases
Distribution
SOII capture propensity
83,256
12,406
917
203
86.0
12.8
.9
.2
76.1
48.0
19.2
4.9
NOTE: Data are calculated using Workers’ Compensation cases from single-establishment firms in Wisconsin.
60
Monthly Labor Review • May 2009
occurred late in the year and were known to SOII respondents at the time they responded, or 3. a combination of 1
and 2. The remaining half of the 1-year-after filings may
reflect continuing or late-developing lost-workday cases
attributed to past injuries. There also exist other possibilities, such as reconciled disputes that enter the books late.
While the SOII program would obviously like to collect
information on all workplace injuries and illnesses occurring in the survey year, the completeness of the data
needs to be weighed against the timeliness in generating
statistics.
Other indicators of low SOII capture propensity
The results in the previous section indicate that some WC
injury and illness cases are reported well after the close of
the survey year, and this raises the question of whether or
not these cases are identifiably different in the WC system.
In other words, are they recognized by the WC system as
distinct from the cases reported within the survey year?
The WC system maintains a variety of fields used to aid in
administration. Some of these fields have data that correlate with the data that are reported late, and this correlation may help in understanding some of the difficulties in
matching administrative data from the WC system with
survey data from the SOII.
To understand WC system data, it helps to understand
WC filing requirements. If an injury or illness results in
days away from work beyond Wisconsin’s 3-day waiting
period, the employer or its insurer must file a first report of
injury within 7 days of onset. The first report contains basic information on the employee and the injury or illness.
The employer or its insurer must also file a supplementary
report within 30 days of onset. This supplementary report
either indicates the amount and type of WC payments to
the employee—including whether the payments are for
temporary total or temporary partial disability—or otherwise must indicate a claim denial or investigation. Additional supplementary reports must be filed as payments
are changed—for example, because of a change in status
from temporary to permanent disability—or stopped,
usually by the employee’s return to work. The WC data
system generates a status flag on the basis of the initial
supplementary report, which typically captures payment
information soon after the onset of the injury or illness.
As shown in table 3, there are clear differences in the SOII
capture propensity across status flag values.
The WC data system maintains information on days
of Total Temporary Disability (TTD), information that is
based on the cumulative supplementary report filings for a
given claim. A day of temporary total disability is roughly
analogous to a lost workday in the SOII. Although the
data are restricted to lost-workday cases in this analysis,
many of the claims have a TTD-day value of zero in the
WC system.11
In an analysis conducted for this article, it was found
that cases reported late tend to have a disproportionately
high number of atypical status flag values and a disproportionately high number of cases with zero TTD days
recorded. It was also found that SOII capture propensity
tends to vary by WC status flag and by the incidence of
zero TTD days recorded, even among WC cases reported
prior to the close of the survey year.
Table 3 shows some of the relevant statistics. The table
displays SOII capture rates, the prevalence of zero-TTDday cases, median case durations, and WC filing lags, all by
WC status flag. The average WC filing lag is based on the
imputed month of filing, as discussed previously. “Case
Table 2.
3. SOII capture propensity and other case characteristics, by Workers’ Compensation status flag, 1998–2001
WC status flag
Total........................................................
Award.........................................................
Electronic..................................................
Final............................................................
Under Investigation..............................
Not final.....................................................
No lost time..............................................
Not required............................................
SOII capture
propensity
Percent with zero
TTD days
Median case
duration
(in days)
Average filing lag
(in months)
71.8
20.2
67.5
74.2
0
37.4
44.2
13.0
11.8
89.8
9.5
10.1
0
38.1
32.1
100.0
10
0
10
10
142
4
3
0
2.1
7.8
1.7
1.9
3.0
11.6
6.3
19.8
Number of cases
96,884
1,787
15,986
78,145
7
12
833
97
NOTE: Data are calculated using Workers’ Compensation cases from single-establishment firms in Wisconsin.
Monthly Labor Review • May 2009 61
Workplace Injuries and Illnesses
duration” refers to the number of days away from work
due to the injury or illness in question.12
About 97 percent of WC cases have a status flag of “electronic” or “final.” Cases marked as “final” have WC payment
information included in the initial supplementary filing.
A case marked as final is likely to be a rather typical case
that has been provisionally recognized by the employer.
Cases marked as “electronic” are those filed electronically;
unfortunately, there is little else that this status flag reveals
about cases. Cases marked as “final” or “electronic” are not
expected to be especially unusual as a group. These cases
are on average reported relatively promptly to the office
that handles WC claims, and they have typical durations.
Of the remaining 3 percent of WC cases, the majority have the “award” status. Cases marked as “award” are
those for which a formal order has been written providing
compensation for the claim. Cases with award status are
typically disputed cases adjudicated in the claimant’s favor
or settled by the claimant and the employer’s insurer. The
SOII only captures 20 percent of the cases with an “award”
status code. When a case is disputed, the final determination of whether the injury or illness is work related can occur long after the year of injury and can result in a lumpsum payment without distinguishing the number of TTD
days involved. This reasoning is consistent with the fact
that about 90 percent of award-status cases have zero TTD
days recorded. The cases with zero TTD days were likely
not perceived as recordable cases by the SOII respondents
at the time of the survey. The status code “no lost time”
indicates the case was initially coded as having no lost
workdays. Consequently, a case coded as “no lost time” can
be one that did not involve days away from work prior
to the initial supplementary report but did involve lost
workdays afterward. The category of no lost time is small,
and cases in the category tend to have low SOII capture
rates, shorter durations than average, and some lag in reporting.
One of the main points of table 3 is that in the WC system, both the type of injury or illness case and the length
of time between the onset of the injury or illness and the
filing date of the case are related to the likelihood of the
case being reported to the SOII. Certain cases or case types
are less likely to be captured by the SOII. The SOII probably misses some cases that it should have captured, but
because of difficulty in determining which cases are in and
out of scope, some of the cases that the SOII is found to
“miss” actually could be cases that are outside its scope.
In order to provide more clarity, the next section of the
article documents the types of injury and illness cases that
are more likely to be reported to the SOII.
62
Monthly Labor Review • May 2009
Better detection of some injuries and illnesses
than others
Both the SOII and WC databases contain information on
the broad type of injury or illness relevant to each case.
This information is referred to as the “nature” of the case,
and it identifies the principal physical characteristics of
the injury or illness. It is easy to imagine that some case
types are easier to identify in general, or are easier to identify specifically as work related, or are more likely to be
perceived as severe and therefore presumably more likely
to be reported in the SOII or in WC claims.
Table 4 shows the most common nature-of-injury-orillness codes in the WC administrative data, ranked in descending order by the SOII capture propensity.13 Like table
3, table 4 also reports the percent of cases with zero TTD
days reported, median case durations, and the average WC
filing lag.
Categories within the nature-of-injury-or-illness column that cover problems one could reasonably view as
severe, easily identifiable, or having a sudden onset tend
to be better captured by the SOII. For example, the capture
propensities for amputation cases and severance cases are
both about 90 percent. At least according to these data,
the vast majority of amputations are reported in the SOII.
Cases involving concussions, fractures, punctures and the
like also tend to have relatively high SOII capture rates.
Case types such as lacerations, contusions, and strains,
in which one might expect somewhat greater heterogeneity of severity or ease of identification, tend to show average SOII capture rates. Given that these kinds of injuries
are quite common, documenting sources of heterogeneity
within this subset of cases is expected to be an important
element of future research.
Injuries that become apparent or worsen over time such
as inflammation or carpal tunnel are reported in the SOII
much less frequently than the average injury or illness.
These case types also tend to show longer-than-average
lags between the onset of the injury or illness and the WC
filing. Presumably, some of these cases develop too late for
inclusion in the SOII’s collection of data; alternatively, the
cases may be reported less often to the SOII because of
greater difficulty in determining whether or not they are
work related.
Note that the SOII appears to capture virtually zero of
the hearing loss cases. These cases tend to have long reporting lags and are overwhelmingly reported as having
zero TTD days. SOII respondents may not believe these
injuries and illnesses to be recordable by the Occupational
Safety and Health Administration, or they may simply
Table 1.
4.
SOII capture propensity and other case characteristics, by nature of injury or illness, 1998–2001
Nature of injury or illness
Total..............................................................
Amputation....................................................
Severance.......................................................
Dislocation.....................................................
Foreign body.................................................
Multiple physical injuries .........................
Fracture...........................................................
Burn..................................................................
Infection..........................................................
Puncture..........................................................
Concussion.....................................................
Hernia...............................................................
Crushing..........................................................
Dermatitis.......................................................
Sprain...............................................................
Laceration.......................................................
Contusion.......................................................
Strain................................................................
Other specific injuries................................
Respiratory disorders.................................
Rupture............................................................
Carpal tunnel syndrome............................
Inflammation.................................................
Other cumulative injuries.........................
Loss of hearing..............................................
Hearing loss (traumatic)............................
SOII capture
propensity
71.8
90.6
90.0
88.4
87.5
84.4
82.8
82.5
82.3
82.0
81.9
79.5
79.0
76.4
75.2
75.2
73.3
70.9
69.1
60.3
58.5
58.4
57.3
51.1
7.4
0
Percent of cases
with zero
TTD days
11.8
13.7
6.6
5.6
7.4
10.1
8.9
5.6
21.7
6.9
2.7
3.3
12.2
40.5
8.0
10.8
8.2
11.9
10.6
19.6
12.7
9.3
13.2
24.4
94.1
100.0
Median case
duration
(days away
from work)
Average filing lag
(in months)
Number of cases
10
11
13
12
5
14
18
6
7
6
7
16
12
10
8
9
8
9
10
6
25
24
12
9
0
0
2.1
1.6
1.1
1.4
1.4
1.7
1.2
.9
1.7
.9
.9
2.7
1.2
3.3
1.3
1.6
1.5
1.9
2.5
3.0
6.4
4.6
2.5
4.1
10.4
11.4
96,884
858
122
414
410
2,080
6,846
1,322
143
676
149
2,481
1,243
304
4,937
5,285
5,773
45,296
10,941
147
461
2,649
1,266
1,620
714
167
NOTE: Data are calculated using Workers’ Compensation cases from single-establishment firms in Wisconsin.
not know they exist at the time of report. Additionally,
these may be cases for which employees have stronger incentives to file a WC claim, as hearing aids are not covered
by most health insurance plans.
The general patterns in table 4 suggest that the SOII does
a very good job of capturing certain classes of cases, but
they also suggest that the SOII fails to capture a noticeable
fraction of cases—a quarter or more—within certain frequently occurring case types such as strains and sprains. It
is possible that differences in circumstances among similar injuries and illnesses within these categories influence
measurability. If such an underlying heterogeneity exists,
identifying it would be a useful step toward understanding the root causes of the estimated SOII undercount.
THE PURPOSE OF THIS ARTICLE IS TO SHOW some of
the dimensions of the estimated SOII undercount. The
patterns of variation of the SOII capture rate shown in
tables 1–4 suggest various possible explanations for the
undercount. It may be that certain types of cases are inherently difficult to identify as work related, especially in a
timely manner. Further, there may be some yet-unknown
differences in scope between WC and the SOII. As an example, some of the WC cases with zero reported TTD days
may be cases with no lost worktime, cases which by design
should not appear in the SOII as days-away-from-work
cases. Finally, a precise matching of cases from these two
different databases may require data that are better suited
for matching than those currently available. That is, some
of the estimated undercount may be due to outstanding
methodological issues that are difficult to resolve absent
finer data. Clearly, there are various hypotheses that have
been proposed with the aim of explaining the discrepancies between the WC and SOII databases. These hypotheses will need to be scrutinized and tested further in order
to achieve a full understanding of the differences between
the ways in which the WC and SOII systems measure
workplace injuries and illnesses.
Monthly Labor Review • May 2009 63
Workplace Injuries and Illnesses
NOTES
1
Leslie I. Boden and Al Ozonoff, “Capture-Recapture Estimates of Nonfatal Workplace Injuries and Illnesses,” Annals of Epidemiology, June 2008, pp.
500–06. See also John Ruser, “Examining evidence on whether BLS undercounts
workplace injuries and illnesses,” Monthly Labor Review, August 2008, pp.
20–32.
2
Boden and Ozonoff are aware of such difficulties in comparing the SOII
and WC data and take great effort to account for them in their calculations.
When making the less straightforward calculations in their study, they often
purposefully err on the side of producing a smaller estimate of the SOII undercount. Of course, the SOII and WC data were not designed in anticipation of
comparing them, and one should therefore expect some data-related problems
to remain.
3
To construct the SOII sampling frame, BLS takes all units within scope for
the SOII from a universe of establishments that report on unemployment insurance. BLS then makes some improvements to this sampling frame on the basis
of historical collection experience. The intent is to construct a frame of physical
establishment locations; however, in some cases firms are Statewide reporters,
in which case they file only one report in each State in which they operate, and
the report covers all their establishments in the State. Firms sometimes also
have other ways of filing one report that covers multiple establishments (and
therefore multiple physical locations).
4
For evidence on incentives to report injuries to the WC program, see Jeff
Biddle and Karen Roberts, “Claiming Behavior in Workers’ Compensation,”
The Journal of Risk and Insurance, December 2003, pp. 759–80.
5
See www.dwd.state.wi.us/wc/WC_Basic_Facts.htm#WC_Claim_and_
Indemnity_Information (visited May 1, 2009).
6
There are also situations in which the SOII, to ease respondent burden,
collects data for only a subset of the cases occurring in a reporting establishment. Other times—though rarely—not all establishments of a given firm are
actually able to provide data on all their cases of injuries and illnesses; this often occurs because the boundaries of establishments can be unclear. In such a
situation, some sampled units are permitted to provide data that cover more or
fewer employees than are officially in the establishment. When, for any of the
aforementioned reasons, the SOII does not have data on all the cases in a given
establishment, weighting adjustments enable the SOII to statistically account for
all cases. However, these situations require further scope adjustments for the
purposes of matching SOII data to WC data. The Boden-Ozonoff study makes
scope adjustments for establishments from which the SOII, to ease respondent
burden, collects data for only a subset of injury and illness cases. It is not able to
make scope adjustments when sampled units are permitted to provide data that
cover more or fewer employees than are officially in the establishment.
7
64
All case totals in this article are weighted totals that are calculated using
Monthly Labor Review • May 2009
SOII
sampling weights.
The Boden-Ozonoff study imputes that approximately 24,000 cases are
missed by both the WC and SOII systems, and the authors report that the SOII
undercount is larger than that of the WC program. The statistics presented here
do not include imputations for cases missed by both surveillance systems.
8
9
An establishment is identified as part of a multiestablishment firm if there
are multiple establishments within the same unemployment insurance reporting number during the survey year. This method of identification oversimplifies
because firms can encompass business lines across more than one unemployment insurance reporting number. The establishments of unknown status have
unemployment insurance reporting numbers that exist in the sampling frame
at the time the sample is drawn, but not during the survey year. These establishments either merged with other establishments, went out of business, or were
otherwise redefined in the sampling frame at some point between the date of
the drawing of the sample and the survey year.
10
This is done by assuming a constant rate of filing over the course of the
year. That is, a claim with an assigned claim number in the bottom fourth of the
distribution of numbers is imputed to have been filed in the first quarter. The
imputed-month-of-filing data are not error free, but they do correlate well with
the date-of-injury-or-illness data recorded in the BLS system for matched cases.
The imputation is therefore believed to be useful.
11
There are a number of scenarios that can lead to a claim being marked
as having zero TTD days in the WC administrative data. As one example, the
employer can continue regular salary payments to an employee whose injury
or illness has caused days away from work, such that no compensation for lost
earnings is due to the employee. As another example, the insurer can erroneously make WC payments (which would initiate a claim in the system) though
the waiting period has not been satisfied. Another possibility is for compromise
settlements to be recorded as having no compensable TTD days due. One cannot
determine the reason that a given case has been designated as a zero-TTD case,
but the scenarios noted here suggest that these cases are probably more difficult
to capture in the SOII. Cases that truly involve no lost workdays, such as cases of
an immediate permanent disability upon injury, are presumably excluded from
these data.
12
The number of days away from work is reported consistently to the SOII.
For cases that are in the WC database but not in the SOII database, the number
of days away from work is imputed using TTD days.
13
The nature-of-injury-or-illness codes used in the Wisconsin WC system
differ from the codes used by BLS in its publications. Therefore, cases identified as, for example, punctures in table 4 would not necessarily be identified as
punctures under the BLS categorization.
Book Review
The Economics of Sustainable Development. By Sisay Asefa, editor, Kalamazoo, MI, W.E. Upjohn Institute
for Employment Research, 2005, 191
pp., $40/cloth, $15/paperback.
Most of us are fairly certain that sustainable development is important.
Trouble is, we are not quite sure what
the term means. This and many other
related issues are taken up in The Economics of Sustainable Development, edited by Sisay Asefa, professor of economics at Western Michigan University. This volume assembles six papers
presented during the annual Werner
Sichel Economics Lecture-Seminar
Series at Western Michigan University within an international development context, emphasizing topics
such as poverty, agriculture, inequality, population growth, and property
rights.
The introduction provides an extensive summary and brief synthesis
of the papers that follow. In the first
paper, Malcom Gillis tells us that although there is no universal agreement on what is meant by sustainable development, the weight of the
knowledge suggests that sustainable
development has to do with discovering a path for growth that maximizes
net benefits for society after taking
into account the costs of environmental degradation. This definition is
65
Monthly Labor Review • May 2009
indeed consistent with those found in
environmental economics textbooks.
The second and third papers deal
with two issues that are critical for the
developing world: avoiding humanitarian disasters and securing greater
agricultural production through productivity gains. Next we learn from
David Lam about how falling mortality rates brought on a world population explosion during the 1950s
and 1960s, and how declining fertility rates brought it to an end. Since
the 1970s and continuing to the present, parents are having fewer children
and investing more in schooling and
health care, a cause for optimism.
In the fifth paper, Daniel Bromley offers a philosophical discussion
of the connection between property
rights and environmental sustainability. The final paper by Scott Swinton
examines whether poor farmers are
forced to overuse natural resources in
order to survive in the short-run. He
finds that the poor are not necessarily bad stewards of natural resources,
but face capacity constraints not encountered by farmers in richer countries. He theorizes that poor farmers
would respond to the proper mix of
incentives that promote sustainable
resource usage, including clearly defined and durable property rights,
support from local institutions, and
an efficient transportation and com-
munication system.
Clearly, the volume deals with quite
a diverse set of topics. Some readers
may have difficulty finding commonalities between the six very different
essays. More attention to an introductory synthesis would have been
helpful in this regard. One theme that
they do have in common is the notion
of capacity building: What institutions, policies, and capabilities lead to
the path of sustainable development
in the developing world?
A minor discomfort with this volume has to do with the title: The
Economics of Sustainable Development
suggests to the reader that what follows is a survey of the economics of
sustainability, which is not the case.
A better title would have been Essays
in Sustainable Development, suggesting a more loose collection of papers
around a general theme.
In general, The Economics of Sustainable Development offers valuable attention to specific issues that may be
of interest to a variety of scholars in
interested in economic development
and sustainability.
—David A. Penn
Director and Associate Professor of
Economics
Middle Tennessee State University
Murfreesboro, TN
Précis
Credit and debit card
rewards
From their origin in the 1980s to today, payment card rewards programs
in the United States have become
more and more widespread. In addition, the types of rewards offered for
using payment cards have become
more diverse, and consumers’ return
on each dollar spent has been increasing. The word “rewards” implies that
the programs are beneficial; nonetheless, one must ask, as economist Fumiko Hayashi does in a recent paper,
“Do U.S. Consumers Really Benefit
from Payment Card Rewards?” (Economic Review, Federal Reserve Bank
of Kansas City, first quarter 2009).
There are two main payment structures for card transactions. In one, the
card issuer bills the cardholder; pockets the “merchant fee,” which averages
1.88 percent of the transaction; and
sends the rest of the money to a “merchant acquirer.”The merchant acquirer
takes a smaller cut of the money and
sends the remainder of the value of
the purchase to the merchant. Debit
cards that require consumers to input a PIN generally charge lower fees
than other types of cards. The other
type of payment structure is similar
to the first but skips the step of the
merchant acquirer.
The value of rewards for credit card
users is typically around 1 percent of
purchases. It is difficult to pinpoint
a source of the money that funds
rewards programs, but there is evidence suggesting that more generous
card rewards lead to greater fees for
merchants. If businesses pass on merchant fees to consumers in the form
of higher prices, then in fact payment
cards are not beneficial to consumers
as a whole (because merchant fees are
generally a larger percentage of the
transaction than are rewards).
Even if more lavish rewards effect
higher merchant fees and the elevated
merchant fees lead to higher consumer prices, it is likely that some type of
66
Monthly Labor Review • May 2009
rewards structure for payment cards
would still be beneficial to society. This
is because cash and check transactions
also cost money to process. The most
efficient card programs likely would
include transaction-based fees for
cardholders in addition to rewards.
The size of the transaction would help
determine whether the cardholder
pays a fee or receives an award for
the transaction. Rewards only maximize efficiency when the benefit to
the merchant for conducting the card
transaction is superior to the cost of
the transaction to the payment service providers. Hayashi acknowledges
that more data are needed to make
a strong case, but she concludes that
available evidence and models indicate that payment card rewards programs currently are too generous and
are therefore inefficient.
Regional effects of the most
recent recession
What are the likely long-term economic effects of the most recent
recession on the Nation’s regions?
In “How the Crash Will Reshape
America” (Atlantic Monthly, March
2009), University of Toronto business
professor and urban theorist Richard
Florida offers some interesting and
well-reasoned speculations in answer
to that question. Professor Florida
analyzes economic and demographic
trends in the major regions of the
United States and argues that in the
long run, geographic location is still
of primary importance to economic
growth. For various reasons, which the
author attempts to explain, some areas will be hit harder by the recession
that began in 2007 than others. In addition, some areas are likely to recover
more quickly than others—some will
even be strengthened—while others
might never fully recover.
Professor Florida begins with
New York City, by most measures the
world’s largest financial center and the
place where the financial crisis began.
He makes the important point that,
throughout modern history, “capitalist power centers” like New York have
remained remarkably stable. Amsterdam was the leading financial center
in the world from the 17th century
to the early 19th century when it was
displaced by London. Although the
U.S. economy was larger than the
British economy by 1900, New York
did not surpass London to emerge as
the world’s largest financial center until after World War II. Because these
centers tend to be densely populated
urban areas, with high concentrations
of educated professionals (financial
specialists, accountants, lawyers, and
so forth) from various industries, they
are very difficult to duplicate elsewhere. As a result, these areas tend to
be more economically stable and thus
able to endure the effects of recessions better than other areas, where
the economies are often more dependent upon just a few industries.
Florida predicts that New York
will emerge from the most recent recession economically stronger that it
was prior to the downturn. He argues
that the portion of the New York
economy represented by the financial
sector had grown too large during the
“recent bubble,” and that the shift in
jobs from the financial sector to other
services will strengthen the economy
in the long run. Moreover, the rest
of the country will continue to be
strongly influenced by the New York
economy, and New York will remain
the financial capital of the world for
some time to come.
The areas of the country that are
likely to suffer the worst effects of the
most recent recession are the older
manufacturing centers, such as the
Rust Belt. The U.S. manufacturing
sector has declined from about 30
percent of total nonfarm employment
in 1950 to about 10 percent currently.
Professor Florida argues that other
areas, such as the Sun Belt, will also
emerge weaker, in part because their
recent booms were driven by “realestate speculation, overdevelopment,
and fictitious housing wealth.”
Current Labor Statistics
Monthly Labor Review
May 2009
NOTE: Many of the statistics in the
following pages were subsequently
revised. These pages have not been
updated to reflect the revisions.
To obtain BLS data that reflect all revisions, see
http://www.bls.gov/data/home.htm
For the latest set of "Current Labor Statistics,"
see http://www.bls.gov/opub/mlr/curlabst.htm
Current Labor Statistics
Notes on current labor statistics . ..............
68
Comparative indicators
1. Labor market indicators..................................................... 80
2. Annual and quarterly percent changes in
compensation, prices, and productivity........................... 81
3. Alternative measures of wages and
compensation changes.................................................... 81
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........................................................
82
83
84
84
Labor compensation and collective
bargaining data
30.
31.
32.
33.
Employment Cost Index, compensation ..........................109
Employment Cost Index, wages and salaries .................... 111
Employment Cost Index, benefits, private industry .......... 113
Employment Cost Index, private industry workers,
by bargaining status, and region..................................... 114
34. National Compensation Survey, retirement benefits,
private industry ............................................................. 115
35. National Compensation Survey, health insurance,
private industry............................................................... 118
36. National Compensation Survey, selected benefits,
private industry.............................................................. 120
37. Work stoppages involving 1,000 workers or more............. 120
Price data
91
92
93
38. Consumer Price Index: U.S. city average, by expenditure
category and commodity and service groups.................. 121
39. Consumer Price Index: U.S. city average and
local data, all items ........................................................ 124
40. Annual data: Consumer Price Index, all items
and major groups........................................................... 125
41. Producer Price Indexes by stage of processing................... 126
42. Producer Price Indexes for the net output of major
industry groups.............................................................. 127
43. Annual data: Producer Price Indexes
by stage of processing..................................................... 128
44. U.S. export price indexes by end-use category................... 128
45. U.S. import price indexes by end-use category................... 129
46. U.S. international price indexes for selected
categories of services...................................................... 129
94
Productivity data
95
47. Indexes of productivity, hourly compensation,
and unit costs, data seasonally adjusted.......................... 130
48. Annual indexes of multifactor productivity........................ 131
49. Annual indexes of productivity, hourly compensation,
unit costs, and prices...................................................... 132
50. Annual indexes of output per hour for select industries..... 133
85
85
86
86
87
90
95
96
96
22. Quarterly Census of Employment and Wages,
10 largest counties . ....................................................... 97
23. Quarterly Census of Employment and Wages, by State... 99
24. Annual data: Quarterly Census of Employment
and Wages, by ownership............................................... 100
25. Annual data: Quarterly Census of Employment and Wages,
establishment size and employment, by supersector....... 101
26. Annual data: Quarterly Census of Employment and
Wages, by metropolitan area ......................................... 102
27. Annual data: Employment status of the population.......... 107
28. Annual data: Employment levels by industry ................. 107
29. Annual data: Average hours and earnings level,
by industry..................................................................... 108
International comparisons data
51. Unemployment rates in 10 countries,
seasonally adjusted......................................................... 136
52. Annual data: Employment status of the civilian
working-age population, 10 countries........................... 137
53. Annual indexes of productivity and related measures,
17 economies................................................................ 138
Injury and Illness data
54. Annual data: Occupational injury and illness..................... 140
55. Fatal occupational injuries by event or exposure ................ 142
Monthly Labor Review • May 2009 67
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
68
Monthly Labor Review • Mayl 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 • May 2009
69
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
70
Monthly Labor Review • Mayl 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 • May 2009
71
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
72
Monthly Labor Review • Mayl 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 • May 2009
73
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
74
Monthly Labor Review • Mayl 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 • May 2009
75
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
76
Monthly Labor Review • Mayl 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 • May 2009
77
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 pub78
Monthly Labor Review • Mayl 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 • May 2009
79
Current Labor Statistics: Comparative Indicators
1. Labor market indicators
Selected indicators
2007
2007
2008
I
II
2008
III
IV
I
II
2009
III
IV
I
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
65.9
62.9
4.5
4.6
10.8
3.6
4.4
9.1
3.5
66.6
63.4
4.5
4.6
11.5
3.5
4.4
9.0
3.6
66.0
63.0
4.7
4.8
11.8
3.6
4.6
9.7
3.7
65.9
62.8
4.8
4.9
12.1
3.7
4.7
9.9
3.8
65.7
62.3
4.9
5.1
12.7
3.9
4.8
10.1
3.9
66.6
62.8
5.4
5.6
13.5
4.2
5.1
11.1
4.1
65.9
62.0
6.0
6.5
14.9
5.1
5.6
11.9
4.5
65.7
61.0
6.9
7.5
16.5
6.0
6.1
11.6
5.2
65.4
59.5
8.1
8.8
18.0
7.4
7.2
12.9
6.2
1
Total nonfarm…………………….................................................... 137,598
Total private....................................................................... 115,380
137,066
114,566
137,400
115,250
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
133,019
110,481
22,233
Manufacturing………….………………..………………………… 13,879
21,419
13,431
22,392
13,966
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
19,537
12,310
Service-providing……………………………………………….…………..…115,366
115,646
115,008
115,356
115,553
116,109
116,014
115,849
115,485
114,542
113,482
Goods-producing ……………………………………………….…………..
Average hours:
Total private........................................…………..........................
Manufacturing………...……………………………………………
Overtime……..………….………………...………………………
33.9
41.2
4.2
33.6
40.8
3.7
33.9
41.2
4.3
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
33.2
39.3
2.7
Civilian nonfarm ……………………………….…………………………….……
3.3
2.6
.9
.8
1.0
.6
.8
.7
.8
.3
.4
Private nonfarm……………...............………...............................
3.0
2.4
.8
.9
.8
.6
.9
.7
.6
.2
.4
2.4
2.4
.4
1.0
.5
.6
1.0
.7
.4
.3
.4
1, 2, 3
Employment Cost Index
Total compensation:
4
5
Goods-producing ……………………………………………….…………
5
Service-providing ……………………………………………….…………
State and local government ……………….………………………
Workers by bargaining status (private nonfarm):
Union……………………………………………………………………
Nonunion…………………………………………………………………
1
3.2
2.5
.9
.9
.9
.6
.9
.7
.6
.3
.4
4.1
3.0
1.0
.6
1.8
.7
.5
.5
1.7
.3
.6
2.0
3.2
2.8
2.4
-.3
1.0
1.2
.9
.5
.8
.7
.6
.8
.9
.8
.7
.7
.6
.6
.2
1.0
.3
Quarterly data seasonally adjusted.
Annual changes are December-to-December changes. Quarterly changes
are calculated using the last month of each quarter.
3
The Employment Cost Index data reflect the conversion to the 2002 North
American Classification System (NAICS) and the 2000 Standard Occupational
Classification (SOC) system. The NAICS and SOC data shown prior to 2006 are
for informational purposes only. Series based on NAICS and SOC became the
official BLS estimates starting in March 2006.
2
80
Monthly Labor Review • May 2009
4
Excludes Federal and private household workers.
Goods-producing industries include mining, construction, and manufacturing. Serviceproviding industries include all other private sector industries.
5
NOTE: Beginning in January 2003, household survey data reflect revised population
controls. Nonfarm data reflect the conversion to the 2002 version of the North
American Industry Classification System (NAICS), replacing the Standard Industrial
Classification (SIC) system. NAICS-based data by industry are not comparable with SIC
based data.
2. Annual and quarterly percent changes in compensation, prices, and productivity
Selected measures
2007
2008
2007
I
II
2008
III
IV
I
II
2009
III
IV
I
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
0.9
.8
0.8
.9
1.0
.8
0.6
.6
0.8
.9
0.7
.7
0.8
.6
0.3
.2
0.4
.4
3.4
3.3
2.7
2.6
1.1
1.1
.7
.8
1.0
.9
.7
.6
.8
.9
.7
.7
.8
.6
.3
.3
.4
.4
2.8
3.8
1.8
1.5
.1
.7
1.7
2.5
0
-3.9
1.2
3.9
4.5
1.8
4.1
12.1
6.3
7.4
2.8
10.5
21.5
2.2
2.8
.3
1.5
5.7
1.9
2.5
-.1
3.2
3.8
.1
.2
-.1
.1
-2.4
1.8
1.9
1.2
2.0
11.9
2.8
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
-9.9
1.6
-13.0
-32.5
.1
.1
.2
-2.7
-6.9
1.6
1.4
2.7
2.8
-.7
-.6
5.7
4.8
7.3
7.0
-1.1
-.5
2.2
2.6
4.7
4.7
2.3
2.2
-.5
-.6
1.1
.8
.7
-
-.6
3.8
3.0
1.2
-.4
8.5
6.4
-3.9
-
1
Consumer Price Index (All Urban Consumers): All Items......
Producer Price Index:
Finished goods.....................................................................
Finished consumer goods.................................................
Capital equipment……………………………………………
Intermediate materials, supplies, and components…………
Crude materials.....................................................................
4
Productivity data
Output per hour of all persons:
Business sector.....................................................................
Nonfarm business sector.......................................................
5
Nonfinancial corporations ……………….…………...………………
1
Annual changes are December-to-December changes. Quarterly changes are
calculated using the last month of each quarter. Compensation and price data are not
seasonally adjusted, and the price data are not compounded.
2
only. Series based on NAICS and SOC became the official BLS estimates starting in
March 2006.
4
Annual rates of change are computed by comparing annual averages. Quarterly
percent changes reflect annual rates of change in quarterly indexes. The data are
seasonally adjusted.
Excludes Federal and private household workers.
3
The Employment Cost Index data reflect the conversion to the 2002 North American
Classification System (NAICS) and the 2000 Standard Occupational Classification (SOC)
system. The NAICS and SOC data shown prior to 2006 are for informational purposes
5
Output per hour of all employees.
3. Alternative measures of wage and compensation changes
Quarterly change
Components
Four quarters ending—
2008
I
II
2009
III
IV
I
2008
I
II
2009
III
IV
I
1
Average hourly compensation:
All persons, business sector..........................................................
All persons, nonfarm business sector...........................................
Employment Cost Index—compensation:
1.9
1.7
5.7
5.7
4.9
5.2
4.1
4.1
3.5
3.5
3.4
3.6
3.7
3.9
4.0
4.1
4.1
4.2
.8
.9
.8
.9
.5
.7
.7
.8
.7
.5
.8
.6
.7
.6
1.7
.3
.2
.6
.2
.3
.4
.4
1.0
.3
.6
3.3
3.2
3.1
3.2
3.6
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
.8
.9
.8
.9
.6
.7
.7
1.1
.7
.5
.8
.6
.7
.6
1.8
.3
.3
.7
.2
.3
.4
.4
.6
.4
.5
3.2
3.2
2.6
3.3
3.5
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
2
3
Civilian nonfarm ……….………………………………………….…………..…
Private nonfarm….......................................................................
Union…………..........................................................................
Nonunion…………....................................................................
State and local government….....................................................
Employment Cost Index—wages and salaries:
3
3.5
3.7
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 • May 2009
81
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
Mar.
Apr.
May
June
July
2009
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
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
233,788 232,995 233,198 233,405 233,627 233,864 234,107 234,360 234,612 234,828 235,035 234,739 234,913 235,086
154,287 153,843 153,932 154,510 154,400 154,506 154,823 154,621 154,878 154,620 154,447 153,716 154,214 154,048
66.0
66.0
66.0
66.2
66.1
66.1
66.1
66.0
66.0
65.8
65.7
65.5
65.6
65.5
145,362 146,023 146,257 145,974 145,738 145,596 145,273 145,029 144,657 144,144 143,338 142,099 141,748 140,887
62.2
8,924
5.8
79,501
62.7
7,820
5.1
79,152
62.7
7,675
5.0
79,267
62.5
8,536
5.5
78,895
62.4
8,662
5.6
79,227
62.3
8,910
5.8
79,358
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
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
104,453 104,052 104,152 104,258 104,371 104,490 104,613 104,741 104,869 104,978 105,083 104,902 104,999 105,095
79,047
78,866
78,820
78,913
79,055
79,286
79,308
79,392
79,380
79,335
78,998
78,585
78,687
78,578
75.7
75.8
75.7
75.7
75.7
75.9
75.8
75.8
75.7
75.6
75.2
74.9
74.9
74.8
74,750
75,216
75,147
74,992
74,949
74,973
74,737
74,503
74,292
74,045
73,285
72,613
72,293
71,655
71.6
4,297
5.4
25,406
72.3
3,650
4.6
25,186
72.2
3,673
4.7
25,332
71.9
3,921
5.0
25,345
71.8
4,106
5.2
25,315
71.8
4,313
5.4
25,204
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
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
112,260 111,902 111,990 112,083 112,183 112,290 112,401 112,518 112,633 112,731 112,825 112,738 112,824 112,908
68,382
68,174
68,118
68,367
68,421
68,273
68,666
68,385
68,700
68,753
68,891
68,584
68,917
68,977
60.9
60.9
60.8
61.0
61.0
60.8
61.1
60.8
61.0
61.0
61.1
60.8
61.1
61.1
65,039
65,079
65,196
65,114
65,169
65,103
65,003
65,008
64,975
64,902
64,860
64,298
64,271
64,148
57.9
3,342
4.9
43,878
58.2
3,095
4.5
43,728
58.2
2,923
4.3
43,872
58.1
3,252
4.8
43,716
58.1
3,252
4.8
43,762
58.0
3,170
4.6
44,017
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
17,075
6,858
40.2
5,573
17,041
6,803
39.9
5,729
17,056
6,993
41.0
5,914
17,064
7,231
42.4
5,868
17,073
6,924
40.6
5,620
17,084
6,947
40.7
5,520
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
32.6
1,285
18.7
10,218
33.6
1,075
15.8
10,237
34.7
1,079
15.4
10,063
34.4
1,363
18.9
9,834
32.9
1,304
18.8
10,149
32.3
1,427
20.5
10,137
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
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
189,540 189,019 189,147 189,281 189,428 189,587 189,747 189,916 190,085 190,221 190,351 190,225 190,331 190,436
125,635 125,208 125,198 125,759 125,712 125,979 125,987 125,844 126,298 126,029 125,634 125,312 125,703 125,599
66.3
66.2
66.2
66.4
66.4
66.4
66.4
66.3
66.4
66.3
66.0
65.9
66.0
66.0
119,126 119,580 119,644 119,611 119,417 119,432 119,082 118,964 118,722 118,226 117,357 116,692 116,481 115,693
62.8
6,509
5.2
63,905
63.3
5,628
4.5
63,811
63.3
5,554
4.4
63,949
63.2
6,148
4.9
63,523
63.0
6,295
5.0
63,716
63.0
6,547
5.2
63,608
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
27,843
17,740
63.7
15,953
27,709
17,688
63.8
16,090
27,746
17,755
64.0
16,200
27,780
17,737
63.8
16,009
27,816
17,708
63.7
16,041
27,854
17,744
63.7
15,989
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
57.3
1,788
10.1
10,103
58.1
1,598
9.0
10,022
58.4
1,555
8.8
9,991
57.6
1,728
9.7
10,043
57.7
1,667
9.4
10,109
57.4
1,755
9.9
10,111
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
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.
82
Monthly Labor Review • May 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
2009
2008
Mar.
Apr.
May
June
July
Aug.
32,141
22,024
68.5
20,346
31,820
21,778
68.4
20,251
31,911
21,920
68.7
20,392
31,998
22,125
69.1
20,565
32,087
22,100
68.9
20,391
32,179
22,062
68.6
20,396
32,273
22,201
68.8
20,404
63.3
1,678
7.6
10,116
63.6
1,527
7.0
10,042
63.9
1,528
7.0
9,990
64.3
1,560
7.0
9,873
63.5
1,709
7.7
9,987
63.4
1,665
7.5
10,117
63.2
1,797
8.1
10,072
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
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
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
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.
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
3
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.
5. Selected employment indicators, monthly data seasonally adjusted
[In thousands]
Annual average
2008
Selected categories
2007
2008
Mar.
Apr.
May
June
July
2009
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Characteristic
Employed, 16 years and older.. 146,047 145,362 146,023 146,257 145,974 145,738 145,596 145,273 145,029 144,657 144,144 143,338 142,099 141,748 140,887
Men....................................... 78,254
77,486
77,985
78,029
77,932
77,726
77,683
77,484
77,249
76,938
76,577
75,847
75,092
74,777
74,053
67,876
68,038
68,228
68,042
68,012
67,913
67,789
67,780
67,720
67,567
67,491
67,007
66,970
66,834
Women............................…… 67,792
Married men, spouse
present................................
46,314
45,860
45,975
45,968
45,871
45,902
46,093
45,804
45,887
45,787
45,610
45,182
44,712
44,502
44,470
35,832
35,869
35,825
36,144
36,122
36,189
36,110
35,994
35,864
35,590
35,649
35,632
35,375
35,563
35,481
4,401
5,875
4,937
5,240
5,290
5,495
5,813
5,879
6,292
6,848
7,323
8,038
7,839
8,626
9,049
2,877
4,169
3,349
3,580
3,658
3,905
4,220
4,240
4,418
4,953
5,399
6,020
5,766
6,443
6,857
1,210
1,389
1,364
1,325
1,305
1,359
1,300
1,412
1,514
1,514
1,585
1,617
1,667
1,764
1,839
reasons……………………… 19,756
19,343
19,402
19,792
19,396
19,428
19,348
19,690
19,275
19,083
18,886
18,922
18,864
18,855
18,833
4,317
5,773
4,826
5,152
5,218
5,390
5,693
5,802
6,167
6,742
7,209
7,932
7,705
8,543
8,942
2,827
4,097
3,276
3,537
3,599
3,839
4,160
4,171
4,279
4,889
5,304
5,938
5,660
6,390
6,773
1,199
1,380
1,354
1,328
1,297
1,340
1,287
1,385
1,541
1,499
1,579
1,619
1,658
1,760
1,850
reasons.................………… 19,419
19,005
19,078
19,436
18,997
19,036
18,992
19,269
18,930
18,808
18,635
18,642
18,567
18,562
18,493
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 • May 2009
83
Current Labor Statistics: Labor Force Data
6. Selected unemployment indicators, monthly data seasonally adjusted
[Unemployment rates]
Annual average
2008
Selected categories
2007
2008
2009
Mar.
Apr.
May
June
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
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
5.1
15.8
4.6
4.5
5.0
15.4
4.7
4.3
5.5
18.9
5.0
4.8
5.6
18.8
5.2
4.8
5.8
20.5
5.4
4.6
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
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
4.5
13.2
14.6
11.8
4.1
4.1
4.4
14.2
15.2
13.1
4.2
3.7
4.9
16.5
18.1
14.8
4.5
4.1
5.0
17.0
18.7
15.3
4.6
4.2
5.2
19.1
22.4
15.6
4.8
4.2
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
8.3
29.4
33.8
25.3
7.9
6.7
10.1
31.2
35.9
26.8
10.2
8.1
9.0
30.8
38.6
24.7
8.5
7.6
8.8
24.6
27.8
22.0
8.6
7.6
9.7
32.3
39.9
25.2
9.2
8.2
9.4
29.8
35.4
24.4
9.7
7.5
9.9
32.0
37.7
26.8
10.3
7.5
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
5.6
2.5
2.8
4.6
4.9
7.6
3.4
3.6
5.8
5.5
7.0
2.8
3.4
5.0
5.3
7.0
2.8
3.0
5.0
5.0
7.0
3.0
3.2
5.5
5.5
7.7
3.1
3.4
5.6
5.4
7.5
3.3
3.4
5.8
5.6
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
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
8.2
7.9
8.4
8.9
8.6
9.7
9.8
10.4
10.6
10.9
12.0
12.6
13.3
Some college or associate degree………..
4.4
3.6
5.7
4.6
5.1
3.9
5.0
4.0
5.2
4.3
5.2
4.4
5.3
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
Bachelor's degree and higher 4…………….
2.0
2.6
2.1
2.1
2.3
2.4
2.5
2.7
2.6
3.1
3.2
3.7
3.8
4.1
4.3
Sept.
Oct.
Nov.
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
Mar.
2,797
2,549
2,444
1,143
1,300
16.1
8.2
Apr.
2,496
2,529
2,652
1,277
1,375
17.0
9.3
May
3,257
2,478
2,808
1,238
1,570
16.8
8.3
June
2,733
3,012
2,966
1,345
1,621
17.6
10.1
July
2,884
2,853
3,168
1,450
1,718
17.3
9.8
NOTE: Beginning in January 2003, data reflect revised population controls used in the household survey.
84
Monthly Labor Review • May 2009
2009
Aug.
3,242
2,874
3,447
1,568
1,878
17.6
9.3
2,864
3,083
3,662
1,621
2,041
18.7
10.3
3,108
3,055
4,109
1,834
2,275
19.8
10.6
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
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
8. Unemployed persons by reason for unemployment, monthly data seasonally adjusted
[Numbers in thousands]
Annual average
Reason for
unemployment
2007
1
Job losers …………………….…
On temporary layoff..............
Not on temporary layoff........
Job leavers..............................
Reentrants...............................
New entrants...........................
2008
2008
Mar.
Apr.
May
June
July
2009
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
3,515
976
2,539
793
2,142
627
4,789
1,176
3,614
896
2,472
766
4,161
1,064
3,097
792
2,126
695
4,043
1,103
2,939
860
2,145
625
4,319
1,121
3,197
881
2,522
832
4,465
1,106
3,358
847
2,562
761
4,595
1,041
3,554
875
2,668
818
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
49.7
13.8
35.9
11.2
30.3
8.9
53.7
13.2
40.5
10.0
27.7
8.6
53.5
13.7
39.8
10.2
27.3
8.9
52.7
14.4
38.3
11.2
28.0
8.1
50.5
13.1
37.4
10.3
29.5
9.7
51.7
12.8
38.9
9.8
29.7
8.8
51.3
11.6
39.7
9.8
29.8
9.1
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
2.7
.5
1.4
.5
2.6
.6
1.4
.4
2.8
.6
1.6
.5
2.9
.5
1.7
.5
3.0
.6
1.7
.5
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
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
Mar.
Apr.
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
5.1
11.4
15.8
18.7
14.2
9.4
4.0
4.2
3.4
5.0
11.0
15.4
20.2
13.4
9.0
4.0
4.2
3.1
5.5
13.1
18.9
21.5
17.6
10.3
4.2
4.5
3.3
5.6
12.9
18.8
23.2
15.9
10.2
4.4
4.6
3.4
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
5.2
12.5
17.8
22.4
15.2
10.3
4.0
4.2
3.3
5.2
12.1
17.0
22.5
14.5
10.0
4.0
4.3
3.0
5.7
14.1
20.8
23.7
19.8
11.1
4.3
4.5
3.5
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
5.0
10.1
13.8
15.3
13.1
8.3
4.1
4.2
4.8
9.8
13.9
18.1
12.2
7.7
3.9
4.1
3.0
3.7
3.4
2.8
1
May
June
July
2009
Aug.
Sept.
5.8
13.5
20.5
24.9
17.6
10.4
4.5
4.7
3.7
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
5.9
14.1
20.8
26.1
17.5
11.2
4.5
4.7
3.5
6.2
15.3
23.5
29.3
20.1
11.7
4.8
5.0
3.8
6.4
14.6
21.1
24.5
19.0
11.7
5.1
5.3
4.3
5.3
11.9
16.7
19.2
15.2
9.5
4.1
4.4
5.3
11.5
16.8
20.4
14.1
8.9
4.2
4.5
5.3
11.6
17.4
20.5
14.9
8.9
4.2
4.4
2.8
3.4
4.3
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
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
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
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
4.5
3.9
4.3
4.3
4.3
5.4
5.3
5.8
Data are not seasonally adjusted.
NOTE: Beginning in January 2003, data reflect revised population controls used in the household survey.
Monthly Labor Review • May 2009
85
Current Labor Statistics: Labor Force Data
10. Unemployment rates by State, seasonally adjusted
Feb.
2008
State
Jan.
Feb.
2009p
2009p
Feb.
2008
State
Jan.
Feb.
2009p
2009p
Alabama............................…………………
Alaska........................................................
Arizona............................……………………
Arkansas....................................................
California............................…………………
4.1
6.5
4.5
4.8
6.2
7.8
7.8
7.0
6.4
10.1
8.4
7.9
7.4
6.4
10.6
Missouri………………………………………
Montana.....................................................
Nebraska............................…………………
Nevada......................................................
New Hampshire............................…………
5.5
4.0
3.0
5.5
3.7
8.1
5.6
4.3
9.4
5.2
8.3
6.0
4.3
10.0
5.7
Colorado....................................................
Connecticut............................………………
Delaware...................................................
District of Columbia............................……
Florida........................................................
4.5
5.2
4.0
6.1
5.2
6.6
7.3
6.7
9.2
8.8
7.2
7.4
7.3
9.9
9.6
New Jersey................................................
New Mexico............................………………
New York...................................................
North Carolina............................……………
North Dakota.............................................
4.7
3.8
4.6
5.2
3.0
7.3
5.1
7.0
9.7
4.2
8.2
5.4
7.8
10.7
4.3
Georgia............................…………………
Hawaii........................................................
Idaho............................………………………
Illinois.........................................................
Indiana............................……………………
5.4
3.1
3.9
5.9
5.0
8.5
6.1
6.5
7.8
9.3
9.2
6.5
6.7
8.6
9.4
Ohio............................………………………
Oklahoma..................................................
Oregon............................……………………
Pennsylvania.............................................
Rhode Island............................……………
5.9
3.2
5.4
4.8
6.5
8.8
5.0
9.8
7.0
10.3
9.5
5.5
10.7
7.5
10.5
Iowa............................………………………
Kansas.......................................................
Kentucky............................…………………
Louisiana...................................................
Maine............................……………………
3.9
4.0
5.6
3.8
4.9
4.8
5.8
8.8
5.1
7.7
4.9
5.9
9.3
5.7
7.8
South Carolina............................…………
South Dakota.............................................
Tennessee............................………………
Texas.........................................................
Utah............................………………………
5.7
2.7
5.5
4.5
3.3
10.3
4.4
8.6
6.4
4.6
10.9
4.6
9.0
6.5
5.1
Maryland............................…………………
Massachusetts...........................................
Michigan............................…………………
Minnesota..................................................
Mississippi............................………………
3.7
4.6
7.4
5.0
5.9
6.2
7.4
11.6
7.5
8.7
6.8
7.7
12.0
8.0
9.1
Vermont............................…………………
Virginia.......................................................
Washington............................………………
West Virginia.............................................
Wisconsin............................………………
Wyoming....................................................
4.4
3.5
4.7
4.2
4.5
2.8
6.8
6.0
7.8
5.2
7.0
3.7
7.1
6.6
8.3
6.0
7.8
3.9
p
= preliminary
11. Employment of workers on nonfarm payrolls by State, seasonally adjusted
State
Feb.
2008
Jan.
Feb.
2009p
2009p
Alabama............................………… 2,166,519 2,146,896
355,101
358,893
Alaska.............................................
Arizona............................…………… 3,085,076 3,156,606
Arkansas........................................ 1,365,006 1,369,899
California............................………… 18,241,516 18,538,119
2,145,502
358,704
3,157,285
1,377,064
18,580,954
State
Feb.
2008
Jan.
Feb.
2009p
2009p
Missouri……………………………… 3,015,452
Montana.........................................
505,044
Nebraska............................…………
991,468
Nevada........................................... 1,349,138
New Hampshire............................…
739,534
3,010,154
503,529
990,459
1,403,121
739,717
3,019,674
501,843
992,445
1,403,105
742,425
Colorado......................................... 2,721,376
Connecticut............................……… 1,865,639
Delaware........................................
441,211
District of Columbia........................
332,077
Florida............................................ 9,163,690
2,738,452
1,889,549
439,918
332,151
9,267,985
2,731,554
1,890,346
440,145
331,791
9,263,707
New Jersey.....................................
New Mexico............................……
New York........................................
North Carolina............................…
North Dakota..................................
4,483,931
954,767
9,612,699
4,525,319
367,766
4,503,013
957,791
9,689,161
4,550,518
371,349
4,514,619
957,436
9,756,388
4,584,277
371,315
Georgia............................………… 4,833,087
Hawaii.............................................
649,807
Idaho............................……………
751,005
Illinois............................................. 6,738,121
Indiana............................…………… 3,226,342
4,814,641
648,894
752,620
6,601,591
3,249,440
4,811,586
650,254
752,227
6,603,239
3,241,553
Ohio............................………………
Oklahoma.......................................
Oregon............................……………
Pennsylvania..................................
Rhode Island............................……
5,964,848
1,732,653
1,942,131
6,349,244
568,420
5,959,911
1,760,691
1,989,651
6,446,871
562,709
5,993,089
1,757,714
1,997,891
6,459,235
566,039
Iowa............................………………
Kansas...........................................
Kentucky............................…………
Louisiana........................................
Maine............................……………
1,674,591
1,487,658
2,029,409
2,053,380
704,859
1,672,080
1,508,667
2,069,935
2,090,968
710,624
1,668,976
1,511,388
2,080,623
2,085,337
708,027
South Carolina............................… 2,126,910 2,186,244 2,189,322
South Dakota..................................
443,880
445,137
447,025
Tennessee............................……… 3,035,123 3,033,462 3,051,531
Texas.............................................. 11,588,581 11,816,124 11,839,609
Utah............................……………… 1,376,386 1,391,116 1,389,134
Maryland............................…………
Massachusetts...............................
Michigan............................…………
Minnesota.......................................
Mississippi............................………
2,990,060
3,417,581
4,972,864
2,920,482
1,307,396
2,978,371
3,426,505
4,862,172
2,941,072
1,322,792
2,969,663
3,427,365
4,857,714
2,951,001
1,326,532
Vermont............................…………
354,704
Virginia........................................... 4,093,737
Washington............................……… 3,447,185
West Virginia..................................
808,069
Wisconsin............................……… 3,084,478
Wyoming........................................
290,524
NOTE: Some data in this table may differ from data published elsewhere because of the continual updating of the database.
p
86
= preliminary
Monthly Labor Review • May 2009
357,112
4,146,570
3,524,564
798,534
3,102,241
293,013
358,111
4,160,683
3,554,065
794,137
3,122,806
292,605
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
Mar.
Apr.
May
June
July
2009
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.p
Mar.p
137,066 137,814 137,654 137,517 137,356 137,228 137,053 136,732 136,352 135,755 135,074 134,333 133,682 133,019
114,566 115,373 115,203 115,029 114,834 114,691 114,497 114,197 113,813 113,212 112,542 111,793 111,139 110,481
22,233
21,419
21,800
21,679
21,612
21,507
21,432
21,351
21,247
21,063
20,814
20,532
20,127
19,842
19,537
724
60.1
663.8
146.2
1
223.4
Mining, except oil and gas ……
77.2
Coal mining……………………
294.3
Support activities for mining……
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..........................
1,562.8
Fabricated metal products.........
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
756
57.8
697.7
156.2
223.6
77.9
317.9
7,401
1,712.6
993.6
4,694.5
13,643
9,853
8,637
6,146
479.8
479.4
450.9
1,557.5
1,193.8
756
58.6
697.8
155.1
222.9
78.1
319.8
7,337
1,693.8
980.5
4,662.3
13,586
9,795
8,587
6,099
477.3
477.2
449.7
1,546.0
1,193.1
763
57.3
705.5
158.8
226.3
79.2
320.4
7,293
1,676.9
982.1
4,633.6
13,556
9,770
8,567
6,077
468.3
473.0
447.9
1,544.8
1,192.2
770
56.0
713.8
160.7
226.9
79.6
326.2
7,232
1,660.6
972.2
4,598.7
13,505
9,723
8,533
6,040
462.9
469.7
446.6
1,534.8
1,190.8
777
55.8
721.3
162.7
227.6
79.5
331.0
7,201
1,655.5
970.9
4,574.6
13,454
9,672
8,502
6,006
458.4
466.4
444.8
1,528.4
1,191.1
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
772
54.7
717.3
167.9
226.1
84.6
323.3
6,599
1,509.7
920.5
4,168.8
12,471
8,800
7,753
5,348
389.4
424.5
395.5
1,398.5
1,100.6
754
51.7
702.2
167.6
224.8
84.6
309.8
6,473
1,476.3
910.1
4,086.2
12,310
8,654
7,628
5,233
389.2
415.2
387.0
1,370.8
1,073.6
products 1……………………… 1,272.5
Computer and peripheral
1,247.6
1,257.9
1,255.7
1,252.8
1,248.5
1,247.3
1,248.3
1,246.5
1,239.8
1,233.3
1,223.7
1,212.9
1,198.6
1,193.3
equipment..............................
Communications equipment…
186.2
128.1
182.8
129.0
183.8
128.3
184.0
129.1
183.6
129.1
182.1
130.2
182.5
129.1
182.6
129.1
182.8
129.2
182.4
128.6
181.8
129.5
180.0
129.1
180.3
129.6
176.6
129.4
175.1
130.0
Semiconductors and
electronic components..........
Electronic instruments……….
447.5
443.2
432.4
441.6
439.2
443.6
437.0
442.9
434.4
443.1
431.2
442.4
431.9
441.8
432.3
442.6
431.0
442.5
428.4
440.2
423.2
438.8
417.4
437.5
410.5
433.8
403.8
431.6
400.6
430.8
Electrical equipment and
appliances...............................
Transportation equipment.........
429.4
1,711.9
424.9
1,606.5
427.4
1,653.8
428.5
1,632.1
428.5
1,636.6
428.3
1,634.3
428.4
1,625.7
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
400.3
1,424.2
391.3
1,398.3
Furniture and related
products.....……………………… 531.1
641.7
Miscellaneous manufacturing
Nondurable goods.....................
5,071
3,725
Production workers................
Food manufacturing.................. 1,484.1
481.0
630.8
4,955
3,663
1,484.8
501.4
635.2
5,006
3,707
1,485.7
495.2
632.5
4,999
3,696
1,483.2
491.6
631.4
4,989
3,693
1,483.1
488.0
629.0
4,972
3,683
1,482.1
483.4
627.9
4,952
3,666
1,478.1
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
416.6
604.5
4,718
3,452
1,467.0
406.4
602.4
4,682
3,421
1,464.2
GOODS-PRODUCING………………
Natural resources and
mining…………..……….......……
Logging....................................
Mining..........................................
Oil and gas extraction……………
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
198.9
158.5
151.0
203.8
33.2
449.9
201.6
155.9
150.1
202.5
33.6
450.6
201.4
154.3
149.1
200.8
33.6
449.8
200.6
150.7
147.1
200.0
34.2
448.2
200.0
149.0
146.2
199.5
33.0
447.1
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
191.5
130.2
134.3
177.2
31.8
422.0
192.8
128.2
129.4
174.8
31.6
418.6
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
607.4
116.3
854.0
747.3
605.6
115.9
854.1
745.5
601.2
117.1
854.2
744.3
594.8
117.6
852.8
743.4
591.5
118.1
850.0
739.3
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
550.0
114.6
829.7
669.5
542.1
114.4
825.8
659.7
SERVICE-PROVIDING...................
115,366
115,646 116,014 115,975 115,905 115,849 115,796 115,702 115,485 115,289 114,941 114,542 114,206 113,840 113,482
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
93,573
93,524
93,417
93,327
93,259
93,146
92,950
92,750
92,398
92,010
91,666
91,297
90,944
26,385
5,963.7
3,060.7
2,053.0
26,629
6,012.5
3,099.8
2,063.0
26,562
5,995.9
3,087.2
2,060.9
26,503
5,989.3
3,078.2
2,063.7
26,467
5,983.1
3,071.7
2,061.5
26,425
5,966.9
3,062.5
2,053.2
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
25,614
5,778.9
2,928.3
2,009.2
25,502
5,747.7
2,901.9
2,006.0
Electronic markets and
agents and brokers……………
831.5
850.1
849.7
847.8
847.4
849.9
851.2
852.9
855.9
853.5
851.8
847.0
845.8
841.4
839.8
Retail trade................................. 15,520.0 15,356.3 15,506.0 15,457.6 15,419.9 15,404.4 15,380.2 15,334.5 15,278.2 15,216.8 15,126.0 15,037.9 14,991.5 14,940.7 14,892.9
Motor vehicles and parts
dealers 1………………………
Automobile dealers..................
1,908.3
1,242.2
1,844.5
1,186.0
1,890.9
1,227.6
1,885.1
1,220.9
1,877.4
1,214.6
1,866.2
1,204.7
1,851.4
1,191.5
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
1,716.4
1,078.8
1,700.3
1,066.9
Furniture and home
furnishings stores....................
574.6
542.8
550.4
549.5
547.6
546.5
545.8
542.3
538.4
532.4
522.6
514.2
508.3
500.0
497.7
Electronics and appliance
stores.......................................
549.4
549.6
552.9
554.5
555.0
552.9
553.0
551.0
547.1
545.1
541.5
538.6
535.5
536.4
526.2
See notes at end of table.
Monthly Labor Review • May 2009
87
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
Mar.
Apr.
May
June
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb. p
Mar.p
1,309.3
2,843.6
1,253.1
2,858.4
1,264.9
2,874.7
1,254.5
2,866.7
1,256.0
2,864.0
1,252.2
2,863.2
1,244.1
2,863.4
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
1,206.4
2,827.1
1,193.0
2,826.7
993.1
861.5
1,002.4
843.4
1,007.7
854.2
1,006.9
848.5
1,004.8
838.1
1,003.6
845.8
1,005.4
843.0
999.0
840.9
998.9
834.8
995.9
836.1
989.4
836.9
991.2
834.4
985.7
833.0
986.0
832.2
985.1
831.3
Clothing and clothing
accessories stores ………………… 1,500.0
1,484.2
1,498.2
1,495.0
1,490.9
1,487.2
1,483.6
1,483.3
1,478.5
1,471.5
1,462.2
1,448.5
1,445.0
1,443.6
1,437.4
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
653.8
3,060.7
1,583.5
854.5
443.1
646.2
3,052.9
1,576.4
855.0
442.8
649.2
3,043.2
1,564.0
851.8
441.9
646.9
3,052.0
1,561.8
849.4
438.5
642.2
3,062.3
1,563.2
848.3
437.7
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
613.8
3,043.4
1,533.7
815.7
419.7
611.4
3,057.2
1,533.4
808.3
418.3
Transportation and
warehousing................................. 4,540.9
Air transportation…………….……… 491.8
Rail transportation……...…………… 233.7
Water transportation………...………
65.5
Truck transportation………..……… 1,439.2
4,505.0
492.6
229.5
65.2
1,391.1
4,553.4
505.4
231.4
66.0
1,414.6
4,551.7
501.9
231.1
66.2
1,410.4
4,536.3
498.3
230.3
65.8
1,405.1
4,521.1
494.9
227.1
66.1
1,393.1
4,518.0
492.9
230.1
66.4
1,391.2
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
4,324.0
475.1
225.3
60.5
1,310.4
4,290.0
473.0
224.9
59.8
1,295.5
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
420.0
40.8
423.0
40.9
418.8
41.7
421.9
42.3
420.8
42.7
422.7
42.5
414.4
43.1
413.8
43.3
411.7
43.2
410.1
43.3
408.1
43.1
406.6
43.0
405.0
42.8
Scenic and sightseeing
transportation…….…………………
28.6
28.0
28.7
28.4
28.1
28.1
27.6
27.3
27.1
27.1
27.2
27.2
26.9
26.6
26.4
584.2
580.7
665.2
553.4
3,032
589.9
575.9
672.8
559.5
2,997
591.2
577.5
677.8
557.4
3,023
593.0
577.8
679.0
557.1
3,017
591.5
578.9
677.8
557.0
3,013
590.9
579.2
677.5
558.2
3,006
592.8
577.7
675.8
559.7
2,995
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
560.4
563.7
652.4
570.0
2,917
553.2
558.6
650.8
570.9
2,907
Publishing industries, except
Internet…………………...…………
901.2
882.6
893.3
893.2
890.4
886.8
882.9
879.4
876.6
872.6
863.6
857.8
846.3
834.8
827.2
Motion picture and sound
recording industries……...…………
Broadcasting, except Internet.
380.6
325.2
381.6
315.9
385.2
319.0
384.5
317.3
383.3
317.7
383.5
315.7
380.1
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
389.0
302.3
395.0
299.7
Internet publishing and
broadcasting………………...………
Telecommunications………….…… 1,030.6
1,021.4
1,028.0
1,025.5
1,025.3
1,025.5
1,022.8
1,023.1
1,021.6
1,014.5
1,010.2
1,004.0
1,001.6
1,000.3
996.4
261.6
133.6
8,146
6,015.2
263.4
134.2
8,204
6,055.8
263.2
132.9
8,190
6,050.8
263.3
132.5
8,179
6,039.7
261.8
132.2
8,162
6,026.1
260.5
133.0
8,154
6,019.9
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
255.4
134.9
7,910
5,863.3
255.2
133.7
7,867
5,838.0
21.6
22.2
22.4
22.7
22.5
22.3
22.3
22.3
22.3
22.1
21.5
21.3
21.0
21.0
20.8
related activities1………………… 2,866.3
Depository credit
2,735.8
2,763.3
2,756.6
2,746.7
2,738.5
2,730.9
2,724.4
2,722.4
2,706.4
2,692.8
2,680.8
2,665.3
2,652.9
2,637.7
intermediation1…………………… 1,823.5
Commercial banking..…………… 1,351.4
1,819.5
1,359.9
1,824.9
1,362.0
1,827.9
1,363.4
1,824.8
1,363.0
1,822.2
1,362.1
1,820.0
1,361.1
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
1,792.7
1,342.4
1,785.2
1,336.0
848.6
858.1
867.5
867.4
865.8
864.4
860.4
861.4
851.4
847.8
842.1
839.9
826.5
819.7
812.4
Insurance carriers and
related activities………………...… 2,306.8
2,308.8
2,313.3
2,313.4
2,314.7
2,310.6
2,316.1
2,312.0
2,307.6
2,311.0
2,300.9
2,292.0
2,287.4
2,281.1
2,279.0
88.7
90.3
89.3
90.7
90.0
90.3
90.2
90.5
90.6
91.4
91.4
90.0
90.2
88.6
88.1
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
2,148.5
1,489.4
630.6
2,139.6
1,486.9
624.3
2,138.9
1,486.2
624.8
2,135.9
1,485.5
622.5
2,134.4
1,481.5
624.4
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
2,047.0
1,435.1
583.6
2,029.1
1,423.4
577.1
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
28.5
28.4
27.9
27.9
28.5
28.2
28.4
28.1
28.3
28.3
28.4
28.3
28.6
Professional and business
services…………………………...…
Professional and technical
17,942
17,778
17,954
17,950
17,887
17,824
17,788
17,727
17,675
17,612
17,488
17,356
17,205
17,027
16,894
services1……………………………
Legal services……………..………
7,659.5
1,175.4
7,829.7
1,163.7
7,818.8
1,168.8
7,833.7
1,166.6
7,821.5
1,165.2
7,828.9
1,164.5
7,833.6
1,163.0
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
7,728.8
1,149.2
7,697.5
1,146.5
Accounting and bookkeeping
services……………………………
935.9
950.1
948.8
954.1
944.9
948.3
947.5
947.9
945.6
946.4
941.0
933.7
927.5
926.3
927.9
Architectural and engineering
services…………………………… 1,432.2
1,444.8
1,450.9
1,451.7
1,449.3
1,450.5
1,449.2
1,447.2
1,441.4
1,437.1
1,428.6
1,419.4
1,411.1
1,392.5
1,376.2
.
See notes at end of table
88
2008
2007
Monthly Labor Review • May 2009
12. Continued—Employment of workers on nonfarm payrolls by industry, monthly data seasonally adjusted
[In thousands]
Industry
Annual average
2008
2009
2007
2008
Mar.
Apr.
May
June
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.p
Mar.p
1,372.1
1,450.3
1,432.4
1,441.7
1,445.8
1,446.2
1,456.2
1,460.6
1,461.6
1,466.1
1,467.9
1,466.8
1,462.4
1,463.9
1,460.0
952.7
1,008.9
997.1
999.2
1,002.3
1,010.1
1,011.3
1,011.6
1,021.0
1,022.9
1,024.9
1,020.5
1,025.7
1,020.6
1,014.5
1,866.4
1,894.6
1,906.7
1,903.8
1,902.1
1,900.6
1,895.3
1,895.2
1,887.1
1,882.8
1,882.0
1,872.1
1,871.7
1,865.3
1,859.0
Administrative and waste
services…………………………… 8,416.3
Administrative and support
8,053.7
8,228.2
8,212.0
8,163.3
8,094.9
8,058.6
7,998.6
7,953.2
7,884.8
7,778.3
7,686.3
7,567.5
7,432.9
7,337.3
7,693.5
3,144.4
2,342.6
823.2
7,870.7
3,304.7
2,486.8
831.1
7,853.6
3,285.6
2,464.0
828.4
7,804.4
3,242.7
2,426.7
822.6
7,736.4
3,184.0
2,383.5
818.1
7,699.3
3,146.9
2,349.1
817.4
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
7,070.9
2,628.4
1,888.5
806.8
6,976.6
2,540.0
1,816.8
804.4
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
1,853.7
1,853.8
1,853.5
1,851.4
1,848.6
1,847.0
1,843.3
1,837.4
1,829.4
1,818.1
1,812.5
1,798.7
1,791.1
Waste management and
remediation services………….
355.0
360.2
357.5
358.4
358.9
358.5
359.3
361.6
361.3
362.8
364.1
361.9
364.4
362.0
360.7
18,322
2,941.4
18,855
3,036.6
18,698
3,006.5
18,752
3,017.4
18,798
3,025.4
18,843
3,049.2
18,888
3,062.4
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
19,141
3,087.1
19,149
3,080.3
Educational and health
services………………...……….
Educational services…….………
Health care and social
assistance……….……………… 15,380.2 15,818.5 15,691.1 15,734.1 15,772.3 15,794.1 15,825.9 15,865.9 15,901.9 15,934.1 15,977.8 16,017.0 16,030.3 16,053.5 16,068.3
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
5,599.3
2,243.7
527.5
943.3
4,599.1
5,622.6
2,251.8
530.4
948.7
4,610.4
5,634.9
2,256.8
531.5
951.8
4,627.2
5,652.0
2,264.6
531.2
955.3
4,634.0
5,676.3
2,272.7
535.4
961.1
4,646.8
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
5,768.2
2,304.9
538.5
989.5
4,710.6
5,775.9
2,308.1
539.2
992.2
4,709.9
Nursing and residential
care facilities 1…………………
Nursing care facilities…………
Social assistance 1………………
Child day care services………
Leisure and hospitality………..
2,958.3
1,602.6
2,433.4
850.4
13,427
3,008.1
1,613.7
2,508.7
859.2
13,459
3,001.3
1,614.7
2,491.4
861.7
13,528
3,006.1
1,615.0
2,495.0
859.9
13,512
3,006.2
1,615.1
2,504.0
863.3
13,495
3,005.7
1,613.0
2,502.4
853.8
13,490
3,006.3
1,612.3
2,496.5
844.6
13,473
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
3,034.1
1,617.7
2,540.6
861.4
13,240
3,040.6
1,620.7
2,541.9
858.8
13,200
Arts, entertainment,
and recreation……….…….……
1,969.2
1,969.3
1,996.1
1,984.9
1,978.3
1,975.1
1,966.6
1,964.7
1,955.3
1,952.0
1,944.0
1,947.1
1,943.8
1,943.7
1,935.1
Performing arts and
spectator sports…………………
405.0
406.3
409.3
409.5
409.4
409.7
406.9
406.2
402.9
402.5
398.8
401.4
405.7
403.7
403.1
Museums, historical sites,
zoos, and parks…………………
130.3
131.8
133.2
132.9
133.9
132.2
132.1
132.1
130.6
129.6
130.6
130.8
130.3
130.6
129.5
1,433.9
1,431.2
1,453.6
1,442.5
1,435.0
1,433.2
1,427.6
1,426.4
1,421.8
1,419.9
1,414.6
1,414.9
1,407.8
1,409.4
1,402.5
Amusements, gambling, and
recreation………………………
Accommodations and
food services…………………… 11,457.4 11,489.3 11,532.0 11,527.5 11,516.7 11,515.3 11,506.3 11,489.3 11,472.4 11,442.7 11,399.6 11,356.5 11,323.7 11,296.2 11,264.7
Accommodations………………. 1,866.9
1,857.3 1,883.9 1,881.1 1,872.1 1,865.0 1,854.6 1,843.6 1,841.3 1,827.9 1,812.1 1,794.3 1,768.4 1,750.9 1,728.3
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
9,648.1
5,537
1,242.2
1,324.2
9,646.4
5,541
1,242.2
1,324.9
9,644.6
5,542
1,239.6
1,325.3
9,650.3
5,535
1,233.6
1,327.4
9,651.7
5,536
1,230.6
1,328.9
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
9,545.3
5,448
1,176.7
1,313.3
9,536.4
5,425
1,166.4
1,304.7
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
2,970.2
2,973.5
2,976.9
2,973.8
2,976.6
2,977.6
2,977.1
2,988.3
2,980.7
2,965.7
2,963.1
2,958.1
2,953.8
22,218
2,734
22,500
2,764
22,441
2,751
22,451
2,758
22,488
2,763
22,522
2,765
22,537
2,776
22,556
2,768
22,535
2,771
22,539
2,775
22,543
2,783
22,532
2,778
22,540
2,793
22,543
2,795
22,538
2,802
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
1,989.6
761.5
5,152
2,334.7
2,817.3
14,538
8,076.4
6,461.5
1,996.4
761.3
5,159
2,340.0
2,819.4
14,534
8,066.2
6,467.6
2,007.7
755.7
5,167
2,348.0
2,818.5
14,558
8,085.2
6,472.9
2,014.6
750.5
5,175
2,355.4
2,819.4
14,582
8,101.3
6,481.1
2,020.2
755.8
5,184
2,365.1
2,819.1
14,577
8,088.3
6,488.2
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
2,070.7
724.0
5,187
2,378.8
2,808.5
14,561
8,081.1
6,479.5
2,079.1
722.8
5,184
2,379.2
2,804.6
14,552
8,080.3
6,471.8
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 • May 2009
89
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
Annual average
Industry
2007
2008
2008
Mar.
Apr.
June
July
2009
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.p
Mar.p
TOTAL PRIVATE…………………………
33.9
33.6
33.8
33.8
33.7
33.6
33.6
33.7
33.6
33.5
33.4
33.3
33.3
33.3
33.2
GOODS-PRODUCING………………………
40.6
40.2
40.6
40.4
40.2
40.3
40.3
40.2
39.9
39.8
39.5
39.4
39.3
39.2
38.9
Natural resources and mining……………
45.9
45.1
46.2
45.0
44.6
44.9
44.8
45.3
44.5
44.7
45.3
44.3
44.2
44.0
43.2
Construction…………………………………
39.0
38.5
38.9
38.9
38.5
38.7
38.7
38.6
38.3
38.3
37.7
38.0
37.9
38.1
37.8
Manufacturing…………………….............
Overtime hours..................................
41.2
4.2
40.8
3.7
41.2
4.0
41.0
4.0
40.9
3.9
40.9
3.8
41.0
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
39.3
2.7
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
41.5
4.1
38.7
43.2
43.0
41.8
42.8
41.0
41.3
42.4
38.7
39.2
41.4
4.0
38.6
42.3
42.6
41.6
42.5
41.1
41.0
42.5
38.7
39.3
41.2
3.9
39.0
42.3
42.4
41.5
42.2
41.1
41.1
41.9
38.8
39.2
41.2
3.8
39.1
42.0
42.5
41.2
42.1
41.2
40.9
42.1
38.7
39.0
41.2
3.7
38.8
42.6
42.2
41.2
42.1
41.1
40.8
42.6
38.3
39.1
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
39.5
2.5
37.0
40.0
39.9
39.4
40.5
40.5
38.8
40.1
37.5
38.2
39.3
2.5
36.8
39.8
40.1
38.9
40.2
39.9
38.2
40.1
37.9
38.2
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
40.7
3.9
40.8
40.1
38.8
39.3
36.7
38.6
43.6
40.5
3.9
40.8
39.4
38.4
38.3
36.6
38.6
43.3
40.5
3.8
40.8
39.5
38.9
38.7
36.0
38.8
42.6
40.4
3.8
40.6
38.8
38.8
38.9
36.4
38.4
42.7
40.6
3.7
40.6
38.7
39.2
39.1
37.0
38.2
42.6
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
39.4
3.0
39.9
36.8
36.5
37.0
35.6
33.1
41.5
39.4
3.0
40.0
35.7
36.6
37.0
36.1
33.3
41.1
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
38.6
43.7
41.9
41.2
38.5
43.2
41.3
41.0
38.6
44.1
41.2
40.9
38.1
44.6
41.6
41.0
38.0
45.5
41.9
41.3
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
37.5
43.8
41.0
39.5
37.5
43.9
40.9
39.4
PRIVATE SERVICEPROVIDING………………………………
32.4
32.3
32.4
32.4
32.4
32.3
32.3
32.4
32.3
32.3
32.2
32.2
32.2
32.1
32.1
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
33.3
38.4
30.2
36.6
43.2
36.5
35.8
33.3
38.3
30.2
36.6
42.6
36.6
35.9
33.2
38.3
30.1
36.4
42.5
36.6
35.9
33.2
38.3
30.0
36.4
43.0
36.7
35.8
33.2
38.4
30.0
36.4
42.4
36.7
35.7
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
43.1
36.9
36.2
32.8
37.7
29.7
36.0
42.2
36.8
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
34.8
32.7
25.3
30.9
34.8
32.6
25.4
30.8
34.9
32.7
25.3
30.8
34.8
32.5
25.3
30.7
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
30.6
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.
90
May
Monthly Labor Review • May 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
Annual average
2008
Industry
2009
2007
2008
Mar.
Apr.
May
June
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.p
Mar.p
TOTAL PRIVATE
Current dollars………………………
Constant (1982) dollars……………
$17.43
8.33
$18.08
8.30
$17.90
8.28
$17.94
8.29
$17.99
8.27
$18.04
8.20
$18.10
8.16
$18.18
8.20
$18.21
8.21
$18.28
8.33
$18.34
8.54
$18.40
8.65
$18.43
8.64
$18.47
8.62
$18.50
8.64
GOODS-PRODUCING...............................
18.67
19.33
19.17
19.16
19.20
19.27
19.36
19.43
19.48
19.56
19.63
19.69
19.72
19.78
19.84
20.97
20.95
17.26
16.43
18.20
15.67
22.50
21.87
17.74
16.97
18.70
16.15
22.28
21.58
17.64
16.82
18.58
16.05
21.77
21.62
17.64
16.82
18.61
16.01
21.79
21.72
17.68
16.88
18.63
16.08
22.04
21.77
17.73
16.94
18.70
16.11
22.54
21.85
17.80
17.03
18.78
16.16
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
23.12
22.44
18.06
17.46
19.07
16.50
23.30
22.61
18.08
17.48
19.16
16.44
PRIVATE SERVICEPROVIDING..........………………..............
17.11
17.77
17.58
17.63
17.69
17.74
17.79
17.87
17.90
17.97
18.03
18.10
18.14
18.17
18.20
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
16.07
20.04
12.83
18.25
28.79
24.58
20.12
16.08
20.05
12.84
18.31
28.54
24.56
20.17
16.13
20.07
12.87
18.39
28.81
24.71
20.23
16.16
20.11
12.87
18.41
29.12
24.78
20.24
16.17
20.15
12.88
18.42
28.67
24.87
20.26
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
20.49
12.96
18.72
29.67
25.07
20.56
16.38
20.56
12.98
18.69
29.25
25.19
20.64
Professional and business
services.................................................
20.15
21.19
20.78
20.90
20.96
21.08
21.19
21.38
21.47
21.63
21.78
21.97
22.04
22.20
22.33
Education and health
services.................................................
Leisure and hospitality..........................
Other services.........................................
18.11
10.41
15.42
18.88
10.84
16.08
18.69
10.75
15.94
18.74
10.81
16.00
18.80
10.83
16.04
18.84
10.85
16.09
18.92
10.87
16.13
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
19.23
10.98
16.25
19.21
10.98
16.24
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 • May 2009
91
Current Labor Statistics: Labor Force Data
15. Average hourly earnings of production or nonsupervisory workers1 on private nonfarm payrolls, by industry
Annual average
2008
Industry
2007
TOTAL PRIVATE……………………………… $17.43
Seasonally adjusted…………………….
–
2008
Mar.
Apr.
May
June
July
Aug.
2009
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.p Mar.p
$18.08 $17.97 $17.95 $17.94 $18.00 $18.02 $18.10 $18.25 $18.27 $18.40 $18.40 $18.49 $18.57 $18.56
– 17.90 17.94 17.99 18.04 18.10 18.18 18.21 18.28 18.34 18.40 18.43 18.47 18.50
GOODS-PRODUCING......................................
18.67
19.33
19.06
19.09
19.15
19.26
19.39
19.53
19.63
19.61
19.65
19.75
19.64
19.64
19.72
Natural resources and mining……………..
20.97
22.50
22.29
21.78
21.52
21.75
22.45
23.06
23.19
22.98
23.31
23.53
23.41
23.20
23.28
Construction.…………..................................
20.95
21.87
21.44
21.49
21.61
21.69
21.90
22.16
22.34
22.28
22.32
22.52
22.32
22.26
22.48
Manufacturing…………………………………… 17.26
17.74
17.62
17.64
17.65
17.73
17.73
17.75
17.84
17.86
17.94
18.06
18.03
18.07
18.07
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
18.56
13.92
16.79
20.23
16.86
17.87
20.76
15.64
23.52
14.42
15.08
18.59
14.00
17.12
20.21
16.82
17.91
20.86
15.74
23.59
14.45
14.96
18.60
14.11
16.89
20.24
16.85
18.01
20.95
15.66
23.59
14.48
14.97
18.70
14.16
16.97
20.26
16.93
17.90
21.02
15.72
23.86
14.58
15.15
18.66
14.25
16.93
20.43
16.94
17.96
21.11
15.85
23.75
14.52
15.35
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
19.08
14.76
17.05
19.68
17.29
18.21
21.37
15.94
24.68
14.86
15.97
19.16
14.70
17.23
19.62
17.31
18.32
21.60
15.99
24.79
14.96
15.97
Nondurable goods………………………......
Food manufacturing ...........................……
Beverages and tobacco products .............
15.67
13.55
18.54
16.15
14.00
19.35
16.01
13.85
19.73
16.03
13.88
19.41
16.05
13.91
19.19
16.08
13.97
18.74
16.20
14.03
19.02
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
16.49
14.29
20.33
16.39
14.25
20.37
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
13.45
11.77
11.35
12.81
18.70
16.64
27.06
19.31
15.72
13.45
11.77
11.51
12.63
18.64
16.63
26.96
19.35
15.80
13.50
11.86
11.43
12.88
18.79
16.66
26.85
19.33
15.74
13.58
11.80
11.35
12.88
18.93
16.77
26.99
19.29
15.72
13.77
11.80
11.35
12.85
19.11
16.81
27.54
19.41
15.87
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
13.71
11.53
11.44
14.31
18.99
16.85
29.57
19.92
16.23
13.77
11.33
11.27
14.25
18.86
16.76
29.66
19.76
16.17
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
17.70
17.67
17.64
17.68
17.68
17.73
17.90
17.94
18.10
18.09
18.23
18.33
18.31
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
16.14
20.08
12.88
18.20
28.90
16.13
20.01
12.89
18.30
28.70
16.12
19.93
12.89
18.35
28.84
16.17
20.05
12.90
18.46
29.02
16.18
20.12
12.92
18.54
28.49
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
20.64
12.98
18.77
29.68
16.43
20.63
13.02
18.62
29.38
Information………………………………….....
23.96
24.77
24.62
24.56
24.65
24.78
24.75
24.87
25.03
25.06
25.03
24.86
25.03
25.11
25.26
Financial activities……..………....................
19.64
20.27
20.17
20.21
20.19
20.26
20.19
20.29
20.42
20.41
20.54
20.50
20.48
20.67
20.69
20.15
21.19
21.00
20.91
20.88
21.09
21.06
21.12
21.31
21.45
21.97
22.01
22.16
22.52
22.56
Professional and business
services…………………………………………
Education and health
services………………………………………… 18.11
18.88
18.74
18.75
18.76
18.79
18.96
18.95
19.08
19.04
19.10
19.23
19.26
19.25
19.22
Leisure and hospitality ………………………
10.41
10.84
10.77
10.81
10.83
10.78
10.73
10.79
10.89
10.93
10.93
11.05
11.03
11.07
10.99
Other services…………………......................
15.42
16.08
16.11
16.09
16.11
16.10
16.06
16.10
16.22
16.17
16.24
16.27
16.34
16.33
16.37
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.
92
Monthly Labor Review • May 2009
16. Average weekly earnings of production or nonsupervisory workers1 on private nonfarm payrolls, by industry
Industry
Annual average
2007
2008
2009
2008
Mar.
Apr.
May
June
July
Aug.
$607.27 $613.59
608.16
612.67
Oct.
Nov.
Dec.
Jan.
Feb.p
Mar.p
$613.20
611.86
$613.87
612.38
$620.08
612.56
$610.88
612.72
$608.32
613.72
$616.52
615.05
$616.19
614.20
791.09
788.32
782.07
778.15
762.03
Sept.
TOTAL PRIVATE………………… $590.04
Seasonally adjusted..........
–
$607.99
–
$607.39
605.02
$603.12
606.37
$602.78
606.26
$613.80
606.14
GOODS-PRODUCING………………
757.34
776.60
770.02
767.42
769.83
783.88
758.10
763.16
Natural resources
and mining………………………..
962.64
1,013.78 1,018.65
991.73
781.42
794.87
969.21
951.18
985.28 1,005.76 1,051.54 1,041.23 1,038.70 1,072.26 1,040.03 1,020.68 1,006.88
816.66
842.36
825.44
825.22
834.15
854.59
858.48
875.32
869.03
866.69
845.93
840.00
828.07
823.62
838.50
Manufacturing……………………… 711.56
724.23
724.18
723.24
721.89
730.48
719.84
727.75
729.66
726.90
726.57
727.82
712.19
708.34
708.34
754.77
539.34
716.78
843.26
687.20
754.19
767.56
547.81
711.30
850.84
701.47
759.92
768.38
533.14
715.25
869.89
703.06
764.84
767.77
540.40
722.46
854.88
699.71
761.18
766.32
554.52
717.83
854.13
697.59
758.22
776.05
566.40
724.62
871.18
699.21
755.38
761.33
560.03
726.30
860.10
692.85
750.73
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
747.94
531.36
658.13
779.33
677.77
737.51
751.07
532.14
675.42
786.76
671.63
734.63
808.80
861.43
851.16
853.17
861.05
872.33
861.29
869.61
874.68
876.08
891.13
883.33
866.98
861.21
861.84
656.46
986.79
645.60
999.94
644.37
643.77
999.60 1,002.58
638.93
647.66
988.42 1,016.44
640.34
650.35
978.50 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
613.69
989.67
607.62
994.08
560.84
554.20
555.17
553.44
557.48
571.54
557.57
566.09
549.61
542.72
546.49
563.98
559.13
548.33
565.49
manufacturing..........................
569.99
591.73
594.15
586.43
583.83
595.40
594.05
608.60
595.56
593.27
593.67
600.60
599.78
605.26
611.65
Nondurable goods.......................
639.99
551.32
652.20
566.91
648.41
558.16
647.61
560.75
646.82
566.14
652.85
568.58
652.86
568.22
654.08
572.02
663.41
581.57
659.33
575.28
658.91
572.47
657.20
573.25
650.49
569.30
644.76
561.60
642.49
564.30
755.22
524.40
467.77
411.39
459.50
795.58
750.18
524.93
453.12
415.17
486.49
809.21
787.23
521.86
463.74
418.82
499.59
809.71
770.58
515.14
449.61
423.57
491.31
805.25
765.68
522.45
454.24
412.62
502.32
791.06
738.36
529.62
468.46
415.41
501.03
806.42
741.78
535.65
462.56
416.55
485.73
808.35
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
740.01
493.56
425.46
403.83
465.08
782.39
721.10
502.61
420.34
409.10
475.95
767.60
632.02
642.50
643.97
638.59
638.08
633.91
630.38
644.59
655.72
659.21
652.48
654.89
627.95
628.51
630.18
CONSTRUCTION
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
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 1,158.17 1,156.58 1,181.40 1,219.95 1,266.84 1,259.90 1,302.33 1,322.61 1,275.43 1,256.38 1,307.94 1,286.30 1,266.48
808.80
809.09
799.16
790.60
808.25
809.40
810.50
820.46
814.34
822.43
814.44
811.51
816.72
806.21
Plastics and rubber
products…………………………
PRIVATE SERVICEPROVIDING…………....................
Trade, transportation,
and utilities………………………
Wholesale trade......…………......
Retail trade…………………………
635.63
649.04
646.09
647.80
645.34
650.81
647.50
650.26
655.13
652.42
658.10
657.72
647.98
637.84
633.86
554.89
574.31
575.25
568.97
569.77
579.90
572.83
576.23
578.17
577.67
588.25
578.88
579.71
592.06
589.58
526.07
748.94
385.11
535.79
769.91
386.39
537.46
775.09
386.40
533.90
764.38
385.41
533.57
761.33
386.70
544.93
779.95
393.45
538.79
770.60
391.48
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
786.38
384.21
538.90
779.81
385.39
Transportation and
warehousing……………………… 654.95
Utilities……………………………… 1,182.65
670.33
667.94
662.46
664.27
681.17
674.86
679.68
676.35
671.51
680.32
679.63
663.14
664.46
672.18
1,231.19 1,242.70 1,225.49 1,222.82 1,250.76 1,205.13 1,205.74 1,244.85 1,238.30 1,236.59 1,256.11 1,243.98 1,282.18 1,233.96
874.65
908.44
903.55
891.53
892.33
919.34
910.80
917.70
926.11
924.71
936.12
917.33
921.10
931.58
932.09
Financial activities………………… 705.13
726.37
730.15
721.50
718.76
737.46
718.76
726.38
728.99
728.64
753.82
731.85
735.23
760.66
755.19
Professional and
business services………………
Information…………………………
700.82
738.25
737.10
727.67
726.62
748.70
730.78
739.20
739.46
750.75
775.54
761.55
762.30
785.95
787.34
Education and………………………
health services…………………… 590.09
614.30
612.80
607.50
609.70
614.43
618.10
617.77
620.10
616.90
624.57
621.13
622.10
625.63
622.73
Leisure and hospitality…………… 265.52
273.27
272.48
272.41
274.00
280.28
276.83
278.38
272.25
273.25
273.25
270.73
264.72
276.75
272.55
Other services……………………… 477.06
494.99
497.80
493.96
494.58
500.71
496.25
500.71
497.95
496.42
501.82
496.24
498.37
501.33
500.92
1 Data relate to production workers in natural resources and mining and manufacturing,
NOTE: See "Notes on the data" for a description of the most recent benchmark revision.
construction workers in construction, and nonsupervisory workers in the service-
Dash indicates data not available.
providing industries.
p = preliminary.
Monthly Labor Review • May 2009
93
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
21.4
22.0
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
15.3
16.4
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
18.6
15.7
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
22.5
20.1
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
11.4
15.7
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
3.0
6.0
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
6.0
3.6
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
7.2
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.
94
Monthly Labor Review • May 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
Percent
2008
Sept.
Total2………………………………………………
Oct.
2009
Nov.
Dec.
Jan.
Feb.
2008
p
Sept.
Mar.
Oct.
2009
Nov.
Dec.
Jan.
Mar.p
Feb.
3,346
3,390
3,311
3,224
2,920
2,973
2,717
2.4
2.4
2.4
2.3
2.1
2.2
2.0
Total private 2…………………………………
2,913
2,964
2,928
2,861
2,461
2,606
2,361
2.5
2.5
2.5
2.5
2.2
2.3
2.1
Construction………………………………
152
79
76
66
55
58
48
2.1
1.1
1.1
0.9
0.8
0.9
0.7
Manufacturing……………………………
236
230
203
188
115
141
123
1.7
1.7
1.5
1.4
0.9
1.1
1.0
Trade, transportation, and utilities………
525
564
624
495
488
488
414
2.0
2.1
2.3
1.9
1.9
1.9
1.6
Professional and business services……
608
603
505
562
501
482
431
3.3
3.3
2.8
3.1
2.8
2.8
2.5
Education and health services…………
624
646
697
685
636
589
558
3.2
3.3
3.5
3.5
3.2
3.0
2.8
Industry
Leisure and hospitality……………………
Government…………………………………
427
417
302
315
272
332
296
3.1
3.0
2.2
2.3
2.0
2.4
2.2
431
427
378
345
417
367
352
1.9
1.9
1.6
1.5
1.8
1.6
1.5
Region 3
Northeast…………………………………
644
636
582
633
560
607
587
2.5
2.4
2.2
2.4
2.2
2.4
2.3
South………………………………………
1,269
1,314
1,267
1,245
1,109
1,109
977
2.5
2.6
2.5
2.5
2.2
2.2
2.0
Midwest……………………………………
674
698
644
607
587
563
510
2.1
2.2
2.0
1.9
1.9
1.8
1.7
West………………………………………
785
734
767
689
655
638
570
2.5
2.3
2.5
2.2
2.1
2.1
1.9
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.
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
Levels1 (in thousands)
Industry and region
2008
Sept.
Total2………………………………………………
Oct.
Percent
2009
Nov.
Dec.
Jan.
Feb.
2008
p
Mar.
Sept.
Oct.
2009
Nov.
Dec.
Jan.
Feb.
Mar.p
4,505
4,486
4,226
4,508
4,460
4,339
4,172
3.3
3.3
3.1
3.3
3.3
3.2
3.1
Total private 2…………………………………
4,263
4,160
3,928
4,214
4,141
4,042
3,877
3.7
3.7
3.5
3.7
3.7
3.6
3.5
Construction………………………………
365
380
340
366
381
370
376
5.1
5.4
4.9
5.3
5.7
5.6
5.8
Manufacturing……………………………
305
290
257
252
237
257
245
2.3
2.2
2.0
2.0
1.9
2.1
2.0
Trade, transportation, and utilities………
959
933
852
891
949
814
882
3.7
3.6
3.3
3.4
3.7
3.2
3.5
Professional and business services……
787
788
783
786
762
730
688
4.5
4.5
4.5
4.5
4.4
4.3
4.1
Education and health services…………
506
544
528
528
539
527
489
2.7
2.9
2.8
2.8
2.8
2.8
2.6
Leisure and hospitality……………………
814
769
706
711
743
704
703
6.1
5.7
5.3
5.3
5.6
5.3
5.3
278
318
281
271
306
275
269
1.2
1.4
1.2
1.2
1.4
1.2
1.2
Industry
Government…………………………………
Region 3
Northeast…………………………………
742
759
661
726
753
837
719
2.9
3.0
2.6
2.9
3.0
3.3
2.9
South………………………………………
1,643
1,652
1,572
1,659
1,663
1,566
1,502
3.3
3.4
3.2
3.4
3.4
3.2
3.1
Midwest……………………………………
1,038
1,051
934
1,009
1,003
904
946
3.3
3.4
3.0
3.3
3.3
3.0
3.1
West………………………………………
1,088
1,043
1,043
1,053
1,002
960
952
3.6
3.4
3.4
3.5
3.3
3.2
3.2
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 • May 2009
95
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
Percent
2008
Sept.
Total2………………………………………………
Oct.
2009
Nov.
Dec.
Jan.
Feb.
2008
p
Mar.
Sept.
Oct.
2009
Nov.
Dec.
Jan.
Mar.p
Feb.
4,852
4,910
4,863
4,958
4,949
4,833
4,737
3.5
3.6
3.6
3.7
3.7
3.6
3.6
Total private 2…………………………………
4,553
4,607
4,571
4,673
4,686
4,555
4,465
4.0
4.0
4.0
4.1
4.2
4.1
4.0
Construction………………………………
412
440
472
452
524
463
488
5.8
6.2
6.8
6.6
7.8
7.0
7.5
Manufacturing……………………………
371
404
384
419
476
424
401
2.8
3.1
2.9
3.2
3.8
3.4
3.3
Trade, transportation, and utilities………
1,046
1,034
1,030
1,041
1,049
920
984
4.0
4.0
4.0
4.0
4.1
3.6
3.9
Professional and business services……
809
906
909
898
866
951
776
4.6
5.1
5.2
5.2
5.0
5.6
4.6
Education and health services…………
488
507
466
498
494
498
479
2.6
2.7
2.4
2.6
2.6
2.6
2.5
Leisure and hospitality……………………
830
794
773
755
763
731
758
6.2
5.9
5.8
5.7
5.7
5.5
5.7
294
294
282
278
277
271
262
1.3
1.3
1.3
1.2
1.2
1.2
1.2
Industry
Government…………………………………
Region 3
Northeast…………………………………
734
743
767
799
813
783
848
2.9
2.9
3.0
3.2
3.2
3.1
3.4
South………………………………………
1,767
1,782
1,841
1,815
1,898
1,742
1,762
3.6
3.6
3.8
3.7
3.9
3.6
3.7
Midwest……………………………………
1,116
1,168
1,105
1,088
1,120
1,121
1,082
3.6
3.8
3.6
3.5
3.7
3.7
3.6
West………………………………………
1,184
1,209
1,205
1,227
1,180
1,188
1,065
3.9
4.0
4.0
4.0
3.9
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
2008
Sept.
Total2………………………………………………
Oct.
Percent
2009
Nov.
Dec.
Jan.
Feb.
2008
p
Mar.
Sept.
Oct.
2009
Nov.
Dec.
Jan.
Feb.
Mar.p
2,454
2,436
2,201
2,114
2,063
1,911
1,831
1.8
1.8
1.6
1.6
1.5
1.4
1.4
2
Total private …………………………………
2,319
2,305
2,076
1,984
1,945
1,831
1,766
2.0
2.0
1.8
1.8
1.7
1.6
1.6
Construction………………………………
128
107
109
92
85
87
85
1.8
1.5
1.6
1.3
1.3
1.3
1.3
Manufacturing……………………………
147
143
122
87
105
105
78
1.1
1.1
.9
.7
.8
.8
.6
Trade, transportation, and utilities………
580
548
489
518
469
372
450
2.2
2.1
1.9
2.0
1.8
1.5
1.8
Professional and business services……
368
477
349
297
326
310
274
2.1
2.7
2.0
1.7
1.9
1.8
1.6
Education and health services…………
290
294
251
256
248
258
244
1.5
1.5
1.3
1.3
1.3
1.3
1.3
Industry
514
516
469
461
443
431
430
3.8
3.8
3.5
3.5
3.3
3.3
3.3
134
132
122
130
105
115
110
.6
.6
.5
.6
.5
.5
.5
Northeast…………………………………
338
347
321
302
278
271
278
1.3
1.4
1.3
1.2
1.1
1.1
1.1
South………………………………………
971
949
879
847
790
759
765
2.0
1.9
1.8
1.7
1.6
1.6
1.6
Midwest……………………………………
577
595
491
452
491
468
428
1.9
1.9
1.6
1.5
1.6
1.5
1.4
West………………………………………
560
541
510
498
492
453
397
1.8
1.8
1.7
1.6
1.6
1.5
1.3
Leisure and hospitality……………………
Government…………………………………
Region 3
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;
96
Monthly Labor Review • May 2009
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 quits level is the number of quits during the entire month; the quits
rate is the number of quits during the entire month as a percent of total
employment.
p
= preliminary.
22. Quarterly Census of Employment and Wages: 10 largest counties, third quarter 2008.
County by NAICS supersector
Establishments,
third quarter
2008
(thousands)
Average weekly wage1
Employment
September
2008
(thousands)
Percent change,
September
2007-082
Third
quarter
2008
Percent change,
third 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 .............................................................................
9,150.8
8,857.7
126.2
889.2
361.0
1,927.8
146.3
866.3
1,528.7
851.2
739.3
1,205.9
293.1
135,173.8
113,499.1
2,003.6
7,255.4
13,345.0
25,953.1
2,973.8
7,919.9
17,752.2
17,996.4
13,568.1
4,482.9
21,674.7
-0.8
-1.1
3.6
-6.7
-3.6
-1.3
-2.0
-2.5
-1.4
2.7
.0
.9
1.0
$841
833
880
922
1,006
719
1,335
1,207
1,045
803
358
544
886
2.8
2.8
7.3
5.1
1.9
1.7
4.9
.8
4.6
3.6
2.9
2.4
3.0
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 .............................................................................
428.8
424.8
.5
14.0
14.6
53.7
8.7
24.1
42.5
28.0
27.0
195.2
4.0
4,141.1
3,581.8
11.7
145.0
432.3
792.1
214.8
233.8
583.7
488.8
401.6
259.5
559.3
-1.5
-1.4
-2.8
-9.5
-3.4
-2.1
( 4)
-5.4
( 4)
1.7
-.2
4.2
( 4)
951
923
1,232
994
1,009
775
1,551
1,482
1,104
888
536
439
1,132
3.1
2.7
9.3
5.2
4.6
2.1
( 4)
.1
( 4)
4.5
3.3
.5
5.8
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 .............................................................................
140.4
139.0
.1
12.4
7.0
27.6
2.5
15.7
28.9
13.9
11.7
14.5
1.4
2,504.2
2,195.4
1.3
92.9
226.3
460.4
56.5
206.3
434.2
378.9
237.8
96.6
308.8
-1.3
-1.5
-3.6
-5.9
-4.1
-2.3
-1.5
-3.2
-2.1
2.9
-1.3
1.5
.0
988
986
960
1,284
1,002
788
1,557
1,538
1,248
873
443
707
1,009
2.8
2.8
-9.3
5.9
2.5
1.8
10.2
-.8
5.3
3.3
3.3
2.2
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
22.1
4.6
19.1
25.6
8.8
11.7
18.0
.3
2,363.8
1,919.7
.2
37.8
35.4
248.9
135.9
372.9
491.8
283.4
218.9
89.1
444.1
.6
.7
-8.9
4.1
-5.8
.4
.0
-2.1
1.4
.6
3.9
2.1
.1
1,552
1,673
1,820
1,535
1,183
1,127
1,982
2,985
1,799
1,059
748
919
1,027
.5
.4
14.0
5.4
-2.6
.4
4.2
-2.2
2.3
4.7
3.2
4.1
1.4
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 .............................................................................
97.3
96.7
1.6
6.7
4.6
22.4
1.4
10.6
19.4
10.3
7.5
11.7
.5
2,047.2
1,796.9
84.8
157.2
187.3
428.3
31.9
118.2
336.5
218.7
174.2
58.5
250.3
1.3
1.1
7.9
( 4)
2.8
1.0
-2.4
( 4)
( 4)
1.6
-1.2
.2
2.7
1,050
1,061
2,585
1,005
1,272
919
1,285
1,287
1,233
865
385
598
973
3.0
2.9
( 4)
( 4)
-1.1
2.1
2.1
2.6
4.8
4.3
5.2
1.2
5.1
Maricopa, AZ ................................................................................
Private industry ........................................................................
Natural resources and mining ..............................................
Construction .........................................................................
Manufacturing ......................................................................
Trade, transportation, and utilities ........................................
Information ...........................................................................
Financial activities ................................................................
Professional and business services .....................................
Education and health services .............................................
Leisure and hospitality .........................................................
Other services ......................................................................
Government .............................................................................
103.0
102.3
.5
11.0
3.6
22.8
1.7
12.9
22.9
10.1
7.4
7.3
.7
1,761.0
1,535.7
8.5
130.8
125.0
361.4
29.8
142.4
293.9
216.2
176.8
49.2
225.3
-3.7
-4.5
.9
-21.8
-5.6
-3.9
-2.0
-4.0
-6.4
7.8
-1.7
-2.3
2.3
836
825
840
878
1,137
770
1,083
1,004
863
906
394
584
915
1.8
1.9
16.5
5.1
2.1
-.3
5.5
-1.8
4.2
2.7
1.8
3.4
.9
See footnotes at end of table.
Monthly Labor Review • May 2009
97
Current Labor Statistics: Labor Force Data
22. Continued—Quarterly Census of Employment and Wages: 10 largest counties, third quarter 2008.
County by NAICS supersector
Establishments,
third quarter
2008
(thousands)
Average weekly wage1
Employment
September
2008
(thousands)
Percent change,
September
2007-082
Third
quarter
2008
Percent change,
third 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 .............................................................................
102.5
101.1
.2
6.9
5.3
17.3
1.3
10.8
19.0
10.0
7.1
17.5
1.4
1,469.5
1,327.1
4.5
90.0
171.4
270.0
29.4
112.3
266.8
148.9
177.8
49.4
142.3
-2.8
-3.0
-10.7
-13.4
-3.2
-4.0
-1.2
-9.0
-4.2
3.9
1.3
2.6
-1.2
$955
947
681
1,094
1,133
880
1,552
1,346
1,071
899
420
551
1,033
3.0
2.4
7.1
6.0
3.5
1.7
15.6
-1.0
4.5
3.7
2.2
-1.6
9.2
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 .............................................................................
68.2
67.6
.6
4.4
3.1
15.1
1.7
8.9
14.8
6.7
5.4
6.5
.5
1,489.1
1,321.8
8.3
84.7
132.9
304.7
47.6
143.9
279.1
150.7
129.7
39.1
167.3
.5
.3
14.7
.3
-4.0
.1
-3.2
.4
.7
3.1
1.5
-.5
2.0
1,025
1,034
4,831
922
1,148
953
1,445
1,311
1,153
938
461
634
952
2.4
2.3
61.8
2.6
-1.0
.3
5.8
-3.7
2.6
4.1
4.5
4.1
3.6
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 .............................................................................
99.6
98.3
.8
7.1
3.1
14.2
1.3
9.6
16.2
8.1
6.9
26.1
1.3
1,318.0
1,099.8
11.4
76.2
102.1
214.5
39.1
75.2
215.9
135.5
165.8
58.2
218.2
-1.2
-1.5
-3.6
-12.9
-.4
-3.2
3.6
-5.2
-2.2
3.8
.0
1.6
.4
921
904
564
988
1,198
733
2,244
1,090
1,131
869
419
489
1,014
3.8
4.1
1.6
4.2
3.3
-.8
30.4
-2.2
4.6
4.3
2.9
1.5
2.7
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 .............................................................................
78.5
78.0
.4
6.9
2.5
15.2
1.8
7.1
13.9
6.6
6.2
17.5
.5
1,198.7
1,045.7
3.2
72.3
112.0
220.2
80.9
74.6
193.2
126.5
115.7
47.2
153.0
1.4
1.3
.8
-2.9
-.8
.3
5.9
-.9
1.3
5.2
1.9
4.2
2.1
1,162
1,176
1,288
1,083
1,259
921
3,364
1,368
1,243
863
447
601
1,064
2.9
2.7
12.1
4.9
.6
3.5
8.3
6.0
-6.3
3.0
.9
4.7
4.9
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 .............................................................................
87.8
87.5
.5
6.6
2.6
23.5
1.5
10.4
18.1
9.4
6.0
7.6
.4
993.1
842.7
7.7
44.2
42.8
248.8
19.0
68.0
129.8
144.2
100.6
35.9
150.4
-3.2
-3.5
-9.6
-20.3
-10.2
-2.1
-7.5
-5.6
-4.4
2.8
-2.0
-.5
-1.4
842
805
474
844
745
746
1,227
1,156
1,011
822
481
523
1,058
2.2
1.5
-2.3
2.9
3.5
-.4
2.8
.3
4.6
1.7
4.3
1.4
4.9
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
98
Totals for the United States do not include data for Puerto Rico or the
Monthly Labor Review • May 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, third quarter 2008.
State
Establishments,
third quarter
2008
(thousands)
Average weekly wage1
Employment
September
2008
(thousands)
Percent change,
September
2007-08
Third
quarter
2008
Percent change,
third quarter
2007-08
United States2 ...................................
9,150.8
135,173.8
-0.8
$841
2.8
Alabama ............................................
Alaska ...............................................
Arizona ..............................................
Arkansas ...........................................
California ...........................................
Colorado ...........................................
Connecticut .......................................
Delaware ...........................................
District of Columbia ...........................
Florida ...............................................
121.8
21.6
164.1
86.1
1,344.6
180.4
113.5
29.5
33.8
625.2
1,936.4
332.1
2,570.1
1,185.0
15,527.1
2,322.7
1,692.5
420.6
688.2
7,546.4
-1.2
1.4
-3.0
-.1
-1.4
.4
-.3
-1.1
1.4
-4.1
730
872
798
649
959
877
1,032
879
1,391
756
3.3
3.7
2.0
3.0
2.9
3.8
1.0
2.1
1.0
2.2
Georgia .............................................
Hawaii ...............................................
Idaho .................................................
Illinois ................................................
Indiana ..............................................
Iowa ..................................................
Kansas ..............................................
Kentucky ...........................................
Louisiana ...........................................
Maine ................................................
276.6
39.1
57.0
369.7
160.5
94.6
86.7
110.4
124.1
50.7
4,018.6
613.0
665.7
5,872.8
2,897.6
1,499.0
1,368.9
1,795.3
1,877.4
610.8
-1.6
-2.1
-1.4
-.7
-1.4
.2
.0
-1.0
-.2
-.6
794
774
643
891
718
696
711
692
756
683
1.5
1.8
1.3
2.9
2.3
4.2
4.6
2.4
5.6
3.5
Maryland ...........................................
Massachusetts ..................................
Michigan ............................................
Minnesota .........................................
Mississippi .........................................
Missouri .............................................
Montana ............................................
Nebraska ...........................................
Nevada ..............................................
New Hampshire ................................
163.9
213.9
259.0
171.6
70.8
175.4
43.3
60.0
77.5
49.8
2,543.4
3,265.7
4,093.9
2,699.6
1,128.3
2,736.1
446.4
925.7
1,253.0
634.6
-.8
.0
-3.0
-.5
-1.3
-.4
.1
.2
-2.7
-.5
920
1,025
820
862
631
739
628
694
809
822
3.1
2.3
1.5
4.7
4.0
2.8
3.1
4.2
2.1
2.8
New Jersey .......................................
New Mexico ......................................
New York ..........................................
North Carolina ...................................
North Dakota .....................................
Ohio ..................................................
Oklahoma ..........................................
Oregon ..............................................
Pennsylvania .....................................
Rhode Island .....................................
277.8
54.7
586.1
259.4
25.8
295.5
100.9
132.5
343.5
35.9
3,952.9
835.2
8,633.8
4,064.2
357.0
5,251.1
1,562.8
1,734.1
5,679.0
476.0
-.7
.7
.5
-1.0
2.8
-1.5
1.2
-1.0
.0
-2.0
990
712
1,030
741
665
766
698
766
822
778
2.5
3.5
2.2
3.1
6.9
2.8
4.5
2.1
2.5
2.5
South Carolina ..................................
South Dakota ....................................
Tennessee ........................................
Texas ................................................
Utah ..................................................
Vermont ............................................
Virginia ..............................................
Washington .......................................
West Virginia .....................................
Wisconsin ..........................................
119.6
30.6
143.5
563.6
87.3
25.1
232.7
225.5
48.9
161.6
1,874.6
401.3
2,730.4
10,438.3
1,229.3
304.2
3,676.1
3,007.5
716.4
2,788.7
-1.5
1.0
-1.5
1.4
-.1
-.5
-.3
1.0
.6
-.6
683
623
745
850
717
722
877
903
661
730
2.9
4.2
2.8
2.9
2.9
3.3
2.3
3.0
5.9
3.4
Wyoming ...........................................
25.2
294.0
3.3
781
6.4
Puerto Rico .......................................
Virgin Islands ....................................
55.6
3.5
992.8
44.9
-1.6
-.9
477
709
5.5
4.3
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 • May 2009
99
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.
100
Monthly Labor Review • May 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 • May 2009
101
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.
102
2006
Monthly Labor Review • May 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 • May 2009
103
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.
104
Percent
change,
2006-07
2006
Monthly Labor Review • May 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 • May 2009
105
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.
106
Percent
change,
2006-07
2006
Monthly Labor Review • May 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 • May 2009
107
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.
108
Monthly Labor Review • May 2009
30. Employment Cost Index, compensation,1 by occupation and industry group
[December 2005 = 100]
2007
Series
Mar.
June
2008
Sept.
Dec.
Mar.
June
2009
Sept.
Dec.
Mar.
Percent change
3 months
ended
12 months
ended
Mar. 2009
2
Civilian workers ……….…….........…………………………………….…
104.2
105.0
106.1
106.7
107.6
108.3
109.2
109.5
109.9
0.4
2.1
Management, professional, and related………………………
Management, business, and financial……………………
Professional and related……………………………………
Sales and office…………………………………………………
Sales and related……………………………………………
Office and administrative support…………………………
104.7
104.4
104.9
103.8
102.4
104.7
105.5
105.2
105.7
104.8
103.6
105.5
106.7
106.2
107.0
105.5
104.1
106.4
107.2
106.6
107.6
106.4
105.2
107.1
108.3
108.2
108.4
106.8
105.0
108.0
109.0
108.9
109.0
107.7
106.1
108.6
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
.5
.2
.5
.1
-1.1
.7
2.4
1.7
2.7
1.5
-.7
2.6
Natural resources, construction, and maintenance…………
Construction and extraction………………………………
Installation, maintenance, and repair……………………
Production, transportation, and material moving……………
Production……………………………………………………
Transportation and material moving………………………
Service occupations……………………………………………
104.1
104.3
103.7
102.7
102.1
103.4
104.8
105.1
105.7
104.4
103.5
102.8
104.4
105.5
106.1
106.5
105.6
104.2
103.3
105.3
106.9
106.8
107.4
106.2
104.7
104.1
105.6
107.7
107.7
108.5
106.7
105.6
104.8
106.6
108.4
108.4
109.6
107.0
106.2
105.3
107.3
109.1
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
.3
.2
.5
.7
.9
.5
.8
2.2
2.3
2.2
2.3
2.3
2.2
2.9
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…………………
102.9
102.0
104.4
104.9
105.4
105.1
104.5
104.5
104.6
103.9
102.9
105.2
105.5
106.1
105.7
105.0
104.9
105.0
104.4
103.2
106.4
107.2
107.1
106.7
105.6
107.3
107.4
105.0
103.8
107.0
107.9
107.9
107.5
106.3
107.9
107.9
106.1
104.7
107.8
108.6
108.9
108.4
107.3
108.3
108.2
106.8
105.1
108.5
109.2
109.6
109.2
108.2
108.9
108.8
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
.5
.6
.5
.5
.8
.8
.6
.4
.4
1.8
1.7
2.3
2.9
2.6
3.0
2.8
3.2
3.4
Public administration ……………………………………… 105.6
106.6
108.0
109.1
109.7
110.1
111.6
112.0
113.0
.9
3.0
104.0
104.9
105.7
106.3
107.3
108.0
108.7
108.9
109.3
.4
1.9
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……………………………………………
104.6
104.3
104.9
103.7
102.4
104.5
104.0
104.4
103.5
102.5
102.1
103.1
104.5
105.5
105.1
105.9
104.7
103.6
105.4
105.0
105.7
104.1
103.3
102.8
104.1
105.2
106.4
106.0
106.7
105.3
104.2
106.0
105.9
106.5
105.2
103.9
103.2
104.9
106.4
106.8
106.3
107.3
106.1
105.2
106.7
106.7
107.4
105.8
104.5
104.0
105.3
107.0
108.1
108.0
108.3
106.6
105.0
107.8
107.6
108.6
106.3
105.5
104.8
106.4
107.8
108.9
108.7
109.0
107.5
106.2
108.5
108.3
109.7
106.6
106.0
105.2
107.2
108.7
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
.5
.1
.6
.0
-1.1
.8
.3
.1
.5
.7
.9
.5
.8
2.1
1.5
2.5
1.2
-.7
2.5
2.1
2.1
2.2
2.1
2.2
1.9
2.7
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………..
102.9
102.7
103.0
104.0
102.1
103.9
103.8
103.7
105.3
102.9
104.4
104.3
104.1
106.1
103.3
105.0
104.4
104.8
107.0
104.0
106.1
106.1
105.1
108.1
104.8
106.8
106.6
106.3
109.0
105.3
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
.4
.2
.2
.0
.8
1.7
.7
2.1
2.1
2.1
Construction…………………………………………………
Manufacturing…………………………………………………
Management, professional, and related…………………
Sales and office……………………………………………
Natural resources, construction, and maintenance……
Production, transportation, and material moving……..
104.7
102.0
102.0
102.4
101.7
101.9
105.9
102.9
103.3
103.2
102.4
102.6
106.9
103.2
103.3
103.5
102.8
103.1
107.6
103.8
103.5
104.3
103.9
103.8
108.9
104.7
104.9
105.0
104.6
104.5
110.1
105.1
105.2
106.1
104.5
105.0
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
.0
.6
.3
.3
.6
.9
1.8
1.7
.8
2.2
1.9
2.1
Service-providing industries…………………………………
Management, professional, and related……………………
Sales and office………………………………………………
Natural resources, construction, and maintenance………
Production, transportation, and material moving………..
Service occupations…………………………………………
104.3
105.0
103.7
104.0
103.0
104.5
105.2
105.9
104.8
104.5
104.0
105.3
106.1
106.8
105.4
105.7
104.7
106.4
106.7
107.3
106.3
106.2
105.2
107.1
107.7
108.5
106.8
106.7
106.4
107.9
108.5
109.3
107.7
107.3
107.0
108.7
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
.4
.5
.0
.6
.6
.8
1.9
2.4
1.1
2.2
2.0
2.6
Trade, transportation, and utilities…………………………
103.1
104.2
104.7
105.5
106.1
107.3
107.6
107.5
107.8
.3
1.6
Workers by occupational group
3
Private industry workers………………………………………
See footnotes at end of table.
Monthly Labor Review • May 2009
109
Current Labor Statistics: Compensation & Industrial Relations
30. Continued—Employment Cost Index, compensation,1 by occupation and industry group
[December 2005 = 100]
2007
Series
Mar.
June
2008
Sept.
Dec.
Mar.
June
2009
Sept.
Dec.
Mar.
Percent change
3 months
ended
12 months
ended
Mar. 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……………
103.7
102.9
102.8
102.8
104.3
104.2
104.6
102.2
104.7
105.1
104.5
105.2
105.0
105.3
105.8
105.7
104.6
103.9
104.0
104.7
105.6
104.6
104.9
103.0
105.9
105.7
104.9
105.9
105.6
106.0
106.4
106.1
104.2
105.1
104.5
105.0
105.8
105.4
105.7
104.1
106.9
106.9
106.7
106.9
106.5
107.5
108.1
107.1
105.3
106.1
104.5
105.6
106.1
105.6
106.1
103.7
107.5
107.7
107.5
107.8
107.3
108.1
108.6
107.6
105.7
106.6
105.6
106.5
106.1
106.8
107.0
105.5
109.0
108.6
108.1
108.8
108.2
109.0
109.5
108.7
107.2
107.6
106.4
108.1
106.2
107.3
107.7
105.7
109.9
109.4
109.1
109.4
109.1
109.3
110.0
109.4
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
0.3
.2
.5
.6
.3
-.3
-.3
.0
.3
.8
.5
.9
.7
.7
.8
.8
1.3
1.6
1.7
2.9
1.5
.0
-.1
1.0
2.7
2.7
3.5
2.5
3.0
2.9
3.2
1.9
105.1
105.7
107.6
108.4
108.9
109.4
111.3
111.6
112.3
.6
3.1
Workers by occupational group
Management, professional, and related………………………
Professional and related……………………………………
Sales and office…………………………………………………
Office and administrative support…………………………
Service occupations……………………………………………
104.9
104.8
105.6
105.7
105.4
105.4
105.3
106.2
106.4
106.3
107.5
107.5
107.9
108.2
108.0
108.3
108.2
108.6
108.9
109.1
108.8
108.6
108.8
109.3
109.7
109.3
109.1
109.3
109.8
110.0
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
.4
.4
1.0
.9
.9
2.9
3.0
3.3
3.2
3.4
Workers by industry
Education and health services………………………………
Education services………………………………………
Schools…………………………………………………
Elementary and secondary schools………………
Health care and social assistance………………………
Hospitals…………………………………………………
104.8
104.6
104.6
104.7
107.1
105.6
105.3
105.0
104.9
105.0
107.6
106.3
107.5
107.4
107.4
107.4
108.6
107.5
108.2
108.0
108.0
108.0
109.3
108.2
108.6
108.4
108.4
108.3
110.1
109.2
109.1
108.8
108.8
108.8
111.1
109.7
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
.4
.5
.5
.5
.1
1.0
3.0
3.1
3.1
3.4
2.9
2.9
105.6
106.6
108.0
109.1
109.7
110.1
111.6
112.0
113.0
.9
3.0
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.
110
Monthly Labor Review • May 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
Mar.
June
2008
Sept.
Dec.
Mar.
June
2009
Sept.
Dec.
Mar.
Percent change
3 months
ended
12 months
ended
Mar. 2009
1
Civilian workers ……….…….........…………………………………….…
104.3
105.0
106.0
106.7
107.6
108.4
109.3
109.6
110.0
0.4
2.2
Management, professional, and related………………………
Management, business, and financial……………………
Professional and related……………………………………
Sales and office…………………………………………………
Sales and related……………………………………………
Office and administrative support…………………………
104.7
104.7
104.7
103.8
102.7
104.5
105.4
105.4
105.3
104.8
103.9
105.3
106.6
106.4
106.7
105.4
104.3
106.1
107.1
106.7
107.4
106.2
105.5
106.8
108.2
108.2
108.3
106.7
105.2
107.8
109.0
109.0
109.0
107.7
106.6
108.5
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
.5
.3
.5
.0
-1.2
.7
2.6
2.0
2.7
1.3
-.9
2.6
Natural resources, construction, and maintenance…………
Construction and extraction………………………………
Installation, maintenance, and repair……………………
Production, transportation, and material moving……………
Production……………………………………………………
Transportation and material moving………………………
Service occupations……………………………………………
104.3
104.6
103.8
103.2
103.2
103.3
104.6
105.1
105.7
104.4
103.9
103.6
104.2
105.3
106.3
106.6
105.8
104.7
104.3
105.1
106.5
107.1
107.7
106.4
105.1
104.7
105.5
107.3
108.1
109.0
107.0
106.1
105.7
106.6
108.0
109.0
109.9
107.8
106.9
106.5
107.3
108.7
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
.1
.1
.4
.5
.7
.3
.8
2.4
2.2
2.8
2.3
2.4
2.1
3.0
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
103.3
104.3
104.4
105.1
104.8
104.1
103.7
103.6
104.7
103.9
105.1
104.9
105.9
105.6
104.7
104.0
103.8
105.4
104.5
106.2
106.6
107.1
106.7
105.8
106.2
106.0
106.0
104.9
106.8
107.4
107.9
107.4
106.4
106.9
106.6
107.1
105.9
107.7
108.0
108.9
108.4
107.4
107.3
107.0
108.0
106.7
108.5
108.7
109.6
109.4
108.1
107.9
107.5
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
.2
.4
.5
.5
.7
.6
.5
.3
.3
2.0
2.1
2.3
2.8
2.6
3.3
2.7
3.0
3.2
Public administration ……………………………………… 104.5
105.2
106.4
107.4
108.2
108.6
109.9
110.4
111.3
.8
2.9
104.3
105.1
106.0
106.6
107.6
108.4
109.1
109.4
109.8
.4
2.0
Workers by occupational group
Management, professional, and related………………………
Management, business, and financial……………………
Professional and related……………………………………
Sales and office…………………………………………………
Sales and related……………………………………………
Office and administrative support…………………………
Natural resources, construction, and maintenance…………
Construction and extraction…………………………………
Installation, maintenance, and repair………………………
Production, transportation, and material moving……………
Production……………………………………………………
Transportation and material moving………………………
Service occupations……………………………………………
104.9
104.7
105.1
103.8
102.8
104.5
104.2
104.7
103.7
103.1
103.1
103.2
104.6
105.8
105.5
106.0
104.8
104.0
105.4
105.1
105.8
104.2
103.8
103.6
104.1
105.3
106.7
106.3
107.0
105.3
104.4
106.0
106.2
106.7
105.6
104.5
104.2
105.0
106.5
107.2
106.6
107.6
106.2
105.5
106.7
107.1
107.8
106.1
105.0
104.6
105.4
107.1
108.5
108.2
108.7
106.7
105.3
107.7
108.1
109.2
106.8
106.0
105.6
106.5
107.9
109.3
109.0
109.5
107.7
106.6
108.5
109.0
110.1
107.6
106.8
106.4
107.4
108.8
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
.5
.3
.6
-.1
-1.3
.8
.1
-.1
.4
.5
.7
.2
.8
2.4
1.9
2.7
1.1
-.9
2.7
2.3
2.0
2.7
2.2
2.4
1.9
2.9
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
104.4
103.4
104.4
103.2
104.7
105.3
104.1
105.6
103.7
105.4
105.9
104.7
106.5
104.4
106.0
106.0
105.5
107.6
104.8
107.1
107.7
105.8
108.8
105.7
108.0
108.4
107.2
109.6
106.6
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
.2
.5
.2
-.2
.4
2.0
1.5
2.2
2.1
2.2
Construction…………………………………………………
Manufacturing…………………………………………………
Management, professional, and related…………………
Sales and office……………………………………………
Natural resources, construction, and maintenance……
Production, transportation, and material moving……..
104.9
103.3
103.8
102.4
103.8
103.1
106.0
103.9
104.6
103.2
104.3
103.6
107.0
104.5
105.0
103.9
105.0
104.2
107.8
104.9
105.3
104.7
105.9
104.5
109.0
105.9
106.7
105.5
106.8
105.4
110.0
106.7
107.2
106.9
107.1
106.3
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
.1
.4
.6
.1
-.2
.4
2.0
2.1
1.6
2.6
1.9
2.2
Service-providing industries…………………………………
Management, professional, and related……………………
Sales and office………………………………………………
Natural resources, construction, and maintenance………
Production, transportation, and material moving………..
Service occupations…………………………………………
104.4
105.0
103.8
103.9
103.0
104.6
105.3
105.9
104.9
104.3
104.0
105.3
106.1
106.8
105.4
105.7
104.6
106.6
106.8
107.4
106.3
106.3
105.2
107.2
107.7
108.6
106.8
106.9
106.3
108.0
108.6
109.4
107.7
108.0
107.1
108.8
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
.4
.5
-.1
.5
.5
.8
2.1
2.6
1.0
2.8
2.2
2.8
Trade, transportation, and utilities…………………………
103.2
104.3
104.6
105.5
105.9
107.2
107.5
107.4
107.8
.4
1.8
Workers by occupational group
2
Private industry workers………………………………………
Monthly Labor Review • May 2009
111
Current Labor Statistics: Compensation & Industrial Relations
31. Continued—Employment Cost Index, wages and salaries, by occupation and industry group
[December 2005 = 100]
2007
Series
Mar.
June
2008
Sept.
Dec.
Mar.
June
2009
Sept.
Dec.
Mar.
Percent change
3 months
ended
12 months
ended
Mar. 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……………
103.8
103.1
102.5
104.3
103.8
104.7
105.4
101.6
104.8
104.8
104.2
104.9
104.6
105.7
106.0
105.7
104.8
104.2
103.7
105.5
104.9
104.9
105.5
102.4
105.9
105.6
104.6
105.8
105.4
106.4
106.5
106.1
104.0
105.1
104.1
106.1
105.2
106.0
106.5
103.6
106.7
106.9
106.4
107.0
106.5
108.1
108.4
107.3
105.2
106.1
104.2
106.8
105.3
105.9
106.6
103.1
107.5
107.7
107.4
107.8
107.2
108.8
109.0
107.9
105.2
106.4
105.0
108.0
105.3
107.2
107.9
104.5
109.1
108.6
107.9
108.7
108.2
109.7
110.0
109.2
107.2
107.6
106.0
109.3
106.3
107.7
108.4
104.7
110.0
109.2
108.6
109.4
109.2
109.9
110.4
109.9
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
0.4
.2
.3
1.3
.3
-.4
-.5
-.1
.4
.7
.3
.8
.6
.7
.8
.9
1.5
1.8
2.1
2.8
2.4
-.4
-.7
1.1
2.9
2.6
3.0
2.6
3.3
3.1
3.4
2.0
104.1
104.6
106.4
107.1
107.7
108.2
110.1
110.4
110.9
.5
3.0
Workers by occupational group
Management, professional, and related………………………
Professional and related……………………………………
Sales and office…………………………………………………
Office and administrative support…………………………
Service occupations……………………………………………
104.0
103.9
104.5
104.7
104.5
104.3
104.2
104.8
105.0
105.2
106.3
106.3
106.3
106.5
106.5
107.0
107.0
107.0
107.3
107.7
107.6
107.5
107.4
107.8
108.3
108.2
108.1
107.9
108.3
108.6
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
.3
.3
.7
.8
1.0
2.9
2.9
2.9
3.0
3.4
Workers by industry
Education and health services………………………………
Education services………………………………………
Schools…………………………………………………
Elementary and secondary schools………………
Health care and social assistance………………………
Hospitals…………………………………………………
104.0
103.7
103.6
103.6
106.6
105.7
104.2
103.9
103.9
103.8
107.2
106.5
106.3
106.1
106.1
106.0
108.2
107.6
107.1
106.8
106.8
106.6
109.2
108.6
107.5
107.2
107.2
106.9
110.1
109.8
108.1
107.7
107.7
107.5
111.0
110.3
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
.2
.3
.3
.2
-.3
.6
3.0
3.0
3.0
3.2
2.7
2.7
104.5
105.2
106.4
107.4
108.2
108.6
109.9
110.4
111.3
.8
2.9
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
112
Monthly Labor Review • May 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
Mar.
June
2008
Sept.
Dec.
Mar.
June
2009
Sept.
Dec.
Mar.
Percent change
3 months
ended
12 months
ended
Mar. 2009
Civilian workers………………………………………………….
104.0
105.1
106.1
106.8
107.6
108.1
108.9
109.1
109.7
0.5
2.0
Private industry workers………………………………………… 103.2
104.3
105.0
105.6
106.5
107.0
107.5
107.7
108.2
.5
1.6
Workers by occupational group
Management, professional, and related………………………
Sales and office…………………………………………………
Natural resources, construction, and maintenance…………
Production, transportation, and material moving……………
103.8
103.4
103.4
101.2
104.9
104.3
104.8
102.4
105.6
105.2
105.3
102.7
106.0
106.0
105.9
103.7
107.3
106.5
106.5
104.4
107.9
107.0
107.0
104.5
108.5
107.6
107.5
104.8
108.5
107.8
107.7
105.1
108.8
108.0
108.2
106.4
.3
.2
.5
1.2
1.4
1.4
1.6
1.9
Service occupations……………………………………………
104.2
105.1
106.0
106.7
107.6
108.5
108.7
108.8
109.7
.8
2.0
100.9
Goods-producing………………………………………………
Manufacturing………………………………………………… 99.6
Service-providing……………………………………………… 104.1
102.2
101.0
105.2
102.4
100.7
106.0
103.2
101.7
106.6
104.0
102.3
107.6
104.4
102.2
108.1
104.6
102.3
108.7
104.7
102.5
108.9
105.4
103.5
109.3
.7
1.0
.4
1.3
1.2
1.6
108.0
110.3
111.0
111.4
111.8
113.9
114.2
115.2
.9
3.4
Workers by industry
State and local government workers…………………………
107.0
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 • May 2009
113
Current Labor Statistics: Compensation & Industrial Relations
33. Employment Cost Index, private industry workers by bargaining status and region
[December 2005 = 100]
2007
Series
Mar.
June
2008
Sept.
Dec.
Mar.
June
2009
Sept.
Dec.
Mar.
Percent change
3 months
ended
12 months
ended
Mar. 2009
COMPENSATION
Workers by bargaining status1
Union………………………………………………………………… 102.7
Goods-producing………………………………………………… 101.5
Manufacturing…………………………………………………
99.2
Service-providing………………………………………………… 103.7
103.9
102.8
100.0
104.7
104.4
103.1
100.0
105.4
105.1
104.0
101.0
106.0
105.9
104.6
101.4
107.0
106.7
105.6
101.7
107.5
107.4
106.2
102.1
108.3
108.0
106.9
102.8
108.8
109.1
108.0
104.4
109.9
1.0
1.0
1.6
1.0
3.0
3.3
3.0
2.7
Nonunion……………………………………………………………
Goods-producing…………………………………………………
Manufacturing…………………………………………………
Service-providing…………………………………………………
104.2
103.3
102.8
104.4
105.1
104.2
103.7
105.3
105.9
104.8
104.1
106.2
106.5
105.4
104.6
106.8
107.5
106.5
105.6
107.7
108.3
107.1
106.2
108.6
108.9
107.6
106.6
109.2
109.1
107.7
106.8
109.4
109.4
107.9
107.1
109.8
.3
.2
.3
.4
1.8
1.3
1.4
1.9
Workers by region1
Northeast……………………………………………………………
South…………………………………………………………………
Midwest………………………………………………………………
West…………………………………………………………………
104.0
104.3
103.3
104.2
105.1
105.3
104.2
104.9
106.2
106.1
104.6
105.7
106.8
106.7
105.3
106.5
107.4
107.8
106.0
107.8
108.1
108.5
107.0
108.4
108.7
109.1
107.4
109.3
109.5
109.3
107.6
109.4
109.8
109.8
107.9
109.9
.3
.5
.3
.5
2.2
1.9
1.8
1.9
Workers by bargaining status1
Union…………………………………………………………………
Goods-producing…………………………………………………
Manufacturing…………………………………………………
Service-providing…………………………………………………
102.8
102.7
102.0
102.9
103.7
103.6
102.5
103.8
104.4
104.3
102.9
104.6
104.7
104.3
102.6
104.9
105.5
105.2
103.4
105.8
106.7
106.4
104.4
106.9
107.4
107.1
104.9
107.7
108.1
107.7
105.5
108.3
108.8
108.2
106.0
109.2
.6
.5
.5
.8
3.1
2.9
2.5
3.2
Nonunion……………………………………………………………
Goods-producing…………………………………………………
Manufacturing…………………………………………………
Service-providing…………………………………………………
104.5
104.2
103.6
104.6
105.3
105.0
104.2
105.4
106.2
105.8
104.9
106.3
106.9
106.4
105.5
107.0
107.9
107.7
106.6
107.9
108.7
108.4
107.3
108.8
109.4
109.0
108.0
109.4
109.6
109.3
108.2
109.7
110.0
109.5
108.6
110.1
.4
.2
.4
.4
1.9
1.7
1.9
2.0
Workers by region1
Northeast……………………………………………………………
South…………………………………………………………………
Midwest………………………………………………………………
West…………………………………………………………………
104.0
104.6
103.6
104.8
105.0
105.6
104.4
105.4
106.1
106.5
105.0
106.2
106.6
107.0
105.6
107.0
107.5
108.1
106.3
108.3
108.2
109.1
107.5
108.9
108.7
109.8
107.9
109.9
109.6
110.0
108.0
110.1
109.9
110.4
108.4
110.5
.3
.4
.4
.4
2.2
2.1
2.0
2.0
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.
114
Monthly Labor Review • May 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
Year
Series
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 ……………….
Sales and office ……………………………………………
2
Blue-collar occupations ………………………………………
Natural resources, construction, and maintenance...…
Production, transportation, and material moving…...…
Service occupations……………………………………………
61
-
-
-
-
59
59
60
62
-
-
-
-
-
61
-
-
-
-
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 ……………………………………………
2
Blue-collar occupations ………………………………………
Natural resources, construction, and maintenance…...
Production, transportation, and material moving…...…
-
-
-
-
50
50
51
52
-
-
-
-
-
51
-
-
-
-
54
Service occupations……………………………………………
21
22
22
24
25
Full-time…………………………………………………………
58
60
60
60
60
Part-time………………………………………………………
18
20
19
21
23
Union……………………………………………………………
83
81
85
80
81
Non-union………………………………………………………
45
47
46
47
47
Average wage less than $15 per hour……...………………
35
36
35
36
36
Average wage $15 per hour or higher……...………………
70
71
71
70
69
Goods-producing industries…………………………………
63
63
64
64
61
Service-providing industries…………………………………
45
47
47
47
48
Establishments with 1-99 workers……………………………
35
37
37
37
37
Establishments with 100 or more workers…………………
65
67
67
67
66
-
-
85
85
84
All workers………………………………………………………
20
21
22
21
21
White-collar occupations 2 ……………………………………
23
24
25
23
-
-
-
-
-
29
19
3
Take-up rate (all workers) ……………………………………
Defined Benefit
Percentage of workers with access
Management, professional, and related ……………….
Sales and office ……………………………………………
-
-
-
-
Blue-collar occupations 2………………………………………
24
26
26
25
-
-
-
-
-
26
26
Natural resources, construction, and maintenance...…
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
Establishments with 1-99 workers……………………………
Establishments with 100 or more workers…………………
9
9
10
9
9
34
35
37
35
34
See footnotes at end of table.
Monthly Labor Review • May 2009
115
Current Labor Statistics: Compensation & Industrial Relations
34. Continued—National Compensation Survey: Retirement benefits in private industry
by access, participation, and selected series, 2003–2007
Year
Series
2003
2004
2005
2007
2006
1
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...…
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
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
20
22
25
7
23
8
68
14
10
20
28
17
25
25
7
23
9
67
15
10
Defined Contribution
Percentage of workers with access
Management, professional, and related ……………….
Sales and office ……………………………………………
2
Blue-collar occupations ……………………………………
Natural resources, construction, and maintenance...…
-
-
-
-
49
49
50
53
-
-
-
-
-
51
Production, transportation, and material moving…...…
-
-
-
-
56
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……………………………………
38
38
38
40
-
Natural resources, construction, and maintenance...…
-
-
-
-
40
Sales and office ……………………………………………
Production, transportation, and material moving…...…
-
-
-
-
41
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.
116
Monthly Labor Review • May 2009
34. Continued—National Compensation Survey: Retirement benefits in private industry
by access, participation, and selected series, 2003–2007
Year
Series
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 • May 2009
117
Current Labor Statistics: Compensation & Industrial Relations
35. National Compensation Survey: Health insurance benefits in private industry
by access, particpation, and selected series, 2003-2007
Year
Series
2003
2004
2005
2007
2006
1
Medical insurance
Percentage of workers with access
All workers…………………………………………………………………………
60
69
70
71
White-collar occupations 2 ………………………………………………………
65
76
77
77
-
-
-
-
-
85
71
Management, professional, and related …………………………………
Sales and office………………………………………………………………
2
Blue-collar occupations ………………………………………………………
Natural resources, construction, and maintenance………………………
71
-
-
-
-
64
76
77
77
-
-
-
-
-
76
Production, transportation, and material moving…………………………
-
-
-
-
78
Service occupations……………………………………………………………
38
42
44
45
46
Full-time…………………………………………………………………………
73
84
85
85
85
Part-time…………………………………………………………………………
17
20
22
22
24
Union………………………………………………………………………………
67
89
92
89
88
Non-union…………………………………………………………………………
59
67
68
68
69
Average wage less than $15 per hour…………………………………………
51
57
58
57
57
87
Average wage $15 per hour or higher…………………………………………
74
86
87
88
Goods-producing industries……………………………………………………
68
83
85
86
85
Service-providing industries……………………………………………………
57
65
66
66
67
Establishments with 1-99 workers………………………………………………
49
58
59
59
59
Establishments with 100 or more workers……………………………………
72
82
84
84
84
All workers…………………………………………………………………………
45
53
53
52
52
White-collar occupations 2 ………………………………………………………
50
59
58
57
-
-
-
-
-
67
48
Percentage of workers participating
Management, professional, and related …………………………………
Sales and office………………………………………………………………
Blue-collar occupations 2………………………………………………………
Natural resources, construction, and maintenance………………………
-
-
-
-
51
60
61
60
-
-
-
-
-
61
Production, transportation, and material moving…………………………
-
-
-
-
60
Service occupations……………………………………………………………
22
24
27
27
28
Full-time…………………………………………………………………………
56
66
66
64
64
Part-time…………………………………………………………………………
9
11
12
13
12
78
Union………………………………………………………………………………
60
81
83
80
Non-union…………………………………………………………………………
44
50
49
49
49
Average wage less than $15 per hour…………………………………………
35
40
39
38
37
70
Average wage $15 per hour or higher…………………………………………
61
71
72
71
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
3
Take-up rate (all workers) ………………………………………………………
-
-
75
74
73
All workers…………………………………………………………………………
40
46
46
46
46
White-collar occupations 2 ………………………………………………………
47
53
54
53
-
-
-
-
-
62
47
Dental
Percentage of workers with access
Management, professional, and related …………………………………
Sales and office………………………………………………………………
2
Blue-collar occupations ………………………………………………………
Natural resources, construction, and maintenance………………………
-
-
-
47
47
46
-
-
-
-
-
43
Production, transportation, and material moving…………………………
-
-
-
-
49
Service occupations……………………………………………………………
22
25
25
27
28
Full-time…………………………………………………………………………
49
56
56
55
56
Part-time…………………………………………………………………………
9
13
14
15
16
Union………………………………………………………………………………
57
73
73
69
68
Non-union…………………………………………………………………………
38
43
43
43
44
Average wage less than $15 per hour…………………………………………
30
34
34
34
34
Average wage $15 per hour or higher…………………………………………
55
63
62
62
61
Goods-producing industries……………………………………………………
48
56
56
56
54
Service-providing industries……………………………………………………
37
43
43
43
44
Establishments with 1-99 workers………………………………………………
27
31
31
31
30
Establishments with 100 or more workers……………………………………
55
64
65
64
64
See footnotes at end of table.
118
40
Monthly Labor Review • May 2009
35. Continued—National Compensation Survey: Health insurance benefits in
private industry by access, particpation, and selected series, 2003-2007
Year
Series
2003
2004
2005
2007 1
2006
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
3
Take-up rate (all workers) …………………………………………………………
-
-
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 • May 2009
119
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
33
Section 125 cafeteria benefits
Healthcare reimbursement account……………………...…
-
-
31
32
Health Savings Account………………………………...………
-
-
5
6
8
Employee assistance program……………………….…………
-
-
40
40
42
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
2008
Measure
2007
Number of stoppages:
Beginning in period.............................
In effect during period…......................
2008
Mar.
Apr.
May
June
July
2009
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.p
Mar.p
21
23
15
16
2
4
1
2
2
4
2
2
1
1
2
2
2
2
1
2
0
1
0
0
0
0
0
0
0
0
Workers involved:
Beginning in period (in thousands)…..
In effect during period (in thousands)…
189.2
220.9
72.2
136.8
5.7
11.8
2.3
5.9
4.2
10.1
4.2
4.2
8.5
8.5
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
Days idle:
Number (in thousands)…....................
1264.8
1954.1
128.8
102.2
129.0
12.3
42.5
100.6
469.8
600.0
0.0
0.0
0.0
0.0
0.0
0.01
0.01
0
0
0
0
0
0
0.02
0.02
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
120
Monthly Labor Review • May 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
2007
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…................................
2008
2009
2008
Mar.
Apr.
May
June
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
213.528
639.636
209.692
209.385
208.203
236.261
199.775
214.823
643.515
211.365
211.102
210.851
240.034
200.770
216.632
648.933
212.251
212.054
211.863
244.192
200.960
218.815
655.474
213.383
213.243
213.171
245.758
202.914
219.964
658.915
215.326
215.299
215.785
250.321
205.075
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
207.3
621.1
203.3
202.9
201.2
222.1
195.6
215.303
644.951
214.225
214.106
214.125
244.853
204.653
Dairy and related products ……….…………………………
Fruits and vegetables….............................................
Nonalcoholic beverages and beverage
194.8
262.6
210.396 206.171 207.680 207.778 209.117 213.981 214.748 213.533 212.733 213.102 210.838 209.632 204.537 199.687
278.932 268.446 272.746 276.481 277.957 280.209 283.296 285.986 285.484 283.677 281.706 282.601 278.721 274.759
materials…..............................................................
Other foods at home…...............................................
Sugar and sweets….................................................
Fats and oils….........................................................
Other foods…...........................................................
153.4
173.3
176.8
172.9
188.2
160.045
184.166
186.577
196.751
198.103
115.1
119.924 117.321 118.500 118.744 118.453 120.510 121.033 121.144 122.699 123.543 123.791 124.012 122.580 122.402
206.7
144.1
207.0
209.6
240.6
234.7
215.769
150.640
214.484
216.264
246.666
243.271
1
1,2
Other miscellaneous foods
……….…………………
1
Food away from home ……….…………………………………
1,2
Other food away from home ……….……………………
Alcoholic beverages…..................................................
Housing..........................................................................
Shelter...............….......................................................
Rent of primary residence…......................................
Lodging away from home……………………………… 142.8
3
Owners' equivalent rent of primary residence ……….
1,2
Tenants' and household insurance ……….……………
Fuels and utilities…...................................................
Fuels...............…......................................................
Fuel oil and other fuels….......................................
Gas (piped) and electricity…..................................
Household furnishings and operations…...................
Apparel ..........................................................................
Men's and boys' apparel….........................................
Women's and girls' apparel…....................................
1
Infants' and toddlers' apparel ……….………………………
Footwear…................................................................
Transportation................................................................
Private transportation...............…................................
2
New and used motor vehicles ……….……………………
New vehicles…........................................................
1
Used cars and trucks ……….………………………………
Motor fuel…...............................................................
Gasoline (all types)…...............................................
Motor vehicle parts and equipment…........................
Motor vehicle maintenance and repair…...................
Public transportation...............…..................................
Medical care...................................................................
Medical care commodities...............….........................
Medical care services...............…................................
Professional services….............................................
Hospital and related services….................................
2
Tuition, other school fees, and child care….............
1,2
1,4
other than telephone services ……….……………
212.537
148.564
212.407
214.389
245.995
240.874
159.730
181.806
184.878
190.640
195.993
213.083
148.667
213.503
214.890
246.004
241.474
158.336
182.680
185.097
193.364
196.787
213.967
149.666
213.532
215.809
246.069
241.803
158.320
183.804
185.558
196.150
197.888
215.015
149.873
213.912
217.941
247.083
242.640
159.346
185.725
187.067
201.205
199.566
216.376
151.120
214.394
219.610
248.075
243.367
160.055
186.991
187.813
203.059
200.961
217.063
151.133
215.094
219.148
247.985
244.181
161.499
187.944
189.929
206.274
201.388
218.225
152.040
216.055
218.184
247.737
244.926
163.727
189.348
190.515
208.300
202.993
219.290
153.544
216.972
217.383
247.844
245.855
163.015
189.301
191.756
205.806
203.058
220.043
153.978
217.492
216.467
247.463
246.681
162.750
190.203
193.312
206.710
203.902
220.684
154.062
217.975
216.073
247.085
247.278
164.882
192.492
197.429
206.886
206.343
221.319
153.402
219.113
216.928
248.292
247.974
164.213
192.404
196.676
205.359
206.621
221.968
154.726
219.682
217.180
248.878
248.305
165.656
192.234
197.137
204.776
206.367
222.216
154.414
219.999
217.374
249.597
248.639
143.664 149.434 146.378 145.634 148.621 153.032 149.146 143.597 141.140 133.555 129.157 133.559 135.809 137.715
246.2
252.426 250.966 251.418 251.576 252.170 252.504 252.957 253.493 253.902 254.669 254.875 255.500 255.779 256.321
117.0
200.6
181.7
251.5
186.3
126.9
119.0
112.4
110.3
118.843
220.018
200.808
334.405
202.212
127.800
118.907
113.032
107.460
117.701
209.221
189.693
332.139
190.105
127.423
120.881
114.994
110.645
118.422
213.302
194.121
342.811
194.379
127.332
122.113
116.653
111.221
118.411
219.881
201.212
363.872
200.999
127.598
120.752
116.479
108.722
119.092
231.412
213.762
389.423
213.375
127.625
117.019
112.011
104.312
118.764
239.039
221.742
395.706
221.805
127.884
114.357
109.669
100.049
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
113.9
122.4
184.7
180.8
113.762
124.157
195.549
191.039
116.037
124.407
195.189
191.067
116.358
126.212
198.608
194.574
114.582
125.537
205.262
201.133
111.555
123.568
211.787
207.257
109.218
122.421
212.806
208.038
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
94.3
136.3
135.7
239.1
238.0
121.6
223.0
230.0
351.1
290.0
369.3
300.8
498.9
111.4
102.9
119.6
93.291
134.194
133.951
279.652
277.457
128.747
233.859
250.549
364.065
296.045
384.943
310.968
533.953
113.254
102.632
123.631
94.318
135.727
137.225
278.739
276.497
126.325
229.765
242.929
363.000
297.308
382.872
308.726
528.968
112.731
103.548
121.832
93.973
135.175
136.787
294.291
291.910
126.049
230.528
244.164
363.184
296.951
383.292
309.227
530.144
112.874
103.477
122.073
93.705
134.669
136.325
322.124
319.787
126.824
231.730
251.600
363.396
294.896
384.505
310.917
531.022
112.987
102.988
122.348
93.598
134.516
135.980
347.418
344.981
127.824
233.162
264.681
363.616
295.194
384.685
311.317
531.606
112.991
102.306
122.828
93.650
134.397
135.840
349.731
347.357
129.118
234.788
270.002
363.963
294.777
385.361
311.926
533.558
113.277
102.203
123.445
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
Recreation ……….………………………………………….………
1,2
Video and audio ……….………………………………………
2
Education and communication ……….………………………
2
Education ……….………………………………………….……… 171.4
Educational books and supplies…........................... 420.4
Communication ……….………………………………………
1,2
Information and information processing ……….……
1,2
Telephone services ……….……………………………
Information and information processing
158.089
178.238
182.214
182.808
192.597
494.1
83.4
181.277 177.407 177.754 177.994 178.385 179.229 183.184 186.148 186.669 186.733 186.916 187.175 187.256 187.298
450.187 439.906 442.160 442.770 443.309 444.382 458.989 462.787 463.825 462.694 464.544 468.432 469.996 472.185
522.098 511.013 511.887 512.579 513.743 516.264 527.230 536.082 537.606 537.906 538.309 538.765 538.878 538.813
84.185 83.502 83.670 83.929 84.394 84.840 84.701 84.524 84.535 84.601 84.737 84.928 84.945 84.922
80.7
98.2
81.352
100.451
80.752
99.031
80.921
99.494
81.080 81.513 81.965 81.815 81.635 81.652 81.723 81.886 82.030 82.052 82.022
99.879 100.677 101.339 101.301 101.311 101.407 101.538 101.688 101.880 101.895 101.991
10.6
10.061
10.246
10.170
10.118
10.071
10.087
10.012
9.901
9.874
9.867
9.906
9.919
9.926
9.872
Personal computers and peripheral
1,2
equipment ……….…………………………………… 108.4
Other goods and services.............................................. 333.3
Tobacco and smoking products...............…................ 554.2
94.944 100.359 98.853 97.028 95.663 94.711 92.921 90.797 89.945 88.984 88.529 88.522 87.696 86.213
345.381 341.827 343.410 344.709 345.885 346.810 346.990 348.166 349.276 349.040 349.220 350.259 351.223 361.156
588.682 574.890 576.359 581.185 589.904 596.782 597.361 597.581 599.744 599.820 602.644 607.403 611.549 679.078
1
Personal care ……….………………………………………….… 195.6
1
Personal care products ……….…………………………… 158.3
1
Personal care services ……….…………………………… 216.6
201.279 199.982 201.028 201.523 201.537 201.545 201.623 202.486 203.107 202.921 202.774 203.080 203.391 204.117
159.290 158.440 159.398 158.790 158.868 158.989 159.252 159.643 159.826 161.000 161.397 162.588 162.508 162.696
223.669 222.752 222.799 223.649 223.520 223.719 224.151 224.614 225.564 226.197 226.281 225.734 225.895 227.982
See footnotes at end of table.
Monthly Labor Review • May 2009
121
Current Labor Statistics: Price Data
38. Continued—Consumer Price Indexes for All Urban Consumers and for Urban Wage Earners and Clerical Workers
U.S. city average, by expenditure category and commodity or service group
[1982–84 = 100, unless otherwise indicated]
Annual average
2007
2008
Mar.
Series
Miscellaneous personal services...............…....
Apr.
May
June
2008
July Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
2009
Feb.
Mar.
325.0 338.921 335.427 337.685 339.824 340.547 340.077 341.053 343.431 343.131 340.174 339.698 340.608 341.188 341.570
Commodity and service group:
Commodities...........…............................................
Food and beverages….........................................
Commodities less food and beverages….............
Nondurables less food and beverages…............
Apparel ….........................................................
Non durables less food, beverages,
and apparel….................................................
Durables…..........................................................
Services…..............................................................
3
Rent of shelter ……….……………………………………
Transportation services…....................................
Other services…..................................................
Special indexes:
All items less food…............................................
All items less shelter…........................................
All items less medical care…...............................
Commodities less food….....................................
Nondurables less food….....................................
Nondurables less food and apparel….................
Nondurables….....................................................
3
Services less rent of shelter ……….…………………
Services less medical care services…................
Energy…..............................................................
All items less energy…........................................
All items less food and energy….......................
Commodities less food and energy…..............
Energy commodities......................................
Services less energy…....................................
167.5 174.764 173.884 175.838 178.341 180.534 181.087 179.148 179.117 175.257 167.673 163.582 164.360 165.891 166.645
203.3
147.5
182.5
119.0
214.225
153.034
196.192
118.907
209.692
153.682
196.185
120.881
211.365
155.690
200.926
122.113
212.251
158.778
207.875
120.752
213.383
161.337
213.489
117.019
215.326
161.301
213.363
114.357
216.419
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
226.2 248.809 247.546 254.599 266.943 278.584 280.062 268.740 265.100 244.935 209.569 192.948 196.490 201.554 203.557
112.5
246.8
250.8
233.7
285.6
110.877
255.498
257.152
244.074
295.780
112.059
252.817
256.470
239.556
292.218
111.671
253.426
256.463
240.150
293.016
111.362
254.509
256.532
242.343
293.959
111.232
256.668
257.585
245.759
294.668
111.275
258.422
258.637
247.869
295.677
110.779
258.638
258.547
248.806
297.923
110.077
258.059
258.255
248.047
299.598
109.677
257.559
258.368
247.762
299.923
109.191
256.967
257.961
247.030
299.996
108.811
256.731
257.567
246.287
300.067
109.025
257.780
258.830
247.006
300.614
109.221
258.328
259.440
248.114
301.471
109.264
258.597
260.197
247.912
302.024
208.1 215.528 214.236 215.462 217.411 219.757 220.758 219.552 218.991 216.250 211.421 208.855 209.777 211.076 211.775
196.6
200.1
149.7
184.0
223.4
193.5
260.8
236.8
207.7
208.9
210.7
140.1
241.0
253.1
205.453
207.777
155.310
197.297
244.443
205.901
273.000
244.987
236.666
214.751
215.572
140.246
284.352
261.017
203.217
205.992
155.881
197.167
243.109
203.767
267.567
242.310
230.505
213.420
214.866
141.056
283.362
259.249
205.040
207.317
157.870
201.693
249.571
207.096
269.007
242.921
240.194
213.851
215.059
141.156
298.757
259.503
207.566
209.170
160.880
208.233
260.703
211.240
271.467
243.982
257.106
214.101
215.180
140.677
326.414
260.049
210.242
211.408
163.385
213.538
271.235
214.783
275.200
246.219
275.621
214.600
215.553
139.925
351.886
261.216
211.468
212.576
163.364
213.447
272.612
215.628
277.982
248.007
280.833
215.335
216.045
139.535
354.423
262.323
210.264
211.653
160.341
207.769
262.470
212.882
278.606
248.198
266.283
215.873
216.476
139.785
328.240
262.867
209.936
211.321
159.825
207.483
259.278
213.274
277.615
247.563
258.020
216.397
216.862
140.528
318.918
262.980
206.776
209.021
154.250
196.442
241.183
207.435
276.297
246.997
231.561
216.695
217.023
140.659
272.921
263.156
201.075
204.721
144.055
175.979
209.344
195.773
275.425
246.351
189.938
216.417
216.690
140.236
193.395
262.901
198.127
202.442
138.536
165.032
194.403
189.557
275.370
246.090
171.158
215.930
216.100
139.228
155.745
262.636
198.936
203.281
139.258
166.282
197.704
190.649
276.227
247.013
174.622
216.586
216.719
139.111
162.395
263.759
200.184
204.265
141.491
170.665
202.323
192.943
276.739
247.439
178.741
217.325
217.685
140.270
172.428
264.547
200.626
204.766
142.728
173.167
204.159
194.105
276.407
247.675
177.454
218.033
218.639
141.662
172.787
265.147
CONSUMER PRICE INDEX FOR URBAN
WAGE EARNERS AND CLERICAL WORKERS
All items....................................................................
202.8 211.053 209.147 210.698 212.788 215.223 216.304 215.247 214.935 212.182 207.296 204.813 205.700 206.708 207.218
All items (1967 = 100)...............................................
Food and beverages................................................
604.0
202.5
202.1
200.3
222.4
195.2
194.5
260.5
Food..................…..................................................
Food at home…....................................................
Cereals and bakery products…..........................
Meats, poultry, fish, and eggs….........................
1
Dairy and related products ……….…………………
Fruits and vegetables…......................................
Nonalcoholic beverages and beverage
materials….......................................................
Other foods at home….......................................
Sugar and sweets….........................................
Fats and oils…..................................................
Other foods…...................................................
1,2
Other miscellaneous foods ……….……………
1
Food away from home ……….……………………………
1,2
Other food away from home ……….………………
Alcoholic beverages…...........................................
Housing....................................................................
Shelter...............…................................................
Rent of primary residence…...............................
2
Lodging away from home ……….……………………
3
Owners' equivalent rent of primary residence …
1,2
Tenants' and household insurance ……….……
Fuels and utilities…...........................................
Fuels...............…..............................................
Fuel oil and other fuels…................................
Gas (piped) and electricity…..........................
Household furnishings and operations…............
Apparel ...................................................................
Men's and boys' apparel….................................
Women's and girls' apparel….............................
1
Infants' and toddlers' apparel ……….………………
Footwear….........................................................
Transportation..........................................................
Private transportation...............….........................
2
New and used motor vehicles ……….………………
See footnotes at end of table.
122
Monthly Labor Review • May 2009
628.661
213.546
213.376
213.017
245.472
204.255
209.773
276.759
622.985
208.927
208.571
207.196
236.764
199.484
205.660
266.030
627.606
210.559
210.252
209.657
240.663
200.285
207.135
270.169
633.830
211.438
211.200
210.624
244.648
200.501
207.088
274.136
641.082
212.700
212.514
212.079
246.493
202.424
208.510
276.641
644.303
214.662
214.577
214.679
250.972
204.557
213.582
278.885
641.155
215.850
215.812
216.214
250.842
207.211
214.139
282.171
640.226
217.098
217.090
217.594
251.448
209.515
212.841
284.612
632.025
218.141
218.120
218.600
253.561
210.314
211.808
283.549
617.472
218.178
218.114
217.956
253.498
209.297
212.184
281.279
610.075
218.269
218.155
217.498
253.759
208.639
209.922
278.835
612.719
219.123
218.998
218.485
255.055
208.161
208.530
279.906
615.719
218.645
218.449
217.111
254.775
207.656
203.023
275.884
617.239
218.119
217.855
215.922
254.395
206.094
198.048
271.727
152.8 159.324 157.488 158.799 157.285 157.309 158.527 159.024 160.850 163.265 162.472 162.280 164.514 163.821 165.437
172.6
175.3
173.6
188.4
115.4
206.4
143.5
207.1
183.637
185.494
197.512
198.303
120.348
215.613
149.731
214.579
177.713
181.033
183.706
192.832
117.754
212.193
147.188
212.748
181.215
183.725
191.560
196.106
118.751
212.794
147.335
213.633
182.241
184.127
194.228
197.081
119.248
213.723
148.517
213.486
183.342
184.378
197.155
198.153
118.879
214.851
149.306
213.976
185.174
186.054
201.821
199.722
121.015
216.177
150.232
214.440
186.458
186.860
203.721
201.119
121.443
217.002
150.301
214.931
187.467
188.914
207.069
201.632
121.589
218.147
151.321
215.728
188.806
189.574
208.973
203.138
123.026
219.219
152.910
216.953
188.685
190.501
206.870
203.126
123.837
220.107
153.464
217.626
189.527
192.120
207.439
203.937
124.144
220.847
153.646
218.445
191.782
195.867
207.400
206.490
124.477
221.497
153.397
219.458
191.620
195.395
206.185
206.547
122.994
222.101
154.520
220.029
191.594
196.015
205.693
206.468
122.837
222.336
154.054
220.500
204.8
233.0
233.8
142.3
223.2
117.4
211.839
239.128
242.196
143.164
228.758
119.136
209.388
237.965
239.932
148.110
227.488
117.999
210.161
238.261
240.507
145.936
227.893
118.683
211.191
238.353
240.818
144.979
228.007
118.615
213.441
239.198
241.623
148.378
228.536
119.293
215.026
239.845
242.276
152.248
228.824
119.006
214.743
240.038
243.010
148.368
229.219
118.894
213.954
240.163
243.741
142.591
229.670
120.279
213.156
240.517
244.624
140.763
230.028
120.258
212.591
240.740
245.425
133.747
230.743
120.589
212.452
240.752
246.026
129.982
230.926
120.360
213.078
241.651
246.696
134.235
231.503
120.715
213.192
242.051
246.991
136.255
231.746
120.960
213.213
242.605
247.285
138.008
232.235
121.099
198.9
179.0
251.1
184.4
122.5
118.5
112.2
110.2
116.3
122.1
217.883
197.537
331.784
200.265
123.635
118.735
113.490
107.489
116.266
124.102
206.861
186.315
329.271
188.143
123.184
120.809
115.808
110.712
118.990
124.343
210.912
190.657
339.009
192.434
123.108
121.855
117.136
110.971
119.200
126.150
217.388
197.554
358.947
199.045
123.287
120.407
116.621
108.594
117.213
125.335
228.843
209.843
381.903
211.398
123.434
116.706
112.395
104.062
114.057
123.381
236.381
217.640
388.208
219.612
123.798
113.978
109.969
99.772
111.502
122.380
233.373
213.807
363.535
216.557
123.944
116.214
110.513
104.584
111.593
122.026
226.709
206.544
345.907
209.442
124.500
120.990
112.973
112.304
115.764
124.873
219.325
198.191
317.012
201.651
124.719
121.957
115.495
111.880
118.496
126.352
214.700
193.000
283.747
197.507
124.466
121.149
114.651
110.612
118.611
126.689
213.861
192.050
260.185
197.545
124.314
117.006
111.232
105.413
115.003
124.152
213.882
191.852
251.976
197.703
124.454
114.969
111.879
100.751
114.775
122.753
212.353
190.110
246.781
196.040
124.865
118.766
116.332
105.538
116.001
124.494
209.400
186.809
236.237
192.922
125.337
122.162
118.735
110.380
117.944
126.858
184.3 195.692 195.710 199.556 206.757 213.633 214.533 207.796 204.785 192.198 170.870 160.914 163.215 165.976 165.978
181.5 192.492 192.740 196.641 203.781 210.423 211.201 204.348 201.476 188.871 167.301 157.272 159.719 162.645 162.659
93.3
92.146 93.455 93.158 92.850 92.714 92.686 92.287 91.305 90.530 89.783 89.482 89.774 89.728 89.418
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
New vehicles…............................................
1
Used cars and trucks ……….……………………
Motor fuel…...................................................
Gasoline (all types)…..................................
Motor vehicle parts and equipment…............
Motor vehicle maintenance and repair….......
Public transportation...............….....................
Medical care.......................................................
Medical care commodities...............…............
Medical care services...............…...................
Professional services….................................
Hospital and related services….....................
2
Recreation ……….………………………………………
Video and audio
1,2
……….……………………………
2
Education and communication ……….……………
2
2008
2009
2008
Mar.
Apr.
May
June
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
137.4 135.338 136.910 136.456 135.933 135.728 135.556 134.540 133.504 133.351 133.380 133.317 134.490 135.248 135.744
136.6
239.9
238.9
121.4
225.5
228.5
134.731
280.817
278.728
128.776
236.353
247.865
138.070
279.975
277.842
126.330
232.344
240.729
137.616
295.618
293.349
126.032
232.983
241.966
137.145
323.495
321.291
126.742
234.221
249.310
136.790
348.762
346.459
127.750
235.550
261.779
136.639
351.124
348.888
128.997
237.324
266.259
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
350.9
282.6
370.1
303.2
493.7
364.208
287.970
386.317
313.446
530.193
363.069
289.254
384.149
311.259
524.534
363.356
288.796
384.753
311.757
526.495
363.462
286.825
385.769
313.294
527.230
363.628
287.033
385.911
313.618
527.948
363.942
286.562
386.560
314.235
529.798
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
108.6 110.143 109.742 109.775 109.876 109.905 110.198 110.698 110.904 110.947 110.826 110.487 110.630 111.257 111.436
102.6 102.654 103.525 103.414 102.958 102.306 102.267 102.643 102.819 102.267 101.974 101.810 101.488 101.857 102.153
116.3 119.827 118.155 118.462 118.737 119.264 119.852 120.809 121.439 121.569 121.636 121.819 122.025 122.092 122.087
Education ……….………………………………………
Educational books and supplies…..............
169.3 178.892 175.101 175.545 175.791 176.148 176.879 180.819 183.613 184.091 184.115 184.352 184.642 184.765 184.824
423.7 452.880 442.639 444.594 445.394 445.740 446.741 461.104 465.570 466.885 465.576 467.179 471.061 473.012 474.880
Tuition, other school fees, and child care…
477.6 504.163 493.546 494.711 495.384 496.449 498.598 509.241 517.389 518.726 518.938 519.500 519.987 520.159 520.146
85.8 86.807 86.016 86.244 86.496 87.017 87.490 87.369 87.224 87.226 87.300 87.444 87.599 87.640 87.615
1,2
Communication ……….……………………………
1,2
Information and information processing …
1,2
Telephone services ……….…………………
Information and information processing
other than telephone services
1,4
……….…
83.9
84.828
84.091
84.320
84.511
98.4 100.502
99.090
99.566
99.939 100.723 101.375 101.339 101.350 101.436 101.564 101.720 101.876 101.890 101.977
11.1
10.745
10.671
10.621
10.567
85.007
10.585
85.484
10.600
85.355
10.525
85.208
10.414
85.214
10.375
85.292
10.367
85.454
10.406
85.581
10.418
85.624
85.595
10.442
10.378
Personal computers and peripheral
1,2
equipment ……….………………………
Other goods and services..................................
Tobacco and smoking products...............…....
1
Personal care ……….…………………………………
108.2 94.863 100.265 98.820 97.010 95.766 94.691 92.931 90.722 89.690 88.631 88.176 88.178 87.622 86.004
344.0 357.906 353.351 354.887 356.523 358.419 359.961 360.102 361.125 362.354 362.550 362.986 364.333 365.522 380.208
555.5 591.100 576.910 578.296 583.296 592.248 599.180 599.823 600.293 602.533 602.881 605.662 610.503 615.012 682.115
193.6 199.170 197.803 198.859 199.367 199.404 199.495 199.501 200.284 200.930 201.036 200.918 201.209 201.426 202.099
1
158.3 159.410 158.730 159.585 158.993 159.052 159.237 159.345 159.730 159.914 160.994 161.295 162.683 162.543 162.516
1
216.8 223.978 223.043 223.088 223.922 223.838 223.994 224.464 224.910 225.800 226.433 226.578 225.951 226.088 228.201
326.1 340.533 336.476 338.851 341.212 341.921 341.763 342.974 345.175 344.622 342.853 342.530 343.022 343.443 344.021
Personal care products ……….…………………
Personal care services ……….…………………
Miscellaneous personal services...............…
Commodity and service group:
Commodities...........….......................................
Food and beverages…....................................
Commodities less food and beverages…........
Nondurables less food and beverages…......
Apparel …...................................................
169.6
202.5
150.9
189.5
118.5
177.618
213.546
157.481
205.279
118.735
176.727
208.927
158.156
205.166
120.809
178.900
210.559
160.488
210.558
121.855
181.837
211.438
164.188
218.794
120.407
184.495
212.700
167.344
225.585
116.706
185.105
214.662
167.376
225.595
113.978
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
Nondurables less food, beverages,
and apparel…............................................
Durables…....................................................
Services….........................................................
3
Rent of shelter ……….………………………………
Transporatation services…............................
Other services….............................................
237.9 263.756 262.252 270.496 285.024 298.593 300.341 287.124 283.056 259.204 217.500 198.108 202.400 208.255 211.287
112.6 111.217 112.549 112.171 111.845 111.769 111.820 111.357 110.451 109.782 109.038 108.576 108.689 108.592 108.413
241.7 250.272 247.197 248.045 249.175 251.365 252.991 253.304 252.861 252.369 252.144 252.176 253.033 253.456 253.591
224.6 230.555 229.443 229.719 229.810 230.620 231.255 231.445 231.541 231.885 232.096 232.112 232.981 233.365 233.903
233.4 242.563 238.496 239.044 240.728 243.395 245.005 246.041 245.722 246.003 246.126 245.881 246.931 248.029 247.862
275.2 284.319 281.017 281.829 282.720 283.449 284.449 286.389 287.792 287.898 288.082 288.227 288.627 289.432 290.043
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.
202.7
193.9
196.6
152.9
190.7
234.2
196.8
210.452
203.102
204.626
159.538
206.047
258.423
210.333
209.055
200.904
202.713
160.152
205.843
256.899
208.101
210.583
202.931
204.290
162.455
211.005
264.488
211.757
212.870
205.774
206.423
166.070
218.809
277.717
216.582
215.498
208.817
208.906
169.169
225.276
290.127
220.813
216.407
210.069
210.002
169.213
225.309
291.760
221.740
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
230.9
232.2
208.1
203.0
203.6
140.6
241.3
247.9
241.567
240.275
237.414
208.719
208.147
141.084
284.270
255.598
236.483
237.201
231.533
207.296
207.406
141.973
283.359
253.589
237.922
238.048
241.518
207.812
207.687
142.040
298.852
254.031
240.181
239.167
258.903
208.021
207.747
141.558
326.565
254.517
243.780
241.422
277.597
208.458
208.007
140.878
351.873
255.513
246.411
243.071
282.579
209.062
208.317
140.492
354.402
256.365
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
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 • May 2009
123
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
2008
schedule1
U.S. city average……………………………………………
Oct.
Nov.
Urban Wage Earners
2009
Dec.
Jan.
Feb.
2008
Mar.
Oct.
Nov.
2009
Dec.
Jan.
Feb.
Mar.
M
216.573 212.425 210.228 211.143 212.193 212.709 212.182 207.296 204.813 205.700 206.708 207.218
Northeast urban ……….………………………………………….………
M
230.837 227.236 225.091 225.436 226.754 227.309 227.762 223.741 221.446 221.704 222.945 223.626
Size A—More than 1,500,000...........................................
M
233.165 229.625 227.681 227.852 229.262 229.749 228.437 224.621 222.628 222.707 224.084 224.597
M
136.730 134.445 132.830 133.308 133.967 134.411 137.489 134.757 132.938 133.345 133.908 134.558
M
206.019 201.737 199.582 200.815 201.453 202.021 201.236 196.346 193.987 195.245 195.813 196.453
M
207.049 202.922 200.465 202.001 202.639 203.240 201.323 196.770 194.120 195.621 196.147 196.855
M
131.946 129.018 128.018 128.636 129.057 129.334 131.699 128.186 127.005 127.768 128.167 128.468
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
202.086 197.883 195.383 195.843 196.421 197.267 200.017 195.114 192.391 192.907 193.527 194.393
South urban…….…..............................................................
M
210.108 205.559 203.501 204.288 205.343 206.001 207.312 201.821 199.399 200.067 201.150 201.737
Size A—More than 1,500,000...........................................
M
212.617 208.644 206.414 207.035 207.929 208.529 210.663 205.753 203.121 203.519 204.501 205.066
M
133.285 130.324 129.099 129.615 130.380 130.873 132.017 128.504 127.055 127.529 128.276 128.686
3
Size B/C—50,000 to 1,500,000 ……….…………………………
Size D—Nonmetropolitan (less than 50,000)………….....
M
213.103 206.659 204.428 205.766 206.671 206.927 213.696 205.777 203.054 204.316 205.337 205.744
West urban…….…...............................................................
M
221.034 217.113 214.685 215.923 217.095 217.357 215.499 210.870 208.088 209.367 210.492 210.661
Size A—More than 1,500,000...........................................
M
224.967 220.925 218.698 219.806 220.955 221.124 217.714 213.143 210.637 211.857 212.890 212.965
M
133.795 131.440 129.725 130.682 131.636 131.775 133.694 130.684 128.641 129.639 130.649 130.674
M
M
M
198.148 194.628 192.646 193.412 194.354 194.750 196.590 192.508 190.272 191.023 191.927 192.327
133.587 130.857 129.519 130.135 130.855 131.230 133.026 129.723 128.157 128.783 129.488 129.833
209.755 204.856 202.359 203.409 203.999 204.672 208.028 202.041 199.228 200.057 200.681 201.485
Chicago–Gary–Kenosha, IL–IN–WI…………………………..
Los Angeles–Riverside–Orange County, CA……….…………
M
M
213.363 209.053 205.959 207.616 207.367 207.462 206.772 202.022 198.434 200.222 199.944 200.218
226.159 222.229 219.620 220.719 221.439 221.376 218.726 214.083 211.007 212.454 213.234 213.013
New York, NY–Northern NJ–Long Island, NY–NJ–CT–PA…
M
238.403 234.498 233.012 233.402 234.663 235.067 232.778 228.727 227.223 227.503 228.653 229.064
Boston–Brockton–Nashua, MA–NH–ME–CT……….…………
1
– 232.354
– 230.806
– 232.155
– 231.854
– 230.095
– 231.884
Cleveland–Akron, OH……………………………………………
1
– 198.187
– 198.232
– 199.457
– 188.860
– 188.798
– 190.107
Dallas–Ft Worth, TX…….………………………………………
1
– 200.051
– 198.623
– 200.039
– 201.479
– 199.416
– 200.770
Washington–Baltimore, DC–MD–VA–WV ……….……………
1
– 138.547
– 137.598
– 138.620
– 137.700
– 136.359
– 137.539
Atlanta, GA……………………..…………………………………
2
206.388
– 196.961
– 199.190
– 205.236
– 195.310
– 197.528
–
Detroit–Ann Arbor–Flint, MI……………………………………
2
205.238
– 197.991
– 201.913
– 200.570
– 192.808
– 196.191
–
Houston–Galveston–Brazoria, TX………………………………
2
191.140
– 185.930
– 187.972
– 190.600
– 183.088
– 185.015
–
Miami–Ft. Lauderdale, FL……………...………………………
2
223.699
– 218.324
– 220.589
– 222.038
– 215.867
– 217.635
–
Philadelphia–Wilmington–Atlantic City, PA–NJ–DE–MD……
2
225.113
– 218.186
– 220.262
– 225.069
– 217.610
– 219.356
–
San Francisco–Oakland–San Jose, CA…….…………………
2
225.824
– 218.528
– 222.166
– 221.192
– 213.685
– 216.797
–
Seattle–Tacoma–Bremerton, WA………………...……………
2
225.915
– 222.580
– 224.737
– 220.687
– 216.424
– 218.752
–
3
Size B/C—50,000 to 1,500,000 ……….…………………………
Size classes:
5
A ……….………………………………………….…………..……………
3
B/C ……………………….….………………………………………….…
D…………….…………......................................................
Selected local areas 6
7
1
Foods, fuels, and several other items priced every month in all areas; most other
goods and services priced as indicated:
M—Every month.
1—January, March, May, July, September, and November.
2—February, April, June, August, October, and December.
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
124
Monthly Labor Review • May 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 • May 2009
125
Current Labor Statistics: Price Data
41. Producer Price Indexes, by stage of processing
[1982 = 100]
Annual average
2008
Grouping
2007
Finished goods....……………………………
Finished consumer goods.........................
Finished consumer foods........................
2008
Mar.
Apr.
May
June
July
Aug.
2009
Sept.
Oct.
Nov.
Dec.p Jan.p Feb.p Mar.p
166.6
173.5
167.0
177.1
186.3
178.4
175.1
184.2
176.0
176.5
185.8
175.5
179.8
190.3
177.6
182.4
193.8
180.0
185.1
197.2
181.0
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
173.8
178.5
170.3
175.7
177.6
170.1
175.4
174.9
168.9
173.9
174.0
excluding foods.....................................
Nondurable goods less food.................
Durable goods......................................
Capital equipment...................................
175.6
191.7
138.3
149.5
189.0
210.5
141.1
153.7
187.1
208.2
139.9
151.8
189.6
211.7
140.5
152.4
195.0
220.0
140.3
152.7
199.0
226.4
139.7
152.7
203.4
233.1
139.6
153.3
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
171.4
182.3
143.9
156.7
174.2
186.1
144.4
157.5
174.7
186.9
144.4
157.4
173.1
184.6
144.2
157.0
Intermediate materials,
supplies, and components........…………
170.7
188.6
184.5
187.3
192.8
197.2
203.1
199.4
198.6
189.0
179.2
172.7
171.6
169.8
168.1
162.4
161.4
184.0
189.8
136.3
177.6
180.6
215.5
203.4
140.3
173.1
180.0
206.0
200.3
137.9
175.5
180.3
209.5
205.6
138.6
179.1
182.7
215.9
211.9
139.4
182.4
185.4
222.8
215.4
140.1
187.4
187.6
234.8
219.2
141.3
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
164.6
171.9
188.1
177.7
142.0
162.9
167.3
188.3
171.6
141.7
161.2
164.1
186.7
167.1
141.6
160.2
163.6
184.8
166.0
141.2
for construction.........................................
Processed fuels and lubricants...................
Containers..................................................
Supplies......................................................
192.5
173.9
180.3
161.7
205.4
206.4
191.9
174.1
197.3
206.1
185.9
170.0
200.2
211.8
187.0
171.3
203.3
227.3
187.6
173.1
206.5
238.4
189.2
174.6
209.8
250.1
191.9
178.3
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
207.6
154.1
198.1
174.0
206.2
154.3
198.0
173.2
204.9
150.1
199.3
172.5
204.2
145.0
198.4
172.0
Crude materials for further
processing.......................…………………
Foodstuffs and feedstuffs...........................
Crude nonfood materials............................
207.1
146.7
246.3
251.7
163.5
313.5
262.1
169.2
327.7
274.6
168.1
352.4
293.1
173.2
382.4
301.2
178.1
393.0
313.3
178.9
414.9
274.6
170.6
350.0
254.2
167.6
314.2
212.0
147.9
253.9
183.3
144.2
203.2
171.7
135.9
189.5
166.9
136.7
179.8
160.3
133.1
170.9
159.9
130.5
172.7
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
176.5
178.6
169.8
176.9
167.2
174.6
177.5
167.6
174.7
165.1
176.4
182.4
168.0
174.9
165.7
180.1
194.8
168.8
175.9
166.1
182.8
204.6
169.4
176.8
166.0
185.9
214.0
170.2
177.7
166.7
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
165.8
130.6
172.3
179.2
170.5
167.9
135.9
172.6
179.3
171.3
168.2
136.4
172.3
178.7
171.6
167.0
132.4
171.9
178.5
171.4
and energy................................................
Consumer nondurable goods less food
170.0
176.3
174.1
174.8
175.2
175.2
175.9
176.6
177.2
180.2
180.0
180.0
180.7
181.2
181.4
and energy..............................................
197.0
206.9
203.6
204.3
205.4
206.0
207.6
208.5
209.7
210.7
210.9
211.2
212.1
213.3
213.8
171.5
154.4
174.6
167.6
189.0
182.2
208.3
181.2
184.7
180.3
208.6
176.0
187.7
180.5
213.4
178.4
193.3
184.5
228.7
181.4
197.8
186.6
240.3
183.9
203.6
195.5
253.5
187.9
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
172.8
170.2
150.6
176.0
172.0
166.9
153.2
174.0
170.1
164.7
148.7
172.8
168.4
164.0
142.6
172.3
and energy................................................
168.4
181.2
175.8
178.3
181.2
183.8
187.5
188.7
188.8
184.8
180.2
176.4
174.6
173.6
173.0
Crude energy materials..............................
Crude materials less energy.......................
Crude nonfood materials less energy.........
232.8
182.6
282.6
308.5
205.7
325.4
325.4
211.7
332.1
346.1
218.5
366.7
386.1
223.9
372.4
400.4
228.2
373.8
426.5
231.7
386.1
339.1
222.3
374.2
303.7
211.7
337.5
244.4
182.0
276.7
194.9
167.6
224.8
178.4
159.9
220.7
165.0
160.9
221.7
151.0
158.6
225.3
153.8
155.7
221.7
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.
126
Monthly Labor Review • May 2009
42. Producer Price Indexes for the net output of major industry groups
[December 2003 = 100, unless otherwise indicated]
NAICS
2008
Industry
Mar.
Apr.
May
June
July
Aug.
2009
Sept.
Oct.
Nov.
Dec. p Jan.p
Feb.p Mar. p
Total mining industries (December 1984=100).............................
Oil and gas extraction (December 1985=100) .............................
Mining, except oil and gas……………………………………………
Mining support activities………………………………………………
287.2
371.6
174.8
169.8
301.6
390.8
186.1
170.1
329.0
436.2
184.7
172.2
341.4
456.0
185.8
173.1
363.8
490.4
191.8
175.9
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
171.5
177.9
175.2
177.1
164.1
165.7
175.4
175.9
155.0
150.3
179.9
167.9
157.2
152.9
181.6
168.2
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
173.4
169.8
112.7
110.4
102.0
152.6
105.9
119.6
108.2
337.1
175.3
171.2
112.9
110.6
102.2
152.7
106.2
120.2
109.0
347.7
179.4
174.0
114.2
111.4
102.2
152.4
108.2
120.5
109.2
384.1
182.0
176.1
114.1
111.7
102.1
153.4
109.2
120.9
109.5
406.0
185.6
180.3
115.0
112.6
102.3
153.8
108.9
121.8
109.8
429.6
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
164.2
172.2
115.8
113.4
102.8
154.7
105.9
127.1
110.2
169.1
164.7
170.0
117.8
113.9
103.2
155.2
104.9
126.4
109.9
180.7
164.2
168.7
119.4
113.0
103.8
155.1
104.0
126.2
109.6
177.9
163.0
167.7
120.3
112.7
103.8
155.0
103.0
125.6
109.4
166.6
325
326
(December 1984=100)………………………………….…………
Chemical manufacturing (December 1984=100)…………………… 218.4
156.4
Plastics and rubber products manufacturing
221.1
156.8
224.5
158.3
228.5
159.4
234.5
162.9
238.2
165.2
240.4
166.9
239.3
167.8
234.5
166.9
230.1
165.1
225.7
162.9
227.1
161.3
226.9
160.6
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
202.4
168.3
114.6
92.7
127.1
106.1
168.3
211.5
171.1
115.1
92.7
127.3
106.7
169.5
221.1
173.0
115.8
92.8
127.8
106.6
170.2
227.8
174.7
116.4
92.8
128.2
105.9
171.3
232.7
177.2
117.9
92.8
129.1
105.9
172.3
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
184.7
178.4
119.5
92.7
126.5
109.5
175.2
176.4
178.1
120.7
92.9
126.2
109.8
175.9
170.5
177.5
120.6
92.7
126.8
110.2
176.3
169.1
176.6
120.5
92.3
126.9
109.5
176.9
339
Miscellaneous manufacturing………………………………………… 109.2
109.3
109.4
109.9
110.8
110.5
110.4
110.6
110.4
110.7
112.2
111.5
111.6
117.9
120.1
113.4
125.5
60.6
133.1
118.9
119.4
119.7
127.2
65.7
136.4
118.3
120.2
118.7
127.3
59.3
136.5
118.1
119.6
105.8
127.8
67.6
141.8
118.4
120.3
106.5
133.8
77.2
140.6
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
117.7
121.8
112.8
136.8
66.6
150.4
117.4
121.1
112.7
135.3
67.1
152.0
116.4
121.0
107.1
137.5
71.0
152.7
117.2
120.7
102.4
137.9
62.4
159.0
Air transportation (December 1992=100)…………………………… 198.6
Water transportation…………………………………………………… 120.6
Postal service (June 1989=100)……………………………………… 175.5
199.5
121.1
175.5
203.7
124.7
180.5
213.5
127.0
180.5
213.6
130.4
180.5
213.0
133.7
180.5
208.6
135.1
180.5
209.3
135.0
180.5
203.8
130.6
180.5
198.0
129.5
180.5
197.8
126.6
180.5
189.3
120.6
181.6
184.9
117.5
181.6
134.5
137.0
141.7
146.8
145.7
140.8
136.0
133.4
134.4
133.1
132.6
130.2
123.3
107.3
125.5
162.9
118.3
117.7
123.2
107.3
125.4
162.7
118.5
118.2
123.2
106.9
125.4
162.7
118.6
118.5
123.2
106.9
125.4
162.6
118.6
118.5
123.5
106.9
125.6
163.2
119.4
118.6
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
107.9
127.1
164.3
120.7
118.9
124.6
108.0
127.4
165.2
121.7
119.2
125.5
108.3
127.6
166.2
122.1
119.8
125.7
108.4
127.4
166.4
121.7
120.4
110.4
105.2
100.6
100.5
121.0
109.7
110.0
106.8
125.1
160.7
113.8
110.9
106.4
101.0
100.4
119.6
109.5
110.2
107.3
120.3
161.1
112.7
110.7
105.5
101.3
100.8
119.6
110.5
106.9
108.3
122.0
160.9
114.0
110.4
104.4
101.1
100.8
120.2
110.4
106.9
108.2
125.4
161.1
112.7
111.0
103.9
101.0
100.9
119.1
110.9
106.8
109.2
136.7
161.5
115.3
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
109.1
100.9
100.9
112.3
111.6
103.2
108.7
124.1
163.1
115.7
111.9
107.0
101.2
100.6
113.4
113.8
98.6
108.5
129.6
164.2
115.1
111.9
108.6
101.1
100.7
112.4
108.5
101.6
110.2
133.1
164.6
115.1
111.4
109.3
101.0
100.8
108.4
110.1
101.6
110.8
133.0
166.0
115.3
140.3
105.3
123.0
98.8
108.9
112.0
145.3
140.5
105.7
122.9
98.8
108.9
112.2
145.6
140.5
106.3
122.7
98.8
109.0
111.9
144.9
141.3
106.3
122.8
98.8
109.1
112.6
147.0
141.6
106.3
123.0
98.8
109.0
112.3
149.9
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
142.1
106.3
124.2
101.4
108.8
110.2
144.3
142.0
104.9
123.3
101.4
109.8
113.6
142.4
142.3
105.2
124.1
101.4
109.7
114.3
139.7
142.3
105.3
123.2
102.6
109.5
116.4
142.3
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…………………………………………………………………… 131.1
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 • May 2009
127
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
178.4
178.6
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
188.6
180.6
208.3
181.2
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
251.7
163.5
308.5
309.0
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]
2008
Category
Mar.
Apr.
May
June
July
Aug.
2009
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
ALL COMMODITIES……………....................................
123.8
124.4
124.8
126.1
128.0
125.9
124.9
122.3
118.4
115.8
116.5
116.2
115.5
Foods, feeds, and beverages……………...……………
Agricultural foods, feeds, and beverages….............
Nonagricultural (fish, beverages) food products……
196.9
202.6
148.3
192.8
198.2
146.4
193.3
198.9
145.5
198.0
204.0
146.1
211.5
218.9
147.0
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
165.7
167.9
147.9
162.5
164.6
145.5
156.9
158.6
143.7
Industrial supplies and materials……………...………… 165.5
167.9
169.6
173.2
177.8
174.0
169.4
161.8
148.2
139.6
138.6
137.8
136.5
Agricultural industrial supplies and materials…........
159.3
157.9
156.9
158.0
162.8
160.9
157.4
148.5
134.2
126.1
125.6
126.6
123.5
Fuels and lubricants…...............................…………
249.5
259.3
275.8
297.2
312.3
275.8
267.2
239.2
193.4
166.8
165.5
159.1
150.9
Nonagricultural supplies and materials,
excluding fuel and building materials…………...…
Selected building materials…...............................…
158.2
114.2
160.1
114.1
160.1
113.9
161.6
113.8
165.1
114.5
165.3
115.2
160.8
115.4
155.5
116.6
145.6
115.6
138.8
115.1
137.8
115.5
137.6
115.8
137.4
114.8
Capital goods……………...…………………………….… 101.2
Electric and electrical generating equipment…........ 108.6
Nonelectrical machinery…...............................……… 93.7
101.5
108.7
93.9
101.6
108.6
93.9
102.0
108.9
94.2
101.9
109.3
94.0
101.9
109.2
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
101.9
107.8
93.4
102.2
107.7
93.8
102.2
107.8
93.5
Automotive vehicles, parts, and engines……………...
128
107.1
107.5
107.5
107.4
107.7
107.8
107.9
108.2
108.1
108.0
108.4
108.1
108.3
Consumer goods, excluding automotive……………... 108.0
Nondurables, manufactured…...............................… 109.3
Durables, manufactured…………...………..........…… 105.4
108.1
109.8
105.1
108.1
110.0
105.1
108.2
110.1
105.2
108.5
109.8
106.0
109.0
109.6
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
108.7
109.7
109.0
109.0
109.5
108.5
108.1
109.4
Agricultural commodities……………...…………………
Nonagricultural commodities……………...……………
190.5
119.6
190.8
120.1
195.2
121.2
208.2
122.3
188.2
121.5
188.3
120.4
172.5
118.7
160.6
115.4
150.8
113.2
160.0
113.3
157.4
113.2
151.9
112.9
Monthly Labor Review • May 2009
194.3
118.8
45. U.S. import price indexes by end-use category
[2000 = 100]
2008
Category
Mar.
Apr.
May
June
July
2009
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
ALL COMMODITIES……………....................................
133.5
137.3
141.2
145.5
147.5
143.0
137.8
129.6
120.0
114.5
113.1
113.0
113.6
Foods, feeds, and beverages……………...……………
Agricultural foods, feeds, and beverages….............
Nonagricultural (fish, beverages) food products……
141.8
157.3
106.8
143.7
159.8
107.2
145.0
162.2
105.9
147.7
165.1
108.4
149.7
167.6
109.1
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
142.4
159.2
104.4
137.8
153.1
103.2
136.4
150.6
104.5
Industrial supplies and materials……………...………… 234.5
248.7
265.0
283.0
290.7
270.7
248.9
213.5
174.6
150.4
143.7
144.7
149.0
Fuels and lubricants…...............................…………
Petroleum and petroleum products…………...……
329.0
347.5
354.6
375.8
388.3
412.2
423.7
450.3
437.6
465.0
392.0
419.5
346.3
371.5
274.1
288.9
197.8
201.6
153.9
150.8
146.4
143.4
150.1
150.8
160.8
166.7
Paper and paper base stocks…...............................
114.1
116.2
117.1
117.3
118.9
119.7
119.9
116.4
115.1
113.2
110.3
108.5
105.9
Materials associated with nondurable
supplies and materials…...............................………
Selected building materials…...............................…
Unfinished metals associated with durable goods…
Nonmetals associated with durable goods…...........
147.8
114.1
241.5
105.2
148.7
114.3
259.2
106.2
149.6
116.2
263.6
107.3
152.9
119.2
273.2
107.6
157.4
121.3
273.4
110.7
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
138.9
117.1
176.6
106.8
136.9
116.4
175.8
106.0
137.4
115.9
172.6
104.8
Capital goods……………...…………………………….… 92.2
Electric and electrical generating equipment…........
109.3
Nonelectrical machinery…...............................……… 87.5
93.0
111.5
88.0
93.3
111.7
88.4
93.2
112.0
88.2
93.4
112.7
88.4
93.4
113.0
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
110.2
87.1
92.0
109.8
86.8
Automotive vehicles, parts, and engines……………...
107.4
107.8
107.8
107.9
108.1
108.3
108.1
108.3
107.9
107.8
108.0
108.2
108.0
Consumer goods, excluding automotive……………...
Nondurables, manufactured…...............................…
Durables, manufactured…………...………..........……
Nonmanufactured consumer goods…………...………
104.0
107.5
100.4
104.3
104.6
107.9
101.1
105.6
104.8
108.0
101.3
105.8
104.9
107.9
101.5
106.6
105.1
108.2
101.7
106.7
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
100.2
102.7
104.5
109.0
100.0
104.4
104.0
108.5
99.7
101.3
46. U.S. international price Indexes for selected categories of services
[2000 = 100, unless indicated otherwise]
2007
Category
Mar.
June
2008
Sept.
Dec.
Mar.
June
2009
Sept.
Dec.
Mar.
Import air freight……………...........................................
Export air freight……………...……………………………
130.7
117.0
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
132.8
122.8
Import air passenger fares (Dec. 2006 = 100)……………
Export air passenger fares (Dec. 2006 = 100)…............
122.9
140.2
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
140.0
Monthly Labor Review • May 2009
129
Current Labor Statistics: Productivity Data
47. Indexes of productivity, hourly compensation, and unit costs, quarterly data seasonally adjusted
[1992 = 100]
2006
Item
I
II
2007
III
IV
I
II
2008
III
IV
I
II
2009
III
IV
I
Business
Output per hour of all persons........................................
Compensation per hour…………………………….………
Real compensation per hour………………………………
Unit labor costs…...............................……………………
Unit nonlabor payments…………...………..........………
Implicit price deflator………………………………………
135.9
167.8
120.4
123.5
133.4
127.2
136.5
168.1
119.6
123.1
136.3
128.0
136.0
169.0
119.2
124.3
136.3
128.8
135.9
172.6
122.1
127.0
133.3
129.4
135.7
174.3
122.1
128.5
134.3
130.7
137.5
175.4
121.6
127.5
137.5
131.2
140.0
177.4
122.3
126.7
139.8
131.6
139.6
178.9
121.6
128.2
139.0
132.2
140.4
180.5
121.3
128.6
140.2
132.9
142.0
181.3
120.6
127.7
142.4
133.2
142.8
183.9
120.4
128.8
144.3
134.6
142.6
186.1
124.6
130.5
141.4
134.6
143.0
187.9
126.6
131.4
142.0
135.4
134.8
166.5
119.5
123.5
135.5
127.9
135.6
167.0
118.9
123.1
138.6
128.8
135.1
168.0
118.5
124.3
138.4
129.5
134.9
171.7
121.4
127.2
134.7
130.0
134.7
173.4
121.5
128.7
135.1
131.1
136.3
174.0
120.6
127.6
138.3
131.5
138.7
175.8
121.2
126.8
140.5
131.8
138.5
177.8
120.8
128.4
139.7
132.5
139.4
179.4
120.6
128.7
141.0
133.2
141.0
180.2
119.8
127.8
143.3
133.5
141.7
182.7
119.7
128.9
145.6
135.0
141.5
185.0
123.9
130.7
143.0
135.2
141.8
186.9
125.9
131.8
143.8
136.2
146.0
164.2
117.8
112.6
112.5
113.0
182.6
131.6
118.8
145.7
164.4
117.0
113.3
112.8
114.6
183.4
133.0
119.5
146.7
165.1
116.5
113.1
112.5
114.5
193.4
135.6
120.3
145.6
167.8
118.7
115.6
115.3
116.5
174.4
132.0
120.8
145.4
170.0
119.1
117.1
116.9
117.6
172.4
132.2
122.1
146.7
171.1
118.6
116.9
116.6
117.9
173.1
132.6
122.0
147.8
172.8
119.1
117.2
116.9
118.2
167.4
131.4
121.7
148.3
174.9
118.9
118.3
117.9
119.3
156.4
129.2
121.7
148.1
176.1
118.4
119.0
118.9
119.4
150.8
127.8
121.8
151.2
177.4
118.0
118.0
117.3
119.8
147.8
127.2
120.6
153.6
180.0
117.9
118.3
117.3
121.3
156.7
130.8
121.8
152.0
182.4
122.1
121.3
120.0
124.7
144.0
129.9
123.3
–
–
–
–
–
–
–
–
–
172.6
170.7
122.5
98.9
172.5
169.4
120.6
98.2
174.4
170.4
120.2
97.7
175.3
174.4
123.4
99.5
176.9
176.6
123.7
99.8
178.2
176.3
122.3
99.0
180.1
177.0
122.0
98.2
181.6
179.6
122.1
98.9
182.8
181.1
121.7
99.1
181.6
182.7
121.5
100.6
180.3
185.1
121.2
102.7
178.3
189.6
126.9
106.3
176.8
195.4
131.6
110.5
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.
130
Monthly Labor Review • May 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……………………… 104.7
Multifactor productivity……………………………………
95.3
Output…...............................………………………….……
82.8
Inputs:
Labor input...................................................................
Capital services…………...………..........………….……
Combined units of labor and capital input………………
Capital per hour of all persons.......................……………
90.7
79.1
86.9
85.9
91.7
104.9
96.2
87.2
94.3
103.5
97.5
91.5
97.2
102.3
98.7
96.2
100.0
100.0
100.0
100.0
102.8
96.0
100.1
100.5
107.1
94.8
101.8
102.0
111.2
95.6
104.4
105.2
114.5
97.5
107.0
109.7
116.8
98.6
108.8
113.8
118.0
99.1
109.4
117.4
120.2
98.1
110.1
120.1
–
–
–
–
94.2
83.2
90.6
87.4
96.4
88.4
93.9
91.1
99.0
94.1
97.5
95.0
100.0
100.0
100.0
100.0
98.6
104.6
100.3
107.0
97.2
107.6
100.2
112.9
97.0
110.0
100.7
116.3
98.4
112.5
102.5
117.4
100.2
115.4
104.6
118.4
102.8
118.5
107.4
119.1
103.8
122.3
109.2
122.3
–
–
–
–
–
Private nonfarm business
–
Productivity:
Output per hour of all persons........……………………… 90.5
Output per unit of capital services……………………… 105.5
Multifactor productivity……………………………………
95.9
Output…...............................………………………….……
82.8
92.0
105.3
96.5
87.2
94.5
103.9
97.8
91.5
97.3
102.5
98.8
96.3
100.0
100.0
100.0
100.0
102.7
96.0
100.1
100.5
107.1
94.7
101.8
102.1
111.0
95.4
104.3
105.2
114.2
97.3
106.8
109.6
116.4
98.3
108.6
113.7
117.6
98.7
109.0
117.4
119.7
97.9
109.7
120.1
–
–
–
–
–
90.2
78.5
86.4
85.8
93.9
82.7
90.3
87.3
96.2
88.1
93.6
91.0
99.0
93.9
97.4
94.9
100.0
100.0
100.0
100.0
98.7
104.7
100.5
107.0
97.2
107.8
100.2
113.1
97.1
110.3
100.8
116.4
98.6
112.7
102.6
117.4
100.4
115.6
104.7
118.4
103.1
118.9
107.6
119.1
104.1
122.8
109.4
122.4
–
–
–
–
–
Productivity:
Output per hour of all persons...…………………………
Output per unit of capital services………………………
Multifactor productivity……………………………………
Output…...............................………………………….……
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......…………………………
Manufacturing [1996 = 100]
NOTE: Dash indicates data not available.
Monthly Labor Review • May 2009
131
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
182.9
121.6
128.9
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
181.8
120.9
129.0
143.2
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
128.9
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
–
–
180.8
184.5
122.7
102.1
–
–
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.
132
Monthly Labor Review • May 2009
50. Annual indexes of output per hour for selected NAICS industries
[1997=100]
NAICS
Industry
1987
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
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………
85.3
80.1
80.1
69.3
57.8
71.0
88.0
79.4
79.4
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
103.5
101.2
101.2
104.5
106.5
108.9
101.2
96.0
96.0
111.4
107.9
107.9
105.8
110.3
112.3
101.2
98.5
98.5
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
100.0
100.0
103.7
99.0
103.5
102.7
107.0
113.2
106.4
110.1
102.9
115.4
105.1
114.1
107.5
118.3
114.3
122.2
115.4
119.1
113.3
119.7
94.1
83.6
81.1
87.6
92.4
100.0
100.0
100.0
100.0
100.0
103.9
109.0
107.5
103.5
107.1
105.9
110.9
116.1
106.5
109.5
107.1
109.7
113.1
109.9
111.8
109.5
131.4
119.5
108.6
121.4
113.8
142.7
122.4
108.0
126.9
116.8
165.8
123.9
112.5
123.0
117.3
149.5
130.3
118.2
126.2
123.3
165.5
133.0
130.7
132.0
121.1
150.4
130.7
129.2
126.9
-
3115
3116
3117
3118
3119
Dairy products…………………………………………… 82.7
Animal slaughtering and processing…………………
97.4
Seafood product preparation and packaging………. 123.1
Bakeries and tortilla manufacturing…………………… 100.9
Other food products……………………………………
97.5
100.0
100.0
100.0
100.0
100.0
100.0
100.0
120.2
103.8
107.8
93.6
101.2
131.6
108.6
111.4
95.9
102.6
140.5
108.3
112.6
97.1
103.7
153.0
109.9
106.2
105.0
107.3
169.8
108.9
111.9
110.5
106.6
173.2
109.3
118.8
107.4
108.0
162.2
113.8
119.3
109.6
117.4
186.1
115.4
116.2
110.2
116.9
203.8
110.5
116.3
-
312
3121
3122
313
3131
Beverages and tobacco products……………………
Beverages………………………………………………
Tobacco and tobacco products………………………
Textile mills………………………………………………
Fiber, yarn, and thread mills……………………………
78.1
77.1
71.9
73.7
66.5
100.0
100.0
100.0
100.0
100.0
97.6
99.0
98.5
102.6
102.1
87.3
90.7
91.0
106.2
103.9
88.3
90.8
95.9
106.7
101.3
89.5
92.7
98.2
109.5
109.1
82.6
99.4
67.0
125.3
133.3
90.9
108.3
78.7
136.1
148.8
94.7
114.1
82.4
138.6
154.1
100.5
120.3
93.1
152.8
143.5
94.0
112.0
94.9
150.5
139.7
-
3132
3133
314
3141
3149
Fabric mills………………………………………………
Textile and fabric finishing mills………………………
Textile product mills……………………………………
Textile furnishings mills…………………………………
Other textile product mills………………………………
68.0
91.3
93.0
91.2
92.2
100.0
100.0
100.0
100.0
100.0
104.2
101.2
98.7
99.3
96.7
110.0
102.2
102.5
99.1
107.6
110.1
104.4
107.1
104.5
108.9
110.3
108.5
104.5
103.1
103.1
125.4
119.8
107.3
105.5
105.1
137.3
125.1
112.7
114.4
104.2
138.6
127.7
123.4
122.3
120.4
164.2
139.8
128.0
125.7
128.9
170.5
126.2
121.1
117.3
126.1
-
315
3151
3152
3159
316
Apparel………………………………………………….
Apparel knitting mills……………………………………
Cut and sew apparel……………………………………
Accessories and other apparel………………………
Leather and allied products……………………………
71.9
76.2
69.8
97.8
71.6
100.0
100.0
100.0
100.0
100.0
101.8
96.1
102.3
109.0
106.6
111.7
101.4
114.6
99.3
112.7
116.8
108.9
119.8
98.3
120.3
116.5
105.6
119.5
105.2
122.4
102.9
112.0
103.9
76.1
97.7
112.4
105.6
117.2
78.7
99.8
103.4
96.6
108.4
70.8
109.5
110.9
120.0
113.5
74.0
123.6
114.0
123.7
117.6
67.3
132.5
-
3161
3162
3169
321
3211
Leather and hide tanning and finishing………………
Footwear…………………………………………………
Other leather products…………………………………
Wood products…………………………………………
Sawmills and wood preservation………………………
94.0
76.7
92.3
95.0
77.6
100.0
100.0
100.0
100.0
100.0
100.3
102.1
113.3
101.2
100.3
98.1
117.3
110.4
102.9
104.7
100.1
122.3
122.8
102.7
105.4
100.3
130.7
117.6
106.1
108.8
81.2
102.7
96.2
113.6
114.4
82.2
104.8
100.3
114.7
121.3
93.5
100.7
127.7
115.6
118.2
118.7
105.6
149.7
123.1
127.3
118.1
115.4
174.6
124.9
129.7
-
3212
3219
322
3221
3222
Plywood and engineered wood products……………
99.7
Other wood products…………………………………… 103.0
Paper and paper products……………………………
85.8
81.7
Pulp, paper, and paperboard mills……………………
Converted paper products……………………………
89.0
100.0
100.0
100.0
100.0
100.0
105.1
101.0
102.3
102.5
102.5
98.7
104.5
104.1
111.1
100.1
98.8
103.0
106.3
116.3
101.1
105.2
104.7
106.8
119.9
100.5
110.3
113.9
114.2
133.1
105.6
107.0
113.9
118.9
141.4
109.6
102.9
119.6
123.4
148.0
112.9
110.2
126.3
124.5
147.7
114.8
117.4
125.3
127.3
151.1
116.6
-
323
3231
324
3241
325
Printing and related support activities…………………
Printing and related support activities…………………
Petroleum and coal products…………………………
Petroleum and coal products…………………………
Chemicals………………………………………………
97.6
97.6
71.1
71.1
85.9
100.0
100.0
100.0
100.0
100.0
100.6
100.6
102.2
102.2
99.9
102.8
102.8
107.1
107.1
103.5
104.6
104.6
113.5
113.5
106.6
105.3
105.3
112.1
112.1
105.3
110.2
110.2
118.0
118.0
114.2
111.1
111.1
119.2
119.2
118.4
114.5
114.5
123.4
123.4
125.8
119.5
119.5
123.8
123.8
134.1
121.1
121.1
122.8
122.8
137.5
-
3251
3252
3253
3254
3255
Basic chemicals…………………………………………
Resin, rubber, and artificial fibers……………………
Agricultural chemicals…………………………………
Pharmaceuticals and medicines………………………
Paints, coatings, and adhesives………………………
94.6
77.4
80.4
87.3
89.4
100.0
100.0
100.0
100.0
100.0
102.8
106.0
98.8
93.8
100.1
115.7
109.8
87.4
95.7
100.3
117.5
109.8
92.1
95.6
100.8
108.8
106.2
90.0
99.5
105.6
123.8
123.1
99.2
97.4
108.9
136.0
122.2
108.4
101.5
115.2
154.4
121.9
117.4
104.1
119.1
165.2
130.5
132.5
110.0
120.8
169.3
134.9
130.7
115.0
115.4
-
3256
3259
326
3261
3262
Soap, cleaning compounds, and toiletries……………
Other chemical products and preparations…………
Plastics and rubber products…………………………
Plastics products………………………………………
Rubber products…………………………………………
84.4
75.4
80.9
83.1
75.5
100.0
100.0
100.0
100.0
100.0
98.0
99.2
103.2
104.2
99.4
93.0
109.3
107.9
109.9
100.2
102.8
119.7
110.2
112.3
101.7
106.0
110.4
112.3
114.6
102.3
124.1
120.8
120.8
123.8
107.1
118.2
123.0
126.0
129.5
111.0
135.3
121.3
128.7
131.9
114.4
153.1
123.5
132.6
135.6
118.7
162.9
118.1
132.8
133.8
124.9
-
327
3271
Nonmetallic mineral products…………………………
Clay products and refractories…………………………
87.6
86.9
100.0
100.0
103.7
101.2
104.3
102.7
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 • May 2009
133
Current Labor Statistics: Productivity Data
50. Continued - Annual indexes of output per hour for selected NAICS industries
[1997=100]
NAICS
Industry
1987
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
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
100.0
100.0
100.0
100.0
100.0
101.3
105.1
114.9
99.0
102.0
106.7
105.9
104.4
95.6
102.8
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
100.0
100.0
100.0
100.0
100.0
101.3
100.6
101.5
111.3
101.2
104.8
93.8
103.5
108.4
104.5
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
100.0
100.0
100.0
100.0
100.0
101.3
103.5
99.9
100.9
100.0
103.0
110.9
108.0
102.0
96.5
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
100.0
100.0
100.0
100.0
100.0
100.5
110.6
99.6
100.9
101.9
105.2
111.4
104.2
101.0
99.6
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
100.0
100.0
100.0
100.0
100.0
102.9
103.3
95.1
106.3
106.2
104.7
94.3
105.8
110.0
110.2
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
100.0
100.0
100.0
100.0
100.0
99.1
105.0
103.7
118.4
140.4
100.3
110.8
106.0
149.5
195.9
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
100.0
100.0
100.0
100.0
100.0
107.1
105.4
125.8
102.3
106.4
135.4
119.6
173.9
106.7
108.9
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
100.0
100.0
100.0
100.0
100.0
103.9
104.4
105.2
100.2
105.8
106.6
102.8
104.0
98.7
114.7
111.5
102.0
117.2
99.4
119.7
111.4
106.7
124.6
101.0
113.1
113.4
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
100.0
100.0
100.0
100.0
100.0
109.7
113.4
102.9
104.9
119.1
118.0
122.6
103.1
110.0
120.8
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
73.8
84.8
85.2
100.0
100.0
100.0
100.0
100.0
103.3
99.3
111.5
102.0
102.2
116.5
112.0
113.8
101.6
103.1
118.5
122.0
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
100.0
100.0
100.0
100.0
100.0
100.0
106.9
105.2
109.0
102.1
98.2
102.0
107.8
111.1
105.0
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
100.0
100.0
100.0
100.0
100.0
100.0
103.4
107.1
106.4
99.9
105.4
125.5
111.2
119.2
120.4
102.3
109.3
162.0
116.5
125.0
116.7
112.5
107.7
181.9
117.7
128.9
120.0
110.7
116.6
217.9
123.3
140.2
133.4
116.0
123.9
264.9
127.5
146.6
137.6
123.9
133.0
299.1
134.8
161.5
143.5
130.0
139.4
352.8
135.8
167.4
146.5
127.1
140.2
402.0
138.6
174.5
162.7
130.6
135.4
447.3
141.5
178.4
161.8
131.1
124.5
508.5
4235
4236
4237
4238
Metals and minerals…………………………………… 101.7
Electric goods…………………………………………… 42.8
Hardware and plumbing………………………………
82.2
Machinery and supplies………………………………
74.1
100.0
100.0
100.0
100.0
100.9
105.9
101.8
104.3
94.0
127.5
104.4
102.9
93.9
152.8
103.7
105.5
94.4
147.6
100.5
102.9
96.3
159.5
102.6
100.3
97.5
165.7
103.9
103.4
106.3
194.1
107.3
112.4
104.2
204.6
104.5
117.6
99.9
222.1
105.6
121.2
94.4
235.1
105.8
121.5
Wholesale trade
134
Monthly Labor Review • May 2009
50. Continued - Annual indexes of output per hour for selected NAICS industries
[1997=100]
NAICS
Industry
1987
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
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
100.0
100.0
100.0
100.0
100.0
100.8
99.1
98.4
94.2
103.6
113.7
100.8
100.1
93.1
105.1
114.7
105.1
100.9
85.9
108.8
116.8
105.1
104.6
84.9
115.2
124.6
105.8
116.6
89.8
122.8
119.6
110.5
119.7
100.2
125.9
135.0
113.6
130.9
105.8
131.0
135.5
114.3
141.7
112.1
140.8
122.3
113.1
136.9
109.7
146.6
118.4
115.0
146.5
104.3
148.3
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
100.0
100.0
100.0
100.0
100.0
101.1
94.3
97.1
88.5
106.5
101.0
101.6
93.3
102.9
105.6
102.4
105.1
87.9
138.1
108.4
101.9
102.1
85.3
140.6
106.4
98.6
98.1
89.1
153.6
106.8
104.9
98.2
92.2
151.1
107.9
104.1
109.3
91.2
163.2
103.1
103.4
111.0
87.4
153.3
104.0
103.8
117.9
85.1
149.4
107.4
109.7
125.1
86.4
149.1
108.5
4249
425
4251
Miscellaneous nondurable goods……………………
Electronic markets and agents and brokers…………
Electronic markets and agents and brokers…………
111.2
64.3
64.3
100.0
100.0
100.0
105.4
102.4
102.4
106.8
112.3
112.3
115.0
120.1
120.1
111.9
110.7
110.7
106.1
109.8
109.8
109.8
104.5
104.5
120.7
101.6
101.6
124.1
91.5
91.5
121.9
95.0
95.0
117.1
98.3
98.3
44-45
441
4411
4412
4413
Retail trade………………………………………………
Motor vehicle and parts dealers………………………
Automobile dealers……………………………………
Other motor vehicle dealers……………………………
Auto parts, accessories, and tire stores………………
79.2
78.4
79.2
74.1
71.8
100.0
100.0
100.0
100.0
100.0
105.7
106.4
106.5
109.6
105.1
112.7
115.1
116.3
114.8
107.6
116.1
114.3
113.7
115.3
108.4
120.1
116.0
115.5
124.6
101.3
125.6
119.9
117.2
133.6
107.7
131.6
124.3
119.5
133.8
115.1
137.9
127.3
124.7
143.3
110.1
141.3
126.7
123.5
134.6
115.5
147.3
129.3
125.8
142.6
115.9
152.7
132.2
129.8
146.9
112.0
442
4421
4422
443
4431
Furniture and home furnishings stores………………
Furniture stores…………………………………………
Home furnishings stores………………………………
Electronics and appliance stores………………………
Electronics and appliance stores………………………
75.1
77.3
71.3
38.0
38.0
100.0
100.0
100.0
100.0
100.0
104.1
104.3
104.1
122.6
122.6
110.8
107.5
115.2
150.6
150.6
115.9
112.0
121.0
173.7
173.7
122.4
119.7
126.1
196.7
196.7
129.3
125.2
134.9
233.5
233.5
134.6
128.8
142.6
292.7
292.7
146.7
139.2
156.8
334.1
334.1
150.5
142.3
161.4
367.5
367.5
158.2
151.1
168.3
412.0
412.0
168.7
156.6
184.6
471.1
471.1
444
4441
4442
445
4451
Building material and garden supply stores…………
Building material and supplies dealers………………
Lawn and garden equipment and supplies stores…
Food and beverage stores……………………………
Grocery stores…………………………………………
75.8
77.6
66.9
110.8
111.1
100.0
100.0
100.0
100.0
100.0
107.4
108.3
102.4
99.9
99.6
113.8
115.3
105.5
101.9
102.5
113.3
115.1
103.1
101.0
101.1
116.8
116.7
118.4
103.8
103.3
120.8
121.3
118.3
104.7
104.8
127.1
127.4
125.7
107.2
106.7
134.6
134.0
140.1
112.9
112.2
134.8
134.9
134.7
117.9
116.8
137.9
138.0
138.3
120.6
118.2
142.2
140.0
162.1
123.8
120.6
4452
4453
446
4461
447
Specialty food stores…………………………………… 138.5
Beer, wine, and liquor stores…………………………
93.6
Health and personal care stores………………………
84.0
Health and personal care stores………………………
84.0
Gasoline stations………………………………………
83.9
100.0
100.0
100.0
100.0
100.0
100.5
104.6
104.0
104.0
106.7
96.4
99.1
107.1
107.1
110.7
98.5
105.7
112.2
112.2
107.7
108.2
107.1
116.2
116.2
112.9
105.3
110.1
122.9
122.9
125.1
112.2
117.0
129.5
129.5
119.9
120.3
127.8
134.3
134.3
122.2
125.3
139.8
133.4
133.4
124.7
139.4
146.1
139.3
139.3
124.9
145.4
156.8
139.0
139.0
129.3
4471
448
4481
4482
4483
Gasoline stations………………………………………
Clothing and clothing accessories stores……………
Clothing stores…………………………………………
Shoe stores………………………………………………
Jewelry, luggage, and leather goods stores…………
83.9
66.3
67.1
65.3
64.5
100.0
100.0
100.0
100.0
100.0
106.7
106.3
108.7
94.2
108.7
110.7
114.0
114.2
104.9
122.5
107.7
123.5
125.0
110.0
130.5
112.9
126.4
130.3
111.5
123.9
125.1
131.3
136.0
125.2
118.7
119.9
138.9
141.8
132.5
132.9
122.2
139.1
140.9
124.8
144.3
124.7
147.6
153.0
132.0
138.9
124.9
162.4
169.4
145.1
148.3
129.3
176.6
186.9
141.6
162.9
451
4511
4512
452
4521
Sporting goods, hobby, book, and music stores……
Sporting goods and musical instrument stores………
Book, periodical, and music stores……………………
General merchandise stores…………………………
Department stores………………………………………
74.9
73.2
78.9
73.5
87.2
100.0
100.0
100.0
100.0
100.0
107.9
111.5
101.0
105.3
100.4
114.0
119.8
103.2
113.4
104.5
121.1
129.4
105.8
120.2
106.2
127.1
134.5
113.0
124.8
103.8
127.6
136.0
111.6
129.1
102.0
131.5
141.1
113.7
136.9
106.8
151.1
166.0
123.6
140.7
109.0
163.5
179.3
134.3
145.0
110.0
170.5
191.4
132.4
149.8
112.7
167.8
189.2
128.3
152.5
107.0
4529
453
4531
4532
4533
Other general merchandise stores……………………
Miscellaneous store retailers…………………………
Florists………………………………………………….
Office supplies, stationery and gift stores……………
Used merchandise stores………………………………
54.8
65.1
77.6
61.4
64.5
100.0
100.0
100.0
100.0
100.0
114.7
108.9
102.3
111.5
119.1
131.0
111.3
116.2
119.2
113.4
147.3
114.1
115.2
127.3
116.5
164.7
112.6
102.7
132.3
121.9
179.3
119.1
113.8
141.5
142.0
188.8
126.1
108.9
153.9
149.7
192.9
130.8
103.4
172.8
152.6
199.8
139.2
123.7
182.4
156.6
204.8
155.0
145.1
204.8
167.6
219.3
160.8
132.9
224.5
182.0
4539
454
4541
4542
4543
Other miscellaneous store retailers……………………
Nonstore retailers………………………………………
Electronic shopping and mail-order houses…………
Vending machine operators……………………………
Direct selling establishments…………………………
68.3
50.7
39.4
95.5
70.8
100.0
100.0
100.0
100.0
100.0
105.3
114.3
120.2
106.3
101.9
103.0
128.9
142.6
105.4
104.3
104.4
152.2
160.2
111.1
122.5
96.9
163.6
179.6
95.7
127.9
94.4
182.1
212.7
91.3
135.1
99.9
195.5
243.6
102.3
127.0
96.9
215.5
273.0
110.5
130.3
101.6
220.6
290.1
114.4
119.6
114.0
261.9
355.9
125.7
127.5
115.4
290.8
397.2
132.4
138.4
481
482111
48412
48421
491
4911
Air transportation………………………………………
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
100.0
100.0
100.0
100.0
100.0
100.0
96.4
102.1
99.4
91.0
101.6
101.6
95.9
105.5
99.1
96.1
102.8
102.8
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………………
-
100.0
100.0
100.0
100.0
100.0
114.8
106.4
106.4
112.1
97.9
122.2
107.7
107.7
112.9
103.4
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 • May 2009
135
Current Labor Statistics: Productivity Data
50. Continued - Annual indexes of output per hour for selected NAICS industries
[1997=100]
NAICS
Industry
1987
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Information
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
100.0
100.0
100.0
100.0
100.0
116.1
103.9
134.8
99.8
100.8
116.3
104.1
129.2
101.8
102.9
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
98.1
Radio and television broadcasting……………………
Cable and other subscription programming………… 105.6
Wired telecommunications carriers…………………… 56.9
Wireless telecommunications carriers………………
75.6
Cable and other program distribution………………… 105.2
100.0
100.0
100.0
100.0
100.0
91.5
136.2
107.7
110.5
97.1
92.6
139.1
116.7
145.2
95.8
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
100.0
97.7
100.8
104.8
102.4
106.9
111.7
117.8
119.3
122.7
123.8
92.7
60.3
77.0
100.0
100.0
100.0
100.1
115.4
113.2
112.2
121.0
129.4
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
100.0
100.0
100.0
100.0
100.0
107.6
111.4
98.2
89.2
124.8
105.8
106.8
98.0
97.9
109.8
100.9
107.6
102.0
107.5
108.9
94.4
111.0
100.1
106.9
102.2
111.4
107.6
100.5
113.1
97.6
110.0
112.6
100.5
121.1
104.2
99.9
118.3
107.8
133.5
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
100.0
100.0
100.0
86.8
111.4
95.3
93.2
115.5
98.6
89.8
119.4
101.0
99.6
115.2
102.1
116.8
127.6
105.6
115.4
147.2
118.8
119.8
167.2
116.6
116.0
179.2
120.7
123.8
183.4
116.1
132.8
190.6
122.3
-
100.0
100.0
100.0
118.8
117.2
121.4
124.7
121.4
129.7
131.9
127.4
139.9
135.3
127.7
148.3
137.6
123.1
163.3
140.8
128.6
160.0
140.8
130.7
153.5
137.8
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
100.0
100.0
110.5
89.9
105.2
89.4
106.0
93.4
93.0
94.3
106.5
96.4
113.2
102.4
101.4
107.9
109.9
106.5
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
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.7
100.0
99.6
101.0
100.9
101.2
100.6
99.7
102.2
105.3
105.4
100.9
100.8
100.4
105.2
98.8
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
104.0
109.1
120.4
137.6
8111
81142
81211
81221
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
100.0
100.0
100.0
100.0
103.6
95.8
108.6
106.8
106.1
105.0
108.6
103.3
109.4
105.5
108.2
94.8
108.9
105.0
114.6
91.8
103.7
102.0
110.4
94.6
104.1
97.2
119.7
95.7
112.0
99.8
125.0
92.9
112.1
101.4
130.0
93.1
111.4
100.0
129.8
99.5
110.4
105.8
134.5
97.0
Professional and technical services
Administrative and waste services
Health care and social assistance
Arts, entertainment, and recreation
Accommodation and food services
Other services
51. Unemployment rates, approximating U.S. concepts, 10 countries, seasonally adjusted
[Percent]
2006
Country
2006
2007
I
II
2008
2007
III
IV
I
II
III
IV
I
II
III
United States………
4.6
4.6
4.7
4.7
4.7
4.4
4.5
4.5
4.7
4.8
4.9
5.3
6.0
Canada………………
5.5
5.3
5.7
5.4
5.6
5.4
5.4
5.3
5.2
5.2
5.2
5.3
5.3
Australia……………
4.8
4.4
5.0
4.9
4.7
4.5
4.5
4.3
4.3
4.3
4.1
4.3
4.2
Japan…………………
4.2
3.9
4.2
4.2
4.2
4.1
4.0
3.8
3.8
3.9
3.9
4.0
4.1
France………………
9.5
8.6
9.9
9.5
9.5
9.2
9.1
8.7
8.5
8.2
8.0
8.0
8.3
Germany……………
10.4
8.7
11.1
10.6
10.1
9.6
9.3
8.9
8.5
8.1
7.8
7.6
7.5
Italy…………………
6.9
6.2
7.3
6.9
6.7
6.5
6.2
6.1
6.2
6.4
6.7
6.8
-
Netherlands…………
3.9
3.2
4.3
3.9
3.8
3.8
3.6
3.2
3.0
3.0
2.9
2.8
2.5
Sweden………………
7.0
6.1
7.3
7.3
6.7
6.5
6.4
6.1
5.8
5.9
5.8
5.8
5.9
United Kingdom……
5.5
5.4
5.3
5.5
5.5
5.5
5.5
5.4
5.3
5.2
5.3
5.4
-
NOTE: Dash indicates data not available.
Quarterly figures for France, Germany, Italy, and the Netherlands are calculated by
applying annual adjustment factors to current published data and therefore should be
viewed as less precise indicators of unemployment under U.S. concepts than the
annual figures. Quarterly figures for Sweden are BLS seasonally adjusted estimates
derived from Swedish not seasonally adjusted data. For further qualifications and
historical annual data, see the BLS report International comparisons of annual labor
force statistics, 10 countries (on the internet at
136
Monthly Labor Review • May 2009
http://www.bls.gov/fls/flscomparelf.htm). For monthly unemployment rates, as
well as the quarterly and annual rates published in this table, see the BLS report
Unemployment rates in 10 countries, civilian labor force basis, approximating U.S.
concepts, seasonally adjusted (on the Internet at http://www.bls.gov/fls/flsjec.pdf).
Unemployment rates may differ between the two reports mentioned, because the
former is updated 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, approximating U.S. concepts, 10 countries
[Numbers in thousands]
Employment status and country
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
137,673
15,135
9,339
67,240
25,434
39,752
23,004
7,744
4,401
28,474
139,368
15,403
9,414
67,090
25,791
39,375
23,176
7,881
4,423
28,786
142,583
15,637
9,590
66,990
26,099
39,302
23,361
8,052
4,482
28,962
143,734
15,891
9,744
66,860
26,393
39,459
23,524
8,199
4,522
29,092
144,863
16,366
9,893
66,240
26,646
39,413
23,728
8,345
4,537
29,343
146,510
16,733
10,079
66,010
26,851
39,276
24,020
8,379
4,557
29,564
147,401
16,955
10,221
65,770
26,937
39,711
24,084
8,439
4,571
29,802
149,320
17,108
10,506
65,850
27,092
40,760
24,179
8,459
4,694
30,138
151,428
17,351
10,699
65,960
27,322
41,250
24,395
8,541
4,748
30,600
153,124
17,696
10,949
66,080
27,535
41,416
24,459
8,686
4,823
30,790
67.1
65.1
64.3
63.2
55.6
57.3
47.3
61.1
63.2
62.5
67.1
65.4
64.3
62.8
56.0
57.7
47.7
61.8
62.8
62.4
67.1
65.9
64.0
62.4
56.3
56.9
47.9
62.5
62.7
62.8
67.1
66.0
64.4
62.0
56.6
56.7
48.1
63.4
63.7
62.8
66.8
66.1
64.4
61.6
56.7
56.7
48.3
64.0
63.6
62.7
66.6
67.1
64.3
60.8
56.8
56.4
48.5
64.7
63.9
62.9
66.2
67.7
64.6
60.3
56.8
56.0
49.1
64.6
63.8
62.9
66.0
67.7
64.6
60.0
56.6
56.4
49.1
64.8
63.6
63.0
66.0
67.4
65.3
60.0
56.5
57.6
48.7
64.7
64.8
63.1
66.2
67.4
65.6
60.0
56.6
58.2
48.9
65.1
64.9
63.5
66.0
67.7
66.0
60.0
56.7
58.4
48.6
65.9
65.3
63.4
United States……………………………………………… 129,558
Canada……………………………………………………
13,637
Australia……………………………………………………
8,444
Japan………………………………………………………
64,900
France……………………………………………………… 22,176
Germany…………………………………………………… 35,508
Italy…………………………………………………………
20,169
Netherlands………………………………………………
7,189
Sweden……………………………………………………
3,969
United Kingdom…………………………………………… 26,413
131,463
13,973
8,618
64,450
22,597
36,059
20,370
7,408
4,033
26,684
133,488
14,331
8,762
63,920
23,080
36,042
20,617
7,605
4,110
27,058
136,891
14,681
8,989
63,790
23,714
36,236
20,973
7,813
4,222
27,375
136,933
14,866
9,086
63,460
24,167
36,350
21,359
8,014
4,295
27,603
136,485
15,223
9,264
62,650
24,312
36,018
21,666
8,114
4,303
27,815
137,736
15,586
9,480
62,510
24,373
35,615
21,972
8,069
4,293
28,077
139,252
15,861
9,668
62,640
24,354
35,604
22,124
8,052
4,271
28,379
141,730
16,080
9,975
62,910
24,493
36,185
22,290
8,056
4,334
28,674
144,427
16,393
10,186
63,210
24,717
36,978
22,721
8,205
4,416
28,930
146,047
16,767
10,470
63,510
25,162
37,815
22,953
8,408
4,530
29,138
63.8
59.6
59.0
61.0
49.1
51.6
41.9
57.7
56.8
58.1
64.1
60.4
59.3
60.2
49.7
52.3
42.2
59.1
57.6
58.5
64.3
61.3
59.6
59.4
50.4
52.1
42.6
60.3
58.3
59.0
64.4
62.0
60.3
59.0
51.4
52.2
43.2
61.5
60.0
59.4
63.7
61.9
60.0
58.4
51.9
52.2
43.8
62.6
60.4
59.5
62.7
62.4
60.2
57.5
51.8
51.5
44.3
62.9
60.6
59.6
62.3
63.1
60.7
57.1
51.5
50.8
44.9
62.2
60.1
59.8
62.3
63.3
61.1
57.1
51.1
50.6
45.1
61.8
59.4
60.0
62.7
63.4
62.0
57.3
51.1
51.2
44.9
61.6
59.9
60.0
63.1
63.6
62.5
57.5
51.2
52.2
45.5
62.5
60.4
60.1
63.0
64.2
63.1
57.6
51.8
53.3
45.6
63.8
61.3
60.0
6,739
1,248
759
2,300
2,940
3,907
2,584
423
445
1,991
6,210
1,162
721
2,790
2,837
3,693
2,634
337
368
1,790
5,880
1,072
652
3,170
2,711
3,333
2,559
277
313
1,728
5,692
956
602
3,200
2,385
3,065
2,388
239
260
1,587
6,801
1,026
658
3,400
2,226
3,110
2,164
186
227
1,488
8,378
1,143
629
3,590
2,334
3,396
2,062
231
234
1,528
8,774
1,147
599
3,500
2,478
3,661
2,048
310
264
1,488
8,149
1,093
553
3,130
2,583
4,107
1,960
387
300
1,422
7,591
1,028
531
2,940
2,599
4,575
1,889
402
361
1,463
7,001
958
512
2,750
2,605
4,272
1,673
336
332
1,670
7,078
929
478
2,570
2,374
3,601
1,506
278
293
1,652
4.9
8.4
8.3
3.4
11.7
9.9
11.4
5.6
10.1
7.0
4.5
7.7
7.7
4.1
11.2
9.3
11.5
4.4
8.4
6.3
4.2
7.0
6.9
4.7
10.5
8.5
11.0
3.5
7.1
6.0
4.0
6.1
6.3
4.8
9.1
7.8
10.2
3.0
5.8
5.5
4.7
6.5
6.8
5.1
8.4
7.9
9.2
2.3
5.0
5.1
5.8
7.0
6.4
5.4
8.8
8.6
8.7
2.8
5.2
5.2
6.0
6.9
5.9
5.3
9.2
9.3
8.5
3.7
5.8
5.0
5.5
6.4
5.4
4.8
9.6
10.3
8.1
4.6
6.6
4.8
5.1
6.0
5.1
4.5
9.6
11.2
7.8
4.8
7.7
4.9
4.6
5.5
4.8
4.2
9.5
10.4
6.9
3.9
7.0
5.5
4.6
5.3
4.4
3.9
8.6
8.7
6.2
3.2
6.1
5.4
Civilian labor force
United States……………………………………………… 136,297
Canada……………………………………………………
14,884
Australia……………………………………………………
9,204
Japan………………………………………………………
67,200
France……………………………………………………… 25,116
Germany…………………………………………………… 39,415
Italy…………………………………………………………
22,753
Netherlands………………………………………………
7,612
Sweden……………………………………………………
4,414
United Kingdom…………………………………………… 28,403
Participation rate1
United States………………………………………………
Canada……………………………………………………
Australia……………………………………………………
Japan………………………………………………………
France………………………………………………………
Germany……………………………………………………
Italy…………………………………………………………
Netherlands………………………………………………
Sweden……………………………………………………
United Kingdom……………………………………………
Employed
Employment-population ratio2
United States………………………………………………
Canada……………………………………………………
Australia……………………………………………………
Japan………………………………………………………
France………………………………………………………
Germany……………………………………………………
Italy…………………………………………………………
Netherlands………………………………………………
Sweden……………………………………………………
United Kingdom……………………………………………
Unemployed
United States………………………………………………
Canada……………………………………………………
Australia……………………………………………………
Japan………………………………………………………
France………………………………………………………
Germany……………………………………………………
Italy…………………………………………………………
Netherlands………………………………………………
Sweden……………………………………………………
United Kingdom……………………………………………
Unemployment rate
United States………………………………………………
Canada……………………………………………………
Australia……………………………………………………
Japan………………………………………………………
France………………………………………………………
Germany……………………………………………………
Italy…………………………………………………………
Netherlands………………………………………………
Sweden……………………………………………………
United Kingdom……………………………………………
1
2
Labor force as a percent of the working-age population.
Employment as a percent of the working-age population.
NOTE: There are breaks in series for the United States (1997, 1998, 1999, 2000, 2003,
2004), Australia (2001), Germany (1999, 2005), the Netherlands (2000, 2003), and Sweden
(2005). For further qualifications and historical annual data, see the BLS report
International comparisons of annual labor force statistics, 10 countries (on the
Internet at http://www.bls.gov/fls/flscomparelf.htm ). Unemployment rates may differ
from those in the BLS report Unemployment rates in 10 countries, civilian labor force
basis, approximating U.S. concepts, seasonally adjusted (on the Internet at
http://www.bls.gov/fls/flsjec.pdf ), because the former is updated annually, whereas
the latter is updated monthly and reflects the most recent revisions in source data.
Monthly Labor Review • May 2009 137
Current Labor Statistics: International Comparisons
53. Annual indexes of manufacturing productivity and related measures, 17 economies
[1996 = 100]
Measure and economy
1980
1990
1993
1994
1995
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Output per hour
United States………………………
Canada………………………….……
Australia…………………….………
Japan…………………………………
Korea, Rep. of………………………
Singapore……………………………
Taiwan………………………………
Belgium…………………………...…
Denmark……………………………
France………………………………
Germany………………………...……
Italy……………………………...……
Netherlands…………………...……
Norway………………………………
Spain………………………………..
Sweden……………………………..
United Kingdom……………….……
58.6
66.5
72.5
54.8
–
–
40.4
57.2
75.3
56.9
67.1
60.1
57.2
77.3
62.8
60.0
55.9
80.1
85.2
91.1
81.3
58.0
68.2
73.9
84.7
90.3
84.2
86.1
82.5
81.4
96.8
86.8
73.9
87.8
88.1
94.0
95.8
87.6
75.9
82.3
83.4
89.6
92.0
90.0
89.1
87.2
86.2
98.3
94.9
82.6
100.1
92.7
99.3
98.4
89.0
82.8
89.5
86.6
94.4
103.4
95.9
95.8
94.9
94.1
98.3
97.8
91.1
102.7
96.2
100.5
97.1
95.6
90.9
95.5
93.0
98.6
103.4
99.7
97.3
99.5
97.9
97.1
101.2
96.8
101.0
104.2
104.5
102.0
103.5
112.8
103.2
104.1
106.3
108.0
105.9
105.9
102.0
100.3
100.2
101.0
109.1
102.0
111.5
109.6
106.9
104.5
125.7
111.2
109.2
107.6
107.4
111.4
106.3
100.6
103.2
97.7
102.7
115.6
102.9
117.1
114.2
108.5
107.3
139.8
122.5
116.0
106.8
109.1
116.2
108.9
101.4
107.4
101.1
104.5
126.2
108.0
126.1
121.1
115.1
113.0
151.7
130.8
122.2
110.9
113.0
124.5
116.5
106.7
115.2
104.2
105.6
134.8
115.4
127.4
118.5
117.9
110.6
150.6
122.9
127.7
111.0
113.2
127.0
119.5
107.0
115.7
107.1
108.0
131.0
119.4
140.9
120.5
122.9
114.7
165.3
133.8
139.2
114.6
113.9
132.4
120.7
105.7
119.2
110.2
108.4
145.3
123.0
149.8
121.1
125.2
122.5
176.8
138.7
143.6
117.8
118.7
138.4
125.0
103.5
121.7
119.7
111.1
157.1
128.2
159.0
122.4
126.8
131.0
197.2
147.3
150.9
123.7
125.5
142.2
129.7
105.0
129.9
126.8
113.2
173.9
136.2
162.2
126.6
127.6
139.6
212.1
149.9
162.3
127.0
129.6
148.7
137.1
106.4
135.8
131.2
115.4
184.7
141.9
169.9
129.3
128.8
141.0
233.5
153.5
173.4
131.8
135.5
154.6
148.6
105.9
140.2
128.5
117.7
202.0
149.1
177.8
132.8
131.3
145.8
253.9
147.5
188.5
137.6
136.0
158.5
155.9
105.4
144.0
128.2
122.2
203.0
153.0
Output
United States…………………..……
Canada………………………………
Australia………………………………
Japan…………………………………
Korea, Rep. of………………………
Singapore……………………………
Taiwan………………………………
Belgium………………………………
Denmark……………………………
France………………………………
Germany……………………………
Italy……………………………………
Netherlands…………………………
Norway………………………………
Spain………………………………..
Sweden………………………………
United Kingdom……………………
60.5
71.2
80.2
59.0
20.5
–
38.2
74.8
85.6
83.2
92.3
74.7
68.7
96.7
75.5
67.1
80.3
80.7
88.7
93.1
94.3
63.2
66.2
76.7
96.6
94.7
97.5
107.2
92.6
89.2
92.9
94.6
80.4
96.9
85.7
87.7
92.7
93.5
75.5
78.5
85.0
92.8
90.3
93.8
99.9
89.9
90.2
93.2
92.4
74.1
93.4
92.2
94.4
97.5
92.1
84.1
88.4
90.1
97.0
100.0
96.8
103.1
95.9
95.0
95.7
94.0
85.5
97.8
96.4
98.7
96.9
95.9
94.0
97.3
95.0
99.6
104.8
100.3
102.1
100.5
98.6
96.1
97.6
96.8
99.3
106.1
106.3
102.3
102.5
104.9
104.3
105.7
104.8
108.2
104.7
104.4
101.5
101.4
104.3
106.4
107.8
101.8
113.2
111.7
105.2
97.1
96.6
103.5
109.1
106.5
109.1
109.7
105.6
102.4
104.8
103.6
112.9
116.7
102.4
118.1
121.0
105.0
96.7
117.6
117.0
117.1
106.9
110.0
113.4
106.6
102.2
108.7
103.5
119.3
127.6
103.6
125.5
133.1
110.0
101.8
137.6
134.7
125.7
111.6
113.9
118.6
113.9
106.5
116.0
102.9
124.6
138.1
105.9
118.5
128.0
108.9
96.2
140.6
119.1
116.4
111.8
114.0
119.8
115.8
106.2
115.8
102.2
128.6
134.9
104.5
121.8
129.0
114.2
94.7
151.2
129.1
126.7
110.9
110.7
119.7
113.4
105.0
115.9
101.6
128.4
143.4
102.2
123.2
128.3
116.2
99.8
159.6
132.9
133.5
109.3
107.6
121.9
114.2
102.2
114.6
105.0
130.0
150.4
101.9
130.1
130.9
116.3
105.6
177.3
151.3
146.5
113.2
109.3
123.0
118.3
103.0
118.5
111.0
130.9
164.2
104.2
131.2
132.9
115.8
111.1
189.8
165.7
156.7
113.1
109.9
125.9
122.3
102.5
120.9
115.9
132.4
171.8
104.0
138.4
132.3
114.7
114.9
205.9
185.4
167.9
116.3
114.5
127.2
131.2
103.7
124.1
119.4
134.8
185.3
105.8
142.4
131.1
118.4
119.1
219.3
196.2
185.3
119.3
118.6
128.8
139.2
104.8
128.1
125.7
138.6
189.6
106.5
Total hours
United States……………………… 103.3
Canada……………………………… 107.0
Australia……………………………… 110.6
Japan………………………………… 107.6
Korea, Rep. of………………………
–
Singapore…………………………… –
Taiwan……………………………… 94.5
Belgium……………………………… 130.9
Denmark…………………………… 113.7
France……………………………… 146.3
Germany…………………………… 137.4
Italy…………………………………… 124.3
Netherlands………………………… 120.1
Norway……………………………… 125.1
Spain……………………………….. 120.3
Sweden……………………………… 111.8
United Kingdom…………………… 143.8
100.7
104.1
102.2
115.9
109.0
96.9
103.7
114.1
104.8
115.8
124.6
112.2
109.6
96.0
109.0
108.8
110.4
97.3
93.3
96.9
106.7
99.5
95.3
101.9
103.5
98.1
104.1
112.1
103.1
104.6
94.8
97.4
89.7
93.3
99.5
95.1
99.1
103.5
101.6
98.8
104.0
102.8
96.7
101.0
107.6
101.1
100.9
97.3
96.1
93.9
95.2
100.2
98.3
99.8
100.4
103.3
101.9
102.2
101.0
101.4
100.6
105.0
100.9
100.7
99.0
96.4
100.0
98.3
101.8
101.6
100.3
99.1
93.0
101.1
101.6
98.6
100.2
98.9
98.6
99.5
101.0
104.1
105.4
98.8
99.8
101.5
101.9
98.4
92.9
76.8
93.1
99.9
98.9
101.5
98.5
99.4
101.8
101.5
106.1
109.9
100.9
99.6
100.9
105.9
96.7
90.2
84.1
95.6
101.0
100.0
100.8
97.6
97.9
100.8
101.2
102.4
114.1
101.1
95.9
99.6
109.9
95.6
90.1
90.7
103.0
102.9
100.7
100.8
95.3
97.7
99.9
100.7
98.8
118.0
102.4
91.8
93.0
107.9
92.4
87.0
93.3
96.9
91.1
100.7
100.7
94.3
96.9
99.3
100.1
95.4
119.0
103.0
87.5
86.5
107.1
92.9
82.6
91.5
96.5
91.1
96.8
97.2
90.4
94.0
99.3
97.2
92.3
118.4
98.7
83.1
82.2
105.9
92.8
81.4
90.2
95.8
92.9
92.8
90.7
88.1
91.4
98.8
94.1
87.7
117.0
95.7
79.5
81.8
106.9
91.7
80.6
89.9
102.8
97.1
91.5
87.1
86.5
91.2
98.1
91.2
87.5
115.6
94.4
76.5
80.9
105.0
90.7
79.6
89.5
110.5
96.5
89.0
84.8
84.7
89.2
96.4
89.0
88.4
114.7
93.0
73.3
81.5
102.3
89.1
81.5
88.2
120.8
96.8
88.2
84.5
82.3
88.3
97.9
88.5
92.9
114.6
91.7
71.0
80.1
98.7
90.2
81.6
86.4
133.0
98.3
86.7
87.2
81.2
89.3
99.4
88.9
98.0
113.4
93.4
69.6
82.7
82.4
79.5
83.0
36.1
64.6
66.5
81.4
83.1
78.9
72.3
70.5
78.8
81.2
65.9
77.4
82.8
93.3
93.5
88.9
94.1
61.6
84.3
82.6
94.8
90.9
91.8
86.7
85.1
91.6
89.2
90.3
85.8
96.2
96.3
96.2
90.0
96.0
70.8
89.1
86.6
95.5
94.1
95.3
90.6
89.6
95.6
91.9
93.6
88.0
98.6
98.1
98.5
95.6
99.2
85.9
93.1
93.8
98.2
96.0
98.1
95.5
94.9
98.1
96.0
97.6
92.8
100.3
102.6
102.4
102.7
103.3
108.7
104.4
103.1
103.8
103.4
102.9
102.0
104.7
102.6
104.5
102.4
105.4
104.4
108.6
107.7
106.9
105.9
118.4
110.5
107.0
105.3
106.1
103.7
103.4
102.8
106.9
110.6
103.2
109.4
112.3
112.9
110.0
111.2
105.7
119.0
101.0
108.9
106.7
108.8
107.0
105.8
105.4
110.5
116.9
102.9
112.8
118.9
123.2
113.6
116.1
105.1
127.1
103.7
111.0
108.5
110.9
112.8
111.3
108.1
115.9
123.5
104.5
117.2
126.2
126.1
116.7
123.5
106.5
131.1
111.8
118.1
113.1
116.2
115.8
114.7
111.8
120.8
130.9
108.7
122.8
131.8
135.2
120.6
129.0
107.2
144.4
114.9
114.4
118.0
121.2
122.8
117.5
115.0
127.5
138.8
111.8
129.4
139.1
144.7
125.5
134.1
104.9
151.5
115.6
116.3
122.0
129.4
125.7
120.2
119.3
132.6
144.5
117.4
135.2
146.1
147.7
129.9
141.1
105.9
173.0
112.5
118.2
125.2
134.4
129.7
120.8
123.4
138.2
149.2
121.5
138.9
153.2
150.5
135.5
150.1
106.8
186.8
111.3
122.8
129.0
142.0
134.4
122.4
127.4
140.3
156.2
127.3
143.6
163.2
156.7
139.7
160.2
105.6
202.9
108.7
126.7
133.7
149.0
140.9
127.4
129.9
144.2
165.8
132.7
147.8
173.7
162.2
144.6
168.6
105.4
218.6
104.1
130.6
140.7
152.9
145.0
129.5
132.7
148.5
173.7
139.2
154.8
174.9
Hourly compensation
(national currency basis)
United States………………………
Canada………………………………
Australia………………………………
Japan…………………………………
Korea, Rep. of………………………
Singapore……………………………
Taiwan………………………………
Belgium………………………………
Denmark……………………………
France………………………………
Germany……………………………
Italy……………………………………
Netherlands…………………………
Norway………………………………
Spain………………………………..
Sweden………………………………
United Kingdom……………………
See notes at end of table.
138
51.2
43.8
–
53.7
–
–
23.1
47.5
39.5
34.6
43.3
22.6
52.3
34.3
23.1
32.9
33.4
Monthly Labor Review • May 2009
53. Continued— Annual indexes of manufacturing productivity and related measures, 17 economies
[1996 = 100]
Measure and economy
1980
1990
1993
1994
1995
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Unit labor costs
(national currency basis)
United States………………………
Canada………………………………
Australia………………………………
Japan…………………………………
Korea, Rep. of………………………
Singapore……………………………
Taiwan………………………………
Belgium………………………………
Denmark……………………………
France………………………………
Germany……………………………
Italy……………………………………
Netherlands…………………………
Norway………………………………
Spain………………………………..
Sweden………………………………
United Kingdom……………………
87.4
65.9
–
98.0
33.6
–
57.1
83.0
52.5
60.9
64.5
37.6
91.5
44.4
36.8
54.9
59.8
103.3
96.7
87.3
102.1
62.3
94.7
89.9
96.1
91.9
93.7
84.0
85.4
96.8
83.9
76.0
104.8
94.3
106.0
99.5
92.8
107.5
81.2
102.5
99.1
105.7
98.9
102.0
97.3
97.5
106.3
90.7
95.1
103.9
96.1
103.9
96.9
91.5
107.9
85.5
99.5
100.0
101.2
91.0
99.4
94.6
94.4
101.6
93.4
95.7
96.6
96.0
102.0
98.0
98.4
103.8
94.5
97.5
100.9
99.6
92.9
98.5
98.2
95.3
100.3
98.9
96.5
95.8
99.4
98.5
98.0
100.7
99.8
96.4
101.2
99.0
97.6
95.7
97.2
96.3
102.7
102.3
104.2
101.4
96.6
102.4
97.4
98.3
100.0
101.3
94.2
99.3
97.9
97.9
98.8
93.1
97.3
102.2
103.6
113.2
100.4
94.7
109.2
96.4
96.3
102.4
98.6
85.1
82.5
93.9
99.9
99.7
92.1
97.1
104.0
102.9
115.7
98.5
89.4
110.1
97.7
93.8
100.9
93.0
83.8
79.3
90.9
97.9
98.1
90.6
95.5
101.4
100.6
118.5
99.0
86.9
109.4
99.0
98.5
104.8
96.2
87.0
91.0
92.5
101.9
102.7
91.2
96.0
104.5
104.4
122.2
100.6
93.8
110.4
96.0
100.0
105.0
93.5
87.3
85.9
82.2
103.0
106.4
92.8
97.4
108.7
106.9
126.0
103.1
89.1
113.1
96.6
103.6
107.1
85.6
85.7
83.3
81.0
103.5
109.0
90.8
96.1
115.3
108.9
120.7
105.6
86.1
113.9
92.9
106.1
111.3
80.8
87.8
76.4
78.4
101.2
107.0
91.2
93.2
117.6
106.3
117.6
107.3
79.9
112.4
92.8
107.1
117.6
76.5
88.1
74.2
75.7
101.5
109.6
90.4
89.3
119.8
103.3
119.1
110.3
77.8
115.1
92.2
108.0
124.4
74.9
86.9
70.8
73.1
101.4
109.9
91.2
85.8
122.6
102.9
129.0
112.7
73.2
116.6
91.2
108.9
128.4
72.3
86.1
70.6
69.2
102.3
112.4
91.5
83.1
125.8
103.1
135.5
113.9
76.3
114.3
Unit labor costs
(U.S. dollar basis)
United States………………………
Canada………………………………
Australia………………………………
Japan…………………………………
Korea, Rep. of………………………
Singapore……………………………
Taiwan………………………………
Belgium………………………………
Denmark……………………………
France………………………………
Germany……………………………
Italy……………………………………
Netherlands…………………………
Norway………………………………
Spain………………………………..
Sweden………………………………
United Kingdom……………………
87.4
76.8
–
47.0
44.6
–
43.6
87.9
54.1
73.7
53.4
67.7
77.7
58.1
65.0
87.0
89.1
103.3
113.1
87.1
76.6
70.5
73.7
91.8
89.1
86.2
88.0
78.2
110.0
89.6
86.6
94.4
118.7
107.8
106.0
105.2
80.6
105.2
81.1
89.4
103.0
94.7
88.4
92.1
88.5
95.6
96.4
82.6
94.5
89.4
92.5
103.9
96.7
85.5
114.8
85.3
91.9
103.8
93.7
83.1
91.7
87.8
90.4
94.1
85.5
90.5
84.0
94.3
102.0
97.4
93.1
120.2
98.4
97.0
104.6
104.7
96.2
101.0
103.2
90.2
105.4
100.8
98.0
90.0
100.5
98.5
96.5
95.7
89.7
81.9
96.0
94.5
84.4
84.0
85.2
83.5
93.0
88.4
95.0
87.6
84.7
107.4
97.4
90.4
80.4
84.1
54.1
83.7
80.2
83.5
85.5
80.7
83.2
90.8
88.0
96.8
85.1
79.8
116.0
96.4
88.4
84.5
94.3
57.6
68.6
79.8
81.7
82.7
76.5
79.6
88.2
83.9
95.7
79.9
72.5
114.1
97.7
86.1
75.0
93.9
59.6
64.8
79.9
69.4
70.3
65.2
67.8
74.6
71.1
86.9
69.6
63.6
106.3
99.0
86.7
69.2
86.1
54.2
71.6
75.1
70.0
71.5
63.7
66.1
74.5
71.5
87.8
68.6
60.8
101.9
96.0
86.9
72.9
81.2
56.2
67.6
65.4
74.8
78.2
68.4
70.8
81.9
77.4
101.9
74.2
61.4
108.9
96.6
100.9
89.3
80.3
57.9
67.4
64.6
90.0
96.1
80.2
83.7
104.0
94.3
110.1
91.1
71.5
119.3
92.9
111.2
104.7
81.3
61.7
63.7
64.5
96.6
103.7
88.5
89.2
116.5
101.2
112.7
101.6
72.9
132.0
92.8
120.5
114.6
75.6
69.3
62.9
64.7
97.0
106.0
87.8
85.5
118.8
98.4
119.4
104.5
69.8
134.2
92.2
129.9
119.7
70.1
73.3
62.8
61.7
97.8
107.3
89.3
82.9
122.7
98.9
130.0
107.8
66.6
137.7
91.2
138.4
137.6
66.7
74.6
66.1
57.9
107.6
119.8
97.8
87.6
137.5
108.1
149.4
118.9
75.7
146.7
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.
Monthly Labor Review • May 2009 139
Current Labor Statistics: Injury and Illness Data
1
54. Occupational injury and illness rates by industry, United States
Industry and type of case
Incidence rates per 100 full-time workers
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
Total cases ............................………………………….
Lost workday cases.....................................................
Lost workdays........………...........................................
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
–
5
Durable goods:
Total cases ............................………………………….
Lost workday cases.....................................................
Lost workdays........………...........................................
Lumber and wood products:
See footnotes at end of table.
140
Monthly Labor Review • May 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
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
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
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
–
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
–
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
–
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
–
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
–
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
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
Leather and leather products:
Total cases ............................…………………………..
Lost workday cases......................................................
Lost workdays........………............................................
13.6
6.5
130.4
12.1
5.9
152.3
Transportation and public utilities
Total cases ............................…………………………..…
Lost workday cases.........................................................
Lost workdays........………...............................................
9.2
5.3
121.5
Wholesale and retail trade
Total cases ............................…………………………..…
Lost workday cases.........................................................
Lost workdays........………...............................................
7.8
4.2
–
7.8
4.2
–
6.8
3.8
–
12.7
7.3
–
12.4
7.3
–
10.9
6.3
–
-
5.5
2.2
–
6.2
3.1
–
6.7
4.2
–
7.4
3.4
–
6.4
3.2
–
6.0
3.2
–
5.2
2.7
–
7.0
3.1
–
6.2
2.6
-
5.8
2.8
–
6.1
3.0
–
5.0
2.4
–
7.9
3.8
–
7.3
3.7
–
7.1
3.7
–
7.0
3.7
–
6.5
3.4
–
6.0
3.2
–
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
–
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
–
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
–
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
–
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
–
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
–
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 • May 2009 141
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.
142
Monthly Labor Review • May 2009
COMPENSATION AND WORKING CONDITIONS
U.S. BUREAU OF LABOR STATISTICS
Recent Modifications of Employee Benefits Data in the National Compensation
Survey
by John E. Buckley
Bureau of Labor Statistics
Originally Posted: May 29, 2009
BLS recently discontinued the collection of data on five types of employee benefits in its National Compensation Survey,
allowing limited resources to be used to provide more pertinent and timely data on benefits.
Introduction
The Bureau of Labor Statistics (BLS) has collected and published data on employee benefits for decades. In 1981, after
conducting pilot studies in 1979 and 1980, BLS launched the Employee Benefits Survey program (EBS), initially publishing
data on the percentage of workers provided specific types of benefits. These were prominent, widely recognized benefits
such as health care, life insurance, and retirement, as well as less prominent types of benefits that were beginning to appear
frequently in employee benefit packages (thrift savings plans and paid military leave, for example). These emerging benefits
were originally listed in EBS publications under the category “Other benefits.” The EBS conducted annual surveys from 1981
to 1998, at which time BLS introduced the National Compensation Survey (NCS).1 Throughout this article, references to
years indicate the year in which the survey was conducted. Typically, the data were published 1 or 2 years after they were
collected.
Over the years, BLS modified the list of other benefits many times, adding new types of benefits that were showing up in the
workplace with some consistency. Some types of benefits grew substantially and therefore were moved from the other
benefits category to a category with a more permanent status. For example, in the mid-1980s, thrift savings plans became
part of Defined contribution plans, as various types of contributory retirement plans became a prominent form of retirement
savings. Benefits that showed no growth, or remained rare after their introduction, were subsequently dropped from the
survey. Under the NCS, other benefits were listed under a variety of table headers: “Family-related benefits,” “Selected
benefits,” and “Quality-of-life benefits.” The shifting of categories is evidence of the ever-changing nature of employee
benefits in the workplace. For the remainder of this article, these emerging benefits are referred to simply as “other benefits.”
BLS strives to publish data that reflect the current labor market; hence, it is important that the types of benefits surveyed
remain current. The NCS monitors developing trends in compensation practices by researching benefits literature and by
relying on reports from BLS field economists, who have constant contact with human resources staff in sampled
establishments. Also, BLS is sensitive to the burden placed on survey respondents and attempts to reduce that burden
whenever possible.2 The most recent adjustment to the list of benefits reduced the number of other benefits studied from 28
to 23, with the following five benefits dropped: 1) adoption assistance, 2) educational assistance, 3) employer-provided home
computers, 4) recreation benefits,3 and 5) travel accident insurance.
The statistical history of data in the other benefits category is complex, not only because of the introduction and removal of
various benefits over the years, but also because of the changing scope, measurement concepts, and definitions of these
benefits used by the surveys. As a result, comparing the estimates of benefits over time should be done with caution. This
article provides a resource for understanding these changes in the surveys and a guide for understanding the data. For all
the benefits analyzed in this article, the surveys measure the percent of workers who had the benefit available to them, not
the percent who used the benefit. The first part of the article provides a general overview of BLS benefits surveys over time,
and the second part focuses on the five benefits that were recently dropped from the NCS.
Overview Of BLS Benefits Surveys
Background. In 1979 and 1980, BLS conducted pilot surveys on employer-provided benefits, leading to the establishment of
the Employee Benefits Survey (EBS) program, which began publishing annual survey data in 1981. In 1981, BLS published
Page 1
COMPENSATION AND WORKING CONDITIONS
U.S. BUREAU OF LABOR STATISTICS
EBS data on the percent of all full-time workers in medium and large private industry establishments (for most years, those
with 100 or more workers) providing specific types of benefits.4 The types of benefits included prominent benefits such as
health insurance and retirement plans.5 EBS data were also published that showed the percent of workers receiving other
benefits, which included separate estimates on the incidence of paid military leave; paid funeral leave; profit sharing, savings,
and stock plans; severance pay; employee discounts; gifts; in-house infirmary; relocation allowances; recreational facilities;
subsidized meals; educational assistance; parking; and use of company automobile. From 1981 to 1984, no estimates for “all
full-time workers” were published for other benefits; only separate estimates for full-time “professional and administrative,”
“technical and clerical,” and “production” employees were published.
Changes in scope and level of detail. The EBS changed in scope over the years, expanding the survey to small private
industry establishments and to State and local government establishments. To reduce costs, the EBS conducted surveys in
alternate years, with data for medium and large private establishments published one year and those for small private and
State and local government establishments the next year.
The National Compensation Survey (NCS) published its first benefits estimates in 2001.6 The estimates, which were for
survey year 1999, were on employer-provided benefits for workers in private industry, with separate estimates for full-time
workers in establishments of any size; part-time workers in establishments of any size; all workers in establishments with 1 to
99 employees; and all workers in establishments with 100 or more employees.7 Since its inception in 1999, the NCS has
expanded the scope of workers for the benefits portion of the survey. The NCS began publishing estimates on employee
benefits in State and local government establishments in March 2008 (with a reference date of September 2007). The NCS
began publishing estimates for all civilian workers (those in private industry and in State and local government, as defined by
the NCS), in addition to separate estimates for private industry workers and State and local government workers, in August
2008 (with a reference date of March 2008).8 (See appendix tables A and B for a summary of the differences in survey scope
for the 1981-2008 period. For all the benefits analyzed in this article, the surveys measured the percent of workers who had
the benefit available to them, not the percent who used the benefit.)
Five Benefits Recently Dropped
As noted previously, changes in scope and level of detail over many years require that comparisons be made with caution.9
To simplify this discussion, the analysis of recently dropped benefits focuses on the benefits estimates for full-time workers in
medium and large private industry establishments. One major limitation to comparisons between EBS and NCS data is the
fact that published EBS data on full-time workers in medium and large private establishments are available for 1981-86,
1988-89, 1991, 1993, 1995, and 1997 (all years except those in which surveys of small private establishments or State and
local governments were conducted), while published NCS data on full-time workers in all establishments (with no
subcategory by establishment size) are available for 1999-2000 and 2003-2008. In addition, the two surveys do not provide
published data within the same establishment and work categories. To make an imperfect, but practical, comparison, Table 1
includes data for full-time workers in medium and large private establishments for the period from 1981 to 1997 and full-time
workers in all private industry establishments for the 1999-2008 period.
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Table 1. Percent of full-time workers in private industry establishments(1), selected employer-provided benefits,
1981-97 and 1999-2008
Educational assistance(2)
Year
Adoption
Assistance
Employer
Fully
and
paid by
employee
employer(4) share
cost(4)
Work
related
Recreation benefits
Nonwork
related
Employerprovided
home
computers
Recreational facilities(3)
Employer
Fully
and
paid by
employee
employer(4) share
cost(4)
Employer
and
employee
cost not
specified
Travel
Accident
Fitness
centers(5)Insurance
1981-97
1981
--
30
48
--
--
--
10
10
21
--
--
1982
--
29
53
--
--
--
12
14
--
--
--
1983
--
26
56
--
--
--
13
16
--
--
--
1984
--
29
53
--
--
--
17
16
--
--
--
1985
--
27
49
--
--
--
--
--
33
--
52
1986
--
--
--
--
--
--
--
--
--
--
--
1988
5
--
--
70
18
--
--
--
25
--
49
1989
5
--
--
69
19
--
--
--
28
--
53
1991
8
--
--
72
23
--
--
--
26
--
42
1993
7
--
--
72
22
--
--
--
27
--
44
1995
11
--
--
65
18
--
--
--
--
19
41
1997
10
--
--
67
20
--
--
--
--
21
42
1999-2008
1999
6
--
--
47
12
--
--
--
--
10
22
2000
6
--
--
44
11
--
--
--
--
10
17
2003
10
--
--
--
--
3
--
--
--
--
--
2004
11
--
--
--
--
3
--
--
--
--
--
2005
11
--
--
56
16
3
--
--
--
14
26
2006
12
--
--
56
16
3
--
--
--
14
25
2007
12
--
--
56
17
3
--
--
--
14
25
2008
13
--
--
56
17
3
--
--
--
15
26
Footnotes:
(1) Estimates from 1981 through 1997 include only full-time workers in medium and large establishments (those with 100 or more workers);
estimates from 1999 through 2008 include full-time workers in establishments with 1 worker or more.
(2) From 1981 through 1985, data on educational assistance were provided on the basis of whether the benefit was fully or partially paid for
by the employer. Beginning in 1988, data were provided on whether the benefit was work related or nonwork related.
(3) After 1984, method of funding (e.g., all or partial payment by employer) was no longer separated.
(4) Small percentages of workers were in firms in which some, but not all, workers were eligible for the benefit. These numbers are not
included here.
(5) Fitness center benefits include those fully paid by the employer and those for which the employer and employee share the cost. Fitness
centers and recreational facilities are defined differently; see Appendix for NCS definitions.
Note: The 1981–84 data are for professional and administrative workers only. Dashes indicate no data were collected or published.
Educational assistance. Educational assistance is the only special benefit that was studied in the inaugural year of the
survey (1981) and remained in the list of “other benefits” through 2008. EBS data on educational assistance from 1981 to
1984 (shown in table 1) include only full-time, professional and administrative workers10 in medium and large private
establishments who were eligible to participate in plans for which the employer either paid all or part of the expenses. The
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COMPENSATION AND WORKING CONDITIONS
U.S. BUREAU OF LABOR STATISTICS
percent of workers offered full or partial reimbursement for educational benefits was relatively constant from 1981 to 1985.
The collection of data on whether educational assistance was fully or partially funded by the employer was dropped in 1988,
and the EBS began collecting data on whether the assistance was job-related or not. Both types of educational assistance
remained fairly steady through 1997, when 67 percent of workers were offered job-related assistance and 20 percent were
offered non-job-related assistance. In 1999, after the NCS was introduced, estimates that include full-time workers in small,
medium, and large establishments showed that 47 percent of these workers had access to work-related educational
assistance; by 2005, that figure had risen to 56 percent and remained steady through 2008. Twelve percent of full-time
workers in private industry had access to non-work related educational assistance in 1999; by 2008, that figure had increased
to 17 percent.
Recreational benefits. Recreational facilities as an employer-provided benefit was collected in 1981 and remained on the
list through the mid-1990s. For the first four survey years (1981–84), separate estimates were published on the percent of
professional and administrative workers in plans where the employer either fully or partially defrayed the expenses. The
percent of professional and administrative workers eligible to use employer-subsidized recreational facilities increased from
about 20 percent in 1981 to 33 percent for all full-time workers in medium and large private establishments in 1985; by 1993,
that figure had decreased to 27 percent. In 1994, the EBS dropped the collection of data on recreational facilities benefits and
began collecting data on fitness center benefits.
In 1995, 19 percent of full-time workers in medium and large private establishments were eligible for fitness center benefits, a
figure that climbed to 21 percent in 1997. In the 1999 estimates, which include full-time workers in establishments of any size,
the comparable figure dropped to 10 percent. This can be explained in part by the inclusion of small private establishments,
which typically are less likely than larger establishments to offer such benefits. The 2005–08 estimates show a slightly higher
rate of access, at 14 to 15 percent. Still, fitness center benefits have remained somewhat uncommon among full-time private
industry workers.
Adoption assistance. Adoption assistance was introduced into the EBS in 1988. That year, 5 percent of full-time workers in
establishments with 100 or more workers were eligible for this benefit. The percent of workers provided the benefit ranged
from 5 to 11 percent between 1988 and 1997. From 1999 to 2008, the percent ranged from 6 percent to 13 percent. Although
survey scope and size of establishments covered differ in the two surveys, the EBS and NCS estimates show that adoption
assistance has remained a relatively rare benefit.
Employer-provided home computers. In the short period that information on employer-provided home computers was
collected (2003 through 2008), the percent of workers with access to the benefit never exceeded 3 percent for full-time
workers. Hence, it was dropped from the survey.
Travel accident insurance. Information on travel accident insurance was first collected in 1985. In that year, 52 percent of
all full-time workers in medium and large private establishments were provided this benefit. The percentage dropped to 42
percent in 1997. In 1999, with smaller private establishments included in the estimate, only 22 percent of full-time workers
had access to travel accident insurance. The percentage remained relatively steady, with 26 percent of full-time workers in all
private industry being offered the benefit in 2008.
Conclusion
As a result of monitoring compensation trends in the labor market, efforts to comply with the directive to reduce respondent
burden whenever possible, and the careful consideration of years of published data have compelled BLS to drop five types of
benefits from the National Compensation Survey. The benefits dropped remained rare among workers in private industry,
were not in great demand, or showed little growth in recent years. Comparisons of the employer-provided benefits estimates
from year to year must be made with caution because of the changing scope and definitions used by the surveys. At the
same time, the changing definitions of employer-provided benefits over the years, first in the EBS and then in the NCS,
attests to the fact that the compensation field is constantly changing. The benefits studied under the NCS will no doubt
continue to change in the future, as BLS strives to provide the public with data that are of the utmost relevance.11
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Appendix
Table 1 provides selected published estimates for the five benefits being dropped from the National Compensation Survey. Because the
scope of the surveys varied over the period from 1981 to 2008, only broad conclusions should be made from these data when analyzing
changes over time. Historical benefits data for the NCS and its predecessor surveys can be found in the 2009 National Compensation
Survey Publications List, on the Internet at http://www.bls.gov/ncs/ncspubs.htm.
The data in tables A and B show some of the differences in the survey scope over the 1981–2008 period. The gaps in the annual data
indicate that there were no comparable data for the missing years or no survey was conducted that year.
Table A. Scope of survey, full-time workers in medium and large private industry establishments, Employee
Benefits Survey, 1981–97.
Year
1981-1986
Establishment size
Occupational group
The minimum employment size
was 50, 100, or 250, depending
on the industry (1)
1988-89
100 or more workers
1991, 1993,
1995, 1997
100 or more workers
Professional and administrative;
technical and clerical; and
production workers
Professional and administrative;
technical and clerical; and
production and service workers
Professional and technical; clerical
and sales, and blue-collar and
service workers
Sector
Geography
Private
US except Alaska
and Hawaii
Private
US except Alaska
and Hawaii
Private
United States
Footnotes:
(1) For industry size details, see Employee Benefits in Medium and Large Private Establishments in the United States, 1981,
Bulletin 2140 (Bureau of Labor Statistics, August 1982), p. 43; available on the Internet at http://www.bls.gov/ncs/ebs/sp/ebbl0038.pdf.
NOTE: The EBS produced data from 1981 through 1997. This study uses data from only medium and large private establishments
surveyed under the EBS; to simplify the analysis, small private establishments and State and local government establishments are
excluded. The EBS published data on medium and large private establishments in 1986; however, no benefits in the "Other benefits"
category were published that year. Beginning in 1999, when the National Compensation Survey took over the collection and publication of
benefits data, establishments with 1 to 99 workers were added to the survey.
Table B. Scope of survey, full-time workers in private industry establishments with one or more workers, National
Compensation Survey, 1999 - 2008
Year
1999-2000
2003-06
2007-08
Establishment
size
1 or more
workers
1 or more
workers
1 or more
workers
Occupational group
Sector
Professional and technical; clerical and sales, and blue-collar and
service workers
Private
White-collar, blue-collar and service workers
Private
Management and professional; service; sales and office; natural
resources, construction, and maintenance; and production,
transportation, and material moving.
Private
Geography
United
States
United
States
United
States
Definitions For The Five Discontinued NCS Benefits
Adoption assistance. Financial aid given to either single or married employees for the purpose of covering all or part of the cost of
adopting a child.
Educational assistance. Educational allowances provide employees with assistance in paying for tuition and/or books for training and
education courses that permit the employee to acquire additional general knowledge or to develop particular knowledge or skills.
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COMPENSATION AND WORKING CONDITIONS
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Employer-provided home computers. This employer-provided benefit helps the employer by giving the employee access to company
data and the employees work projects. If the employee cannot go into the office they may still be productive by using his or her home
computer.
Employers may purchase the computers outright and provide them to employees. Other options include the following:
• Allowing employees to lease computers at a nominal rate with the employee owning the computer at the end of the lease
• Loans at low or no interest rates
• Computer subsidies or grants
If an employer only provides a home computer as part of a flexible workplace arrangement, employees are not considered as having
employer-provided home computers.
Fitness Center Benefit. A program where the employer fully or partially pays the cost of membership in a fitness center or health club. The
club or center may be on or off the employers premises.
Note: The former benefit type “recreation facilities” is a more inclusive category than the more recent “fitness centers” benefit. Employersubsidized recreational facilities can include golf clubs, swimming pools, tennis courts, and other similar facilities, whether they are provided
on-site, off-site, or whether membership dues are reimbursed in full or in part by the employer.
Travel accident insurance (also called “travelers insurance”). A specific form of accidental death and dismemberment insurance that
provides payments in the event of death or injury of an employee who is traveling on company business.
John E. Buckley
Economist, Division of Compensation Data Analysis and Planning, Office of Compensation and Working Conditions, Bureau of
Labor Statistics.
Telephone: (202) 691-6299; E-mail: Buckley.John@bls.gov.
Notes
1 The National Compensation Survey started collecting data on occupational wages and employer cost of total compensation (wages and
benefits, according to NCS definition) in 1996.
2 The Paperwork Reduction Act of 1980 is the Federal legislation that established the principle that surveys should minimize reporting burden.
The text of the Paperwork Reduction Act can be found on the National Archives website at http://www.archives.gov/federal-register/laws/
paperwork-reduction/3501.html.
3 Recreation benefits, a category used only for discussion purposes in this article, includes recreation facilities and fitness centers. See
appendix for definitions.
4 See appendix for details.
5 EBS published more extensive incidence data on paid holiday, vacation, and personal leave; work schedules; paid lunch time and rest time;
sick leave; health insurance for employees; health insurance for dependents; retirement pensions; life insurance; accident and sickness
insurance; and long-term disability insurance, including the percent of employees offered various plan provisions. Plan provisions included a
wide variety of measures, for example, the number of days of paid holidays per year, the annual coinsurance limit of major medical coverage,
and whether the minimum service requirement of a pension plan is based on age, years of service, or both.
6 See Employee Benefits in Private Industry, 1999, USDL 01-43 (U.S. Department of Labor), December 19, 2001; available on the Internet at
http://www.bls.gov/ncs/ebs/sp/ebnr0006.pdf.
7 The NCS published benefits estimates for additional establishment size categories in 1999, 2007, and 2008.
8 See Employee Benefits in State and Local Government--September 2007, USDL 08-0408 (U.S. Department of Labor) March 25, 2008;
available on the Internet at http://www.bls.gov/news.release/ebs3.nr0.htm; see also Employee Benefits in the United States, March 2008,
Bulletin 2715 (Bureau of Labor Statistics, September 2008); available on the Internet at http://www.bls.gov/ebs/#bulletins.
9 Although standard errors have been calculated for the 2008 estimates presented in this article, no standard errors have been calculated for
the 1981–2007 estimates; therefore, the quality of comparisons made cannot be verified with a statistical test.
10 EBS published separate estimates for professional and administrative employees, technical and clerical employees, and production
employees in the early years of the survey. Estimates for all occupations were not published for other benefits until 1985.
11 The following link provides the most recent data on employer-provided employee benefits: www.bls.gov/ncs/ebs.
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U.S. Bureau of Labor Statistics | Division of Information and Marketing Services, PSB Suite 2850, 2 Massachusetts Avenue, NE Washington, DC
20212-0001 | www.bls.gov/OPUB | Telephone: 1-202-691-5200 | Contact Us
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COMPENSATION AND WORKING CONDITIONS
U.S. BUREAU OF LABOR STATISTICS
Beyond Basic Benefits: Employee Access to Other Types of Benefits, 1979-2008
by John E. Buckley
Bureau of Labor Statistics
Originally Posted: May 29, 2009
Since the late 1970s, the Bureau of Labor Statistics has collected data on employee access to various employer-provided
benefits beyond the basics of health insurance, retirement savings, and vacation, sick and holiday leave. Periodically, BLS
has modified the list of benefits by adding those that were increasing in popularity and dropping those that showed no growth,
remained rare, or had limited user interest.
For many decades, the BLS National Compensation Survey (NCS) and its predecessor surveys have collected and published
data on employee benefits. The early surveys concentrated on the presence among workers of major employee “fringe”
benefits within sampled establishments. (The percent of workers that have enrolled in a particular benefit or have it available
for their use is known as the “incidence rate.”) Generally, the data obtained from surveyed firms were tied to commonly
known benefits for which information was readily available and concepts easily understood. For example, one question might
be, “Does your establishment offer health insurance to a majority of your office or plant workers?” Responses were limited to
Yes, No, or Data not available. If the answer was yes, the funding of the benefit was determined--that is, whether the
employer paid all of the costs or costs were shared by the employee. If a majority in a group was offered a benefit, all
workers were considered covered; if fewer than a majority was offered a benefit, no worker was considered covered.
In the early part of the 20th century, nonwage benefits were sparse, and the term “fringe benefit” was appropriate. In a 2001
article by BLS economists Robert Van Giezen and Albert E. Schwenk, the authors noted that the cost of benefits in the
mid-1920s “was still a very small part of a workers compensation package, accounting for less than three percent of the
employers cost for employee compensation.”1 In recent years, however, that figure has grown considerably. Data from the
BLS Employer Costs for Employee Compensation (ECEC) program show that benefits accounted for about 30 percent of
total compensation in December 2008.2
The advent of the BLS Employee Benefits Survey (EBS) greatly expanded the types of benefit details collected and
published. The EBS was developed in the 1970s, during a period when the Federal Office of Personnel Management initiated
its Total Compensation Comparability (TCC) program, which was designed to compare Federal and private pay and benefits.
In 1979 and 1980, BLS conducted experimental surveys of benefits in medium and large firms.3 The EBS was designed to
provide a timely and comprehensive measure covering all elements of employees nonwage compensation. If the EBS was
to be comprehensive, newly appearing benefits had to be monitored and collected when they showed growth potential. In the
1981 EBS bulletin, a number of these benefits were published as “other benefits,” which covered benefits as disparate as
paid funeral leave, subsidized meals, and employee parking.4 Table 1 shows these “other benefits” data for three
occupational groups in private industry in 1981: professional and administrative, technical and clerical, and production
employees.5
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COMPENSATION AND WORKING CONDITIONS
U.S. BUREAU OF LABOR STATISTICS
Table 1. Other benefits: Percent of full-time employees in medium and large establishments providing specified
benefits by percent of eligible employees, private industry, 1981
Benefit
All workers eligible
Some workers eligible
Professional and administrative employees
Paid leave:
Funeral leave
87
1
Military leave
79
1
Profit sharing
20
5
Savings and thrift
32
8
Stock bonus plans
11
2
Stock purchase plans
16
3
Other stock plans(1)
21
3
53
4
Employee discounts
46
1
Gifts
11
3
In-house infirmary
48
4
Relocation allowance
Profit sharing, savings, and stock plans:
Income continuation plans:
Severance pay
Miscellaneous benefits:
75
9
Full defrayment of expenses
59
5
Partial defrayment of expenses
16
4
Recreational facilities
21
1
Full defrayment of cost
10
1
Partial defrayment of cost
10
(2)
25
4
1
1
24
3
Subsidized meals
Full defrayment of cost
Partial defrayment of cost
Educational assistance
78
4
Full defrayment of expenses
30
2
Partial defrayment of expenses
48
2
67
10
64
8
Parking
Provided at no cost
Provided below commercial rates
2
2
2
25
1
19
1
6
Funeral leave
88
1
Military leave
76
1
Automobile
Without reimbursing the company
Partially reimbursing the company
Technical and clerical employees
Paid leave:
Footnotes:
(1) Other stock plans include Employee Stock Ownership Plans and Tax Reduction Act Stock Ownership Plans.
(2) Less than 0.5 percent.
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COMPENSATION AND WORKING CONDITIONS
U.S. BUREAU OF LABOR STATISTICS
Benefit
All workers eligible
Some workers eligible
Profit sharing, savings, and stock plans:
Profit sharing
21
5
Savings and thrift
26
8
Stock bonus plans
7
2
Stock purchase plans
15
3
Other stock plans(1)
15
4
51
5
Employee discounts
55
2
Gifts
12
3
In-house infirmary
38
7
Relocation allowance
40
5
Full defrayment of expenses
30
4
Partial defrayment of expenses
10
1
Income continuation plans:
Severance pay
Miscellaneous benefits:
Recreational facilities
16
1
Full defrayment of cost
8
(2)
Partial defrayment of cost
8
1
23
5
2
1
21
4
Subsidized meals
Full defrayment of cost
Partial defrayment of cost
Educational assistance
69
3
Full defrayment of expenses
27
1
Partial defrayment of expenses
42
3
61
14
58
11
3
3
1
2
(2)
1
1
1
Funeral leave
83
3
Military leave
64
2
Profit sharing
13
4
Savings and thrift
14
5
Stock bonus plans
5
1
Stock purchase plans
9
1
16
3
Parking
Provided at no cost
Provided below commercial rates
Automobile
Without reimbursing the company
Partially reimbursing the company
Production employees
Paid leave:
Profit sharing, savings, and stock plans:
Other stock plans(1)
Footnotes:
(1) Other stock plans include Employee Stock Ownership Plans and Tax Reduction Act Stock Ownership Plans.
(2) Less than 0.5 percent.
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COMPENSATION AND WORKING CONDITIONS
U.S. BUREAU OF LABOR STATISTICS
Benefit
All workers eligible
Some workers eligible
Income continuation plans:
Severance pay
28
5
46
1
Miscellaneous benefits:
Employee discounts
Gifts
9
2
In-house infirmary
47
3
Relocation allowance
26
5
Full defrayment of expenses
13
4
Partial defrayment of expenses
12
1
15
(2)
Full defrayment of cost
7
(2)
Partial defrayment of cost
8
(2)
11
3
Recreational facilities
Subsidized meals
Full defrayment of cost
Partial defrayment of cost
Educational assistance
1
1
10
1
56
5
Full defrayment of expenses
18
3
Partial defrayment of expenses
39
2
76
6
76
5
1
1
Parking
Provided at no cost
Provided below commercial rates
Automobile
1
1
Without reimbursing the company
1
1
Partially reimbursing the company
(2)
(2)
Footnotes:
(1) Other stock plans include Employee Stock Ownership Plans and Tax Reduction Act Stock Ownership Plans.
(2) Less than 0.5 percent.
The data in table 1 show similarities and differences among the three occupational groups. For example, the percent of
workers who were eligible for funeral leave ranged from 83 percent for production workers to 88 percent for technical and
clerical. In contrast, 75 percent of professional and administrative employees were eligible for relocation allowances, but only
40 percent of technical and clerical employees and 26 percent of production employees were eligible for relocation
allowances.
The “paid leave” category grew over the years, starting only with paid funeral leave and military leave, but expanding to
include paid sick leave, holidays, vacation leave, leave for jury duty, and personal leave, and paid and unpaid family leave.
The items in the “profit sharing, savings, and stock plans” category moved from the “other benefits” category to form an
entirely new category called “defined contribution plans,” which is now part of the retirement benefits category. Several
benefits that were published in 1981 are no longer collected in the NCS, either because they lacked growth potential or
because the costs, in terms of respondent burden and BLS resources, did not justify the collection effort. Table 2 shows the
benefits that were studied at some point between 1979 and 2008 and subsequently dropped from the NCS.
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COMPENSATION AND WORKING CONDITIONS
U.S. BUREAU OF LABOR STATISTICS
Table 2. List of miscellaneous benefits dropped, 1979-2008
Benefit
Years of publication
Adoption assistance
1988-2008
Child care: funds(1)
1995-2008
Child care: on-site or off-site(1)
1995-2008
Child care: resource or referral(1)
2003-2008
Company automobile for personal business
1981-1984
Education assistance: work and nonwork unspecified
1981-1985
Education assistance: work and nonwork specified
1988-2008
Employee discounts
1981-1991
Employer-provided home computers
2003-2008
Eldercare
1989-1995
Financial counseling
1985-1989
Fitness centers
1995-2008
Gifts
1981-1991
In-house infirmary
1981-1993
Paid lunch time
1979-1993
Paid rest time
1980-1993
Parking
1981-1991
Prepaid legal services
1985-1993
Recreational facilities
1981-1993
Relocation allowance
1981-1988
Sabbatical leave
1991
Severance pay
1981-2000
Subsidized meals
1981-1991
Supplemental unemployment benefits
1985-2000
Travel accident insurance
1985-2008
Footnotes:
(1) An estimate of the total (the percent of workers with one or more of the three separate child care items) first appeared in EBS publications
in 1994.
Note: Pilot studies were conducted by the Employee Benefits Survey in 1979 and 1980; annual publications of the Employee Benefits Survey
began with the publication of the 1981 survey year data.
Some of the dropped items had elements that were retained in the later NCS lists of benefits. The three child-care items, for
example, were combined and are shown as one benefit on the new list. In addition, wellness programs now include some of
the activities related to fitness centers. (See the accompanying article by the same author in this issue of CWC Online.)
Two traditional benefits that were included in the EBS--paid lunch time and paid rest time--were dropped from the EBS after
being collected from 1979 through 1993. During that period, in medium and large private establishments, the percent of fulltime workers with a paid lunch time ranged from 13 percent in 1979 to 8 percent in 1991. A paid rest time was much more
widespread than a paid lunch time, but the percent with the benefit dropped from its high of 76 percent in 1982 to 67 percent
in 1991. The two benefits were eliminated from the survey because they showed little growth over time, there was limited
public interest in them, and the collection costs could no longer be justified.6
Recently, there has been a renewed interest in rest time, in the form of napping. Some advocates of a napping break
maintain that there is a productivity gain rather than a loss when napping is allowed, because the employee returns from his
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COMPENSATION AND WORKING CONDITIONS
U.S. BUREAU OF LABOR STATISTICS
or her break feeling more energized. In an article by stress management consultant Elizabeth Scott, the author notes that
because there are “pros and cons to each length of sleep” any amount can be helpful. “If you only have 5 minutes to spare,”
she writes, “just close your eyes; even a brief rest has the benefit of reducing stress and helping you relax a little, which can
give you more energy to complete the tasks of your day.”7
For 2009--that is, published data collected after March 2008--the NCS once again changed the list of benefits to better reflect
current practices in the benefits environment, to conserve both BLS and respondent resources, and to drop items that were
rarely encountered, showed no growth, and had limited user interest.
Over the years, there were several different lists of “other benefits,” with the list for 2009 collecting data on 23 benefits, down
from the 28 benefits collected for the 2008 survey year. Table 3 shows some of the benefits previously collected, some new
benefits, and some benefits that existed but have been changed, such as combining a three-part child-care benefit into one
question, the addition of retiree health plans for those under 65 years of age and those 65 years and older, and financial
planning benefits.
Table 3. Percent of private industry workers with access to quality-of-life benefits, pretax benefits, and miscellaneous
benefits, and survey status of benefit item, National Compensation Survey, March 2008
Benefit(1)
Percent of workers with access(2)
Kept or dropped for 2009 survey year?
Quality of life benefits
Education assistance of any type
(3)
Dropped
Work related
50
Dropped
Nonwork related
15
Dropped
Adoption assistance
11
Dropped
Child-care assistance(4)
15
Kept
3
Kept
5
Kept
11
Kept
31
Kept
5
Kept
Employer-provided funds
On-site and off-site childcare
Child-care resource and referral services
Dependent care reimbursement account
Flexible workplace
Employer-provided home computers
Employee assistance programs
Subsidized commuting
2
Dropped
42
Kept
6
Kept
Long-term care insurance
13
Kept
Fitness centers
13
Dropped
17
Kept
Pretax benefits
Cash or deferred arrangements with no
employer contribution(5)
Footnotes:
(1) For definitions, see the Technical Note in National Compensation Survey: Employee Benefits in Private Industry in the United States,
March 2007, Summary 07-05 (Bureau of Labor Statistics, August 2007), pp. 37-39; available on the Internet at http://www.bls.gov/ncs/ebs/sp/
ebsm0006.pdf.
(2) All workers in private industry = 100 percent
(3) An estimate for the entire category is not available.
(4) The total is less than the sum of individual child-care provisions because many employees have access to more than one of the benefits.
(5) Cash or Deferred Arrangements with no Employer Contribution is the new title for out-of-scope salary reduction plans. There was no
change in the definition.
(6) Items listed under "Miscellaneous benefits" may have appeared under other categories in other years.
(7) Stock options moved to the "nonproduction bonuses" category.
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Benefit(1)
Percent of workers with access(2)
Health savings account
Kept or dropped for 2009 survey year?
8
Kept
(3)
Kept
Flexible benefits
17
Kept
Health care reimbursement account
33
Kept
31
Kept
8
Kept
Section 125 cafeteria benefits
Dependent care reimbursement accounts
Miscellaneous benefits (6)
Stock options(7)
Wellness programs
25
Kept
Job-related travel accident insurance
23
Dropped
Footnotes:
(1) For definitions, see the Technical Note in National Compensation Survey: Employee Benefits in Private Industry in the United States,
March 2007, Summary 07-05 (Bureau of Labor Statistics, August 2007), pp. 37-39; available on the Internet at http://www.bls.gov/ncs/ebs/sp/
ebsm0006.pdf.
(2) All workers in private industry = 100 percent
(3) An estimate for the entire category is not available.
(4) The total is less than the sum of individual child-care provisions because many employees have access to more than one of the benefits.
(5) Cash or Deferred Arrangements with no Employer Contribution is the new title for out-of-scope salary reduction plans. There was no
change in the definition.
(6) Items listed under "Miscellaneous benefits" may have appeared under other categories in other years.
(7) Stock options moved to the "nonproduction bonuses" category.
Table 3 also shows the percent of workers with access to “other benefits” in 2008. (Employees are considered as having
access to a benefit plan if it is available for their use.) The benefits with the highest rate of worker access were work-related
education assistance (50 percent) and employee assistance programs (42 percent). Among the benefits with lower access
rates, 2 percent of workers in private industry had access to employer-provided personal computers for home use, and 3
percent of workers had access to employer provided child-care funds.
Some of the “other benefits” items published in 1981 are no longer in the NCS program, while others are now regularly
studied. This is a direct result of the NCS keeping pace with changes in the labor market and responsive to data users
requests. Since 1981, paid funeral and military leave became part of the regularly studied benefits. In 1981, approximately 88
percent of private industry employees were eligible for paid funeral leave; the estimate for 2008 was 69 percent. The estimate
for paid military leave also declined, from about 80 percent in 1981 to 48 percent in 2008. Education assistance is another
benefit that had published estimates in 1981 and 2008. About 78 percent of employees were eligible to get the benefit in the
earlier period and approximately 65 percent had access in 2008.8
John E. Buckley
Economist, Division of Compensation Data Analysis and Planning, Office of Compensation and Working Conditions, Bureau of
Labor Statistics.
Telephone: (202) 691-6299; E-mail: Buckley.John@bls.gov.
Notes
1 Robert Van Giezen and Albert E. Schwenk, “Compensation from before World War I through the Great Depression,” Compensation and
Working Conditions, fall 2001, p.19.
2 The Employer Costs for Empoyee Compensation (ECEC) data provide estimates of employer costs per hour worked for employee
compensation, with the benefits broken down by cost and percent for the component parts. For example, in table 1 of the publication providing
December 2008 ECEC data, employer costs per hour worked for employees insurance totaled $2.45 (or 8.4 percent of total costs), with
health insurance accounting for most of the insurance bill, $2.31 (or 7.9 percent of total costs). See Employer Costs for Employee
Compensation--December 2008, USDL 09-0247 (U.S. Department of Labor), March 12, 2009; available on the Internet at http://www.bls.gov/
news.release/archives/ecec_03122009.htm.
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3 Medium and large establishments are those with 100 or more workers, except for the early years of the Employee Benefits Survey, when
employment size varied by industry. For more information on establishment size, see the technical note in Employee Benefits in Medium and
Large Firms, 1981, Bulletin 2140 (Bureau of Labor Statistics, August 1982), pp. 41–44; available on the Internet at http://www.bls.gov/ncs/ebs/
sp/ebbl0038.pdf.
4 See Employee Benefits in Medium and Large Firms, 1981, Bulletin 2140.
5 The data in table 1 are from Employee Benefits in Medium and Large Firms, 1981, Bulletin 2140.
6 For more information, see Hilery Simpson, “Paid Lunch and Paid Rest Time Benefits: Highlights from the Employee Benefits Survey,
1979-93,” Compensation and Working Conditions, December 1996, pp. 18-23.
7 See Elizabeth Scott, “Sleep Benefits: Power Napping for Increased Productivity, Stress Relief & Health,” About.com: Stress Management,
updated July 7, 2008; available on the Internet at http://stress.about.com/od/lowstresslifestyle/a/powernap.htm.
8 Additional 2008 estimates of “other benefits” are available on the BLS website at http://www.bls.gov/ncs/ebs/benefits/2008/
benefits_other.htm.
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