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The NLSY97: An Introduction

The NLSY97:
an introduction
The National Longitudinal Survey of Youth 1997
follows the lives of 12- to 16-year-olds
as they make pivotal decisions
regarding education and employment
Michael Horrigan
and
James Walker

Michael Horrigan is director of the National
Longitudinal Surveys
Program in the Office
of Employment and
Unemployment Statistics, Bureau of Labor
Statistics. James Walker
is professor of economics at the University of
Wisconsin-Madison
and is principal investigator for the NLSY97.
E-mail:
horrigan_m@bls.gov

T

his issue of the Monthly Labor Review
introduces readers to the newest addition
to the family of surveys sponsored by the
National Longitudinal Surveys (NLS) Program of
the Bureau of Labor Statistics (BLS). Termed the
NLSY97, the respondents to this survey are individuals who were aged 12 to 16 on December
31, 1996. The first set of interviews began January 1997 (hence, the NLSY97), and members of
this longitudinal cohort have been interviewed
on an annual basis ever since. This survey is
conducted as an in-person interview, with the
field interviewer entering the respondent’s answers into a laptop computer—sometimes called
a Computer Assisted Personal Interview (CAPI).
Designed as a longitudinal survey, the NLSY97
follows the lives of these young men and women
as they make pivotal decisions as to whether they
should continue their education after high school
or choose an occupation and enter the world of
work. We follow the progression of their lives
as they become independent adults, settle into
careers, form relationships, and make decisions
about cohabitation, marriage, and the formation
of families.
A key difference between cross-sectional surveys (such as the Current Population Survey)
and longitudinal surveys (such as the NLSY97) is
that annual interviews with the same individuals
enable researchers to chronicle important events

that individuals experience over the course of
their lifetimes. For example, the collection of
data on jobs held by sample members allows the
construction of a week-by-week history of every job held (and the characteristics of those
jobs) since the age of 14. Knowledge of the employment history of individuals, coupled with
the rich array of the socioeconomic and demographic information collected in each interview,
gives researchers the ability to investigate and
isolate how the choices individuals make at
younger ages can affect outcomes later in life.
For example, does working during the school
year while in high school have a net positive or
negative impact on labor market success as
adults?
This issue of the Monthly Labor Review contains five articles that use data from the first
round of interviews with the NLSY97 cohort.
These articles, which are described briefly below, investigate important aspects of the early
labor market experiences of these youths. The
NLSY97 questionnaires, however, collect information on a much wider set of topical areas,
reflecting the complexity of the lives of our respondents. The diversity of questions also reflects the interest and mission of our partners in
the Federal Government. A number of Federal
Government agencies have and continue to provide funding support for various questionnaire

Monthly Labor Review

August 2001

3

The

NLSY97:

An Introduction

modules in the NLS family of surveys, including the NLSY97.
In the first round of interviews, information was collected
about the youths’ relationships with their parents, contact
with absent parents, marital and fertility histories to date,
and sexual activity. Funding support was received from the
National Institute for Child Health and Human Development
for these question modules. With support from the Office of
Juvenile Justice and Delinquency Prevention, modules were
constructed that asked respondents about criminal behavior,
contact with the criminal justice system, and alcohol and
drug use. Areas of the youth survey that are potentially sensitive, such as sexual activity and criminal behavior, are
asked in a self-administered portion of the survey in which
the respondent listens to the questions on earphones and
types his or her answers directly into the laptop computer.
In addition, just prior to the first round of interviews with
the NLSY97 cohort, BLS conducted a survey of schools to determine the nature and extent of school-to-work programs.
This survey of schools (and a follow up survey conducted in
2001) provides a valuable complement to the data on these
programs reported by the NLSY97 respondents. Funding from
the Departments of Education and Labor’s National Schoolto-Work Office provided support for both the surveys of
schools and for the development of a questionnaire module
on School-to-Work programs that have been included in the
NLSY97 first round interview.
Funding was also received from the Department of Defense to identify a sample of 18- to 23-year-olds and a separate sample of youth entering 10th–12th grades for the purpose
of administering the Armed Services Vocational Aptitude
Battery (ASVAB) examination. This test is designed to serve
as the basis for constructing civilian test norms against which
the scores of enlistees to the Armed Services can be compared. The ASVAB examination also was administered to the
NLSY97 cohort, thereby providing an important measure of
skill level at a point in time.
Finally, in this first round of the NLSY97, BLS also decided
to conduct an interview with a parent or parent figure for
each youth respondent. These interviews provide a tremendous amount of context for understanding the lives of our
youth respondents. During the parent interview, retrospective (lifetime) information was collected from the parent
about the youth respondent’s health while growing up, the
schools the youth attended, and the history of the youth’s
living arrangements. Also, the parent being interviewed was
asked to report his or her own lifetime history of employment, education, training, marriages, and fertility, as well as
provide the same information for his or her spouse. Question modules on family income and assets and participation
in government assistance programs also were administered.
Finally, many of the same “attitude” questions asked of the

4

Monthly Labor Review

August 2001

youths about their parents were also asked of the parents
about their children.
To begin exploring the richness of these data, the NLS program cosponsored a conference on November 18–19, 1999,
with the Joint Center for Poverty Research (Northwestern
University and the University of Chicago) to present findings from the first round of NLSY97 interviews. Selected papers
from this conference are being published in three venues: the
Journal of Human Resources (JHR); a special volume of papers
being published by the Russell Sage Foundation entitled
Social Awakenings: Adolescent Behavior as Adulthood Approaches, edited by Robert T. Michael (New York, Russell
Sage Press, 2001); and the articles contained in this issue of
the Review. A listing of titles from both the JHR and the
Russell Sage volumes gives an idea of the breadth of research that has already resulted using data from the NLSY97.1
The NLSY97-based articles being published in this issue
of the Review emphasize more traditional labor market topics.
Mary Joyce and David Neumark, in their article, “Schoolto-work programs: information from two surveys,” examines the degree to which youths participate in “school-towork” programs. Based on the 1994 School to Work Opportunity Act, a variety of programs have been set up in our
Nation’s schools designed to help youth make the transition
from school to the world of work. Although the NLSY97 cohort is still too young to investigate the impact of participation in the programs on subsequent labor market outcomes,
Joyce and Neumark have been able to determine which
youths were most likely to have participated in these programs.
The other articles in this issue closely examine the nature
and extent of youth employment. The article by Lynn Huang,
Michael Pergamit, and Jamie Shkolnik, “Youth initiation
into the labor market,” examines the employment experiences of 12 and 13 year olds. The NLSY97 questionnaire
makes a concerted effort to collect information on work experiences of respondents when they were very young.
Donna Rothstein’s article, “Youth employment in the United
States,” examines the prevalence of working while aged 14–
16. She examines traditional employee jobs in which youths
have an ongoing relationship with a particular employer,
such as a restaurant or supermarket, and “freelance” jobs,
where the youth is doing one or a few tasks for several people
but has no “boss.” Examples of freelance jobs are babysitting
and yard work.
Rothstein’s other article, “Youth employment during
school: results from two longitudinal surveys,” examines
employment patterns during the school year for both the
NLSY79 cohort (aged 14–21 on December 31, 1978) and the
NLSY97 cohort. She also presents findings in the literature as
to how the youth’s working while in high school impacts his

or her life as an adult.
Rosella Gardecki’s article, “Racial differences in youth
employment,” looks at the differences by racial group in their
decisions to work while young. Part of her focus is on examining how working while young (age 14) affects the likelihood that an individual will choose to work as an older
teen (age 16). She examines patterns of employment behavior on the basis of racial differences, and, at the same time,
accounts for differences among youth on the basis of certain
other individual characteristics (highest grade in school, participation in criminal activity, for example), family characteristics (employment status of parent(s), type of family, for
example), and neighborhood and geographic factors (such
as, the local unemployment rate or county poverty rate).
FUTURE DIRECTIONS OF THE SURVEY will be to continue collecting core labor market information and introduce age-appropriate specialized questionnaire modules. As of this writing,
the NLSY97 has just completed the fourth round of interviews,
and public-use data from the third round of interviews have
recently become available. The NLSY97 is constantly intro-

ducing new questionnaire modules that reflect the changing
nature of the lives of our respondents as they enter their early
twenties. For example, one question module will explore
whether these young adults decide to attend college, and if
so, how the youth respondents arrived at their particular
choice of college. As our youth respondents become parents, they will be asked questions on how they handle
childcare responsibilities. We also plan a series of questions
on the various relationships our respondents enter into as
young adults, with an emphasis on dating, cohabitation, and
the decision to marry. As we introduce these specialized
modules, we will continue to ask a core set of questions on
labor market experiences, education, and training. The
NLSY97 is an exciting new source of longitudinal information that will provide social science researchers with a rich
database to use in studying the impact of public policies. It
also will provide valuable insights into the dynamic processes
that influence the pathways that are taken through life. We
do hope you enjoy the articles in this issue, and we look
forward to seeing a new generation of research articles using this valuable source of longitudinal data.
□

Notes
1
The titles are as follows. In the Journal of Human Resources, volume 36, issue 4: “Measuring Poverty in the NLSY97,” by Carolyn J. Hill
and Robert T. Michael; “Evaluating School-to-Work Programs Using the
New NLSY,” by David Neumark and Mary Joyce; “The Role of Parental
Allowances in Determining Youth Employment,” by Sabrina Wulff
Pabilonia; “Rising College Expectations Among Youth in the U.S.: A
Comparison of 15 and 16 Year Olds in the 1979 and 1997 NLSY,” by John
Reynolds and Jennifer Pemberton; “Savings of Young Parents,” by
Annamaria Lusardi, Ricardo Cossa, and Erin L. Kleindorfer; “Does Head
Start Yield Long-Term Benefits?” by Alison Aughinbaugh.
In Social Awakenings: Adolescent Behavior as Adulthood Approaches,
the titles are: “A Lens on Adolescence: The 1997 National Longitudinal
Survey of Youth,” by Robert T. Michael; “The Effect of Family Structure on Youth Outcomes in the NLSY97,” by Charles R. Pierret; “Patterns
of Nonresident-Father Involvement,” by Laura M. Argus and H. Elizabeth Peters; “Parental Regulation and Adolescent Discretionary Time-

Use Decisions: Findings from the NLSY97,” by Robin L. Tepper; “Family
Environment and Adolescent Sexual Debut in Alternative Household
Structures,” by Mignon R. Moore; “Exploring Determinants of Adolescents’ Early Sexual Behavior,” by Robert T. Michael and Courtney
Bickert; “Body Weight and the Dating and Sexual Behaviors of Young
Adolescents,” by John Cawley; “Adolescents’ Expectations Regarding
Birth Outcomes: A Comparison of the NLSY79 and NLSY97 Cohorts,” by
James R. Walker; “Who are Youth ‘At Risk’? Expectations Evidence in
the NLSY97,” by Jeff Domnitz, Charles F. Manski, and Baruch Fischhoff;
“Food Stamp Program Participation and Health: Estimates from the
NLSY97,” by Diane Gibson; “What Determines Adolescent Demand for
Alcohol and Marijuana? A Comparison of Findings from the NLSY79 and
the NLSY97,” by Pinka Chatterji; “Changes in Gender and Racial Gaps in
Adolescent Antisocial Behavior: The NLSY 79 versus the NLSY 97,” by
Yasuyo Abe; and “City Kids and Country Cousins: Rural and Urban
Youths, Deviance, and Labor Market Ties,” by L. Susan Williams.

Monthly Labor Review

August 2001

5

Youth Employment

Youth Employment

Youth employment
in the United States
Data from the National Longitudinal Survey
of Youth 1997 show substantial work activity
among 14- and 15-year-olds
Donna S. Rothstein

T

oday’s youths commonly gain employment
experience through working for a particular
employer, such as a fast-food restaurant, or
through a less formal arrangement, such as
babysitting for a neighbor. The purpose of this
article is to provide a detailed profile of the employment of today’s youths using round-1 data
from a new survey of youth: the National Longitudinal Survey of Youth 1997 (NLSY97). The article
reports the incidence, intensity, and timing of
youth employment (school vs. summer), shows the
industries and occupations in which youths commonly work, and examines employment differences
across gender, race, ethnic group, household income, and family structure.

Data and definitions

Donna S. Rothstein is
a research economist in the Office of
Employment and
Unemployment
Statistics, Bureau of
Labor Statistics.
E-mail:
rothstein_d@bls.gov

6

The data presented are from the first interview of
the NLSY97, a nationally representative sample of
about 9,000 young men and women who were born
between January 1, 1980, and December 31, 1984.1
The first interview took place in 1997, when these
youths were aged 12 to 17 years. The NLSY97 collects extensive information on youths’ labor market experiences, in addition to information on a
wide array of other topics, such as schooling and
family background. Members of the sample are interviewed annually.2
Early work experience can include “employee”
jobs, wherein a youth has an ongoing relationship
with a particular employer, such as a job working in
a supermarket or restaurant, and “freelance” jobs,
in which the youth does one or a few tasks without

Monthly Labor Review

August 2001

a specific “boss,” such as babysitting, mowing
lawns, or working for oneself. The NLSY97 seeks
to gather a longitudinal record of youths’ employment experiences, rather than taking a snapshot of their labor market status at a particular
point in time.3 In order to accomplish this, survey
respondents aged 14 and older are asked to list
all employee jobs they held from the age of 14 to
the date of the interview. A calendar is filled out
by the interviewer and is shown to the respondent to confirm all beginning and ending dates of
employee jobs, as well as any gaps between those
dates within which the respondent did not work.
Respondents also provide other information
about each employee job held, such as the industry and occupation into which the job was classified. Next, respondents 14 and older are asked to
list all freelance jobs they held from the age of 14
to the date of the interview. Again, a calendar is
used to confirm all beginning and ending dates
of freelance jobs. Due to the sporadic nature of
freelance jobs, however, data on periods of
nonwork between those dates are not collected.
Respondents also provide information on the
characteristics of each freelance job they held.
Tables in the sections that follow describe
youth employment in employee jobs and freelance jobs at some time during a specific period,
including “at age 14” and “at age 15.” When a
youth is said to have worked “at age 14,” for example, the reference is to the youth having worked
at some time during the entire 52-week period
between the youth’s 14th and 15th birthdays.4
Because the NLSY97 collects data on all employ-

Table 1. Percent of youths employed at ages 14 and 15 in 1994–97, by type of job, sex, race or Hispanic origin, household
income, and family structure1

Percent employed at—
Age in 1994–97 and characteristic

Total working at age 14 ..........................
Sex: ..............................................................
Male ..........................................................
Female ......................................................
.....................................................................
Race or ethnicity: .........................................
White .........................................................
Black .........................................................
Hispanic origin ..........................................
.....................................................................
Household annual income: ...........................
Less than $25,000 ....................................
$25,000 to $44,999 ...................................
$45,000 to $69,999 ...................................
$70,000 or more ........................................
.....................................................................
Family structure: ..........................................
Two-biological-parent family ......................
Two-parent family ......................................
Female-parent family .................................
Not living with parents ...............................
Total working at age 15 ...........................
Sex: ..............................................................
Male ..........................................................
Female ......................................................
.....................................................................
Race or ethnicity: .........................................
White .........................................................
Black .........................................................
Hispanic origin ..........................................
.....................................................................
Household annual income: ...........................
Less than $25,000 ....................................
$25,000 to $44,999 ...................................
$45,000 to $69,999 ...................................
$70,000 or more ........................................
.....................................................................
Family structure: ..........................................
Two-biological-parent family ......................
Two-parent family ......................................
Female-parent family .................................
Not living with parents ...............................
.....................................................................

Employee
jobs
only

Freelance
jobs
only

Both
employee and
freelance
jobs

42.8

14.4

33.3

9.4

28.1
19.3

36.8
49.1

18.5
10.1

27.1
39.9

9.7
9.2

64.3
43.3
41.3

27.5
16.0
16.7

48.3
33.1
30.1

16.1
10.2
11.3

36.8
27.3
24.6

11.4
5.8
5.4

48.6
62.7
63.0
63.5

20.5
25.5
26.5
25.0

34.7
46.4
49.3
49.5

13.9
16.3
13.6
13.9

28.1
37.3
36.5
38.5

6.6
9.1
12.9
11.0

61.5
59.2
53.9
39.4

26.0
23.8
21.4
10.9

46.4
44.4
40.3
31.4

15.0
14.7
13.6
8.0

35.4
35.4
32.6
28.5

11.0
9.1
7.8
2.9

63.7

37.6

39.8

23.9

26.1

13.7

63.4
64.1

41.5
33.5

34.1
45.8

29.3
18.2

21.9
30.6

12.2
15.3

71.8
43.6
47.9

44.0
22.2
26.5

44.8
28.7
28.1

27.0
14.9
19.8

27.9
21.4
21.4

17.0
7.3
6.7

52.3
70.9
69.4
75.6

32.3
40.8
39.8
42.2

30.9
44.7
46.9
49.4

21.4
26.1
22.5
26.2

20.0
30.1
29.6
33.4

10.9
14.7
17.3
16.0

68.0
64.8
63.6
43.3

38.6
38.3
38.2
25.9

44.1
39.3
40.2
22.5

23.8
25.4
23.4
20.8

29.3
26.5
25.4
17.3

14.8
12.8
14.8
5.1

Any
job

Any
employee
Job

57.2

23.8

55.2
59.2

1
When a youth is said to have worked “at age 14,” for example, the
reference is to the youth having worked at some time during the entire 52-week
period between the youth’s 14th and 15th birthdays.

NOTE: The National Longitudinal Survey of Youth 1997 surveyed male and

ment spells in employee jobs, it is possible to determine
whether a youth did any work at all while he or she was a
particular age and also to determine how many weeks the
youth worked at that age. The method the analysis that follows uses to determine whether an individual worked at a
freelance job at a particular age is less precise than that used
for employee jobs, because only data on beginning and ending employment dates are collected. If a period between any
freelance job’s beginning and ending date spans any of the

Any
freelance
job

female youths who were aged 12 to 16 on December 31, 1996. Rows of the
table referring to youths working at age 14 exclude individuals who were not
yet 15 years of age when they were interviewed. Rows referring to youths
working at age 15 exclude individuals who were not yet 16 years of age when
they were interviewed.

weeks the respondent was 14 (for example), the respondent is
defined as having worked in a freelance job at age 14. This
approach may overstate youths’ incidence of employment in
freelance jobs: the data do not allow one to calculate the number of weeks a respondent worked at such a job.
Over the years, policymakers have been concerned about
youth employment during the school term.5 The nature of the
NLSY97 data on employee jobs allows one to calculate the
percentage of youths working during the school year or durMonthly Labor Review

August 2001

7

Youth Employment

ing the summer (or both). One can also calculate the percentage of school and summer weeks that youths work in employee jobs. It is convenient to depict the timing of youth
employment (especially graphically) during a calendar year,
rather than at a particular age. Tables and charts on the timing
of youth employment are shown for calendar year 1996, for
one birth year: 1981. These youths were 15 as of December 31,
1996, and thus ranged from 14 to 15 years old in 1996.
Unlike most data sets, the NLSY97 captures employment of
the very young. The survey asks all youths aged 12 or 13 at
the interview date about all of their work activities since the
age of 12. The survey does not distinguish between employment in freelance and employee jobs for this age group, but
the structure of the questions is similar to that of questions
asked of older youths in the freelance section. In this article,
the incidence of employment of the very young is measured
over the year youths are age 12.6
Past research suggests that youth employment behavior
varies by factors such as sex, race, ethnicity, household income, and family structure.7 Accordingly, the tables that follow tabulate youth employment by these factors. Household
income is measured for calendar year 1996 and is broken down
into four mutually exclusive categories. Family structure is
decomposed into five mutually exclusive categories and is
measured for the same period as are the youth employment
variables (for example, at age 14 or during calendar year 1996).8

Incidence of youth employment
This profile of youth employment in the NLSY97 begins with
an examination of the incidence of employment among 14and 15-year-olds. When calculating employment experience,
researchers often use age 16 as a starting point. However, as
table 1 shows, a significant percentage of youths engage in
employment activities at ages 14 and 15.9 More than half (57
percent) of all youths held a job at least sometime at age 14.
The majority of working youths held only freelance jobs at
that age. Almost two-thirds (64 percent) of youths had worked
at least sometime at age 15. Accompanying this increase in
youth employment was a shift away from freelance work and
into employee jobs.
Overall, 55 percent of male youths and 59 percent of female
youths worked at least sometime at age 14. At age 15, about
equal percentages of male and female youths worked (63 percent and 64 percent, respectively). However, the mix between
freelance and employee jobs differed considerably by gender:
at both ages, female youths were much more likely to hold
freelance jobs and less likely to hold employee jobs than were
male youths.
Past research has consistently found substantial differences by race or ethnicity in the incidence of youth employ-

8

Monthly Labor Review

August 2001

Table 2. Percent of individuals aged 14 to 15 in 1994–97
and aged 14 to 16 on December 31, 1996, who
worked at an employee job, and average
number of weeks worked, by sex, race or
Hispanic origin, household income, and family
structure1

Age in 1994–97 and characteristic

Percent with
Average
an employee
number of
job
weeks worked

Total working at age 14 .....................

23.8

24.6

Sex: .........................................................
Male .......................................................
Female ...................................................

28.1
19.3

24.6
24.6

Race or ethnicity: ....................................
White .....................................................
Black .....................................................
Hispanic origin .......................................

27.5
16.0
16.7

26.3
17.0
17.9

Household annual income: ......................
Less than $25,000 ................................
$25,000 to $44,999 ...............................
$45,000 to $69,999 ...............................
$70,000 or more ....................................

20.5
25.5
26.5
25.0

21.0
23.9
27.6
24.0

Family structure: .....................................
Two-biological-parent family ...................
Two-parent family ...................................
Female-parent family .............................
Not living with parents ...........................

26.0
23.8
21.4
10.9

26.2
24.4
21.1
14.2

Total working at age 15 ..........................
................................................................
Sex: .........................................................
Male .......................................................
Female ...................................................

37.6

25.9

41.5
33.5

27.2
24.1

Race or ethnicity: ....................................
White .....................................................
Black .....................................................
Hispanic origin .......................................

44.0
22.2
26.5

27.1
20.6
20.5

Household annual income: ......................
Less than $25,000 ................................
32.3
23.8
$25,000 to $44,999 ...............................
40.8
26.5
$45,000 to $69,999 ...............................
39.8
30.1
$70,000 or more ....................................
42.2
24.8
................................................................
Family structure: .....................................
Two-biological-parent family ...................
38.6
28.2
Two-parent family ...................................
38.3
25.8
Female-parent family .............................
38.2
24.1
Not living with parents ...........................
25.9
17.0
................................................................
1
When a youth is said to have worked “at age 14,” for example, the
reference is to the youth having worked at some time during the entire 52week period between the youth’s 14th and 15th birthdays.
NOTE: The National Longitudinal Survey of Youth 1997 surveyed male and
female youths who were aged 12 to 16 on December 31, 1996. Rows of the
table referring to youths working at age 14 exclude individuals who were not
yet 15 years of age when they were interviewed. Rows referring to youths
working at age 15 exclude individuals who were not yet 16 years of age when
they were interviewed.

ment, and the NLSY97 data show this difference as well. Employment is much higher among whites at these ages than
among blacks or Hispanics. At age 14, 64 percent of whites, 43
percent of blacks, and 41 percent of Hispanics had worked
sometime.10 By age 15, 72 percent of whites and 48 percent of
Hispanics had worked sometime, significantly higher percent-

Table 3. Top 10 industries of longest-held employee job
of youths at ages 14 and 15 in 1994–971
Industry

Percent
of youths

Age 14
Eating and drinking places ..................................................
17.4
Miscellaneous entertainment and recreation services .........
8.7
Construction ........................................................................
8.4
Newspaper publishing and printing ......................................
4.9
Agricultural production, crops .............................................
4.4
Private households (personal services) ..............................
4.1
Landscape and horticultural services ..................................
3.6
Agricultural production, livestock ........................................
2.9
Elementary and secondary schools ....................................
1.9
Services to dwellings and other buildings ...........................
1.9
............................................................................................
Age 15 ............................................
............................................................................................
Eating and drinking places ..................................................
28.8
Miscellaneous entertainment and recreation services .........
9.0
Construction ........................................................................
5.3
Grocery stores ....................................................................
4.5
Newspaper publishing and printing ......................................
2.9
Landscape and horticultural services ..................................
2.3
Agricultural production, crops .............................................
2.0
Agricultural production, livestock ........................................
1.8
Automotive repair and related services ...............................
1.6
Private households (personal services) ..............................
1.5
............................................................................................
1
When a youth is said to have worked “at age 14,” for example, the
reference is to the youth having worked at some time during the entire 52week period between the youth’s 14th and 15th birthdays.
NOTE: The National Longitudinal Survey of Youth 1997 surveyed male
and female youths who were aged 12 to 16 on December 31, 1996. Rows
of the table referring to 14-year-olds exclude individuals who were not yet
15 years of age when they were interviewed. Rows referring to 15-yearolds exclude individuals who were not yet 16 years of age when they were
interviewed.

ages than those at age 14. Black employment, however, remained nearly constant, at 44 percent.
Youths in households with low income were less likely to
work. One possible explanation for this finding is that they
may have lived in areas with less economic opportunity and,
consequently, may have had less access to transportation,
which could have decreased their likelihood of working. At
age 14, 49 percent of youths whose households had annual
incomes of less than $25,000 worked in an employee or
freelance job or both. In contrast, about 63 percent of youths
in households with higher levels of income worked at age 14.
Similar differences are observed for youths aged 15: 52 percent of those in households with annual incomes of less than
$25,000 worked, compared with at least 69 percent in households with higher income.
Youths in two-biological-parent and other two-parent families were more likely to work at age 14 (62 percent and 59
percent, respectively) than those in female-parent families (54
percent). Youths in female-parent families may have faced relatively more obstacles to working due to issues related to their
having a lower income or to having fewer adults in the household to provide them with transportation to a job. However,

employment differences between youths in these types of
family structure were not significant for 15-year-olds.11
With regard to the incidence and intensity (in terms of
weeks) of youth employment in employee jobs, the percentage of youths working at such jobs increased substantially,
from 24 percent at age 14 to 38 percent at age 15. In addition,
at both of these ages, employed youths worked a significant
portion of the year (about one-half of it; see table 2.)
Male youths were more likely than female youths to work at
an employee job at age 14 or 15. However, of those who held an
employee job at age 14, both sexes worked about half the year.
At age 15, male youths with jobs worked slightly more weeks
than did female youths (27 and 24 weeks, respectively).
At ages 14 and 15, whites were considerably more likely to
work at employee jobs than were blacks or Hispanics. At age
14, whites worked 26 weeks, while blacks worked 17 weeks
and Hispanics worked 18 weeks. At age 15, whites worked 27
weeks, and blacks and Hispanics worked about 21 weeks.
Youths in households with annual incomes of less than
$25,000 were less likely to work in employee jobs at ages 14
and 15 than were youths in households with higher incomes.
Table 4. Top 10 industries of longest-held employee job
of youths at age 14 in 1994–97, by sex1
Percent
of youths

Industry

Male youths
..........................................................................................
Eating and drinking places ................................................
Construction ......................................................................
Miscellaneous entertainment and recreation services .......
Newspaper publishing and printing ....................................
Agricultural production, crops ...........................................
Landscape and horticultural services ................................
Agricultural production, livestock ......................................
Elementary and secondary schools ..................................
Automotive repair and related services .............................
Grocery stores ..................................................................
..........................................................................................
Female youths ................................
..........................................................................................
Eating and drinking places ................................................
Private households (personal services) ............................
Miscellaneous entertainment and recreation services .......
Construction ......................................................................
Child day care services .....................................................
Newspaper publishing and printing ....................................
Religious organizations .....................................................
Services to dwellings and other buildings .........................
Social services, N.E.C. .......................................................
Agricultural production, crops ...........................................

15.8
11.4
8.8
6.1
5.9
5.4
3.7
2.4
2.3
1.8

19.8
8.6
8.5
3.8
3.5
3.1
2.8
2.1
1.9
1.9

1
When a youth is said to have worked “at age 14,” for example, the
reference is to the youth having worked at some time during the entire 52week period between the youth’s 14th and 15th birthdays.

NOTE: The National Longitudinal Survey of Youth 1997 surveyed male
and female youths who were aged 12 to 16 on December 31, 1996. All rows
of the table exclude individuals who were not yet 15 years of age when they
were interviewed. N.E.C. = not elsewhere classified.

Monthly Labor Review

August 2001

9

Youth Employment

Table 5. Top 10 industries of longest-held employee job
of youths at age 15 in 1995–97, by sex1

Percent
of youths

Industry
Male youths

Eating and drinking places ................................................
27.3
Construction ......................................................................
8.3
Miscellaneous entertainment and recreation services .......
7.6
Grocery stores ..................................................................
4.7
Newspaper publishing and printing ....................................
4.2
Landscape and horticultural services ................................
4.0
Agricultural production, crops ...........................................
2.6
Agricultural production, livestock ......................................
2.5
Automotive repair and related services .............................
2.0
Miscellaneous retail stores ................................................
1.5
..........................................................................................
Female youths .................................
..........................................................................................
Eating and drinking places ................................................
30.8
Miscellaneous entertainment and recreation services .......
10.9
Grocery stores ..................................................................
4.2
Private households (personal services) ............................
3.0
Religious organizations .....................................................
2.3
Child day care services .....................................................
2.3
Services to dwellings and other buildings .........................
1.7
Apparel and accessory stores, except shoe ....................
1.6
1.5
Food stores, N.E.C. .............................................................
Hotels and motels ..............................................................
1.4
..........................................................................................
1
When a youth is said to have worked “at age 14,” for example, the
reference is to the youth having worked at some time during the entire 52week period between the youth’s 14th and 15th birthdays.
NOTE: The National Longitudinal Survey of Youth 1997 surveyed male and
female youths who were aged 12 to 16 on December 31, 1996. All rows of the
table exclude individuals who were not yet 16 years of age when they were
interviewed. N.E.C. = not elsewhere classified.

continued to be a prominent employer of male youths at age
15, although it did not appear in the top-10 list for 15-year-old
female youths. By contrast, work in private households was
significant for 14- and 15-year-old young women, but did not
appear in the top-10 industry list for male youths.
Youth employment also appears to be concentrated in a
small number of occupations. Table 6 lists the top 10 detailed
three-digit Census occupations of employee jobs youths held
at ages 14 and 15;13 at each age, about 50 percent of employed
youths worked in one of those occupations. The most likely
detailed occupation for employed youths is janitors and cleaners at age 14 (9 percent) and cashiers at age 15 (10 percent).
The latter is the third most likely occupation for 14-year-olds.
Male and female youths exhibit significant differences in
occupations at the two ages studied. Male and female 14year-olds shared only two common occupations in their top10 lists, while their 15-year-old counterparts shared five. (See
tables 7 and 8.) Cashier was the most common occupation of
employed female youths: 11 percent worked as cashiers at
age 14 and 16 percent at age 15. By contrast, the occupation
of cashier did not even reach the top-10 list of employed male
14-year-olds and was the fifth most common occupation of
employed male 15-year-olds. Male youths were most likely to
Table 6. Top 10 occupations of longest-held employee
job of youths at ages 14 and 15 in 1994–971
Occupation

Percent
of youths

Total at age 14

However, only 14- and 15-year-old youths in households with
annual incomes in the $45,000–$69,999 range worked a significantly greater number of weeks than did youths in households with an income of less than $25,000 per year.

Youth industries and occupations
Fourteen- and 15-year-olds’ employee jobs were concentrated
in a small number of industries. Table 3 lists the top 10 detailed
three-digit Census industries of employee jobs youths held at
ages 14 and 15.12 Nearly 60 percent of employed youths
worked in one of these industries sometime at age 14 or 15. At
both of these ages, eating and drinking places constituted the
most common industry in which youths were employed, with
17-percent representation among 14-year-olds and a significantly higher 29-percent showing among 15-year-olds.
Male and female 14-year-olds shared 5 of the top 10 industries, while their 15-year-old counterparts shared only 3. (See
Tables 4 and 5.) Not surprisingly, eating and drinking establishments were the most common employers of male and female youths at both ages 14 and 15. At age 14, male youths in
employee jobs were nearly 3 times as likely to work in the
construction industry as were female youths. Construction
10

Monthly Labor Review

August 2001

Janitors and cleaners ....................................................
Farm workers .................................................................
Cashiers ........................................................................
News vendors ................................................................
Groundskeepers and gardeners, except farm ...............
Laborers, except construction ......................................
Construction laborers ....................................................
Cooks ............................................................................
Waiters’ and waitresses’ assistants ...............................
General office clerks .....................................................

8.7
5.9
5.5
5.3
4.5
4.1
3.9
3.8
3.5
2.9

Total at age 15 ............................
Cashiers ........................................................................
Cooks ............................................................................
Miscellaneous food preparation occupations ................
Janitors and cleaners ....................................................
Waiters’ and waitresses’ assistants ...............................
Stock handlers and baggers .........................................
Laborers, except construction ......................................
Sales workers, other commodities .................................
Construction laborers ....................................................
News vendors ................................................................

10.0
5.9
5.7
5.5
4.7
4.5
4.2
4.1
3.1
3.0

1
When a youth is said to have worked “at age 14,” for example, the
reference is to the youth having worked at some time during the entire 52week period between the youth’s 14th and 15th birthdays.

NOTE: The National Longitudinal Survey of Youth 1997 surveyed male
and female youths who were aged 12 to 16 on December 31, 1996. Rows of
the table referring to 14-year-olds exclude individuals who were not yet 15
years of age when they were interviewed. Rows referring to 15-year-olds
exclude individuals who were not yet 16 years of age when they were
interviewed.

Table 7. Top 10 occupations of longest-held employee
job of youths at age 14 in 1994–97, by sex1
Occupation

Percent
of youths

Male youths
Janitors and cleaners .....................................................
Farm workers .................................................................
Groundskeepers and gardeners, except farm ...............
News vendors ................................................................
Construction laborers .....................................................
Laborers, except construction .......................................
Cooks .............................................................................
Waiters’ and waitresses’ assistants ..............................
Miscellaneous food preparation occupations .................
Attendants, amusement and recreational facilities .......
.......................................................................................
Female youths .............................
.......................................................................................
Cashiers .........................................................................
Janitors and cleaners .....................................................
Child care workers, private household ...........................
General office clerks ......................................................
Child care workers, N.E.C. ...............................................
Waiters and waitresses ..................................................
Receptionists .................................................................
Teachers, N.E.C. ..............................................................
Farm workers ..................................................................
Secretaries .....................................................................
.......................................................................................

9.4
7.1
6.9
6.7
4.7
5.9
4.2
4.1
3.4
2.8

10.9
7.5
5.9
5.8
5.2
4.7
4.3
3.9
3.9
3.5

1
When a youth is said to have worked “at age 14,” for example, the
reference is to the youth having worked at some time during the entire 52week period between the youth’s 14th and 15th birthdays.

NOTE: The National Longitudinal Survey of Youth 1997 surveyed male and
female youths who were aged 12 to 16 on December 31, 1996. All rows of the
table exclude individuals who were not yet 15 years of age when they were
interviewed. N.E.C. = not elsewhere classified.

be employed as janitors and cleaners at age 14 (9 percent)
and as cooks (8 percent) at age 15. Female 15-year-olds were
about half as likely to be employed as cooks. Another interesting gender difference is that 14- and 15-year-old female
youths were likely to be employed as waitresses, whereas
male youths were likely to be employed as waiters’ and waitresses’ assistants.
Babysitting and yard work were by far the most common
freelance jobs youths reported having worked at at ages 14
and 15. Table 9 shows that 43 percent of youths engaged in
freelance jobs at age 14. Of these, 62 percent worked as
babysitters and 38 percent did yard work.14 At age 15, 40
percent of youths worked in freelance jobs, of whom 60 percent worked as babysitters and 37 percent did yard work.
There are dramatic differences in freelance occupations
by sex. At age 14, more than 91 percent of female youths who
held freelance jobs worked as babysitters, compared with
less than 25 percent of male youths. In contrast, almost 73
percent of male youths in freelance jobs did yard work, compared with less than 11 percent of female youths in freelance
jobs. The pattern continues for youths who worked at age
15, with, again, about 91 percent of female youths in freelance

jobs having worked as babysitters, but only 20 percent of
male youths having done so. At age 15, male youths who
held freelance jobs were far more likely to do yard work (73
percent) than were female youths who held freelance jobs (9
percent).
Whites were more likely to hold freelance jobs at ages 14
and 15 than were blacks or Hispanics. At age 14, whites holding a freelance job were more likely to work as babysitters
than were blacks.

Employment while in school
This section examines the timing of youth employment during school and during summer weeks. The analysis focuses
on the employment during the year 1996 of youths aged 15
years as of December 31, 1996. Thus, the data are for one
birth year, 1981, so that the youths in question were aged 14
to 15 during 1996.
Chart 1 depicts the percent of enrolled youths working at
employee jobs over each week of the 1996 calendar year;
shading marks summer weeks.15 The chart shows a general
upward trend in the percent of youths aged 14 to 15 working
Table 8.

Top 10 occupations of longest-held employee
job of youths at age 14 in 1995–97, by sex1
Occupation

Male youths
......................................................................
Cooks ....................................................................
Janitors and cleaners ............................................
Miscellaneous food preparation occupations ........
Waiters’ and waitresses’ assistants .......................
Cashiers ................................................................
Construction laborers ............................................
Stock handlers and baggers .................................
Groundskeepers and gardeners, except farm .......
Laborers, except construction ..............................
News vendors ........................................................
..............................................................................
Female youths ........................
..............................................................................
Cashiers ................................................................
Waiters and waitresses .........................................
General office clerks .............................................
Sales workers, other commodities .........................
Miscellaneous food preparation occupations ........
Receptionists ........................................................
Cooks ....................................................................
Janitors and cleaners ............................................
Laborers, except construction ..............................
Teachers, N.E.C. .....................................................

Percent
of youths

7.7
6.9
6.4
6.0
5.8
5.5
5.5
5.1
4.8
4.5

15.7
5.7
5.6
4.7
4.7
4.1
3.6
3.6
3.4
3.3

1
When a youth is said to have worked “at age 14,” for example, the
reference is to the youth having worked at some time during the entire 52week period between the youth’s 14th and 15th birthdays.

NOTE: The National Longitudinal Survey of Youth 1997 surveyed male
and female youths who were aged 12 to 16 on December 31, 1996. All rows
of the table exclude individuals who were not yet 16 years of age when they
were interviewed. N.E.C. = not elsewhere classified.

Monthly Labor Review

August 2001

11

Youth Employment

Table 9. Percent of youths engaged in freelance jobs at ages 14 and 15 in 1994–97, by type of job, sex, race or Hispanic
origin, and household income1

Age in 1994–97 and characteristic

Percent of those with a
freelance job engaged in—

Percent with
a freelance
job

Babysitting

Yard work

Total working at age 14 ...................................

42.8

62.0

37.9

Sex: .......................................................................
Male ` ..................................................................
Female .................................................................

36.8
49.1

24.6
91.4

72.8
10.6

Race or ethnicity: ..................................................
White ...................................................................
Black ...................................................................
Hispanic origin .....................................................

48.3
33.1
30.1

63.3
55.2
59.9

37.4
41.1
40.2

Household annual income: ....................................
Less than $25,000 ..............................................
$25,000 to $44,999 .............................................
$45,000 to $69,999 .............................................
$70,000 or more ..................................................

34.7
46.4
49.3
49.5

58.7
63.2
61.5
67.8

35.1
39.1
41.1
35.0

Family structure: ...................................................
Two-biological-parent family .................................
Two-parent family .................................................
Female-parent family ...........................................
Not living with parent ...........................................

46.4
44.4
40.3
31.4

62.5
67.0
60.6
66.2

38.5
35.8
32.0
40.4

Total working at age 15 ...................................

39.8

59.8

37.2

34.1
45.8

19.6
91.4

72.8
9.3

44.8
28.7
28.1

61.0
52.9
59.7

37.2
41.2
34.1

30.9
44.7
46.9
49.4

52.3
64.3
61.1
62.3

33.0
33.6
42.8
39.5

44.1
39.3
40.2
22.5

61.2
64.4
59.6
66.8

38.7
35.5
30.8
39.8

Sex: .......................................................................
Male .....................................................................
Female .................................................................
..............................................................................
Race or ethnicity: ..................................................
White ...................................................................
Black ...................................................................
Hispanic origin .....................................................
Household annual income: ....................................
Less than $25,000 ..............................................
$25,000 to $44,999 .............................................
$45,000 to $69,999 .............................................
$70,000 or more ..................................................
..............................................................................
Family structure: ...................................................
Two-biological-parent family .................................
Two-parent family .................................................
Female-parent family ...........................................
Not living with parent ...........................................

1
When a youth is said to have worked “at age 14,” for example, the
reference is to the youth having worked at some time during the entire 52week period between the youth’s 14th and 15th birthdays.

at employee jobs during the weeks leading up to the summer.
A peak in youth employment occurred during the middle of
the summer. The trend line then became fairly flat during the
fall school term, but still lay above its spring-term level.
This general employment pattern also held for male and
female youths separately. (See Chart 2.) However, over the
summer months, male youths experienced a steeper increase
and subsequent decrease in employment than did female
youths. Throughout the 1996 calendar year, male employ12

Monthly Labor Review

August 2001

NOTE: The National Longitudinal Survey of Youth 1997 surveyed male
and female youths who were aged 12 to 16 on December 31, 1996. Rows
of the table referring to youths working at age 14 exclude individuals who
were not yet 15 years of age when they were interviewed.

ment was higher than female employment.
Chart 3 shows the week-by-week incidence of employment separately by race and ethnicity. White, black, and Hispanic youths all exhibited a peak in employment during the
summer weeks. However, while white youths experienced an
upward trend in employment during the spring semester of
1996, the trend line of black and Hispanic youths remained
fairly flat. Over the weeks of 1996, white youth employment
was consistently much higher than employment for black and

Table 10. Percent of youths aged 15 as of December 31, 1996, with an employee job during 1996, by timing
of employment, sex, race or Hispanic origin, household income, family structure, and grade attending school1
Worked during school-year weeks
Characteristic

Total .....................................................
Sex: ............................................................
Male ..........................................................
Female ......................................................
...................................................................
Race or ethnicity: .......................................
White ........................................................
Black ........................................................
Hispanic origin ..........................................
...................................................................
Household annual income: .........................
Less than $25,000 ...................................
$25,000 to $44,999 ..................................
$45,000 to $69,999 ..................................
$70,000 or more .......................................
...................................................................
Family structure: ........................................
Two-biological-parent family ......................
Two-parent family ......................................
Female-parent family ................................
Not living with parent ................................
Grade attending school, fall 1996 ..............
6th, 7th, or 8th .........................................
9th ............................................................
10th ..........................................................
11th or 12th ..............................................

Percent with
an employee
job

Total

Worked
during schoolyear weeks
only

Worked during
both schoolyear and
summer weeks

Worked
during
summer
weeks only

31.9

24.9

5.8

19.1

7.0

37.0
26.6

29.0
20.6

6.6
5.0

22.4
15.6

7.9
6.0

36.6
22.9
20.1

30.4
14.1
12.4

6.3
6.3
4.0

24.1
7.8
8.4

6.2
8.8
7.6

24.1
33.4
38.6
38.9

18.1
25.0
33.4
30.3

6.6
7.5
5.8
5.9

11.5
17.6
27.5
24.4

6.1
8.4
5.3
8.6

34.6
38.5
26.4
24.5

28.3
29.5
19.4
21.1

5.1
9.7
6.3
3.8

23.3
19.9
13.1
17.3

6.3
8.9
7.0
3.3

18.4
28.9
35.3
35.0

12.4
21.6
28.1
32.9

5.4
4.8
6.7
4.2

7.0
16.8
21.4
28.7

6.1
7.3
7.2
2.1

1
When a youth is said to have worked “at age 14,” for example, the
reference is to the youth having worked at some time during the entire 52-week
period between the youth’s 14th and 15th birthdays.

NOTE: The National Longitudinal Survey of Youth 1997 surveyed male and
female youths aged 12 to 16 on December 31, 1996.

Table
Table11.
11. Percent of youths aged 13 engaged in work activities at age 12 sometime during 1995–97, by type of job, sex,
race or Hispanic origin, and household income1
Age in 1995–97 and characteristic

Percent with
a work
activity

Percent of those with a work activity engaged in—
Babysitting

Yard work

Total ........................................................

49.6

55.6

39.7

Sex: ...............................................................
Male .............................................................
Female .........................................................

48.3
51.0

26.3
84.9

65.8
13.6

Race or ethnicity: ..........................................
White ...........................................................
Black ...........................................................
Hispanic origin .............................................

56.5
36.2
36.0

54.6
46.9
61.3

40.1
41.7
37.0

Household annual income: ............................
Less than $25,000 ......................................
$25,000 to $44,999 .....................................
$45,000 to $69,999 .....................................
$70,000 or more ..........................................

48.7
52.2
53.8
53.9

50.1
51.2
55.6
61.5

45.9
41.5
39.1
39.1

Family structure: ...........................................
Two-biological-parent family .........................
52.2
Two-parent family .........................................
50.9
Female-parent family ...................................
51.6
Not living with parent ...................................
41.2
1
When a youth is said to have worked “at age 14,” for example, the
reference is to the youth having worked at some time during the entire 52week period between the youth’s 14th and 15th birthdays.

55.2
41.3
53.7
39.8
56.4
38.8
49.5
32.0
NOTE: The National Longitudinal Survey of Youth 1997 surveyed male
and female youths who were aged 12 to 16 on December 31, 1996. All rows
of the table exclude individuals who were not yet 13 years of age when
interviewed.

Monthly Labor Review

August 2001

13

Youth Employment

Hispanic youths. Black and Hispanic youths experienced
fairly similar rates of employment during the spring and summer of 1996. However, during the fall semester, the trend line
for Hispanic youth employment was above that of black
youth employment.
Most youths who worked at employee jobs did so during
both the summer and the school term. More specifically, 19
percent of enrolled youths aged 14 to 15 worked at an employee job at some point during both the summer and the
school term in 1996. (See table 10.) Six percent of youths
worked in an employee job only during the school year in
1996. Thus, 25 percent of youths aged 14 to 15 worked at an
employee job at some point while school was in session during the 1996 calendar year. An additional 7 percent worked in
an employee job only during the summer, but not the school
term, of 1996.
The 19 percent of enrolled youths who worked during
both the summer and the school year worked much more
intensively, in terms of percent of weeks worked, than students employed only during the school months or only during the summer (numbers not shown in table). That is, this
group of youths worked in employee jobs about 61 percent
of school weeks and 80 percent of summer weeks; in con-

trast, those who worked only during the school year worked
under 20 percent of the school weeks, and youths who
worked only during the summer worked slightly under half
of the summer weeks.
A higher percentage of male youths than female youths
worked in employee jobs at some point during the school
term (29 percent and 21 percent, respectively). However,
among youths who worked, there was little difference by
gender in the percent of weeks worked (numbers not shown
in table).
Whites were much more likely to work in employee jobs
at some point while school was in session (30 percent) than
were blacks (14 percent) or Hispanics (12 percent). Almost a
quarter of whites worked in employee jobs during both the
summer and the school year, compared with about 8 percent
of blacks and Hispanics. Employed whites in this group
worked significantly more school and summer weeks than
did blacks—about 62 percent of school weeks and 81 percent of summer weeks, compared with 46 percent of school
weeks and 67 percent of summer weeks (numbers not shown
in table).
The timing of youth employment also varies by household income and family structure. Youths in households with

Chart 1. Percent of school-enrolled youths aged 15 on December 31, 1996, who worked in
employee jobs during 1996, week by week
Percent

Percent

30

30

25

25

Summer weeks

20

20

15

15

10

10

5

5

0

0
1

4

7

10

13

16

19

22

25

28

31

Weeks of 1996

14

Monthly Labor Review

August 2001

34

37

40

43

46

49

52

Chart 2. Percent of school-enrolled youths aged 15 on December 31, 1996, who worked in
employee jobs during 1996, week by week, by sex
Percent

Percent
30

30

Summer weeks

25

25

20

20

Male youths
15

15

Female youths

10

10

5

5

0

0
1

4

7

10

13

16

19

22

25

28

31

34

37

40

43

46

49

52

Weeks of 1996

Chart 3. Percent of school-enrolled youths aged 15 on December 31, 1996, who worked in
employee jobs during 1996, week by week, by race and Hispanic origin
Percent
30

Percent
30

Summer weeks

25

25
White

20

20
15

15

10

10

Hispanic

5

5

Black

0

0
1

4

7

10

13

16

19

22

25

28

31

34

37

40

43

46

49

52

Weeks of 1996

Monthly Labor Review

August 2001

15

Youth Employment

yearly incomes of less than $25,000 were less likely to hold employee jobs during the school year (18 percent) than were youths
in households in higher income categories (from 25 percent to
33 percent). Youths in two-biological-parent families and other
two-parent families were more likely to work while school was in
session than were youths in female-parent families.
Being in a higher grade in school was also associated with a
higher incidence of youth employment. In the fall of 1996, the
cohort born in 1981 was mostly in the 9th and 10th grades.
Youths in 10th grade were more likely to work during the school
term than were youths in lower grades. Tenth graders were also
significantly more likely to work both during the school year
and during the summer than were youths in lower grades.

Employment of the very young
The NLSY97 also provides data on the work activities of
youths who have not reached their teenage years. Nearly
half of all youths aged 13 years at the time of the survey were
engaged in work activities at some point while they were age 12.
(See table 11.) Of these, 56 percent worked as babysitters and 40
percent did yard work.16 Female youths were about equally as
likely as male youths to engage in work activities at age 12.
However, gender differences in the types of work activities
youths participated in at that age were substantial, with 85
percent of working female youths engaged in babysitting,

compared with 26 percent of male youths. Conversely, about
two-thirds of working male youths performed yard work at
age 12, compared with only 14 percent of working female
youths. Whites are much more likely to engage in work activities at age 12 (57 percent) than are blacks (36 percent) or
Hispanics (36 percent). There is little difference by household income level.
YOUTHS ENGAGE IN SUBSTANTIAL WORK ACTIVITY across the various measures of youth employment examined in this article.
From age 14 to 15, youths appear to shift more toward working in employee jobs and less in freelance jobs. At both of
those ages, gender and racial differences in employment are
significant. At both ages, female youths are more likely to
hold freelance jobs than male youths, but less likely to hold
employee jobs. In addition, significant gender differences
exist in the types of employee and freelance jobs held by
youths. Finally, whites are more likely to engage in work activities than are blacks or Hispanics.
An examination of the timing of youth employment indicates that youths who hold employee jobs at ages 14 to 15
are likely to work during school weeks. Youths who hold
employee jobs during both summer and school weeks tend
to work a higher percentage of weeks in each of those periods than those who work only during the summer or only
during the school year.
□

Footnotes
1
Data include oversamples of black and Hispanic youths. Subsequent
to the release of round-1 NLSY97 data, some duplicate observations were
discovered, and the sample size for that round then fell from 9,022 to
8,984. Sample weights at the time this article was begun were based on all
9,022 observations, and the tables that are presented use the full round1 sample, as well as round-1 sample weights to adjust for differing sample
rates; this approach ensures that the data are nationally representative of
U.S. youths born in the years 1980–84.

6
As just stated, only youths aged 12 or 13 at the date of the
interview report employment at these young ages. Thus, it is not
possible to use round-1 NLSY 97 data to calculate youth employment
for the entire year that youths are age 13.
7
Mark Schoenhals, Marta Tienda, and Barbara Schneider, “The
Educational and Personal Consequences of Adolescent Employment,”
Social Forces, December 1998, pp. 723–62, provide a brief summary
of this research.

2

A number of the tables in this article also appear in Press Release
99–110 and Report on the Youth Labor Force (Bureau of Labor
Statistics, November 2000).
USDL

3
However, the round-1 survey also contains a “CPS Section” containing questions from the Current Population Survey that can be used to
determine a youth’s labor force status in the week prior to the interview.
The article “Youth employment: results from two longitudinal surveys
school” (this issue, pp. 25–37) uses data from the “CPS Section.”
4
Youths are aged 12–16 as of December 31, 1996. The round-1
interview occurred in 1997, when most youths had not yet turned 17.
Because the number of youths for whom data were collected for the
entire year they were 16 is small, the article does not show tabulations
for 16-year-olds.
5
See, for example, National Research Council, Protecting Youth at
Work (Washington, DC, National Academy Press, 1998).

16

Monthly Labor Review

August 2001

8
The categories are (1) families with two biological parents or two
adoptive parents (called, for simplicity, two-biological-parent families), (2) families with one biological parent and one step- or adoptive
parent (called simply two-parent families), (3) families with one female biological parent and no other parent (female-parent families),
(4) families with one male biological parent and no other parent
(male-parent families), and (5) families consisting of children living
with foster parents, grandparents and no parents, or other relatives
and no parents; families of children living in group quarters; and other
family arrangements (all lumped together as children not living with
parents). Due to the small sample size of male-parent families, the
tables that follow exclude that category.
9
Robert T. Michael and Nancy B. Tuma, “Youth Employment:
Does Life Begin at 16?” Journal of Labor Economics , October 1984,
pp. 464–76, point out that significant percentages of youths in the
NLSY79 work before age 16.

10
In all tables and charts in this article, the racial and Hispanic
groups are mutually exclusive. Totals include American Indians, Alaskan natives, and Asians and Pacific Islanders, not shown separately.
11
At ages 14 and 15, youths who do not live with a parent work
less than youths who live in the other family structures listed in table
1. Youths who do not live with a parent live in varied arrangements,
including living with foster parents, grandparents, and other relatives,
as well as living in group quarters.
12

The industry shown in this table and in tables 4 and 5 is for the
employee job the youth held for the most weeks at a particular age.
13

The occupation shown in this table and in tables 7 and 8 is for the

employee job the youth held for the most weeks at a particular age.
14
Yard work includes mowing lawns, shoveling snow, landscaping,
and gardening. In explaining the concept of freelance jobs to youth
respondents, NLSY 97 interviewers used babysitting and mowing lawns
as examples. Youths who have more than one freelance job at the age
of 14 or 15 may appear in both the babysitting and yard-work columns of table 9.
15
Summer is defined as the 13-week period from June 2 through
August 31, 1996.
16
Youths who had more than one work activity at age 12 may
appear in both the babysitting and yard-work columns of table 11.

Where are you publishing your research?
The Monthly Labor Review will consider for publication studies of the labor force, labormanagement relations, business conditions, industry productivity, compensation, occupational safety and health, demographic trends, and other economic developments. Papers
should be factual and analytical, not polemical in tone.
We prefer (but do not require) submission in the form of an electronic file in Microsoft
Word, either on a diskette or as an attachment to e-mail. Please use separate files for the text
of the article; the tables; and charts. We also accept hard copies of manuscripts.
Potential articles should be mailed to: Editor-in-Chief, Monthly Labor Review, Bureau of
Labor Statistics, Washington, DC 20212, or by e-mail to mlr@bls.gov

Monthly Labor Review

August 2001

17

Job Initiation

Job Initiation

Youth initiation
into the labor market
About half of 12- and 13-year-olds surveyed
engage in some sort of work;
such work is more likely among youths
from higher socio-economic backgrounds
or who have engaged in ‘delinquent’ behaviors
Lynn Huang,
Michael Pergamit,
and
Jamie Shkolnik

Lynn Huang is
research scientist,
and Michael Pergamit
is research vice
president at the
National Opinion
Research Center,
Washington, DC;
Jamie Shkolnik is senior
research scientist at
American Institutes for
Research,
Palo Alto, CA.
e-mail:
pergamit@
norcmail.uchicago.edu

18

Y

oung people acquire substantial work experience before age 16, the age at which
official statistics begin counting employment. Using the National Longitudinal Survey of
Youth—1979 cohort (NLSY79), R.T. Michael and
N.B. Tuma examined the amount of work performed by 14- and 15-year-olds using definitions
from the Current Population Survey (CPS). 1 Importantly, they found significant differences between black and white youths, and also found
that youths who worked at ages 14 and 15 were
more likely to be working 2 years later. They
concluded that social scientists should include
such early work experience in their models. Their
findings were influential in the design considerations for the National Longitudinal Survey of
Youth—1997 cohort (NLSY97).
Other surveys that capture information about
youths as young as 12 do not typically include
information on their work activities, and data that
focus on work have not sampled those below
age 14.2 The Fair Labor Standards Act prohibits
employment of those younger than age 14, and
restricts the hours and jobs allowed for those
younger than 16. However, many youths have
“jobs” before these ages. These jobs, while not
always like those of adults, frequently involve
learning work behavior (for example, showing up
at a particular time every week), personal responsibility (for example, caring for someone’s child),
remuneration, and other characteristics that teach

Monthly Labor Review

August 2001

young adolescents the basic nature of working
for someone else.
The NLSY97 provides a unique opportunity
to study the very early work experiences of
youths and relate these experiences to future labor market behavior. For 12- and 13-year-olds,
information was collected about jobs they had
held since age 12.
This article examines exclusively 12- and 13year-olds, focusing on who holds jobs and the
nature of those jobs. Is early initiation into the
labor market (age at obtaining first job) associated with youths from upper income, more educated families, or does it occur among those who
most likely will not pursue advanced schooling?
Does work serve to supplement household income in lower-income, single-parent families?
These and related questions are examined in relation to race/ethnicity; parental income, education,
and marital status; and the presence of siblings.
Schooling achievement—as measured by the
Peabody Individual Achievement Test (PIAT)
Mathematics score—and time use are compared
for youths who have jobs with those who do
not. Measuring time use can determine if homework, outside classes, and so forth are substitutes for, or complements to, work. We also observe whether youths in early-age jobs also engaged in or had early initiation into risky behaviors (such as drug and alcohol use, or other delinquency). Finally, we can observe how youths

Youths were asked first to list the kinds of jobs they have
had since their 12th birthday. Then they were asked whether
they got help in finding this kind of work; who helped them;
when they started doing this kind of work; whether they are
currently doing this kind of work, and if not, when was the
last time they did. In addition, for the beginning and end of
each kind of job, youths were asked the usual number of
hours worked per week, the usual amount of money earned
per week, and the number of days and hours worked on weekdays and weekends.
A main purpose of this study was to identify youths who
work and the number of hours they worked. Therefore, the
analysis focuses on two measures of youth employment: A
discrete variable measures whether the respondent reported
any jobs; a count variable measures the number of hours the
respondent worked per week. The information on the number of work hours per week was collected for each kind of
work performed—when it was initiated and when it was last
(or is currently) performed. However, we do not know the
sequential order of jobs performed or whether jobs were (are)
performed at the same time. Given this, we use the hours
when jobs were last (or are currently) performed, and among
those, we use the hours per week on the job with most hours.4

found jobs (that is, did they have help from their parents,
other help, or no help at all).

Study methodology
Data for this article are from the first wave of the National
Longitudinal Survey of Youth, 1997 Cohort, sponsored by the
Bureau of Labor Statistics, U.S. Department of Labor. The
survey’s main goal is to document the transition from school
to work for the U.S. population born during the 1980–84 period. The first wave of the survey includes 9,022 youths aged
12–18 when interviewed.3

Work experience. The NLSY97 has a unique set of questions
on employment that permits investigation of youth initiation
into the labor market. The 12- and 13-year-old respondents
were asked about any job experiences since their 12th birthday. This experience could include working for a particular
employer (for example, delivering newspapers) or doing tasks
for several people—freelance jobs (for example, baby-sitting
or mowing lawns). Most jobs reported at these ages were
freelance jobs. Respondents aged 14 and older were also
asked about their experience in freelance jobs since their 14th
birthday. However, information on initial entrance into the
labor market is incomplete for those respondents, as freelance
jobs that ended before age 14 are not included. For this
reason, respondents aged 14 and older were excluded from
this study.

Associated factors. Which youths are more likely to enter
the labor market in the early adolescent years? Which youths
work more hours than others? It is of particular interest to
examine labor market initiation with other factors that affect

Cumulative age initiation for 12- and 13-year-olds who have worked by the time
they were interviewed, NLSY97

Chart 1.
Percent

Percent

100

100

80

80

60

60

40

40

20

20

0

0
0

1

2

3

4

5

6

7

8

9

10

11

12

13

14

Age started first job (years)

Monthly Labor Review

August 2001

19

Job Initiation

Table 1.

Characteristics of 12- and 13-year-old youths, NLSY97

[In percent unless noted otherwise]
Weighted mean

Weighted mean

Variable

Variable
Total

Male

Female

Total

Male

Female

17.0
32.6
23.9
20.3
6.2

16.9
32.4
22.7
21.5
6.5

17.1
32.7
25.3
19.1
5.8

14.5
30.4
17.0
20.8
17.2

13.9
30.7
17.0
21.9
16.5

15.1
30.1
17.1
19.8
18.0

PIAT-Math percentile score ...........

18.4
54.8

25.5
55.5

10.9
54.5

Spent time doing homework ........

91.2

90.8

91.7

Hours on homework per week ...

6.4

5.6

7.2

Spent time on extra classes ........

30.4

26.4

34.6

Hours on extra classes
per week ...................................

3.7

3.4

3.9

Spent time watching TV ...............

96.6

97.1

96.2

Hours watching TV per week .....

19.8

20.8

18.8

Spent time reading for pleasure ..

65.6

60.7

70.9

Hours reading for pleasure
per week ..................................

3.4

5.0

13.5

Ever smoked ...............................

25.3

25.4

25.3

Ever drank alcohol ......................

24.3

27.0

21.5

Ever used marijuana ...................

6.9

7.9

5.9

Job characteristic
Mother’s educational attainment:
Percent who reported jobs .........

52.5

51.2

53.9

Conditional on having a job:
Number of jobs .........................
Age started job (years) ..........

1.6
11.6

1.7
11.5

1.5
11.7

Percent who got help in finding
jobs ........................................

61.8

64.2

59.4

7.1

6.6

7.5

7.9

7.2

8.7

7.4
5.9

7.5
5.4

7.3
6.4

$22.93

$26.87

$18.94

49.3
22.8
3.5
2.9
2.1
2.0
1.8
1.5
1.1

17.0
42.7
4.7
5.7
2.5
3.5
2.0
1.0
1.7

81.8
3.5
2.3
.2
1.7
.5
1.7
2.1
0.6

1.1

2.1

0

Hours per week on job with most
hours ......................................
Hours per week for those
finding a job with help of:
Parents ..............................
Someone other than
parents ............................
No one ...............................
Earnings per week on job with
highest earnings ....................

Father’s educational attainment:

Top 10 job types from the first
job listed:
Baby-sitting ..............................
Mowing / other yard work .........
Paper route ...............................
Snow shoveling ........................
Chores, odd jobs ......................
Farm work .................................
House cleaning .........................
Pet care ....................................
Selling ......................................
Carpentry, building, painting,
construction ..........................

Sex ..........................................
White, non-Hispanic ..................
Black, non-Hispanic ..................
Hispanic ....................................
Other race/ethnicity ..................

100.0
62.6
15.6
12.5
5.7

51.5
66.5
15.4
12.9
5.2

48.5
65.8
15.8
12.1
6.4

Northeast ..................................
North Central .............................
West ..........................................
South .........................................

17.8
25.1
33.7
23.3

17.6
26.1
33.6
22.7

18.1
24.1
33.8
24.0

Metropolitan Statistical Area .....

80.0

81.7

78.2

Lived with two parents/
guardians ...............................

69.3

70.7

67.8

Lived with siblings .....................

84.5

84.5

84.4

20

Monthly Labor Review

High school dropout ..................
High school graduate ................
Some college ............................
College and up ..........................
Missing ......................................

School performance
and time use
Ever suspended from school ......

Demographic characteristics

Parents’ earnings:
$0–9,999 ................................
10,000–19,999 .......................
20,000–39,999 .......................
40,000–79,999 .......................
80,000 and more ....................
Missing ...................................

High school dropout ..................
High school graduate ................
Some college ............................
College and up ..........................
Missing ......................................

17.9
10.3
20.7
29.7
9.9
11.5

17.4
9.9
21.6
29.9
10.5
10.7

August 2001

18.4
10.8
19.7
29.5
9.2
12.5

Substance use
and delinquency

Ever ran away .............................

6.0

6.5

5.4

Ever carried a handgun ...............

7.7

13.5

1.5

Ever purposely
destroyed property ....................

25.3

32.1

18.2

Ever attacked another person .....

14.6

19.3

9.7

Ever been arrested for illegal or
delinquency offenses ..............

3.2

4.5

2.0

Gender:
Boy ..........................................
Girl ...........................................

51.2
53.9

6.6
7.5

Race/ethnicity:
White, non-Hispanic .................
Black, non-Hispanic .................
Hispanic ...................................
Others ......................................

58.9
40.6
39.3
38.5

6.7
7.5
9.1
6.8

Region:
Northeast .................................
North Central ............................
South .......................................
West ........................................

55.8
58.8
46.9
51.4

6.4
7.1
7.2
7.4

Metropolitan Statistical Areas:
Not in MSA ..............................................
In MSA ......................................................

57.5
51.3

8.1
6.8

performance: ever being suspended from school and Peabody
Individual Achievement Test-Math percentile score. The
PIAT-Math score is categorized into quartiles: 0–25, 26–50,
51–75, and 76–100. For time use, respondents were asked
about four typical youth activities: doing homework, taking
extra classes, watching TV, and reading for pleasure. They
were asked if they ever spent time on each activity, then the
hours per day spent on each activity on weekdays and weekends. We created discrete variables measuring whether respondents ever spent time in each activity, and variables measuring hours per week spent on each activity.
The next issue examined was whether youths who work
were more likely to be associated with risky behaviors. Discrete variables for substance use include cigarette smoking,
drinking alcohol, and marijuana use. Discrete variables for
delinquent behaviors include running away from home, handgun possession, purposely destroying property, attacking
another person, and being arrested last year.

Number of parents/guardians:
Living with two parents ............
Other ........................................

53.3
50.7

6.6
8.1

Results

Siblings in the household:
Yes ...........................................
No ............................................

53.1
48.6

7.1
6.9

Parents’ earnings:
$0–$9,999 ................................
10,000–19,999 .........................
20,000–39,999 .........................
40,000–79,999 .........................
80,000 and more .....................
Missing ....................................

49.1
49.8
51.9
57.2
59.3
43.2

8.0
7.2
8.5
8.6
5.0
7.1

Mother’s educational attainment:
High school dropout .................
High school graduate ...............
Some college ...........................
College and up .........................
Missing ....................................

43.8
53.8
56.4
57.9
36.6

8.4
7.1
7.3
5.2
10.2

Father’s educational attainment:
High school dropout .................
High school graduate ...............
Some college ...........................
College and up .........................
Missing ....................................

46.7
53.3
57.2
57.8
45.1

7.2
7.6
7.1
5.0
8.8

Table 2.

Percent of 12- to 13-year-old youths who report
jobs and hours per week on job with most hours,
by demographic characteristics, NLSY97

Demographic
categories

Percentage who
report jobs

Hours/week on job
with most hours

the overall well-being of youths’ lives and their future adult
lives. This issue is examined from different aspects: demographic background, family background, school performance, time use, and risky behaviors.
The two job measures, “ever held a job” and “hours per
week on the job with the most hours,” are examined first by
demographic and family backgrounds—age, race/ethnicity,
region, and metropolitan/nonmetropolitan area residence; the
number of parents/guardians and siblings in the household;
mother’s highest grade completed; father’s highest grade
completed; and parents’ earnings.
Then we examined the two job measures with school performance and time use. There are two measures for school

Job characteristics. Of the almost 3,000 12- and 13-year-olds
surveyed, 52.5 percent had held a job. (See table 1, page 5).
Of those who had worked, the average number of jobs held
was 1.6, and the average age of initiation was 11.6 years (the
median age of initiation was 12.0). Chart 1 on page 4 shows
the cumulative distribution of age initiation for those who
have worked by the time they were interviewed. It is easy to
see a major upturn in initiation around age 12. While recalling that nearly half the youths had not yet been initiated into
the labor force, it is clear that age 12 is a time when many
adolescents first get exposure to the working world.
These respondents are too young to work legally at restaurants, stores, and similar businesses. The types of jobs
held by 12- and 13-year-olds include primarily “freelance”
jobs, mainly baby-sitting, lawn mowing, and other yard work.
These three jobs make up nearly 75 percent of the jobs listed.
On average, these youths spend approximately 7 hours per
week on the job with the most hours (although the median is
only 4 hours per week),5 and their earnings average about $23
a week. Of the youths sampled, 62 percent had received
some kind of help in finding jobs.
Demographic characteristics. Girls seem somewhat more
likely than boys to hold jobs and spend more hours on the
job. (See table 2.) In fact, 54 percent of girls held a job,
compared with 51 percent of boys; 59 percent of white youths
held jobs, compared with about 40 percent of blacks, Hispanics, and others. Similarly, the higher the parents’ earnings, the
higher the likelihood that their child will have a job. This is
not surprising, as most of these jobs will be performed for
neighbors and friends who probably have similar income lev-

Monthly Labor Review

August 2001

21

Job Initiation

els; lower income neighbors may be less likely to pay someone to do these jobs. Comparable results are found for
mother’s and father’s education level—the higher the parents’
educational attainment, the more likely the child is to have a
job. Note, however, that working youths who are minority,
poorer, and have less-educated parents seem to work longer
hours.

School performance and time use. A similar pattern emerges
when examining the percentile score of the PIAT-Math
achievement test. The higher the youth’s score, the more
likely he or she is to have a job. (See table 3.) This is consistent with the previous relationships because minorities and
lower socio-economic status youths, on average, are likely to
have lower test scores. Number of hours worked is lowest for
the top quartile of students, but students in the quartile with
the second highest scores work the most hours per week.
Those who have at some time been suspended from school
are as likely to work as those never suspended; but when they
work, they work more hours.
One argument that has been raised against permitting 12and 13-year-old children to work is that it takes time away
from other important activities, such as schoolwork and reading. Conversely, working could have positive effects through
the responsibility it teaches and by reducing time spent in
unproductive activities. Respondents were asked whether
they spend time on the following activities: homework, extra
classes, watching television, and reading for pleasure. Surprisingly, in each case, those who responded yes were more
likely to hold a job. The most dramatic difference is in those
who report spending time on homework; of them, 53.5 percent reported holding a job. Of those who reported not doing
any homework (9 percent of the sample), only 44.6 percent
held jobs. Student workers who spend no time on homework
work an average of 9.4 hours per week, while those who do
spend time on homework spend only 6.9 hours per week on
the job. Similarly, student workers who do not take extra
classes work more hours than do student workers who take
extra classes (7.3 hours compared with 6.5).
It is possible that work is complementary with these four
activities. However, it is impossible to determine, as there is
no complete description of the youths’ time use. A bigger
caveat is that the time-use measure is essentially contemporaneous with the interview date, whereas the work hours measure could be from any time period. And given the probable
over-representation of summer jobs, it is doubtful that these
data represent either time substitution or complementarity.
Substance use and delinquency. Youths who exhibit risky or
dangerous behaviors are consistently more likely to have jobs
and tend to work longer hours than their more cautious counterparts. Respondents were asked questions about smoking,
22

Monthly Labor Review

August 2001

Table 3.

Percent of 12- to 13-year-old youths who report
jobs and hours per week on job with most
hours, by school performance, PIAT-Math score,
and time use, NLSY97
Categories

Percentage who Hours/week on job
report jobs
with most hours

School performance:
Ever suspended
from school ..........................
Never suspended
from school ..........................

53.4

8.6

52.4

6.7

45.3
53.9
56.6
58.1

7.0
7.6
7.8
6.3

53.5

6.9

44.6
57.4

9.4
6.5

50.5
52.9

7.3
7.1

44.8

5.9

53.2

7.2

51.4

6.8

PIAT-Math percentile score:

0–25 ........................................
26–50 ......................................
51–75 ......................................
76–100 ....................................
Time use:
Spent time on homework ........
Did not spend time
on homework ........................
Spent time on extra classes ...
Did not spend time
on extra classes ..................
Spent time watching TV ..........
Did not spend time
watching TV .........................
Spent time reading
for pleasure ..........................
Did not spend time reading
for pleasure ..........................

Table 4.

Percent of 12- to 13-year-old youths who report
jobs and hours per week on job with most
hours, by substance use or delinquent
behavior, NLSY97

Categories

Substance use
Ever smoked cigarettes .................
Never smoked cigarettes ...............
Ever drank alcohol .........................
Never drank alcohol .......................
Ever used marijuana .......................
Never used marijuana .....................
Delinquency
Ever run away from home ..............
Never run away from home .............
Ever carried a hand gun .................
Never carried a hand gun ...............
Ever purposely destroyed
property ......................................
Never purposely destroyed
property ......................................
Ever attacked another person ........
Never attacked another person ......
Arrested past year .........................
Not arrested past year ...................

Percentage who Hours/wk. on job
report jobs
with most hours

63.1
49.0
59.2
50.4
63.0
51.8

8.6
6.4
7.8
6.8
9.0
6.9

59.1
52.1
53.4
52.5

8.2
7.0
8.4
6.9

58.3

7.0

50.6
56.0
52.0
63.8
52.2

7.1
7.9
6.9
8.2
7.0

drinking, smoking marijuana, running away from home, carrying handguns, destroying property, fighting, and getting arrested. In every category, youths who answered yes to the
dangerous behavior are more likely to hold jobs. (See table 4.)

Also, they work at least as many hours as those who answered that they had not participated in the drug use or delinquency activities. There could be several explanations.
For example, these youths may engage in work to support
the cost of the dangerous or risky activities. However, the
causality could be in the other direction. With more disposable income, the youths have more choices about the types
of activities in which they can participate. Of course, it could
be an unobserved factor that influences both early initiation
into work and risky behaviors. Regardless of the explanation, this is interesting in light of the earlier results indicating
that youths who were white, had higher socio-economic status, and were higher-achieving students were more likely to
hold jobs.

Regression analysis. The previous analysis measures the
differences in the likelihood of employment (and hours
worked) for various characteristics of youths. However, the
analysis considers each variable separately, not all at once.
A regression model is used to examine the impact of all of
these variables on whether or not a youth has ever been
employed.6 Specifically, a probit regression model is used to
measure the impact of each variable on the probability of
having ever been employed.7
Table 5 shows the results of a probit regression of the
probability of having a job as related to demographic, school
performance and time use, and substance use and delinquency variables. The impact of the non-demographic variables can vary by sex. The model confirms earlier results that
being white and of higher socio-economic status (higher parental earnings and education levels) increases the probability that an individual will hold a job. However, the “number
of parents” variable indicates that children in two-parent families are less likely to hold a job than those in one-parent
families. Also, unlike the simpler tabulations, boys are more
likely to work than girls.
All six of the schooling and time-use variables have statistically significant effects for both sexes; however, not all
are numerically significant. Youths with higher PIAT-Math
test scores are more likely to hold jobs, though the effect is
not large. Most time-use variables have quite small effects,
although females who take extra classes are more likely to
hold jobs. Interestingly, the one strong effect is that students who had been suspended from school are more likely
to hold jobs.
As shown earlier, having smoked or been arrested in the
past year have positive associations with the likelihood of
having a job for both sexes. Males who had smoked marijuana, run away from home, or fought also had positive associations, as did females who drank alcohol or purposely destroyed property. Some rates are small, but having smoked
cigarettes is strongly associated with having worked. Inter-

Table 5.

Estimated marginal effects from probit
regression modeling the probability of
12- to 13-year-old youths having a job,
Variable

NLSY97

Estimated marginal effect

Intercept .....................................................
Age .............................................................
Male ............................................................
Black, non-Hispanic ....................................
Hispanic ......................................................
Other race/ethnicity ....................................
Northeast ....................................................
North Central ..............................................
West ...........................................................
Metropolitan Statistical Area .......................
Number of parents/guardians ....................
Number of siblings .....................................

–1.11 (0.001)
.10 (0.0001)
.03 (0.0003)
–.12 (0.0002)
–.14 (0.0002)
–.20 (0.0002)
.02 (0.0002)
.03 (0.0002)
–.05 (0.0002)
–.03 (0.0001)
–.05 (0.0001)
.004(0.00005)

Parents’ earnings, with greater than or
equal to $80,000 as the reference group:
$0–$9,999 ...............................................
10,000–19,999 ........................................
20,000–39,999 ........................................
40,000–79,999 ........................................
Missing ....................................................

–.04 (0.0003)
–.04 (0.0003)
–.03 (0.0002)
–.02 (0.0002)
–.12 (0.0003)

Mother’s education, with college graduate
as the reference group:
High school dropout ................................
High school graduate ..............................
Some college ...........................................
Missing ....................................................

–.02 (0.0002)
.01 (0.0002)
.01 (0.0002)
–.15 (0.0003)

Father’s education, with college graduate
as the reference group:
High school dropout ................................
High school graduate ..............................
Some college ...........................................
Missing ....................................................
Boys:
Ever suspended from school ..................
PIAT-Math percentile score .......................
Hours/week on homework .......................
Hours/week on extra classes ..................
Hours/week watching TV .........................
Hours/week reading for pleasure .............
Ever smoked cigarettes ..........................
Ever drank alcohol ..................................
Ever used marijuana ...............................
Ever run away from home .......................
Ever carried a hand gun ..........................
Ever purposely destroyed property .........
Ever attacked another person ................
Arrested past year ..................................
Girls:
Ever suspended from school ..................
PIAT-Math percentile score .......................
Hours/week on homework .......................
Hours/week on extra classes ..................
Hours/week watching TV .........................
Hours/week reading for pleasure .............
Ever smoked cigarettes ..........................
Ever drank alcohol ..................................
Ever used marijuana ...............................
Ever run away from home .......................
Ever carried a hand gun ..........................
Ever purposely destroyed property .........
Ever attacked another person ................
Arrested past year ..................................
LR test (Chi-Square) ................................
P-value ....................................................

Monthly Labor Review

–.05 (0.0002)
–.02 (0.0002)
.01 (0.0002)
–.08 (0.0002)
.04 (0.0002)
.0002 (0.000003)
.004 (0.00001)
–.001 (0.00002)
–.002 (0.00001)
–.001 (0.00001)
.09 (0.0002)
–.002 (0.0002)
.07 (0.0003)
.10 (0.0003)
–.07 (0.0002)
–.01 (0.0002)
.09 (0.0002)
.16 (0.0004)
.09 (0.0003)
.001 (0.000003)
–.0002 (0.00001)
006 (0.00002)
–.002 (0.00001)
–.001 (0.00001)
.15 (0.0002)
.03 (0.0002)
–.07 (0.0004)
–.01 (0.0004)
–.11 (0.0006)
.09 (0.0002)
–.09 (0.0003)
.02 (0.0005)
737025153
.0000

August 2001

23

Job Initiation

estingly, having carried a handgun is negatively associated
with having worked for both sexes, but having fought and
smoked marijuana are negative for females only.
To summarize, youths from families of higher socio-economic status, with better school performance (higher PIATMath scores), and who engage in positive time-use activities
such as reading and homework are more likely to be employed.
At the same time, youths who engage in risky behaviors or
have been suspended from school also have increased likelihood of early employment. It is difficult to speculate why
these various relationships exist. It could be that some
youths are “go-getters” who initiate early into many activities, good and bad. Or there could be two different types of
youth that engage in early work activity. As additional data
are released, it will be possible to estimate longitudinal models that are better suited to control for unobserved heterogeneity. In the future, the relationship between various adolescent behaviors, good and bad, with employment might be
better understood.

More research needed
This article used a rich new data source, the NLSY97, to look
at youths’ initiation into the labor market. Unlike any previous data set, the NLSY97 collects information on employment

from adolescents as young as 12 years. The NLSY97 provides detailed information about the responding youths, their
parents, and other family members, allowing a study of the
antecedents to labor market participation and labor supply.
The data also allow a better understanding of factors that
influence entry into the labor market.
Much concern exists over the impact of youths working
while in school, and the evidence is unclear.8 Models that
can capture earlier experiences will be richer in controlling for
the types of unobserved heterogeneity that confound the
work-school relationship. This article seeks to lay the groundwork for later research. We find that youths who are white
and come from higher socio-economic families are more likely
to initiate work earlier. These results are consistent with studies of older adolescents. However, a number of contrasting
results suggest there is more to the story. For example, youths
who have been suspended from school at some time and
youths who smoke (as well as engage in other deviant activities) are also more likely to work at early ages.
The long-term effects of early initiation into the labor market will become apparent as more years of data are collected
and as these 12- and 13-year-olds complete their schooling
and fully enter the labor market. The cumulative years of data
will allow a much better job of modeling work development
and the pathways to successful adult outcomes.
□

Notes
ACKNOWLEDGMENT: An earlier version of this article was presented
at the Conference of Early Results for the National Longitudinal
Survey of Youth, 1997 Cohort, November 18–19, 1999, Washington, DC . This project was funded by the U.S. Department of Labor.
However, views or opinions stated in this article are the authors and
do not necessarily represent the official position or policy of the
Department of Labor.
1
R.T. Michael and N.B. Tuma, “Youth Employment: Does Life
Begin at 16?,” Journal of Labor Economics , 1984, vol. 2, no. 4, pp.
465–476.
2
See for example, the National Educational Longitudinal Survey–
1988 or the Youth Risk Behavior Survey.
3
Analysis of the interview data revealed the final sample size to be
8,984.
4
The measure we’ve chosen will most likely over-represent summer

24

Monthly Labor Review

August 2001

jobs that have a greater number of hours. This over-representation
may affect the relationships we estimate with some of the variables.
5
The distribution has a very long right tail. We considered truncating the distribution to eliminate some very high values, but could not
establish clearly that these were errors.
6
Because youths aged 12–13 are not officially in the labor force and
no information is available on whether or not a respondent is looking
for employment, we do not distinguish between the concept of being in
the labor force and the concept of being employed.
7
A probit model is indicated because the outcome variable, whether
a respondent ever worked, is discrete. See D.R. Cox, Analysis of Binary
Data (London, Cambridge University Press, 1970).
8
See for example C.J. Ruhm, “Is High School Employment Consumption or Investment?,” Journal of Labor Economics , 1997, vol.
15, no. 4, pp. 735–776.

Working while in School

Youth employment during school:
results from two longitudinal surveys
Students who worked 20 or fewer hours per week
during the school year were more likely to attend college;
youths who worked a greater percentage of weeks
during the school year worked more consistently
when they reached ages 18 to 30
Donna S. Rothstein

Donna S. Rothstein is
a research economist
in the Office of
Employment and
Unemployment
Statistics, Bureau of
Labor Statistics. E-mail:
rothstein_d@bls.gov

A

ccording to a popular perception, youths
work more today than in the past and
their employment may not always lead to
desirable consequences. The concern is that a
young person’s employment, particularly when
the individual works many hours, may reduce
study time, increase school lateness and absenteeism rates, and adversely affect grades. However, a youth’s employment also may provide
some positive benefits, teaching about workplace
norms and responsibilities and helping to ease
the person’s subsequent transition from school
to work full time. In addition, these costs and benefits associated with a person’s working while
young could have an impact on the individual’s
long-term educational and labor market outcomes.
The first part of this article compares the employment of today’s youth with that of a youth
cohort from nearly 20 years ago. It asks whether
15- and 16-year-olds are, in fact, more likely to
work today and examines whether the likelihood
of a young person’s being employed while attending school varies across youths with different demographic characteristics. Also examined
in this part is how the distribution of hours of
work of 16-year-olds varies across the two cohorts.
Data come from the first round of a new survey of
youth—the National Longitudinal Survey of Youth
1997 (NLSY97)—and from the National Longitudinal Survey of Youth 1979 (NLSY79). In the first
round of each survey, 15- and 16-year-olds answered similar questions about their current em-

ployment status and hours of work. In addition,
many demographic measures that may be associated with youths’ decisions to work are similar
across the two surveys.
The second part of the article looks at the relationship between the employment of 16- and 17year-old youths attending school and their future
academic and labor market outcomes—specifically,
college attendance, weeks of work from ages 18
through 30, and number of jobs held from ages
18 through 30. Data are from the NLSY79, which
has followed the lives of survey respondents for
more than 20 years. As the NLSY97 cohort ages,
researchers will be able to use that survey to
study how today’s school-enrolled youths’ employment affects their long-term educational and
labor market experiences.

Background
Youths may choose to work while they are enrolled in school for a variety of reasons. They
may want to earn income to support their family,
pay for personal expenses (for example, a car), or
save for college. Parents may encourage youths
to work because they believe that working will
teach them responsibility and punctuality. In addition, youths (particularly those who are not bound
for college) may want to obtain job experience that
will assist them in their subsequent transition from
school to work. A goal of the 1994 School-to-Work
Opportunities Act is to strengthen the relation-

Monthly Labor Review

August 2001

25

Working while in School

ship between schooling and work. However, youths’ employment may, in fact, decrease their time for completing homework, cause them to come to school tired and less focused on
schoolwork, and, thus, adversely affect their academic
achievement.
Many earlier studies that examined the impact of youth
employment failed to take into account that the choice to
work while attending school and the consequences of working are intertwined. Youths who choose to work may be systematically different from youths who do not work. In addition,
youths who work a high number of hours may be different (even
before they begin to work) from those who work a moderate
number of hours. The differences may be related to observable characteristics, such as one’s family background, or to
unobservable characteristics, such as one’s motivation.
Thus, in itself, working while attending school may not be
the cause of particular positive or negative consequences;
rather, youths who choose to work may have some preexisting differences and would have had those outcomes anyway.
This factor complicates any evaluation of the impact of youth
employment.1
A few recent studies by economists have attempted to account for potential underlying differences between youths
who work and youths who do not work in analyzing the effects of employment on high school youths. Three studies in
particular used the NLSY79. Gerald S. Oettinger found that
intensive employment (in terms of either weeks or hours) during the school year has a negative impact on minority students’ grade point averages.2 Audrey Light, using a sample
of male terminal high school graduates, examined the impact
of high school employment on subsequent wages over a 9year period and concluded that such employment has a positive effect on wages only for the first 6 years after graduation
from high school.3 In contrast, Christopher J. Ruhm found
that employment during high school has a positive impact on
earnings 6 to 9 years after the student’s senior year.4 Although
both Ruhm and Light used NLSY79 data, they did so on different samples: Ruhm did not restrict his sample to those with no
postsecondary education and included both male and female
youths in his sample.
The article begins by looking at differences in characteristics of youths who worked while they were in school in 1979
and in 1997. It then examines the relationship between NLSY79
youths’ employment and their long-term educational and labor market outcomes. As noted earlier, this relationship does
not necessarily imply cause and effect.

Youth employment in 1979 and 1997
Data and variables. This section compares the employment
of two groups of 15- and 16-year-olds born nearly 20 years
apart. It uses two data sets that focus specifically on youth:
26

Monthly Labor Review

August 2001

the NLSY79 and the new NLSY97. The NLSY79 consists of data
on more than 12,000 youths aged 14 through 21 as of December 31, 1978. The NLSY97 data set has information on 9,000
youths aged 12 through 16 as of December 31, 1996. The discussion that follows uses information on the employment of
15- and 16-year-olds from the first interview year of each of
the two surveys.5
In comparing youth employment over time, it is important
to have a measure that is based on similar questions with the
same reference period. This is possible with the NLSY79 and
the NLSY97, because both cohorts received a section that
consists of questions from the Current Population Survey
(CPS) on their employment status and hours of work in the
week prior to the interview. Only NLSY97 respondents who
were aged 15 and older received these questions, while all
NLSY79 youths received them. Thus, this measure can be constructed for 15- and 16-year-olds across both surveys.6 Because the focus in this article is on the employment of youths
during the school term, only enrolled youths who were interviewed during the months of January through May are included in tabulations.
Studies have found that gender, race, ethnicity, family income, family structure, and maternal employment are predictors of the likelihood of a person’s working while young.7
Similar measures of these factors were constructed across the
two surveys, and the tables that follow tabulate youth employment by the various factors. For example, past studies
have found that white males are more likely to work than other
groups. Comparable measures of gender, race, and ethnicity
can be formed for both cohorts. Grade might also be a factor.
Holding age constant (at 15 or 16), being in a higher grade,
perhaps with peers who are older and thus more likely to work,
could increase the likelihood of a youth’s working while he or
she is in school.
Household income can have an ambiguous effect on
the likelihood of working. On the one hand, those in households with lower income may be more likely to work because they need to help support their families. On the other
hand, youths in low-income households may live in areas
with less economic opportunity and have less access to
transportation, decreasing the likelihood of their working.
The NLSY 79 contains a measure of family income in the
year prior to the survey, and the NLSY 97 has a measure of
household income in the previous year. The two measures
are fairly similar and are categorized into four income levels in the analysis that follows.
Maternal employment and family structure may affect the
likelihood of youths’ employment. Families in which the
mother is employed may place a stronger emphasis on work
among all household members. Both the NLSY79 and the
NLSY97 have measures of whether the mother worked during
the previous year. Measures of family structure are con-

structed as of the date of the interview for both cohorts.8
Youths who have engaged in certain behaviors may be more
likely to work. For example, youths who have smoked cigarettes or used marijuana may be more anxious to enter the
adult world, which includes working. Round 1 of the NLSY97
asked youths whether they had ever used marijuana or ever
smoked a cigarette. The 1984 interview of the NLSY79
asked the age when the youth first smoked a cigarette and
the year the youth first used marijuana. These questions are
used to construct a measure of whether those who ever
engaged in the behavior at issue did so by the date of their
1979 interview.9
The effect of having ever been suspended from school on
the likelihood of working is ambiguous. On the one hand,
youths who have received suspensions may enjoy school
less than others and be more likely to want to enter the world
of work. On the other hand, if potential employers check with
the school as a reference, youths who have received suspensions may be less likely to be offered a job. The NLSY97 round1 interview asked whether the youth had ever been suspended.
In the 1980 interview, the NLSY79 asked for the number of
times the youth had ever been suspended and the date of the
most recent suspension. The questions are used to determine
whether the youth had ever been suspended by the date of
the 1979 interview.10

Employment of 15- and 16-year-olds. Are youths working
more now than in the past? NLSY79 and NLSY97 data suggest
that the answer is no. About equal percentages (25 percent to
26 percent) of 15-year-olds who were enrolled in school
worked during the reference week—that is, the week prior to
the NLSY79 and NLSY97 survey interviews. (See table 1.) The
percentage of school-enrolled 16-year-olds who worked during the reference week was also nearly the same in the two
survey years (36 percent and 38 percent; see table 2.)11 There
is a clear step up of more than 10 percentage points in the
percent of youths working at age 15 to the percent working at
age 16. In part, this may be due to legal restrictions on the
types of work that 15-year-olds can perform. In addition, most
youths may obtain a driver’s license at age 16, which can
increase their access to jobs and also motivate them to work
to pay for the expenses of having a car.12 The actual number
of hours worked in the week prior to the interview among
youths who did work were also fairly similar across the two
cohorts (numbers not shown in table). The average was 10.6
for 15-year-olds in 1979 and 8.4 for 15-year-olds in 1997, a
small decrease over time. Average hours of work per week
were higher for 16-year-olds: 15.2 in 1979 and 14.6 in 1997.
Turning first to 15-year-olds, table 1 shows that the likelihood of a youth’s working while in school varies by many
background characteristics. The direction of many of the effects is similar across the two cohorts. For example, whites

were more likely to work than were blacks or Hispanics.13
Also, blacks were more than 40 percent more likely to work
while in school in 1997 than in 1979. In both cohorts, youths
in eighth grade or lower were less likely to work than youths
in higher grades. Youths who had ever smoked were more
likely to work than other youths. Youths in households with
lower income were generally less likely to work, possibly because, as mentioned earlier, they may have lived in more depressed areas and have had less access to public transportation.
The table also shows that youths in both types of two-parent
families were more likely to work than those in female-parent
families. Only in the NLSY97 sample were youths who had
ever been suspended substantially less likely to work. In the
NLSY79, 15-year-old female youths were less likely to work
than their male counterparts, but the gender difference between the percent of youths working was not significant in
the NLSY97.
Sixteen-year-old female youths were also significantly less
likely to work than males were in the NLSY79, but not the
NLSY97. (See table 2.) In both cohorts, whites were more likely
to work than were blacks or Hispanics. Black 16-year-olds in
1997 were almost 40 percent more likely to work than in 1979.
The school grade appears to matter for both cohorts: youths
in the 11th grade were more likely to work than youths in the
10th grade. In the NLSY79 cohort only, youths who had ever
smoked or used marijuana were significantly more likely to
work. In both survey cohorts, youths in households with less
than $25,000 income were less likely to work, and in both cohorts, youths in households where the mother worked were
more likely to work themselves.
The information in tables 1 and 2 suggests that young workers in 1979 and 1997 shared many characteristics. Particularly
interesting are the hours of work among 16-year-olds in both
cohorts.

Hours of work of 16-year-olds. In 1998, a National Research
Council panel recommended that the number of hours of work
for 16-year-olds during the school term be limited.14 The Fair
Labor Standards Act imposes a maximum of 18 hours of work in
a school week for 14- and 15-year-olds engaged in nonagricultural jobs.15 Although the National Research Council does not
recommend a particular maximum number of hours for 16-yearolds, it does note that research indicates that working more than
20 hours per school week can have a negative impact on youths’
academic outcomes. Table 3 shows that similar percentages of
youths enrolled in school in the two cohorts worked more than
20 hours during the week prior to the survey (8.4 percent in the
NLSY79 and 10.5 percent in the NLSY97).
As with the employment of 15- and 16-year-olds, gender
differences are seen in hours of work in the NLSY79 cohort
only. Male 16-year-olds in the NLSY79 were more likely to
work more than 20 hours per week than were their female

Monthly Labor Review

August 2001

27

Working while in School

Table 1.

Percent of school-enrolled 15-year-olds who
worked during the week prior to the interview,1
National Longitudinal Survey of Youth (NLSY),
1979 and 1997, by sex, race or Hispanic
origin, grade in school, delinquent behavior,
household income, family structure, and
mother’s work status

Characteristic

NLSY79

NLSY97

Total .......................................................
Sex:
Male ..............................................................
Female ..........................................................

25.2

25.8

27.8
22.4

Race or ethnicity:
White ............................................................
Black ............................................................
Hispanic origin ..............................................
Grade in school:
Less than 9 ..................................................
9 ...................................................................
10 .................................................................

Table 2.

Percent of school-enrolled 16-year-olds who
worked during the week prior to the interview,1
National Longitudinal Survey of Youth (NLSY),
1979 and 1997, by sex, race or Hispanic
origin, grade in school, delinquent behavior,
household income, family structure, and
mother’s work status

Characteristic

NLSY79

NLSY97

Total ....................................................

36.4

38.4

27.9
23.7

Sex:
Male ............................................................
Female ........................................................

39.3
33.6

39.7
36.9

28.7
10.6
15.0

30.3
15.3
17.1

Race or ethnicity:
White ..........................................................
Black ..........................................................
Hispanic origin ............................................

40.4
17.8
26.1

45.0
24.5
29.7

20.1
21.5
29.2

15.0
25.8
29.5

Grade in school:
Less than 10 ..............................................
10 ...............................................................
11 ...............................................................

23.8
29.5
43.3

19.1
37.1
48.0

40.7
35.7

37.4
38.8

Delinquent behavior:
Ever suspended?
Yes ............................................................
No ..............................................................

24.4
25.4

18.5
28.7

Delinquent behavior:
Ever suspended?
Yes ..........................................................
No ............................................................

Ever smoked a cigarette?
Yes ............................................................
No ..............................................................

28.9
21.0

28.3
23.2

Ever smoked a cigarette?
Yes ..........................................................
No ............................................................

39.8
31.9

40.8
35.2

Ever used marijuana?
Yes ............................................................
No ..............................................................

28.5
24.2

29.5
24.4

Ever used marijuana?
Yes ..........................................................
No ............................................................

44.5
32.1

39.8
37.7

Household income (in 1996 dollars):
Less than $25,000 .......................................
$25,000–$44,999 ..........................................
$45,000–$69,999 ..........................................
$70,000 or more ...........................................

18.7
19.9
30.1
28.4

23.3
18.7
34.6
30.1

Household income (in 1996 dollars):
Less than $25,000 .....................................
$25,000–$44,999 ........................................
$45,000–-$69,999 ......................................
$70,000 or more .........................................

23.3
34.7
47.7
42.8

26.4
45.7
42.6
40.9

Family structure and mother’s work status:
Two-biological-parent family ..........................
Two-parent family ..........................................
Female-parent family ....................................
Not living with parent ....................................

26.4
34.4
19.0
12.9

30.2
26.5
18.7
18.3

Family structure and mother’s work status:
Two-biological-parent family ........................
Two-parent family ........................................
Female-parent family ..................................
Not living with parent ..................................

37.6
42.8
33.3
16.6

41.3
42.3
31.4
24.4

Mother worked in previous calendar year?
Yes ............................................................
No ..............................................................

27.9
21.9

28.8
20.2

Mother worked in previous calendar year?
Yes ..........................................................
No ............................................................

40.7
31.5

42.7
27.1

1
The interview took place in any of the months from January through May,
in 1979 or 1997.

1
The interview took place in any of the months from January through May,
in 1979 or 1997.

NOTE: The National Longitudinal Survey of Youth 1979 (NLSY79) surveyed male and female youths who were aged 14 to 21 years on December
31, 1978. The National Longitudinal Survey of Youth 1997 (NLSY97) surveyed
male and female youths who were aged 12 to 16 on December 31, 1996.

NOTE: The National Longitudinal Survey of Youth 1979 (NLSY79) surveyed male and female youths who were aged 14 to 21 years on December
31, 1978. The National Longitudinal Survey of Youth 1997 (NLSY97) surveyed
male and female youths who were aged 12 to 16 on December 31, 1996.

counterparts. Female youths in the NLSY97 cohort were about
70 percent more likely to work more than 20 hours per week
than female youths in the NLSY79 cohort. Racial differences
in employment are found in both cohorts, with whites more
likely than blacks to work more than 20 hours per week as
well as between 1 and 20 hours per week.
In both cohorts, youths in the 11th grade were nearly twice

as likely to work more than 20 hours per week than youths in
the 10th grade. With respect to delinquent behavior, youths
in both cohorts who had ever been suspended were more
likely to work 21 or more hours per week. In the NLSY79 cohort only, 16-year-olds who had ever smoked a cigarette were
significantly more likely to work more than 20 hours per week,
and those who had ever used marijuana were much more

28

Monthly Labor Review

August 2001

Table 3.

Hours worked per week by school-enrolled 16-year-olds in the week prior to the interview,1
National Longitudinal Survey of Youth (NLSY), 1979 and 1997, by sex, race or Hispanic origin, grade
in school, delinquent behavior, household income, family structure, and mother’s work status
NLSY79

Characteristic

NLSY97

0
hours

20 or
fewer
hours

21 or
more
hours

0
hours

20 or
fewer
hours

21 or
more
hours

Total .........................................................................
Sex:
Male ...................................................................................
Female ...............................................................................

63.6

28.0

8.4

61.6

27.9

10.5

60.7
66.4

28.4
27.7

10.9
6.0

60.3
63.1

29.1
26.7

10.7
10.2

Race or ethnicity:
White .................................................................................
Black .................................................................................
Hispanic origin ...................................................................

59.6
82.2
73.9

31.1
13.8
18.2

9.3
4.0
8.0

55.0
75.5
70.3

32.7
18.3
21.7

12.3
6.2
8.0

Grade in school:
Less than 10 .....................................................................
10 ......................................................................................
11 ......................................................................................

76.2
70.5
56.7

18.3
23.9
32.4

5.5
5.7
10.9

80.9
62.9
52.0

13.5
28.8
31.8

5.6
8.3
16.1

59.3
64.3

29.2
28.1

11.5
7.6

62.6
61.2

23.1
29.9

14.4
8.9

60.2
68.1

29.9
26.1

9.8
5.7

59.2
64.8

29.3
26.2

11.6
9.0

55.5
67.9

34.4
24.9

10.1
7.3

60.2
62.3

27.8
28.0

12.0
9.6

Household income (in 1996 dollars)
Less than $25,000 ............................................................
$25,000–$44,999 ...............................................................
$45,000–$69,999 ...............................................................
$70,000 or more ................................................................

76.7
65.3
52.3
57.2

20.5
25.7
35.8
32.5

2.8
9.0
11.9
10.3

73.6
54.3
57.4
59.1

18.7
35.1
29.0
33.2

7.7
10.6
13.5
7.7

Family structure and mother’s work status:
Two-biological-parent family ...............................................
Two-parent family ...............................................................
Female-parent family .........................................................
Not living with parent .........................................................

62.4
57.2
66.7
83.4

28.6
29.4
27.2
14.6

9.0
13.4
6.0
2.1

58.7
57.7
68.6
75.6

31.4
28.8
21.7
23.3

9.9
13.5
9.6
1.1

Mother worked in previous calendar year?
Yes .................................................................................
No ...................................................................................

59.3
68.5

32.0
22.4

8.7
9.1

57.3
72.9

31.5
20.1

11.3
6.9

Delinquent behavior:
Ever suspended?
Yes .................................................................................
No ...................................................................................
Ever smoked a cigarette?
Yes .................................................................................
No ...................................................................................
Ever used marijuana?
Yes .................................................................................
No ...................................................................................

1
The interview took place in any of the months from January through May,
in 1979 or 1997.
NOTE: The National Longitudinal Survey of Youth 1979 (NLSY79) sur-

likely to work between 1 and 20 hours per week. Also in the
NLSY79 cohort only, youths in households with an annual
income of less than $25,000 were much less likely to work
more than 20 hours per week than were youths in households with higher incomes. However, youths in households
in the lower income category in both cohorts were generally
less likely than youths in households with higher incomes to
work between 1 and 20 hours per week. These results suggest that 16-year-olds in lower income households are not
shouldering a larger burden of work hours than are 16-yearolds in households with higher incomes.
In sum, 15- and 16-year-olds were as likely to work while
attending school in 1997 as they were nearly 20 years earlier,

veyed male and female youths who were aged 14 to 21 years on December
31, 1978. The National Longitudinal Survey of Youth 1997 (NLSY97) surveyed
male and female youths who were aged 12 to 16 on December 31, 1996.

according to information from the first interviews of the two
surveys of youths. Youths also worked about the same average number of hours in 1997 as they did in 1979. In both
cohorts, from age 15 to age 16, there is a significant increase
in the percentage of youths working and the average number
of hours they worked.
In both cohorts, the likelihood of working while young
varies across numerous background characteristics. Many
patterns of youth employment are similar for 15- and 16-year
olds across both cohorts. In general, whites tend to be more
likely to work than blacks or Hispanics. Also, youths in higher
grade levels are more likely to be employed, as are youths
who have participated in delinquent activities. Further,
Monthly Labor Review

August 2001

29

Working while in School

youths in households with low income are less likely to work.
Gender differences are found in the NLSY79 cohort only: male
youths are more likely to be employed and to work more hours
than female youths. An interesting result is also found with
respect to race: blacks in the NLSY97 are more likely to work
than blacks in the NLSY79 cohort.

Youth employment and long-term outcomes
Data. This section examines the relationship between the
number of hours and weeks a 16- or 17-year-old works during
school weeks and later outcomes in terms of college attendance, weeks worked each year, and the number of jobs held
from ages 18 through 30. Data are from the NLSY79, a sample
of more than 12,000 men and women born in the years 1957
through 1964. These individuals were first interviewed in 1979,
when they were ages 14 to 22; they were interviewed annually
through 1994 and are now surveyed biennially. The analysis
that follows uses data for members of the sample who were
born in 1962–64, for whom a week-by-week employment history is available from age 16 on.
In contrast to the previous section, in which youth work
experience is defined for the week prior to the interview date,
work experience in this section exploits the longitudinal nature of the NLSY79 data and is measured over school weeks
while youths were ages 16 and 17.16 To differentiate between
effects of the number of weeks worked and effects of the
number of hours worked per week, youths’ work behavior at
ages 16 and 17 is divided into five mutually exclusive categories of intensity:
Table 4.

1. did not work during school weeks at age 16 or 17;
2. worked less than 50 percent of school weeks and averaged 20 or fewer hours of work per week;
3. worked less than 50 percent of school weeks and averaged more than 20 hours of work per week;
4. worked more than 50 percent of school weeks and averaged 20 or fewer hours of work per week;
5. worked more than 50 percent of school weeks and averaged more than 20 hours of work per week.17
The analysis that follows explores the association between
youths’ early work behavior and longer term educational and
labor market experiences.18 The education outcome is whether
the individual received some college education by age 30. Detailed work history data are used to create two employment outcome measures: percent of weeks of work from ages 18 through
30 and number of jobs held from ages 18 through 30.19 Note that
this analysis of youth employment and longer term labor market
and educational experiences cannot imply causality. Indeed,
youths within each of the foregoing five categories may be systematically different from one another even before they begin
working. However, the unique longitudinal NLSY79 data can
provide valuable insights into the possible relationship between
individuals’ working while they are young and the outcomes
they attain as adults.

Youth employment at ages 16 and 17. Eighty percent of
youths worked at ages 16 and 17 at some point while school was
in session. (See table 4.) About 41 percent of youths worked

Work status during the school year of youths aged 16 to 17 years in 1978–82,1 by sex, race or Hispanic origin,
and family income
Worked 50 percent or less
of school weeks

Age in 1978–82
and characteristic

Worked more than 50 percent
of school weeks

Did not work
Averaged 20 or fewer Averaged 21 or more Averaged 20 or fewer Averaged 21 or more
hours per week
hours per week
hours per week
hours per week

Total ...................................
Sex:
Male ........................................
Female ....................................

20.0

19.6

18.0

22.0

18.8

17.5
22.5

17.9
21.3

20.3
15.6

20.7
23.4

21.7
15.9

Race or ethnicity:
White ......................................
Black ......................................
Hispanic origin ........................

15.3
40.8
26.0

20.1
19.2
17.8

17.0
20.4
24.6

24.8
10.3
14.4

21.1
8.4
16.5

Family income in 1979 (in 1996
dollars):
Less than $25,000 ................
$25,000 to $44,999 ...............
$45,000 to $69,999 ...............
$70,000 or more ....................

31.6
23.6
11.2
11.4

18.8
19.3
22.3
21.2

22.3
17.0
16.8
14.8

12.4
19.7
24.7
33.8

13.7
18.8
23.4
17.9

1

Individuals aged 14 to 16 on December 31, 1978.

NOTE: The National Longitudinal Survey of Youth 1979 (NLSY79) surveyed male and female youths who were aged 14 to 21 years on December

30

Monthly Labor Review

August 2001

31, 1978. The table excludes individuals who turned 16 before 1978. Rows do
not add to 100, due to the nonreporting of information on hours and weeks of
work for a small number of working respondents.

more than half of all school weeks. These youths were fairly
evenly split between averaging 20 or fewer hours per week
and averaging more than 20 hours per week. The same was
true of those who worked a relatively low percentage of school
weeks (50 percent or less). Note that the work undertaken at
ages 16 and 17 for this group born in 1962–64 occurred during
1978–82, a period that included the last 2 years of a business
cycle expansion and both the 1980 and 1981–82 recessions.
Male youths were more likely than female youths to have
worked during school weeks at ages 16 and 17 (83 percent and
78 percent, respectively). In addition, working male youths
were more likely than female youths to average 21 or more
hours per week.
White and Hispanic 16- and 17-year-olds were much more
likely to have worked during school weeks (85 percent and 74
percent, respectively) than were blacks (59 percent). Hispanics were more likely to work a high average number of hours
and a relatively low percentage of weeks, compared with
whites and blacks. Whites were more likely to average a high
number of hours per week and to work a relatively high percentage of weeks, compared with blacks and Hispanics.
Differences in 16- and 17-year-olds’ work behavior while
they were in school were also found with respect to family
income categories. Youths in families with incomes of less
than $25,000 were less likely to work than youths in families
in higher income categories. Youths in families with incomes
of $70,000 or more were more likely both to average a low
number of hours per week and to work a high percentage of
school weeks, compared with youths in lower family income
categories.

Educational attainment at age 30. More than half of those
who averaged 20 or fewer hours of work per school week at
ages 16 and 17 had at least some college education by age 30.
(See chart 1.) By contrast, by age 30, less than half of those
who did not work at all or who worked more than 20 hours a
week at ages 16 and 17 had attained at least some college
education. These findings hold regardless of whether one
worked more or less than 50 percent of school weeks, and the
same pattern is also generally found for 30-year-old men and
women separately. (See chart 2.)
The findings apply to whites as well (see chart 3), but the
educational attainment of blacks and Hispanics is not as
clearly related to the hours they worked at 16 and 17. With one
exception, blacks who did not work at all at those ages were
significantly less likely than blacks who did work to have at
least some college education by age 30. The lone exception is
the group that worked 50 percent or less of school weeks and
averaged 21 or more hours per week. More than 60 percent of
Hispanics who worked more than 50 percent of school weeks,
but fewer than 20 hours a week, had some college education

by age 30, whereas much less than half of Hispanics in each of
the other weeks-and-hours-of-work categories had any college education.

Work experience, ages 18 through 30. The NLSY79 collects
extensive employment data from respondents. The analysis
that follows uses this detailed work history information to
examine the percentage of weeks worked by individuals over
the years when they are aged 18 through 30. The analysis
continues to focus on groups divided by hours and weeks of
work undertaken by those attending school at ages 16 and
17.
The data show a general pattern: each step up in the percentage of school weeks worked at the aforementioned ages
is associated with a step up in the percentage of weeks
worked during the next 13 years, regardless of the category
of hours worked per week. More specifically, individuals who
did not work during school weeks at ages 16 and 17 worked
64 percent of weeks from ages 18 through 30 (see table 5),
and those who worked 50 percent or less of school weeks at
ages 16 and 17 worked an average of 74 percent of weeks
from ages 18 to 30. The percentage was even higher (between 82 percent and 84 percent, depending on the category
of hours worked per week) for youths who worked more than
50 percent of school weeks at those ages. This overall stepup pattern also holds over ages 18 through 30 for both men
and women and regardless of race or ethnicity. Furthermore,
the pattern essentially holds for the narrower age ranges of
18 to 22, 23 to 26, and 27 to 30. In general, the percentage of
weeks worked rises from ages 18 to 22 to ages 23 to 26 and
then remains steady at ages 27 to 30.
Tables in this article indicate that white youths tend to work
more than black youths. Whites also typically work more
weeks from ages 18 to 30 than do blacks, regardless of the
number of hours or weeks they work while they are in school.
The sole exception is that, for those individuals who worked
more than 50 percent of school weeks and averaged 21 or
more hours per week while they were young, there was no
significant difference between the percentage of weeks
worked by blacks and whites from ages 18 through 30.
From ages 23 through 30, individuals who attained some
college education by age 30 worked a higher percentage of
weeks than did individuals with no college education. For
those 18 through 22, however, the pattern was reversed, probably because individuals with some college education pursued their college careers during those years. The overall pattern that each step up in the number of school weeks a person
worked at ages 16 and 17 is associated with a step up in the
number of weeks that person worked when he or she was
older generally holds for those in both the higher and lower
educational groups. For individuals with some college, however, the percentage of weeks worked at ages 27 through 30

Monthly Labor Review

August 2001

31

Working while in School

Percent of
of individuals
individuals with
with at
at least
least some
some college
college education
education at
at age
age 30,
30, by
by average
average hours
hours
Chart 1. Percent
worked
worked during
during school
school weeks
weeks at
at ages
ages 16
16 and
and 17
17 in
in 1978–82
1978–82
Percent

Percent
70

70

60

60

50

50

40

40

30

30

20

20

10

10

0

Did not work

Averaged 21 or more Averaged 20 or fewer
hours per week
hours per week

Averaged 20 or fewer
hours per week

Worked 50 percent or less of weeks

0
Averaged 21 or more
hours per week

Worked more than 50 percent of weeks

SOURCE: National Longitudinal Survey of Youth 1979.

Percent of individuals with at least some college education at age 30, by average hours
worked during school weeks at ages 16 and 17 in 1978–82, by sex

Chart 2.

Percent

Percent

70
60

70

■
□

Men
Women

60

50

50

40

40

30

30

20

20

10

10

0

0
Did not work

Averaged 20 or fewer
hours per week

Averaged 21 or more Averaged 20 or fewer Averaged 21 or more
hours per week
hours per week
hours per week

Worked 50 percent or less of weeks
SOURCE: National Longitudinal Survey of Youth 1979.

32

Monthly Labor Review

August 2001

Worked more than 50 percent of weeks

Chart 3.

Percent of individuals with at least some college education at age 30, by average hours
worked during school weeks at ages 16 and 17 in 1978–82, by race and Hispanic origin
Percent
70

Percent
70
60

White

Black

Hispanic origin

60

50

50

40

40

30

30

20

20

10

10

0

0
Did not work

Averaged 20 or
fewer hours per
week

Averaged 21 or
more hours per
week

Worked 50 percent or less of weeks

Averaged 20 or
fewer hours per
week

Averaged 21 or
more hours per
week

Worked more than 50 percent of
weeks

SOURCE : National Longitudinal Survey of Youth 1979.

differs little among those who had different work experiences
while they were young.

Number of jobs held, ages 18 through 30. The analysis concludes with an examination of the number of jobs individuals
held during various periods when they were aged 18 through
30. Again, individuals are grouped by hours and percent of
school weeks worked at ages 16 and 17. Young workers tend
to have a high level of job mobility during their early years in
the labor market and thus hold a relatively high number of
jobs. Early job mobility may represent job shopping and may
be beneficial for a variety of reasons. For example, it can allow
young workers to learn about different work environments.
However, as workers age, they often have less job mobility,
which may represent better matching between workers and
their jobs.20
From ages 18 through 30, individuals who did not work
while they were 16 and 17 held a lower average number of jobs
than persons who worked at those ages. (See table 6.) Although this relationship also held for the narrower range from
age 18 to age 22, across the older age ranges, the number of

jobs was fairly similar across all categories of hours and weeks
worked while the individual was young.
Men held an average of 8.9 jobs, and women held an average
of 8.4 jobs, from ages 18 through 30. At ages 18 through 22, men
and women held about the same number of jobs within all categories of hours and weeks of work while they were 16 and 17.
From ages 27 to 30, however, men held a significantly higher
number of jobs than women did within most of the categories.
Whites held more jobs (8.7) than did blacks or Hispanics
(8.3 and 8.2, respectively) from ages 18 through 30. Whites
also held more jobs from ages 18 to 22 than did blacks across
the aforementioned work categories. However, from ages 27
to 30, whites generally held either the same or fewer jobs than
blacks did within each category.
Individuals with at least some college education held 9.1
jobs from ages 18 through 30, in contrast to 8.2 jobs held by
those with a high school or lower education level. Over those
ages, within both education categories, individuals who did
not work at ages 16 and 17 generally held a lower average
number of jobs than those who worked during the school
term at those ages.

Monthly Labor Review

August 2001

33

Working while in School

Table 5.

Percent of weeks employed by individuals aged 18 to 30 years in 1980–95, by age, education, sex, race or
Hispanic origin, and percent of school weeks and number of hours worked at ages 16 and 17
Worked 50 percent
or less
of school weeks

Age in 1980–95 and characteristic

Total

Worked more than 50 percent
of school weeks

Did not work
Averaged 21
Averaged 20 Averaged 21
Averaged 20
or more
or fewer
or fewer
or more
hours per week hours per week hours per week hours per week

Total, 18 to 30 years in 1980–95 ......................
Sex:
Men .........................................................................
Women ....................................................................

75.7

63.8

74.3

74.3

81.8

83.9

81.3
70.0

70.1
58.7

79.6
69.8

78.1
69.2

87.1
77.0

89.0
76.6

Race or ethnicity:
White .......................................................................
Black .......................................................................
Hispanic origin .........................................................

78.1
64.6
72.7

67.7
56.2
62.7

75.7
66.7
72.9

76.5
68.0
70.7

82.5
72.1
79.9

83.9
82.5
84.8

Education:
High school or less .................................................
Some college or more ..............................................

73.3
78.3

59.5
70.0

71.8
76.6

72.0
77.3

82.5
81.2

83.0
85.0

Total, 18 to 22 years in 1980–87 ......................

65.9

48.0

63.5

63.0

75.5

78.8

Sex:
Men .........................................................................
Women ....................................................................

69.2
62.5

52.8
44.1

64.6
62.5

65.0
60.2

76.7
74.5

83.0
73.1

Race or ethnicity:
White .......................................................................
Black .......................................................................
Hispanic origin .........................................................

68.9
51.3
62.8

52.0
40.0
47.9

65.6
51.4
63.5

64.7
58.9
58.6

76.6
60.3
74.4

78.8
75.7
82.0

Education:
High school or less .....................................................
Some college or more .................................................

67.4
64.2

48.4
47.2

65.3
61.9

65.2
60.1

80.7
71.5

81.2
76.0

Total, 23 to 26 years in 1985–91 ......................
Sex:
Men .........................................................................
Women ....................................................................

80.5

70.5

79.8

80.1

85.0

87.1

86.5
74.5

78.0
64.6

85.7
74.8

84.0
74.9

90.3
80.4

92.8
79.3

Race or ethnicity:
White .......................................................................
Black .......................................................................
Hiispanic origin ........................................................

82.8
70.6
76.5

74.7
62.2
69.1

81.1
74.6
74.2

82.4
74.2
76.7

85.7
77.1
79.9

87.2
85.9
87.5

Education:
High school or less .................................................
Some college or more ..............................................

76.2
85.2

64.4
79.8

75.3
83.7

75.9
85.6

82.8
86.7

84.8
89.9

Total, 27 to 30 years in 1989–95 ......................

80.8

73.2

79.7

80.1

85.0

85.8

Sex:
Men .........................................................................
Women ....................................................................

88.2
73.4

80.4
67.6

88.7
72.0

85.3
73.1

93.5
77.3

91.5
77.8

Race or ethnicity:
White .......................................................................
Black .......................................................................
Hispanic origin .........................................................

82.8
71.7
78.2

76.8
66.2
71.7

80.7
74.1
79.8

82.7
71.0
76.7

85.5
78.2
82.5

86.0
86.2
84.8

Education:
High school or less .................................................
Some college or more ..............................................

76.4
85.7

66.3
83.4

74.8
84.0

75.1
86.8

83.7
85.9

83.5
88.7

N OTE : The National Longitudinal Survey of Youth 1979 ( NLSY79) surveyed
male and female youths who were aged 14 to 21 years on December 31, 1978.

34

Monthly Labor Review

August 2001

The table excludes individuals who turned 16 before 1978.

Table 6.

Number of jobs held by individuals aged 18 to 30 years in 1980–95, by age, education, sex, race or Hispanic
origin, and percent of school weeks and number of hours worked at ages 16 and 17
Worked 50 percent
or less
of school weeks

Age in 1980–95 and characteristic

Total

Did
not
work

Worked more than 50 percent
of school weeks

Averaged 20
Averaged 20
Averaged 21
Averaged 21
or fewer
or fewer
or more
or more
hours per week hours per week hours per week hours per week

Total, 18 to 30 years in 1980–95 .................

8.6

7.7

9.0

9.2

8.8

8.4

Sex:
Men .......................................................................
Women ..................................................................

8.9
8.4

8.3
7.2

9.3
8.8

9.3
9.1

8.8
8.8

8.8
7.9

Race or ethnicity:
White .....................................................................
Black .....................................................................
Hispanic origin .......................................................

8.7
8.3
8.2

8.1
7.4
6.2

9.1
8.5
9.5

9.3
9.3
8.4

8.7
8.7
9.5

8.4
9.0
8.6

Education:
High school or less ...............................................
Some college or more ............................................

8.2
9.1

7.1
8.5

8.9
9.1

9.2
9.3

8.0
9.5

8.1
8.9

Total, 18 to 22 years in 1980–87 .................
Sex:
Men .......................................................................
Women ..................................................................

4.5

3.5

4.7

4.7

4.9

4.6

4.5
4.4

3.7
3.4

4.7
4.7

4.7
4.7

4.9
5.0

4.6
4.5

Race or ethnicity
White .....................................................................
Black .....................................................................
Hispanic origin .......................................................

4.6
3.7
4.2

3.9
3.0
2.8

4.8
4.1
5.0

4.8
4.4
4.3

5.0
4.3
5.0

4.6
4.2
4.5

Education:
High school or less ...............................................
Some college or more ............................................

4.1
4.8

3.2
4.0

4.4
4.9

4.6
4.8

4.5
5.3

4.3
5.0

Total, 23 to 26 years in 1985–91 .................
Sex:
Men .......................................................................
Women ..................................................................

3.0

2.8

3.0

3.0

3.1

3.0

3.1
2.8

3.1
2.5

3.0
3.0

3.0
3.0

3.0
3.1

3.2
2.6

Race or ethnicity:
White .....................................................................
Black .....................................................................
Hispanic origin .......................................................

3.0
2.9
2.8

2.9
2.7
2.4

3.0
3.0
3.0

3.0
3.1
2.7

3.1
2.8
3.1

2.9
3.2
3.0

Education:
High school or less ...............................................
Some college or more ............................................

2.7
3.2

2.5
3.2

2.9
3.2

2.9
3.1

2.7
3.3

2.8
3.2

Total, 27 to 30 years in 1989–95 .................
Sex:
Men .......................................................................
Women ..................................................................

3.0

3.0

3.1

3.3

2.8

2.9

3.2
2.8

3.2
2.8

3.3
2.9

3.4
3.2

2.9
2.7

3.2
2.6

Race or ethnicity:
White .....................................................................
Black .....................................................................
Hispanic origin .......................................................

3.0
3.2
2.9

3.0
3.0
2.4

3.1
3.0
3.1

3.3
3.4
3.0

2.7
3.2
3.2

2.9
3.5
3.0

Education:
High school or less ...............................................
Some college or more ............................................

3.0
3.0

2.8
3.1

3.3
2.9

3.4
3.3

2.7
2.9

3.0
2.9

NOTE: The National Longitudinal Survey of Youth 1979 (NLSY79) surveyed
male and female youths who were aged 14 to 21 years on December 31, 1978.

The table excludes individuals who turned 16 before 1978.

Monthly Labor Review

August 2001

35

Working while in School

In sum, 80 percent of youths born in 1962–64 worked at
some point during the school term while they were ages 16
and 17. Youths who worked an average of 20 or fewer hours
per school week were more likely to have at least some college
education by age 30 than those who did not work or those
who averaged more than 20 hours of work per school week. In
addition, the data show an interesting pattern with respect to
a person’s work experience while he or she was young and the
person’s later employment experience: each step up in the
percentage of school weeks worked while the individual was
young is associated with a step up in the percentage of weeks

the person worked from ages 18 through 30, regardless of the
amount of hours per week the person worked while he or she
was young. As noted throughout this article, without controlling for other factors that can influence the longer term outcomes—in particular, the characteristics of those who choose
to work (and of those who choose to work more intensively)
during high school—the findings do not imply that youth
employment caused those outcomes. However, they do afford an insight into the possible relationship between youth
employment and longer term educational and labor market
outcomes.
□

Notes
1
See Christopher J. Ruhm, “Is High School Employment Consumption or Investment?” Journal of Labor Economics, October 1997, pp.
735–76; and National Research Council, Protecting Youth at Work
(Washington, National Academy Press, 1998), for extensive reviews of
the literature on the impact of youth employment. In general, the
literature shows mixed results regarding whether youth employment
affects academic outcomes. It does, however, generally suggest that
working while enrolled in school positively affects subsequent labor
market outcomes.
2
Gerald S. Oettinger, “Does High School Employment Affect High
School Academic Performance?” Industrial and Labor Relations Review, October 1999, pp. 136–51.
3
Audrey Light, “High School Employment, High School Curriculum, and Post-school Wages,” Economics of Education Review, June
1999, pp. 291–309.
4

Ruhm, “Is High School Employment Consumption or Investment?”

5

The years 1979 and 1997 both saw an upturn in the economy.
Economic expansion peaked in 1979, just prior to the 1980 recession.
Another strong economic expansion had 1997 in its midst. Note that,
subsequent to the release of round-1 NLSY97 data, some duplicate observations were discovered. The NLSY 97 round-1 sample size then fell
from 9,022 to 8,984. Sample weights at the time this article was begun
were based on all 9,022 observations, and tabulations in the article use
the full round-1 sample. Also, tabulations based on data in both surveys
use round-1 sampling weights, thereby ensuring that the data are nationally representative of each youth cohort.
6
Most youths surveyed in the NLSY97 had not yet turned 17, so
their employment is not examined. Both the NLSY79 and the NLSY97
contain detailed, week-by-week employment histories. However, these
are available for the younger NLSY 79 respondents only from age 16
forward and for the NLSY97 respondents only from age 14 forward. At
this point, there is not much age overlap in the histories across the two
surveys. However, the next section uses the employment histories in
the NLSY 79 solely to examine the relationship between youth employment and long-term outcomes.
7
Mark Schoenhals, Marta Tienda, and Barbara Schneider, “The
Educational and Personal Consequences of Adolescent Employment,”
Social Forces, December 1998, pp. 723–62, provide a brief summary
of the literature on the subject.
8
Family structure is defined as five mutually exclusive categories:
(1) families with two biological parents or two adoptive parents (called,
for simplicity, two-biological-parent families), (2) families with one
biological parent and one step- or adoptive parent (called simply twoparent families), (3) families with one female biological parent and no
other parent (female-parent families), (4) families with one male biological parent and no other parent (male-parent families), and (5)

36

Monthly Labor Review

August 2001

families consisting of children living with foster parents, grandparents and no parents, or other relatives and no parents; families of
children living in group quarters; and other family arrangements (all
lumped together as children not living with parents). Due to the small
sample size of male-parent families, the tables that follow exclude
that category.
9
If, for example, the youth was 15 years old at the date of the
interview, he or she is considered to have ever smoked if smoking
occurred by age 14 or younger. If the youth used marijuana before 1979,
he or she is considered to have ever used marijuana. In the NLSY97,
youths answered the smoking and marijuana questions in a special selfadministered section. Youths in the NLSY79 were asked these questions
directly by the interviewer.
10

The NLSY79 suspension variable is constructed as follows: if the
most recent suspension occurred before the 1979 interview, the youth
is considered to have ever been suspended. If the most recent suspension occurred on or after the 1979 interview and the youth had been
suspended only one time, then the youth is considered not to have ever
been suspended. Otherwise, if the youth received more than one suspension (two suspensions) and the most recent one occurred in 1979
(1980), then the youth is considered to have ever been suspended.
11
CPS data show an actual decline in employment-to-population
ratios of youths between the late 1970s and the late 1990s, as well as a
significantly lower percentage of youths working than the NLSY97 data
depict. The difference may be due to the CPS data containing mostly
proxy responses for the youths, while the NLSY surveys are answered by
the youths themselves. (See “A Comparison of CPS and NLSY97 Information about Youth Employment,” Report on the Youth Labor Force,
Appendix to Chapter 4 (Bureau of Labor Statistics, November 2000),
pp. 47–51.
12
Neither survey asks the youths whether they own or have access
to a car.
13
In all tables and charts in this article, the racial and Hispanic origin
groups are mutually exclusive. Totals include American Indians, Alaskan Natives, and Asians and Pacific Islanders, not shown separately.
14

Protecting Youth at Work (National Research Council, 1998).

15

States, however, may adopt more or less stringent standards than
the Fair Labor Standards Act imposes. However, when both the Federal
Act and State laws apply, the Act requires the use of the more stringent
standard. (See National Research Council, Protecting Youth at Work, for
details on State standards.)
16
The expression “while youths were ages 16 and 17” refers to
the 2-year period between the youth’s 16th and 18th birthdays.
School weeks are weeks other than those in June, July, or August,
the last week in December, and the first week in January. If a youth
dropped out or graduated from high school at age 17, only those

school weeks prior to that event are used in employment calculations. Youths who dropped out or graduated from high school at
age 16 are excluded from the analysis.
17
Hours are averaged over school weeks in which the youth worked
and are defined according to the following methodology: Survey respondents report the usual number of hours they worked per week as of
each job’s termination date (or as of the interview date for ongoing
jobs). Hours reported for each job are then filled in back to the job’s
starting date. Thus, a total number of hours worked across all jobs is
reported for each week a youth worked. Hours per week are then averaged over the number of weeks the youth worked at ages 16 and 17
during the school year (prior to dropping out or graduating from school).
Given this methodology, work hours from other periods (for example,
during the summer, after the youth turned 18, and after the youth
dropped out or graduated from school) are sometimes filled back into
school-year weeks. This can lead to an overstatement of the average

number of hours worked. On average, about one-third (32 percent) of
weeks worked at ages 16 and 17 during the school year were filled back
with hours from another period: 8 percent with summer hours, 15
percent with information on hours worked after the youth turned 18,
and 9 percent with information on work hours from other periods, such
as times subsequent to dropping out or graduating from school.
18

See also Report on the Youth Labor Force.

19

All results are weighted by using the 1996 survey weights (the
latest year’s data available when this analysis began) that correct for
oversampling, nonresponse to the interview, and permanent attrition
from the survey. When weighted, the data represent all persons living
in the United States in 1978 and born between 1962 and 1964.
20
For a further discussion of the topic, see Work and Family: Jobs
Held and Weeks Worked by Young Adults, Report 827 (Bureau of Labor
Statistics, August 1992).

Monthly Labor Review

August 2001

37

School-to-Work Programs

School-to-Work Programs

School-to-work programs:
information from two surveys
Data from the 1996 School Administrator's Survey show
that three-fifths of U.S. high schools offer school-to-work
programs, while data from the 1997 National Longitudinal Survey
show that nearly two-fifths of students participate in such programs;
also, public high school students and those who work are more
likely to participate in school-to-work programs
Mary Joyce
and
David Neumark

I

n 1994, the U.S. Congress passed the Schoolto-Work Opportunities Act providing federally
funded grants to the States and to local partnerships of business, government, education, and
community organizations to develop “school-towork systems.”1 The law encouraged the States
and their local partners to develop models that
would work best for their particular situations. As
a result, the features of school-to-work programs
often vary from grant to grant and thus are difficult
to describe in general terms. The Act did, however,
outline three core elements that all school-to-work
programs must entail:2

• School-based learning, which encompasses
rigorous classroom instruction that is
linked to workplace experiences and provides students with the information and
skills needed to identify and prepare for
promising careers;

• Work-based learning, which includes work
Mary Joyce is an
economist formerly
with the Bureau of
Labor Statistics. David
Neumark is a professor of economics at
Michigan State
University and a
research affiliate at
the National Bureau
of Economic
Research.

38

experience, structured training, and other
workplace learning experiences appropriate to students’ career interests and linked
to school curricula;

• Connecting activities, which are efforts un-

Monthly Labor Review

dertaken to help employers and schools
forge and maintain links between the
school-based and work-based components
of school-to-work programs.

August 2001

The general goal of the School-to-Work Act is to
improve the transitions from school to work for all
youths in the United States. The Act points to a “lack
of a comprehensive and coherent system to help
youths acquire the knowledge, skills, abilities, and
information about and access to the labor market that
are necessary to make an effective transition from
school to work or further education.”3
In this article, we are interested in studying
the extent to which school-to-work programs
have been implemented in our Nation’s high
schools since the Act’s passage in 1994, as well
as the extent to which high school students are
choosing to participate in these programs. To inform our study, we use two promising new data
sources. The first, the 1997 National Longitudinal Survey of Youth (NLSY97), provides information obtained directly from students on the extent to which they participated in school-to-work
programs. The second source, the 1996 School
Administrator’s Survey (SAS96), provides information obtained from the schools attended by
the NLSY97 interviewees on whether they offered
any school-to-work programs. Using these data
sources, we examine the prevalence of school-towork programs from two different perspectives,
investigating the kinds of schools offering such
programs and the students participating in them.
These data offer several attractive features for
our study. First, the two surveys asked about a
number of different types of school-to-work

programs, which allows us to analyze both work-based activities and school-based activities. Second, both surveys
asked about the same programs and used similar definitions.
Third, responses for the schools in the SAS96 can be linked
to those for individuals in the NLSY97. Finally, the surveys
collected extensive information on the characteristics of the
schools and the youths, thus allowing researchers to examine the characteristics of the high schools that offer schoolto-work programs as well as the characteristics of the students who participate in them. Ultimately, these data should
become an excellent source for studying the effectiveness
of school-to-work programs in helping students settle into
their careers; currently, however, the available data do not
support this line of inquiry.4

Data
1996 School Administrator’s Survey (SAS96). The National
School-to-Work Office sponsored a supplemental data collection effort within the NLSY97 to support their overall research interest in understanding the effectiveness of the
School-to-Work Act. As its name suggests, the SAS96 collects administrative data directly from the schools on the extent to which they offer school-to-work programs; it also provides information on the kinds of schools offering these programs. The sample includes all schools with a 12th grade within
the primary sampling units5 of the NLSY97. The survey asked
questions on school policy generally and on school-to-work
programs in particular, as well as the characteristics of students, teachers, and administrators. The SAS96 questionnaire
was mailed to 7,985 schools in September 1996. Of these
schools, 595 were excluded because they no longer existed
or because they did not have a 12th grade. Of the 7,390 remaining schools, the response rate was about 72 percent.6
Table 1 provides descriptive statistics on the 5,253
schools used in the analysis. We focus on characteristics of
the school that are related to the quality of the school, as
well as characteristics that indicate something about the socioeconomic status of the school’s student population.
These characteristics include the following: whether the
school is private or public; school size; school location; the
graduation rate at the school; the percentage of the school’s
graduates that enroll in a 4-year college; the racial and ethnic composition of the students; and whether or not the
school offered a school breakfast program, Title I services,7
or a dropout prevention program.
Among schools with a 12th grade, 74 percent are public
and 26 percent are private.8 Because public schools tend to
be larger than private schools, we defined school-size variables separately for public and private schools. For example, a
“small” public school is defined as one with fewer than 750
students, whereas a small private school is one with fewer

Table 1. Descriptive statistics on

SAS96

sample of schools

with 12th grade

Weighted
percentage

Characteristic

Unweighted N

Total ..................................
.............................................................
Type: ....................................................
Public .................................................
Private ................................................
.............................................................
Size ...............................

5,253

100.0

3,401
1,852

73.9
26.1

1,680
1,295
426

72.2
22.6
5.2

818
624
410

53.3
34.6
12.1

1,765
2,822
571

20.8
44.4
33.2

1,574
1,066
1,016
826

29.1
22.8
26.6
21.5

1,073
702
1,133
1,584

29.3
21.0
24.9
24.8

Black:
Less than 25 percent .........................
25 to 75 percent .................................
More than 75 percent .........................
.............................................................

3,633
696
265

83.3
12.4
4.4

Hispanic: ..............................................
Less than 25 percent .........................
25 to 75 percent .................................
More than 75 percent .........................
.............................................................

3,457
709
166

89.8
9.1
1.1

School breakfast program .........
Yes .......................................................
No .........................................................
.............................................................

2,521
2,732

52.3
47.7

Title I .........................
Yes .......................................................
No .........................................................

1,763
3,490

43.1
56.9

Dropout prevention program
Yes .......................................................
No ........................................................

2,028
3,225

42.5
57.5

Public: ..................................................
Small (fewer than 750 students) ........
Medium (750 to 1,500 students) ........
Large (more than 1,500 students) ......
.............................................................
Private: ................................................
Small (fewer than 100 students) ........
Medium (100 to 300 students) ...........
Large (more than 300 students) .........
.............................................................
Location ........................
Urban ...................................................
Suburban ..............................................
Rural .....................................................
High school graduates ............
Graduation rates by quartile: ..........................
1st quartile (less than 85 percent) .....
2nd quartile (86 to 94 percent) ...........
3rd quartile (94.8 to 97 percent) .........
4th quartile (98 percent or more) ........
.............................................................
Percent of graduates who
attend 4-year college: .........................
1st quartile (less than 30 percent) .....
2nd quartile (31 to 44 percent) ...........
3rd quartile (45 to 67 percent) ............
4th quartile (68 percent or more) ........
Student body .......................

Note: Missing information on a particular characteristic will result in
numbers (Ns) that do not add up to 5,253. Due to bunching, the percent in
each quartile does not necessarily equal 25 percent.

Monthly Labor Review

August 2001

39

School-to-Work Programs

than 100 students. The majority of both public and private
schools fall into the smallest size categories.
Among the schools in our study, 44 percent were in suburban areas, 21 percent were in urban areas, and 33 percent were
in rural areas. In addition, only 4 percent of schools reported
that 75 percent or more of their student body was black, and
only 1 percent reported that 75 percent or more of their student body was Hispanic. A sizable number of schools (43 to
52 percent) have school breakfast programs, receive Title I
funding, or have a dropout prevention program.

The National Longitudinal Survey of Youth, 1997 (NLSY97).
The first round of the NLSY97 was administered in 1997 to a
nationally representative sample of 8,984 young men and
women who were ages 12 to 16 as of December 31, 1996. The
survey was administered through personal interviews with
the youths and one of their parents, and it gathered extensive
information on the youths’ labor market behavior, education
and training, family and community background, as well as
important life events such as marriage or the birth a child.
Through annual follow-up interviews, the NLSY97 will continue to track these youths as they make the transition from
school to the world of work.
In the 1997 interview, youths who had attended the 9th grade
or higher were asked a number of questions about participation in school programs designed to help them prepare for the
world of work. Of the nearly 9,000 respondents, roughly half
were asked the school-to-work questions.9 The present analysis is restricted to these respondents, and table 2 provides some
basic descriptive information on the group. The first column
of table 2 provides the number of respondents with a particular
characteristic, and the second column provides the weighted
percentage that those respondents represent in the national
population of youths born between 1980 and 1984.
The sample contains roughly equal numbers of girls and
boys. Given the ages of the NLSY97 cohort, however, the majority of the high school respondents were in either the 9th or
10th grades in 1997. Only 74 respondents were in the 12th
grade or higher. To the extent that participation in school-towork programs is greater in the upper grades of high school,
which we suspect is likely, our estimates on overall participation from the NLSY97 would underestimate school-to-work
participation in high school.10 While table 1 showed that almost three-quarters of the schools are public, table 2 shows
that more than 90 percent of youths in 9th grade or higher attended public schools, again reflecting the fact that public
schools tend to be larger than private schools.
The variables listed in table 2 are youth characteristics that
we conjectured might be related to participation in school-towork programs. These characteristics can be divided into two
groups. The first set consists of characteristics related to socioeconomic status and is aimed at assessing the extent to

40

Monthly Labor Review

August 2001

Table 2. Descriptive statistics on NLSY97 sample of youths
in 9th grade or higher in 1997

Characteristic

Unweighted N

Weighted
percentage

Total ................................................
.........................................................

4,484

100.0

2,213
2,271

50.4
49.6

1,925
1,635
850
74

41.5
36.3
20.3
1.9

2,625
1,176
643
40

72.4
15.3
11.5
0.8

935
3,537

13.0
87.0

1,002
774
689
665

25.1
24.9
25.0
25.0

710
227
1,413
641
388
1,059

11.7
5.0
32.6
15.1
9.4
26.3

4,013
276
158

90.2
6.9
2.9

2,631
1,853

54.4
45.6

469
2,359
1,656

9.9
50.2
39.9

1279
3205

32.5
67.5

164
297
628
2,250

5.3
8.2
17.7
68.9

2,593
500
1,391

56.0
10.4
33.6

Sex ...........................
Male ......................................................
Female .................................................
Grade level ......................
9th ......................................................
10th ......................................................
11th ......................................................
12th or higher .......................................
Race ..........................
White ....................................................
Black ....................................................
Other ....................................................
Unknown ...............................................
Ethnicity .........................
Hispanic ................................................
Non-Hispanic .......................................
.............................................................
Household income ............
1st quartile: Less than $26,000 ..........
2nd quartile: $26,001 to $45,015 ........
3rd quartile: $45,016 to $70,002 .........
4th quartile: $70,003 or more ..............
.............................................................
Biological mother's education
Less than high school ..........................
GED ......................................................
High school graduate ...........................
Some college, no degree ......................
Associates degree ...............................
College graduate ..................................
School type ...................
Public ...................................................
Private ..................................................
Other ....................................................
.............................................................
Location .....................
Urban ...................................................
Rural .....................................................
GPA in 8th grade .................
Low (Cs and/or Ds) ...............................
Medium (Cs and/or Bs) .........................
High (As and/or Bs) .............................
.............................................................

Employment status last week ....
Working ................................................
Not working ...........................................
College expectations .............
0 percent chance .................................
1 to 33 percent chance ........................
34 to 66 percent chance ......................
More than 66 percent chance ..............
.............................................................
Course of study in high school ....
General .................................................
Vocational, technical, or business ........
College prep .........................................

Note: Missing information on a particular characteristic will result in
numbers (Ns) that do not add up to 4,484. Due to bunching, the percent in
each quartile does not necessarily equal 25 percent.

which disadvantaged youths are targeted for school-to-work
programs. These characteristics include gender, race, ethnicity,
household income, education level of the youth’s biological
mother, whether the youth attends a public or private school,
and whether the youth lives in an urban or rural location. The
second set includes other characteristics that are related to the
youth’s work or school performance and are aimed at investigating what kinds of students tend to participate in these programs. These include academic performance in 8th grade,
whether or not the youth is currently working, his or her expectations for completing college, and the course of study the
youth is pursuing in high school.
Due to missing information, data on some of these youth
characteristics are not available for all 4,484 respondents who
were asked the questions about school-to-work programs.11 For
example, household income is missing for more than 1,300 youths
in our analysis sample. There are two reasons for the high rate of
missing data on income: First, respondents often refuse to answer questions about their income; second, the income information was collected in a separate interview with one of the youth’s
parents and not all parents provided an interview.

School-to-work programs
Under the guidance of the National School-to-Work Office,
a limited number of school-to-work programs were chosen
for inclusion in both the SAS96 and the NLSY97 questionnaires: internship/apprenticeship programs (asked about
separately in SAS96, but combined in the NLSY97), job shadowing, mentoring, school-sponsored enterprise, career
major, and cooperative education. The definitions given to
respondents in the two surveys are similar but not identical.
(See Appendix 1.)
Although the two surveys ask about the same programs,
the students and the school administrators may not interpret
the questions in exactly the same way. For example, a student
who has received some career counseling may incorrectly respond that they had participated in a “career major” program,
whereas a school administrator, who may have read the definition more closely, probably would not categorize career
counseling as a career major program.
Given that the schools in the SAS96 were selected from the
primary sampling units’s where the NLSY97 youths live, we
are able to match the NLSY97 youths with the high schools
that they attend to examine the consistency in reporting of
school-to-work programs between youths and schools. If the
school reports offering a program and the student does not
report participating, then no inconsistency need exist, since
some students may not participate. On the other hand, if a
school reports not offering a particular program and the student reports participating in this program, then there is a potential inconsistency.12

Comparison of participation rates. Table 3 shows participation rates in school-to-work programs for four different groups of youths who have attended 9th grade or higher:
all youths, youths in schools that reported having the program, youths in schools that reported no corresponding program, and youths in schools that did not participate in the
SAS96.
We find the results in Table 3 troubling because the participation rates among youths in schools with a particular program are very similar to those of youths in schools not offering the program. It is not clear whether the schools or the
youths are incorrectly reporting. One problem with the school
survey data is the substantial non-response to individual
questions about school-to-work programs—roughly 12 to 18
percent of administrators did not respond to individual questions on whether or not the school offered a particular program. In defining whether a school offered a program in table
3, we treated nonresponses as “no” responses. For instance,
if a school administrator did not respond to the question on whether
the school offered an apprenticeship program, then it was assumed
that the school did not have the program. Because this approach
could result in misclassifying a school as not offering a program
when in fact it did (but just failed to respond), we recalculated table
3 treating nonresponses to a particular program as nonrespondents
(that is, we moved them to the “not surveyed or not responding”
column of table 3). This reduced the discrepancy slightly, but by no
means eliminated it. Another possible explanation for the inconsistency between school and youth reports is misclassification on
the part of the youths. It may be that youths participated in schoolto-work programs, but because they did not fully understand the
Table 3. Participation rates in school-to-work programs
by school reports

Participation rates of youths
attending 9th grade or higher
Characteristic
Total

Any school- or workbased activity ..............

Youths in Youths in
Youths in
schools
schools not surveyed
reporting reporting
schools
program no program
or not
responding

38.3

38.5

36.4

38.7

Any work-based activity .
Job shadowing .............
School-sponsored
enterprise ..................

24.2
12.6

26.1
15.1

23.7
12.1

22.4
11.5

9.1

13.5

8.7

8.3

Mentoring ........................
Apprenticeship/
internship ....................

4.8

5.9

4.7

4.3

4.3

4.6

2.9

5.9

25.1
19.6
7.4

21.0
16.6
6.5

26.6
19.9
8.9

6.3

6.5

7.5

Any school-based
activity .......................... 24.9
Career major ............... 18.1
Tech prep ...................
7.6
Cooperative
education ..................
6.8

Monthly Labor Review

August 2001

41

School-to-Work Programs

Table 4. Percentage of schools with a 12th grade offering
school-to-work programs in 1996 (SAS96)

Percent
Activity

Percentage of schools
in 1996 that offered

Any school- or work-based activity ...........
..................................................................

64.2

Any work-based activity ............................
Job shadowing ........................................
Internship ................................................
Mentoring ................................................
Apprenticeship ........................................
School-sponsored enterprise ..................
..................................................................

44.9
28.7
16.6
15.1
13.9
12.7

Any school-based activity .........................
Cooperative education ............................
Tech prep ................................................
Career major ............................................

50.4
32.5
33.2
13.2

definitions of the various types of programs, they misreported their
participation in them; or, they simply interpreted the definitions
differently from the school survey respondents.
Short of conducting a validation study, we have no way of
knowing the source of the reporting error. As a result, the actual levels of participation rates by youths and incidence rates
by schools should be viewed as rough estimates. However, unless reporting errors vary systematically by youth or school
characteristics, differences across groups in participation or
offering rates should be less affected by measurement error.

Incidence rates in SAS96
According to the SAS96 64.2 percent of schools with a 12th
grade offered at least one school-to-work program to their
students.13 (See table 4.) The most prevalent work-based activity offered by schools was job shadowing, with nearly 29
percent of schools offering such programs. Job shadowing
was followed by internship, mentoring, apprenticeship, and
school-sponsored enterprise programs, with incidence rates
for these programs ranging from 13 to 17 percent. In 1996,
school-based activities were more commonly offered by
schools than were work-based activities. Technical preparatory and cooperative education programs were the most common school-based activities and were offered by approximately 33 percent of schools. Career major programs were less
prevalent, with 13.2 percent of schools offering them.
Next, we examine the extent to which schools offer more
than one of these school-to-work programs. While 64 percent
of schools offered at least one program, 26 percent offered
three or more programs, and about 9 percent offered five or
more programs. (See table 5.) About 22 percent of schools
offered only one program, while 31 percent of schools offered
at least one work-based and one school-based activity.
Table 6 shows the proportion of schools offering various
42

Monthly Labor Review

August 2001

school-to-work programs by characteristics of the school and
its student body. In the discussion that follows, we only mention differences in incidence rates that were found to be statistically significant.14 In general, private schools have much
smaller incidence rates for school-to-work programs. Only 24
percent of private schools offered at least one school-to-work
program in 1996, compared with 78 percent of public schools.
Incidence rates for each individual school-to-work program
also were considerably lower among private schools than
public schools. Among public schools, the percent of schools
providing any school-to-work programs was highest among
medium-size schools (750 to 1,500 students). This size pattern
among public schools also holds for most of the individual
school-to-work programs. Among private schools, the largest schools (i.e., schools with more than 300 students) were
more likely to offer any school-to-work programs. However,
this size pattern does not hold consistently for all of the various school-to-work programs.
In 1996, a higher percentage of suburban schools offered
school-to-work programs than did urban or rural schools. This
was particularly true for apprenticeship, school-sponsored
enterprise, cooperative education, and technical preperatory
programs. School-to-work programs were considerably less
prevalent in schools with high graduation rates and a high
percentage of graduates who go on to attend 4-year colleges.
Table 6 shows that schools from which 98 percent or more of
the students graduate had incidence rates for any school-towork programs of 43 percent compared with about 70 percent
for schools with lower graduation rates. We found similar differences between schools in which 68 percent or more of the
students went on to attend 4-year colleges and schools with
Table 5. Co-existence of selected school-based and

work-based activities in school with 12th grade
SAS96

Activity

Total activities
At least 1 ....................................................
At least 2 ....................................................
At least 3 ....................................................
At least 4 ....................................................
At least 5 ....................................................
......................................................................
Work-based activities .................
At least 1 ....................................................
At least 2 ....................................................
At least 3 ....................................................
......................................................................
School-based activities ................
At least 1 ....................................................
At least 2 ....................................................
At least 3 ....................................................
Exactly one school-to-work activity ....
At least one work-based and one-school
based activity ............................................

Percentage of schools
in 1996 that offered:

64.2
42.6
26.0
15.2
9.1

44.9
23.3
11.6

50.4
22.7
5.7
21.6
31.2

-

Table 6. Prevalence of selected work- or school-based activities by school characteristics
Percentage of schools
Work-based activities
Characteristic

Total .........................................
........................................................
Type ........................
Public ..............................................
Private .............................................
........................................................
Size .......................
Public: .............................................
Small .............................................
Medium ..........................................
Large .............................................
........................................................
Private: ...........................................
Small .............................................
Medium ..........................................
Large .............................................

Any
activities ApprenticeInternship
ship

Job
shadowing

School-based activities

Mentoring

Schooleducation
enterprise

Career
major

Cooperative

Tech
prep

64.2

13.9

16.6

28.7

15.1

12.7

13.2

32.5

33.2

78.3
24.2

17.8
3.1

20.1
6.9

36.1
7.9

19.2
3.7

15.0
6.0

17.0
2.3

42.1
5.3

43.4
4.3

75.3
87.3
82.1

16.0
23.2
18.4

16.4
30.0
28.1

34.3
43.4
30.5

15.6
29.6
23.9

12.3
23.2
18.2

14.8
22.8
23.7

36.1
57.8
57.3

40.3
54.7
38.1

22.3
24.6
31.2

5.0
.7
1.5

8.3
5.6
4.6

5.9
9.0
13.4

4.6
3.0
1.7

5.1
8.0
4.3

2.4
1.8
3.8

5.8
3.8
7.6

2.6
5.4
8.6

Location ....................
Urban ...............................................
Suburban .........................................
Rural ................................................

57.5
67.4
64.2

12.6
16.2
10.9

20.4
18.9
11.1

26.9
29.5
29.6

17.5
18.4
9.6

13.7
16.0
7.2

13.7
14.3
11.6

30.6
36.2
30.1

26.7
40.7
28.0

........................................................
Graduation rates quartile ......
1st quartile (less than 85 percent) ..
2nd quartile (86 to 94 percent) ........
3rd quartile (94.8 to 97 percent) ......
4th quartile (more than 98 percent) .

67.9
71.6
72.3
42.5

14.4
17.3
14.2
7.9

20.0
18.6
18.7
7.3

31.8
33.4
40.3
10.3

23.9
13.1
14.7
7.3

15.5
14.1
15.3
4.4

20.4
11.2
12.8
7.1

35.3
45.3
28.9
18.8

37.2
42.9
38.5
14.7

........................................................
Percentage of graduates who
attend 4-year college .......
1st quartile (less than 30 percent) ..
2nd quartile (31 to 44 percent) ........
3rd quartile (45 to 67 percent) .........
4th quartile (more than 68 percent) .

70.3
76.7
74.6
42.5

10.8
23.0
18.3
5.7

15.9
23.6
22.0
11.0

30.8
45.7
35.5
14.0

15.9
26.9
17.1
6.6

14.8
20.3
13.4
5.8

16.2
15.0
15.2
3.9

33.9
47.0
35.2
15.9

35.7
44.1
44.6
18.2

Black: ..............................................
Less than 25 percent ....................
25 to 75 percent ............................
More than 75 percent ....................

67.0
72.8
67.3

14.5
17.6
21.8

16.3
22.8
15.9

32.4
26.6
17.5

15.6
22.0
16.7

14.0
13.1
17.2

11.2
23.4
32.2

34.0
41.8
24.1

37.6
35.6
23.4

Hispanic: .........................................
Less than 25 percent ....................
25 to 75 percent ............................
More than 75 percent ....................

69.8
69.1
67.6

14.8
10.2
18.1

18.1
17.9
24.1

33.3
24.9
22.7

16.3
19.7
22.0

14.6
13.3
13.9

12.1
28.4
26.9

35.0
39.0
39.4

37.4
34.3
41.4

School breakfast
Yes ..................................................
No ....................................................
........................................................

78.2
48.8

17.3
10.2

20.5
12.3

33.4
23.6

18.4
11.5

14.7
10.5

18.3
7.6

41.4
22.7

40.6
25.1

Title I .........................
Yes ..................................................
No ....................................................
........................................................

68.1
61.2

11.1
16.1

15.4
17.5

30.3
27.5

13.5
16.4

10.5
14.3

14.4
12.3

32.7
32.3

34.6
32.1

73.8
57.1

18.7
10.4

21.5
13.0

35.0
24.0

19.0
12.3

15.6
10.5

18.7
9.1

43.3
24.5

38.7
29.1

Dropout prevention ...........
Yes ..................................................
No ....................................................

Monthly Labor Review

August 2001

43

School-to-Work Programs

lower college enrollment rates—the schools with the higher
college enrollment rates were less likely to offer any of the
individual school-to-work programs.
As mentioned previously, the School-to-Work Act emphasizes the need to improve the transition from school to
work for all students, but especially students from disadvantaged backgrounds. To see if school-to-work programs are
more typical for such students, we next show how incidence
rates of school-to-work programs vary with our descriptors
for disadvantaged student bodies.
Schools in which 25 to 75 percent of the student body is
black had a higher incidence rate for any school-to-work programs than did schools in which less than 25 percent of the
student body is black.15 This pattern also holds for the provision of apprenticeship, internship, mentoring, career major,
and cooperative education programs. Provision of job shadowing programs, however, was highest among schools with
the lowest percentage of black students. The provision of
school-to-work programs does not appear to vary systematically by the percentage of Hispanic students. However,
schools that offer a breakfast program or a dropout prevention program were more likely to provide school-to-work programs. The results for Title I schools were mixed, with higher
incidence rates than non-Title I schools for some school-towork programs and lower incidence rates for other programs.

Regression analysis. Thus far in our analysis, we have
shown incidence rates for school-to-work programs by various characteristics of the schools. Next, we use logistic regression analysis to estimate the probability that a school
with any given set of characteristics offers school-to-work
programs. This approach allows us to see the independent
relationship of a particular characteristic with incidence rates,
while holding constant the relationship of school-to-work programs to other characteristics.
We ran logistic regressions for three different dependent
variables: provision of any school-to-work program, provision of any work-based program, and provision of any schoolbased program. Table 7 provides the odds ratios obtained
from the logistic regressions. The odds ratios indicate how
much more likely schools that differ with respect to a particular characteristic are to offer a given program, compared
with other schools.16 An odds ratio of 2 on the dummy variable for private school indicates that private schools are
twice as likely to offer school-to-work programs as public
schools. Similarly, an odds ratio of 1 indicates that they are
equally likely, and an odds ratio of 0.5 indicates that they are
half as likely. Table 7 shows that the actual odds ratio is 0.14,
indicating that private schools are roughly 1/7th as likely as
public schools to offer any school-to-work programs.
For characteristics that are continuous, such as school
size, the odds ratio tells us how much more likely schools
44

Monthly Labor Review

August 2001

that are one unit away from the mean for that characteristic
are to offer a given program compared with schools at the
mean for that characteristic. Because a change of one unit
is not always the most meaningful, we divided school size
by 100 and the percentage of blacks and Hispanics by 10
before entering them into the logistic analysis. By doing
this, the resulting odds ratio for school size represents the
change attributable to a change in school size of 100, and
the odds ratio for percentage black or Hispanic represents
the change attributable to a 10 percentage-point change in
the percentage black or Hispanic.
The results from the regression analysis largely confirm
our findings from the cross-tabulation analysis—namely,
private schools are significantly less likely to provide
school-to-work programs than are public schools. They are
0.3 times as likely as public schools to provide any workbased programs and 0.1 as likely to provide any school-based
programs. School size is somewhat positively related to provision of school-to-work programs, particularly schoolbased programs. However, among private schools, large
schools are slightly less likely to offer school-to-work programs. In terms of location, urban schools are less likely
than suburban schools to provide school-based programs,
while rural schools are less likely than suburban schools to
provide work-based programs.
Schools with the highest graduation rates are less likely
than other schools to provide any school-to-work programs,
work-based programs, or school-based programs. Schools
with the highest percentage of graduates going on to 4-year
colleges also are less likely to provide any school-to-work
program, especially school-based programs.
The findings are mixed regarding whether schools with
less privileged student populations are more likely to offer
school-to-work programs. For example, the percentage of black
students at a school is not significantly related to the probability of providing school-to-work programs, whereas the
percent Hispanic is slightly negatively related to provision of
Table 7. Logistic regression results for probability
of offering school-to-work programs

Odds ratio
Characteristic

Private school ..............................
School size/100 ............................
Private school size/1001 ..........................
Urban ...........................................
Rural .............................................
Highest graduation rate quartile
(98 percent or more) ..................
Highest 4-year college
enrollment rate quartile
(68 percent or more) ..................
1

Any
1

Work-based

0.14
1.03
1
.92
.97
.85

1

1

1

74

.68

Significantly different from 1 at 5-percent level.

1

0.26
1.01
1
.91
1.12
1
.78
1

Schoolbased
1

0.11
1.05
1
.95
1
.84
1.03

1

1

.69

93

80

1

.48

Table 8. Participation rates in school-to-work programs
NLSY97
Characteristics

Percentage of students in
9th grade or higher in
1997 who participated

Any school- or work-based activity ......
.............................................................

38.3

Any work-based activity .......................
Job shadowing ...................................
School-sponsored enterprise .............
Mentoring ...........................................
Apprenticeship/internship ...................
.............................................................

24.2
12.6
9.1
4.7
4.3

Any school-based activity ....................
Career major .......................................
Tech prep ...........................................
Cooperative education .......................

24.9
18.2
7.6
6.8

these programs. Furthermore, Title I schools are slightly less
likely than non-Title I schools to offer school-to-work programs, but schools with dropout prevention programs are
more likely to offer school-to-work programs.

Participation rates in the NLSY97
After examining how many and what types of schools offer
school-to-work programs, we now turn to the question of how
many students participate in these programs and what kinds
of students choose to participate. To examine participation in
school-to-work programs, we use data from the NLSY97. The
data show that 38 percent of youths who have attended 9th
grade or higher participated in at least one of the school-towork programs covered in the survey. (See table 8.)
Among work-based activities, job shadowing was the most
prevalent, with nearly 13 percent of youths participating in
such programs. School-sponsored enterprise ranked second
at 9.1 percent, and apprenticeships/internships and mentoring
programs followed, with participation rates of about 4 percent
each. In terms of school-based learning activities, the most
common program was career major, with 18.2 percent of youths
reporting having participated in such a program. This was
followed by technical preparatory at 7.6 percent, and cooperative education at 6.8 percent.
Table 9 shows the extent to which the youths in our study
participated in more than one school-to-work program. Participation in multiple programs is not common: only 6 percent
of youths participated in three or more programs, and fewer
than 1 percent participated in five or more programs. About 10
percent of youths who have attended the 9th grade or higher
participated in at least one work-based activity and one
school-based activity. The majority of students that participated in at least one program tended to participate in only
that program—23 percent of youths reported participating in

only one activity.
What kinds of students tend to participate in school-to-work
programs? Table 10 shows participation rates in the various
programs by characteristics of the youths that we felt may influence the quality of worker that the youth ultimately may
become when he or she joins the workforce. In the discussion
that follows, we only mention differences in participation rates
across groups that were found to be statistically significant.17
Participation in any school-to-work program does not appear to vary according to the youths’ academic performance
when in 8th grade. However, participation rates in certain programs do differ by grade point average. For example, youths
whose grades were average had higher participation rates in
apprenticeship/internship programs than youths with higher
grades. Those with higher grades were more likely to participate in job shadowing.
Youths who worked while going to school were more likely
to participate in school-to-work programs: 43 percent of the
youths who reported working during the survey week participated in at least one school-to-work program, compared with
36 percent of the youths who did not work. Participation
rates in most of the individual programs also were higher
for working youths.18
Although the School-to-Work Act emphasizes the need
to make school-to-work programs available to all students,
we wondered if college-bound youths are as likely to participate in these programs as youths who do not intend to go
to college. To address this question, we examine how parTable 9. Co-existence of selected school-based
and work-based activities (NLSY97)

Characteristics

Percentage of students
in 9th grade or higher
in 1997 who participated
in activities

Total activities: ............................
At least 1 ....................................
At least 2 ....................................
At least 3 ....................................
At least 4 ....................................
At least 5 ....................................

38.3
16.1
5.6
1.9
.8

Work-based activities: ................
At least 1 ....................................
At least 2 ....................................
At least 3 ....................................

24.2
5.3
1.1

School-based activities: ..............
At least 1 ....................................
At least 2 ....................................
At least 3 ....................................
....................................................
Exactly one school
to work activity .............................
....................................................
At least one work-based
and one-school based activity ....

Monthly Labor Review

24.9
6.7
1.0

22.7

10.3

August 2001

45

School-to-Work Programs

-

Table 10. Participation in school-to-work program by worker-related charcteristics
Percentage of youths in 9th grade or higher in 1997 who participated in activities
Work-based activities
Characteristic

Total ............................
..................................................
GPA in 8th grade ............................
Low (Cs and/or Ds) ........................
Medium (Cs and/or Bs) ..................
High (As and/or Bs) .......................
..................................................
Employment status
last week ..................
Working ..........................................
Not working ....................................
..................................................
College expectations ......
0 percent chance ...........................
1 to 33 percent chance ..................
34 to 66 percent chance ................
More than 66 percent chance ........
..................................................
Course of study in high school
General ...........................................
Vocational, technical, or business .....
College prep ...................................

Any
program

Apprenticeship or
internship

Job
shadowing

Monthly Labor Review

Mentoring

Schoolsponsored
enterprise

Career
major

Cooperative
education

Tech prep

38.3

4.3

12.6

4.8

9.1

18.1

6.8

7.6

38.8
38.6
37.8

3.8
5.4
3.1

10.4
11.7
14.3

4.2
5.0
4.6

6.9
9.0
9.7

16.1
19.1
17.6

8.3
6.8
6.4

10.0
7.7
6.9

43.1
36.0

4.7
4.1

14.3
11.8

5.9
4.2

11.4
8.0

20.1
17.2

8.1
6.1

7.0
7.9

34.2
37.3
37.9
40.5

3.7
6.2
3.9
4.9

9.4
8.8
11.7
4.2

2.5
4.4
4.5
5.6

7.9
7.3
8.2
10.1

15.6
19.4
20.7
18.8

7.0
6.3
8.7
6.6

8.5
9.9
7.8
8.0

33.7
63.5
38.1

3.7
10,7
3.4

11.0
13.8
15.0

3.8
6.6
5.8

7.4
14.9
10.0

16.0
36.5
16.1

5.3
20.0
5.2

5.7
20.7
6.8

ticipation in various school-to-work programs differs by the
youth’s self-reported expectations about completing college,
while recognizing that these expectations may be influenced
by school-to-work programs.
In the NLSY97 questionnaire, youths were asked: “What
is the percent chance that you will have a four-year college
degree by the time you turn 30?” Youths were then placed
into four groups: those who said they had zero chance of
receiving a college degree, those who said they had a 1- to
33-percent chance, those who said they had a 34- to 66percent chance, and those who said their chance was greater
than 66 percent. Interestingly, nearly 70 percent of the
youths fell into the latter category, and only 5 percent said
they had no expectations of completing a degree. Findings
in Table 10 show that, if anything, individuals who perceive
themselves as more likely to complete college have greater
participation in school-to-work programs.
Participation in school-to-work programs was considerably higher for youths who characterized their course of
study in high school as being a vocational, technical, or
business program as opposed to a general or college preparatory program. This strong positive relationship is not
surprising given that vocational, technical, or business-oriented programs are by their nature more focused on linking educational curricula to careers.
Table 11 shows participation rates in the various programs
by youth characteristics related to socioeconomic status.
These characteristics are of interest given the emphasis

46

School-based activities

August 2001

placed in the School-to-Work Act on providing school-to-work
opportunities to youths that may ultimately become high school
dropouts or have difficulties in the workforce.
Although women’s labor force participation rates are approaching those of men, gender differences still exist in terms
of occupational choices and long-term attachment to the
workforce. Some of these differences may influence decisions
about participating in certain school-to-work programs. Overall,
participation rates in school-to-work programs are similar for
young men and women. However, high school girls are more
likely than their male counterparts to participate in a job shadowing program, and high school boys are more likely than their female counterparts to participate in a technical preparatory program.
Findings from NLSY97 indicate that black youths were more
likely than other racial groups to participate in at least one
school-to-work program. Blacks also had higher participation
rates than whites in apprenticeship or internship programs, as
well as in mentoring, career major, cooperative education, and
technical preparatory programs. Hispanics, on the other hand,
were less likely than non-Hispanics to participate in at least
one school-to-work program, with significantly lower participation in job shadowing, school-sponsored enterprise, and
career major programs.
As part of the interview with one of the youth’s parents,
information was collected on total income for the household
in which the youth resides. Using this information, we were
able to group the youths into four equal-sized income groups
to see if participation in school-to-work programs varies by

household income. Participation rates in any school-to-work
program do not vary systematically by income level. However,
some differences do exist for individual programs. Youths in
the highest income group, for example, were more likely to
participate in job shadowing programs than those in the lowest
income group. Youths in the bottom two income groups were
more likely to participate in a career major program than were
youths in the highest income group. Youths in the highest income
group also were less likely than youths in the lowest income group
to participate in cooperative education programs.
Although participation rates did not vary much by students’
college expectations, the education level of the youth’s biological mother does appear to be negatively related to participation in school-to-work programs. Youths whose mothers are
college graduates are less likely to participate in at least one
school-to-work program than are youths whose mothers are
high school graduates. This relationship also holds for participation in apprenticeship or internship, career major, cooperative education, and technical preparatory programs. Youths

-

Table 11.

whose mothers have less than a high school education are less
likely to participate in at least one school-to-work program
than are youths whose mothers are high school graduates.
Consistent with the school survey, youths attending private high schools are less likely to participate in school-towork programs than are those attending public schools. Approximately 26 percent of youths in private schools participated in at least one school-to-work program, whereas nearly
39 percent of public school students did.

Regression analysis. Similar to the strategy used in analyzing the school data, we now turn to our logistic regression
analyses that estimate the probability that a youth with any
given set of characteristics participates in school-to-work programs. This approach allows us to see the independent relationship of a particular characteristic with participation rates
while holding constant the relationship of other characteristics. We ran regressions for three different dependent variables: participation in any school to work program, participa-

Participation in school-to-work programs by socioeconomic status-related characteristics
Percentage of youths in 9th grade or higher in 1997 who participated in activities

Characteristic

Any
program

Work-based activities

School-based activities

Apprentice
ship or
internship

Job
shadowing

Mentoring

Schoolsponsored
enterprise

Career
major

38.4
38.2

4.3
4.3

11.0
14.3

4.6
5.0

9.0
9.2

18.9
17.4

7.3
6.3

8.7
6.6

37.7
44.8
34.5

3.9
6.7
4.3

13.2
11.1
10.9

4.2
6.2
6.0

8.6
10.3
10.5

17.4
24.2
15.9

6.2
10.1
5.6

7.2
10.7
6.5

32.0
39.2

4.1
4.4

8.9
13.1

4.7
4.8

7.3
9.4

15.8
18.5

5.4
7.0

6.9
7.7

39.5
40.8
38.8
38.6

6.1
3.2
3.6
4.3

11.3
12.6
14.1
14.7

3.9
5.7
5.4
4.3

8.1
10.0
10.2
9.2

20.5
19.2
18.0
15.1

8.5
6.9
5.5
6.0

7.7
8.6
8.7
6.3

High school graduate ....
Some college, no degree .
Associates degree ........
College graduate ...........

36.3
42.0
41.1
41.1
40.1
32.9

4.3
7.9
5.5
2.8
4.3
3.0

9.7
13.0
12.7
14.1
13.8
12.7

5.0
5.8
4.6
5.5
5.4
4.0

8.2
9.4
9.0
11.1
10.3
8.1

19.0
17.9
21.5
17.1
19.7
13.6

7.1
10.0
7.8
6.6
5.1
5.4

7.4
9.6
8.2
9.0
8.2
5.5

School type .......
Public ............................
Private ..........................

38.5
25.9

4.0
3.2

12.8
9.5

4.7
2.5

9.0
8.6

18.6
6.8

6.5
3.5

7.5
1.8

Location ............
Urban ............................
Rural ..............................

37.6
39.2

4.6
4.0

11.7
13.8

4.8
4.7

9.6
8.5

17.7
18.8

6.6
7.0

7.4
7.9

Sex
Male ...............................
Female ..........................
......................................
Race ..............................
White .............................
Black .............................
Other .............................
......................................
Ethnicity ...........
Hispanic ........................
Non-Hispanic ................
......................................
Household income ...
Less than $26,000 ........
$26,001 to 45,015 .........
$45,016 to 70,002 .........
$70,003 or more ............
......................................
Biological mother’s
education .........
Less than high school ...
GED ..............................................

Monthly Labor Review

Cooperative Tech prep
education

August 2001

47

School-to-Work Programs

Table 12.. Logistic regression results for probability of participating in school-to-work programs
Odds ratio

Characteristic
Any
Worker-related characteristics
Low grades in 8th (Cs and/or Ds) ........................................................
Medium grades in 8th (Cs and/or Bs) ..................................................
Working ..............................................................................................
0 percent chance of completing 4-year college ................................
1 to 33 percent chance of completing 4-year college .......................
34 to 66 percent chance of completing 4-year college .....................
General course of study in high school .............................................
Vocational, technical, or business program .......................................
...........................................................................................................
Socio-economic status related characteristics ..........
Female ...............................................................................................
Black ..................................................................................................
Other ..................................................................................................
Hispanic ..............................................................................................
Log of annual household income ........................................................
Biological mother has less than high school degree ..........................
Biological mother has GED ............................................................................................
Biological mother has some college, no degree .................................
Biological mother has associates degree ...........................................
Biological mother has college degree .................................................
Private school ....................................................................................
Other type of school ..........................................................................
Urban ..................................................................................................
1

.99
1.33
1.06
.85
1.05
.97
1.07
1.10
.99
1
.97
1
.55
1.36
.97

1

School-based

0.95
1.05
1.31
.77
.72
73
1
.75
1.26

0.93
.90
1.15
.69
.76
1
90
.87
1
2.70

1

1.13
1.22
1.24
.76
1.07
1.09
1.13
1.21
1.03
1.00
1
.73
1.18
1.03

1

1

.82
1.41
.90
.95
.99
95
.87
.90
.99
1
.93
1
.36
1
1.68
.90
1

Significantly different from 1 at 5-percent level..

tion in any work-based program, and participation in any
school-based program. Table 12 provides the odds ratios obtained from the logistic regressions.19
Findings from the logistic regression analysis confirm
many of the cross-tabulation results discussed previously.
Youths who work are more likely (about 1.3 times more
likely) to participate in any school-to-work program and any
work-based program. Youths who characterized their course
of study as general are less likely than college preparatory
students to participate in any school-to-work program and
any work-based program, whereas those who characterized
their course of study as vocational, technical, or businessoriented were more than twice as likely as college preparatory students to participate in any school-to-work program
and any school-based program.
In addition, black youths are more likely than white youths
to participate in any program, any work-based program, and
any school-based program. Students who attend private
schools are less likely to participate in any program, any
work-based program, and any school-based program than
were students who attend public school. Lastly, students
whose mothers are college graduates were slightly less likely
to participate in any program and any school-based program
than were students whose mothers are high school graduates.
HOW COMMON ARE SCHOOL-TO-WORK PROGRAMS? We have examined this question from two different perspectives—that
of the Nation’s high schools and that of its students. The

48

0.97
98
1.31
1
.68
1
.73
1
80
1
.81
1
2.26
1

Work-based

Monthly Labor Review

August 2001

SAS96 data show that school-to-work programs are commonly

offered in U.S. high schools, with more than 60 percent of schools
providing at least one such program. The NLSY97 data show
that a fair number of high school students are participating in
school-to-work programs, with about 38 percent of students
reporting having participated in at least one program. However,
we have some concerns about the quality of these data because
sizable numbers of students in schools that supposedly do not
have school-to-work programs reported participating in
them.What kinds of schools offer school-to-work programs, and
what kinds of students participate in them? The data indicate
that private high schools and high schools with high graduation rates and college attendance rates are less likely to offer
school-to-work programs.
Regarding the likelihood of schools with disadvantaged
student populations offering school-to-work programs, our
findings are somewhat ambiguous—on the one hand, schools
with dropout prevention programs are more likely than other
schools to offer school-to-work programs, while on the
other hand, schools with high percentages of Hispanic
students (who are more likely to be disadvantaged) and
schools receiving Title I funding are less likely to offer
these programs. Students who work while going to school are
more likely to participate in school-to-work programs, as are
youths who reported their course of study in high school as
technical, vocational, or business-oriented. Also, blacks are more
likely than whites to participate in school-to-work programs,
whereas youths whose mothers are highly educated are less
likely to participate in these kinds of programs.
□

NOTES
The views expressed in this article are those of the authors and do
not necessarily reflect the views of the U.S. Department of Labor.
1
The Act called for approximately $300 million to be appropriated for fiscal year 1995, with equal amounts being available for fiscal
years 1996–99. Federal funding for school-to-work programs is scheduled to end in 2001.
2
Concise definitions of these three components were not provided in the Act. The definitions that follow were developed by
Mathematica Policy Research, Inc., an organization that has been
involved in a large-scale study to evaluate school-to-work grants. See
The First National Survey of Local School-to-Work Partnerships: Data
Summary, August 1997.
3
A copy of the School-to-Work Act is available on the Internet at
www
.stw
.ed.gov/factsht/act.htm
www.stw
.stw.ed.gov/factsht/act.htm
.ed.gov/factsht/act.htm.
4
The NLSY 97 is an annual survey that, among other things, will
interview youths while they make their transition from school to the
workforce. When the present analysis was conducted, however, data
were available from only one interview with these youths, and most of
them were still attending school. Nonetheless, for an analysis of the
effects of school-to-work programs on early youth outcomes, see
David Neumark and Mary Joyce, “Evaluating School-To-Work Programs Using the New NLSY ,” Working Paper 7719 (Cambridge, MA ,
National Bureau of Economic Research, May 2000).
5
Primary sampling units are geographical constructs consisting of
either a metropolitan area or a county.
6
Or 5,295 responses out of 7,390. Among the respondents, another 42 failed to answer any of the first 11 questions in the schoolto-work section and thus were dropped from the analysis.
7
“Title I” is short for “Part A of Title I of the Improving
America’s Schools Act of 1994, Reauthorization of the Elementary
and Secondary Education Act of 1965.” Title I is the largest Federal
aid program for our Nation’s schools and is aimed at providing educational services to children who are the furthest from meeting the
standards that each State has set for all children.
8
Throughout this article, all estimates of means, proportions, and
percentages are sample-weighted. The logistic regression estimates
that appear later are not weighted.
9
Or 4,484 out of 8,984. Actually, 4,489 were asked the school-towork questions, but 5 were dropped from the analysis due to missing or
ambiguous information on their current grade level.
10
Clearly, we will be able to examine this issue when data from later
waves of the survey are available.
11
To determine the number of respondents for which information
on a given characteristic is missing, simply add up the unweighted
numbers in the first column of table 2 and subtract the resulting sum
from 4,484.
12
There are, however, instances where this may be valid. In par-

Appendix:

ticular, in the NLSY 97, the youth was asked whether they “ever”
participated in these programs and not whether they participated in
the programs at their current school, so it is possible that the youth
could have participated in the program at another school or through
an another organization (i.e. church, business group, or civic organization). However, we suspect that this is at most a minor part of the
problem, as the inconsistencies appear almost as severe for schoolbased as for work-based programs.
13
As mentioned previously, a nonresponse to the question on
whether the school offered a particular program was treated as a “no”
response. To the extent that this is not the case, the percent of
schools estimated to have these programs will be underestimated.
14
That is, we conducted a statistical test that incorporated the
standard error associated with each estimate and found that the hypothesis that the two estimates are equal could be rejected at the 5percent significance level.
15
The incidence rate for schools in which 25 to 75 percent of the
student body is black also was larger than the incidence rate for schools
in which more than 75 percent of the student body is black; however,
this difference, while similar in magnitude to the difference mentioned in the text, was not statistically significant.
16
Note that the odds ratios on a discrete variable should be interpreted relative to the excluded category. The excluded categories in
Table 7 are public schools, schools in suburban locations, schools with
graduation rates in quartiles 1 to 3, schools with college enrollment in
quartiles 1 to 3, schools without breakfast programs, schools without
Title I funding, and schools without dropout prevention programs.
17
Meaning that we conducted statistical tests incorporating the
standard errors associated with each estimate and found that the hypothesis that the two estimates are equal could be rejected at the 5percent significance level.
18
We also examined the relationship between school-to-work programs and two alternative measures of working that may signal a different level of attachment to the labor force than holding a job during the
survey week. The first was an indicator variable for whether or not the
youth worked for an employer at any time during the 1996–97 school
year or following summer. The second was an indicator variable for
whether or not the youth worked for an employer during the 1996–97
school year. The results using the first work variable were very similar to
those discussed in the text. The second work variable also was positively
related to participation in school-to-work programs, but the association
was not statistically significant.
19
The excluded categories in Table 12 are youths whose grades in 8th
grade were in the “A” to “B” range, youths not working, youths who said
their chance of completing college was greater than 66 percent, youths
in college preparatory course of study, male youths, nonblack and nonHispanic youths, youths whose biological mother has a high school education, youths in public schools, and youths in rural areas.

Definitions of school-to-work programs in NLSY97 and SAS96

The NLSY97 interviewers were instructed to show the respondents a card with the school-to-work programs and their definitions. The interviewers then asked, “Here is a list of some
of the kinds of programs schools offer to help students prepare for the world of work. Have you ever participated in any
of these programs through your school?” The following is
the list of programs and their definitions (listed in the order in
which they were asked):

•
•
•
•

Career major program, which is a defined sequence of
courses based upon an occupational goal;
Job shadowing, which is to spend time following workers
at a work site;
Mentoring, which involves being matched with an individual in an occupation;
Cooperative education, which combines academic and

Monthly Labor Review

August 2001

49

School-to-Work Programs

•

•

•

vocational studies with a job in a related field;
School-sponsored enterprise, which involves the production of goods or services by students for sale to or use
by others;
Tech prep, which is a planned program of study with a
defined career focus that links secondary and post-secondary education;
Internship or apprenticeship, which involves working for
an employer to learn about a particular occupation or
industry.

The SAS96 was administered by a paper questionnaire that
was filled out by school administrators and mailed back to
the National Opinion Research Center. The specific schoolto-work programs were asked about in a grid-style questionnaire with each column pertaining to a different program.
The grid was preceded by the following instructions and definitions of terms:

students alternate or parallel their academic and vocational studies with a job in a related field. May or may not
include paid work experiences.
•

Internship: For a specified period of time, students work
for an employer to learn about a particular industry or
occupation. Students’ workplace activities may include
special projects, a sample of tasks from different jobs, or
tasks from a single occupation. May or may not include
paid work experiences.

•

Job shadowing: Typically as part of career exploration
activities in early high school, a student follows an employee for one or more days to learn about a particular
occupation or industry. Job shadowing is intended to
help students hone their career objectives and select a
career major for the latter part of high school.

•

Mentoring: Pairing a student with an employee over an
extended period of time during which the employee helps
the student master certain skills and knowledge the employee possesses, models workplace behavior, challenges the student to perform well, and assesses the
student’s performance. Mentoring may be combined with
other work-based learning activities, such as internships
or on-the-job training.

•

School-sponsored enterprise: The production of goods
or services by students for sale to or use by others.
School-sponsored enterprises typically involve students
in the management of the project. Enterprises may be
undertaken on or off the school site.

•

Tech prep: A planned program of study with a defined
career focus that links secondary and post-secondary
education.

The questions on the following pages are about work-based
and career-oriented activities offered at your school. Please
refer to the glossary that follows for definitions of activities and terms referenced in this section.
•

Apprenticeship: Typically, multiyear programs that
combine school- and work-based learning in specific
occupational areas or occupational clusters and are designed to lead directly into either a related postsecondary
program, entry-level job, or registered apprenticeship program. May or may not include paid work experiences.

•

Career major: A coherent sequence of courses based upon
an occupational goal.

•

Cooperative education: A method of instruction whereby

50

Monthly Labor Review

August 2001

Racial Differences in Youth Employment

Racial differences
in youth employment
Work experience at an early age positively impacts
labor force attachment of different racial groups;
however, racial gaps in employment that are present
in the early teen years seem to continue into adulthood
Rosella M. Gardecki

Rosella M. Gardecki is
a senior research associate, Center for
Human Resource Research at The Ohio
State University.
E-mail:
gardecki@postoffice.
chrr.ohio-state.edu

S

ince the late 1960s, researchers have noted
large differences in employment and unemployment rates among black workers,
Hispanic workers, and white workers. These differences have generally been the greatest for
younger workers. For example, Robert Flanagan
documents that white workers have historically
held jobs at a higher rate than black workers; for
young workers, this gap widened in the 1960s
and the 1970s when the employment rate of black
teens decreased further.1 Recent studies show
that this early joblessness has an impact on later
employment probabilities and wage outcomes.2
However, few studies have examined the impact
of jobholding on later employment probabilities
among the youngest workers.
Data from the National Longitudinal Survey
of Youth 1997 cohort (NLSY97) indicate that the
youngest teens follow the same employment
trends. Slightly more than half of the NLSY97 14year-olds report some type of work activity;
nearly 24 percent of them are working at an employee-type job (that is, working for an employer), while about 43 percent report employment at a freelance job (for example, babysitting,
snow shoveling, pet care).3 Jobholding among
14- and 15-year-old nonblack/non-Hispanic
youths is markedly higher than among their black
and Hispanic counterparts.
Working at a freelance job differs from working at an employee-type job in a number of as-

pects that may make freelance jobs a more viable
option for many teens. Periods of actual work at
freelance jobs typically are more sporadic and
generally have low hours requirements. In addition, freelance jobs are not subject to the Fair
Labor Standards Act—that is, they have neither
maximum hours constraints nor the need for parental permission—and can be held at any age.
As a result, many 12- and 13-year-olds, who are
not eligible for most employee-type jobs, hold
freelance jobs. Freelance jobholding in the
NLSY97 does not stop at these ages, but continues to be a regular source of employment and
income throughout the teenage years.4
This article examines the factors that affect
different types of jobholding among teens in order to better understand employment decisions
the youngest workers must confront, and how
these decisions may differ by racial group. It focuses on the individual, family, neighborhood,
and spatial characteristics that affect jobholding
among teens living in a parental household. The
pattern of an employee-type jobholder is examined separately from that of a freelance jobholder
in an attempt to measure differences between the
propensity to hold either type of job. This article
presents a brief review of the existing literature
on teen employment; explains the data used and
the selection criteria for the NLSY97 sample; lists
the factors that affect employment at any job for
young workers—those aged 12 through 18 are
Monthly Labor Review

August 2001

51

Racial Differences in Youth Employment

considered—as a whole and by racial group (black, Hispanic,
nonblack/non-Hispanic); examines the types of jobs held—
that is, employee-type jobs and freelance jobs, and discusses
the effect of holding a job, during the year that the youth was
14, on the probability of employment among teens ages 16
and older.

What previous research shows
According to recent figures, racial differentials in employment have continued into the present decade, improved economic conditions notwithstanding.5 Despite the sizable gap
in employment for teens, only a limited number of studies
focus on this group; most researchers consider differences
in labor force status among older workers who have finished
their formal education.
In one of the few studies to examine jobholding among
younger teens, Robert Michael and Nancy Brandon Tuma
used data from the NLSY79 to consider differential employment effects for 14- and 15-year-old workers.6 Nearly 25 percent of 14-year-olds reported being employed at the time of
the survey, and this percentage increased for each age group.
Even among the youngest workers, large differences in employment patterns were present between racial groups. White
teens were more likely to be employed than their black or
Hispanic counterparts at any age. Further, 16- and 17-yearold youths who reported employment prior to the age of 16
were more likely to be employed and were working more hours
than those without prior experience.
Most of the remaining research focuses on racial differences in employment among older teens—those who are at
least aged 16 years.7 Although debate continues regarding
which factors cause the differential, a number of characteristics have been identified. These factors can be grouped into
four areas: individual characteristics, family determinants,
neighborhood and geographic factors, and spatial mismatch
measures.

Individual characteristics. Aside from the typical demographic characteristics (for example, age, race, gender, schooling),
other individual characteristics may impact on the probability of a youth working. In particular, a number of studies
focus on the relationship between employment and criminal
activity. Not surprisingly, most of these studies support the
hypothesis that crime and employment are competing forces
for a youth’s time.8 As a result, participation in criminal activity decreases the probability that a teen is employed. Richard Freeman used self-reports of criminal activity as a measure of the tradeoff between crime and employment. He found
that youths who reported committing a crime in the previous
month were less likely to be employed than those who did
52

Monthly Labor Review

August 2001

not report criminal activity. Least likely to be employed were
youths who reported high income from criminal activities or
who had been jailed in the previous year.9
John Bound and Richard Freeman, and Jeff Grogger found
that a proportion of the employment differential between black
and white youths can be attributed to whether a youth has a
criminal record.10 These figures do not necessarily result entirely from a time tradeoff between criminal activity and employment, because an arrest may signal to employers that the
youth will not be a dedicated worker. On the other hand,
using the National Longitudinal Survey of Young Men, Freeman found that church attendance is a strong indication that
a youth will “escape” a background of poverty to become
employed.11

Family characteristics. Characteristics of the youth’s family
may also affect his or her probability of working. These factors may either indicate unobserved family characteristics
that promote labor market attachment or point to household
characteristics that may ease the youth’s transition into the
labor market (for example, established job networks or employment opportunities that arise through another household member’s work). Factors most often considered include
the employment behavior of the respondent’s parents and
siblings, single parent households, and the poverty status of
the household.
Mary Corcoran, Richard Gordon, Deborah Laren, and Gary
Solon used a sample of men from the Panel Study of Income
Dynamics (PSID) to examine the relationship between family,
community, and employment.12 Their strongest result indicates that family or community welfare receipt negatively affects the men’s probability of working; not surprisingly, those
from families who have spent more time in poverty are also
less likely to work. Albert Rees and Wayne Gray found that
parental characteristics have no effect on employment, while
siblings who work positively affect the respondent’s work
behavior.13
Neighborhood and geographic factors. A number of studies have found that the characteristics of the youth’s geographic area—and especially the immediate neighborhood—
affect whether a youth begins working at an early age. The
types of jobs prevalent in the region may determine the availability of teen jobs; for example, areas dominated by heavy
industry may present teens with fewer opportunities due to
safety regulations. In addition, neighborhood factors may
impact on the probability of working in two ways, according
to Bruce Weinberg, Patricia Reagan, and Jeffrey Yankow.14
First, these factors may influence the decision to work by
changing the stigma attached to unemployment; for example,
a neighborhood with a high unemployment rate may attach

less of a stigma to not working than may a low-unemployment neighborhood. Second, certain neighborhood characteristics may determine how effective the job network is. High
unemployment may degrade the job network because fewer
residents are in the labor market and able to pass along information about employers or job openings.
Bound and Freeman showed that geographic location accounts for part of the racial difference in employment.15 Finding that the black/white employment and earnings gaps in
the 1970s and 1980s were larger in the Midwest than elsewhere, they attribute part of this outcome to regional changes
in industrial composition and dominant occupations. In a
separate study, Freeman determined that economic activity
in a geographic area impacts on the probability of youth employment. 16 He found that the important indicators of economic activity are the area’s unemployment rate, poverty status, growth in personal income, industrial composition, and
proportion of older to younger workers.17
On a neighborhood level, Katherine O’Regan and John
Quigley used 1990 Census data to consider the effects of
living in a predominantly nonblack/non-Hispanic census tract
and of living in a census tract with higher poverty, which
they refer to as social isolation.18 Focusing on black and
Hispanic youths who live at home, their results indicate that
the employment probabilities of a minority youth living in a
predominately white or lower poverty census tract are higher
than minorities residing elsewhere. Finally, Weinberg, Reagan,
and Yankow examined the block-groups in which male NLSY79
respondents reside, and determined that neighborhood characteristics do affect the probability of employment. However, they also find that ordinary least square overstates the
impact of neighborhoods, and that including individual fixed
effects reduces the residence effect by two-thirds or more
when compared to ordinary least square regressions.19

Spatial mismatch. According to the spatial mismatch theory
first advanced by John Kain, housing segregation affects
black employment opportunities because jobs are located
outside of the urban areas with high black populations.20
Also applied to Hispanics in subsequent studies, this theory
is particularly appealing when considering the employment
of teens because this group is generally tied to their residential area by their parents. Neighborhood factors differ from
spatial mismatch in that the first takes into account the composition of the residence along a number of dimensions while
the second considers the proximity of jobs to the residents of
an area. Richard Arnott states that spatial mismatch may either involve problems encountered in job search or reflect
job access or difficulties with transportation.21
First, the job search aspect of spatial mismatch theory
suggests that urban teens cannot search effectively for a job

due to poor connections to an area rich in jobs. Using a
sample of nonenrolled civilian men in the 1981 and 1982 NLSY79
surveys, Harry Holzer found that informal job search, which
involves job networks (for example, checked with friends or
relatives and direct application without a reference), results
in the most job offers for both black (60 percent) and white
teens (70 percent).22 However, white youths have a higher
probability of a job offer using any search method. Holzer
concluded that this difference accounts for the racial gap in
employment, with job offers resulting from informal job search
leading to 87 to 90 percent of the differential.
The second problem relates to access to jobs and lack of
transportation for youths ages 14 and 15—a problem that is
aggravated by their inability to drive. Research suggests the
impact of this factor is not uniform across metropolitan areas.
A number of researchers used microdata and discovered that
proximity to a job-rich area, as measured by commute times,
affects the probability that a youth is employed.23 Keith
Ihlanfeldt and David Sjoquist found that the “nearness” of
jobs impacts on both black and white youth employment in
Philadelphia, but only affects black youths in Los Angeles
and Chicago. Using an index of commute times in four metropolitan areas in New Jersey, O’Regan and Quigley determined
that longer commutes have a negative impact on minority
teen employment, but the magnitude and significance of their
measure varies across metropolitan areas.
Combining the two problems, Holzer, Ihlanfeldt, and
Sjoquist considered the effect of longer travel times on both
work and search behavior.24 Although they focus on slightly
older workers—NLSY79 respondents aged 16 to 24—this
group is similar to younger workers in that a number lived in
the parental home. Their findings indicate that greater travel
for work or search activity was positively related to wage
gains. Due to residence constraints and nonownership of an
auto, black respondents faced higher travel costs per mile,
resulting in a smaller search area.

Constructing the study
Aside from extensive employment data, the round 1 NLSY97
provides current and retrospective data on all youth respondents, limited data on the current status of other household
members, and, in cases in which the parent interview was
completed, extensive data on the responding parent. The
round 1 NLSY97 sample consists of 8,984 respondents who
were aged 12 to 18 at the time they were interviewed.25 In
round 2 NLSY 97, 8,386 of the youth respondents completed
an interview; in addition to answering questions about themselves, they also provided all updates and changes to household composition and parental information, excluding family
income.

Monthly Labor Review

August 2001

53

Racial Differences in Youth Employment

What factors influence youth employment? This question
is addressed using round 1 NLSY97 data. How does early
work experience affect the probability that older teens work?
To address this question requires restricting the sample to
youths age 16 or older. In round 1, a large majority of youths
interviewed were aged 15 or younger, so data from rounds 1
and 2 of the NLSY97 were merged.26

Variable definitions. The employment variables discussed
in this article equal 1 if the respondent worked at any job, at
a freelance job, or at an employee-type job within 4 weeks of
the interview date and zero otherwise. To measure the probability of working at an employee-type or a freelance job at
age 14, a dummy variable is formed based on the starting and
ending dates of the respective job types and birth dates reported by youths in the NLSY97.
Both age and highest grade completed are continuous variables taken directly from the survey instrument and measured
as of the interview date. The dummy variables for black and
Hispanic are created from the expanded race and ethnicity
codes collected in the screener part of the round 1 instrument. Any youth who is reported as Hispanic in either the
race or the ethnicity question is considered Hispanic in this
study; black respondents who are also Hispanic are coded as
Hispanic.27 Enrollment is defined as continuous enrollment;
thus, youths on summer vacation are still considered enrolled.
The variable “summer” equals 1 if the respondent was interviewed during the summer months (June, July, and August)
and zero otherwise. Because teens tend to hold jobs with
greater frequency during the summer, this variable is included
to capture differences in jobholding based solely on the time
of year the youth was interviewed. Youths with any number
of children are coded as a 1 in the “has a child” variable; all
other youths are coded as zero.
Because the respondents are at the age where peer effects
may influence their present and future behaviors, the NLSY97
presents a unique opportunity to look at the groups that
impact on youths by asking the respondent a number of questions about his or her peers. The survey includes a number of
questions about the respondent’s perception of peer involvement in various activities and of peer educational plans; from
these questions, three variables were formed to capture teen
activities.28 The first looks at the percent of peers who plan
to attend college. The effect that this variable might have on
teen work is uncertain. If more motivated youths tended to
go to college, this variable would have a positive effect on
employment; conversely, if teens who were focused on college spent more time studying, they would work less. The
second variable focuses on “positive activities” for youths
as measured by church-going activity and volunteerism. It is
unclear whether these types of activities serve as a signal
54

Monthly Labor Review

August 2001

that a youth is a “good kid” or whether knowing large numbers of people who participate in these activities actually
changes the behavior of teens.29 Finally, NLSY97 considers
whether knowing a number of peers who participate in “negative activities”—such as taking part in illegal activities or
belonging to a gang—affects employment behavior. Like the
positive activities, it is unclear whether associating with peers
involved in these activities provides a signal for future employers or indicates something about the pre-existing work
ethic of respondents.
For the purposes of this article, “crime” is defined as stealing something worth $50 or more, selling drugs, or other property crimes, such as fencing stolen property, possessing or
receiving stolen property, or deliberately selling something
for more than it was worth. Youths who have been institutionalized for any crime are coded as 1 in the criminal institution variable.
The family variables are derived from the household roster, created during the screener portion of the NLSY97 interview. Siblings equals 1 if siblings of any type (biological,
adoptive, step, or foster) were recorded in the household; the
employment of siblings is a count of the number of these
siblings age 16 or older who were employed as of the survey
date. The employment of parental figures and living in a female-headed household are determined for the same relationships (for example, biological, adoptive, step, and foster).
Residence variables were originally created by NLSY97 staff
based on respondent addresses. For this article, four dummy
variables indicate the respondent’s region of residence.30
The urban/rural variable on the NLSY97 Main CD was similarly
changed into a dummy variable, with residence in an urban
area equal to 1.31 Taken from the NLSY97 Geographic CD, the
unemployment rate in the respondent’s metropolitan area is a
continuous exact number based on the March CPS. The poverty rate variable indicates the percent of households in the
respondent’s county of residence with incomes below the
poverty level.
Finally, the spatial access variable used in this article is
the mean travel time to work at the county level; it is derived
from the 1994 County-City Data Book.32 Although this variable is constructed from data for older workers (those aged
16 and older), it serves as a proxy for the distance between
youths and jobs.

Sample construction. Sample one uses the employment behavior of at-home teens, regardless of age, as reported in the
round 1 survey. This sample includes at-home respondents
who have valid data for all variables as defined above. These
youths were aged 12 to 18 during round 1 of the survey. In
addition, sample one includes only respondents with an identifiable parent or a parent figure. After these restrictions are

applied, the sample includes 8,511 respondents, of whom 5,743
were at least 14 years old and eligible to report employeetype jobs. Details on the number of respondents excluded
due to each restriction are provided in the appendix.
Sample two is used to address the issue of whether work
experience at age 14 impacts on the employment probabilities
of older teens. Answering this question requires information
on the youth’s residence both at age 14 and at the interview
date because the spatial mismatch literature indicates that
this may impact on employment probability. Because most
respondents had not yet turned 16 at the date of the first
interview, data from both round 1 and round 2 of the NLSY97
survey are examined to increase the size of sample two. At
the time this research was conducted, round 2 addresses were
not geocoded, and only teens who met certain residence restrictions (described in the appendix) were included in the
sample. In short, these restrictions required teens to remain
at the same residence for a period of time. After imposing the
residence restrictions, 2,512 respondents remained in sample
two.
Note that rather than measuring the effect of jobholding in
the 14th year on later employment, this article addresses
whether, among at-home teens who remain in the same labor
market from the age of 14, those who hold a job do better than
those who do not work. Although the difference may seem
subtle, the issue of sample selection bias must be considered. Nonmoving youths may have more stable job networks
(for example, family, friends, former employers) and may be
more likely to be employed at older ages as a result. In addition, movers may have a lack of familiarity with the area and
with available employers that hinders their ability to find work.
Finally, since most teen positions are awarded on the basis of
recommendations rather than work experience, movers may
have more difficulty obtaining a known reference in a new
area.
Due to these factors, the returns to holding a previous job
may be biased upward for this sample. The following tabulation shows the weighted effect of residence restrictions on
probability of employment at age 14:
Variable
Any job at age 14 .............................
Employee-type job at age 14 ........
Freelance-type job at age 14 .........
Employee type job at age 16 ........

In-scope Out-of-scope
0.61
.27
.47
.46

0.58
.24
.44
.39

A larger percentage of the nonmovers held any type of job
(61 percent versus 58 percent for movers) at the age of 14; the
same was true of employee-type jobs (27 percent versus 24
percent) and freelance jobs (47 percent versus 44 percent).
Further, a larger percentage of nonmovers than movers in this

sample held a job within 1 month of the latest survey date (46
percent versus 39 percent). In addition, this type of sample
selection bias may affect the family variables because older
family members who lived in the same location for a period of
time may have better connections to jobs for the respondent
through friends and coworkers. This may cause returns to
employment of the respondent’s parent(s) or siblings to be
overstated. However, determining how this sample selection
may bias other measures is beyond the scope of this article.

Racial disparities
In the last several decades, jobholding among teens—especially those in the youngest age group—has been increasing. Looking at the first year of the NLSY79, Michael and Tuma
found that approximately 25 percent of 14-year-olds held
jobs, with the rate increasing to slightly more than 50 percent
by age 17.33 The following tabulation shows the weighted
employment rates by age group:
Survey

Age
14

Age
15

Age
16

Age
17

...................................... 25.1

26.9

38.0

50.9

41.7
41.7
41.7

44.4
44.4
44.4

54.3
54.3
54.3

61.2
61.2
61.2

and employee-type job ...... 41.7

44.4

54.3

61.2

NLSY79

NLSY97 any job .........................
NLSY97 employee-type job ...
NLSY97 freelance job ..............
NLSY97 both freelance

Also presented in the above tabulation is the percentage
of NLSY97 teens eligible for this article, as described above,
who hold jobs.34 The percentage of eligible youths holding
jobs in the NLSY97 is higher than in the NLSY79 when all jobs
are considered. Although this may reflect that more teens are
working in the late 1990s than in the early 1980s, when economic conditions would have been worse, it may also reflect
differences in the fielding periods that contribute to the NLSY97
collecting higher numbers of jobs.35
The increase in jobholding as the cohort ages follows the
same pattern as in the NLSY79. A lower percentage of younger
respondents in both surveys work and that percentage increases over time.) As expected, employee-type jobholding,
increases with age as respondents in the NLSY97 both become more mobile and age out of the Fair Labor Standards act
restrictions to become eligible to work at more jobs. Freelance
jobholding increases and then falls as more youths begin
holding employee-type jobs; the percentage of those holding freelance jobs is higher for 14-year-olds than for any other
age group.
Across all respondents, who are between the ages of 12 and
18 in round 1, jobholding by youths in the NLSY97 is the norm

Monthly Labor Review

August 2001

55

Racial Differences in Youth Employment

rather than the exception. About 66 percent of the round 1
respondents in this sample reported having ever held either
an employee-type job or a freelance job. Jobholding was
higher among nonblack/non-Hispanic youths (71.1 percent)
than either black (52.2 percent) or Hispanic youths (51.6 percent). (See table 3.) Looking at type of job reveals that a larger
percentage of nonblack/non-Hispanic youths (44.6 percent
and 55.9 percent, respectively) hold either employee-type or
freelance jobs than their black or Hispanic counterparts. More
Hispanic than black teens reported holding employee-type
jobs, although more black youths reported participating in
freelance activity.
Given the racial disparities with respect to the prevalence
and type of youth employment, it is important to consider
whether holding any type of job during the early teenage
years has an impact on later employment probabilities. In
short, it does. The percentage (67) of youths who reported
holding any type of job during their 14th year worked at an
employee-type job after the age of 16, compared with only 53
percent of those who were not early jobholders. The following tabulation shows the weighted probabilities of employment at employee-type jobs for older teens by employment
status at age 14:
Variable

All
Black Hispanic Nonblack/
youths youths youths
nonHispanic
youths

No job held .................

0.53

0.40

0.39

0.59

Held any job ...............
Employee-type
job .........................
Freelance job ...........
Both employee-type
and freelance jobs .

.67

.58

.66

.69

.82
.59

.73
.51

.74
.62

.84
.60

.73

.56

.69

.75

This is true regardless of racial group. It is interesting to
note that the type of job also seems to matter. Those who
held an early employee-type job (82 percent) were working
after their 16th birthday, while only 59 percent of those reporting a freelance job during their 14th year were working
after the age of 16. This holds for all racial groups, although
the probability of attaining an employee-type job after the
age of 15 is about the same for nonblack/non-Hispanic teens
who held a freelance jobs during their 14th year as it is for
those who did not work.
Other differences exist among the groups included in the
survey, with potential effects on early employment. (See table
1.) Across racial groups, there are only minor differences in
age and years of schooling. The majority of respondents (89.4

56

Monthly Labor Review

August 2001

percent) report at least one parent who works; black teens are
the least likely to have a parent working, and nonblack/nonHispanic youths are the most. Conversely, nearly 51 percent
of black teens live in female-headed households, while only
20 percent of nonblack/non-Hispanic youths do so.
Turning to peer effects, about 57 percent of the respondents reported that a large percentage of their peers planned
to attend college, while only 21 percent reported that most of
their peers were involved in negative activities. Interestingly,
more black youths reported that their peers were involved in
both negative (28.4 percent) and positive activities (34.4 percent) than their nonblack/non-Hispanic (19.0 percent and
30.6 percent, respectively) or Hispanic (23.8 percent and 28.1
percent, respectively) counterparts. Despite their peers’ behavior, only about 16 percent of each group reported committing a serious crime themselves and about 2 percent reported
having been institutionalized for any crime.
Geographically, more Hispanic respondents live in the
West, in urban areas, and in areas of relatively high unemployment, while the majority of black youths are located in
the South, in urban areas, and in counties with a high poverty
rate. Finally, nonblack/non-Hispanic respondents live in
counties with lower average travel times to work than either
black or Hispanic teens.

Probability of employment
What is the impact of individual, family, geographic, and access measures on the probability that a youth is working at
any type of job?36 Being black or Hispanic significantly reduces the probability of employment. (See table 2.) Conversely, being female is positively associated with working.
Completing more years of formal education has a significant
positive relationship to working, although being enrolled has
no effect.
Youth behavior also impacts on the probability of working. Believing that at least 75 percent of one’s peers intend to
attend college increases the probability of employment; other
peer behaviors have no significant effect. Contrary to previous studies, those who report committing a serious crime are
nearly 4 percentage points more likely to be employed. This
counterintuitive finding may indicate that working teens have
more opportunities to commit a crime (such as theft) than do
nonworking teens. Further, the base amount for stealing may
be too low to be considered a serious crime since most youths
caught stealing this small amount would most likely not face
serious consequences, such as institutionalization. As expected, being institutionalized for any crime—regardless of
the crime’s severity—has a negative impact on the probability that a teen is employed.
The work behavior of a parent has a significant positive

Table 1.

Weighted sample means by racial group
Variable

Total

Black

Hispanic

Nonblack/
non-Hispanic

Ever held any job .......................................................
...................................................................................
Ever held employee job .............................................
...................................................................................
Ever held freelance job ............................................
...................................................................................
Age .............................................................................
...................................................................................
Female .......................................................................
...................................................................................
Enrolled in school ......................................................
...................................................................................
Highest grade completed ...........................................
...................................................................................
Interviewed in summer ...............................................
...................................................................................
Has a child .................................................................
...................................................................................

0.659
(.474)
.410
(.492)
.513
(.500)
14.4
(1.51)
.486
(.500)
.978
(.147)
7.74
(1.59)
.226
(.418)
.005
(.069)

0.522
(.500)
.306
(.461)
.402
(.491)
14.4
(1.52)
.490
(.500)
.983
(.128)
7.66
(1.61)
.240
(.427)
.014
(.119)

0.515
(.500)
.329
(.470)
.373
(.484)
14.4
(1.49)
.464
(.499)
.967
(.179)
7.70
(1.61)
.239
(.427)
.003
(.056)

0.711
(.453)
.446
(.497)
.559
(.497)
14.3
(1.51)
.489
(.500)
.979
(.145)
7.76
(1.58)
.221
(.415)
.003
(.055)

Percent of peers who expect
to attend college ....................................................
...................................................................................
Percent of peers in positive activities ......................
...................................................................................
Percent of peers in negative activities .....................
...................................................................................
Ever committed a crime .............................................
...................................................................................
Ever been institutionalized for a crime .....................
...................................................................................
Has a sibling ..............................................................
...................................................................................
Siblings employed ......................................................
...................................................................................
Female head of household ........................................
...................................................................................
Parents employed ......................................................
...................................................................................

.574
(.494)
.308
(.462)
.210
(.407)
.164
(.370)
.021
(.144)
.844
(.363)
.308
(.581)
.253
(.435)
.894
(.308)

.470
(.500)
.344
(.475)
.284
(.451)
.163
(.370)
.020
(.139)
.826
(.380)
.306
(.625)
.506
(.500)
.794
(.405)

.493
(.500)
.281
(.450)
.238
(.426)
.167
(.373)
.026
(.160)
.884
(.320)
.399
(.662)
.294
(.456)
.849
(.358)

.609
(.488)
.306
(.461)
.190
(.393)
.163
(.370)
.021
(.142)
.840
(.366)
.292
(.555)
.195
(.396)
.921
(.269)

Northeast ...................................................................
...................................................................................
North-central ..............................................................
...................................................................................
South ..........................................................................
...................................................................................
West ...........................................................................
...................................................................................
Urban ..........................................................................
...................................................................................
Unemployment rate ....................................................
...................................................................................
Percent in poverty (county) ......................................
...................................................................................
Mean travel time to work (county) ............................
...................................................................................

.187
(.390)
.266
(.442)
.325
(.468)
.222
(.416)
.537
(.499)
5.17
(2.60)
9.88
(5.51)
21.9
(4.79)

.148
(.355)
.169
(.375)
.574
(.495)
.110
(.313)
.645
(.479)
4.80
(2.12)
13.1
(7.20)
23.2
(4.96)

.151
(.358)
.122
(.327)
.277
(.448)
.450
(.498)
.725
(.446)
6.74
(3.82)
10.8
(5.63)
23.6
(4.93)

.201
(.401)
.311
(.463)
.283
(.451)
.205
(.404)
.482
(.500)
4.96
(2.31)
9.07
(4.79)
21.3
(4.61)

Number in sample ......................................................

8,511

2,105

1,808

4,598

1
Youths aged 12 and 13 do not specifically report employee jobs. Therefore, the number of cases for this variable differs from all other variables. The
numbers of cases are as follows: total: 5,743; black: 1,454; Hispanic: 1,201; and nonblack/non-Hispanic: 3,088.

NOTE: Standard errors are in parentheses.

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August 2001

57

Racial Differences in Youth Employment

effect on the employment probability of the youth. (See table
2.) As pointed out earlier, this may indicate either the presence of better connections to the labor market or unobserved
family characteristics. However, the number of siblings, the
siblings’ employment status, and living in a female-headed
household do not significantly affect the employment probability of the youth.
Youths living in the Northeast are about 6 percentage
points less likely to be employed than those in the west;
however, the employment probability of youths who live in
the north central or the southern region is not significantly
different from those in the West. Not surprisingly, living in
areas with high unemployment rates or high poverty rates
decreases the probability of employment, although living in
an urban area does not significantly impact on the probability of work.
Finally, table 2 presents a measure of average travel time
to work, reflecting job access and spatial mismatch. Living in
areas in which the average travel time to work is higher has a
significant negative impact on the probability that a teen is
employed.

Employee-type jobs. The probability that a youth works at
an employee-type job is included in table 3. As in the previous set of regressions, being black or Hispanic has a significant negative relationship to holding an employee-type job.
Regardless of race, being male or completing more years of
education increases the probability of holding an employeetype job. These effects are strongest for nonblack/non-Hispanic youths.
In general, the behavior of the teen’s peers does not affect
the probability of attaining an employee-type job; for
nonblack/non-Hispanic youths, however, associating with
peers engaged in positive activities significantly decreases
the probability of working. This seems counterintuitive; however, this may reflect nonblack/non-Hispanic youths trading time
that would have been spent at a job for time spent at church
or volunteering. In addition, having an employed sibling
significantly increases the probability that nonblack/non-Hispanic youths work. Regardless of racial group, the employment
of a parent is positively associated with the teen working at
an employee-type job, supporting the theory that unobserved family characteristics may influence the youth’s employment decision or that an established job network may
help the respondent find a job.
Finally, geographic factors influence the probability that
teens are working at employee-type jobs. Neighborhood factors have a significant negative impact on the probability
that a minority youth works at an employee-type job. Black
teens living in areas of high poverty, in counties with longer
commute times, or in areas of high unemployment are less
58

Monthly Labor Review

August 2001

likely to work. Only the unemployment rate is negatively associated with the probability of working for Hispanic teens.
Nonblack/non-Hispanic youths are not significantly affected
by these neighborhood characteristics; however, living in
the north central or southern regions increases the probability of employment for these teens.

Freelance jobs. The factors affecting freelance jobholding
are in table 4. Being black or Hispanic is negatively related to
holding a freelance job, as it was with employee-type jobs.
However, being younger or being female is positively associated with holding freelance jobs, regardless of race. Completing
more years of education does not impact on the probability
that teens hold a freelance job; however, being enrolled in
school increases the probability that a Hispanic youth works
at this type of job.
Peer behavior affects freelance jobholding. Knowing a
larger number of peers who plan to attend college increases
the probability that Hispanic and nonblack/non-Hispanic
youths work at a freelance job. Rather than college plans, it is
the percent of the teen’s peers involved in “good activities”
that positively impacts on the probability that a black teen
works; this supports Freeman’s finding that church attendance positively affects jobholding among black teens.37 As
expected, hanging out with a “bad crowd” or committing a
crime has a significant negative impact, but only for nonblack/
non-Hispanic youths. Conversely, committing a crime is positively associated with the probability that black and Hispanic
teens work for themselves. This counterintuitive result may
reflect the fact that working at a freelance job provides an
opportunity for committing a crime (for example, stealing from
customers) or it may reflect the reporting of illegal activity as
a freelance job (for example, lookout for a drug seller). As
expected, the effect of serving time in a criminal institution on
freelance jobholding is negative, but only for Hispanic
youths; serving time does not seem to affect the other groups.
Turning to family factors, having at least one parent in the
labor force or the presence of a sibling is positively related to
the probability that nonblack/non-Hispanic youths work.
This result does not extend to black or Hispanic teens. Unlike
employee-type jobholding, the employment of the
respondent’s sibling(s) does not matter.
Finally, geographic location affects the probability that
teens will work for themselves. Living in the West is positively related to holding a freelance job for black teens, while
living in the South or in urban areas negatively impacts on
the probability that Hispanic youths work for themselves.
Living in areas of high unemployment increases the probability that nonblack/non-Hispanic teens work at a freelance job,
possibly because fewer employee-type jobs are available. Regardless of racial group, living in counties with high poverty

Table 2.

Probability of employment for all youths
Spatial
effects

Variable

Individual effects

Family effects

Geographic
effects

Age .............................................................................
...................................................................................
Black ..........................................................................
...................................................................................
Hispanic .....................................................................
...................................................................................
Female .......................................................................
...................................................................................
Enrolled in school ......................................................
...................................................................................
Highest grade completed ...........................................
...................................................................................
Interviewed in summer ...............................................
...................................................................................
Has a child .................................................................
...................................................................................

0.012
(.008)
–.204
(.012)
–.212
(.012)
.042
(.011)
.006
(.037)
.045
(.007)
.014
(.014)
–.082
(.061)

0.016
(.008)
–.189
(.012)
–.206
(.012)
.044
(.011)
–.010
(.038)
.041
(.008)
.015
(.014)
–.082
(.061)

0.017
(.008)
–.167
(.014)
–.179
(.014)
.043
(.011)
–.009
(.038)
.041
(.008)
.016
(.014)
–.087
(.061)

0.014
(.008)
–.150
(.014)
–.165
(.014)
.042
(.011)
–.008
(.038)
.045
(.008)
.017
(.014)
–.090
(.061)

Percent of peers who expect
to attend college ....................................................
...................................................................................
Percent of peers in positive activities ......................
...................................................................................
Percent of peers in negative activities .....................
...................................................................................
Ever commmitted a crime ..........................................
...................................................................................
Ever been institutionalized for a crime .....................
...................................................................................
Has a sibling ..............................................................
...................................................................................
Siblings employed ......................................................
...................................................................................
Female head of household ........................................
...................................................................................
Parents employed ......................................................
...................................................................................

.042
(.011)
–.0002
(.012)
.007
(.014)
.036
(.016)
–.100
(.034)
–
–
–
–
–
–
–
–

.038
(.011)
–.001
(.012)
.010
(.014)
.037
(.016)
–.085
(.035)
.020
(.016)
–.004
(.009)
–.012
(.013)
.101
(.016)

.037
(.011)
.0003
(.012)
.008
(.014)
.028
(.016)
–.091
(.035)
.023
(.016)
–.003
(.009)
–.009
(.013)
.090
(.017)

.039
(.012)
.002
(.012)
.008
(.014)
.027
(.016)
–.096
(.035)
0.025
(.016)
–.002
(.009)
–.011
(.013)
.085
(.017)

Northeast ...................................................................
...................................................................................
North-central ..............................................................
...................................................................................
South ..........................................................................
...................................................................................
Urban ..........................................................................
...................................................................................
Unemployment rate (Metropolitan Statistical Area) ..
...................................................................................
Percent in poverty (county) ......................................
...................................................................................
Mean travel time to work (county) ............................
...................................................................................

–
–
–
–
–
–
–
–
–
–
–
–
–
–

–
–
–
–
–
–
–
–
–
–
–
–
–
–

–.053
(.017)
–.008
(.017)
–.021
(.016)
–.015
(.012)
–.0008
(.0002)
–.006
(.001)
–
–

–.034
(.018)
–.008
(.017)
–.015
(.016)
–.013
(.012)
–.0006
(.0002)
–.007
(.001)
–.008
(.001)

P-value, family variables (LR test) ............................
P-value, neighborhood variables (LR test) ...............
P-value, access variable (LR test) ...........................

–
–
–

.000
–
–

–
.000
–

–
–
.000

Number in sample ......................................................
Pseudo R2 ..................................................................

8,511
.066

8,511
.070

8,511
.076

8,511
.080

NOTE: Standard errors are in parentheses. Partial derivatives of probability of outcome associated with dependent variables with respect to
independent variables.

Monthly Labor Review

August 2001

59

Racial Differences in Youth Employment

Table 3.

Probability of working at an employee-type job by racial group
Nonblack/
non-Hispanic
youths

All youths

Black
youths

Hispanic
youths

Age ..............................................................................
....................................................................................
Black ...........................................................................
....................................................................................
Hispanic ......................................................................
....................................................................................
Female ........................................................................
....................................................................................
Enrolled in school .......................................................
....................................................................................
Highest grade completed ............................................
....................................................................................
Interviewed in summer ................................................
....................................................................................
Has a child ..................................................................
....................................................................................

0.047
(.008)
–.091
(.013)
–.056
(.014)
–.065
(.011)
–.044
(.035)
.061
(.007)
.035
(.013)
–.016
(.051)

0.010
(.012)
–
–
–
–
–.042
(.017)
–.026
(.060)
.054
(.011)
.018
(.020)
–.004
(.049)

0.038
(.015)
–
–
–
–
–.049
(.021)
–.068
(.062)
.040
(.013)
–0.021
(.023)
–.050
(.098)

0.074
(.014)
–
–
–
–
–.088
(.017)
–.039
(.054)
.067
(.012)
.077
(.021)
–.009
(.123)

Percent of peers who expect
to attend college .....................................................
....................................................................................
Percent of peers in positive activities .......................
....................................................................................
Percent of peers in negative activities ......................
....................................................................................
Ever committed a crime ..............................................
....................................................................................
Ever been institutionalized for a crime ......................
....................................................................................
Has a sibling ...............................................................
....................................................................................
Siblings employed .......................................................
....................................................................................
Female head of household .........................................
....................................................................................
Parents employed .......................................................
....................................................................................

.005
(.011)
–.019
(.012)
.017
(.013)
.022
(.015)
–.067
(.025)
–.019
(.015)
.018
(.009)
–.024
(.013)
.082
(.015)

–.004
(.017)
.006
(.019)
–.001
(.017)
.008
(.023)
–.070*
(.030)
–.012
(.022)
–.014
(.014)
.001
(.017)
.048
(.019)

.018
(.021)
–.011
(.024)
.012
(.023)
.030
(.028)
–.056
(.039)
.003
(.033)
.002
(.015)
–.034
(.023)
.071
(.024)

–.0003
(.017)
–.035
(.019)
.030
(.020)
.024
(.022)
–.071
(.043)
–.030
(.023)
.052
(.014)
–.028
(.021)
.102
(.027)

Northeast ....................................................................
....................................................................................
North-central ...............................................................
....................................................................................
South ...........................................................................
....................................................................................
Urban ...........................................................................
....................................................................................
Unemployment rate (Metropolitan Statistical Area) ...
....................................................................................
Percent in poverty (county) .......................................
....................................................................................
Mean travel time to work (county) .............................
....................................................................................

–.001
(.018)
.024
(.017)
.023
(.016)
.004
(.011)
–.0007
(.0002)
–.005
(.001)
–.003
(.001)

.014
(.040)
.020
(.034)
.029
(.028)
.004
(.019)
–.0008
(.0005)
–.005
(.001)
–.005
(.002)

.003
(.032)
–.014
(.035)
–.032
(.025)
–.024
(.023)
–.001
(.0003)
–.003
(.002)
–.004
(.002)

.017
(.028)
.059
(.026)
.046
(.028)
.015
(.017)
–.0002
(.0004)
–.002
(.002)
–.001
(.002)

P-value, family variables (LR test) .............................
P-value, neighborhood variables (LR test) ................
P-value, access variable (LR test) ............................

.000
.000
.004

.112
.001
.011

.015
.000
.104

.000
.134
.497

Number in sample .......................................................
Pseudo R2 ...................................................................

5,743
.132

1,454
.123

1,201
.125

3,088
.121

Variable

NOTE: Standard errors are in parentheses. Partial derivatives of probability of outcome associated with dependent variables with respect to
independent variables.

60

Monthly Labor Review

August 2001

Table 4.

Probability of working at a freelance job by racial group
Variable

All youths

Black
youths

Hispanic
youths

Nonblack/
non-Hispanic
youths

Age ................................................................................
......................................................................................
Black .............................................................................
......................................................................................
Hispanic ........................................................................
......................................................................................
Female ..........................................................................
......................................................................................
Enrolled in school .........................................................
......................................................................................
Highest grade completed ..............................................
......................................................................................
Interviewed in summer ..................................................
......................................................................................
Has a child ....................................................................
......................................................................................

–0.029
(.007)
–.098
(.012)
–.138
(.012)
.084
(.010)
.062
(.032)
.010
(.007)
–.006
(.012)
–.081
(.055)

–0.026
(.011)
–
–
–
–
.036
(.018)
–.030
(.071)
.012
(.011)
–.014
(.021)
–.049
(.057)

–0.015
(.012)
–
–
–
–
.040
(.018)
.126
(.028)
.010
(.011)
–.023
(.020)
–.057
(.117)

–0.036
(.011)
–
–
–
–
.124
(.014)
.048
(.052)
.009
(.011)
.008
(.019)
–.217
(.108)

Percent of peers who expect
to attend college .......................................................
......................................................................................
Percent of peers in positive activities .........................
......................................................................................
Percent of peers in negative activities ........................
......................................................................................
Ever committed a crime ................................................
......................................................................................
Ever been institutionalized for a crime ........................
......................................................................................
Has a sibling .................................................................
......................................................................................
Siblings employed .........................................................
......................................................................................
Female head of household ...........................................
......................................................................................
Parents employed .........................................................
......................................................................................

.029
(.010)
.008
(.011)
–.008
(.012)
.010
(.014)
–.039
(.034)
.033
(.013)
–.008
(.008)
.003
(.012)
.043
(.015)

–.018
(.018)
.034
(.020)
.007
(.020)
.053
(.027)
–.048
(.053)
.028
(.023)
–.001
(.014)
.008
(.018)
.015
(.022)

.038
(.018)
.005
(.020)
.027
(.022)
.073
(.028)
–.101
(.035)
.022
(.028)
–.008
(.013)
.029
(.021)
.029
(.024)

.041
(.015)
–.003
(.016)
–.039
(.019)
–.034
(.021)
.008
(.054)
.036
(.020)
–.015
(.013)
–.004
(.019)
.074
(.027)

Northeast ......................................................................
......................................................................................
North-central .................................................................
......................................................................................
South .............................................................................
......................................................................................
Urban .............................................................................
......................................................................................
Unemployment rate (Metropolitan Statistical Area) .....
......................................................................................
Percent in poverty (county) .........................................
......................................................................................
Mean travel time to work (county) ...............................
......................................................................................

–.034
(.015)
–.024
(.015)
–.028
(.014)
–.020
(.010)
.00002
(.0002)
–.004
(.001)
–.007
(.001)

–.097
(.028)
–.079
(.027)
–.098
(.030)
–.036
(.020)
–.00007
(.0005)
–.002
(.001)
–.005
(.002)

–.038
(.026)
.058
(.037)
–.045
(.022)
–.033
(.020)
–.0004
(.0003)
–.003
(.002)
–.010
(.002)

–.003
(.023)
–.002
(.022)
.015
(.023)
–.001
(.015)
.001
(.0003)
–.006
(.002)
–.006
(.002)

P-value, family variables (LR test) ...............................
P-value, neighborhood variables (LR test) ..................
P-value, access variable (LR test) ..............................

.008
.000
.000

.735
.004
.026

.524
.000
.000

.017
.003
.000

Number in sample .........................................................
Pseudo R2 .....................................................................

8,511
.054

2,105
.025

1,808
.061

4,598
.034

NOTE: Standard errors are in parentheses. Partial derivatives of probability of outcome associated with dependent variables with respect to
independent variables.

Monthly Labor Review

August 2001

61

Racial Differences in Youth Employment

rates or with long commute times negatively impacts on the
probability of freelance jobholding.

Jobholding of older youths. Does holding a job as a 14-yearold impact on the probability that youths age 16 and older
work at an employee-type job? It should again be noted that
the composition of this sample differs greatly from the composition of the prior sample, due to the residence restriction.
These results, while informative, cannot be generalized to the
teen population but rather address only nonmoving teens.
(See table 5.) Column 1 of the table presents the base specification without the prior jobholding information included; in
column 2, a dummy variable indicates whether the teen held
any type of job at the age of 14; column 3 separates the jobs
held at 14 into freelance and employee-type jobs. The results
indicate that holding any type of job at age 14 increases the
probability that older teens work for an employer. Further,
teens who held an employee-type job in their 14th year are
more likely to hold an employee-type job later compared with
freelance jobholders; however, both types have a positive
significant association with jobholding at older ages.
Holding an employee-type job as a teen increases the probability of employment regardless of racial group. (See table
6.) Hispanic youths gain the most from early work at an employee-type job, although black and nonblack/non-Hispanic
teens also benefit. Holding freelance jobs at age 14 is positively associated with the employment probabilities of black
and Hispanic youths, but has no effect on the nonblack/nonHispanic group.
Although these results provide an indication of the effect
of early employment, they may not capture the extent to which
unobserved characteristics affect early jobholding. For example, older nonworking teens who did not hold a job may
have chosen to devote their time to schooling or volunteer
activities rather than investing in work experience. Conversely, those who took a job between the ages of 14 and 15
may possess an unobserved family trait that makes them more
likely to work than other teens at later ages. Thus, the results
may bias the coefficient on holding a job of either type at
aged 14 and older.38

Groundwork for further study
Overall, this article has attempted to shed some light on
whether historical racial differences in both employee-type
and freelance jobholding were present for today’s teens and
to determine whether early differences affected later employment. Due to the ages of the respondents and the number of
rounds completed, these later outcomes were limited to teens
aged 16–19 with a stable geographic residence. Regardless,
the information presented here is important because racial

62

Monthly Labor Review

August 2001

gaps that are present for young workers seem to continue
into adulthood. Even more valuable would be a follow-up
study that considered similar questions after more rounds of
data are complete (for example, does early work experience
impact on labor market attachment when the respondent’s
formal education is finished?).
Keeping the strict sample selection criteria in mind, this
article has found that having previous work experience positively impacted on labor force attachment for different racial
groups for the NLSY97 cohort, as it did for the NLSY79 cohort.39 That is, nonmoving teens who held an employee-type
job at age 14 were more likely to work at an employee-type job
at age 16 and older than were their counterparts, regardless
of race or ethnicity. The effect of holding a freelance job was
not as clear. Black and Hispanic youths who worked for
themselves at an early age were more likely to work at an
employee-type job than were those who did not; however,
freelance jobholding had no effect for nonblack/non-Hispanic
youths.
It should be reiterated that these results may overstate the
effect of holding an early job because nonmovers have advantages in an area that movers may not have. For example,
nonmovers may be more familiar with the employers in the
area and have established job networks. More research is
needed on the effect of early jobholding for youths who move
between their 14th and 16th birthdays to determine the effects of early work experience when a youth must adjust to an
area.
Throughout this article, the employment of older teens
was considered to be a positive outcome, and to this end, the
results can be interpreted to offer some support for programs
that encourage early jobholding, preferably employee-type
jobs. Although additional analysis may be needed, these
findings suggest that a successful program would address
issues such as teen job opportunities and job search networks. These would include programs that provided information about labor market opportunities or that established job
networks to assist in job search. Some of these programs may
fit into the school-to-work transition, with internships or cooperative education providing experience—although more
research should be done on this topic before a positive recommendation is made. Other programs may be communitybased to target areas in which neighborhood characteristics
indicate a problem. Given the finding that parent’s work behavior is positively associated with the probability that the
respondent holds an employee-type job, these programs may
be extended to adult workers in certain communities.
Full support for these policy provisions would require
more analysis. In particular, using block-level neighborhood
effects rather than county-level effects would provide better
recommendations as teens are usually constrained geographi-

Table 5.

Probability of working at an employee-type job for nonmovers

Variable

Base
specifications

Hold
any job

Freelance/
employee-type
job holding

Held any job at age 14 ...............................................
....................................................................................
Held an employee job at age 14 .................................
....................................................................................
Held a freelance job at age 14 ...................................
....................................................................................

–
–
–
–
–
–

0.115
(.020)
–
–
–
–

–
–
.186
(.025)
.025
(.021)

Age ..............................................................................
....................................................................................
Black ...........................................................................
....................................................................................
Hispanic ......................................................................
....................................................................................
Female ........................................................................
....................................................................................
Enrolled in school .......................................................
....................................................................................
Highest grade completed ............................................
....................................................................................
Interviewed in summer ................................................
....................................................................................
Has a child ..................................................................
....................................................................................
Ever committed a crime ..............................................
....................................................................................
Ever been institutionalized for a crime ......................
....................................................................................
Has a sibling ...............................................................
....................................................................................
Siblings employed .......................................................
....................................................................................
Female head of household .........................................
....................................................................................
Parents employed .......................................................
....................................................................................

.105
(.014)
–.130
(.025)
–.077
(.028)
–.024
(.020)
.024
(.012)
.053
(.012)
.014
(.113)
.012
(.070)
.063
(.028)
–.016
(.052)
–.004
(.028)
.041
(.018)
.012
(.026)
.053
(.039)

.101
(.014)
–.117
(.026)
–.056
(.029)
–.029
(.021)
.021
(.011)
.050
(.012)
–.003
(.111)
.025
(.071)
.058
(.028)
–.022
(.052)
–.009
(.028)
.041
(.018)
.013
(.026)
.053
(.039)

.113
(.014)
–.124
(.026)
–.061
(.029)
–.013
(.021)
.022
(.012)
.047
(.012)
.026
(.114)
.025
(.071)
.055
(.028)
–.022
(.052)
–.006
(.028)
.038
(.018)
.011
(.026)
.054
(.039)

Northeast ....................................................................
....................................................................................
North-central ...............................................................
....................................................................................
South ...........................................................................
....................................................................................
Urban ...........................................................................
....................................................................................
Unemployment rate (Metropolitan Statistical Area) ...
....................................................................................
Percent in poverty (county) .......................................
....................................................................................
Mean travel time to work (county) .............................
....................................................................................

.006
(.033)
.010
(.033)
.093
(.032)
.018
(.021)
–.001
(.0004)
–.008
(.002)
–.007
(.002)

.008
(.033)
.102
(.032)
.094
(.032)
.019
(.021)
–.001
(.0004)
–.008
(.002)
–.006
(.002)

.003
(.033)
.097
(.033)
.010
(.032)
.018
(.021)
–.001
(.0004)
–.008
(.002)
–.006
(.002)

P-value, early employment (LR test) ..........................

–

–

.000

Number in sample .......................................................
Pseudo R2 ...................................................................

2,512
.115

2,512
.125

2,512
.133

NOTE: Standard errors are in parentheses. Partial derivatives of probability of outcome associated with dependent variables with respect to
independent variables.

Monthly Labor Review

August 2001

63

Racial Differences in Youth Employment

Table 6.

Probability of working at an employee-type job for nonmovers by racial group

Black
youths

Variable

Hispanic
youths

Nonblack/
non-Hispanic
youths

Held an employee job at age 14 .................................
....................................................................................
Held a freelance job at age 14 ...................................
....................................................................................

0.169
(.054)
.099
(.043)

0.244
(.067)
.107
(.053)

0.171
(.031)
–.018
(.028)

Age ..............................................................................
....................................................................................
Female ........................................................................
....................................................................................
Enrolled in school .......................................................
....................................................................................
Highest grade completed ............................................
....................................................................................
Interviewed in summer ................................................
....................................................................................
Has a child ..................................................................
....................................................................................
Ever committed a crime ..............................................
....................................................................................
Ever been institutionalized for a crime ......................
....................................................................................
Has a sibling ...............................................................
....................................................................................
Siblings employed .......................................................
....................................................................................
Female head of household .........................................
....................................................................................
Parents employed .......................................................
....................................................................................

.063
(.023)
–.007
(.038)
.045
(.031)
.054
(.020)
.104
(.316)
.008
(.084)
.004
(.052)
–0.100
(.069)
.021
(.045)
.046
(.030)
.031
(.038)
.061
(.049)

.113
(.031)
–.022
(.044)
–.010
(.023)
.050
(.026)
–
–
–.008
(.141)
.166
(.056)
.053
(.106)
–.014
(.074)
.049
(.034)
.016
(.054)
.075
(.066)

.136
(.020)
.0001
(.028)
.030
(.015)
0.028
(.017)
.138
(.146)
.148
(.132)
.087
(.038)
–.035
(.075)
–.016
(.038)
.015
(.026)
–.018
(.038)
–.022
(.072)

Northeast ....................................................................
....................................................................................
North-central ...............................................................
....................................................................................
South ...........................................................................
....................................................................................
Urban ...........................................................................
....................................................................................
Unemployment rate (Metropolitan Statistical Area) ...
....................................................................................
Percent in poverty (county) .......................................
....................................................................................
Mean travel time to work (county) .............................
....................................................................................

–.115
(.062)
.078
(.085)
.115
(.062)
.094
(.039)
–.001
(.001)
–.005
(.003)
.005
(.004)

–.071
(.065)
–.017
(.074)
.074
(.062)
.011
(.047)
–.001
(.001)
–.006
(.004)
–.001
(.005)

.044
(.046)
.133
(.043)
.112
(.046)
.015
(.028)
.0002
(.0007)
–.010
(.003)
–.008
(.003)

P-value, early employment (LR test) ..........................

.000

.000

.000

Number in sample .......................................................
Pseudo R2 ...................................................................

580
.150

478
.198

1,451
.101

NOTE: Standard errors are in parentheses. Partial derivatives of probability of outcome associated with dependent variables with respect to
independent variables.

64

Monthly Labor Review

August 2001

cally. This is especially true for younger workers who may
have trouble finding transportation outside their immediate
neighborhood. Additionally, further investigation of movers
may suggest that this group of teens would benefit more
than nonmovers from job networking programs geared toward the immediate neighborhood.
Beyond the scope of this article is the question of whether

jobholding among early teens provides valuable work experience that encourages later employment or whether it signals
characteristics that make the teen more likely to engage in
labor market activity in future years. It is also unclear whether
encouraging very early labor market attachment leads to more
successful adult outcomes as measured along other dimensions, such as wages or the provision of employee benefits. □

Notes
This article is based on a report prepared for the NLSY 97 Early
Results Conference at the Bureau of Labor Statistics and funded by the
Department of Labor. Points of view or opinions stated in this document are the author’s and do not necessarily represent the official
position or policy of the Department of Labor.
1
Robert J. Flanagan, “On the Stability of the Racial Unemployment Differential , ” American Economic Review, May 1976, 302-08.
2
See David T. Ellwood, “Teenage Unemployment: Permanent Scars
or Temporary Blemishes?” in Richard B. Freeman and David A. Wise,
eds., The Youth Labor Market Problem: Its Nature, Causes, and Consequences (Chicago, University of Chicago Press, 1982), 349–85;
Christopher J. Ruhn, “Is High School Employment Consumption or
Investment?” Journal of Labor Economics, October 1997, 735–76;
Robert H. Meyer and David A Wise, “High School Preparation and
Early Labor Force Experience,” in Richard B. Freeman and David A.
Wise, eds., The Youth Labor Market Problem: Its Nature, Causes, and
Consequences (Chicago, University of Chicago Press, 1982), 277339; and Brian E. Becker and Stephen Hills, “The Long-Run-Effects
of Job Changes and Unemployment among Male Teenagers,” Journal
of Human Resources, Summer 1983, 197–212.
3
BLS press release announcing the NLSY97 Round 1 data, "Employment experience and other characteristics of youths: results from a
new longitudinal survey, USDL 99-110, Apr. 30, 1999.
4

Using the NLSY97 sample as defined in section two, 15 percent of
male 17-year-olds and 23 percent of female 17-year-olds report holding a freelance job in the month prior to the survey.
5
According to figures from the October 1999 CPS , the employment-to-population rate for white teens aged 16 to 19 was 47.7; for
black teens ages 16 to 19, the corresponding rate was 25.4.
6
Robert T. Michael and Nancy Brandon Tuma, “Youth Employment: Does Life Begin at 16?” Journal of Labor Economics, April
1984, 464–76. According to current Child Labor Laws, teens aged 14
and 15 may work outside school hours in various nonmanufacturing,
nonmining, and nonhazardous jobs. The job may include no more
than 18 hours per week during the school year and 40 hours per week
during vacation periods. An exception to this rule is when these teens
are enrolled in an approved Work Experience and Career Exploration
Program (WECEP ); in this case, they may be employed for up to 23
hours during a school week.
7
For an overview of this literature, see Albert Rees, “An Essay on
Youth Joblessness,” Journal of Economic Literature, June 1986, 613–29.
8
See Gary Becker, “Crime and Punishment: An Economic Approach,” Journal of Political Economy March-April 1968, 169-217.
9
. Richard B. Freeman, “The Relation of Criminal Activity to
Black Youth Employment,” Review of Black Political Economy, Summer-Fall 1987, 99–108.

10
John Bound and Richard B. Freeman, “What Went Wrong? The
Erosion of Relative Earnings and Employment Among Young Black
Men in the 1980s,” The Quarterly Journal of Economics, February
1992, 201-32; Jeff Grogger, “Arrests, Persistent Youth Joblessness,
and Black/White Employment Differentials,” Review of Economics
and Statistics, February 1992, 100–06.
11
Richard B. Freeman, “Who Escapes? The Relation of ChurchGoing and Other Background Factors to the Socio-Economic Performance of Black Male Youths from Inner-City Poverty Tracts,” NBER
Working Paper No. 1656, June 1985.
12
Mary Corcoran, Richard Gordon, Deborah Laren and Gary Solon, “The Association between Men’s Economic Status and Their
Family and Community Origins,” Journal of Human Resources, Fall
1992, 575–601.
13
Albert Rees and Wayne Gray, “Family Effects in Youth Employment,” in Richard B. Freeman and David A. Wise, eds., The Youth
Labor Market Problem: Its Nature, Causes, and Consequences (Chicago, University of Chicago Press, 1982), 453–64.
14
Bruce A. Weinberg, Patricia B. Reagan, and Jeffrey J. Yankow,
“Do Neighborhoods Matter? Evidence from the NLSY79.” Unpublished
paper, 1999.
15

Bound and Freeman, “What Went Wrong…,” 201–32.

16

Richard B. Freeman, “Economic Determinants of Geographic
and Individual Variation,” in Richard B. Freeman and David A. Wise,
eds., The Youth Labor Market Problem: Its Nature, Causes, and Consequences (Chicago, University of Chicago Press, 1982), 115–48.
17
Freeman points out that these factors should be used to determine the employment rate of young workers—and not to distinguish
between the states of unemployed and out of the labor force—since
his findings indicate that factors that affect employment also affect
labor force participation.
18
Katherine M. O’Regan and John M. Quigley, “Teenage Employment and the Spatial Isolation of Minority and Poverty Households,”
Journal of Human Resources, Summer 1996, 692-702.
19

Weinberg, et. al., “Do Neighborhoods Matter?…,” 1999.

20

John F. Kain, “Housing Segregation, Negro Employment, and
Metropolitan Decentralization.” The Quarterly Journal of Economics, May 1968, 175–97. Some disagreement exists over the extent to
which the data support the spatial mismatch theory. For a review of
this literature, see Harry J. Holzer, “The Spatial Mismatch Hypothesis: What Has the Evidence Shown?” Urban Studies, February 1991,
105–22 and John F. Kain, “The Spatial Mismatch Hypothesis: Three
Decades Later,” Housing Policy Debate, volume 3, issue 2, 1992,
371-462.
21
Richard Arnott, “Economic Theory and the Spatial Mismatch
Hypothesis.” Unpublished paper, 1997.

Monthly Labor Review

August 2001

65

Racial Differences in Youth Employment

22
Harry Holzer, “Informal Job Search and Black Youth Unemployment.” American Economic Review, June 1987, 446–52.

residents or more. Youths in urbanized areas with less than 2,500
youths are defined as “rural.”

23
See Keith R. Ihlanfeldt and David L. Sjoquist, “Job Accessibility
and Racial Differences in Youth Employment Rates,” American Economic Review, March 1990, 267–76; and Katherine O’Regan,
Katherine and John M. Quigley, “Spatial Effects upon Employment
Outcomes: The Case of New Jersey Teenagers.” Unpublished paper,
1998.

32
County and City Data Book: 1994 (U.S. Department of Commerce, Bureau of the Census, 1995).

24
Harry J. Holzer, Keith R. Ihlanfeldt, and David L. Sjoquist, “Work,
Search, and Travel among White and Black Youth,” Journal of Urban
Economics May 1994, 110–30.
25
The NLSY97 sampling frame focused on youths who were 12 to 16
years old on December 31, 1996; round 1 interviews were conducted
from January to October 1997 and from March to May 1998. For
more information, see the NLSY97 User’s Guide (Columbus, OH, Center for Human Resource Research, Ohio State University, 2001).
26
The round 1 data are from an internal version of the NLSY 97
Public Use & Event History Data (Release 1.1); the round 2 variables
are from an internal version of the round 2 data from September
1999. Survey staff may edit these data as additional information becomes available.
27
Hispanic was not a choice in the race question; some screener
respondents reported that the household members did not fit into
standard racial categories and specified “Hispanic” in answer to the
race question.
28
For each NLSY97 question, a value of 1 was assigned if the youth
reported 75 percent or more of his or her peers engaged in that
activity; otherwise, the variable was coded as a zero. When more than
1 activity is combined to form a dummy variable, the youth must have
answered 75 percent to at least 1 of the NLSY97 questions for the value
to equal one; otherwise the variable was coded as a zero.
29

Freeman, “Who Escapes?…,” NBER Working Paper 1656, June 1985.

30

Respondents living in the northeast are coded as 1 if they reside
in Connecticut, Maine, Massachusetts, New Hampshire, New Jersey,
New York, Pennsylvania, Rhode Island, or Vermont and zero otherwise. Respondents coded as living in the north central region included
those who lived in Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, and
Wisconsin. The states that comprised the southern region included
Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia,
Kentucky, Louisiana, Maryland, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, and West Virginia.
Residents of other states were coded as living in the West.
31

This variable defines urban as a place with a population of 2,500

33
Using monthly totals from the CPS and aggregating to an annual
figure, Diane Wescott (in “The youngest workers: 14- and 15-yearolds,” Monthly Labor Review, February 1981, 65-69) found lower
employment rates than did Michael and Tuma. She reports that nearly
21 percent of 14- and 15-year-olds worked in the late 1970s.
34
It should be noted that Michael and Tuma used the CPS section
from the NLSY79 to calculate their figures; this section asks about labor
force activity in the week prior to the survey, regardless of month.
The NLSY 97 numbers come from the YEMP section, in which all employee-type jobs and all freelance jobs are collected in a roster. The
percentages stated in this article refer to employee-type jobs that the
respondent reported working in the 4 weeks prior to the survey or to
freelance jobs that were current at the time of the survey. It should be
noted that respondents ages 12 and 13 are only able to report jobs in
the freelance section, regardless of the job type (for example,,
freelance or employee-type). Undercounting of employee-type jobs
at these ages is most likely minimal, as these youths are not legally
allowed to hold most employee-type jobs.
35
The 1979 field period for the NLSY79 was January 1979 to August
1979, with the majority of respondents interviewed during the school
year when jobholding would have been lower. The round 1 NLSY97 field
period began in January 1997 to October 1997 and March 1998 to
May 1998. Due the screen-and-go method used in the NLSY 97, more
respondents were interviewed during the summer months than in late
winter and spring. In addition, the NLSY79 did not distinguish between
freelance jobs and employee-type jobs, whereas the NLSY97 prompted
respondents to report each type of job separately. As a result, it is not
possible to determine the extent to which the NLSY 97 may collect
information on more jobs due to survey design rather than actual
increases in jobholding.
36
Tables 5–9 contain probit estimates. The partial derivatives of
probability of outcome associated with dependent variable with respect to independent variables, and standard errors of these estimated
derivatives, are reported.
37

Freeman, “Who Escapes?…,” NBER Working Paper 1656, June 1985.

38

A fixed effects model using NLSY97 sibling data may remove the
family-specific portion of the unobserved heterogeneity; however,
this cohort is not yet old enough to yield enough sibling pairs to do
this type of estimation.
39

Michael and Tuma, “Youth Employment…,” 464–76.

Appendix: Sample construction
This appendix explains the selection of respondents for consideration in this research. Due to the types of information
required for this study, some NLSY97 respondents had to be
excluded if given variables were unavailable. The criteria for
the two parts of the study are somewhat different; the restrictions for the examination of job holding at age 14 are described first and the restrictions for the examination of early
employment as an indicator of employment at age 16 are then
discussed.
The selection criteria for the sample one are as follows.
66

Monthly Labor Review

August 2001

Any member without a valid age, race, and ethnicity is deleted, leaving 8,960 respondents. Next, 359 youths without at
least one biological parent, adoptive parent, stepparent, or
foster parent listed on the household roster are deleted from
the sample. Other relatives listed on the household roster
may serve as a legal guardian (for example, grandparent, aunt,
uncle); however, it is unclear in the literature whether the
employment behavior of a legal guardian has a different impact on the youth than the employment behavior of a parent.
As a result, respondents living in this situation are dropped

from the sample. Nine respondents who have missing or incomplete freelance or employee-type job data are dropped
from the sample, leaving 8,592 eligible sample members. Finally, 81 observations with other missing values are dropped
from the sample. The final sample size from the round 1 data is
8,511 respondents; of these, 5,743 were age 14 or over at the
time of the survey and were eligible to report employee-type
jobs in the employment section (all respondents answered
questions about freelance jobs).
The article examines whether work experience at the age of
14 has an impact on employment probabilities for youth aged
16 and older. Answering this question requires information
on the youth’s residence both at age 14 and at the most recent interview date because the spatial mismatch literature
indicates that this may affect employment probability. Because most respondents had not reached age 16 at the time of
the round 1 interview, the study also uses data from round 2
to increase the sample size. (Residence data in the round 1
survey are fairly limited; parents report the number of residences in which the youth respondent has lived since age 12
but do not provide any information about the location of
these residences. Thus, youths who had moved cannot be
included in the sample. Including the round 2 data increases
the full sample size to 2,512; of these 581 respondents are
black, 478 are Hispanic, and 1,451 are nonblack/non-Hispanic.)
The restrictions imposed for sample two are presented in
table A-1. Construction of the sample for this section begins
with the 8,511 respondents eligible in sample one. There are
several additional requirements. First, all respondents must
be age 16 or older by their most recent interview date. This
decreases the sample to 4,930 respondents. Youths who lived
outside of the parental home in round 2 were dropped from
the sample, leaving a sample size of 4,628. As in the first
sample, those with missing data for jobs and other variables
were also deleted from sample two; 4,591 remained eligible.
Sample two further requires that the respondent must not
have moved during the period under consideration to ensure
that residence information is accurate. This requirement is
needed because the locations of residences prior to the initial
interview are not recorded and the round 2 geocode data
were not available when this research was conducted. Respondents remaining in the sample had to fulfill one of the
following restrictions.
1. The respondent was age 16 or older during round 1,
had not moved since the age of 12, and was not interviewed in round 2. All information is from the round 1
interview.
2. The respondent was age 15 or older during round 1,
had not moved since the age of 12, and did not move
between round 1 and round 2. All information, except

the since age 12 residence question, is from the round
2 interview. Round 2 location information is taken from
the interviewer locator questions at the end of the
survey, when respondents are asked to report
changes to their address. However, including only
those who report no changes understates the number of nonmovers since some respondents updated
incorrect round 1 address information but had not
moved. Regardless, this restriction is necessary (until the round 2 geocode data are available) to ensure
that all county-level information is correct.
3. The respondent was age 14 or younger during round
1 and did not move between the round 1 and round 2
survey dates. All information is from the round 2 interview. As in the second restriction above, the location information is taken from the locator questions
at the end of the survey and may understate the number of nonmovers.
This information about the construction of the sample is summarized in table A-1.
Table A-1.

NLSY97

sample construction

Sample
modification

Total sample
remaining

Sample one
Full round 1 sample ..........................................................

8,984

Delete observations with age, race,
or ethnicity missing .......................................................
Delete observations without parent listed
on the household roster ................................................

8,601

Delete observations with employment data missing .........

8,592

Delete observations with other data missing ....................

8,511

8,960

Sample two
Delete observations less than 16 years of age
by latest interview date .................................................

4,930

Delete observations without parent listed
on household roster ......................................................

4,628

Delete observations with employment data missing .........

4,591

Delete observations with other data missing ....................

4,569

Delete observations with missing residence data ............

2,512

N OTE: Residence data in the round 1 survey are fairly limited;
parents report the number of residences in which the youth has lived
since age 12, but do not provide any information about the location of
these residences. Thus, youths who had moved cannot be included in
the sample. Including the round 2 data increases the full sample size
to 2,512; of these, 581 respondents are black, 478 are Hispanic, and
1,451 are nonblack/non-Hispanic.

Monthly Labor Review

August 2001

67

Current Labor Statistics
Monthly Labor Review
August 2001

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

LLabor
abor Statistics
Statistics
Current
Current Labor

Notes on labor statistics

.............................. 74

Comparative indicators
1. Labor market indicators .................................................... 84
2. Annual and quarterly percent changes in
compensation, prices, and productivity ....................... 85
3. Alternative measures of wages and
compensation changes ................................................... 85

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 States,
seasonally adjusted .......................................................
11. Employment of workers by States,
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. Annual data: Employment status of the population ........
19. Annual data: Employment levels by industry ..................
20. Annual data: Average hours
and earnings levels by industry .....................................

86
87
88
89
89
90
91
91

26. Participants in benefits plans, small firms
and government ............................................................. 95
27. Work stoppages involving 1,000 workers or more ........... 96

Price data
28. Consumer Price Index: U.S. city average, by expenditure
category and commodity and service groups ................
29. Consumer Price Index: U.S. city average and
local data, all items ........................................................
30. Annual data: Consumer Price Index, all items
and major groups ...........................................................
31. Producer Price Indexes by stage of processing .................
32. Producer Price Indexes for the net output of major
industry groups .............................................................
33. Annual data: Producer Price Indexes
by stage of processing ...................................................
34. U.S. export price indexes by Standard International
Trade Classification ......................................................
35. U.S. import price indexes by Standard International
Trade Classification ......................................................
36. U.S. export price indexes by end-use category .................
37. U.S. import price indexes by end-use category ................
38. U.S.international price indexes for selected
categories of services .....................................................

109
112
113
114
115
116
117
118
119
120
120

92
94
95
96
97
98
99
99
100

Productivity data
39. Indexes of productivity, hourly compensation,
and unit costs, data seasonally adjusted .......................
40. Annual indexes of multifactor productivity ......................
41. Annual indexes of productivity, hourly compensation,
unit costs, and prices ....................................................
42. Annual indexes of output per hour for selected
industries .......................................................................

121
122
123
124

International comparisons data

101

43. Unemployment rates in nine countries,
data seasonally adjusted ................................................ 127
44. Annual data: Employment status of the civilian
working-age population, 10 countries ........................... 128
45. Annual indexes of productivity and related measures,
12 countries ................................................................... 129

103

Injury and illness data

104

46. Annual data: Occupational injury and illness
incidence rates ............................................................... 130
47. Fatal occupational injuries by event or
exposure ........................................................................ 132

Labor compensation and collective
bargaining data
21. Employment Cost Index, compensation,
by occupation and industry group ................................
22. Employment Cost Index, wages and salaries,
by occupation and industry group ................................
23. Employment Cost Index, benefits, private industry
workers, by occupation and industry group .................
24. Employment Cost Index, private nonfarm workers,
by bargaining status, region, and area size ....................
25. Participants in benefit plans, medium and large firms ......

Labor compensation and collective
bargaining data—continued

105
106

Monthly Labor Review

August 2001

73

Current Labor
Statistics
Notes
on
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
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 past experience.
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, 16–17, 39, and 43. Seasonally adjusted
labor force data in tables 1 and 4–9 were revised in the February 2001 issue of the Review. Seasonally adjusted establishment survey data shown in tables 1, 12–14 and 16–
17 were revised in the July 2000 Review and
reflect the experience through March 2000.
A brief explanation of the seasonal adjustment methodology appears in “Notes on the
data.”
Revisions in the productivity data in table
45 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
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
74

Monthly Labor Review

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 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:
http://stats.bls.gov/cpshome.htm
Historically comparable unadjusted and seasonally adjusted data from the establishment
survey also are available on the Internet:
http://stats.bls.gov/ceshome.htm
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:
http://stats.bls.gov/iprhome.htm
For additional information on interna-

August 2001

tional comparisons data, see International
Comparisons of Unemployment, BLS 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. = not elsewhere classified.
n.e.s. = not elsewhere specified.
p = preliminary. To increase the timeliness of some series, preliminary
figures are issued based on representative but incomplete returns.
r = 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-to-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 pr
oductivity are presented in table 2.
productivity

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 measur
es of wage and commeasures
pensation rates of change
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.

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.

Employment and
Unemployment Data

ceding 4 weeks. Persons who did not look
for work because they were on layoff are
also counted among the unemployed. The
unemployment rate represents the number unemployed as a percent of the civilian
labor force.
ce consists of all
The civilian labor for
force
employed or unemployed persons in the
civilian noninstitutional population. Persons
not in the labor for
ce are those not classified
force
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 for
ce par
ticipation rate is the
force
participation
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; 4–20)

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.
Labor force data in tables 1 and 4–9 are
seasonally adjusted. Since January 1980,
national labor force data have been seasonally adjusted with a procedure called X-11
ARIMA which was developed at Statistics
Canada as an extension of the standard X11 method previously used by BLS. A detailed description of the procedure appears
in the X-11 ARIMA Seasonal Adjustment
Method, by Estela Bee Dagum (Statistics
Canada, Catalogue No. 12-564E, January
1983).
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 seasonally adjusted data usually are revised for
only the most recent 5 years. In July, new
seasonal adjustment factors, which incorporate the experience through June, are produced for the July–December period, but no

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 50,000 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 pre-

revisions are made in the historical data.
FOR 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 300,000
establishments representing all industries
except agriculture. Industries are classified
in accordance with the 1987 Standard Industrial Classification (SIC) Manual. 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 manufacturing
include working supervisors and nonsupervisory workers closely associated with production operations. Those workers mentioned in tables 11–16 include production
workers in manufacturing and mining; construction workers in construction; and
nonsupervisory workers in the following industries: transportation and public utilities;
wholesale and retail trade; finance, insurance, and real estate; and services. These
groups 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

Monthly Labor Review

August 2001

75

Current Labor Statistics

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 6-month
spans are seasonally adjusted, while those
for the 12-month span are unadjusted. Data
are centered within the span. Table 17 provides an index on private nonfarm employment based on 356 industries, and a manufacturing index based on 139 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 latest adjustment, which incorporated March 1999
benchmarks, was made with the release of
May 2000 data, published in the July 2000
issue of the Review. Coincident with the
benchmark adjustment, historical seasonally
adjusted data were revised to reflect updated
seasonal factors. Unadjusted data from April
1999 forward and seasonally adjusted data
from January 1996 forward are subject to
revision in future benchmarks.
In addition to the routine benchmark revisions and updated seasonal factors introduced
with the release of the May 2000 data, all estimates for the wholesale trade division from
April 1998 forward were revised to incorporate a new sample design. This represented the
first major industry division to convert to a
probability-based sample under a 4-year
phase-in plan for the establishment survey
sample redesign project. For additional information, see the the June 2000 issue of Employment and Earnings.
Revisions in State data (table 11) occurred with the publication of January 2000
data.
Beginning in June 1996, the BLS uses the
X-12 ARIMA methodology to seasonally ad76

Monthly Labor Review

just 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. Thus, fourth-quarter data are
published as preliminary in January and
February and as final in March.
FOR ADDITIONAL INFORMATION on establishment survey data, contact the Division
of Monthly Industry 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

August 2001

(202) 691–6559 (table 11).

Compensation and
Wage Data
(Tables 1–3; 21–27)
COMPENSATION AND WAGE DATA are gathered
by the Bureau from business establishments,
State and local governments, labor unions,
collective bargaining agreements on file with
the Bureau, and secondary sources.

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 uses a fixed market
basket of labor—similar in concept to the
Consumer Price Index’s fixed market basket
of goods and services—to measure change
over time in employer costs of employing
labor.
Statistical series on total compensation
costs, on wages and salaries, and on benefit
costs are available for private nonfarm workers excluding proprietors, the self-employed,
and household workers. The total compensation costs and wages and salaries series are
also available for State and local government
workers and for the civilian nonfarm economy,
which consists of private industry and State
and local government workers combined. Federal workers are excluded.
The Employment Cost Index probability
sample consists of about 4,400 private nonfarm establishments providing about 23,000
occupational observations and 1,000 State
and local government establishments providing 6,000 occupational observations selected
to represent total employment in each sector.
On average, each reporting unit provides
wage and compensation information on five
well-specified occupations. Data are collected each quarter for the pay period including the 12th day of March, June, September,
and December.
Beginning with June 1986 data, fixed
employment weights from the 1980 Census
of Population are used each quarter to
calculate the civilian and private indexes
and the index for State and local governments. (Prior to June 1986, the employment
weights are from the 1970 Census of Population.) These fixed weights, also used to
derive all of the industry and occupation
series indexes, 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 bargaining
status, region, and metropolitan/non-metropolitan area series, however, employment
data by industry and occupation are not
available from the census. Instead, the 1980
employment weights are reallocated within
these series each quarter based on the current sample. Therefore, these indexes are not
strictly comparable to those for the aggregate, industry, and occupation 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 payment-inkind, free room and board, and tips.

Notes on the data
The Employment Cost Index for changes in
wages and salaries in the private nonfarm
economy was published beginning in 1975.
Changes in total compensation cost—wages
and salaries and benefits combined—were
published beginning in 1980. The series of
changes in wages and salaries and for total
compensation in the State and local government sector and in the civilian nonfarm
economy (excluding Federal employees)
were published beginning in 1981. Historical indexes (June 1981=100) are available on
the Internet:
http://stats.bls.gov/ecthome.htm
F OR ADDITIONAL INFORMATION on the
Employment Cost Index, contact the Office
of Compensation Levels and Trends: (202)
691–6199.

Employee Benefits Survey
Description of the series
Employee benefits data are obtained from
the Employee Benefits Survey, an annual
survey of the incidence and provisions of
selected benefits provided by employers.
The survey collects data from a sample of
approximately 9,000 private sector and
State and local government establishments.
The data are presented as a percentage of employees who participate in a certain benefit, or

as an average benefit provision (for example,
the average number of paid holidays provided
to employees per year). Selected data from the
survey are presented in table 25 for medium
and large private establishments and in table
26 for small private establishments and State
and local government.
The survey covers paid leave benefits
such as holidays and vacations, and personal,
funeral, jury duty, military, family, and sick
leave; short-term disability, long-term disability, and life insurance; medical, dental,
and vision care plans; defined benefit and
defined contribution plans; flexible benefits
plans; reimbursement accounts; and unpaid
family leave.
Also, data are tabulated on the incidence of several other benefits, such as
severance pay, child-care assistance, wellness programs, and employee assistance
programs.

Definitions
Employer
-pr
ovided benefits are benefits
Employer-pr
-provided
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, longterm care insurance and postretirement life
insurance paid entirely by the employee are
included because the guarantee of insurability and availability at group premium rates
are considered a benefit.
Participants are workers who are covered
by a benefit, whether or not they use that benefit.
If the benefit plan is financed wholly by
employers and requires employees to complete
a minimum length of service for eligibility, the
workers are considered participants whether or
not they have met the requirement. If workers
are required to contribute towards the cost of
a plan, they are considered participants only
if they elect the plan and agree to make the
required contributions.
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-deferr
ed savings plans are a type of
ax-deferred
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
Surveys of employees in medium and large
establishments conducted over the 1979–86
period included establishments that
employed at least 50, 100, or 250 workers,
depending on the industry (most service
industries were excluded). The survey
conducted in 1987 covered only State and
local governments with 50 or more
employees. The surveys conducted in 1988
and 1989 included medium and large
establishments with 100 workers or more in
private industries. All surveys conducted over
the 1979–89 period excluded establishments
in Alaska and Hawaii, as well as part-time
employees.
Beginning in 1990, surveys of State and
local governments and small private
establishments were conducted in evennumbered years, and surveys of medium and
large establishments were conducted in oddnumbered years. The small establishment
survey includes all private nonfarm
establishments with fewer than 100 workers,
while the State and local government survey
includes all governments, regardless of the
number of workers. All three surveys include
full- and part-time workers, and workers in all
50 States and the District of Columbia.
F OR ADDITIONAL INFORMATION on the
Employee Benefits Survey, contact the Office of Compensation Levels and Trends on
the Internet:
http://stats.bls.gov/ebshome.htm

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 27.
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
stoppages: The number of
strikes and lockouts involving 1,000 workers or more and lasting a full shift or longer.
Workers involved
involved: The number of

Monthly Labor Review

August 2001

77

Current Labor Statistics

workers directly involved in the stoppage.
Number of days idle
idle: The aggregate
number of workdays lost by workers involved in the stoppages.
Days of idleness as a percent of estimated
working time
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.
FOR ADDITIONAL INFORMATION on work
stoppages data, contact the Office of Compensation and Working Conditions: (202)
691–6282, or the Internet:
http://stats.bls.gov/cbahome.htm

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 29. 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.

Price Data

Notes on the data

(Tables 2; 28–38)

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 home-ownership so that the index would reflect only the
cost of shelter services provided by owneroccupied homes. An updated CPI-U and CPIW were introduced with release of the January 1987 and January 1998 data.
F OR ADDITIONAL INFORMATION on consumer prices, contact the Division of Consumer Prices and Price Indexes: (202)
691–7000.

P RICE 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—1982 = 100 for many Producer Price
Indexes, 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 (CPIW) 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 selfemployed, short-term workers, the unemployed, retirees, and others not in the labor
force.
78

Monthly Labor Review

Producer Price Indexes
Description of the series
Pr
oducer Price Indexes (PPI) measure avProducer
erage 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 stageof-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

August 2001

accordance with the Standard Industrial Classification (SIC) and the product code extension of the SIC developed by the U.S. Bureau of the Census.
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.
F OR ADDITIONAL INFORMATION on producer prices, contact the Division of Industrial Prices and Price Indexes: (202)
691–7705.

International Price Indexes
Description of the series
ogram produces
The International Price Pr
Program
monthly and quarterly export and import
price indexes for nonmilitary goods 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,
allowances, and rebates applicable to the reported prices, so that the price used in the
calculation of the indexes is the actual price for
which the product was bought or sold.
In addition to general indexes of prices
for U.S. exports and imports, indexes are also
published for detailed product categories of
exports and imports. These categories are
defined according to the five-digit level of
detail for the Bureau of Economic Analysis
End-use Classification (SITC), and the fourdigit 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. Price
relatives are assigned equal importance
within each harmonized group and are then
aggregated to the higher level. The values assigned to each weight category are based on
trade value figures compiled by the Bureau
of the Census. The trade weights currently
used to compute both indexes relate to 1995.
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 the export price indexes, the preferred
pricing is f.a.s. (free alongside ship) U.S. port
of exportation. When firms report export
prices f.o.b. (free on board), production point
information is collected which enables the
Bureau to calculate a shipment cost to the port
of exportation. An attempt is made to collect
two prices for imports. The first is the import
price f.o.b. at the foreign port of exportation,
which is consistent with the basis for valuation of imports in the national accounts. The
second is the import price c.i.f.(costs, insurance, and freight) at the U.S. port of importation, which also includes the other costs as-

sociated with bringing the product to the U.S.
border. It does not, however, include duty
charges. For a given product, only one price
basis series is used in the construction of an
index.
FOR ADDITIONAL INFORMATION on international prices, contact the Division of International Prices: (202) 691–7155.

Productivity Data
(Tables 2; 39–42)

Business sector 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 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
oductivity is the quaninput. Multifactor pr
productivity
tity 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, non-energy 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 currentdollar value of output and dividing by output.
Unit nonlabor costs contain all the
components of unit nonlabor payments except unit profits.
Unit pr
ofits include corporate profits
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 iinputs
nputs 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 39–42 describe the relation-

Monthly Labor Review

August 2001

79

Current Labor Statistics

ship 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 data
supplement the measures for the business
economy and major sectors with annual
measures of labor productivity for selected
industries at the three- and four-digit levels
of the Standard Industrial Classification
system. In addition to labor productivity,
the industry data also include annual
measures of compensation and unit labor
costs for three-digit industries and measures
of multifactor productivity for three-digit
manufacturing industries and railroad
transportation. 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 consist of the hours
of all employees (production workers and nonproduction workers), the hours of all persons
(paid employees, partners, proprietors, and
unpaid family workers), or the number of employees, depending upon the industry.
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 out-

80

Monthly Labor Review

put. 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 the combined inputs consumed in
producing that output. Combined inputs
include capital, labor, and intermediate purchases. The measure of capital input used
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 Bureau of the Census,with additional data supplied by other government
agencies, trade associations, and other
sources.
For most industries, the productivity
indexes refer to the output per hour of all
employees. For some trade and services industries, indexes of output per hour of all
persons (including self-employed) are constructed. For some transportation industries, only indexes of output per employee
are prepared.
FOR ADDITIONAL INFORMATION on this series, contact the Division of Industry Productivity Studies: (202) 691–5618.

International Comparisons
(Tables 43–45)

Labor force and
unemployment
Description of the series
Tables 43 and 44 present comparative measures of the labor force, employment, and unemployment—approximating U.S. concepts—for the United States, Canada, Australia, Japan, and several European countries.
The unemployment statistics (and, to a lesser
extent, employment statistics) published by
other industrial countries are not, in most
cases, comparable to U.S. unemployment
statistics. Therefore, the Bureau adjusts the
figures for selected countries, where necessary, for all known major definitional differences. Although precise comparability may
not be achieved, these adjusted figures provide a better basis for international compari-

August 2001

sons 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.

Definitions
For the principal U.S. definitions of the labor
force, employment
employment, and unemployment
unemployment, see
force
the Notes section on Employment and Unemployment Data: Household survey data.

Notes on the data
The adjusted statistics have been adapted to
the age at which compulsory schooling ends
in each country, rather than to the U.S. standard of 16 years of age and older. Therefore,
the adjusted statistics relate to the population aged 16 and older in France, Sweden,
and the United Kingdom; 15 and older in
Australia, Japan, Germany, Italy from 1993
onward, and the Netherlands; and 14 and older
in Italy prior to 1993. An exception to this
rule is that the Canadian statistics for 1976
onward are adjusted to cover ages 16 and
older, whereas the age at which compulsory
schooling ends remains at 15. The institutional population is included in the denominator of the labor force participation rates
and employment-population ratios for Japan
and Germany; it is excluded for the United
States and the other countries.
In the U.S. labor force survey, persons on
layoff who are awaiting recall to their jobs
are classified as unemployed. European and
Japanese layoff practices are quite different
in nature from those in the United States;
therefore, strict application of the U.S. definition has not been made on this point. For
further information, see Monthly Labor Review, December 1981, pp. 8–11.
The figures for one or more recent years
for France, Germany, Italy, the Netherlands,
and the United Kingdom are calculated using
adjustment factors based on labor force surveys for earlier years and are considered preliminary. The recent-year measures for these
countries, therefore, are subject to revision
whenever data from more current labor force
surveys become available.
There are breaks in the data series for the
United States (1990, 1994, 1997, 1998, 1999,
2000), Canada (1976) France (1992), Germany (1991), Italy (1991, 1993), the Netherlands (1988), and Sweden (1987).
For the United States, the break in series
reflects a major redesign of the labor force
survey questionnaire and collection methodology introduced in January 1994. Revised
population estimates based on the 1990 census, adjusted for the estimated undercount,
also were incorporated. In 1996, previously

published data for the 1990–93 period were
revised to reflect the 1990 census-based
population controls, adjusted for the undercount. In 1997, revised population controls were introduced into the household survey. Therefore, the data are not strictly
conparable with prior years. In 1998, new
composite estimation procedures and minor
revisions in population controls were introduced into the household survey. Therefore,
the data are not strictly comparable with data
for 1997 and earlier years. See the Notes section on Employment and Unemployment
Data of this Review.
BLS recently introduced a new adjusted
series for Canada. Beginning with the data
for 1976, Canadian data are adjusted to more
closely approximate U.S. concepts. Adjustments are made to the unemployed and labor
force to exclude: (1) 15-year-olds; (2) passive jobseekers (persons only reading newspaper ads as their method of job search); (3)
persons waiting to start a new job who did
not seek work in the past 4 weeks; and (4)
persons unavailable for work due to personal
or family responsibilities. An adjustment is
made to include full-tine students looking for
full-time work. The impact of the adjustments was to lower the annual average unemployment rate by 0.1–0.4 percentage point
in the 1980s and 0.4–1.0 percentage point in
the 1990s.
For France, the 1992 break reflects the
substitution of standardized European Union
Statistical Office (EUROSTAT) unemployment
statistics for the unemployment data estimated according to the International Labor
Office (ILO) definition and published in the
Organization for Economic Cooperation and
Development (OECD) annual yearbook and
quarterly update. This change was made because the EUROSTAT data are more up-to-date
than the OECD figures. Also, since 1992, the
EUROSTAT definitions are closer to the U.S.
definitions than they were in prior years. The
impact of this revision was to lower the unemployment rate by 0.1 percentage point in
1992 and 1993, by 0.4 percentage point in
1994, and 0.5 percentage point in 1995.
For Germany, the data for 1991 onward
refer to unified Germany. Data prior to 1991
relate to the former West Germany. The impact of including the former East Germany
was to increase the unemployment rate from
4.3 to 5.6 percent in 1991.
For Italy, the 1991 break reflects a revision in the method of weighting sample data.
The impact was to increase the unemployment rate by approximately 0.3 percentage
point, from 6.6 to 6.9 percent in 1991.
In October 1992, the survey methodology was revised and the definition of unemployment was changed to include only those
who were actively looking for a job within
the 30 days preceding the survey and who

were available for work. In addition, the
lower age limit for the labor force was raised
from 14 to 15 years. (Prior to these changes,
BLS adjusted Italy’s published unemployment rate downward by excluding from the
unemployed those persons who had not
actively sought work in the past 30 days.)
The break in the series also reflects the incorporation of the 1991 population census results. The impact of these changes was to
raise Italy’s adjusted unemployment rate by
approximately 1.2 percentage points, from
8.3 to 9.5 percent in fourth-quarter 1992.
These changes did not affect employment
significantly, except in 1993. Estimates by
the Italian Statistical Office indicate that employment declined by about 3 percent in
1993, rather than the nearly 4 percent indicated by the data shown in table 44. This
difference is attributable mainly to the incorporation of the 1991 population benchmarks
in the 1993 data. Data for earlier years have
not been adjusted to incorporate the 1991
census results.
For the Netherlands, a new survey questionnaire was introduced in 1992 that allowed
for a closer application of ILO guidelines.
EUROSTAT has revised the Dutch series back
to 1988 based on the 1992 changes. The 1988
revised unemployment rate is 7.6 percent;
the previous estimate for the same year was
9.3 percent.
There have been two breaks in series in
the Swedish labor force survey, in 1987 and
1993. Adjustments have been made for the
1993 break back to 1987. In 1987, a new
questionnaire was introduced. Questions regarding current availability were added and
the period of active workseeking was reduced from 60 days to 4 weeks. These
changes lowered Sweden’s 1987 unemployment rate by 0.4 percentage point, from 2.3
to 1.9 percent. In 1993, the measurement
period for the labor force survey was
changed to represent all 52 weeks of the year
rather than one week each month and a new
adjustment for population totals was introduced. The impact was to raise the unemployment rate by approximately 0.5 percentage point, from 7.6 to 8.1 percent. Statistics Sweden revised its labor force survey
data for 1987–92 to take into account the
break in 1993. The adjustment raised the
Swedish unemployment rate by 0.2 percentage point in 1987 and gradually rose to 0.5
percentage point in 1992.
Beginning with 1987, BLS has adjusted the
Swedish data to classify students who also
sought work as unemployed. The impact of
this change was to increase the adjusted unemployment rate by 0.1 percentage point in
1987 and by 1.8 percentage points in 1994,
when unemployment was higher. In 1998,
the adjusted unemployment rate had risen
from 6.5 to 8.4 percent due to the adjustment

to include students.
The net effect of the 1987 and 1993
changes and the BLS adjustment for students
seeking work lowered Sweden’s 1987 unemployment rate from 2.3 to 2.2 percent.
FOR ADDITIONAL INFORMATION on this series, contact the Division of Foreign Labor
Statistics: (202) 691–5654.

Manufacturing productivity
and labor costs
Description of the series
Table 45 presents comparative indexes of
manufacturing labor productivity (output per
hour), output, total hours, compensation per
hour, and unit labor costs for the United
States, Canada, Japan, and nine European
countries. These measures are trend comparisons—that is, series that measure changes
over time—rather than level comparisons.
There are greater technical problems in comparing the levels of manufacturing output
among countries.
BLS constructs the comparative indexes
from three basic aggregate measures—output,
total labor hours, and total compensation.
The hours and compensation measures refer
to all employed persons (wage and salary
earners plus self-employed persons and unpaid family workers) in the United States,
Canada, Japan, France, Germany, Norway,
and Sweden, and to all employees (wage and
salary earners) in the other countries.

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

Monthly Labor Review

August 2001

81

Current Labor Statistics

To preserve the comparability of the U.S.
measures with those for other economies, BLS
uses gross product originating in manufacturing for the United States for these comparative measures. The gross product originating series differs from the manufacturing
output series that BLS publishes in its news
releases on quarterly measures of U.S. productivity and costs (and that underlies the
measures that appear in tables 39 and 41 in
this section). The quarterly measures are on
a “sectoral output” basis, rather than a valueadded basis. Sectoral output is gross output
less intrasector transactions.
Total labor hours refers to hours worked
in all countries. The measures are developed
from statistics of manufacturing employment
and average hours. The series used for France
(from 1970 forward), Norway, and Sweden
are official series published with the national
accounts. Where official total hours series are
not available, the measures are developed by
BLS using employment figures published with
the national accounts, or other comprehensive employment series, and estimates of
annual hours worked. For Germany, BLS uses
estimates of average hours worked developed
by a research institute connected to the Ministry of Labor for use with the national accounts employment figures. For the other
countries, BLS constructs its own estimates
of average hours.
Denmark has not published estimates of
average hours for 1994–97; therefore, the BLS
measure of labor input for Denmark ends in
1993.
Total compensation (labor cost) 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. The measures are from the national accounts of each
country, except those for Belgium, which are
developed by BLS using statistics on employment, average hours, and hourly compensation. For Canada, France, and Sweden, compensation is increased to account for other significant taxes on payroll or employment. For
the United Kingdom, compensation is reduced
between 1967 and 1991 to account for employment-related subsidies. Self-employed
workers are included in the all-employed-persons measures by assuming that their hourly
compensation is equal to the average for wage
and salary employees.

Notes on the data
In general, the measures relate to total manufacturing as defined by the International Standard Industrial Classification. However, the
measures for France (for all years) and Italy
(beginning 1970) refer to mining and manufacturing less energy-related products, and
the measures for Denmark include mining

82

Monthly Labor Review

Survey of Occupational
Injuries and Illnesses

cludes 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.

Description of the series

Notes on the data

and exclude manufacturing handicrafts from
1960 to 1966.
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.
FOR ADDITIONAL INFORMATION on this series, contact the Division of Foreign Labor
Statistics: (202) 691–5654.

Occupational Injury
and Illness Data
(Tables 46–47)

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 in-

August 2001

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 fulltime 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:
http://www
.bls.gov/oshhome.htm
http://www.bls.gov/oshhome.htm

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 result-

ing 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 workrelated 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:
http:/
.bls.gov
http:///www
www.bls.gov
.bls.gov//oshhome.htm

Bureau of Labor Statistics Internet
The Bureau of Labor Statistics World Wide Web site on the Internet contains a range of
data on consumer and producer prices, employment and unemployment, occupational compensation, employee benefits, workplace injuries and illnesses, and productivity. The
homepage can be accessed using any Web browser:
http://stats.bls.gov
Also, some data can be accessed through anonymous FTP or Gopher at
stats.bls.gov

Monthly Labor Review

August 2001

83

Current Labor Statistics:

Comparative Indicators

1. Labor market indicators
Selected indicators

1999

1999

2000
II

2000

III

IV

I

II

2001
III

IV

I

II

Employment data
Employment status of the civilian noninstitutionalized
1

population (household survey):

Labor force participation rate........................................................
Employment-population ratio........................................................
Unemployment rate………………………………………………….…
Men………………………………………………..…….….…………
16 to 24 years...........................................................................
25 years and over.....................................................................
Women……………………………………………….….……………
16 to 24 years...........................................................................
25 years and over.....................................................................

67.1
64.3
4.2
4.1
10.3
3.0
4.3
9.5
3.3

67.2
64.5
4.0
3.9
9.7
2.8
4.1
8.9
3.2

67.1
64.2
4.3
4.2
10.5
3.0
4.4
9.2
3.5

67.1
64.2
4.2
4.1
10.1
3.0
4.3
9.6
3.3

67.1
64.3
4.1
4.0
10.3
2.9
4.2
9.4
3.1

67.4
64.6
4.1
3.9
9.7
2.8
4.2
9.5
3.2

67.3
64.6
4.0
3.9
9.8
2.8
4.1
9.0
3.2

67.0
64.3
4.0
3.9
9.8
2.8
4.2
8.6
3.3

67.1
64.4
4.0
4.0
9.6
2.9
4.0
8.6
3.0

67.2
64.4
4.2
4.3
10.6
3.1
4.2
8.6
3.3

66.9
63.9
4.5
4.6
11.2
3.4
4.3
9.2
3.4

1

Employment, nonfarm (payroll data), in thousands:

Total………………………..............................................................
Private sector..............................................................................
Goods-producing…………………...………………………………
Manufacturing………….………………..…………………………
Service-producing…………………………...………………………

128,916
108,709
25,507
18,552
103,409

131,759
111,079
25,709
18,469
106,050

128,430
108,319
25,454
18,543
102,976

129,073
108,874
25,459
18,516
103,614

129,783
109,507
25,524
18,482
104,259

130,984
110,456
25,704
18,504
105,280

131,854
110,917
25,711
18,510
106,143

131,927
111,293
25,732
18,487
106,195

132,264
111,669
25,704
18,378
106,560

132,559
111,886
25,621
18,188
106,938

132,485
111,708
25,314
17,885
107,171

Average hours:
Private sector........................................………….......................
Manufacturing………...……………………………………………
Overtime……..………….………………...………………………

34.5
41.7
4.6

34.5
41.6
4.6

34.5
41.7
4.6

34.5
41.8
4.6

34.5
41.7
4.7

34.5
41.8
4.7

34.5
41.8
4.7

34.4
41.5
4.5

34.3
41.1
4.3

34.3
41.0
4.1

34.2
40.8
3.9

3.4
3.4

4.1
4.4

1.0
1.1

1.1
.9

.9
.9

1.3
1.5

1.0
1.2

1.0
.9

.7
.7

1.3
1.4

.9
1.0

2

Employment Cost Index

Percent change in the ECI, compensation:
All workers (excluding farm, household and Federal workers)......
Private industry workers.............………......................................
3

Goods-producing ……………………………………………….…………

3.4

4.4

.7

.9

1.0

1.6

1.2

.9

.6

1.3

.9

Service-producing ……………………………………………….…………
State and local government workers.............………...................

3.4
3.4

4.4
3.0

1.3
.4

.9
1.5

.8
1.0

1.4
.6

1.2
.3

1.0
1.3

.7
.7

1.4
.9

1.0
.6

Workers by bargaining status (private industry):
Union……………………………………………………………………
Nonunion…………………………………………………………………

2.7
3.6

4.0
4.4

.7
1.2

.9
.9

.7
1.0

1.3
1.5

1.0
1.2

1.2
1.0

.5
.7

.7
1.5

1.1
1.0

3

1

Quarterly data seasonally adjusted.

2

Annual changes are December-to-December changes. Quarterly changes are calculated using the last month of each quarter.

3

Goods-producing industries include mining, construction, and manufacturing. Service-producing industries include all other private sector industries.

84

Monthly Labor Review

August 2001

2. Annual and quarterly percent changes in compensation, prices, and productivity
Selected measures

1999

1999

2000
II

Compensation data

2000

III

IV

I

II

2001
III

IV

I

II

1,2

Employment Cost Index—compensation (wages,
salaries, benefits):
Civilian nonfarm..................................................................
Private nonfarm..............................................................
Employment Cost Index—wages and salaries:
Civilian nonfarm……………………………………………….
Private nonfarm..............................................................
Price data

3.4
3.4

4.1
4.4

1.0
1.1

1.1
.9

0.9
.9

1.3
1.5

1.0
1.2

1.0
.9

0.7
.7

1.3
1.4

0.9
1.0

3.5
3.5

3.8
3.9

1.0
1.2

1.1
.9

.8
.9

1.1
1.2

1.0
1.0

1.1
1.0

.6
.6

1.1
1,2

.9
1.0

2.7

1.0

.7

1.0

.2

1.7

.7

.8

–.1

1.0

1.0

2.9
3.8
.3
3.7
15.3

1.0
1.0
1.0
1.0
1.2

1.2
1.8
–.4
1.9
9.4

1.5
2.2
–.4
1.9
10.2

.1
–.2
1.2
.1
–3.5

1.4
1.8
.1
1.9
9.1

1.3
1.8
.0
1.6
11.2

.6
.7
.0
1.0
.3

1.0
1.0
l.0
–.1
1.1

1.0
1.0
–.1
1.0
–.1

1.0
1.0
1.0
1.0
1.0

2.8
2.6

4.3
4.3

–1.1
–1.4

2.9
3.0

7.0
7.4

3.5

4.2

.4

2.8

4.5

–.6
–.6
4.0

7.3
6.3
7.1

1.0
1.4
4.0

3.0
2.3
1.6

.0
.1
.6

2.8
2.5
–

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....................................................................
Productivity data

3

Output per hour of all persons:
Business sector....................................................................
Nonfarm business sector......................................................
4

Nonfinancial corporations ……………….…………...………………
1

Annual changes are December-to-December changes. Quarterly changes are
calculated using the last month of each quarter. Compensation and price data are not
seasonally adjusted, and the price data are not compounded.
2

Excludes Federal and private household workers.

3

Annual rates of change are computed by comparing annual averages. Quarterly per-

cent changes reflect annual rates of change in quarterly indexes. The
data are seasonally adjusted.
4

Output per hour of all employees.

3. Alternative measures of wage and compensation changes
Quarterly average
Components

2000
I

II

Four quarters ending
2001

III

IV

I

2000
II

I

II

2001
III

IV

I

II

1

Average hourly compensation:
All persons, business sector.........................................................
All persons, nonfarm business sector...........................................

5.9
6.2

8.6
7.6

6.5
7.1

9.4
8.9

5.3
5.1

5.2
4.7

4.7
5.0

5.7
5.8

6.1
6.3

7.6
7.4

7.4
7.2

6.6
6.4

1.3
1.5
1.3
1.5
.6

1.0
1.2
1.0
1.2
.3

1.0
.9
1.2
1.0
1.3

.7
.7
.5
.7
.7

1.3
1.4
.7
1.5
.9

.9
1.0
1.1
1.0
.6

4.3
4.6
3.6
4.7
3.6

4.4
4.6
3.9
4.6
3.5

4.3
4.6
4.2
4.7
3.3

4.1
4.4
4.0
4.4
3.0

4.1
4.2
3.4
4.3
3.3

3.9
4.0
3.5
4.2
3.6

1.1
1.2
.5
1.3
.6

1.0
1.0
.9
1.1
.3

1.1
1.0
1.1
1.0
1.7

.6
.6
.9
.6
.7

1.1
1.2
.6
1.2
.7

.9
1.0
1.1
.9
.5

4.0
4.2
2.7
4.4
3.8

4.0
4.1
2.8
4.3
3.7

4.0
4.1
3.2
4.3
3.5

3.8
3.9
3.4
4.0
3.3

3.8
3.8
3.6
3.9
3.5

3.7
3.8
3.8
3.7
3.7

Employment Cost Index—compensation:
2

Civilian nonfarm ……….………………………………………….…………..…
Private nonfarm….......................................................................
Union…………..........................................................................
Nonunion…………....................................................................
State and local governments…...................................................
Employment Cost Index—wages and salaries:
2

Civilian nonfarm ……….………………………………………….…………..…
Private nonfarm….......................................................................
Union…………..........................................................................
Nonunion…………....................................................................
State and local governments…...................................................
1

Seasonally adjusted. "Quarterly average" is percent change from a quarter ago, at an annual rate.

2

Excludes Federal and household workers.

Monthly Labor Review

August 2001

85

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

Annual average
1999

2000

2001

2000

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

Jan.

Feb.

Mar.

Apr.

May

June

209,699
140,863
67.2
135,208

209,543
140,757
67.2
135,183

209,727
140,546
67.0
134,898

209,935
140,724
67.0
134,939

210,161
140,847
67.0
135,310

210,378
141,000
67.0
135,464

210,577
141,136
67.0
135,478

210,743
141,489
67.1
135,836

210,889
141,955
67.3
135,999

211,026
141,751
67.2
135,815

211,171
141,868
67.2
135,780

211,348
141,757
67.1
135,354

211,525
141,272
66.8
135,103

211,725
141,354
66.8
135,379

64.5
5,655
4.0
68,836

64.5
5,574
4.0
68,786

64.3
5,648
4.0
69,181

64.3
5,785
4.1
69,211

64.4
5,537
3.9
69,314

64.4
5,536
3.9
69,378

64.3
5,658
4.0
69,441

64.5
5,653
4.0
69,254

64.5
5,956
4.2
68,934

64.4
5,936
4.2
69,275

64.3
6,088
4.3
69,304

64.0
6,402
4.5
69,592

63.9
6,169
4.4
70,254

63.7
6,422
4.5
70,370

91,555
79,104
76.7
67,761

92,580
70,930
76.6
68,580

92,546
70,785
76.5
68,489

92,642
70,782
76.4
68,495

92,754
71,029
76.6
68,710

92,863
71,053
76.5
68,728

92,969
71,155
76.5
68,774

93,061
71,135
76.4
68,683

93,117
71,289
76.6
68,848

93,184
71,492
76.7
68,916

93,227
71,288
76.5
68,761

93,285
71,261
76.4
68,534

93,410
71,575
76.6
68,706

93,541
71,351
76.3
68,595

93,616
71,346
76.2
68,466

74.0
2,028

74.1
2,252

74.0
2,262

73.9
2,280

74.1
2,276

74.0
2,350

74.0
2,219

73.8
2,122

73.9
2,232

74.0
2,122

73.8
2,154

73.5
2,150

73.6
2,117

73.3
2,169

73.1
2,035

65,517
2,433
3.5

66,328
2,350
3.3

66,227
2,296
3.2

66,215
2,287
3.2

66,434
2,319
3.3

66,378
2,325
3.3

66,555
2,381
3.3

66,561
2,452
3.4

66,616
2,441
3.4

66,795
2,576
3.6

66,607
2,527
3.5

66,383
2,728
3.8

66,589
2,869
4.0

66,426
2,756
3.9

66,430
2,880
4.0

1
population ……………………. 100,158
Civilian labor force.............. 60,840
Participation rate..........
60.7
Employed........................ 58,555
Employment-pop2
58.5
ulation ratio ……………
803
Agriculture...................
Nonagricultural
industries...........…… 57,752
2,285
Unemployed...................
3.8
Unemployment rate....

101,078
61,565
60.9
59,352

101,007
61,561
60.9
59,282

101,111
61,535
60.9
59,273

101,209
61,265
60.5
58,992

101,321
61,486
60.7
59,344

101,448
61,528
60.6
59,425

101,533
61,625
60.7
59,506

101,612
61,819
60.8
59,708

101,643
62,126
61.1
59,894

101,686
62,220
61.2
59,932

101,779
62,412
61.3
60,178

101,870
62,132
61.0
59,741

101,938
62,119
60.9
59,766

102,023
61,890
60.7
59,510

58.7
818

58.7
829

58.6
797

58.3
808

58.6
764

58.6
748

58.6
797

58.8
822

58.9
852

58.9
839

59.1
819

58.6
847

58.6
822

58.3
752

58,535
2,212
3.6

58,453
2,279
3.7

58,476
2,262
3.7

58,184
2,273
3.7

58,580
2,142
3.5

58,677
2,103
3.4

58,709
2,119
3.4

58,886
2,111
3.4

59,042
2,232
3.6

59,093
2,288
3.7

59,359
2,233
3.6

58,895
2,390
3.8

58,943
2,353
3.8

58,759
2,380
3.8

16,042
8,369
52.2
7,216

15,991
8,411
52.6
7,412

15,974
8,229
51.5
7,130

15,972
8,430
52.8
7,237

15,977
8,308
52.0
7,238

15,960
8,317
52.1
7,265

15,983
8,376
52.4
7,289

16,014
8,381
52.3
7,280

16,063
8,337
51.9
7,188

16,113
8,243
51.2
7,122

16,108
8,195
50.9
7,067

16,068
8,050
50.1
6,907

16,046
7,802
48.6
6,742

16,086
8,118
50.5
6,956

45.4
235

46.4
222

44.6
218

45.3
233

45.3
242

45.5
274

45.6
257

45.5
220

44.7
205

44.2
143

43.9
191

43.0
229

42.0
201

43.2
209

7,041
1,093
13.1

7,190
999
11.9

6,912
1,099
13.4

7,004
1,193
14.2

6,996
1,070
12.9

6,991
1,052
12.6

7,032
1,087
13.0

7,060
1,101
13.1

6,983
1,149
13.8

6,980
1,121
13.6

6,876
1,127
13.8

6,678
1,143
14.2

6,541
1,060
13.6

6,748
1,162
14.3

174,428
117,574
67.4
113,475

174,316
117,477
67.4
113,493

174,443
117,298
67.2
113,201

174,587
117,554
67.3
113,378

174,745
117,553
67.3
113,464

174,899
117,603
67.2
113,584

175,034
117,640
67.2
113,509

175,145
117,945
67.3
113,811

175,246
118,276
67.5
114,015

175,362
118,287
67.5
113,902

175,416
118,243
67.4
113,853

175,533
118,145
67.3
113,434

175,653
117,688
67.0
113,185

175,789
117,773
67.0
113,037

65.1
4,099
3.5

65.1
3,984
3.4

64.9
4,097
3.5

64.9
4,176
3.6

64.9
4,089
3.5

64.9
4,019
3.4

64.8
4,131
3.5

65.0
4,134
3.5

65.1
4,261
3.6

65.0
4,385
3.7

64.9
4,389
3.7

64.6
4,711
4.0

64.4
4,503
3.8

64.3
4,696
4.0

25,218
16,603
65.8
15,334

25,191
16,573
65.8
15,277

25,221
16,501
65.4
15,232

25,258
16,540
65.5
15,239

25,299
16,489
65.2
15,304

25,339
16,627
65.6
15,401

25,376
16,732
65.9
15,485

25,408
16,742
65.9
15,470

25,382
16,773
66.1
15,372

25,412
16,691
65.7
15,440

25,441
16,789
66.0
15,348

25,472
16,666
65.4
15,299

25,501
16,639
65.2
15,311

25,533
16,756
65.6
15,343

60.8
1,269
7.6

60.6
1,296
7.8

60.4
1,269
7.7

60.3
1,301
7.9

60.5
1,185
7.2

60.8
1,226
7.4

61.0
1,247
7.5

60.9
1,272
7.6

60.6
1,401
8.4

60.8
1,251
7.5

60.3
1,441
8.6

60.1
1,367
8.2

60.0
1,328
8.0

60.1
1,413
8.4

TOTAL
Civilian noninstitutional
1

population ……………………. 207,753
Civilian labor force.............. 139,368
Participation rate..........
67.1
Employed........................ 133,488
Employment-pop64.3
ulation ratio2……………
5,880
Unemployed...................
Unemployment rate....
4.2
Not in the labor force........ 68,385
Men, 20 years and over
Civilian noninstitutional
1

population …………………….
Civilian labor force..............
Participation rate..........
Employed........................
Employment-population ratio2……………
Agriculture...................
Nonagricultural
industries...........……
Unemployed...................
Unemployment rate....
Women, 20 years and over
Civilian noninstitutional

Both sexes, 16 to 19 years
Civilian noninstitutional
1
population ……………………. 16,040
Civilian labor force..............
8,333
52.0
Participation rate..........
Employed........................
7,172
Employment-pop2
44.7
ulation ratio ……………
Agriculture...................
234
Nonagricultural
industries...........……
6,938
1,162
Unemployed...................
Unemployment rate....
13.9

White
Civilian noninstitutional
1

population ……………………. 173,085
Civilian labor force.............. 116,509
67.3
Participation rate..........
Employed........................ 112,235
Employment-pop64.8
ulation ratio2……………
Unemployed...................
4,273
Unemployment rate....
3.7
Black
Civilian noninstitutional
1
population ……………………. 24,855
Civilian labor force.............. 16,365
Participation rate..........
65.8
Employed........................ 15,056
Employment-pop60.6
ulation ratio2……………
1,309
Unemployed...................
8.0
Unemployment rate....

See footnotes at end of table.

86

Monthly Labor Review

August 2001

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

Employment status

1999

2000

2001

2000

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

Jan.

Feb.

Mar.

Apr.

May

June

22,393
15,368
68.6
14,492

22,355
15,320
68.5
14,456

22,422
15,243
68.0
14,384

22,488
15,312
68.1
14,439

22,555
15,513
68.8
14,647

22,618
15,491
68.5
14,711

22,687
15,626
68.9
14,686

22,749
15,671
68.9
14,772

22,769
15,540
68.1
14,612

22,830
15,653
68.6
14,673

22,889
15,770
68.9
14,782

22,957
15,775
68.7
14,747

23,021
15,608
67.8
14,634

23,090
15,570
67.4
14,538

64.7
876
5.7

64.7
864
5.6

64.2
859
5.6

64.2
873
5.7

64.9
866
5.6

65.0
780
5.0

64.7
940
6.0

64.9
899
5.7

63.8
989
6.4

64.3
980
6.3

64.6
988
6.3

64.2
1,028
6.5

63.6
975
6.2

63.0
1,032
6.6

Hispanic origin
Civilian noninstitutional
1
population …………………….. 21,650
Civilian labor force.............. 14,665
Participation rate..........
67.7
Employed........................ 13,720
Employment-pop63.4
ulation ratio2……………
Unemployed...................
945
6.4
Unemployment rate....
1

The population figures are not seasonally adjusted.

2

Civilian employment as a percent of the civilian noninstitutional population.

NOTE: Detail for the above race and Hispanic-origin groups will not sum to totals
becausedata for the "other races" groups are not presented and Hispanics are included in
both the white and black population groups.

5. Selected employment indicators, monthly data seasonally adjusted
[In thousands]
Annual average

Selected categories

1999
Characteristic
Employed, 16 years and over... 133,488
Men...................................... 771,446
Women............................…… 62,042

2000

2001

2000

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

Jan.

Feb.

Mar.

Apr.

May

June

135,208
72,293
62,915

135,183
72,240
62,943

134,898
72,141
62,757

134,939
72,379
62,560

135,310
72,398
62,912

135,464
72,427
63,037

135,478
72,354
63,124

135,836
72,534
63,302

135,999
72,589
63,410

135,815
72,359
63,456

135,780
72,201
63,578

135,354
72,245
63,109

135,103
71,978
63,125

134,932
71,926
63,006

Married men, spouse
present...............................

43,254

43,368

43,364

43,308

43,375

43,321

43,345

43,251

43,293

43,134

43,340

43,385

43,516

43,733

43,428

Married women, spouse
present...............................

33,450

33,708

33,745

33,621

33,507

33,491

33,622

33,633

33,635

34,249

34,059

34,080

33,662

33,686

33,380

Women who maintain
families...............................

8,229

8,387

8,340

8,460

8,492

8,516

8,449

8,495

8,501

8,426

8,373

8,049

8,160

8,319

8,529

2,034
1,233
38

2,051
1,187
44

2,065
1,189
39

2,048
1,241
36

2,018
1,274
38

2,041
1,182
32

2,005
1,180
25

2,019
1,198
34

1,983
1,182
25

1,839
1,291
29

1,910
1,231
36

1,902
1,223
47

1,958
1,201
38

1,775
1,166
36

123,128
19,053
104,076
890
103,186
8,674
101

123,020
18,836
104,184
926
103,258
8,660
74

122,744
18,592
104,152
821
103,331
8,619
86

122,931
18,644
104,287
781
103,506
8,618
114

123,117
19,003
104,114
824
103,290
8,786
108

123,461
19,073
104,388
812
103,576
8,561
136

123,632
19,146
104,486
827
103,659
8,533
128

123,813
19,352
104,461
879
103,582
8,600
121

124,035
18,843
105,192
859
104,333
8,698
110

124,069
19,103
104,966
823
104,143
8,617
142

123,814
19,134
104,680
881
103,800
8,784
138

123,395
18,854
104,541
812
103,729
8,608
93

123,416
19,067
104,349
789
103,559
8,530
103

123,009
18,812
104,197
744
103,453
8,741
94

3,190

3,125

3,110

3,170

33,188

3,222

3,416

3,234

3,327

3,273

3,164

3,201

3,371

3,637

1,927

1,858

1,871

1,980

2,051

1,909

2,183

1,964

2,035

2,043

1,914

2,097

2,215

2,299

944

981

918

880

831

947

886

896

954

933

907

873

900

1,025

18,722

18,444

18,579

18,704

18,595

18,758

18,896

18,993

18,568

19,021

18,647

18,713

18,581

18,472

3,045

2,981

2,972

3,038

3,030

3,044

3,285

3,088

3,227

3,143

3,007

3,061

3,197

3,532

1,835

1,760

1,773

1,901

1,940

1,808

2,082

1,882

1,971

1,970

1,828

1,985

2,089

2,234

924

982

896

861

817

923

871

877

945

910

877

864

876

1,024

18,165

17,897

18,052

18,142

18,024

18,206

18,323

18,437

18,040

18,509

18,132

18,176

18,061

18,039

Class of worker
Agriculture:
Wage and salary workers...…
1,944
Self-employed workers.........
1,297
Unpaid family workers..........
40
Nonagricultural industries:
Wage and salary workers...… 121,323
Government.......................... 18,903
Private industries.................. 102,420
Private households.........
933
Other.............................. 101,487
Self-employed workers........
8,790
Unpaid family workers.........
95
1

Persons at work part time

All industries:
Part time for economic
reasons…………………….… 3,357
Slack work or business
conditions………….........
1,968
Could only find part-time
1,079
work………………………
Part time for noneconomic
reasons……………………… 18,758
Nonagricultural industries:
Part time for economic
reasons…………………….… 3,189
Slack work or business
conditions.......................
1,861
Could only find part-time
work………………………
1,056
Part time for noneconomic
reasons.................………… 18,197
1

Excludes persons "with a job but not at work" during the survey period for such reasons as vacation, illness, or industrial disputes.

Monthly Labor Review

August 2001

87

Current Labor Statistics:

Labor Force Data

6. Selected unemployment indicators, monthly data seasonally adjusted
[Unemployment rates]
2000

Annual average

Selected categories

1999

2000

2001

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

Jan.

Feb.

Mar.

Apr.

May

June

Characteristic
Total, 16 years and over............................
Both sexes, 16 to 19 years.....................
Men, 20 years and over.........................
Women, 20 years and over....................

4.2
13.9
3.5
3.8

4.0
13.1
3.3
3.6

4.0
11.9
3.2
3.7

4.0
13.4
3.2
3.7

4.1
14.2
3.3
3.7

3.9
12.9
3.3
3.5

3.9
12.6
3.3
3.4

4.0
13.0
3.4
3.4

4.0
13.1
3.4
3.4

4.2
13.8
3.6
3.6

4.2
13.6
3.5
3.7

4.3
13.8
3.8
3.6

4.5
14.2
4.0
3.8

4.4
13.6
3.9
3.8

4.5
14.3
4.0
3.8

White, total............................................
Both sexes, 16 to 19 years................
Men, 16 to 19 years.......................
Women, 16 to 19 years..................
Men, 20 years and over....................
Women, 20 years and over...............

3.7
12.0
12.6
11.3
3.0
3.3

3.5
11.4
12.3
10.4
2.8
3.1

3.4
9.9
11.7
7.9
2.8
3.2

3.5
11.5
12.5
10.4
2.8
3.2

3.6
12.0
13.1
10.8
2.8
3.3

3.5
11.4
12.2
10.6
2.9
3.1

3.4
11.2
11.8
10.5
2.9
3.0

11.5
11.7
12.4
10.9
3.0
3.0

3.5
11.5
12.2
10.7
2.9
3.1

3.6
11.7
13.3
9.8
3.2
3.0

3.7
10.9
12.6
9.2
3.2
3.3

3.7
11.6
11.8
11.2
3.3
3.1

4.0
11.8
12.8
10.8
3.5
3.5

3.8
11.8
13.1
10.5
3.3
3.4

4.0
12.6
14.5
10.6
3.6
3.3

Black, total.............................................
Both sexes, 16 to 19 years................
Men, 16 to 19 years.......................
Women, 16 to 19 years..................
Men, 20 years and over....................
Women, 20 years and over...............

8.0
27.9
30.9
25.1
6.7
6.8

7.6
24.7
26.4
23.0
7.0
6.3

7.8
25.6
31.5
19.3
6.9
6.5

7.7
26.4
25.7
27.1
6.8
6.3

7.9
26.8
31.7
22.3
7.2
6.2

7.2
24.1
26.7
21.7
6.5
5.8

7.4
23.9
27.0
21.2
7.0
5.8

7.5
21.9
22.5
21.3
6.9
6.2

7.6
26.7
30.1
23.4
7.3
5.7

8.4
27.9
26.9
28.9
6.9
7.3

7.5
28.8
31.7
25.7
6.6
5.8

8.6
28.9
27.7
30.2
8.5
6.3

8.2
31.6
34.9
28.6
8.2
5.5

8.0
25.1
30.0
20.3
7.6
6.4

8.4
28.2
30.7
26.0
7.8
6.8

Hispanic origin, total...........................

6.4

5.7

5.6

5.6

5.7

5.6

5.0

6.0

5.7

6.0

6.3

6.3

6.5

6.2

6.6

Married men, spouse present.............
Married women, spouse present.........
Women who maintain families.............
Full-time workers.................................
Part-time workers................................

2.2
2.7
6.4
4.1
5.0

2.0
2.7
5.9
3.9
4.8

1.9
2.6
6.0
3.8
4.9

2.0
2.7
7.7
3.8
5.1

2.0
2.8
6.0
3.9
5.0

2.1
2.7
5.4
3.8
4.6

2.1
2.5
5.4
3.8
4.5

2.2
2.5
5.2
3.9
4.5

2.2
2.6
5.1
3.9
4.6

2.3
2.5
6.4
4.1
4.9

2.3
2.6
6.1
4.0
4.8

2.5
2.7
6.2
4.2
4.8

2.5
2.9
6.3
4.3
5.5

2.6
2.9
6.2
4.3
4.6

2.6
3.0
6.3
4.4
5.3

4.3
5.7
7.0
3.6
3.5
3.9
3.0
5.2
2.3
4.1
2.2
8.9

4.1
3.9
6.4
3.6
3.4
4.0
3.1
5.0
2.3
3.8
2.1
7.5

4.0
3.9
6.0
3.4
3.4
3.2
2.9
5.1
2.3
3.8
2.5
7.2

4.1
4.5
6.0
3.6
3.3
4.0
3.1
5.0
2.2
3.9
2.1
7.2

4.1
4.3
6.4
3.5
3.1
4.1
3.1
5.1
2.4
3.8
2.3
8.0

4.0
5.0
6.4
3.6
3.2
4.3
3.2
4.8
2.1
3.7
2.1
7.9

4.0
7.1
6.5
4.0
3.8
4.3
2.8
4.8
2.3
3.6
2.0
8.8

4.0
3.5
6.9
3.6
3.5
3.9
2.6
4.7
1.9
3.7
2.3
9.4

4.0
3.6
6.5
3.6
3.4
4.0
3.2
4.8
2.1
3.6
2.2
8.9

4.3
2.2
6.8
4.2
4.2
4.3
2.8
5.0
2.3
4.0
2.2
9.0

4.5
4.6
7.0
4.5
4.2
5.0
2.9
5.1
2.5
4.2
1.5
9.2

4.5
3.5
6.2
5.0
5.0
5.0
3.1
5.3
2.6
4.1
2.1
11.3

4.6
5.1
7.1
4.6
4.3
5.1
4.1
5.3
2.7
4.1
2.3
9.2

4.5
5.5
6.6
4.8
4.9
4.7
3.8
5.3
2.3
3.9
2.0
8.2

4.8
6.8
6.7
5.0
5.0
4.9
4.4
5.3
2.6
4.4
2.0
9.6

6.7
3.5

6.4
3.5

6.4
3.4

6.4
3.4

6.3
3.7

6.2
3.4

6.4
3.5

6.6
3.5

6.3
3.4

6.8
3.8

7.7
3.8

6.9
3.9

6.6
3.8

6.5
3.9

6.8
3.9

2.8
1.8

2.7
1.7

2.8
1.6

2.7
1.7

2.7
1.7

2.6
1.9

2.4
1.6

2.7
1.6

2.7
1.6

3.0
1.6

2.7
1.6

2.7
2.0

3.0
2.3

3.0
2.1

3.2
2.2

Industry
Nonagricultural wage and salary
workers.....................................................
Mining....................................................
Construction..........................................
Manufacturing.......................................
Durable goods....................................
Nondurable goods..............................
Transportation and public utilities..........
Wholesale and retail trade....................
Finance, insurance, and real estate......
Services................................................
Government workers.................................
Agricultural wage and salary workers........
Educational attainment

1

Less than a high school diploma................
High school graduates, no college.............
Some college, less than a bachelor's
degree......................................................
College graduates……………………………
1

88

Data refer to persons 25 years and over.

Monthly Labor Review

August 2001

7. Duration of unemployment, monthly data seasonally adjusted
[Numbers in thousands]
Weeks of
unemployment

Annual average
1999

2000

2000

2001

June

July

Aug.

Sept

Oct.

Nov.

Dec.

Jan.

Feb.

Mar.

Apr.

May

June

Less than 5 weeks...........................
5 to 14 weeks..................................
15 weeks and over..........................
15 to 26 weeks.............................
27 weeks and over.......................

2,568
1,832
1,480
755
725

2,543
1,803
1,309
665
644

2,572
1,776
1,260
609
651

2,493
1,811
1,319
650
669

2,567
1,832
1,373
673
700

2,498
1,750
1,247
618
629

2,510
1,755
1,311
702
609

2,531
1,796
1,317
713
604

2,440
1,852
1,326
675
651

2,613
1,977
1,371
731
640

2,797
1,669
1,490
793
697

2,674
1,992
1,517
814
703

2,958
1,977
1,499
759
740

2,679
2,028
1,484
852
632

2,809
2,084
1,540
804
737

Mean duration, in weeks.................
Median duration, in weeks...............

13.4
6.4

12.6
5.9

12.5
5.9

13.2
5.9

13.0
6.1

12.1
5.3

12.4
6.1

12.4
6.1

12.6
6.1

12.6
5.9

12.9
6.0

13.0
6.5

12.6
5.8

12.2
6.5

13.0
6.2

8. Unemployed persons by reason for unemployment, monthly data seasonally adjusted
[Numbers in thousands]
Reason for
unemployment
1

Job losers …………………….………
On temporary layoff......................
Not on temporary layoff................
Job leavers......................................
Reentrants.......................................
New entrants............................……

Annual average
1999

2000

2,622
848
1,774
783
2,005
469

2,492
842
1,650
775
1,957
431

2000

2001

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

Jan.

Feb.

Mar.

Apr.

May

June

2,439
917
1,522
692
2,042
416

2,450
857
1,593
788
1,960
412

2,585
907
1,678
780
1,930
503

2,502
837
1,665
756
1,798
429

2,446
825
1,621
815
1,868
398

2,501
877
1,624
768
1,936
429

2,514
937
1,577
746
1,899
466

2,742
1,032
1,711
838
1,956
446

2,853
945
1,908
820
1,927
372

2,963
991
1,972
814
1,908
382

3,199
1,053
2,146
749
2,005
462

3,159
1,084
2,075
820
1,801
482

3,291
940
2,351
810
1,906
477

Percent of unemployed
1

Job losers …………………….………
On temporary layoff......................
Not on temporary layoff................
Job leavers......................................
Reentrants.......................................
New entrants............................……

44.6
14.4
30.2
13.3
34.1
8.0

44.1
14.9
29.2
13.7
34.6
7.6

43.6
16.4
27.2
12.4
36.5
7.4

43.7
15.3
28.4
14.0
34.9
7.3

44.6
15.6
28.9
13.5
33.3
8.7

45.6
15.3
30.4
13.8
32.8
7.8

44.3
14.9
29.3
14.7
33.8
7.2

44.4
15.6
28.8
13.6
34.4
7.6

44.7
16.7
28.0
13.3
33.8
8.3

45.8
17.2
28.6
14.0
32.7
7.4

47.8
15.8
32.0
13.7
32.3
6.2

48.8
16.3
32.5
13.4
31.4
6.4

49.9
16.4
33.5
11.7
31.3
7.2

50.4
17.3
33.1
13.1
28.8
7.7

50.8
14.5
36.3
12.5
29.4
7.4

1.9
.6
1.4
.3

1.8
.6
1.4
.3

1.7
.5
1.5
.3

1.7
.6
1.4
.3

1.8
.6
1.4
.4

1.8
.5
1.3
.3

1.7
.6
1.3
.3

1.8
.5
1.4
.3

1.8
.5
1.3
.3

1.9
.6
1.4
.3

2.0
.6
1.4
.3

2.1
.6
1.3
.3

2.3
.5
1.4
.3

2.2
.6
1.3
.3

2.3
.6
1.3
.3

Percent of civilian
labor force
1

Job losers …………………….………
Job leavers......................................
Reentrants.......................................
New entrants............................……
1

Includes persons who completed temporary jobs.

Monthly Labor Review

August 2001

89

Current Labor Statistics:

Labor Force Data

9. Unemployment rates by sex and age, monthly data seasonally adjusted
[Civilian workers]
Sex and age

2000

Annual average
1999

Aug.

Sept.

Total, 16 years and over...................
16 to 24 years...............................
16 to 19 years............................
16 to 17 years.........................
18 to 19 years.........................
20 to 24 years............................
25 years and over.........................
25 to 54 years.........................
55 years and over...................

4.2
9.9
13.9
16.3
12.4
7.5
3.1
3.2
2.8

4.0
9.3
13.1
15.4
11.5
7.1
3.0
3.1
2.6

4.0
9.1
11.9
13.4
10.7
7.5
3.0
3.1
2.4

4.0
9.2
13.4
16.3
11.5
6.9
3.0
3.1
2.4

4.1
9.4
14.2
16.9
12.6
6.6
3.1
3.2
2.7

3.9
8.9
12.9
15.7
11.1
6.6
3.0
3.0
2.7

3.9
8.9
12.6
15.2
11.1
6.8
2.9
3.0
2.8

4.0
9.1
13.0
15.4
11.4
6.8
3.0
3.0
2.9

4.0
9.2
13.1
15.8
11.6
7.0
3.0
3.0
2.6

4.2
9.6
13.8
17.4
11.5
7.2
3.2
3.2
2.7

4.2
9.5
13.6
17.2
11.0
7.2
3.2
3.2
2.8

4.3
10.0
13.8
16.0
12.3
7.8
3.2
3.4
2.6

4.5
10.4
14.2
16.7
12.6
8.3
3.4
3.5
2.8

4.4
9.9
13.6
15.5
12.2
7.9
3.3
3.5
2.6

4.5
10.4
14.3
16.0
13.1
8.2
3.5
3.6
2.8

Men, 16 years and over..................
16 to 24 years.............................
16 to 19 years..........................
16 to 17 years.......................
18 to 19 years.......................
20 to 24 years..........................
25 years and over.......................
25 to 54 years.......................
55 years and over.................

4.1
10.3
14.7
17.0
13.1
7.7
3.0
3.0
2.8

3.9
9.7
14.0
16.8
12.2
7.3
2.8
2.9
2.7

3.9
9.6
14.2
15.9
13.0
7.0
2.8
2.9
2.3

3.8
9.6
14.1
17.5
12.0
7.1
2.8
2.8
2.4

4.0
10.2
15.8
17.1
15.2
6.9
2.8
2.9
2.7

3.9
9.5
13.7
17.5
11.2
7.1
2.8
2.9
2.6

3.9
9.4
13.4
17.6
10.7
7.3
2.9
2.9
2.8

4.0
9.5
13.6
17.5
11.3
7.3
3.0
2.9
2.9

4.0
9.7
14.1
18.4
11.7
7.2
3.0
2.9
2.8

4.3
10.3
15.0
20.5
11.8
7.6
3.1
3.1
3.0

4.2
10.8
15.5
18.5
13.1
8.2
3.0
3.0
2.9

4.4
10.9
13.8
15.6
12.7
9.3
3.2
3.3
2.9

4.6
10.9
15.1
18.7
12.8
8.7
3.5
3.5
2.9

4.5
11.0
15.3
17.4
13.9
8.7
3.3
3.5
2.9

4.7
11.8
15.9
18.0
14.5
9.5
3.4
3.5
3.0

Women, 16 years and over............
16 to 24 years.............................
16 to 19 years..........................
16 to 17 years.......................
18 to 19 years.......................
20 to 24 years..........................
25 years and over.......................
25 to 54 years.......................

4.3
9.5
13.2
15.5
11.6
7.2
3.3
3.4

4.1
8.9
12.1
14.0
10.8
7.0
3.2
3.3

4.1
8.5
9.4
10.7
8.2
8.0
3.2
3.3

4.2
8.9
12.6
15.0
10.9
6.7
3.3
3.4

4.2
8.6
12.4
16.8
9.8
6.3
3.4
3.5

4.0
8.2
12.0
13.8
11.0
6.0
3.2
3.2

3.9
8.4
11.9
12.8
11.6
6.3
3.0
3.1

4.0
8.6
12.3
13.4
11.5
6.3
3.1
3.2

4.0
8.7
12.1
13.2
11.6
6.7
3.0
3.1

4.1
8.8
12.4
14.1
11.3
6.7
3.2
3.4

4.2
8.1
11.6
15.7
8.7
6.1
3.4
3.5

4.2
8.9
13.7
16.4
11.9
6.3
3.2
3.5

4.4
9.8
13.3
14.5
12.4
7.8
3.3
3.4

4.3
8.8
11.8
13.6
10.4
7.1
3.4
3.6

4.4
8.9
12.7
14.0
11.6
6.7
3.5
3.8

55 years and over.................

2.8

2.6

2.4

2.4

2.6

2.8

2.8

2.7

2.4

2.5

2.7

2.2

2.6

2.2

2.5

90

Monthly Labor Review

2000

June

August 2001

July

2001
Oct.

Nov.

Dec.

Jan.

Feb.

Mar.

Apr.

May

June

10. Unemployment rates by State, seasonally adjusted
May
2000

State

Apr.
2001

May
p

2001

May
2000

State

Apr.
2001

May
p

2001

Alabama............................…………………
Alaska.......................................................
Arizona............................……………………
Arkansas...................................................
California............................…………………

4.5
6.8
3.9
4.6
5.0

5.3
5.8
4.3
4.5
4.9

4.7
5.6
4.2
4.6
4.9

Missouri............................…………………
Montana....................................................
Nebraska............................…………………
Nevada......................................................
New Hampshire............................…………

3.4
3.1
3.1
3.8
3.1

4.0
3.0
3.0
4.9
2.9

3.8
2.8
2.8
4.4
2.8

Colorado....................................................
Connecticut............................………………
Delaware...................................................
District of Columbia............................……
Florida.......................................................

2.7
2.3
4.0
5.6
3.6

2.7
2.2
3.3
4.6
3.9

2.8
2.3
3.4
4.9
3.9

New Jersey...............................................
New Mexico............................………………
New York...................................................
North Carolina............................……………
North Dakota.............................................

3.7
4.7
4.6
3.6
3.0

4.2
5.6
4.3
4.9
2.6

4.3
5.7
4.3
5.2
2.3

Georgia............................…………………
Hawaii.......................................................
Idaho............................………………………
Illinois........................................................
Indiana............................……………………

3.9
4.3
4.8
4.3
3.5

4.0
4.8
4.9
5.4
2.9

3.7
4.3
4.8
5.2
3.1

Ohio............................………………………
Oklahoma..................................................
Oregon............................……………………
Pennsylvania.............................................
Rhode Island............................……………

4.1
3.1
5.1
4.1
4.3

3.9
2.9
5.2
4.4
4.4

4.0
2.9
5.6
4.7
4.5

Iowa............................………………………
Kansas......................................................
Kentucky............................…………………
Louisiana...................................................
Maine............................……………………

2.6
3.9
4.1
5.5
3.8

2.7
3.5
5.4
5.4
3.1

2.8
3.6
5.6
5.6
3.5

South Carolina............................…………
South Dakota............................................
Tennessee............................………………
Texas........................................................
Utah............................………………………

4.1
2.4
3.9
4.3
3.2

4.3
2.5
4.3
4.3
3.9

4.4
2.6
4.1
4.5
4.0

Maryland............................…………………
Massachusetts..........................................
Michigan............................…………………
Minnesota..................................................
Mississippi............................………………

4.0
2.7
3.5
3.3
6.0

3.6
3.2
4.6
3.9
5.0

3.7
3.6
5.0
3.9
5.0

Vermont............................…………………
Virginia......................................................
Washington............................………………
West Virginia.............................................
Wisconsin............................………………
Wyoming...................................................

3.0
2.2
5.2
5.6
3.7
4.0

3.1
2.7
5.8
5.1
4.2
3.4

2.9
3.0
5.5
5.3
4.1
3.6

p

= preliminary

11. Employment of workers on nonfarm payrolls by State, seasonally adjusted
[In thousands]
State

May
2000

Alabama............................………
1,938.5
Alaska..........................................
283.5
Arizona............................…………
2,246.8
Arkansas......................................
1,161.3
California............................……… 14,479.5

Apr.
2001

May
p

2001

State

May
2000

Apr.
2001

May
p

2001

1,926.2
287.5
2,276.4
1,164.2
14,818.3

1,925.3
288.1
2,276.7
1,165.4
14,813.4

Missouri............................…………
Montana.......................................
Nebraska............................………
Nevada.........................................
New Hampshire............................

2,751.7
389.4
908.9
1,024.0
621.5

2,756.9
393.1
911.3
1,068.6
627.3

2,746.3
393.2
914.2
1,070.4
627.0

Colorado......................................
Connecticut............................……
Delaware......................................
District of Columbia......................
Florida..........................................

2,209.1
1,695.2
418.7
645.9
7,071.2

2,270.4
1,700.8
425.4
649.9
7,264.1

2,265.2
1,701.8
424.7
651.3
7,286.7

New Jersey..................................
New Mexico............................……
New York......................................
North Carolina............................…
North Dakota................................

3,998.8
744.4
8,636.4
3,942.1
328.0

4,027.3
754.7
8,729.5
3,975.7
328.6

4,028.2
757.5
8,722.2
3,985.4
327.7

Georgia............................…………
Hawaii..........................................
Idaho............................……………
Illinois...........................................
Indiana............................…………

3,983.1
550.8
561.3
6,042.3
3,011.0

4,045.6
560.0
564.8
6,058.2
2,995.8

4,052.0
557.8
568.2
6,058.5
2,996.2

Ohio............................……………
Oklahoma.....................................
Oregon............................…………
Pennsylvania................................
Rhode Island............................…

5,641.2
1,487.8
1,607.1
5,693.1
476.3

5,652.1
1,501.2
1,600.5
5,736.6
478.8

5,641.5
1,498.3
1,598.4
5,732.9
478.8

Iowa............................……………
Kansas.........................................
Kentucky............................………
Louisiana......................................
Maine............................……………

1,476.6
1,349.5
1,821.5
1,936.3
604.0

1,482.0
1,363.7
1,835.9
1,951.7
611.9

1,477.9
1,367.0
1,839.0
1,948.7
610.6

South Carolina............................…
South Dakota...............................
Tennessee............................……
Texas...........................................
Utah............................……………

1,878.1
379.1
2,733.2
9,436.8
1,075.0

1,893.0
378.7
2,759.7
9,626.4
1,092.5

1,898.6
381.3
2,753.9
9,640.0
1,093.4

Maryland............................………
Massachusetts.............................
Michigan............................………
Minnesota....................................
Mississippi............................………

2,451.2
3,312.9
4,684.1
2,667.4
1,161.3

2,473.3
3,362.8
4,693.1
2,689.2
1,145.5

2,475.7
3,365.7
4,676.5
2,693.2
1,145.6

Vermont............................…………
Virginia.........................................
Washington............................……
West Virginia................................
Wisconsin............................………
Wyoming......................................

298.2
3,503.8
2,719.0
746.9
2,834.1
238.6

299.9
3,560.6
2,744.2
739.7
2,848.8
245.1

299.9
3,562.6
2,745.0
737.1
2,843.8
243.6

p

= preliminary

NOTE: Some data in this table may differ from data published elsewhere because of the continual updating of the data base.

Monthly Labor Review

August 2001

91

Current Labor Statistics:

Labor Force Data

12. Employment of workers on nonfarm payrolls by industry, monthly data seasonally adjusted
[In thousands]
Industry

Annual average
1999

2000

2001
p

p

2000

June

July

Aug.

Sept.

Oct.

Nov

Dec.

Jan.

Feb.

Mar.

Apr.

May

June

TOTAL............................……128,916
PRIVATE SECTOR................... 108,709

131,739
111,079

131,969
111,029

131,899
111,180

131,837
111,237

132,046
111,463

132,145
111,564

132,279
111,689

132,367
111,753

132,428
111,799

132,595
111,915

132,654
111,943

132,489
111,742

132,530
111,760

132,437
111,622

GOODS-PRODUCING................... 25,507
1
Mining …………..……….......…………
539
Metal mining..............................
44
Oil and gas extraction................
297
Nonmetallic minerals,
except fuels...........……………
113

25,709
543
41
311

25,727
453
41
312

25,774
542
40
313

25,727
543
40
313

25,696
547
40
316

25,713
551
40
320

25,711
548
40
319

25,688
548
41
320

25,633
550
39
325

25,627
555
39
328

25,602
557
38
331

25,421
560
37
335

25,324
564
37
339

25,198
565
35
340

114

113

113

114

115

115

114

112

111

113

113

113

112

112

Construction...............................
General building contractors......
Heavy construction, except
building...................................
Special trades contractors.........

6,415
1,458

6,698
1,528

6,663
1,520

6,678
1,520

6,699
1,525

6,728
1,538

6,758
1,549

6,781
1,548

6,791
1,543

6,826
1,538

6,880
1,555

6,929
1,552

6,852
1,548

6,881
1,556

6,867
1,549

874
4,084

901
4,269

896
4,247

897
4,256

900
4,274

900
4,290

904
4,305

909
4,324

913
4,335

921
4,367

930
4,395

938
4,439

915
4,389

923
4,402

926
4,392

Manufacturing............................
Production workers..............

18,552
12,747

18,469
12,628

18,521
12,675

18,554
12,688

18,485
12,631

18,421
12,559

18,404
12,545

18,382
12,511

18,349
12,466

18,257
12,394

18,192
12,323

18,116
12,254

18,009
12,166

17,879
12,066

17,766
11,963

Durable goods..........................
Production workers..............

11,111
7,596

11,138
7,591

11,168
7,617

11,207
7,635

11,172
7,608

11,129
7,568

11,126
7,560

11,120
7,544

11,102
7,517

11,031
7,462

10,997
7,415

10,941
7,358

10,870
7,308

10,778
7,235

10,695
7,160

834
548

832
558

837
559

836
565

831
559

826
560

821
559

817
557

811
555

806
552

799
549

799
548

800
543

797
540

798
532

566
699
1,521

579
698
1,537

579
700
1,543

581
700
1,546

580
700
1,541

579
695
1,540

577
695
1,536

577
691
1,537

577
686
1,536

579
681
1,526

578
679
1,514

578
671
1,509

577
667
1,503

574
660
1,488

571
654
1,479

2,136

2,120

2,120

2,137

2,133

2,121

2,123

2,122

2,119

2,117

2,105

2,084

2,072

2,054

2,031

Lumber and wood products.....
Furniture and fixtures...............
Stone, clay, and glass
products................................
Primary metal industries..........
Fabricated metal products.......
Industrial machinery and
equipment.............................
Computer and office
equipment...........................
Electronic and other electrical
equipment.............................
Electronic components and
accessories.........................…
Transportation equipment........
Motor vehicles and
equipment............................
Aircraft and parts...................
Instruments and related
products.....……………………
Miscellaneous manufacturing
industries...............................

368

361

354

362

365

364

365

365

366

369

370

369

367

366

357

1,672

1,719

1,719

1,735

1,740

1,736

1,738

1,737

1,738

1,735

1,726

1,715

1,684

1,656

1,624

641
1,888

682
1,849

678
1,868

689
1,855

695
1,836

698
1,822

704
1,822

708
1,822

710
1,817

714
1,772

711
1,786

702
1,775

686
1,768

670
1,757

649
1,752

1,018
496

1,013
465

1,025
466

1,027
465

1,015
464

1,005
464

994
463

995
462

990
464

952
462

967
464

956
465

950
464

939
465

934
465

855

852

849

856

856

858

861

865

867

870

871

871

866

865

865

391

394

394

396

396

392

394

395

396

393

390

391

390

387

389

Nondurable goods...................
Production workers..............

7,441
5,150

7,331
5,038

7,353
5,058

7,347
5,053

7,313
5,023

7,292
4,991

7,278
4,985

7,262
4,967

7,647
4,949

7,226
4,932

7,195
4,908

7,175
4,896

7,139
4,854

7,101
4,831

7,071
4,803

Food and kindred products......
Tobacco products....................
Textile mill products.................
Apparel and other textile
products................................
Paper and allied products........
Printing and publishing.............
Chemicals and allied products.
Petroleum and coal products...
Rubber and miscellaneous
plastics products....................
Leather and leather products...

1,682
37
559

1,684
34
528

1,685
35
531

1,686
34
530

1,679
33
528

1,674
33
523

1,678
32
518

1,679
33
514

1,682
32
510

1,684
32
505

1,686
31
496

1,687
32
494

1,687
32
489

1,684
33
480

1,686
33
472

690
668
1,552
1,035
132

633
657
1,547
1,038
127

639
657
1,552
1,037
129

637
656
1,553
1,036
128

625
655
1,549
1,036
128

620
655
1,547
1,037
127

616
655
1,544
1,038
126

611
654
1,540
1,038
127

604
652
1,539
1,039
127

599
651
1,534
1,039
127

595
645
1,529
1,039
127

590
642
1,524
1,039
126

581
641
1,512
1,036
128

579
639
1,502
1,033
127

569
635
1,469
1,034
128

1,006
77

1,011
71

1,016
72

1,013
74

1,009
71

1,006
70

1,002
69

997
69

993
69

987
68

979
68

973
68

967
66

959
65

954
64

SERVICE-PRODUCING................ 103,409

106,050

106,242

106,125

106,110

106,350

106,432

106,568

106,679

106,795

106,968

107,052

107,068

107,206

107,239

6,834
4,411
235

7,019
4,529
236

7,015
4,520
233

7,034
4,536
235

6,963
4,548
236

7,062
4,553
235

7,076
4,559
234

7,093
4,573
235

7,108
4,583
232

7,106
4,580
229

7,123
4,591
231

7,127
4,591
230

7,119
4,576
230

7,130
4,584
230

7,114
4,568
227

478
1,810
186
1,227
13
463

476
1,856
196
1,281
14
471

472
1,854
197
1,278
14
472

477
1,860
195
1,282
14
473

478
1,860
198
1,288
14
474

478
1,861
199
1,291
14
475

477
1,861
200
1,298
14
475

478
1,864
200
1,306
14
476

478
1,866
200
1,316
14
477

479
1,868
201
1,312
14
477

480
1,870
200
1,318
14
478

480
1,872
201
1,316
13
479

477
1,864
202
1,313
14
476

483
1,867
203
1,315
14
472

482
1,865
201
1,310
14
469

2,423
1,560

2,490
1,639

2,495
1,644

2,498
1,647

2,415
1,565

2,509
1,660

2,517
1,668

2,520
1,672

2,525
1,678

2,526
1,679

2,532
1,685

2,536
1,690

2,543
1,696

2,546
1,699

2,546
1,700

Transportation and public
utilities...................................
Transportation............................
Railroad transportation............
Local and interurban
passenger transit...................
Trucking and warehousing.......
Water transportation................
Transportation by air................
Pipelines, except natural gas...
Transportation services..........
Communications and public
utilities.....................................
Communications......................
Electric, gas, and sanitary
services.................................

863

851

851

851

850

849

849

848

847

847

847

846

847

847

847

Wholesale trade.........................

6,911

7,024

7,019

7,030

7,037

7,042

7,059

7,070

7,068

7,067

7,064

7,066

7,053

7,038

7,022

Retail trade.................................
Building materials and garden
supplies...................................
General merchandise stores......
Department stores...................

22,848

23,307

23,280

23,311

23,348

23,371

23,380

23,395

23,406

23,415

23,472

23,457

23,530

23,546

23,570

988
2,798
2,459

1,016
2,837
2,491

1,016
2,831
2,482

1,014
2,820
2,470

1,015
2,830
2,483

1,012
2,834
2,487

1,012
2,829
2,481

1,011
2,835
2,492

1,010
2,822
2,480

1,007
2,789
2,448

1,007
2,807
2,462

1,006
2,797
2,451

999
2,804
2,459

1,006
2,821
2,473

1,015
2,822
2,476

See footnotes at end of table.

92

Monthly Labor Review

August 2001

12. Continued—Employment of workers on nonfarm payrolls by industry, monthly data seasonally adjusted
[In thousands]
Industry

Annual average
1999

Food stores............................…
Automotive dealers and
service stations.......................
New and used car dealers.......
Apparel and accessory stores....
Furniture and home furnishings
stores......................................
Eating and drinking places.........
Miscellaneous retail
establishments…………………

2000

2000
June

July

Aug.

Sept.

2001
Oct.

Nov.

Dec.

Jan.

Feb.

Mar.

Apr.

p

May

June

p

3,497

3,521

3,522

3,523

3,526

3,520

3,528

3,527

3,532

3,538

3,548

3,550

3,562

3,553

3,547

2,368
1,080
1,171

2,412
1,114
1,193

2,410
1,114
1,190

2,412
1,116
1,196

2,418
1,118
1,195

2,420
1,120
1,202

2,426
1,122
1,202

2,426
1,123
1,208

2,425
1,123
1,214

2,424
1,124
1,221

2,424
1,124
1,227

2,420
1,124
1,228

2,421
1,122
1,226

2,428
1,126
1,231

2,430
1,127
1,228

1,087
7,961

1,134
8,114

1,136
8,098

1,135
8,123

1,138
8,132

1,138
8,138

1,142
8,137

1,144
8,142

1,148
8,149

1,147
8,157

1,146
8,171

1,147
8,158

1,140
8,213

1,136
8,216

1,136
8,241

2,978

3,080

3,077

3,088

3,094

3,098

3,105

3,103

3,106

3,132

3,142

3,151

3,165

3,155

3,151

7,555
3,688
2,056
1,468
254
709

7,560
3,710
2,029
1,430
253
681

7,541
3,699
2,028
1,430
253
676

7,546
3,701
2,024
1,425
252
675

7,549
3,707
2,024
1,425
253
674

7,556
3,718
2,024
1,524
253
677

7,569
3,725
2,023
1,421
253
678

7,575
3,729
2,023
1,420
253
678

7,582
3,735
2,025
1,420
253
677

7,594
3,738
2,024
1,418
253
678

7,609
3,748
2,025
1,417
254
683

7,618
3,755
2,028
1,418
254
686

7,626
3,761
2,032
1,421
255
691

7,644
3,770
2,037
1,426
255
697

7,631
3,768
2,040
1,428
256
701

689

748

745

751

756

762

767

770

774

777

781

781

780

776

766

234
2,368
1,610

251
2,346
1,589

250
2,345
1,590

251
2,340
1,585

253
2,341
1,585

255
2,335
1,580

257
2,337
1,580

248
2,340
1,583

259
2,339
1,582

259
2,346
1,588

259
2,351
1,592

260
2,353
1,593

258
2,356
1,596

260
2,358
1,598

261
2,356
1,598

758
1,500

757
1,504

755
1,497

755
1,495

756
1,501

755
1,503

757
1,507

757
1,506

757
1,508

758
1,510

759
1,510

760
1,510

760
1,509

760
1,516

758
1,507

Services ………………………….…… 39,055
Agricultural services...................
766
1,848
Hotels and other lodging places.
Personal services.......................
1,226
Business services......................
9,300
Services to buildings................
983
Personnel supply services.......
3,616
Help supply services..............
3,248
Computer and data
processing services...............
1,875
Auto repair services
and parking.............................
1,196
Miscellaneous repair services....
372
Motion pictures..........................
599
Amusement and recreation
services...................................
1,651

40,460
801
1,912
1,251
9,858
994
3,887
3,487

14,447
795
1,917
1,247
9,876
992
3,916
3,517

40,495
798
1,923
1,250
9,884
994
3,909
3,505

40,613
801
1,923
1,256
9,921
994
3,917
3,506

40,736
804
1,924
1,257
9,965
995
3,947
3,547

40,767
808
1,927
1,259
9,939
994
3,890
3,465

40,845
811
1,939
1,261
9,933
998
3,869
3,461

40,901
813
1,946
1,265
9,893
1,002
3,816
3,404

40,984
818
1,952
1,261
9,888
1,007
3,779
3,372

41,020
821
1,957
1,261
9,851
1,007
3,731
3,339

41,073
828
1,960
1,265
9,822
1,007
3,694
3,201

40,993
824
1,944
1,267
9,729
1,009
3,600
3,202

41,078
834
1,835
1,277
9,702
1,013
3,590
3,198

41,087
834
1,922
1,280
9,668
1,009
3,558
3,160

2,095

2,091

2,106

2,114

2,124

2,135

2,152

2,164

2,176

2,186

2,195

2,199

2,200

2,205

1,248
366
594

1,240
365
597

1,248
365
596

1,254
366
596

1,260
366
590

1,266
366
588

1,270
366
593

1,278
365
597

1,291
365
600

1,291
365
600

1,298
364
605

1,300
364
601

1,309
363
587

1,302
361
596

1,728

1,726

1,735

1,741

1,738

1,747

1,755

1,759

1,769

1,772

1,775

1,764

1,787

1,776

Health services..........................
Offices and clinics of medical
doctors...................................
Nursing and personal care
facilities..................................
Hospitals..................................
Home health care services......
Legal services............................
Educational services..................
Social services...........................
Child day care services............
Residential care.......................
Museums and botanical and
zoological gardens..................
Membership organizations.........
Engineering and management
services...................................
Engineering and architectural
services..................................
Management and public
relations................................

10,036

10,197

10,078

10,097

10,114

10,131

10,146

10,164

10,184

10,211

10,236

10,259

10,280

10,296

10,329

1,875

1,924

1,921

1,923

1,926

1,933

1,938

1,941

1,948

1,953

1,958

1,962

1,967

1,973

1,981

1,786
3,974
636
996
2,267
2,783
680
771

1,795
3,990
643
1,009
2,325
2,903
712
806

1,793
3,982
643
1,010
2,335
2,887
712
804

1,793
3,988
645
1,010
2,337
2,883
715
807

1,798
3,993
645
1,011
2,352
2,889
719
809

1,797
4,001
645
1,013
2,344
2,928
719
813

1,799
4,005
646
1,014
2,329
2,950
724
817

1,800
4,016
644
1,013
2,338
2,958
727
820

1,803
4,025
642
1,015
2,357
2,977
729
823

1,806
4,035
646
1,017
2,363
2,985
732
827

1,806
4,045
645
1,020
2,375
2,997
734
829

1,811
4,055
648
1,022
2,384
3,009
739
831

1,816
4,062
646
1,021
2,388
3,023
743
835

1,814
4,071
645
1,027
2,431
3,039
745
835

1,820
4,086
648
1,027
2,429
3,052
752
842

99
2,436

106
2,475

106
2,474

107
2,466

107
2,470

107
2,482

107
2,482

108
2,486

108
2,487

109
2,487

110
2,487

110
2,489

109
2,489

110
2,496

111
2,497

1,031

1,090

1,089

1,090

1,098

1,102

1,108

1,113

1,116

1,119

1,123

1,125

1,124

1,121

1,125

Government................................
Federal.......................................
Federal, except Postal
Service..................................
State..........................................
Education.................................
Other State government..........
Local..........................................
Education.................................
Other local government...........

20,206
2,669

20,681
2,777

20,940
3,101

20,719
2,820

20,600
2,653

20,583
2,623

20,581
2,622

20,590
2,620

20,614
2,613

20,629
2,613

20,680
2,615

20,711
2,613

20,747
2,615

20,770
2,612

20,815
2,601

1,796
4,709
1,983
2,726
12,829
7,289
5,540

1,917
4,785
2,032
2,753
13,119
7,440
5,679

2,238
4,776
2,029
2,747
13,063
7,396
5,667

1,957
4,782
2,033
2,749
13,117
7,438
5,679

1,790
4,794
2,037
2,757
13,153
7,456
5,697

1,762
4,813
2,051
2,762
13,147
7,439
5,708

1,762
4,798
2,035
2,763
13,161
7,445
5,716

1,761
4,798
2,033
2,765
13,172
7,449
5,723

1,754
4,809
2,037
2,772
13,192
7,457
5,735

1,755
4,800
2,028
2,772
13,216
7,468
5,748

1,756
4,825
2,048
2,777
13,240
7,479
5,761

1,754
4,836
2,055
2,781
13,262
7,492
5,770

1,756
4,847
2,065
2,782
13,285
7,495
5,790

1,754
4,854
2,066
2,788
13,304
7,512
5,792

1,752
4,880
2,087
2,793
13,334
7,521
5,813

Finance, insurance, and
real estate................................
Finance............................………
Depository institutions..............
Commercial banks.................
Savings institutions................
Nondepository institutions........
Security and commodity
brokers...................................
Holding and other investment
offices....................................
Insurance............................……
Insurance carriers....................
Insurance agents, brokers,
and service............................
Real estate............................……
1

1

3,256

3,419

3,421

3,423

3,440

3,455

3,467

3,478

3,490

3,496

3,504

510

3,517

3,512

3,529

957

1,017

1,018

1,022

1,026

1,030

1,034

1,035

1,040

1,046

1,050

1,052

1,053

1,057

1,060

Includes other industries not shown separately.

p

= preliminary.
NOTE: See "Notes on the data" for a description of the most recent benchmark revision.

Monthly Labor Review

August 2001

93

Current Labor Statistics:

Labor Force Data

13. Average weekly hours of production or nonsupervisory workers on private nonfarm payrolls, by industry, monthly
data seasonally adjusted
Annual average
Industry

1999

2000

2000
June

2001

July

Aug.

Sept.

Oct.

Nov.

Dec.

Jan.

Feb.

Mar.

Apr.

p

June

May

p

PRIVATE SECTOR.………………………

34.5

34.5

34.5

34.4

34.3

34.4

34.4

34.3

34.2

34.4

34.3

34.3

34.2

34.2

34.2

GOODS-PRODUCING………………………

41.0

41.0

41.0

41.1

40.8

40.7

40.8

40.6

40.1

40.5

40.3

40.5

40.6

40.5

40.3

MINING…………………….........................

43.2

43.1

43.0

43.2

43.1

43.0

43.1

43.0

42.5

43.1

43.2

43.8

44.0

43.9

43.3

MANUFACTURING……………………......
Overtime hours..................................

41.7
4.6

41.6
4.6

41.7
4.6

41.8
4.7

41.4
4.5

41.4
4.4

41.4
4.5

41.2
4.3

40.6
4.1

41.0
4.2

40.9
3.9

41.0
4.1

41.0
3.9

40.7
3.9

40.7
3.9

Durable goods..…………………............
Overtime hours.................................
Lumber and wood products................
Furniture and fixtures..........................
Stone, clay, and glass products..........
Primary metal industries......................
Blast furnaces and basic steel
products..........................................
Fabricated metal products………………

42.2
4.8
41.1
40.3
43.4
44.5

42.1
4.7
41.0
40.0
43.1
44.9

42.2
4.8
41.0
40.2
42.8
45.1

42.4
4.8
41.0
40.1
43.2
45.2

41.9
4.6
40.7
39.6
43.0
44.7

41.8
4.5
40.8
39.7
42.9
44.7

41.9
4.6
40.9
39.7
43.2
44.4

41.6
4.4
40.8
39.4
43.0
44.4

41.0
4.1
40.2
38.8
42.3
43.5

41.3
4.1
39.8
39.2
43.0
43.8

41.1
3.9
40.1
39.1
42.8
43.2

41.3
4.0
40.3
39.1
43.7
43.4

41.3
3.9
40.1
39.3
43.2
44.3

41.0
3.9
40.6
38.6
43.9
43.5

40.9
3.9
40.3
38.3
44.1
43.8

45.2
42.4

46.0
42.6

46.5
42.7

46.2
43.0

45.9
42.3

45.8
42.2

45.1
42.2

45.2
42.1

44.7
41.3

44.7
41.7

44.4
41.7

44.4
41.9

45.4
42.0

44.6
41.4

45.1
41.1

Industrial machinery and equipment...
Electronic and other electrical
equipment........................................
Transportation equipment...................
Motor vehicles and equipment..........
Instruments and related products.......
Miscellaneous manufacturing..............

42.1

42.2

42.3

42.5

42.1

41.9

42.0

41.7

41.1

41.5

41.0

41.2

41.3

40.7

40.4

41.2
43.8
45.0
41.3
39.8

41.1
43.4
44.4
41.3
39.0

41.2
43.6
44.7
41.5
39.0

41.5
43.7
44.5
41.6
39.3

40.5
43.2
44.3
40.9
38.7

40.7
42.9
43.8
41.1
38.5

40.7
43.0
43.9
41.2
38.6

40.5
42.5
43.2
41.2
38.4

40.3
41.5
41.5
40.7
38.1

40.3
42.0
42.1
41.0
38.3

40.3
42.0
42.0
41.1
38.2

40.1
42.0
42.3
41.0
38.2

39.8
42.4
43.3
41.0
38.2

39.1
42.4
43.6
41.0
37.9

39.3
41.9
42.9
40.8
38.4

Nondurable goods................................
Overtime hours.................................
Food and kindred products.................
Textile mill products............................
Apparel and other textile products......
Paper and allied products...................

40.9
4.4
41.8
40.9
37.5
43.4

40.8
4.4
41.7
41.2
37.8
42.5

40.8
4.4
41.9
41.1
37.9
42.6

41.0
4.5
41.8
41.6
38.1
42.6

40.7
4.4
41.8
40.8
37.7
42.5

40.7
4.3
41.6
40.8
37.6
42.4

40.6
4.3
41.5
40.6
37.5
42.3

40.5
4.2
41.4
40.5
37.6
42.2

40.1
4.1
40.9
40.5
37.2
41.7

40.6
4.3
41.3
40.7
37.6
41.9

40.4
4.0
41.1
40.4
37.6
41.7

40.5
4.1
41.2
40.5
37.5
41.8

40.5
3.9
41.3
40.3
38.0
42.0

40.3
4.0
41.1
40.3
37.8
41.6

40.3
3.9
41.2
40.5
37.5
41.7

Printing and publishing........................
Chemicals and allied products............
Rubber and miscellaneous
plastics products...............................
Leather and leather products..............

38.1
43.0

38.3
42.5

38.4
42.4

38.4
42.7

38.1
42.3

38.2
42.4

38.2
42.3

38.2
42.1

37.O
42.1

38.4
42.6

38.4
42.3

38.6
42.3

38.2
42.6

38.0
42.4

38.0
42.3

41.7
37.4

41.4
37.5

41.3
37.4

41.5
37.6

41.3
37.4

41.3
37.3

41.2
37.4

41.0
37.3

40.4
36.8

41.0
36.9

40.9
36.4

41.0
36.1

40.8
36.6

40.6
35.9

40.7
36.2

SERVICE-PRODUCING………………….....

32.8

32.8

32.8

32.8

32.7

32.8

32.8

32.8

32.7

32.9

32.8

32.8

32.7

32.7

32.8

TRANSPORTATION AND
PUBLIC UTILITIES........……………….

38.7

38.6

38.5

38.5

38.4

38.5

38.6

38.6

38.7

38.7

38.5

38.3

38.1

38.1

38.1

WHOLESALE TRADE........……………….

38.3

38.5

38.5

38.5

38.3

38.4

38.4

38.4

38.3

38.3

38.1

38.3

38.2

38.2

38.2

RETAIL TRADE.…………….....................

29.0

28.9

28.9

28.9

28.9

28.8

28.9

28.9

28.7

29.1

28.9

28.8

28.8

28.8

28.7

p

= preliminary.

NOTE: See "Notes on the data" for a description of the most recent benchmark revision.

94

Monthly Labor Review

August 2001

14. Average hourly earnings of production or nonsupervisory workers on private nonfarm payrolls, by industry,
seasonally adjusted
Industry

Annual average

PRIVATE SECTOR (in current dollars)..
Goods-producing…………………………
Mining..................................................
Construction........................................
Manufacturing.....................................
Excluding overtime...........................

2000

2001
p

p

1999

2000

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

Jan.

Feb.

Mar.

Apr.

May

June

$13.24

$13.75

$13.72

$13.75

$13.80

$13.84

$13.90

$13.97

$14.03

$14.03

$14.11

$14.17

$14.21

$14.24

$14.31

14.83

15.40

15.35

15.38

15.45

15.47

15.57

15.63

15.65

15.67

15.74

15.79

15.78

15.86

15.91

17.05
17.19
13.90
13.17

17.24
17.88
14.38
13.62

17.29
17.80
14.35
13.60

17.29
17.86
14.37
13.62

17.25
17.93
14.43
13.69

17.24
17.97
14.44
13.73

17.30
18.02
14.54
13.80

17.38
18.16
14.57
13.84

17.43
18.17
14.58
13.88

17.49
18.28
14.54
13.83

17.52
18.30
14.63
13.94

17.55
18.33
14.66
13.96

17.53
18.15
14.72
14.04

17.54
18.22
14.78
14.09

17.76
18.29
14.81
14.13

Service-producing..........……………….

12.73

13.24

13.22

13.24

13.29

13.34

13.39

13.46

13.53

13.54

13.62

13.68

13.73

13.76

13.84

Transportation and public utilities........
Wholesale trade..................................
Retail trade..........................................
Finance, insurance, and real estate....
Services..............................................

15.69
14.59
9.09
14.62
13.37

16.22
15.20
9.46
15.07
13.91

16.26
15.21
9.44
15.04
13.87

16.18
15.24
9.47
15.07
13.92

16.27
15.25
9.50
15.13
13.97

16.31
15.33
9.54
15.19
14.01

16.39
15.37
9.57
15.20
14.07

16.42
15.44
9.61
15.28
14.16

16.50
15.55
9.65
15.35
14.23

16.51
15.53
9.64
15.44
14.25

16.64
15.60
9.69
15.55
14.35

16.68
15.68
9.72
15.61
14.40

16.74
15.74
9.74
15.64
14.48

16.76
15.70
9.79
15.74
14.49

16.89
15.84
9.84
15.84
14.55

PRIVATE SECTOR (in constant (1982)
dollars)...................................................

7.86

7.89

7.87

7.87

7.90

7.88

7.90

7.92

7.94

7.90

7.92

7.95

7.94

7.93

7.95

p

= preliminary.

NOTE: See "Notes on the data" for a description of the most recent benchmark revision.

Monthly Labor Review

August 2001

95

Current Labor Statistics:

Labor Force Data

15. Average hourly earnings of production or nonsupervisory workers on private nonfarm payrolls, by industry
Industry

Annual average

2000

2001
p

p

1999

2000

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

Jan.

Feb.

Mar.

Apr.

May.

June

PRIVATE SECTOR………………………… $13.24

$13.75

$13.63

$13.69

$13.68

$13.89

$13.97

$13.99

$14.04

$14.10

$14.16

$14.19

$14.27

$14.22

$14.22

MINING………………………………..........

17.05

17.24

17.15

17.21

17.13

17.16

17.28

17.32

17.54

17.67

17.61

17.57

17.60

17.49

17.62

CONSTRUCTION..………….....................

17.19

17.88

17.73

17.92

18.05

18.17

18.22

18.20

18.23

18.17

18.16

18.30

18.07

18.17

18.22

MANUFACTURING…………………………

13.90

14.38

14.33

14.35

14.36

14.51

14.53

14.60

14.67

14.59

14.61

14.65

14.74

14.75

14.79

Durable goods……………………….......
Lumber and wood products.................
Furniture and fixtures..........................
Stone, clay, and glass products..........
Primary metal industries......................
Blast furnaces and basic steel
products..........................................
Fabricated metal products..................

14.36
11.51
11.29
13.97
15.80

14.82
11.93
11.73
14.53
16.42

14.76
11.93
11.70
14.47
16.46

14.74
11.99
11.76
14.58
16.67

14.81
12.01
11.83
14.65
16.49

14.96
12.07
11.88
14.77
16.54

14.99
12.09
11.86
14.75
16.48

15.05
12.07
11.90
14.76
16.58

15.11
12.12
11.93
14.72
16.65

14.98
12.13
11.92
14.65
16.66

15.03
12.08
12.03
14.68
16.58

15.09
12.08
12.04
14.79
16.63

15.14
12.13
12.07
14.96
16.90

15.19
12.16
12.09
15.03
16.82

15.24
12.19
12.15
15.14
16.96

18.84
13.50

19.82
13.87

20.00
13.82

20.35
13.83

19.97
13.85

19.83
13.99

19.84
14.01

19.71
14.03

19.88
14.09

20.16
13.99

20.05
14.03

20.00
14.08

20.37
14.11

20.26
14.23

20.42
14.26

Industrial machinery and equipment...
Electronic and other electrical
equipment........................................
Transportation equipment...................
Motor vehicles and equipment..........
Instruments and related products........
Miscellaneous manufacturing..............

15.03

15.55

15.49

15.57

15.61

15.69

15.66

15.67

15.81

15.73

15.74

15.77

15.74

15.79

15.81

13.43
17.79
18.10
14.08
11.26

13.80
18.45
18.79
14.43
11.63

13.66
18.40
18.81
14.30
11.55

13.77
18.02
18.22
14.46
11.57

13.76
18.37
18.68
14.44
11.56

13.91
18.77
19.12
14.58
11.66

14.00
18.88
19.26
14.62
11.75

14.04
19.05
19.43
14.64
11.82

14.17
19.00
19.31
14.80
11.94

14.07
18.57
18.77
14.64
11.98

14.16
18.68
18.91
14.60
11.98

14.26
18.76
19.02
14.73
12.05

14.39
18.77
19.13
14.80
12.04

14.38
18.83
19.18
14.75
12.10

14.49
18.90
19.25
14.81
12.05

Nondurable goods………………………
Food and kindred products.................
Tobacco products................................
Textile mill products............................
Apparel and other textile products......
Paper and allied products...................

13.21
12.11
19.87
10.81
8.92
15.88

13.69
12.50
21.57
11.16
9.30
16.25

13.65
12.51
22.52
11.13
9.33
16.21

13.75
12.54
22.90
11.18
9.29
16.36

13.68
12.49
22.60
11.21
9.29
16.27

13.80
12.59
22.13
11.30
9.36
16.37

13.81
12.59
22.47
11.23
9.37
16.43

13.89
12.69
21.85
11.27
9.33
16.50

13.97
12.71
21.76
11.27
9.37
16.61

12.97
12.70
21.34
11.32
9.39
16.53

13.97
12.65
21.49
11.27
9.36
16.54

13.97
12.68
22.63
11.31
9.46
16.56

14.12
12.79
22.59
11.30
9.44
16.74

14.07
12.83
23.01
11.29
9.39
16.72

14.12
12.87
23.21
11.32
9.44
16.90

Printing and publishing........................
Chemicals and allied products............
Petroleum and coal products..............
Rubber and miscellaneous
plastics products...............................
Leather and leather products..............

13.96
17.42
21.43

14.40
18.15
22.00

14.33
18.10
21.83

14.41
18.33
21.93

14.39
18.21
21.78

14.56
18.32
22.06

14.50
18.27
22.14

14.56
18.35
22.23

14.66
18.47
22.31

14.59
18.34
22.10

14.64
18.41
22.21

14.69
18.33
21.83

14.75
18.64
22.09

14.75
18.52
21.83

14.76
18.55
21.79

12.40
9.71

12.85
10.18

12.79
10.11

12.88
10.13

12.87
10.24

12.96
10.31

12.98
10.33

13.10
10.32

13.20
10.37

13.24
10.51

13.31
10.35

13.19
10.46

13.33
10.37

13.30
10.26

13.30
10.35

TRANSPORTATION AND
PUBLIC UTILITIES…………..................

15.69

16.22

16.18

16.19

16.22

16.31

16.38

16.43

16.53

16.56

16.68

16.65

16.78

16.70

16.81

WHOLESALE TRADE…….......................

14.59

15.20

15.12

15.27

15.19

15.33

15.45

15.45

15.58

15.56

15.62

15.58

15.86

15.66

15.75

RETAIL TRADE………………...................

9.09

9.46

9.39

9.40

9.41

9.58

9.59

9.61

9.65

9.69

9.72

9.74

9.78

9.78

9.78

FINANCE, INSURANCE,
AND REAL ESTATE………………………

14.62

15.07

14.93

15.01

14.99

15.11

15.24

15.25

15.32

15.45

15.63

15.67

15.81

15.74

15.73

SERVICES………………….......................

13.37

13.91

13.72

13.78

13.74

14.00

14.11

14.20

14.33

14.39

14.47

14.48

14.58

14.46

14.40

p

= preliminary.

NOTE: See "Notes on the data" for a description of the most recent benchmark revision.

96

Monthly Labor Review

August 2001

16. Average weekly earnings of production or nonsupervisory workers on private nonfarm payrolls, by industry
Industry

Annual average
1999

2000

2001
p

p

2000

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

Jan.

Feb.

Mar.

Apr.

May

June

PRIVATE SECTOR
Current dollars............................. $456.78
Seasonally adjusted................
–
Constant (1982) dollars............. 271.25

$474.38
–
272.16

$471.60
473.34
270.10

$477.78
473.00
273.33

$474.70
473.34
271.72

$479.21
476.10
272.43

$484.76
478.16
275.28

$479.86
479.17
272.03

$480.17
479.83
272.51

$477.99
482.63
269.74

$481.44
483.97
270.62

$482.46
486.03
270.89

$486.61
485.98
271.70

$484.90
487.01
269.39

$489.17
489.40
271.46

MINING………………………………… 736.56

743.04

742.60

748.64

746.87

751.61

756.86

743.03

747.20

750.98

751.95

757.27

765.60

769.56

769.99

CONSTRUCTION............................

672.13

702.68

700.34

716.80

725.61

728.62

732.44

704.34

694.56

692.28

682.82

702.52

695.70

728.62

726.98

MANUFACTURING
Current dollars............................
Constant (1982) dollars..............

579.63
344.20

598.21
343.21

598.99
343.06

592.66
339.05

594.50
340.30

606.52
344.81

604.45
343.24

607.36
344.31

607.34
344.69

596.73
336.76

591.71
332.61

597.72
335.61

588.13
328.38

600.33
333.52

603.43
334.87

605.99

623.92

625.82

614.66

620.54

624.31

626.36

494.02
473.20

630.09
486.01
476.01

607.11

489.19
466.87

633.61
494.87
474.81

620.20

495.10
472.68

631.08
499.32
474.40

613.22

489.13
469.20

632.81
496.08
481.14

615.68

473.06
454.99

477.92
464.88

473.54
461.95

483.20
467.15

483.99
457.45

497.34
462.22

497.35
467.78

606.30
703.10

626.24
737.26

623.66
742.35

634.23
741.82

641.67
733.81

646.93
742.65

647.53
731.71

637.63
746.10

624.13
735.93

613.84
731.37

610.69
716.26

631.53
718.42

638.79
730.08

665.83
731.67

672.22
742.85

851.57
572.40

911.72
590.86

930.00
594.26

944.24
583.63

916.62
585.86

908.21
598.77

890.82
596.83

902.72
597.68

890.62
596.01

901.15
581.98

882.20
580.84

884.00
585.73

920.72
567.22

899.54
589.12

920.94
588.94

632.76

656.21

655.23

653.94

652.50

658.98

656.15

658.14

662.44

655.94

648.49

651.30

628.03

644.23

640.31

553.32
779.20

567.18
800.73

562.79
807.76

561.82
758.64

558.66
789.91

573.09
822.13

575.00
819.39

575.64
821.06

585.22
807.50

567.02
772.51

566.40
775.22

568.97
789.80

554.02
765.82

559.38
804.04

569.46
799.47

814.50

834.28

852.09

772.53

823.79

860.40

857.07

852.98

826.47

778.96

786.66

808.35

791.98

840.08

837.38

581.50
488.15

595.96
453.57

592.02
450.45

595.75
446.60

587.71
448.53

597.78
455.91

602.34
457.08

607.56
457.43

621.72
460.88

603.17
454.04

605.90
454.04

605.40
461.52

594.96
450.30

602.48
458.59

602.77
462.72

Nondurable goods.......................
Food and kindred products........
Tobacco products......................
Textile mill products...................
Apparel and other textile
products..................................
Paper and allied products..........

540.29

558.55

556.92

559.63

556.78

567.18

564.83

569.49

569.98

565.79

560.20

561.59

559.15

564.21

569.04

506.20
763.01
442.13

521.25
877.90
459.79

522.92
939.08
459.67

524.17
964.09
458.38

525.83
942.42
458.49

535.08
927.25
465.56

528.78
878.12
457.06

534.25
895.85
460.94

528.74
892.16
462.07

520.70
832.26
459.59

509.80
831.66
449.67

513.54
893.89
458.06

510.32
885.53
444.09

522.18
906.59
454.99

528.96
956.25
459.59

334.50
689.19

351.54
690.63

356.41
687.30

349.30
693.66

351.16
688.22

352.87
699.00

352.31
699.92

352.67
706.20

353.25
705.93

349.31
697.57

352.87
683.10

355.70
687.24

346.45
688.01

355.88
690.54

356.83
701.35

Printing and publishing..............
Chemicals and allied products..
Petroleum and coal products.....
Rubber and miscellaneous
plastics products......................
Leather and leather products....

531.88
749.06
908.63

551.52
771.38
932.80

547.41
767.44
910.31

550.46
775.36
925.45

549.70
766.64
886.45

562.02
776.77
930.93

558.25
772.82
952.02

564.93
778.04
955.89

564.41
788.67
952.64

555.88
781.28
987.87

557.78
778.74
957.25

565.57
773.53
936.51

554.60
790.34
965.33

556.08
783.40
910.31

557.93
780.96
932.61

517.08
363.15

531.99
381.75

530.79
383.17

525.50
375.82

528.96
389.12

540.43
390.75

537.37
389.44

539.72
390.10

543.84
382.65

544.16
384.67

543.05
373.64

538.15
375.51

529.20
369.17

539.98
370.39

543.97
379.85

TRANSPORTATION AND
PUBLIC UTILITIES......................

607.20

626.09

622.93

634.65

627.71

631.20

638.82

632.56

638.06

632.59

637.18

362.70

641.00

632.93

642.14

WHOLESALE TRADE....................

558.80

585.20

582.12

592.48

581.78

588.67

597.92

593.28

596.71

589.72

590.44

592.04

607.44

598.59

601.65

Durable goods Durable goods
Lumber and wood products.......
Furniture and fixtures................
Stone, clay, and glass
products..................................
Primary metal industries............
Blast furnaces and basic
steel products........................
Fabricated metal products.........
Industrial machinery and
equipment..............................
Electronic and other electrical
equipment...............................
Transportation equipment.........
Motor vehicles and
equipment.............................
Instruments and related
products……………………….
Miscellaneous manufacturing....

RETAIL TRADE......…………..........

263.61

273.39

275.13

280.12

277.60

275.90

277.15

274.85

278.89

273.26

276.05

276.62

281.66

280.69

284.60

FINANCE, INSURANCE,
AND REAL ESTATE....................

529.24

547.04

540.47

550.87

539.64

545.47

557.78

549.00

553.05

556.20

567.37

564.12

580.23

565.78

569.43

SERVICES.......................................

435.86

454.86

448.64

456.12

452.05

455.00

464.22

462.92

467.16

464.80

471.72

472.05

476.77

469.95

472.32

p

= preliminary.
NOTE: See "Notes on the data" for a description of the most recent benchmark revision. Dash indicates data not available

Monthly Labor Review

August 2001

97

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, 356 industries
Over 1-month span:
1998..............................................
1999..............................................
2000..............................................
2001..............................................

63.2
55.1
55.7
53.7

56.2
59.6
59.3
50.4

59.3
52.8
61.0
55.8

60.2
57.2
54.2
45.0

58.9
58.2
47.7
46.0

57.1
54.2
60.5
44.9

55.4
57.1
57.8
–

58.4
54.4
55.1
–

54.8
55.2
52.0
–

55.0
57.9
54.8
–

58.2
59.9
55.1
–

56.4
56.8
54.2
–

Over 3-month span:
1998..............................................
1999..............................................
2000..............................................
2001..............................................

65.3
60.8
61.6
51.7

66.1
57.8
63.3
54.1

64.6
58.5
61.9
48.6

65.7
55.8
56.2
49.2

62.2
58.1
55.1
43.1

57.9
57.9
57.9
44.6

57.5
57.2
61.5
–

58.4
59.2
56.4
–

59.1
59.8
54.1
–

59.2
59.1
53.3
–

59.3
61.0
55.7
–

59.2
60.6
53.3
–

Over 6-month span:
1998..............................................
1999..............................................
2000..............................................
2001..............................................

70.4
59.8
63.5
52.0

67.4
59.8
60.6
50.6

65.0
58.2
62.6
48.0

62.5
60.3
63.7
46.6

63.6
56.7
61.5
–

60.5
59.2
55.5
–

59.2
61.8
56.1
–

58.6
60.8
58.6
–

57.9
62.2
54.2
–

59.6
61.2
54.8
–

60.6
62.3
51.8
–

59.9
64.9
54.2
–

Over 12-month span:
1998..............................................
1999..............................................
2000..............................................
2001..............................................

69.7
61.2
62.5
50.0

67.6
60.2
63.0
–

67.4
58.2
61.8
–

66.0
60.8
59.5
–

64.0
60.8
58.4
–

62.7
61.6
56.8
–

61.9
62.2
55.7
–

62.0
61.3
56.5
–

60.9
63.9
54.2
–

59.3
63.0
53.4
–

60.8
61.3
53.0
–

58.8
60.9
51.8
–

Manufacturing payrolls, 139 industries
Over 1-month span:
1998..............................................
1999..............................................
2000..............................................
2001..............................................

57.4
46.9
44.9
37.9

51.5
44.5
56.6
32.4

53.7
43.0
55.5
41.5

53.3
42.3
46.7
31.3

43.8
50.4
41.2
29.4

48.2
39.3
54.8
33.1

38.2
51.5
53.7
–

51.5
39.3
38.6
–

41.9
45.2
34.6
–

41.5
46.3
41.5
–

41.2
53.3
43.8
–

43.4
46.7
44.1
–

Over 3-month span:
1998..............................................
1999..............................................
2000..............................................
2001..............................................

59.6
41.2
50.0
28.3

59.6
39.0
54.0
29.4

55.9
38.2
52.9
24.6

50.4
41.8
42.3
26.5

46.7
40.8
43.0
22.1

37.9
45.2
48.5
26.1

41.5
39.0
48.2
–

41.5
45.2
33.6
–

41.9
40.8
28.7
–

38.2
44.9
30.5
–

36.8
46.3
39.0
–

40.8
46.0
35.7
–

Over 6-month span:
1998..............................................
1999..............................................
2000..............................................
2001..............................................

63.2
36.0
51.5
26.8

54.4
38.2
44.5
25.4

50.4
37.5
48.5
19.9

40.4
41.2
55.1
21.0

44.5
36.8
43.8
–

40.1
39.7
34.9
–

37.5
43.0
33.5
–

36.4
41.5
34.6
–

34.9
46.0
30.1
–

40.1
40.4
29.4
–

37.1
46.3
25.0
–

34.2
51.5
27.9
–

Over 12-month span:
1998..............................................
1999..............................................
2000..............................................
2001..............................................

54.8
38.6
46.3
20.6

52.2
34.6
45.2
–

51.8
32.4
41.2
–

46.7
36.0
37.9
–

40.4
37.9
33.8
–

40.1
39.0
31.3
–

38.2
40.1
31.3
–

37.5
40.4
31.3
–

36.4
44.5
27.6
–

34.6
46.0
25.4
–

35.7
44.9
24.3
–

34.2
44.5
21.3
–

Dash indicates data not available.
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

98

Monthly Labor Review

August 2001

decreasing employment. Data for the 2 most recent months
shown in each span are preliminary. See the "Definitions" in this
section. See "Notes on the data" for a description of the most
recent benchmark revision.

18. Annual data: Employment status of the population
[Numbers in thousands]
1992

1993

1994

1995

1996

1997

1998

1999

2000

Civilian noninstitutional population...........
Civilian labor force............................……
Labor force participation rate..............

Employment status

192,805
128,105
66.4

194,838
129,200
66.3

196,814
131,056
66.6

198,584
132,304
66.6

200,591
133,943
66.8

203,133
136,297
67.1

205,220
137,673
67.1

207,753
139,368
67.1

209,699
140,863
67.2

Employed............................…………
Employment-population ratio..........
Agriculture............................………
Nonagricultural industries.............

118,492
61.5
3,247
115,245

120,259
61.7
3,115
117,144

123,060
62.5
3,409
119,651

124,900
62.9
3,440
121,460

126,708
63.2
3,443
123,264

129,558
63.8
3,399
126,159

131,463
64.1
3,378
128,085

133,488
64.3
3,281
130,207

135,208
64.5
3,305
131,903

Unemployed............................………
Unemployment rate.........................
Not in the labor force............................…

9,613
7.5
64,700

8,940
6.9
65,638

7,996
6.1
65,758

7,404
5.6
66,280

7,236
5.4
66,647

6,739
4.9
66,837

6,210
4.5
67,547

5,880
4.2
68,385

5,655
4.0
68,836

19. Annual data: Employment levels by industry
[In thousands]
1992

1993

1994

1995

1996

1997

1998

1999

2000

Total employment............................…………
Private sector............................……………
Goods-producing....................................
Mining............................………………
Construction............................…………
Manufacturing............................………

Industry

108,601
89,956
23,231
635
4,492
18,104

110,713
91,872
23,352
610
4,668
18,075

114,163
95,036
23,908
601
4,986
18,321

117,191
97,885
24,265
581
5,160
18,524

119,608
100,189
24,493
580
5,418
18,495

122,690
103,133
24,962
596
5,691
18,675

125,865
106,042
25,414
590
6,020
18,805

128,916
108,709
25,507
539
6,415
18,552

131,759
111,079
25,709
543
6,698
18,469

Service-producing............................……
Transportation and public utilities........
Wholesale trade............................……
Retail trade............................…………
Finance, insurance, and real estate....
Services............................………………

85,370
5,718
5,997
19,356
6,602
29,052

87,361
5,811
5,981
19,773
6,757
30,197

90,256
5,984
6,162
20,507
6,896
31,579

92,925
6,132
6,378
21,187
6,806
33,117

95,115
6,253
6,482
21,597
6,911
34,454

97,727
6,408
6,648
21,966
7,109
36,040

100,451
6,611
6,800
22,295
7,389
37,533

103,409
6,834
6,911
22,848
7,555
39,055

106,050
7,019
7,024
23,307
7,560
40,460

Government............................…………
Federal............................……………
State............................………………
Local............................………………

18,645
2,969
4,408
11,267

18,841
2,915
4,488
11,438

19,128
2,870
4,576
11,682

19,305
2,822
4,635
11,849

19,419
2,757
4,606
12,056

19,557
2,699
4,582
12,276

19,823
2,686
4,612
12,525

20,206
2,669
4,709
12,829

20,681
2,777
4,785
13,119

NOTE: See "Notes on the data" for a description of the most recent benchmark revision.

Monthly Labor Review

August 2001

99

Current Labor Statistics:

Labor Force Data

20. Annual data: Average hours and earnings of production or nonsupervisory workers on nonfarm
payrolls, by industry
Industry

1992

1993

1994

1995

1996

1997

1998

1999

2000

Private sector:
Average weekly hours.......……................................
Average hourly earnings (in dollars).........................
Average weekly earnings (in dollars)........................

34.4
10.57
363.61

34.5
10.83
373.64

34.7
11.12
385.86

34.5
11.43
394.34

34.4
11.82
406.61

34.6
12.28
424.89

34.6
12.78
442.19

34.5
13.24
456.78

34.5
13.75
474.38

Mining:
Average weekly hours............................................
Average hourly earnings (in dollars).......................
Average weekly earnings (in dollars)......................

43.9
14.54
638.31

44.3
14.60
646.78

44.8
14.88
666.62

44.7
15.30
683.91

45.3
15.62
707.59

45.4
16.15
733.21

43.9
16.91
742.35

43.2
17.05
736.56

43.1
17.24
743.04

Construction:
Average weekly hours............................................
Average hourly earnings (in dollars).......................
Average weekly earnings (in dollars)......................

38.0
14.15
537.70

38.5
14.38
553.63

38.9
14.73
573.00

38.9
15.09
587.00

39.0
15.47
603.33

39.0
16.04
625.56

38.9
16.61
646.13

39.1
17.19
672.13

39.3
17.88
702.68

Manufacturing:
Average weekly hours............................................
Average hourly earnings (in dollars).......................
Average weekly earnings (in dollars)......................

41.0
11.46
469.86

41.4
11.74
486.04

42.0
12.07
506.94

41.6
12.37
514.59

41.6
12.77
531.23

42.0
13.17
553.14

41.7
13.49
562.53

41.7
13.90
579.63

41.6
14.38
598.21

Transportation and public utilities:
Average weekly hours............................................
Average hourly earnings (in dollars).......................
Average weekly earnings (in dollars)......................

38.3
13.43
514.37

39.3
13.55
532.52

39.7
13.78
547.07

39.4
14.13
556.72

39.6
14.45
572.22

39.7
14.92
592.32

39.5
15.31
604.75

38.7
15.69
607.20

38.6
16.22
626.09

Wholesale trade:
Average weekly hours..………................................
Average hourly earnings (in dollars).......................
Average weekly earnings (in dollars)......................

38.2
11.39
435.10

38.2
11.74
448.47

38.4
12.06
463.10

38.3
12.43
476.07

38.3
12.87
492.92

38.4
13.45
516.48

38.3
14.07
538.88

38.3
14.58
558.80

38.5
15.20
585.20

Retail trade:
Average weekly hours............................................
Average hourly earnings (in dollars).......................
Average weekly earnings (in dollars)......................

28.8
7.12
205.06

28.8
7.29
209.95

28.9
7.49
216.46

28.8
7.69
221.47

28.8
7.99
230.11

28.9
8.33
240.74

29.0
8.74
253.46

29.0
9.09
263.61

28.9
9.46
273.39

Finance, insurance, and real estate:
Average weekly hours............................................
Average hourly earnings (in dollars).......................
Average weekly earnings (in dollars)......................

35.8
10.82
387.36

35.8
11.35
406.33

35.8
11.83
423.51

35.9
12.32
442.29

35.9
12.80
459.52

36.1
13.34
481.57

36.4
14.07
512.15

36.2
14.62
529.24

36.3
15.07
547.04

Services:
Average weekly hours............................................
Average hourly earnings (in dollars).......................
Average weekly earnings (in dollars)......................

32.5
10.54
342.55

32.5
10.78
350.35

32.5
11.04
358.80

32.4
11.39
369.04

32.4
11.79
382.00

32.6
12.28
400.33

32.6
12.84
418.58

32.6
13.37
435.86

32.7
13.91
454.86

100

Monthly Labor Review

August 2001

21. Employment Cost Index, compensation,1 by occupation and industry group
[June 1989 = 100]
1999

2000

2001

Series
June
2

Civilian workers ……….…….........…………………………………….…

Sept.

Dec.

Mar.

June

Sept.

Dec.

Mar.

June

Percent change
3
12
months
months
ended
ended
June 2001

141.8

143.3

144.6

146.5

148.0

149.5

150.6

152.5

153.8

0.9

3.9

143.3
142.2
145.4
143.4
138.3
142.4

145.0
143.9
147.3
144.7
139.5
143.1

146.3
145.3
148.6
146.1
140.6
144.8

148.4
146.7
150.5
148.6
142.7
146.0

149.9
148.3
151.9
150.1
144.1
147.1

151.5
150.0
153.7
151.8
145.6
148.5

152.5
151.3
154.6
152.8
146.5
150.0

154.4
153.2
156.6
155.3
148.2
152.0

156.0
154.3
158.6
156.8
149.3
153.3

1.0
.7
1.3
1.0
.7
.9

4,1
4.0
4.4
4.5
3.6
4.2

140.0
140.9
142.4
143.2
141.4
142.2
141.7
141.5
141.9

141.2
142.1
144.0
145.1
142.7
143.4
144.6
142.4
143.4

142.5
143.6
145.3
146.5
144.3
145.0
145.8
144.4
144.7

144.9
146.0
147.1
148.0
145.9
146.3
146.5
145.7
146.6

146.6
147.5
148.4
149.3
147.5
147.7
146.8
146.1
148.0

148.0
148.7
150.1
151.2
149.0
149.5
149.7
146.9
149.6

148.8
149.3
151.1
152.4
150.7
151.3
150.6
148.3
150.7

150.7
152.2
151.352.6154.4
153.0
155.4
154.3
154.6
152.5
155.6
153.2
152.2
151.7
151.9
150.6
154.0
152.6
154.0

1.0
.9
.9
.7
1.4
1.6
.3
.9
.9

3.8
3.5
4.0
4.1
4.8
5.3
3.7
4.0
4.1

Private industry workers……….…….........…………………
Excluding sales occupations….......................................

142.0
141.9

143.3
143.2

144.6
144.5

146.8
146.5

148.5
148.2

149.9
149.8

150.9
150.9

153.0
153.0

154.5
154.4

1.0
.9

4.0
4.2

Workers, by occupational group:
White-collar workers.........................................................
Excluding sales occupations….....................................
Professional specialty and technical occupations….......
Executive, adminitrative, and managerial occupations…
Sales occupations…………............................................
Administrative support occupations, including clerical…
Blue-collar workers…........................................................
Precision production, craft, and repair occupations........
Machine operators, assemblers, and inspectors............
Transportation and material moving occupations...........
Handlers, equipment cleaners, helpers, and laborers....

144.1
144.5
144.1
145.8
142.6
143.7
138.2
138.4
138.4
133.6
142.3

145.6
146.0
145.2
147.7
144.1
145.0
139.4
139.6
139.9
134.4
143.2

146.9
147.3
146.7
149.1
145.3
146.2
140.5
140.6
141.4
135.2
144.4

149.3
149.4
148.4
151.1
148.9
149.0
142.6
142.3
144.0
137.5
146.4

151.1
151.3
150.7
152.7
150.3
150.6
144.1
144.1
145.0
138.6
148.1

152.6
152.9
152.2
154.4
151.2
152.3
145.5
145.8
146.0
139.9
149.4

153.6
154.1
153.7
155.3
151.4
153.4
146.4
146.7
146.8
141.1
150.4

155.7
156.5
156.3
157.3
152.3
156.1
148.2
148.7
148.3
142.6
152.2

157.4
158.1
157.5
159.4
154.5
157.7
149.3
149.7
149.1
143.9
153.4

1.1
1.0
.8
1.3
1.4
1.0
.7
.7
.5
.9
.8

4.2
4.5
4.5
4.4
2.8
4.7
3.6
3.9
2.8
3.8
3.6

Workers, by occupational group:
White-collar workers...........................................................
Professional specialty and technical….............................
Executive, adminitrative, and managerial…………...........
Administrative support, including clerical…………............
Blue-collar workers…..........................................................
Service occupations............................................................
Workers, by industry division:
Goods-producing................................................................
Manufacturing…...............................................................
Service-producing...............................................................
Services..............…..........................................................
Health services...............................................................
Hospitals..............….....................................................
Educational services.......................................................
3

Public administration ……….…………………………………………
Nonmanufacturing..............................................................

Service occupations…………...........................................

140.6

141.0

142.6

143.9

145.4

146.6

148.1

150.0

151.3

.9

4.1

Production and nonsupervisory occupations ……….………

140.8

141.9

143.1

145.3

146.9

148.4

149.5

151.4

152.7

.9

3.9

Workers, by industry division:
Goods-producing..............................................................
Excluding sales occupations......................................
White-collar occupations...............................................
Excluding sales occupations......................................
Blue-collar occupations.................................................
Construction…................................................................
Manufacturing….............................................................
White-collar occupations...............................................
Excluding sales occupations......................................
Blue-collar occupations.................................................
Durables…......................................................................
Nondurables…................................................................

139.9
139.3
142.7
141.3
138.3
136.9
140.9
143.0
141.3
139.4
141.0
140.4

141.1
140.5
143.9
142.5
139.4
137.9
142.1
144.3
142.5
140.5
142.3
141.5

142.5
141.8
145.5
143.9
140.7
138.7
143.6
145.8
143.8
142.1
144.0
142.8

144.8
144.2
148.1
146.5
142.8
140.8
146.0
148.2
146.2
144.4
146.5
144.9

146.6
145.9
150.1
148.4
144.4
143.2
147.5
150.2
148.2
145.6
148.3
146.0

147.9
147.2
151.3
149.6
145.8
145.1
148.7
151.4
149.3
146.7
149.4
147.5

148.8
148.2
151.9
150.5
146.8
146.7
149.3
151.5
149.7
147.8
150.1
147.7

150.7
150.1
154.5
153.0
148.2
148.2
151.3
154.2
152.2
149.1
151.8
150.4

152.1
151.5
156.5
155.0
149.2
150.3
152.6
156.0
154.0
150.0
153.1
151.6

.9
.9
1.3
1.3
.7
1.4
.9
1.2
1.2
.6
.9
.8

3.8
3.8
4.3
4.4
3.4
5.0
3.5
3.9
3.9
3.0
3.2
3.8

Service-producing..............................................................
Excluding sales occupations......................................
White-collar occupations...............................................
Excluding sales occupations......................................
Blue-collar occupations.................................................
Service occupations......................................................
Transportation and public utilities…................................
Transportation…...........................................................
Public utilities................................................................
Communications........................................................
Electric, gas, and sanitary services............................
Wholesale and retail trade…..........................................
Excluding sales occupations......................................
Wholesale trade…........................................................
Excluding sales occupations......................................
Retail trade…................................................................
General merchandise stores…...................................
Food stores….............................................................

142.8
143.3
144.3
145.5
137.8
140.5
140.9
138.1
144.6
144.9
144.2
141.1
141.9
144.6
144.0
139.1
135.6
135.7

144.1
144.6
145.8
147.0
139.1
140.8
141.8
138.7
145.7
146.1
145.1
142.2
142.8
146.3
145.8
140.0
137.2
137.0

145.3
145.9
147.0
148.3
139.8
142.4
142.3
139.5
146.1
146.0
146.1
143.5
144.3
148.5
147.4
140.7
138.3
138.1

147.4
147.7
149.3
150.3
141.8
143.6
143.9
140.4
148.6
148.4
148.9
145.6
146.4
150.0
149.6
143.2
139.7
140.1

149.1
149.4
151.0
152.1
143.1
145.1
145.7
141.8
150.9
150.9
151.0
147.3
148.1
151.8
151.1
144.8
141.0
142.5

150.6
151.1
152.6
153.9
144.5
146.3
147.4
142.8
153.5
153.9
152.9
148.3
149.6
152.1
152.7
146.2
142.2
143.4

151.7
152.2
153.7
155.1
145.3
147.9
148.3
143.9
154.1
154.7
153.4
149.4
150.6
154.4
154.9
146.6
144.4
144.5

153.8
154.6
155.8
157.5
147.7
149.6
150.5
145.4
157.3
158.3
156.0
151.0
152.6
155.1
156.9
148.7
147.3
146.1

155.3
156.0
157.4
159.1
148.7
150.8
152.4
146.9
159.8
161.1
158.1
152.6
153.9
157.8
158.5
149.7
149.4
148.2

1.0
.9
1.0
1.0
.7
.8
1.3
1.0
1.6
1.8
.3
1.1
.9
1.7
1.0
.7
1.4
1.4

4.2
4.4
4.2
4.6
3.9
3.9
4.6
3.6
5.9
6.8
4.7
3.6
3.9
4.0
4.9
3.4
6.0
4.0

4

See footnotes at end of table.

Monthly Labor Review

August 2001

101

Current Labor Statistics:

Compensation & Industrial Relations

21. Continued—Employment Cost Index, compensation,1 by occupation and industry group
[June 1989 = 100]
1999

2000

2001

Series
June

Sept.

Dec.

Mar.

June

Sept.

Dec.

Mar.

June

Percent change
3
12
months
months
ended
ended
June 2001

Finance, insurance, and real estate…............................

145.8

147.6

148.3

152.0

153.1

155.2

155.7

157.9

159.5

1.0

4.2

Excluding sales occupations…..................................
Banking, savings and loan, and other credit agencies..
Insurance......................................................................
Services..........................................................................
Business services…......................................................
Health services.............................................................
Hospitals….................................................................
Educational services.....................................................
Colleges and universities…........................................

148.8
155.4
144.0
144.6
148.7
141.4
142.1
148.7
149.6

151.0
159.3
144.5
146.1
150.7
142.6
143.0
152.2
152.6

151.6
159.8
145.8
147.6
151.9
144.2
144.6
153.0
153.3

154.2
162.7
149.9
149.4
154.2
145.8
145.8
154.0
154.6

155.5
164.2
151.3
151.2
156.3
147.5
147.5
154.9
155.5

157.4
165.8
154.8
152.9
157.5
149.0
149.2
158.8
158.6

158.4
166.5
155.2
154.1
158.4
150.6
151.1
159.9
159.2

161.2
170.8
157.6
156.5
160.5
152.7
153.5
162.3
162.2

163.1
172.7
159.3
157.8
163.0
154.7
155.9
162.6
162.6

1.2
1.1
1.1
.8
1.6
1.3
1.6
.2
.2

4.9
5.2
5.3
4.4
4.3
4.9
5.7
5.0
4.6

Nonmanufacturing..........................................................

142.0

143.4

144.5

146.7

148.4

150.0

151.1

153.1

154.7

1.0

4.2

White-collar workers.....................................................
Excluding sales occupations….................................
Blue-collar occupations….............................................
Service occupations………….......................................

144.1
145.3
136.8
140.4

145.6
146.8
138.0
140.7

146.9
148.1
138.7
142.3

149.2
150.2
140.6
143.5

151.0
152.0
142.3
145.1

152.6
153.8
143.9
146.3

153.7
155.1
144.8
147.8

155.8
157.5
146.9
149.5

157.5
159.1
148.1
150.7

1.1
1.0
.8
.8

4.3
4.7
4.1
3.9

State and local government workers...................................

141.0

143.1

144.6

145.5

145.9

147.8

148.9

150.3

151.2

.6

3.6

140.2
139.3
142.8
141.3
139.5

142.6
142.0
144.5
143.0
140.9

144.0
143.2
146.1
145.0
142.5

144.9
144.1
147.0
145.9
143.7

145.3
144.5
147.2
146.5
144.2

147.3
146.6
149.2
148.3
145.9

148.3
147.4
150.7
149.4
147.2

149.5
148.4
152.4
150.7
148.6

150.4
149.2
153.7
151.6
149.0

.6
.5
.9
.6
.3

3.5
3.3
4.4
3.5
3.3

140.5
140.3
142.0
142.7
140.3
140.6
140.0
142.1
141.5

143.2
142.6
144.2
144.8
143.1
143.5
142.9
144.8
142.4

144.5
143.8
145.8
146.3
144.4
144.7
144.1
146.5
144.4

145.2
145.2
147.3
147.9
145.0
145.3
144.5
147.4
145.7

145.5
145.8
147.9
148.4
145.2
145.5
144.7
147.6
146.1

148.0
147.6
150.0
150.7
147.9
148.2
147.3
150.5
146.9

148.9
148.8
151.6
152.0
148.7
149.0
148.1
151.7
148.3

149.9
150.1
152.1
152.2
149.6
149.9
148.5
153.7
150.6

150.6
151.9
154.4
154.7
150.1
150.5
149.0
154.3
151.9

.5
1.2
1.5
1.6
.3
.4
.3
.4
.9

3.5
4.2
4.4
4.2
3.4
3.4
3.0
4.5
4.0

Workers, by occupational group:
White-collar workers...........................................................
Professional specialty and technical….............................
Executive, administrative, and managerial………….........
Administrative support, including clerical…………............
Blue-collar workers…..........................................................
Workers, by industry division:
Services............................................................................
5

Services excluding schools ……….………………………………
Health services.............................................................
Hospitals....................................................................
Educational services.....................................................
Schools......................................................................
Elementary and secondary…..................................
Colleges and universities….....................................
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.

102

Monthly Labor Review

August 2001

3

Consists of legislative, judicial, administrative, and regulatory activities.

4

This series has the same industry and occupational coverage as the Hourly
Earnings index, which was discontinued in January 1989.
5

Includes, for example, library, social, and health services.

22. Employment Cost Index, wages and salaries, by occupation and industry group
[June 1989 = 100]
1999

2000

2001

Series
June
1

Sept.

Dec.

Mar.

June

Sept.

Dec.

Mar.

June

Percent change
3
12
months
months
ended
ended
June 2001

Civilian workers ……….…….........…………………………………….…

139.8

141.3

142.5

144.0

145.4

147.0

147.9

149.5

150.8

0.9

3.7

Workers, by occupational group:
White-collar workers...........................................................
Professional specialty and technical….............................
Executive, adminitrative, and managerial…………...........
Administrative support, including clerical…………............
Blue-collar workers…..........................................................
Service occupations............................................................

141.6
141.0
143.8
140.9
135.8
139.4

143.3
142.6
145.9
142.3
137.0
140.1

144.6
144.0
147.2
143.5
137.9
141.7

146.2
144.9
148.6
145.5
139.2
143.0

147.6
146.4
149.9
146.9
140.6
144.0

149.2
148.3
151.6
148.5
142.0
145.7

150.2
149.6
152.4
149.6
142.9
147.1

151.7
151.1
154.0
151.6
144.7
148.6

153.1
152.155.8
152,7
146.0
149.7

.9
.6
1.2
.8
.9
.7

3.7
3.8
3.9
4.0
3.8
4.0

Workers, by industry division:
Goods-producing................................................................
Manufacturing…...............................................................
Service-producing...............................................................
Services..............…..........................................................
Health services...............................................................
Hospitals..............….....................................................
Educational services.......................................................

137.4
139.0
140.7
142.3
139.7
138.8
140.6

138.6
140.2
142.3
144.1
140.9
140.1
143.7

139.7
141.5
143.5
145.5
142.5
141.6
144.7

141.3
142.9
145.0
146.6
143.8
142.6
145.3

143.0
144.4
146.3
147.9
145.3
143.8
145.6

144.3
145.7
148.0
149.9
146.7
145.6
148.9

145.3
146.5
148.9
151.0
148.3
147.3
149.6

147.0
148.5
150.5
152.6
149.8
148.8
150.5

147,6
150.0
151.7
153.6
151.8
151.2
151.0

1.1
1.0
.8
.7
1.3
1.6
.3

3.9
3.9
3.7
3.9
4.5
5.1
3.7

137.8
139.9

139.5
141.5

141.5
142.6

142.5
144.2

142.9
145.5

144.6
147.2

146.1
148.1

147.6
149.7

148.7
149.7

.7
.8

4.1
3.7

Private industry workers……….…….........…………………
Excluding sales occupations….......................................

139.7
139.6

141.0
140.8

142.2
142.0

143.9
143.5

145.4
145.1

146.8
146.5

147.7
147.6

149.4
149.5

150.9
150.8

1.0.9
1.3

3.8
3.9

Workers, by occupational group:
White-collar workers.........................................................
Excluding sales occupations….....................................
Professional specialty and technical occupations….......
Executive, adminitrative, and managerial occupations…
Sales occupations…………............................................
Administrative support occupations, including clerical…
Blue-collar workers…........................................................
Precision production, craft, and repair occupations........
Machine operators, assemblers, and inspectors............
Transportation and material moving occupations...........
Handlers, equipment cleaners, helpers, and laborers....

142.1
142.5
141.8
144.3
140.5
141.4
135.6
135.6
136.7
131.0
138.3

143.5
143.9
142.6
146.4
142.1
142.7
136.8
136.7
138.3
131.9
139.4

144.8
145.2
144.1
147.6
143.3
143.8
137.7
137.5
139.5
132.7
140.4

146.6
146.7
145.1
149.2
146.7
146.0
139.1
138.9
140.7
134.1
141.8

148.3
148.5
147.3
150.7
147.9
147.5
140.5
140.6
141.6
135.2
143.6

149.7
149.9
148.6
152.3
149.0
149.1
141.9
142.0
142.9
136.5
145.0

150.6
151.1
150.2
153.0
148.7
150.1
142.8
142.8
143.7
137.6
146.2

152.3
153.0
152.1
154.7
149.2
152.3
144.6
144.6
145.6
139.5
148.0

153.8
154.4
153.2
156.5
151.5
153.6
145.9
145.7
146.9
140.7
149.8

1.0
.8
.7
1.2
1.5
.9
.9
.8
.9
.9
1.2

3.7
4.0
4.0
3.8
2.4
4.1
3.8
3.6
3.7
4.1
4.3

2

Public administration ……….…………………………………………
Nonmanufacturing..............................................................

Service occupations…………...........................................

137.8

138.0

139.6

141.0

142.5

143.5

144.9

146.4

147.5

.8

3.5

Production and nonsupervisory occupations ……….………

138.2

139.3

140.4

142.1

143.7

145.0

146.0

147.7

149.0

.9

3.7

Workers, by industry division:
Goods-producing..............................................................
Excluding sales occupations......................................
White-collar occupations...............................................
Excluding sales occupations......................................
Blue-collar occupations.................................................
Construction…................................................................
Manufacturing….............................................................
White-collar occupations...............................................
Excluding sales occupations......................................
Blue-collar occupations.................................................
Durables…......................................................................
Nondurables…................................................................

137.3
136.6
140.5
138.8
135.4
131.9
139.0
141.4
139.6
137.2
139.1
138.7

138.5
137.8
141.7
140.1
136.6
133.0
140.2
142.7
140.8
138.4
140.4
139.7

139.7
138.9
143.0
141.3
137.6
133.6
141.5
144.0
142.0
139.7
141.8
140.9

141.3
140.5
145.0
143.2
139.0
136.0
142.9
145.8
143.7
140.8
143.0
142.7

143.0
142.1
146.8
144.9
140.5
138.0
144.4
147.7
145.6
142.0
144.7
143.9

144.3
143.4
147.9
146.0
142.0
139.4
145.7
148.7
146.6
143.4
146.1
145.0

145.2
144.6
148.7
147.2
143.1
140.7
146.5
149.2
147.5
144.6
147.3
145.4

147.0
146.3
150.5
148.9
144.7
142.1
148.5
151.1
149.9
146.4
149.0
147.5

148.6
147.8
152.3
150.5
146.1
143.9
150.0
152.7
150.5
147.8
150.5
149.0

1.1
1.0
1.2
1.1
1.0
1.3
1.0
1.1
.9
1.0
1.0
1.0

3.9
4.0
3.7
3.9
4.0
4.3
3.9
3.4
3.4
4.1
4.0
3.5

Service-producing..............................................................
Excluding sales occupations......................................
White-collar occupations...............................................
Excluding sales occupations......................................
Blue-collar occupations.................................................
Service occupations......................................................
Transportation and public utilities…................................
Transportation…...........................................................
Public utilities................................................................
Communications........................................................
Electric, gas, and sanitary services............................
Wholesale and retail trade…..........................................
Excluding sales occupations......................................
Wholesale trade…........................................................
Excluding sales occupations......................................
Retail trade…................................................................
General merchandise stores…...................................
Food stores….............................................................

140.8
141.4
142.3
143.7
135.9
137.8
136.8
133.7
140.6
141.1
140.0
139.6
141.1
142.3
143.0
138.3
134.3
132.8

142.1
142.6
143.8
145.1
137.0
138.0
137.5
134.4
141.5
141.9
140.9
140.7
141.8
144.3
144.8
138.9
135.6
133.9

143.3
143.8
145.0
146.4
137.8
139.6
137.9
134.9
141.8
142.2
141.3
142.0
143.3
146.5
146.4
139.6
136.7
134.9

145.0
145.3
146.9
147.8
139.1
141.1
138.5
134.9
143.2
143.4
143.0
143.8
145.2
147.4
147.9
142.1
137.8
136.7

146.5
146.9
148.5
149.6
140.3
142.5
140.0
136.2
144.9
145.0
144.7
145.5
146.8
149.4
149.7
143.5
138.5
139.5

147.9
148.3
150.0
151.2
141.6
143.5
141.3
137.4
146.4
146.7
145.9
146.4
148.2
149.6
151.3
144.8
139.7
140.2

148.9
149.4
150.9
152.3
142.2
144.8
142.3
138.6
147.1
147.4
146.6
147.4
149.0
151.6
153.2
145.2
142.2
141.6

150.5
151.3
152.5
154.3
144.3
146.1
143.7
139.8
148.7
149.2
148.1
148.4
150.7
151.6
154.9
146.9
143.8
143.3

151.9
152.6
154.0
155.6
145.3
147.2
145.7
141.6
151.0
151.8
149.9
150.1
151.9
154.5
156.5
147.8
145.5
144.5

.9
.9
1.0
.8
.7
.8
1.4
1.3
1.5
1.7
1.2
1.1
.8
1.9
1.0
.6
1.2
.8

3.7
3.9
3.7
4.0
3.6
3.3
4.1
4.0
4.2
4.7
3.6
3.2
3.5
3.4
4.5
3.0
5.1
3.6

3

See footnotes at end of table.

Monthly Labor Review

August 2001

103

Current Labor Statistics:

Compensation & Industrial Relations

22. Continued—Employment Cost Index, wages and salaries, by occupation and industry group
[June 1989 = 100]
1999

2000

2001

Series
June

Sept.

Dec.

Mar.

June

Sept.

Dec.

Mar.

June

Percent change
3
12
months
months
ended
ended
June 2001

Finance, insurance, and real estate…............................
Excluding sales occupations…..................................
Banking, savings and loan, and other credit agencies..
Insurance......................................................................
Services..........................................................................
Business services…......................................................
Health services.............................................................
Hospitals….................................................................
Educational services.....................................................
Colleges and universities…........................................

142.4
144.8
154.5
139.8
143.2
146.3
139.6
138.3
144.2
144.4

144.5
147.5
159.2
140.2
144.5
148.5
140.6
139.3
147.5
147.2

145.2
148.0
159.6
141.5
146.0
149.8
142.2
140.9
148.2
147.9

148.7
150.2
162.0
145.5
147.4
152.0
143.5
141.8
148.9
148.9

149.5
151.5
163.3
146.6
149.1
154.1
145.3
143.3
149.6
149.4

151.7
153.3
165.0
150.7
150.6
155.3
146.6
144.9
153.4
152.5

151.7
154.1
165.7
150.8
151.8
156.0
148.1
146.8
154.3
152.9

153.9
156.6
169.4
152.4
153.8
158.2
149.8
148.5
155.4
154.1

154.6
157.6
170.8
153.3
155.0
160.8
151.8
151.0
156.1
155.0

0.5
.6
.8
.6
.8
1.6
1.3
1.7
.5
.6

3.4
4.0
4.6
4.6
4.0
4.3
4.5
5.4
4.3
3.7

Nonmanufacturing..........................................................
White-collar workers.....................................................
Excluding sales occupations….................................
Blue-collar occupations….............................................
Service occupations………….......................................

139.7
142.0
143.2
134.0
137.7

141.0
143.5
144.6
135.1
137.9

142.1
144.7
145.9
135.8
139.5

143.9
146.5
147.4
137.4
140.9

145.5
148.2
149.1
138.9
142.4

146.9
149.6
150.7
140.3
143.4

147.9
150.6
151.9
140.9
144.7

149.5
152.3
153.9
142.8
146.0

150.9
153.8
155.3
143.9
147.1

.9
1.0
.9
.8
.8

3.7
3.8
4.2
3.6
3.3

State and local government workers............…………………

139.6

142.2

143.5

144.3

144.7

147.2

148.3

150.2

151.2

.5

3.7

Workers, by occupational group:
White-collar workers...........................................................
Professional specialty and technical….............................
Executive, administrative, and managerial………….........
Administrative support, including clerical…………............
Blue-collar workers…..........................................................

139.3
139.4
140.5
137.5
137.6

142.1
142.5
142.7
139.6
139.4

143.4
143.6
144.3
141.7
140.7

144.1
144.3
144.9
142.4
141.5

144.5
144.7
145.1
143.0
142.1

147.1
147.4
147.3
145.0
143.9

148.0
148.2
148.8
146.2
145.1

149.0
149.1
150.1
147.0
146.0

149.8
149.8
151.5
147.6
146.5

.5
.5
.9
.4
.3

3.4
3.5
4.4
3.2
3.1

Workers, by industry division:
Services............................................................................
4

Services excluding schools ……….………………………………
Health services.............................................................
Hospitals....................................................................
Educational services.....................................................
Schools......................................................................
Elementary and secondary…..................................
Colleges and universities….....................................

139.9

142.9

144.0

144.6

144.9

147.9

148.7

149.5

150.2

.5

3.7

139.6
140.4
140.6
139.8
140.0
139.9
139.8

142.1
142.8
142.8
142.9
143.1
143.1
142.6

143.2
144.2
144.1
144.0
144.2
144.1
144.4

144.3
145.3
145.3
144.5
144.7
144.5
144.9

144.8
145.7
145.6
144.8
144.9
144.6
145.6

146.7
147.7
147.7
148.0
148.1
147.9
148.3

147.9
149.3
149.2
148.7
148.9
148.5
149.5

149.1
149.9
149.5
149.5
149.7
149.0
151.4

150.7
151.9
151.8
150.0
150.2
149.5
151.8

1.1
1.3
1.5
.3
.3
.3
.3

4.1
4.3
4.3
3.6
3.7
3.4
4.3

2

Public administration ……….…………………………………………

137.8
139.5
141.5
142.5
142.9
144.6
146.1
147.6
148.7
.7
4.1
3
Consists of private industry workers (excluding farm and household workers) and
This series has the same industry and occupational coverage as the Hourly
State and local government (excluding Federal Government) workers.
Earnings index, which was discontinued in January 1989.
1

2

4

Consists of legislative, judicial, administrative, and regulatory activities.

Includes, for example, library, social, and health services.

23. Employment Cost Index, benefits, private industry workers by occupation and industry group
[June 1989 = 100]
1999

2000

2001

Series
June

Sept.

Dec.

Mar.

June

Sept.

Dec.

Mar.

June

Percent change
3
12
months
months
ended
ended
June 2001

147.3

148.6

150.2

153.8

155.7

157.5

158.6

161.5

163.2

1.1

4.8

Workers, by occupational group:
White-collar workers...........................................................
Blue-collar workers…..........................................................

149.4
143.6

151.0
144.8

152.5
146.2

156.3
150.0

158.5
151.6

160.4
153.1

161.5
154.1

165.2
155.7

167.4
156.7

1.3
.3

5.6
3.0

Workers, by industry division:
Goods-producing................................................................
Service-producing…...........................................................
Manufacturing.....................................................................
Nonmanufacturing…...........................................................

145.2
147.9
144.5
148.0

146.3
149.4
145.7
149.4

148.2
150.7
147.8
150.7

152.3
154.0
152.3
154.0

154.2
156.0
153.9
156.1

155.7
157.9
154.9
158.1

156.2
159.4
154.8
159.7

158.5
162.6
157.1
162.9

159.6
164.6
157.9
164.9

.7
1.2
.5
1.2

3.5
5.5
2.6
5.6

Private industry workers......................................................

104

Monthly Labor Review

August 2001

24. Employment Cost Index, private nonfarm workers by bargaining status, region, and area size
[June 1989 = 100]
1999

2000

2001

Series
June

Sept.

Dec.

Mar.

June

Sept.

Dec.

Mar.

June

Percent change
3
12
months
months
ended
ended
June 2001

COMPENSATION
Workers, by bargaining status

1

Union.......................................................................................
Goods-producing.................................................................
Service-producing…............................................................
Manufacturing......................................................................
Nonmanufacturing…............................................................

139.0
138.2
139.7
138.1
139.2

140.2
139.2
141.0
139.1
140.3

141.2
140.8
141.4
141.0
140.8

143.0
143.3
142.5
144.5
141.7

144.4
144.8
143.9
145.4
143.4

146.1
146.8
145.2
147.1
145.0

146.9
147.3
146.4
147.4
146.2

147.9
147.9
147.6
147.9
147.3

149.5
149.3
149.5
148.8
149.4

1.1
.9
1.3
.6
1.4

0.6
3.1
3.9
2.3
4.2

Nonunion.................................................................................
Goods-producing.................................................................
Service-producing…............................................................
Manufacturing......................................................................
Nonmanufacturing…............................................................

142.5
140.5
143.0
141.7
142.4

143.8
141.8
144.4
143.0
143.8

145.2
143.1
145.7
144.4
145.1

147.4
145.4
148.0
146.5
147.4

149.1
147.2
149.6
148.2
149.1

150.6
148.4
151.2
149.2
150.7

151.6
149.3
152.3
149.9
151.8

153.8
151.6
154.4
152.4
153.9

155.3
153.1
155.9
153.7
155.4

1.0
1.0
1.0
.9
1.0

4.2
4.0
4.2
3.7
4.2

141.5
140.7
143.6
142.1

143.2
141.8
145.0
143.3

144.3
143.0
146.3
144.7

146.3
145.0
148.9
147.0

147.6
146.7
150.7
148.8

149.3
147.6
152.2
150.8

150.3
148.6
153.3
151.8

151.6
151.1
154.8
154.3

153.7
152.3
156.0
156.0

1.4
.8
.8
1.1

4.1
3.8
3.5
4.8

142.0
141.8

143.3
143.1

144.7
143.6

146.9
146.0

148.6
147.7

150.1
148.8

151.0
150.3

153.1
152.1

154.6
153.7

1.0
1.1

4.0
4.1

Union.......................................................................................
Goods-producing.................................................................
Service-producing…............................................................
Manufacturing......................................................................
Nonmanufacturing…............................................................

134.7
133.8
135.8
134.7
134.6

135.7
134.9
136.8
135.8
135.6

136.5
136.1
137.2
137.5
135.9

137.2
137.2
137.6
138.8
136.4

138.5
138.4
138.9
139.7
137.8

140.0
140.2
140.1
141.4
139.2

141.2
141.3
141.5
142.6
140.4

142.1
142.4
142.2
143.9
141.1

143.7
144.2
143.7
145.5
142.7

1.1
1.3
1.1
1.1
1.1

3.8
4.2
3.5
4.2
3.6

Nonunion.................................................................................
Goods-producing.................................................................
Service-producing…............................................................
Manufacturing......................................................................
Nonmanufacturing…............................................................

140.7
138.8
141.3
140.5
140.5

142.0
140.0
142.6
141.7
141.8

143.3
141.1
143.9
142.9
143.0

145.1
142.9
145.8
144.4
145.0

146.7
144.7
147.3
146.1
146.6

148.1
145.8
148.7
147.2
148.0

149.0
146.8
149.6
148.0
148.9

150.8
148.8
151.4
150.1
150.7

152.2
150.3
152.7
151.6
152.0

.9
1.0
.9
1.0
.9

3.7
3.9
3.7
3.8
3.7

138.2
139.4
141.0
140.2

139.9
140.2
142.4
141.3

140.9
141.5
143.6
142.6

142.3
143.0
145.3
144.7

143.7
144.6
147.1
146.3

145.3
145.3
148.6
148.2

146.0
146.3
149.6
149.2

147.3
148.3
150.9
151.3

149.2
149.3
152.3
152.9

1.3
.7
.9
1.1

3.8
3.3
3.5
4.5

139.9
138.4

141.2
139.8

142.5
140.2

144.1
142.2

145.7
143.7

147.1
144.7

148.0
146.0

149.8
147.4

151.2
148.8

.9
.9

3.8
3.5

Workers, by region

1

Northeast................................................................................
South......................................................................................
Midwest (formerly North Central)............................................
West........................................................................................
Workers, by area size

1

Metropolitan areas..................................................................
Other areas.............................................................................
WAGES AND SALARIES
Workers, by bargaining status

Workers, by region

1

1

Northeast................................................................................
South......................................................................................
Midwest (formerly North Central)............................................
West........................................................................................
Workers, by area size

1

Metropolitan areas..................................................................
Other areas.............................................................................

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.

Monthly Labor Review

August 2001

105

Current Labor Statistics:

Compensation & Industrial Relations

25. Percent of full-time employees participating in employer-provided benefit plans, and in selected features within plans,
medium and large private establishments, selected years, 1980–97
Item

1980

Scope of survey (in 000's)…………………………….…
Number of employees (in 000's):
With medical care……...…………………………….…
With life insurance…………………………………..…
With defined benefit plan………………………………

1982

1984

1986

1988

1989

1991

1993

1995

1997

21,352

21,043

21,013

21,303

31,059

32,428

31,163

28,728

33,374

38,409

20,711
20,498
17,936

20,412
20,201
17,676

20,383
20,172
17,231

20,238
20,451
16,190

27,953
28,574
19,567

29,834
30,482
20,430

25,865
29,293
18,386

23,519
26,175
16,015

25,546
29,078
17,417

29,340
33,495
19,202

10
–
75
–
–
–
99
10.1
20
–
100

9
25
76
25
–
–
99
10.0
24
3.8
99

9
26
73
26
–
–
99
9.8
23
3.6
99

10
27
72
26
88
3.2
99
10.0
25
3.7
100

11
29
72
26
85
3.2
96
9.4
24
3.3
98

10
26
71
26
84
3.3
97
9.2
22
3.1
97

8
30
67
28
80
3.3
92
10.2
21
3.3
96

9
29
68
26
83
3.0
91
9.4
21
3.1
97

_
_
_
_
80
3.3
89
9.1
22
3.3
96

_
_
_
_
81
3.7
89
9.3
20
3.5
95

62
–
–
_

67
–
–
_

67
–
–
_

70
–
–
_

69
33
16
_

68
37
18
_

67
37
26
_

65
60
53
_

58
_
_
84

56
_
_
93

97

97

97

95

90

92

83

82

77

76

–
58
–

–
62
–

46
62
8

66
70
18

76
79
28

75
80
28

81
80
30

86
82
42

78
73
56

85
78
63

26
–
46
–

27
–
51
–

36
$11.93
58
$35.93

43
$12.80
63
$41.40

44
$19.29
64
$60.07

47
$25.31
66
$72.10

51
$26.60
69
$96.97

61
$31.55
76
$107.42

67
$33.92
78
$118.33

69
$39.14
80
$130.07

Participants in life insurance plans………………………
Percent of participants with:
Accidental death and dismemberment
insurance……………..........................………………
Survivor income benefits………………………………
Retiree protection available……………………………
Participants in long-term disability
insurance plans………….............……………………
Participants in sickness and accident
insurance plans…………....................…………………

96

96

96

96

92

94

94

91

87

87

69
–
–

72
–
64

74
–
64

72
10
59

78
8
49

71
7
42

71
6
44

76
5
41

77
7
37

74
6
33

40

43

47

48

42

45

40

41

42

43

54

51

51

49

46

43

45

44

_

_

Participants in short-term disability plans 1……………

_

_

_

_

_

_

_

_

53

55

84

84

82

76

63

63

59

56

52

50

55
98
–
53
45

58
97
–
52
45

63
97
47
54
56

64
98
35
57
62

59
98
26
55
62

62
97
22
64
63

55
98
7
56
54

52
95
6
61
48

52
96
4
58
51

52
95
10
56
49

–

–

–

60

45

48

48

49

55

57

–

–

–

33

36

41

44

43

54

55

2
5
5
12
_
_
fits at less than full pay.

9
23
_

10
36
_

12
52
_

12
38
5

13
32
7

Time-off plans
Participants with:
Paid lunch time…………………………………………
Average minutes per day……………………………
Paid rest time……………………………………….….
Average minutes per day……………………………
Paid funeral leave…………………….…………………
Average days per occurrence………………………
Paid holidays…………………………………..…………
Average days per year…………………………………
Paid personal leave……………………………………
Average days per year…………………………………
Paid vacations……………………………………………
1

Paid sick leave …………………………………………
Unpaid maternity leave…………………………………
Unpaid paternity leave…………………………………
Unpaid family leave ……………………………………
Insurance plans
Participants in medical care plans………………………
Percent of participants with coverage for:
Home health care……..................……………………
Extended care facilities………………………………
Physical exam…………….……………………………
Percent of participants with employee
contribution required for:
Self coverage……….................................…………
Average monthly contribution………………………
Family coverage………………………………………
Average monthly contribution………………………

Retirement plans
Participants in defined benefit pension plans…………
Percent of participants with:
Normal retirement prior to age 65……...................
Early retirement available……………………………
Ad hoc pension increase in last 5 years………..….
Terminal earnings formula……………………………
Benefit coordinated with Social Security……………
Participants in defined contribution plans………………
Participants in plans with tax-deferred savings
arrangements………..............………….................…
Other benefits

Employees eligible for:
Flexible benefits plans…………..…..........……………
–
–
–
2
–
–
–
Reimbursement accounts ……………………………
_
_
_
Premium conversion plans……………………………
1
The definitions for paid sick leave and short-term disability (previously sickness and
accident insurance) were changed for the 1995 survey. Paid sick leave now includes only
plans that specify either a maximum number of days per year or unlimited days. Shortterms disability now includes all insured, self-insured, and State-mandated plans available
on a per-disability basis, as well as the unfunded per-disability plans previously reported as
sick leave. Sickness and accident insurance, reported in years prior to this survey, included
only insured, self-insured, and State-mandated plans providing per-disability bene-

106

Monthly Labor Review

August 2001

2

Prior to 1995, reimbursement accounts included premium conversion plans, which
specifically allow medical plan participants to pay required plan premiums with pretax
dollars. Also, reimbursement accounts that were part of flexible benefit plans were
tabulated separately.
NOTE: Dash indicates data not available.

26. Percent of full-time employees participating in employer-provided benefit plans, and in selected features
within plans, small private establishments and State and local governments, 1987, 1990, 1992, 1994, and 1996
Small private establishments

Item
1990

1992

1994

State and local governments
1996

1987

1990

1992

1994

Scope of survey (in 000's)…………………………….…

32,466

34,360

35,910

39,816

10,321

12,972

12,466

12,907

Number of employees (in 000's):
With medical care……...…………………………….…
With life insurance…………………………………..…
With defined benefit plan………………………………

22,402
20,778
6,493

24,396
21,990
7,559

23,536
21,955
5,480

25,599
24,635
5,883

9,599
8,773
9,599

12,064
11,415
11,675

11,219
11,095
10,845

11,192
11,194
11,708

Time-off plans
Participants with:
Paid lunch time…………………………………………
Average minutes per day……………………………
Paid rest time……………………………………….….
Average minutes per day……………………………
Paid funeral leave…………………….…………………
Average days per occurrence………………………
Paid holidays…………………………………..…………

8
37
48
27
47
2.9
84

9
37
49
26
50
3.0
82

–
–
–
–
50
3.1
82

–
–
–
–
51
3.0
80

17
34
58
29
56
3.7
81

11
36
56
29
63
3.7
74

10
34
53
29
65
3.7
75

–
–
–
–
62
3.7
73

Average days per year1………………………………
Paid personal leave……………………………………
Average days per year…………………………………
Paid vacations……………………………………………

9.5
11
2.8
88

9.2
12
2.6
88

7.5
13
2.6
88

7.6
14
3.0
86

10.9
38
2.7
72

13.6
39
2.9
67

14.2
38
2.9
67

11.5
38
3.0
66

Paid sick leave …………………………………………

47

53

50

50

97

95

95

94

Unpaid leave………………………….…………………
Unpaid paternity leave…………………………………
Unpaid family leave……………………………………

17
8
–

18
7
–

–
–
47

–
–
48

57
30
–

51
33
–

59
44
–

–
–
93

69

71

66

64

93

93

90

87

79
83
26

80
84
28

–
–
–

–
–
–

76
78
36

82
79
36

87
84
47

84
81
55

Percent of participants with employee
contribution required for:
Self coverage……….................................…………
Average monthly contribution………………………
Family coverage………………………………………

42
$25.13
67

47
$36.51
73

52
$40.97
76

52
$42.63
75

35
$15.74
71

38
$25.53
65

43
$28.97
72

47
$30.20
71

Average monthly contribution………………………

$109.34

$150.54

$159.63

$181.53

$71.89

$117.59

$139.23

$149.70

64

64

61

62

85

88

89

87

78
1
19

76
1
25

79
2
20

77
1
13

67
1
55

67
1
45

74
1
46

64
2
46

19

23

20

22

31

27

28

30

6

26

26

_

14

21

22

21

_

_

_

29

_

_

_

_

20

22

15

15

93

90

87

91

54
95
7
58
49

50
95
4
54
46

–
–
–
–
–

47
92
–
53
44

92
90
33
100
18

89
88
16
100
8

92
89
10
100
10

92
87
13
99
49

31

33

34

38

9

9

9

9

17

24

23

28

28

45

45

24

2

Insurance plans
Participants in medical care plans………………………
Percent of participants with coverage for:
Home health care……..................……………………
Extended care facilities………………………………
Physical exam…………….……………………………

Participants in life insurance plans………………………
Percent of participants with:
Accidental death and dismemberment
insurance……………..........................………………
Survivor income benefits………………………………
Retiree protection available……………………………
Participants in long-term disability
insurance plans………….............……………………
Participants in sickness and accident
insurance plans…………....................…………………
2

Participants in short-term disability plans ……………
Retirement plans
Participants in defined benefit pension plans…………
Percent of participants with:
Normal retirement prior to age 65……...................
Early retirement available……………………………
Ad hoc pension increase in last 5 years………..….
Terminal earnings formula……………………………
Benefit coordinated with Social Security……………
Participants in defined contribution plans………………
Participants in plans with tax-deferred savings
arrangements………..............………….................…
Other benefits
Employees eligible for:
Flexible benefits plans…………..…..........……………
3

Reimbursement accounts ……………………………
Premium conversion plans ….…………………………

1

2

3

4

5

5

5

5

8

14

19

12

5

31

50

64

_

_

_

7

_

_

_

_

1

Methods used to calculate the average number of paid holidays were revised
in 1994 to count partial days more precisely. Average holidays for 1994 are
not comparable with those reported in 1990 and 1992.

sick leave. Sickness and accident insurance, reported in years prior to this
survey, included only insured, self-insured, and State-mandated plans

2

3

The definitions for paid sick leave and short-term disability (previously
sickness and accident insurance) were changed for the 1996 survey. Paid sick
leave now includes only plans that specify either a maximum number of days
per year or unlimited days. Short-term disability now includes all insured, selfinsured, and State-mandated plans available on a per-disability basis, as well
as the unfunded per-disability plans previously reported as

providing per-disability benefits at less than full pay.
Prior to 1996, reimbursement accounts included premium conversion plans,
which specifically allow medical plan participants to pay required plan
premiums with pretax dollars. Also, reimbursement accounts that were part of
flexible benefit plans were tabulated separately.
NOTE: Dash indicates data not available.

Monthly Labor Review

August 2001

107

Current Labor Statistics:

Compensation & Industrial Relations

27. Work stoppages involving 1,000 workers or more
Measure

Annual totals

I

1999

1999

2000

Dec.

2000
p

Jan.

p

Feb.

p

Mar.

Apr.

p

p

May

June

p

p

July

Aug.

p

p

Sept.

Oct.

p

p

Nov.

p

Dec.

Number of stoppages:
Beginning in period.............................
In effect during period…......................

17
21

39
40

0
1

0
1

1
2

2
4

6
7

2
4

5
8

3
6

6
8

5
10

7
12

0
3

2
3

Workers involved:
Beginning in period (in thousands)…..
In effect during period (in thousands)…

73
80

394
397

.0
3.0

.0
3.0

17.0
20.0

5.7
25.7

26.7
29.7

136.9
141.3

11.4
150.8

7.2
146.9

99.2
237.2

17.8
167.8

60.3
211.6

.0
4.5

8.7
10.3

1,995

20,419

63.0

60.0

298.0

327.6

272.2 3,095.3 3,134.0 2,804.4 4,186.6 3,029.3

3,088.6

64.5

58.9

.01

.06

()

.01

.01

2)

()

Days idle:
Number (in thousands)…....................
1

Percent of estimated working time ……
1

2

2

()

.01

.10

.10

.10

.13

.11

.11

(

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 worked is found in " 'Total economy' measures of strike idleness," Monthly Labor Review , October 1968, pp. 54–56.

108

2

Less than 0.005.

p

= preliminary.

Monthly Labor Review

August 2001

2

28. 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

1999

2000

2000
June

July

Aug.

Sept.

2001
Oct.

Nov.

Dec.

Jan.

Feb.

Mar.

Apr.

May

June

CONSUMER PRICE INDEX
FOR ALL URBAN CONSUMERS
All items.....................................................................
All items (1967 = 100)................................................

166.6
499.0

172.2
515.8

172.4
516.5

172.8
517.5

172.8
517.6

173.7
520.3

174.0
521.2

174.1
521.5

174.0
521.1

175.1
524.5

175.8
526.7

176.2
528.0

176.9
529.9

177.7
532.2

178.0
533.3

Food and beverages.................................................

164.6
164.1
164.2
185.0
147.9

168.4
167.8
167.9
188.3
154.5

167.9
167.3
167.3
187.7
154.9

168.7
168.1
168.3
189.6
155.8

169.2
168.7
168.9
189.9
156.8

169.4
168.9
169.0
188.6
156.9

169.6
169.1
169.1
190.1
156.8

169.5
168.9
168.8
189.0
155.5

170.5
170.0
170.2
190.7
156.6

171.4
170.9
171.3
191.1
158.0

171.8
171.3
171.8
191.9
159.5

172.2
171.7
172.0
191.9
160.1

172.4
171.9
172.2
192.5
160.7

172.9
172.5
172.8
193.2
160.8

173.4
173.0
173.3
194.2
161.7

159.6
203.1

160.7
204.6

159.5
199.9

160.5
201.0

161.0
202.5

161.6
204.6

161.9
206.2

161.4
207.3

161.5
215.1

163.6
212.6

163.6
211.5

163.2
211.5

163.4
213.3

164.7
213.1

166.9
211.8

134.3
153.5
152.3
148.3
168.9

137.8
155.6
154.0
147.4
172.2

137.5
156.2
154.0
146.6
173.4

138.5
156.6
154.1
148.1
173.5

138.2
156.9
154.6
148.9
173.7

138.0
156.7
154.6
148.7
173.4

137.4
155.8
153.9
149.7
172.0

137.9
156.0
153.0
146.5
173.3

136.7
156.3
153.5
150.2
172.7

139.4
157.8
155.7
153.0
173.8

139.9
157.9
155.8
152.6
174.0

139.5
158.6
155.7
153.1
175.1

138.9
157.6
154.0
151.5
174.4

138.1
159.6
155.8
154.7
176.4

138.6
159.5
155.7
156.7
175.7

104.9

107.5

108.4

108.8

109.5

107.7

106.8

110.0

108.9

109.0

108.7

108.4

108.5

108.8

107.7

165.1

169.0

168.6

169.1

169.5

170.0

170.3

170.4

170.8

171.4

171.8

172.3

172.7

173.1

173.6

105.2
169.7

109.0
174.7

108.1
174.4

108.7
175.2

109.3
175.6

110.0
175.5

110.5
175.9

111.0
176.4

111.1
176.5

111.3
177.2

111.4
177.7

111.6
177.8

111.8
178.1

112.4
178.5

112.6
179.1

163.9
187.3

169.6
193.4

169.6
193.3

170.6
194.1

170.9
194.7

175.4
199.2

175.9
199.6

177.3
200.7

183.9
122.8
198.6

184.6
123.0
199.2

171.9
195.1
187.6

175.4
198.9

183.2
120.5
198.2

171.6
195.2
186.8

174.7
197.6

183.9
117.5
198.7

171.7
195.2
186.1

174.1
196.4

177.5
112.3
192.9

171.4
194.6
185.3
118.1
199.9

118.5
200.5

113.9
201.2

108.8
201.8

188.2
114.1
202.4

188.9
119.1
105.4

189.6
124.2
203.6

190.2
121.8
204.2

191.0
120.0
204.9

191.6
123.7
205.7

101.3
128.8
113.5
91.4
120.9
126.7

103.7
137.9
122.8
129.7
128.0
128.2

103.9
138.9
124.0
120.9
130.2
128.1

104.2
141.3
126.5
120.8
133.0
128.6

104.0
140.9
125.9
120.8
132.4
128.6

104.2
143.8
129.1
133.7
134.8
129.0

104.2
143.1
128.3
137.6
133.6
128.7

104.5
142.7
127.7
140.3
132.7
128.9

104.7
145.3
130.6
144.9
135.6
128.6

105.0
153.8
139.8
149.1
145.7
128.8

105.1
152.3
138.0
144.6
144.0
129.1

105.4
150.8
136.3
138.1
142.6
129.1

105.5
149.7
135.1
134.4
141.6
129.1

106.8
151.3
136.8
131.9
143.8
128.9

107.0
155.7
141.6
129.6
149.4
129.2

131.3
131.1
123.3

129.6
129.7
121.5

128.3
129.4
119.2

124.5
126.4
113.9

125.3
126.8
115.6

130.4
129.1
124.2

132.8
130.4
127.9

131.8
131.3
124.8

127.8
128.0
119.7

125.4
125.5
115.5

128.4
126.6
121.0

132.2
127.5
127.8

131.9
128.2
127.0

129.8
129.1
122.3

126.3
125.8
117.5

129.0
125.7
144.4
140.5

130.6
123.8
153.3
149.1

130.5
123.9
155.7
151.4

128.1
120.3
155.0
150.6

126.7
120.7
153.2
148.6

127.4
124.9
154.7
150.4

130.8
125.3
154.4
150.4

130.7
125.4
155.2
151.1

128.2
123.8
154.4
150.3

127.4
121.4
154.4
150.3

129.3
122.6
154.9
150.7

1316.0
125.2
153.9
149.7

131.4
124.9
156.1
152.1

130.6
124.4
159.2
155.3

127.3
122.1
158.3
154.0

Food..................…...................................................
Food at home….....................................................
Cereals and bakery products…...........................
Meats, poultry, fish, and eggs…..........................
1

Dairy and related products ……….……………………
Fruits and vegetables….......................................
Nonalcoholic beverages and beverage
materials….......................................................
Other foods at home…........................................
Sugar and sweets…..........................................
Fats and oils…...................................................
Other foods…....................................................
Other miscellaneous foods

1,2

……….……………

1

Food away from home ……….……………………………
1,2

Other food away from home ……….………………
Alcoholic beverages…............................................
Housing....................................................................
Shelter...............….................................................
Rent of primary residence…................................
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

100.1
142.9

100.8
142.8

100.8
142.9

100.6
142.5

100.4
141.9

100.4
141.4

100.8
141.6

101.5
142.7

102.1
143.6

102.3
143.7

102.2
143.3

101.9
142.8

101.8
142.7

101.4
142.3

101.1
141.7

1

Used cars and trucks ……….…………………………
Motor fuel….........................................................
Gasoline (all types)…........................................
Motor vehicle parts and equipment…..................
Motor vehicle maintenance and repair….............
Public transportation...............…...........................

152.0
100.7
100.1
100.5
171.9
197.7

155.8
129.3
128.6
101.5
177.3
209.6

155.7
139.0
138.3
101.2
176.8
212.6

155.3
136.1
135.4
101.5
177.2
213.7

155.2
128.4
127.7
101.5
178.2
215.7

156.2
135.2
134.3
101.7
178.7
213.0

157.9
133.1
132.3
101.7
179.4
208.0

159.3
133.0
132.2
102.5
179.9
209.1

160.2
127.8
127.0
103.1
179.9
209.5

160.4
126.6
125.8
103.6
180.6
210.2

160.4
127.5
126.8
104.0
181.5
212.1

159.9
124.1
123.3
104.7
181.7
210.0

159.7
133.6
132.8
104.2
181.9
208.3

159.1
146.8
146.0
104.4
182.5
209.3

158.9
142.0
141.3
104.4
182.7
216.3

Medical care.............................................................
Medical care commodities...............…..................
Medical care services...............….........................
Professional services….......................................
Hospital and related services…...........................

250.6
230.7
255.1
229.2
299.5

260.8
238.1
266.0
137.7
317.3

260.5
238.2
265.6
237.9
315.6

261.4
238.6
266.7
238.3
318.1

262.6
239.2
268.0
238.9
321.3

263.1
239.4
268.7
239.3
322.5

263.7
239.6
269.4
239.7
323.6

264.1
240.0
269.8
239.8
324.7

264.8
241.1
270.4
240.3
325.3

267.1
242.3
273.0
242.6
328.5

268.9
243.8
274.9
244.1
331.0

270.0
244.9
275.9
244.8
332.8

270.8
245.7
276.8
245.6
333.6

271.4
246.6
277.3
245.8
335.1

272.5
248.1
278.3
246.5
336.6

102.1

103.3

103.4

103.7

103.9

103.8

103.8

103.7

103.7

104.1

104.3

104.3

105.0

105.0

104.8

100.7

101.0

101.5

101.3

101.6

101.5

101.0

100.9

100.7

101.2

101.6

101.6

101.7

101.6

101.3

101.2

102.5

101.5

102.0

102.8

102.9

103.6

103.2

103.6

103.9

104.0

104.3

104.1

104.0

104.4

107.0
261.7

112.5
279.9

111.5
277.5

111.8
278.1

113.0
280.2

114.9
284.8

115.3
285.2

115.4
284.8

115.5
285.4

115.8
289.2

116.0
290.4

116.1
290.8

116.1
290.8

116.4
290.7

116.9
293.9

308.4
96.0

324.0
93.6

320.9
92.6

321.7
93.3

325.4
93.7

330.8
92.1

332.1
93.1

332.5
92.3

332.7
93.0

333.3
93.3

333.7
93.2

334.0
93.7

334.1
93.3

335.0
92.9

336.2
93.1

New and used motor vehicles ……….………………
New vehicles…..................................................

2

Recreation ……….………………………………………….…
Video and audio

1,2

……….…………………………………
2

Education and communication ……….…………………
2
Education ……….………………………………………….…
Educational books and supplies….....................
Tuition, other school fees, and child care…......
1,2

Communication ……….…………………………………
1,2
Information and information processing ………
1,2

Telephone services ……….………………………
Information and information processing
1,4

other than telephone services ……….………
Personal computers and peripheral
1,2

equipment ……….………………………………
Other goods and services.........................................
Tobacco and smoking products...............…..........
1

95.5

92.8

91.8

92.5

93.0

91.3

92.3

91.5

92.2

92.4

92.2

92.7

92.3

91.8

92.1

100.1

98.5

97.2

98.2

98.9

97.0

98.3

97.5

98.4

98.8

98.7

99.4

99.0

98.7

99.0

30.5

25.9

26.0

25.7

25.2

25.0

24.7

24.2

23.8

23.2

22.9

22.5

22.1

21.7

21.4

53.5

41.1

41.2

40.3

39.5

38.9

38.3

37.3

36.5

35.0

33.9

32.4

31.7

30.4

29.8

258.3
355.8

271.1
394.9

269.6
388.5

272.2
400.7

271.6
394.1

274.7
408.0

273.0
396.7

276.2
411.0

274.0
396.6

275.9
404.3

277.2
408.5

277.7
407.7

277.7
424.2

281.3
418.7

281.2
421.0

161.1

165.6

165.4

165.7

166.2

166.6

167.0

167.4

167.8

168.2

168.6

169.1

169.6

169.5

170.0

Personal care products ……….………………………

1

151.8

153.7

153.6

153.7

154.3

154.3

153.4

153.9

155.5

155.3

155.3

155.7

155.8

153.2

154.6

1

171.4

178.1

177.9

178.2

179.3

179.9

180.3

180.6

181.3

181.6

181.9

182.2

183.4

184.1

184.1

Personal care ……….………………………………………
Personal care services ……….…………………………
See footnotes at end of table.

Monthly Labor Review

August 2001

109

Current Labor Statistics:

Price Data

28. 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

1999

2000

2000
June

July

Aug.

Sept.

2001
Oct.

Nov.

Dec.

Jan.

Feb.

Mar.

Apr.

May

June

Miscellaneous personal services...............…..

243.0

252.3

252.0

252.9

253.6

254.0

255.1

255.7

255.7

257.3

258.6

259.5

260.2

261.0

261.8

Commodity and service group:
Commodities...........…..........................................
Food and beverages….......................................
Commodities less food and beverages…...........
Nondurables less food and beverages….........
Apparel …......................................................

144.4
164.6
132.5
137.5
131.3

149.2
168.4
137.7
147.4
129.6

149.7
167.9
138.6
149.1
128.3

149.3
169.4
137.7
147.5
124.5

148.6
169.2
136.4
145.6
125.3

150.3
169.4
138.8
149.9
130.4

150.4
169.6
138.9
149.9
132.8

150.6
169.5
139.3
150.2
131.8

150.0
170.5
137.8
147.2
127.8

150.0
171.4
137.4
146.4
125.4

150.6
171.8
138.1
147.7
128.4

150.7
172.2
138.0
147.9
132.2

151.9
172.4
139.7
151.0
131.9

152.9
172.9
140.8
153.5
129.8

152.1
173.4
139.4
151.3
126.3

Nondurables less food, beverages,
and apparel…...............................................
Durables….......................................................

146.0
126.0

162.5
125.4

165.8
125.4

165.4
125.2

162.0
124.7

165.9
124.8

164.7
125.0

165.7
125.5

163.1
125.9

163.2
125.9

163.7
125.9

161.9
125.5

167.0
125.4

172.0
124.9

170.4
124.5

Services…............................................................

188.8

195.3

195.3

196.3

197.0

197.2

197.6

197.6

198.0

200.2

201.0

201.8

201.9

202.5

204.0

Rent of shelter ……….……………………………………
Transporatation services…...............................
Other services…................................................
Special indexes:

195.0
190.7
223.1

201.3
196.1
229.9

201.2
196.1
228.7

202.1
196.5
229.9

202.7
197.4
231.3

202.6
197.2
231.5

203.3
197.0
232.6

203.2
198.0
232.4

203.1
198.3
233.0

204.5
199.1
234.1

205.7
200.3
234.8

207.2
200.2
235.4

207.4
200.1
236.2

207.8
200.4
236.4

209.0
202.0
236.7

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…..................................................

167.0
160.2
162.0
134.0
139.4
147.5
151.2

173.0
165.7
167.3
139.2
149.1
162.9
158.2

173.3
166.0
167.6
140.1
150.7
166.0
158.8

173.6
166.2
167.9
139.2
149.3
165.7
158.4

173.5
166.0
167.9
138.0
147.5
162.6
157.6

174.6
167.4
168.8
140.3
151.5
166.2
160.0

174.9
167.5
169.1
140.4
151.6
165.1
160.1

175.0
167.7
169.2
140.8
151.8
166.0
160.2

174.7
167.5
169.0
139.3
149.0
163.6
159.1

175.9
168.6
170.1
139.0
148.3
163.9
159.1

176.6
169.1
170.8
139.7
149.6
164.3
160..0

177.1
169.2
171.2
139.6
149.8
162.7
160.3

177.8
170.1
171.8
141.2
152.8
167.4
162.0

178.6
170.9
172.6
142.4
155.1
172.0
163.6

179.0
171.0
172.9
141.0
153.1
170.6
162.7

195.8
182.7
106.6
174.4
177.0
144.1
100.0
195.7

202.9
188.9
124.6
178.6
181.3
144.9
129.5
202.1

202.9
188.9
129.6
178.3
181.0
144.5
137.6
201.9

204.2
189.9
129.7
178.7
181.3
143.8
135.0
202.7

205.0
190.5
125.9
179.1
181.7
143.7
127.9
203.5

205.7
190.7
130.6
179.6
182.3
145.1
135.2
203.5

205.8
191.1
129.3
180.1
182.8
145.6
133.6
204.1

205.9
191.1
129.0
180.3
183.0
146.0
133.8
204.2

206.9
191.5
128.1
180.2
182.8
145.1
129.3
204.4

210.0
193.6
132.5
181.0
183.5
144.8
128.6
205.7

210.5
194.3
132.0
181.8
184.4
145.9
129.1
206.8

210.6
195.1
129.5
182.6
185.3
146.2
125.4
207.7

210.6
195.2
133.1
182.9
185.6
146.6
133.8
208.0

211.4
195.7
140.1
182.9
185.5
145.7
145.6
208.4

213.3
197.2
140.5
183.3
185.9
144.9
141.1
209.4

All items..................................................................
All items (1967 = 100)............................................

163.2
486.2

168.9
503.1

169.2
504.1

169.4
504.7

169.3
504.2

170.4
507.6

170.6
508.2

170.9
509.0

170.7
508.5

171.7
511.6

172.4
513.4

172.6
514.2

173.5
516.7

174.4
519.4

174.6
520.0

Food and beverages.............................................

163.8
163.4
163.0
184.7
147.6

167.7
167.2
166.8
188.0
154.1

167.3
166.8
166.3
187.3
154.6

168.0
167.6
167.3
189.2
155.4

168.6
189.9
156.8
161.0
202.5

168.8
168.3
168.1
188.4
156.6

169.0
168.5
168.1
189.9
156.4

168.8
168.3
167.8
188.6
155.3

169.8
169.3
169.1
190.4
156.3

170.8
170.3
170.3
190.9
157.9

171.2
170.8
170.8
191.7
159.2

171.6
171.1
171.1
191.7
160.0

171.9
171.4
171.3
192.2
160.7

172.3
171.9
171.8
192.9
160.6

172.8
172.4
172.4
193.9
161.4

159.4
201.8

160.5
203.4

159.4
198.9

160.5
200.0

138.2
201.5

161.6
203.6

161.9
204.7

161.4
205.8

161.5
213.3

163.8
210.9

163.5
210.1

163.1
209.8

163.5
211.7

164.7
211.5

166.9
210.5

133.2
152.8
152.2
147.9
168.8

136.9
155.1
153.9
147.2
172.3

136.7
155.6
153.9
146.4
173.4

137.5
156.0
154.2
147.9
173.5

137.4
156.2
154.4
148.6
173.6

137.1
156.1
154.4
148.5
173.5

136.6
155.3
153.8
149.4
172.0

137.1
155.4
152.7
146.3
173.4

135.8
155.8
153.3
149.9
173.0

138.7
157.3
155.4
152.8
174.0

139.3
157.3
155.6
152.4
174.1

138.8
158.2
155.6
153.0
175.4

138.2
157.1
153.7
151.4
174.6

137.2
159.1
155.8
154.3
176.5

137.8
159.1
155.5
156.4
176.0

104.6

107.1

108.0

108.4

109.0

107.5

106.3

109.6

108.6

108.5

108.5

108.5

108.4

108.7

108.0

165.0
105.1
168.8

169.0
109.2
173.8

168.6
108.4
173.6

169.1
108.8
174.4

169.5
109.6
174.7

170.0
110.4
174.4

170.3
110.9
174.8

170.5
111.2
175.6

170.8
111.4
175.8

171.4
111.5
176.5

171.8
111.6
177.0

172.3
111.8
177.2

172.7
112.0
177.6

173.1
112.5
178.0

173.5
112.8
178.4

160.0
181.6

165.4
187.4

165.5
187.2

166.4
187.9

166.6
188.4

167.3
188.7

167.5
189.3

167.6
189.5

168.1
189.6

170.2
190.6

170.5
191.5

171.0
192.6

171.0
192.9

171.7
193.5

173.0
194.4

177.1
122.2
175.7

183.4
117.3
180.8

182.7
120.9
180.4

183.4
123.1
180.8

184.1
122.5
181.3

184.8
118.3
181.9

185.6
118.6
182.4

186.2
113.9
183.0

187.0
108.7
183.5

187.7
113.8
184.1

188.3
118.5
184.5

189.0
123.8
185.2

189.6
121.2
185.7

190.4
119.9
186.3

191.0
123.2
187.0

101.6
128.7
113.0
91.7
120.4
124.7
130.1
131.2
121.3

103.9
137.4
121.8
128.8
127.5
125.5
128.3
129.7
119.3

104.1
138.7
123.3
120.2
129.9
125.3
127.3
129.5
117.4

104.4
141.0
125.7
120.1
132.5
125.7
123.6
126.6
112.2

104.2
140.4
125.0
120.1
131.8
125.7
124.0
126.8
113.2

104.4
143.4
128.2
133.1
134.4
126.1
128.7
128.8
121.5

104.4
142.5
127.2
136.7
133.0
125.8
131.3
130.3
125.5

104.7
142.0
126.5
139.3
132.1
126.0
130.5
131.3
122.6

104.9
144.6
129.3
144.1
134.8
125.6
126.6
128.0
117.5

105.2
153.2
138.6
150.1
144.8
125.7
124.1
125.8
113.2

105.3
151.5
136.6
145.0
143/0
125.9
127.0
126.9
118.4

105.6
149.9
134.8
138.0
141.5
125.9
130.6
127.6
125.2

105.8
148.8
133.6
133.9
140.4
126.0
130.5
128.3
124.7

106.9
150.8
135.7
131.5
142.9
125.7
128.5
129.2
120.2

107.2
155.2
140.5
129.2
148.5
125.9
125.2
126.3
115.6

130.3
126.2
143.4
140.7

132.3
124.2
152.8
150.1

132.0
124.6
155.5
152.8

129.8
120.9
154.4
151.6

128.4
121.5
152.3
149.3

129.0
124.8
154.2
151.4

132.6
125.5
154.0
151.3

132.7
125.7
154.9
152.2

130.0
124.0
153.9
151.2

129.0
121.5
154.0
151.2

131.0
122.4
154.5
151.7

133.3
125.2
153.3
150.5

133.2
125.2
155.8
153.2

132.0
124.5
159.2
156.6

128.6
122.1
157.9
155.1

100.4

101.4

101.4

101.1

100.9

101.0

101.4

102.2

102.8

102.9

102.8

102.5

102.4

102.0

101.7

3

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…..................................
CONSUMER PRICE INDEX FOR URBAN
WAGE EARNERS AND CLERICAL WORKERS

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….................................................
Other miscellaneous foods

1,2

……….…………

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.

110

Monthly Labor Review

August 2001

28. 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

1999
New vehicles…...............................................

2000

2000
June

July

Aug.

Sept.

2001
Oct.

Nov.

Dec.

Jan.

Feb.

Mar.

Apr.

May

June

144.0

143.9

144.1

143.7

143.1

142.5

142.7

143.7

144.6

144.8

144.5

143.8

143.8

143.4

142.7

Used cars and trucks ……….………………………
Motor fuel…......................................................
Gasoline (all types)….....................................
Motor vehicle parts and equipment…...............
Motor vehicle maintenance and repair…..........
Public transportation...............…........................

153.3

157.1

157.1

156.6

156.5

157.5

159.3

160.7

161.6

161.7

161.7

161.1

160.9

160.2

160.0

100.8
100.2
100.0
173.3
193.1

129.5
128.8
100.9
178.8
203.4

140.1
139.4
100.5
178.3
205.5

136.2
135.5
100.8
178.7
206.9

128.0
127.3
100.7
179.6
208.7

135.3
134.6
100.9
180.2
206.4

133.1
132.3
101.0
180.9
202.4

133.2
132.4
101.8
181.4
203.2

127.7
126.9
102.3
181.5
203.7

126.9
126.2
103.0
182.1
204.3

127.8
127.1
103.4
183.1
205.8

124.1
123.4
104.0
183.3
204.2

134.0
133.3
103.5
183.4
202.7

147.4
146.7
103.6
184.1
203.5

142.1
141.1
103.6
184.4
209.5

Medical care..........................................................
Medical care commodities...............…...............
Medical care services...............…......................
Professional services…....................................
Hospital and related services…........................

249.7
226.8
254.9
230.8
295.5

259.9
233.6
265.9
239.6
313.2

259.7
233.7
265.6
239.9
311.7

260.6
234.2
266.6
240.3
314.2

261.7
234.6
267.9
240.9
317.1

262.2
235.0
268.5
241.3
318.2

262.8
235.2
269.2
241.8
319.2

263.1
235.5
269.4
241.7
320.3

263.8
236.5
270.1
242.3
320.9

266.3
237.8
272.8
244.9
323.9

268.1
239.1
274.7
246.4
326.6

269.1
240.2
275.7
247.0
328.3

269.9
241.0
276.5
247.8
329.1

270.4
241.7
277.0
248.0
330.6

271.5
243.2
278.0
248.7
332.0

101.3

102.4

102.5

102.7

102.9

102.8

102.8

102.7

102.6

103.0

103.1

103.0

103.7

103.7

103.5

100.5

100.7

101.2

100.9

101.3

101.1

100.7

100.6

100.3

100.8

101.2

101.0

101.2

101.1

100.7

101.5

102.7

101.7

102.2

103.0

102.9

103.7

103.2

103.7

104.0

104.1

104.4

104.2

104.1

104.5

107.2
264.1

112.8
283.3

111.8
280.9

112.1
281.5

113.2
283.6

115.1
288.6

115.4
289.0

115.6
288.6

115.7
289.2

116.0
292.9

116.2
294.1

116.3
294.7

116.4
294.7

116.7
294.5

117.2
298.2

302.8
96.9

318.2
94.6

315.4
93.6

316.2
94.3

319.2
94.8

324.7
93.1

325.7
94.2

326.3
93.3

326.5
94.1

327.0
94.4

327.4
94.4

327.9
94.8

328.2
94.4

329.1
94.0

330.3
94.3

1

2

Recreation ……….………………………………………….
1,2

Video and audio

……….………………………………
2

Education and communication ……….………………
2
Education ……….…………………………………………
Educational books and supplies….................
Tuition, other school fees, and child care…...
1,2

Communication ……….………………………………
1,2
Information and information processing ……
1,2

Telephone services ……….……………………
Information and information processing
1,4

other than telephone services ……….……
Personal computers and peripheral
1,2

equipment ……….……………………………
Other goods and services.....................................
Tobacco and smoking products...............….......
1

96.5

94.1

93.0

93.9

94.4

92.6

93.8

92.8

93.6

93.8

93.7

94.1

93.8

93.4

93.6

100.2

98.7

97.4

98.4

99.1

97.1

98.6

97.6

98.6

99.0

98.9

99.5

99.2

98.8

99.2

31.6

26.8

27.0

26.6

26.1

25.9

25.5

25.1

24.6

24.0

23.8

23.3

22.8

22.4

22.2

53.1

40.5

40.7

39.8

39.1

38.5

37.8

36.7

35.9

34.3

33.4

31.8

31.1

29.9

29.4

261.9
356.2

276.5
395.2

274.5
388.7

277.9
400.9

276.8
394.2

280.9
408.2

278.2
397.0

282.3
411.3

279.2
396.9

281.5
404.6

283.2
409.2

283.5
408.5

288.2
424.8

286.8
419.8

287.9
421.6

161.3

165.5

165.3

165.5

166.1

166.5

166.8

167.1

167.7

168.1

168.5

169.0

169.4

169.3

169.9

1

152.5

154.2

154.0

154.1

155.0

155.1

153.9

154.2

155.8

155.7

155.7

155.9

156.0

153.8

155.4

Personal care services ……….………………………
Miscellaneous personal services...............…..
Commodity and service group:

1

171.7
243.1

178.6
251.9

178.3
251.4

178.6
252.2

179.7
253.0

180.3
253.4

180.8
254.5

181.1
255.1

181.7
255.3

182.1
257.0

182.4
258.4

182.8
258,3

183.9
260.0

184.7
260.7

184.8
261.6

Commodities...........…..........................................
Food and beverages….......................................
Commodities less food and beverages…...........
Nondurables less food and beverages….........
Apparel …......................................................
Nondurables less food, beverages,

144.7
163.8
133.2
138.1
130.1

149.8
167.7
139.0
149.1
128.3

150.6
167.3
140.3
151.5
127.3

150.1
168.0
139.2
149.7
123.6

149.3
168.6
137.7
147.2
124.0

151.0
168.8
140.2
151.8
128.7

151.0
169.0
140.2
151.6
131.3

151.4
168.8
140.8
152.1
130.5

150.6
169.8
139.1
148.6
126.6

150.8
170.8
138.8
148.1
124.1

151.4
171.2
139.5
149.4
127.0

151.4
171.6
139.3
149.3
130.6

152.8
171.9
141.2
153.1
130.5

153.9
172.3
142.6
156.2
128.5

153.0
172.8
141.1
153.6
125.2

and apparel…...............................................
Durables….......................................................

147.2
126.0

165.3
125.8

169.6
125.9

168.7
125.6

164.6
125.2

169.3
125.3

167.6
125.6

168.8
126.2

165.5
126.6

166.0
126.6

166.5
126.6

164.4
126.2

170.5
126.0

176.3
125.5

174.1
125.2

Personal care ……….……………………………………
Personal care products ……….……………………

Services…............................................................

185.3

191.6

191.2

192.2

193.0

193.4

193.9

194.0

194.5

196.6

197.2

197.8

198.0

198.7

200.1

Rent of shelter ……….……………………………………
Transporatation services…...............................
Other services…................................................
Special indexes:

174.9
187.9
219.6

180.5
192.9
225.9

180.3
192.6
224.7

181.0
193.0
225.9

181.5
193.8
227.3

181.7
193.7
227.3

182.3
193.9
228.4

182.5
195.0
228.1

182.6
195.2
228.9

183.6
196.0
229.9

184.4
197.2
230.6

185.5
197.2
231.2

185.8
197.2
231.9

186.3
197.6
232.2

187.2
198.9
232.6

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…..................................................

163.1
158.1
159.2
134.6
140.0
148.4
151.3

169.1
163.8
164.7
140.4
150.7
165.4
158.9

169.5
164.3
165.0
141.7
152.9
169.4
159.9

169.6
164.3
165.1
140.6
151.2
168.7
159.4

169.4
163.9
165.0
139.1
148.9
164.9
158.3

170.7
165.4
166.2
141.6
153.3
169.2
160.8

170.9
165.5
166.4
141.6
153.1
167.7
160.8

171.3
165.7
166.6
142.2
153.6
168.8
161.0

170.9
165.5
166.4
140.6
150.3
165.8
159.7

171.9
166.5
167.4
140.3
149.9
166.3
159.9

172.5
167.0
168.0
141.0
151.1
166.8
160.8

172.8
167.0
168.2
140.8
151.1
164.9
160.9

173.8
168.0
169.1
142.7
154.7
170.5
163.0

174.7
169.1
170.0
144.1
157.6
175.9
164.8

174.9
169.0
170.2
142.6
155.3
173.9
163.8

174.1
179.5
106.1
171.1
173.1
144.3
100.3
192.6

180.1
185.4
124.8
175.1
177.1
145.4
129.7
198.7

180.2
185.1
130.9
174.6
176.6
145.0
139.1
198.0

181.3
186.0
130.1
174.9
176.8
144.5
135.4
198.8

181.9
186.6
125.7
175.3
177.2
144.2
127.7
199.5

182.5
187.2
130.9
176.0
178.0
145.7
135.4
200.0

182.7
187.6
129.3
176.5
178.6
146.1
133.5
200.6

182.8
187.7
129.0
176.8
179.0
146.7
133.8
200.8

183.7
188.3
127.6
176.8
178.7
145.8
128.9
201.1

186.6
190.3
131.8
177.4
179.3
145.5
128.5
202.2

186.9
190.8
131.3
178.2
180.1
146.2
129.1
203.1

187.0
191.4
128.6
178.8
180.9
146.8
125.1
204.0

187.0
191.6
132.9
179.2
181.3
147.3
134.2
204.4

187.8
192.3
140.6
179.2
181.2
146.4
146.6
204.8

189.6
193.6
140.3
179.5
181.4
145.6
141.5
205.7

3

3

Services less rent of shelter ……….…………………
Services less medical care services…..............
Energy…...........................................................
All items less energy…......................................
All items less food and energy….....................
Commodities less food and energy…...........
Energy commodities....................................
Services less energy…..................................
1

Not seasonally adjusted.

2

Indexes on a December 1997 = 100 base.

3

Indexes on a December 1982 = 100 base.

4

Indexes on a December 1988 = 100 base.
Dash indicates data not available.
NOTE: Index applied to a month as a whole, not to any specific date.

Monthly Labor Review

August 2001

111

Current Labor Statistics:

Price Data

29. Consumer Price Index: U.S. city average and available local area data: all items
[1982–84 = 100, unless otherwise indicated]
Pricing
sched-

Area

1

ule
U.S. city average……………………………………………

All Urban Consumers

May

Urban Wage Earners
2000

2001

2000
June

Mar.

Apr.

May

June

May

2001

June

Mar.

Apr.

May.

June

M

171.5

172.4

176.2

176.9

177.7

178.0

168.2

169.2

172.6

173.5

174.4

174.6

Northeast urban……….………………………………………….………

M

178.4

179.0

183.7

184.2

184.6

185.3

175.4

175.9

180.3

180.9

181.6

182.1

Size A—More than 1,500,000..........................................

M

179.1

179.7

184.6

185.0

185.6

186.4

175.1

175.7

180.2

180.7

181.6

182.3

M

107.4

107.7

110.4

110.7

110.8

111.0

107.0

107.3

109.8

110.2

110.4

110.5

M

167.5

169.7

171.7

172.8

174.2

173.8

163.9

166.2

167.8

169.0

170.7

170.1

M

169.2

171.3

173.3

174.4

175.6

175.3

164.6

166.9

168.5

169.6

171.0

170.5

M

107.0

108.4

109.7

110.4

111.6

111.2

107.0

108.7

109.6

110.6

112.0

111.4

M

161.4

163.1

165.9

166.7

167.9

167.5

160.0

161.8

164.3

165.1

166.4

165.8

South urban…….….............................................................

M

166.7

167.5

170.6

171.4

171.7

172.2

165.0

165.8

168.7

169.6

170.0

170.3

Size A—More than 1,500,000..........................................

M

166.0

167.2

170.9

171.6

171.9

172.7

163.8

165.0

168.4

169.3

169.7

170.5

M

107.2

107.6

109.4

109.9

110.1

110.3

107.0

107.4

109.1

109.7

109.9

110.0

M

167.2

167.1

169.5

170.6

171.0

171.4

168.0

168.1

170.4

171.8

172.0

172.3

West urban…….…..............................................................

M

174.0

174.3

180.1

180.4

181.3

182.0

169.6

169.9

175.3

175.8

176.7

177.3

Size A—More than 1,500,000..........................................

M

175.5

175.8

182.0

182.5

183.4

184.4

169.4

169.6

175.4

176.0

177.0

177.9

M

107.3

107.7

110.7

110.6

111.1

111.2

107.1

107.4

110.4

110.4

110.9

110.9

M
M
M

155.5
107.2
166.9

156.4
107.8
167.5

160.3
109.8
170.3

160.9
110.2
171.2

161.6
110.7
171.9

162.1
110.8
172.1

154.1
107.0
166.2

155.1
107.7
166.8

158.6
109.5
169.5

159.3
110.1
170.5

160.2
110.7
171.1

160.6
110.6
171.2

Chicago–Gary–Kenosha, IL–IN–WI…………………………..
Los Angeles–Riverside–Orange County, CA……….…………

M
M

173.7
171.1

176.0
171.0

177.1
176.2

178.4
176.6

179.8
177.5

179.2
178.9

168.1
164.4

170.4
164.3

171.4
169.1

172.6
169.6

174.0
170.5

173.4
171.9

New York, NY–Northern NJ–Long Island, NY–NJ–CT–PA…

M

181.4

182.0

186.4

186.6

187.3

188.3

177.0

177.6

181.8

181.9

183.0

183.8

Boston–Brockton–Nashua, MA–NH–ME–CT……….…………

1

181.7

–

190.9

–

190.9

–

180.6

–

189.3

–

190.1

–

Cleveland–Akron, OH……………………………………………

1

166.6

–

172.3

–

173.7

–

159.0

–

163.9

–

165.6

–

Dallas–Ft Worth, TX…….………………………………………

1

163.2

–

168.9

–

169.4

–

163.1

163.1

168.5

–

169.1

–

Washington–Baltimore, DC–MD–VA–WV ……….………………
Atlanta, GA……………………..…………………………………

1

106.7

–

109.7

–

110.1

–

106.7

–

109.4

–

109.9

–

2

–

171.3

–

176.6

–

177.8

–

168.9

–

173.8

–

175.4

2

Region and area size

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)………….....

3

Size B/C—50,000 to 1,500,000 ……….…………………………
Size D—Nonmetropolitan (less than 50,000)………….....

3

Size B/C—50,000 to 1,500,000 ……….…………………………
Size classes:
5

A ……….………………………………………….…………..……………
3
B/C ……………………….….………………………………………….…
D…………….…………......................................................
6

Selected local areas

7

Detroit–Ann Arbor–Flint, MI……………………………………

2

–

170.9

–

174.5

–

175.8

–

165.8

–

169.1

–

170.4

Houston–Galveston–Brazoria, TX………………………………

2

–

154.1

–

159.5

–

159.6

–

153.1

–

157.8

–

158.4

Miami–Ft. Lauderdale, FL……………...………………………

2

–

168.0

–

172.8

–

173.5

–

165.7

–

170.4

–

171.2

Philadelphia–Wilmington–Atlantic City, PA–NJ–DE–MD……

2

–

176.6

–

181.2

–

182.5

–

176.1

–

180.7

–

182.1

San Francisco–Oakland–San Jose, CA…….…………………

2

–

179.1

–

189.1

–

190.9

–

175.2

–

184.9

–

186.9

Seattle–Tacoma–Bremerton, WA………………...……………

2

–

179.2

–

184.2

–

186.3

–

174.5

–

179.4

–

181.3

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 Report : Anchorage, AK;
Cincinnati–Hamilton, OH–KY–IN; Denver–Boulder–Greeley, CO; Honolulu, HI; Kansas City,

112

Monthly Labor Review

August 2001

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.
Dash indicates data not available.

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 longterm 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.

30. 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............................……………………

1992

1993

1994

1995

1996

1997

1998

1999

2000

140.3
3.0

144.5
3.0

148.2
2.6

152.4
2.8

156.9
3.0

160.5
2.3

163.0
1.6

166.6
2.2

172.2
3.4

138.7
1.4

141.6
2.1

144.9
2.3

148.9
2.8

153.7
3.2

157.7
2.6

161.1
2.2

164.6
2.2

168.4
2.3

137.5
2.9

141.2
2.7

144.8
2.5

148.5
2.6

152.8
2.9

156.8
2.6

160.4
2.3

163.9
2.2

169.6
3.5

131.9
2.5

133.7
1.4

133.4
–.2

132.0
–1.0

131.7
–.2

132.9
.9

133.0
.1

131.3
–1.3

129.6
–1.3

126.5
2.2

130.4
3.1

134.3
3.0

139.1
3.6

143.0
2.8

144.3
0.9

141.6
–1.9

144.4
2.0

153.3
6.2

190.1
7.4

201.4
5.9

211.0
4.8

220.5
4.5

228.2
3.5

234.6
2.8

242.1
3.2

250.6
3.5

260.8
4.1

183.3
6.8

192.9
5.2

198.5
2.9

206.9
4.2

215.4
4.1

224.8
4.4

237.7
5.7

258.3
8.7

271.1
5.0

138.2
2.9

142.1
2.8

145.6
2.5

149.8
2.9

154.1
2.9

157.6
2.3

159.7
1.3

163.2
2.2

168.9
3.5

Monthly Labor Review

August 2001

113

Current Labor Statistics:

Price Data

31. Producer Price Indexes, by stage of processing
[1982 = 100]
Grouping

Annual average
1999

Finished goods....……………………………
Finished consumer goods........................
Finished consumer foods.......................
Finshed consumer goods
excluding foods.....................................
Nondurable goods less food.................
Durable goods......................................
Capital equipment...................................

2000

2000

2001

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

Jan.

Feb.

Mar.

Apr.

May

June

133.0
132.0
135.1

138.0
138.2
137.2

138.6
139.1
137.6

138.6
139.0
137.5

138.2
138.6
137.2

139.4
140.1
137.4

140.1
140.7
138.0

140.0
140.5
138.2

139.7
140.1
137.9

141.2
141.9
138.4

141.5
142.5
139.5

141.0
141.9
140.9

141.7
142.7
141.6

142.5
143.8
141.8

142.1
143.3
141.9

130.5
127.9
133.0
137.6

138.4
138.7
133.9
138.8

139.6
140.5
133.4
138.5

139.5
140.5
133.1
138.6

139.0
140.0
132.7
138.5

141.1
143.0
132.5
138.6

141.6
142.6
135.3
139.8

141.3
142.1
135.4
139.9

140.8
141.5
135.3
139.9

143.3
144.9
135.2
140.2

143.6
145.9
134.2
139.7

142.1
143.8
134.1
139.7

142.9
144.9
134.2
140.0

144.5
147.3
133.8
139.7

143.7
146.5
133.2
139.6

Intermediate materials,
supplies, and components........…………
Materials and components
for manufacturing.....................................
Materials for food manufacturing..............
Materials for nondurable manufacturing...
Materials for durable manufacturing.........
Components for manufacturing................

123.2

129.2

129.8

130.3

129.9

131.1

130.8

130.5

130.6

131.5

131.3

130.8

130.6

131.2

131.4

124.6
120.8
124.9
125.1
125.7

128.1
119.2
132.6
129.0
126.2

128.6
120.6
133.7
129.4
126.2

128.9
120.5
134.5
129.4
126.3

128.6
119.4
133.9
129.0
126.3

128.5
119.0
133.6
129.3
126.4

128.4
119.1
133.7
128.8
126.4

128.0
118.9
133.3
127.5
126.5

128.1
119.8
133.5
128.0
126.1

128.6
120.4
135.0
127.2
126.4

128.8
120.3
136.1
127.0
126.2

128.9
122.3
135.8
126.7
126.4

128.7
122.3
135.2
126.0
126.6

128.6
124.6
134.2
126.9
126.4

128.3
125.7
133.4
126.5
126.4

Materials and components
for construction.........................................
Processed fuels and lubricants...................
Containers..................................................
Supplies......................................................

148.9
84.6
142.5
134.2

150.7
102.0
151.6
136.9

151.2
103.3
153.3
137.1

150.8
105.0
153.3
137.3

150.4
104.5
153.0
137.0

150.3
110.5
153.3
137.4

150.2
109.2
153.4
137.7

150.1
108.8
153.0
138.0

149.9
108.3
153.0
138.1

149.6
111.4
153.0
138.9

150.0
109.9
153.0
138.5

150.2
106.9
152.8
138.7

150.4
105.9
153.2
139.0

151.6
108.1
153.9
139.0

151.7
110.2
154.1
138.8

Crude materials for further
processing.......................…………………
Foodstuffs and feedstuffs...........................
Crude nonfood materials............................

98.2
98.7
94.3

120.6
100.2
130.4

125.6
101.9
137.3

122.7
99.3
134.4

118.3
95.5
129.7

126.0
97.6
141.0

130.3
99.5
146.7

128.4
100.4
143.0

136.2
103.9
153.5

155.0
105.3
183.5

133.2
104.5
148.2

131.5
108.9
142.2

132.9
109.1
144.5

130.9
110.3
140.4

122.8
109.7
–

132.3
78.8
143.0
145.2
146.1

138.1
94.1
144.9
147.4
148.0

138.8
97.7
144.7
147.3
147.5

138.8
97.3
144.7
147.3
147.6

138.4
95.9
144.7
147.3
147.7

139.9
100.6
144.8
147.5
147.8

140.6
99.6
146.0
148.6
149.2

140.4
98.9
146.1
148.7
149.2

140.1
97.9
145.9
148.5
149.1

141.9
101.9
146.7
149.4
150.0

142.0
103.6
146.6
149.5
149.4

140.9
99.7
147.1
150.2
149.5

141.6
101.2
147.5
150.6
149.8

142.6
104.1
147.7
151.6
150.0

–
102.7
147.6
150.9
149.9

151.7

154.0

153.6

153.5

153.8

154.0

155.5

155.4

155.3

156.5

155.9

156.1

156.4

156.9

156.7

166.3

169.8

169.4

169.6

170.4

170.9

171.3

171.2

171.0

173.2

173.2

173.5

174.0

175.4

175.5

123.9
111.1
84.3
131.7

130.1
111.7
101.7
135.0

130.7
113.4
103.0
135.5

131.2
112.7
104.6
135.7

131.0
110.6
104.2
135.3

132.2
111.1
110.1
135.4

131.9
111.5
108.8
135.4

131.5
111.7
107.6
135.2

131.5
113.5
107.9
135.3

132.4
115.1
110.9
135.8

132.3
113.6
109.5
135.8

131.7
114.1
106.4
136.0

131.6
114.0
105.5
136.0

132.1
114.9
107.6
136.1

132.3
116.3
109.7
135.9

133.1

136.6

137.0

137.2

137.0

137.0

137.0

136.8

136.8

137.1

137.3

137.4

137.4

137.5

137.2

78.5
107.9
135.2

122.1
111.7
145.2

130.6
113.4
146.7

127.6
110.8
144.3

122.4
107.4
141.9

136.7
109.2
142.9

144.8
110.1
141.0

140.9
109.9
137.8

154.7
112.4
137.5

193.4
113.7
138.7

148.3
112.4
136.1

141.0
115.2
134.6

145.2
114.3
130.8

139.8
115.3
130.9

123.1
114.8
130.6

Special groupings:
Finished goods, excluding foods................
Finished energy goods...............................
Finished goods less energy........................
Finished consumer goods less energy.......
Finished goods less food and energy.........
Finished consumer goods less food
and energy...............................................
Consumer nondurable goods less food
and energy.............................................
Intermediate materials less foods
and feeds..................................................
Intermediate foods and feeds.....................
Intermediate energy goods.........................
Intermediate goods less energy.................
Intermediate materials less foods
and energy...............................................
Crude energy materials..............................
Crude materials less energy.......................
Crude nonfood materials less energy.........

114

Monthly Labor Review

August 2001

32. Producer Price Indexes for the net output of major industry groups
[December 1984 = 100, unless otherwise indicated]
Industry

SIC
–
10
12
13
14

Total mining industries....................................
Metal mining....................................................
Coal mining (12/85 = 100)...............................
Oil and gas extraction (12/85 = 100)...............
Mining and quarrying of nonmetallic
minerals, except fuels...................................

Annual average
1999

2000

2000

2001

June

July

Aug.

Sept.

Oct.

Nov.

Dec.

Jan.

Feb.

Mar.

Apr.

May

June

78.0

113.5

118.4

118.1

113.8

124.7

131.8

128.9

139.6

170.8

138.2

130.7

132.2

127.5

115.5

70.3
87.3
78.5

73.8
84.8
126.8

73.7
85.1
133.1

73.9
85.6
132.8

73.4
83.3
127.4

75.2
83.5
141.9

75.1
83.6
151.5

73.3
84.1
147.7

73.5
84.8
162.0

73.5
83.6
204.4

72.4
90.8
159.4

73.1
90.3
149.3

70.0
90.6
151.5

71.4
92.2
144.9

71.0
87.7
129.6

134.0

137.0

137.2

137.6

137.8

138.0

138.0

138.0

138.2

139.3

140.1

140.8

140.8

140.7

141.8

Total manufacturing industries.......................
Food and kindred products.............................
Tobacco manufactures...................................
Textile mill products........................................
Apparel and other finished products
made from fabrics and similar materials.......
Lumber and wood products,
except furniture.............................................
Furniture and fixtures......................................
Paper and allied products...............................

128.3
126.3
325.7
116.3

133.5
128.5
345.8
116.7

134.2
129.4
342.2
116.6

133.9
129.4
342.3
116.7

133.5
128.7
350.4
116.9

134.7
128.5
351.1
116.6

134.9
128.7
351.6
116.8

134.9
128.8
351.6
117.0

134.4
129.6
351.8
117.5

134.7
130.1
372.4
117.4

134.7
130.4
372.4
117.9

134.6
131.7
372.3
117.0

135.4
132.5
372.1
117.0

136.3
133.2
391.2
117.1

136.0
133.8
391.7
117.2

125.3

125.7

125.6

125.9

125.9

125.9

126.0

125.7

125.9

125.7

125.7

125.7

125.9

125.8

125.7

161.8
141.3
136.4

158.1
143.3
145.8

158.7
143.5
147.3

157.6
143.5
147.3

155.7
143.6
147.3

155.3
143.5
147.7

155.0
143.7
147.6

154.5
143.8
147.5

154.2
143.8
147.0

153.2
144.2
147.4

153.8
144.3
147.0

154.5
144.8
147.0

154.7
144.7
147.0

160.5
144.9
146.9

161.3
145.2
146.8

Printing, publishing, and allied industries........
Chemicals and allied products........................
Petroleum refining and related products.........
Rubber and miscellaneous plastics products..
Leather and leather products..........................
Stone, clay, glass, and concrete products......
Primary metal industries.................................
Fabricated metal products,
except machinery and transportation
equipment.............................

177.6
149.7
76.8
122.2
136.5
132.6
115.8

182.9
156.7
112.8
124.6
137.9
134.6
119.8

183.1
156.5
119.9
124.4
137.2
135.1
120.2

183.2
157.4
115.7
125.0
137.5
134.8
120.3

183.6
157.5
112.6
124.7
137.8
134.5
120.4

183.6
158.3
125.1
125.4
138.4
134.8
120.5

184.9
158.6
121.8
125.3
138.4
134.5
120.2

185.0
158.3
121.9
126.5
138.8
134.3
119.0

185.1
159.0
114.4
124.8
138.9
134.1
119.2

186.8
160.4
112.5
126.0
139.1
134.4
118.5

187.2
161.6
112.0
126.1
140.6
135.0
118.0

187.6
161.9
107.3
126.8
140.9
135.4
117.4

188.4
161.4
114.1
127.4
142.8
135.6
116.8

188.8
160.4
120.9
126.6
142.9
136.0
116.9

188.4
160.0
116.9
126.4
142.6
135.7
116.5

129.1

130.3

130.3

130.3

130.4

130.5

130.6

130.5

130.5

130.6

130.7

130.8

131.2

131.1

131.1

35

Machinery, except electrical............................

117.3

117.5

117.5

117.6

117.6

117.6

117.6

117.7

117.7

117.7

117.8

117.8

118.0

118.0

118.1

36

Electrical and electronic machinery,
equipment, and supplies...............................
Transportation.................................................
Measuring and controlling instruments;
photographic, medical, and optical
goods; watches and clocks...........................
Miscellaneous manufacturing industries
industries (12/85 = 100)................................

109.5
134.5

108.3
136.8

108.5
136.0

108.5
136.1

108.1
135.7

108.1
135.7

108.0
138.4

107.9
138.6

107.7
138.4

107.7
138.7

107.6
137.6

107.5
137.9

107.5
138.1

107.4
137.4

107.3
137.1

–
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34

37
38

39

125.7

126.2

126.2

126.2

126.2

126.3

126.4

121.8

126.4

126.9

127.1

126.9

126.9

127.3

127.4

130.3

130.9

130.7

130.9

131.0

131.0

131.0

131.2

131.3

131.7

131.9

132.3

132.2

132.5

132.5

114.8
135.3
113.0
130.8
98.3

119.4
135.2
122.6
147.7
102.3

119.0
135.2
124.1
147.2
102.1

118.9
135.2
125.2
147.6
102.5

120.1
135.2
126.1
147.9
102.5

121.2
135.2
127.0
151.5
102.4

121.4
135.2
126.5
152.5
102.7

121.8
135.2
124.2
152.7
102.7

121.5
135.2
126.1
154.2
102.7

121.9
141.3
125.8
154.7
109.1

122.5
141.3
127.8
154.0
109.1

122.6
141.3
126.8
155.4
108.9

122.7
141.3
125.9
155.4
108.9

123.0
141.3
125.6
156.4
109.0

123.2
141.3
130.3
156.6
109.0

Service industries:
42
43
44
45
46

Motor freight transportation
and warehousing (06/93 = 100).....................
U.S. Postal Service (06/89 = 100)....................
Water transportation (12/92 = 100)..................
Transportation by air (12/92 = 100).................
Pipelines, except natural gas (12/92 = 100).....

Monthly Labor Review

August 2001

115

Current Labor Statistics:

Price Data

33. Annual data: Producer Price Indexes, by stage of processing
[1982 = 100]
Index

1992

1993

1994

1995

1996

1997

1998

1999

2000

Finished goods
Total...............................................................................
Foods............................…………………………….……
Energy............……………………………………….….…
Other…...............................………………………….……

123.2
123.3
77.8
134.2

124.7
125.7
78.0
135.8

125.5
126.8
77.0
137.1

127.9
129.0
78.1
140.0

131.3
133.6
83.2
142.0

131.8
134.5
83.4
142.4

130.7
134.3
75.1
143.7

133.0
135.1
78.8
146.1

138.0
137.2
94.1
148.0

Intermediate materials, supplies, and
components
Total...............................................................................
Foods............……………………………………….….…
Energy…...............................………………………….…
Other.................…………...………..........………….……

114.7
113.9
84.3
122.0

116.2
115.6
84.6
123.8

118.5
118.5
83.0
127.1

124.9
119.5
84.1
135.2

125.7
125.3
89.8
134.0

125.6
123.2
89.0
134.2

123.0
123.2
80.8
133.5

123.2
120.8
84.3
133.1

129.2
119.2
101.7
136.6

Crude materials for further processing
Total...............................................................................
Foods............................…………………………….……
Energy............……………………………………….….…
Other…...............................………………………….……

100.4
105.1
78.8
94.2

102.4
108.4
76.7
94.1

101.8
106.5
72.1
97.0

102.7
105.8
69.4
105.8

113.8
121.5
85.0
105.7

111.1
112.2
87.3
103.5

96.8
103.9
68.6
84.5

98.2
98.7
78.5
91.1

120.6
100.2
122.1
118.0

116

Monthly Labor Review

August 2001

34. U.S. export price indexes by Standard International Trade Classification
[1995 = 100]
SITC
Rev. 3

2000

Industry

2001

July

Aug.

Sept.

Oct.

Nov.

Dec.

Jan.

Feb.

Mar.

Apr.

May

June

0 Food and live animals………………………………………… 87.4
01
Meat and meat preparations........................................... 109.3
04
Cereals and cereal preparations.....................................
71.6
87.8
05
Vegetables, fruit, and nuts, prepared fresh or dry...........

85.8
108.2
66.9
91.3

83.6
103.7
64.0
88.6

85.9
105.2
67.8
91.9

87.1
107.4
70.8
88.7

88.5
107.6
74.0
89.8

88.7
105.9
75.8
88.9

89.8
105.4
78.8
86.9

88.6
107.1
76.4
86.2

89.1
107.1
77.2
87.8

88.6
109.8
74.7
89.5

87.9
110.8
74.7
87.4

87.9
110.7
73.5
88.4

2 Crude materials, inedible, except fuels...........................
21
Hides, skins, and furskins, raw........................................
Oilseeds and oleaginous fruits........................................
22
24
Cork and wood................................................................
25
Pulp and waste paper......................................................
26
Textile fibers and their waste...........................................
27
Crude fertilizers and crude minerals................................
28
Metalliferous ores and metal scrap..................................

84.4
86.7
86.3
86.7
97.6
69.6
93.3
78.2

82.9
89.7
80.3
86.5
95.9
67.7
93.3
78.0

82.9
95.4
78.0
88.4
91.7
70.7
93.1
78.7

83.7
100.5
83.8
86.9
90.7
72.2
91.5
78.7

83.5
104.7
81.3
87.2
89.8
72.0
90.7
79.5

82.2
102.1
79.3
86.5
88.6
72.2
90.6
76.2

82.6
103.3
85.0
85.9
85.9
73.2
90.6
74.7

82.0
105.6
83.9
85.2
85.8
70.4
90.9
74.1

80.9
106.5
78.1
84.3
83.6
70.6
90.9
74.7

79.7
107.5
79.0
83.5
82.3
67.6
89.9
72.5

78.4
119.2
75.0
81.6
80.6
64.8
89.4
73.0

77.5
123.2
76.0
80.9
75.2
64.1
89.2
72.2

76.9
103.8
79.9
80.6
73.6
63.0
89.4
71.7

3 Mineral fuels, lubricants, and related products..............
32
Coal, coke, and briquettes...............................................
33
Petroleum, petroleum products, and related materials....

144.9
93.8
168.2

151.2
93.8
178.3

147.6
93.1
172.3

166.3
93.1
203.3

157.2
93.3
189.0

162.1
93.1
193.4

157.4
93.0
183.6

157.5
93.1
181.1

159.5
93.1
185.2

152.4
93.6
172.4

156.0
100.2
178.4

159.0
154.2
100.4
100.7
184.4 1,770.0

4 Animal and vegetable oils, fats, and waxes....................

67.1

64.6

63.2

61.7

60.0

59.0

58.7

61.0

60.8

60.6

61.6

65.0

67.1

5 Chemicals and related products, n.e.s. ..........................
54
Medicinal and pharmaceutical products..........................
55
Essential oils; polishing and cleaning preparations.........
57
Plastics in primary forms ................................................
58
Plastics in nonprimary forms...........................................
Chemical materials and products, n.e.s. ........................
59

95.5
99.7
102.8
98.1
99.3
99.1

94.7
100.5
103.3
97.0
99.4
99.3

94.9
100.3
103.3
95.4
99.4
99.2

94.4
100.2
103.4
92.8
99.3
99.2

94.9
100.4
103.4
92.3
98.9
99.2

94.0
100.2
103.3
91.2
98.3
99.1

93.0
100.1
103.2
90.0
98.3
99.9

93.1
99.7
103.4
90.5
96.6
98.4

92.9
99.6
103.2
91.5
96.5
98.5

93.4
99.4
103.4
92.7
96.7
98.5

92.8
99.7
103.0
91.2
96.8
98.6

91.6
99.6
102.9
89.9
96.1
98.2

90.9
99.7
102.9
89.0
96.5
98.2

6 Manufactured goods classified chiefly by materials.....

100.3

100.7

100.9

101.1

100.8

100.5

100.4

101.0

100.6

100.4

100.1

99.9

99.7

104.4

104.8

104.7

104.7

104.6

104.1

103.8

104.4

104.3

104.7

104.0

104.0

104.1

89.8
106.5
100.1

90.4
106.3
103.0

90.3
106.3
105.1

90.0
106.1
105.0

89.9
105.8
104.9

89.6
105.9
103.4

89.1
105.6
104.9

88.6
106.2
109.1

88.4
106.2
108.1

87.8
106.0
106.5

87.7
106.5
103.1

87.6
106.6
101.6

87.0
107.0
99.8

62
64
66
68

June

Rubber manufactures, n.e.s. ..........................................
Paper, paperboard, and articles of paper, pulp,
and paperboard……………………………...………........
Nonmetallic mineral manufactures, n.e.s. ......................
Nonferrous metals...........................................................

7 Machinery and transport equipment...............................
Power generating machinery and equipment..................
Machinery specialized for particular industries................
General industrial machines and parts, n.e.s.,
and machine parts.........................................................
75
Computer equipment and office machines......................
76
Telecommunications and sound recording and
reproducing apparatus and equipment..........................
77
Electrical machinery and equipment................................
78
Road vehicles..................................................................
87 Professional, scientific, and controlling
instruments and apparatus……………………………..…

71
72
74

97.3

97.3

97.3

97.4

97.3

97.4

97.4

97.5

97.6

97.9

97.8

97.8

97.7

112.0
106.5

112.4
106.4

112.3
106.5

112.4
106.3

112.4
106.3

113.7
106.5

113.7
106.6

115.2
106.8

115.2
107.1

14.7
106.8

115.0
106.7

115.0
106.7

114.9
106.7

108.2
68.2

108.3
68.3

108.1
67.8

108.2
67.8

108.3
67.7

108.4
67.8

108.5
67.6

108.6
67.1

108.8
67.1

109.2
66.8

109.5
66.7

109.5
66.2

109.6
65.6

96.9
85.7
103.9

96.7
85.7
103.9

96.8
85.8
103.9

96.8
85.8
104.1

96.6
85.4
104.0

96.5
85.3
103.9

96.3
85.4
104.0

96.5
85.2
104.1

96.4
85.2
104.1

96.4
85.2
104.1

96.5
84.8
104.1

96.5
84.8
104.1

96.6
84.6
104.1

105.8

106.4

106.4

106.5

106.9

106.9

106.6

107.0

107.0

107.0

106.8

106.9

107.1

Monthly Labor Review

August 2001

117

Current Labor Statistics:

Price Data

35. U.S. import price indexes by Standard International Trade Classification
[1995 = 100]
SITC
Rev. 3

2000

Industry
June

0 Food and live animals…………………………………………
01
03
05
07

Meat and meat preparations...........................................
Fish and crustaceans, mollusks, and other
aquatic invertebrates………………………….................
Vegetables, fruit, and nuts, prepared fresh or dry...........
Coffee, tea, cocoa, spices, and manufactures
thereof……………………..………………………….........

Aug.

Sept.

Oct.

2001

Nov.

Dec.

Jan.

Feb.

Mar.

Apr.

May

June

91.3

91.5

91.7

91.2

91.5

90.2

92.4

92.8

91.3

93.0

90.8

89.8

88.5

99.1

98.1

98.9

99.0

95.5

95.7

97.3

95.5

96.1

100.4

102.6

104.4

104.3

109.1
95.7

110.7
97.2

113.5
97.6

112.6
97.8

110.7
100.9

109.3
96.8

109.1
104.5

107.4
106.1

105.6
101.7

102.2
109.5

100.1
102.3

99.7
100.5

98.8
97.0

59.5

56.8

55.8

54.5

54.1

51.9

50.8

50.5

51.1

51.1

52.1

50.8

49.8

1 Beverages and tobacco……………………………………… 113.0

112.5

112.9

113.6

113.5

113.3

113.2

113.2

113.3

113.0

113.2

114.8

114.4
112.1

11

Beverages…………….....................................................

110.1

109.4

109.9

110.7

110.6

110.7

110.6

110.5

110.8

110.4

110.7

112.5

2 Crude materials, inedible, except fuels...........................

90.7

90.7

89.6

88.9

89.8

87.7

88.5

87.5

88.9

86.1

86.6

89.5

94.2

Cork and wood................................................................
Pulp and waste paper......................................................
Metalliferous ores and metal scrap..................................
Crude animal and vegetable materials, n.e.s. ................

110.1
80.1
100.7
92.7

107.0
80.7
101.2
101.8

102.2
81.4
102.1
101.3

99.7
82.0
101.6
103.0

101.6
83.4
102.3
104.3

97.7
83.4
100.1
99.1

101.7
83.4
98.8
97.1

95.6
84.3
100.8
102.0

97.6
82.9
100.9
115.3

97.5
80.4
98.1
97.7

102.9
76.8
98.1
91.8

114.1
72.5
97.0
100.7

133.0
68.3
97.3
98.6

3 Mineral fuels, lubricants, and related products..............
Petroleum, petroleum products, and related materials....
33
34
Gas, natural and manufactured.......................................

172.0
171.0
195.4

170.6
168.5
202.9

172.1
169.9
205.4

189.0
187.6
218.1

186.3
181.8
242.6

188.4
183.3
249.3

180.2
163.9
331.8

177.1
152.0
401.0

169.9
153.9
316.9

154.1
144.7
244.5

153.1
143.5
244.4

158.2
150.6
233.5

153.5
149.6
197.8

5 Chemicals and related products, n.e.s. ..........................
52
Inorganic chemicals….....................................................
53
Dying, tanning, and coloring materials............................
Medicinal and pharmaceutical products..........................
54
55
Essential oils; polishing and cleaning preparations.........
57
Plastics in primary forms.................................................
Plastics in nonprimary forms...........................................
58
59
Chemical materials and products, n.e.s. ........................

94.1
91.5
86.1
96.8
89.6
94.3
80.8
99.7

95.5
92.5
87.6
97.5
89.9
95.5
81.5
100.2

95.9
92.6
88.6
97.3
89.4
95.4
80.9
100.0

95.4
92.5
87.9
96.7
88.8
95.3
80.8
101.1

95.1
93.1
87.0
96.0
87.6
96.0
80.0
100.4

94.7
93.7
86.9
95.7
87.2
95.9
79.5
100.4

95.0
94.2
86.9
95.7
86.9
95.8
78.6
100.6

95.8
98.5
88.8
95.1
87.1
95.5
80.3
101.8

96.3
98.9
89.6
94.9
88.2
95.5
84.5
101.6

96.6
97.9
89.1
94.6
88.6
95.8
84.4
101.9

96.3
95.0
88.4
94.0
88.1
95.8
83.2
101.4

95.7
92.4
87.9
93.8
87.7
95.7
83.1
100.6

94.8
91.5
87.7
93.8
87.6
96.8
82.1
100.3
95.3

24
25
28
29

6 Manufactured goods classified chiefly by materials.....
62
64
66
68
69

Rubber manufactures, n.e.s. ..........................................
Paper, paperboard, and articles of paper, pulp,
and paperboard…………………….……………..............
Nonmetallic mineral manufactures, n.e.s. ......................
Nonferrous metals...........................................................
Manufactures of metals, n.e.s. .......................................

97.6

98.0

98.8

97.9

97.6

97.2

97.3

98.2

98.7

97.3

96.3

95.5

91.8

92.1

91.9

91.7

91.6

91.5

91.8

91.8

91.9

91.8

91.6

91.5

91.2

89.1
100.5
110.7
95.7

89.5
100.9
112.5
95.8

89.4
100.9
118.7
95.4

91.4
100.8
114.4
95.4

91.6
100.2
115.7
95.2

91.9
100.2
114.3
94.9

92.2
100.2
114.4
95.0

92.1
100.7
121.0
95.3

92.6
100.5
124.0
95.0

92.8
100.5
116.4
94.9

93.7
100.3
110.9
95.7

92.8
100.2
107.0
95.7

91.9
99.9
106.1
95.6

7 Machinery and transport equipment...............................

89.6

89.6

89.5

89.3

89.2

89.1

89.0

88.9

88.8

88.8

88.4

88.2

88.1

Machinery specialized for particular industries................
General industrial machines and parts, n.e.s.,
and machine parts.........................................................
Computer equipment and office machines......................
Telecommunications and sound recording and
reproducing apparatus and equipment..........................
Electrical machinery and equipment................................
Road vehicles..................................................................

96.1

96.7

96.5

95.9

95.7

95.4

95.3

95.9

96.6

96.3

96.0

95.8

95.7

96.2
60.0

96.7
59.9

96.4
59.9

96.1
59.8

95.5
58.8

95.3
58.8

95.4
58.7

95.9
58.3

95.9
57.8

95.6
57.5

95.1
56.5

94.7
56.4

94.6
56.3

84.6
83.3
102.8

84.3
82.8
102.8

84.2
82.7
102.7

84.1
82.6
102.6

83.9
82.7
102.9

83.7
82.5
102.9

83.6
82.2
102.9

83.0
82.1
102.9

82.8
81.8
102.8

82.8
82.5
102.8

82.1
82.1
102.6

82.0
82.0
102.4

82.1
81.7
102.6

85

Footwear…………...........................................................

100.3

100.9

101.0

100.9

100.8

100.7

100.6

101.0

101.2

101.5

101.1

101.0

100.8

88

Photographic apparatus, equipment, and supplies,
and optical goods, n.e.s. …...........................................

91.6

92.5

92.1

91.4

91.4

91.0

90.7

91.2

91.3

91.4

90.6

90.6

90.3

72
74
75
76
77
78

118

July

Monthly Labor Review

August 2001

36. U.S. export price indexes by end-use category
[1995 = 100]
2000

Category
June

July

Aug.

Sept.

2001
Oct.

Nov.

Dec.

Jan.

Feb.

Mar.

Apr.

May

June

96.3

96.2

96.0

96.6

96.5

96.5

96.3

96.5

96.5

96.2

96.1

95.9

95.7

Foods, feeds, and beverages……………...……………
Agricultural foods, feeds, and beverages….............
Nonagricultural (fish, beverages) food products……

87.1
86.2
98.1

85.1
84.0
97.9

82.8
81.3
99.7

85.3
84.3
97.9

85.8
84.6
99.5

86.7
85.7
98.2

87.4
86.7
96.3

88.2
87.3
98.6

86.6
85.7
97.0

87.3
86.4
97.6

86.6
85.9
95.3

86.2
85.9
91.0

86.8
86.5
90.9

Industrial supplies and materials……………...…………

95.2

95.5

95.4

96.6

96.2

95.8

95.0

95.0

94.9

93.9

93.8

93.1

92.3

Agricultural industrial supplies and materials….......

78.2

77.9

80.3

81.9

82.3

82.0

82.9

82.4

82.6

80.7

80.7

81.0

78.6

Fuels and lubricants…...............................…………
Nonagricultural supplies and materials,
excluding fuel and building materials…………...…
Selected building materials…...............................…

135.6

141.1

137.9

155.0

146.9

150.7

146.2

145.2

147.1

139.8

144.8

147.7

143.4

91.9
89.9

91.7
89.6

91.7
90.5

91.4
89.4

91.6
89.8

90.7
89.0

90.1
89.0

90.4
88.8

90.1
88.2

89.8
87.4

89.2
86.8

88.0
86.3

87.6
87.0

Capital goods……………...…………………………….…
Electric and electrical generating equipment…........
Nonelectrical machinery…...............................………

96.1
99.2
91.7

96.1
99.1
91.6

96.1
99.7
91.6

96.2
99.9
91.5

96.1
99.5
91.5

96.2
99.6
91.5

96.3
99.7
91.5

96.4
100.0
91.5

96.5
100.5
91.5

96.7
100.1
915.0

96.6
100.5
91.3

96.6
100.9
91.1

96.5
100.9
90.9

104.1

104.4

104.4

104.5

104.5

104.4

104.4

104.6

104.5

104.6

104.7

104.7

104.7

Consumer goods, excluding automotive……………... 102.3
Nondurables, manufactured…...............................… 102.1
Durables, manufactured…………...………..........…… 101.3

102.5
102.4
101.5

102.4
102.4
101.4

102.2
102.2
101.3

102.3
102.4
101.2

102.2
102.2
101.2

102.0
102.0
101.1

102.1
102.0
101.3

102.0
101.5
101.5

101.9
101.3
101.5

101.8
101.2
101.3

101.7
101.2
101.2

101.8
101.3
101.3

82.6
97.8

80.9
97.7

83.5
98.0

83.9
97.9

84.7
97.8

85.7
97.5

86.1
97.7

84.9
97.7

85.1
97.5

84.7
97.4

84.7
97.1

84.8
96.9

ALL COMMODITIES……………...................................

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

Agricultural commodities……………...…………………
Nonagricultural commodities……………...……………

84.4
97.6

Monthly Labor Review

August 2001

119

Current Labor Statistics:

Price Data

37. U.S. import price indexes by end-use category
[1995 = 100]
2000

Category
June

July

2001

Aug.

Sept.

Oct.

Nov.

Dec.

Jan.

Feb.

Mar.

Apr.

May

June

99.6

99.7

99.9

101.0

100.6

100.6

100.0

100.0

99.3

97.8

97.2

97.5

97.1

Foods, feeds, and beverages……………...…………… 91.1
Agricultural foods, feeds, and beverages….............
84.1
Nonagricultural (fish, beverages) food products…… 109.7

91.1
83.7
110.5

91.3
83.2
112.9

90.7
82.5
112.5

90.7
83.0
111.2

89.4
81.9
109.5

91.0
84.2
109.1

90.8
84.3
107.9

89.8
83.4
106.7

90.6
85.6
103.9

88.9
83.8
102.4

88.7
83.5
102.1

87.6
82.3
101.4

Industrial supplies and materials……………...………… 121.8

121.8

122.8

127.6

126.6

126.9

124.5

124.4

122.3

116.1

115.4

116.7

115.6

Fuels and lubricants…...............................………… 170.6
Petroleum and petroleum products…………...…… 170.4

169.2
168.0

170.9
169.5

187.4
187.1

184.5
181.9

186.8
183.6

178.7
165.6

176.7
155.7

169.3
156.1

153.3
145.9

152.3
144.2

157.4
151.0

153.1
149.8

87.0
Paper and paper base stocks…...............................
Materials associated with nondurable
supplies and materials…...............................……… 91.7
Selected building materials…...............................… 105.0
Unfinished metals associated with durable goods… 105.0
Nonmetals associated with durable goods…...........
87.0

87.5

87.6

89.8

90.4

90.6

91.0

91.0

91.2

90.8

91.1

89.0

87.1

92.7
103.4
106.5
87.7

93.4
100.2
109.5
87.6

92.8
98.7
105.9
87.2

92.8
99.3
105.6
87.3

92.6
97.2
104.1
87.1

93.3
99.1
103.7
87.2

94.1
95.3
107.2
87.8

94.3
96.0
108.7
88.7

94.4
96.2
103.8
88.8

93.1
98.3
101.1
88.5

92.1
104.9
98.2
88.2

90.9
116.5
97.9
88.0

80.9
94.3
77.1

80.9
94.1
77.1

80.7
93.7
77.0

80.6
93.5
76.8

80.2
93.4
76.4

80.1
93.1
76.3

80.0
93.1
76.1

79.9
93.1
76.0

79.7
92.9
75.8

79.3
95.2
75.6

79.3
94.5
75.0

79.1
94.9
74.8

79.1
95.0
74.7

102.7

102.8

102.7

102.5

102.6

102.7

102.7

102.7

102.6

102.6

102.5

102.3

102.4

96.5
99.5
93.2
98.0

96.8
99.8
93.4
99.5

96.8
100.0
93.2
99.2

96.6
99.8
93.0
99.6

96.6
99.8
92.8
99.8

96.5
99.8
92.8
99.1

96.4
99.6
92.8
98.8

96.6
92.9
92.9
99.5

96.6
99.8
92.8
101.5

96.6
100.1
92.8
99.1

96.4
100.0
92.5
98.0

96.4
100.0
92.3
99.4

96.2
99.8
92.1
99.0

ALL COMMODITIES……………...................................

Capital goods……………...…………………………….…
Electric and electrical generating equipment…........
Nonelectrical machinery…...............................………
Automotive vehicles, parts, and engines……………...
Consumer goods, excluding automotive……………...
Nondurables, manufactured…...............................…
Durables, manufactured…………...………..........……
Nonmanufactured consumer goods…………...……

38. U.S. international price Indexes for selected categories of services
[1995 = 100]
1999

Category
June

Sept.

2000
Dec.

Mar.

June

2001

Sept.

Dec.

Mar.

June

Air freight (inbound)…………….....................................
Air freight (outbound)……………...………………………

86.2
92.8

87.9
92.7

90.7
91.7

88.9
91.7

88.4
92.8

88.5
92.6

87.4
92.6

86.5
92.6

84.0
90.5

Air passenger fares (U.S. carriers)………………………
Air passenger fares (foreign carriers)….........................
Ocean liner freight (inbound)…………...………..........…

112.3
106.3
133.7

114.2
108.6
148.0

106.8
102.2
139.4

107.3
102.6
136.3

113.3
107.9
143.0

115.5
109.1
142.8

111.9
103.2
142.8

114.2
106.4
145.1

119.2
109.7
142.3

120

Monthly Labor Review

August 2001

39. Indexes of productivity, hourly compensation, and unit costs, quarterly data seasonally adjusted
[1992 = 100]
Quarterly indexes
1998

Item

1999

2000

2001

II

III

IV

I

II

III

IV

I

II

III

IV

I

II

Business
Output per hour of all persons.......................................
Compensation per hour…………………………….………
Real compensation per hour………………………………
Unit labor costs…...............................……………………
Unit nonlabor payments…………...………..........………
Implicit price deflator………………………………………

110.3
118.9
104.1
107.8
115.1
110.5

110.8
120.3
105.0
108.6
114.5
110.7

111.8
121.6
105.7
108.8
114.6
110.9

112.5
123.0
106.4
109.3
115.1
111.4

112.7
124.3
106.8
110.4
114.2
111.8

114.0
125.9
107.4
110.5
114.4
111.9

116.1
127.1
107.6
109.5
116.9
112.2

115.0
129.0
108.1
112.1
114.2
112.9

117.1
131.7
109.6
112.5
115.2
113.5

117.4
133.8
110.3
114.0
113.9
113.9

118.2
136.8
112.0
115.7
112.1
114.4

118.2
138.2
112.3
117.2
111.8
115.2

119.0
140.4
112.9
117.9
112.1
115.8

Nonfarm business
Output per hour of all persons.......................................
Compensation per hour…………………………….………
Real compensation per hour………………………………
Unit labor costs…...............................……………………
Unit nonlabor payments…………...………..........………
Implicit price deflator………………………………………

110.1
118.3
103.6
107.5
116.2
110.7

110.5
119.8
104.5
108.4
115.7
111.0

111.4
120.9
105.1
108.6
115.8
111.2

111.9
122.1
105.6
109.0
116.7
111.8

112.0
123.4
106.0
110.2
115.8
112.2

113.4
125.0
106.6
110.2
116.1
112.4

115.6
126.3
107.0
109.3
118.6
112.7

114.5
128.4
107.6
112.1
116.0
113.5

116.3
130.7
108.8
112.4
116.7
114.0

116.7
133.0
109.7
114.0
115.4
114.5

117.4
135.9
111.3
115.8
113.5
114.9

117.4
137.6
111.5
117.2
113.1
115.7

118.1
139.1
111.9
117.8
113.4
116.2

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………………………………………

111.7
115.2
100.9
102.6
103.1
101.2
147.7
113.0
106.4

113.1
116.7
101.8
102.5
103.2
100.7
152.0
113.8
106.7

113.7
117.8
102.4
103.2
103.6
102.1
145.3
113.1
106.8

114.6
119.0
103.0
103.2
103.9
101.3
150.6
113.9
107.2

115.3
120.3
103.3
103.7
104.3
102.2
148.6
114.0
107.5

116.6
121.8
103.9
104.0
104.5
102.9
144.4
113.5
107.5

118.3
123.0
104.2
103.9
104.0
103.4
147.0
114.5
107.5

117.7
124.7
104.5
105.9
106.0
105.5
134.3
112.9
108.3

119.7
127.2
105.8
106.0
106.2
105.3
137.8
113.6
108.7

120.9
129.3
106.6
106.6
106.9
105.6
133.8
112.8
108.9

121.4
132.3
108.3
108.2
109.0
106.0
118.5
109.2
109.0

121.5
134.1
108.7
109.6
110.3
107.5
109.2
107.9
109.5

–
–
–
–
–
–
–
–
–

Manufacturing
Output per hour of all persons....................................... 123.2
Compensation per hour…………………………….……… 116.8
Real compensation per hour……………………………… 102.2
Unit labor costs…...............................……………………
94.8

125.7
118.0
103.0
93.9

126.8
119.0
103.4
93.9

128.9
119.9
103.7
93.0

130.2
121.2
104.1
93.1

131.9
122.8
104.7
93.1

135.0
124.1
105.2
91.9

135.2
125.9
105.5
93.2

137.3
128.1
106.6
93.3

139.4
131.2
108.3
94.1

141.3
135.2
110.7
95.7

140.0
137.2
111.3
98.0

139.9
139.3
112.1
99.6

NOTE Dash indicates data not available.

Monthly Labor Review

August 2001

121

Current Labor Statistics:

Productivity Data

40. Annual indexes of multifactor productivity and related measures, selected years
[1996 = 100, unless otherwise indicated]
Item

1960

1970

1980

1990

1991

1992

1993

1994

1995

1996

1997

1998

Private business
Productivity:
Output per hour of all persons......…………….............
45.6
Output per unit of capital services……………………… 110.4
65.2
Multifactor productivity……………………………………
Output…...............................………………………….…… 27.5
Inputs:
Labor input...................................................................
54.0
Capital services…………...………..........………….……
24.9
Combined units of labor and capital input……………… 42.3
Capital per hour of all persons.......................…………… 41.3

63.0
111.1
80.0
42.0

75.8
101.5
88.3
59.4

90.2
99.3
95.3
83.6

91.3
96.1
94.4
82.6

94.8
97.7
96.6
85.7

95.4
98.5
97.1
88.5

96.6
100.3
98.1
92.8

97.3
99.7
98.4
95.8

100.0
100.0
100.0
100.0

102.0
100.5
101.1
105.2

104.8
100.1
102.6
110.6

61.0
37.8
52.4
56.7

71.9
58.6
67.3
74.7

89.4
84.2
87.7
90.8

88.3
86.0
87.5
95.0

89.3
87.7
88.8
97.0

91.8
89.8
91.1
96.8

95.6
92.6
94.6
96.3

98.0
96.0
97.3
97.6

100.0
100.0
100.0
100.0

103.7
104.7
104.0
101.5

106.4
110.4
107.7
104.7

64.9
118.3
82.6
41.9

77.3
105.7
90.5
59.6

90.3
100.0
95.6
83.5

91.4
96.6
94.7
82.5

94.8
97.9
96.6
85.5

95.3
98.8
97.1
88.4

96.5
100.3
98.1
92.6

97.5
99.9
98.6
95.8

100.0
100.0
100.0
100.0

101.7
100.2
100.9
105.1

104.5
99.8
102.4
110.6

59.3
35.5
50.7
54.8

70.7
56.4
65.9
73.1

89.2
83.5
87.3
90.3

88.0
85.4
87.1
94.7

89.0
87.3
88.4
96.8

91.8
89.5
91.0
96.5

95.4
92.3
94.4
96.3

97.8
95.9
97.2
97.6

100.0
100.0
100.0
100.0

103.8
104.9
104.2
101.5

106.6
110.8
108.0
104.7

54.2
116.5
84.4
56.5

70.1
100.9
86.6
75.3

92.8
101.6
99.3
97.3

95.0
97.5
98.3
95.4

100.0
100.0
100.0
100.0

101.9
101.1
100.4
103.3

105.0
104.0
102.6
108.7

109.0
105.0
105.0
113.4

112.8
104.5
106.1
116.9

117.1
105.6
109.8
123.5

124.3
106.5
113.2
130.7

104.2
48.5
85.4
44.8
48.8
67.0

107.5
74.7
92.5
75.0
73.7
87.0

104.8
95.8
99.9
92.5
92.5
98.0

100.4
97.9
100.1
93.6
92.1
97.0

100.0
100.0
100.0
100.0
100.0
100.0

101.4
102.2
103.7
105.7
103.0
102.9

103.6
104.5
107.3
111.3
105.1
106.0

104.0
108.0
109.5
112.8
110.0
107.9

103.7
111.9
107.0
120.4
108.9
110.2

105.5
116.9
103.9
120.4
114.2
112.5

105.2
122.8
109.2
127.2
116.8
115.5

Private nonfarm business
Productivity:
Output per hour of all persons........……………………… 48.7
Output per unit of capital services……………………… 120.1
Multifactor productivity……………………………………
69.1
Output…...............................………………………….…… 27.2
Inputs:
Labor input...................................................................
50.1
Capital services…………...………..........………….……
22.6
Combined units of labor and capital input……………… 39.3
Capital per hour of all persons......………………………… 40.5
Manufacturing (1992 = 100)
Productivity:
Output per hour of all persons...………………………… 41.8
Output per unit of capital services……………………… 124.3
Multifactor productivity……………………………………
72.7
Output…...............................………………………….…… 38.5
Inputs:
Hours of all persons.....................................................
92.0
Capital services…………...………..........………….……
30.9
Energy……………….………........................................
51.3
38.2
Nonenergy materials....................................................
Purchased business services......................................
28.2
Combined units of all factor inputs…………...………...
52.9

122

Monthly Labor Review

August 2001

41. Annual indexes of productivity, hourly compensation, unit costs, and prices, selected years
[1992 = 100]
Item

1960

1970

1980

1990

1991

1993

1994

1995

1996

1997

1998

1999

2000

Business
Output per hour of all persons.......................................
Compensation per hour…………………………….………
Real compensation per hour………………………………
Unit labor costs…...............................……………………
Unit nonlabor payments…………...………..........………
Implicit price deflator………………………………………

48.8
13.7
60.0
28.0
25.2
27.0

67.0
23.5
78.9
35.1
31.6
33.9

80.4
54.2
89.4
67.4
61.5
65.2

95.2
90.7
96.5
95.3
93.9
94.8

96.3
95.0
97.5
98.7
97.0
98.1

100.5
102.5
99.9
101.9
102.5
102.2

101.9
104.5
99.7
102.6
106.4
104.0

102.6
106.7
99.3
104.1
109.4
106.0

105.4
110.1
99.7
104.5
113.3
107.7

107.8
113.5
100.6
105.3
117.1
109.7

110.8
119.6
104.6
108.0
115.1
110.6

113.8
125.1
107.1
109.9
115.1
111.8

116.9
132.8
110.1
113.6
113.9
113.7

Nonfarm business
Output per hour of all persons.......................................
Compensation per hour…………………………….………
Real compensation per hour………………………………
Unit labor costs…...............................……………………
Unit nonlabor payments…………...………..........………
Implicit price deflator………………………………………

51.9
14.3
62.8
27.5
24.6
26.5

68.9
23.7
79.5
34.4
31.3
33.3

82.0
54.6
90.0
66.5
60.5
64.3

95.3
90.5
96.3
95.0
93.6
94.5

96.4
95.0
97.5
98.5
97.1
98.0

100.5
102.2
99.6
101.7
103.0
102.2

101.8
104.3
99.5
102.5
106.9
104.1

102.8
106.6
99.2
103.7
110.4
106.1

105.4
109.8
99.4
104.2
113.5
107.6

107.5
113.1
100.2
105.2
118.0
109.8

110.4
119.0
104.0
107.7
116.3
110.8

113.2
124.2
106.4
109.7
116.8
112.3

116.2
132.0
109.4
113.6
115.4
114.2

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………………………………………

55.4
15.6
68.3
26.8
28.1
23.3
50.2
30.2
28.8

70.4
25.3
84.7
34.8
35.9
31.9
44.4
35.1
35.6

81.1
56.4
93.1
68.4
69.6
65.1
68.8
66.0
68.4

95.4
90.8
96.7
95.9
95.2
98.0
94.3
97.1
95.8

97.7
95.3
97.8
98.8
97.5
102.1
93.0
99.7
98.3

100.7
102.0
99.5
101.0
101.3
100.2
113.2
103.5
102.1

103.1
104.2
99.4
101.1
101.0
101.3
131.7
109.0
103.7

104.2
106.2
98.8
102.0
101.9
102.2
139.0
111.6
105.1

107.5
109.0
98.7
101.2
101.4
100.6
152.2
113.8
105.5

108.4
110.3
97.8
101.5
101.8
100.9
156.9
115.2
106.2

112.3
115.9
101.3
102.6
103.2
101.2
148.9
113.4
106.6

116.2
121.1
103.7
103.7
104.2
102.5
147.6
114.0
107.4

119.9
128.3
106.4
106.7
107.0
105.6
131.0
112.1
108.7

Manufacturing
Output per hour of all persons.......................................
Compensation per hour…………………………….………
Real compensation per hour………………………………
Unit labor costs…...............................……………………
Unit nonlabor payments…………...………..........………
Implicit price deflator………………………………………

41.8
14.9
65.2
35.6
26.8
30.2

54.2
23.7
79.5
43.8
29.3
34.9

70.1
55.6
91.7
79.3
80.2
79.8

92.8
90.8
96.6
97.8
99.7
99.0

95.0
95.6
98.1
100.6
99.0
99.6

101.9
102.7
100.2
100.8
100.9
100.9

105.0
105.6
100.8
100.7
102.8
102.0

109.0
107.9
100.4
99.0
106.9
103.9

112.8
109.3
99.0
96.9
109.9
104.9

117.1
111.4
98.8
95.1
109.6
104.0

124.3
117.3
102.6
94.4
104.4
100.5

129.6
122.0
104.5
94.1
105.5
101.1

46.3
130.1
107.8
94.1
–
–

August 2001

123

Dash indicates data not available.

Monthly Labor Review

Current Labor Statistics:

Productivity Data

42. Annual indexes of output per hour for selected 3-digit SIC industries
[1987 = 100]
Industry

SIC

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

Mining
Copper ores……………………………………………
Gold and silver ores…………………...………….……
Bituminous coal and lignite mining……………………
Crude petroleum and natural gas……………………
Crushed and broken stone……………………………

102
104
122
131
142

102.7
122.3
118.7
97.0
102.2

100.5
127.4
122.4
97.9
99.8

115.2
141.6
133.0
102.1
105.0

118.1
159.8
141.2
105.9
103.6

126.0
160.8
148.1
112.4
108.7

117.2
144.2
155.9
119.4
105.4

116.5
138.3
168.0
123.9
107.2

118.9
158.5
176.6
125.2
112.6

118.3
187.6
188.0
127.4
110.2

105.5
200.0
192.2
132.3
104.8

Meat products…………………………………………
Dairy products…………………………………………
Preserved fruits and vegetables………………………
Grain mill products……………………………………
Bakery products…………………………………………

201
202
203
204
205

97.1
107.3
95.6
105.4
92.7

99.6
108.3
99.2
104.9
90.6

104.6
111.4
100.5
107.8
93.8

104.3
109.6
106.8
109.2
94.4

101.2
111.8
107.6
108.4
96.4

102.3
116.4
109.1
115.4
97.3

97.4
116.0
109.2
108.0
95.6

102.5
119.3
110.7
118.2
99.1

102.3
119.3
117.8
126.2
100.8

102.2
114.1
120.0
130.4
107.5

Sugar and confectionery products……………………
Fats and oils……………………………………………
Beverages………………………………………………
Miscellaneous food and kindred products……………
Cigarettes………………………………………………

206
207
208
209
211

103.2
118.1
117.0
99.2
113.2

102.0
120.1
120.0
101.7
107.6

99.8
114.1
127.1
101.5
111.6

104.5
112.6
126.4
105.2
106.5

106.2
111.8
130.1
100.9
126.6

108.3
120.3
133.5
102.9
142.9

113.8
110.1
135.0
109.1
147.2

116.7
120.2
135.5
104.1
147.2

123.0
137.3
136.4
112.7
152.2

130.0
156.1
132.4
116.3
135.8

Broadwoven fabric mills, cotton………………………
Broadwoven fabric mills, manmade…………………
Narrow fabric mills……………………….……………
Knitting mills……………………………………………
Textile finishing, except wool…………………………

221
222
224
225
226

103.1
111.3
96.5
107.5
83.4

111.2
116.2
99.6
114.0
79.9

110.3
126.2
112.9
119.3
78.6

117.8
131.7
111.4
127.9
79.3

122.1
142.5
120.1
134.1
81.2

134.0
145.3
118.9
138.3
78.5

137.3
147.6
126.3
150.3
79.2

131.2
162.2
110.8
138.0
94.3

136.2
168.6
117.7
135.9
99.1

138.7
171.9
122.4
144.8
101.0

Carpets and rugs………………………………………
Yarn and thread mills…………………………………
Miscellaneous textile goods……………………………
Men's and boys' furnishings………………….………
Women's and misses' outerwear……………………

227
228
229
232
233

93.2
110.2
109.2
102.1
104.1

89.2
111.4
104.6
108.4
104.3

96.1
119.6
106.5
109.1
109.4

97.1
126.6
110.4
108.4
121.8

93.3
130.7
118.5
111.7
127.4

95.8
137.4
123.7
123.4
135.5

100.2
147.4
123.1
134.7
141.6

100.3
150.4
118.7
162.1
149.9

102.3
153.0
120.1
174.7
151.9

97.8
169.5
127.0
187.0
174.5

Women's and children's undergarments……………
Hats, caps, and millinery………………………...……
Miscellaneous apparel and accessories……………
Miscellaneous fabricated textile products……………
Sawmills and planing mills……………………………

234
235
238
239
242

102.1
89.2
90.6
99.9
99.8

113.7
91.1
91.8
100.7
102.6

117.4
93.6
91.3
107.5
108.1

124.5
87.2
94.0
108.5
101.9

138.0
77.7
105.5
107.8
103.3

161.3
84.3
116.8
109.2
110.2

174.5
82.2
120.1
105.6
115.6

208.9
87.1
101.4
119.2
116.9

216.4
99.5
107.7
117.2
118.7

293.0
108.7
105.8
129.2
125.4

Millwork, plywood, and structural members…………
Wood containers………………...……………………
Wood buildings and mobile homes…………………
Miscellaneous wood products…………………………
Household furniture……………………………………

243
244
245
249
251

98.0
111.2
103.1
107.7
104.5

98.0
113.1
103.0
110.5
107.1

99.9
109.4
103.1
114.2
110.5

97.0
100.1
103.8
115.3
110.6

94.5
100.9
98.3
111.8
112.5

92.7
106.1
97.0
115.4
116.9

92.4
106.7
96.7
114.4
121.6

89.1
106.2
100.3
123.4
121.3

91.3
106.6
99.2
131.2
125.8

90.7
105.0
96.8
141.3
128.7

Office furniture…………………………………………
Public building and related furniture…………………
Partitions and fixtures…………………………………
Miscellaneous furniture and fixtures…………………
Pulp mills…………………………………………………

252
253
254
259
261

95.0
119.8
95.6
103.5
116.7

94.1
120.2
93.0
102.1
128.3

102.5
140.6
102.7
99.5
137.3

103.2
161.0
107.4
103.6
122.5

100.5
157.4
98.9
104.7
128.9

101.1
173.3
101.2
110.0
131.9

106.4
181.5
97.5
113.2
132.6

118.3
214.9
121.1
110.7
82.3

113.1
207.6
125.6
121.9
86.6

109.8
210.9
127.0
122.7
88.4

Paper mills………………………………………………
Paperboard mills………………………………………
Paperboard containers and boxes……………………
Miscellaneous converted paper products……………
Newspapers……………………………………...……

262
263
265
267
271

102.3
100.6
101.3
101.4
90.6

99.2
101.4
103.4
105.3
85.8

103.3
104.4
105.2
105.5
81.5

102.4
108.4
107.9
107.9
79.4

110.2
114.9
108.4
110.6
79.9

118.6
119.5
105.1
113.3
79.0

111.6
118.0
106.3
113.6
77.4

112.0
126.7
109.7
119.5
79.0

114.9
127.8
113.5
122.9
83.6

122.7
131.0
113.5
127.3
86.3

Periodicals………………………………………………
Books……………………………………………………
Miscellaneous publishing………………………………
Commercial printing……………………………………
Manifold business forms………………………………

272
273
274
275
276

93.9
96.6
92.2
102.5
93.0

89.5
100.8
95.9
102.0
89.1

92.9
97.7
105.8
108.0
94.5

89.5
103.5
104.5
106.9
91.1

81.9
103.0
97.5
106.5
82.0

87.8
101.6
94.8
107.2
76.9

89.1
99.3
93.6
108.3
75.2

100.1
102.6
114.5
108.8
77.9

115.0
101.0
119.5
109.9
76.7

115.1
105.4
128.3
115.2
73.6

Greeting cards…………………………………………
Blankbooks and bookbinding…………………………
Printing trade services…………………………………
Industrial inorganic chemicals…………………………
Plastics materials and synthetics……………………

277
278
279
281
282

100.6
99.4
99.3
106.8
100.9

92.7
96.1
100.6
109.7
100.0

96.7
103.6
112.0
109.7
107.5

91.4
98.7
115.3
105.6
112.0

89.0
105.4
111.0
102.3
125.3

92.5
108.7
116.7
109.3
128.3

90.8
114.5
126.2
110.1
125.3

92.2
114.2
123.3
116.8
135.4

104.2
116.4
126.7
145.8
142.2

103.9
123.3
120.5
170.7
145.7

Drugs……………………………………………………
Soaps, cleaners, and toilet goods……………………
Paints and allied products……………………………
Industrial organic chemicals…………………………
Agricultural chemicals…………………………………
See footnotes at end of table.

283
284
285
286
287

103.8
103.8
106.3
101.4
104.7

104.5
105.3
104.3
95.8
99.5

99.5
104.4
102.9
94.6
99.5

99.7
108.7
108.8
92.2
103.8

104.6
111.2
116.7
99.9
105.0

108.7
118.6
118.0
98.6
108.5

112.5
120.9
125.6
99.0
110.0

112.4
126.4
126.4
111.2
119.8

104.3
122.7
126.8
105.7
117.5

104.8
116.8
125.6
111.3
106.9

Manufacturing

124

Monthly Labor Review

August 2001

42. Continued—-Annual indexes of output per hour for selected 3-digit SIC industries
[1987 = 100]
Industry

SIC

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

Miscellaneous chemical products……………………
Petroleum refining……………………...………………
Asphalt paving and roofing materials…………………
Miscellaneous petroleum and coal products………
Tires and inner tubes…………………………………

289
291
295
299
301

97.3
109.2
98.0
94.8
103.0

96.1
106.6
94.1
90.6
102.4

101.8
111.3
100.4
101.5
107.8

107.1
120.1
108.0
104.2
116.5

105.7
123.8
104.9
96.3
124.1

107.8
132.3
111.2
87.4
131.1

110.1
142.0
113.1
87.1
138.8

120.3
149.2
123.1
96.5
149.1

120.6
155.7
124.7
98.5
144.2

128.1
169.5
115.7
90.7
145.5

Hose and belting and gaskets and packing…………
Fabricated rubber products, n.e.c……………………
Miscellaneous plastics products, n.e.c………………
Footwear, except rubber………………………………
Flat glass…………………………………………………

305
306
308
314
321

96.1
109.0
105.7
101.1
84.5

92.4
109.9
108.3
94.4
83.6

97.8
115.2
114.4
104.2
92.7

99.7
123.1
116.7
105.2
97.7

102.7
119.1
120.8
113.0
97.6

104.6
121.5
121.0
117.1
99.6

107.4
121.0
124.7
126.1
101.5

113.5
125.3
129.9
121.4
107.6

112.7
132.3
133.8
110.9
114.0

114.0
140.8
141.2
131.6
127.7

Glass and glassware, pressed or blown……………
Products of purchased glass…………………………
Cement, hydraulic………………………………………
Structural clay products………………………………
Pottery and related products…………………………

322
323
324
325
326

104.8
92.6
112.4
109.6
98.6

102.3
97.7
108.3
109.8
95.8

108.9
101.5
115.1
111.4
99.5

108.7
106.2
119.9
106.8
100.3

112.9
105.9
125.6
114.0
108.4

115.7
106.1
124.3
112.6
109.3

121.4
122.0
128.7
119.6
119.3

128.3
125.1
133.1
111.9
123.2

135.2
122.0
134.1
114.8
127.1

143.6
134.0
139.6
124.0
120.8

Concrete, gypsum, and plaster products……………
Miscellaneous nonmetallic mineral products………
Blast furnace and basic steel products………………
Iron and steel foundries………………………………
Primary nonferrous metals……………………………

327
329
331
332
333

102.3
95.4
109.7
106.1
102.3

101.2
94.0
107.8
104.5
110.7

102.5
104.3
117.0
107.2
101.9

104.6
104.5
133.6
112.1
107.9

101.5
106.3
142.4
113.0
105.3

104.5
107.8
142.6
112.7
111.0

107.3
110.4
147.5
116.2
110.8

107.6
114.6
155.0
120.8
112.0

112.8
114.7
151.0
121.1
125.8

114.4
114.6
148.9
126.2
131.2

Nonferrous rolling and drawing………………………
Nonferrous foundries (castings)………………………
Miscellaneous primary metal products………………
Metal cans and shipping containers…………………
Cutlery, handtools, and hardware……………………

335
336
339
341
342

92.7
104.0
113.7
117.6
97.3

91.0
103.6
109.1
122.9
96.8

96.0
103.6
114.5
127.8
100.1

98.3
108.5
111.3
132.3
104.0

101.2
112.1
134.5
140.9
109.2

99.2
117.8
152.2
144.2
111.3

104.0
122.3
149.6
155.2
118.2

111.3
127.0
136.2
160.3
114.6

115.2
131.5
140.0
163.8
115.7

122.7
130.8
150.4
160.3
123.9

Plumbing and heating, except electric………………
Fabricated structural metal products…………………
Metal forgings and stampings…………………………
Metal services, n.e.c……………………………………
Ordnance and accessories, n.e.c……………………

343
344
346
347
348

102.6
98.8
95.6
104.7
82.1

102.0
100.0
92.9
99.4
81.5

98.4
103.9
103.7
111.6
88.6

102.0
104.8
108.7
120.6
84.6

109.1
107.7
108.5
123.0
83.6

109.2
105.8
109.3
127.7
87.6

118.6
106.5
113.6
128.4
87.5

127.3
111.9
120.2
124.4
93.7

130.3
112.7
125.9
127.3
96.6

126.9
112.7
130.3
127.9
92.2

Miscellaneous fabricated metal products……………
Engines and turbines…………………………………
Farm and garden machinery…………………………
Construction and related machinery…………………
Metalworking machinery………………………………

349
351
352
353
354

97.5
106.5
116.5
107.0
101.1

97.4
105.8
112.9
99.1
96.4

101.1
103.3
113.9
102.0
104.3

102.0
109.2
118.6
108.2
107.4

103.2
122.3
125.0
117.7
109.9

106.6
122.7
134.7
122.1
114.8

108.3
136.6
137.2
123.3
114.9

107.7
136.9
141.2
132.5
119.2

111.5
145.9
148.5
137.5
119.8

110.3
151.2
125.5
137.2
123.5

Special industry machinery……………………………
General industrial machinery…………………………
Computer and office equipment………………………
Refrigeration and service machinery…………………
Industrial machinery, n.e.c……………………………

355
356
357
358
359

107.5
101.5
138.1
103.6
107.3

108.3
101.6
149.6
100.7
109.0

106.0
101.6
195.7
104.9
117.0

113.6
104.8
258.6
108.6
118.5

121.2
106.7
328.6
110.7
127.4

132.3
109.0
469.4
112.7
138.8

134.0
109.4
681.3
114.7
141.4

131.7
110.0
960.2
115.0
129.3

125.1
111.2
1350.6
121.4
127.5

139.3
111.4
1840.2
123.2
134.3

Electric distribution equipment………………………
Electrical industrial apparatus
Household appliances…………………………………
Electric lighting and wiring equipment………………
Communications equipment…………………………

361
362
363
364
366

106.3
107.7
105.8
99.9
123.8

106.5
107.1
106.5
97.5
129.1

119.6
117.1
115.0
105.7
154.9

122.2
132.9
123.4
107.8
163.0

131.8
134.9
131.4
113.4
186.4

143.0
150.8
127.3
113.7
200.6

143.9
154.3
127.4
116.9
229.5

142.8
164.2
142.9
121.8
275.3

147.5
162.3
150.3
129.2
276.0

146.6
162.9
150.2
132.4
327.1

Electronic components and accessories……………
Miscellaneous electrical equipment & supplies……
Motor vehicles and equipment………………………
Aircraft and parts………………………………………
Ship and boat building and repairing…………………

367
369
371
372
373

133.4
90.6
102.4
98.9
103.7

154.7
98.6
96.6
108.2
96.3

189.3
101.3
104.2
112.3
102.7

217.9
108.2
106.2
115.2
106.2

274.1
110.5
108.8
109.6
103.8

401.5
114.1
106.7
107.9
98.0

514.9
123.1
107.2
113.0
99.2

613.4
128.3
116.3
114.7
105.3

768.0
135.3
125.2
140.1
102.0

107.0
140.7
136.5
139.6
112.6

Railroad equipment…………………..…………………
Motorcycles, bicycles, and parts………………………
Guided missiles, space vehicles, parts………………
Search and navigation equipment……………………
Measuring and controlling devices……………………

374
375
376
381
382

141.1
93.8
116.5
112.7
106.4

146.9
99.8
110.5
118.9
113.1

147.9
108.4
110.5
122.1
119.9

151.0
130.9
122.1
129.1
124.0

152.5
125.1
118.9
132.1
133.8

150.0
120.3
121.0
149.5
146.4

148.3
125.5
129.4
142.2
150.5

184.2
120.4
136.5
149.5
142.4

189.1
127.7
142.4
149.1
143.5

205.1
121.4
158.2
139.7
152.9

Medical instruments and supplies……………………
Ophthalmic goods………………………………………
Photographic equipment & supplies…………………
Jewelry, silverware, and plated ware…………………
Musical instruments……………………………………

384
385
386
391
393

116.9
121.2
107.8
99.3
97.1

118.7
125.1
110.2
95.8
96.9

123.5
144.5
116.4
96.7
96.0

127.3
157.8
126.9
96.7
95.6

126.7
160.6
132.7
99.5
88.7

131.5
167.2
129.5
100.2
86.9

139.8
188.2
128.7
102.6
78.8

147.4
196.3
121.5
114.2
82.9

158.6
199.1
124.8
113.1
81.4

160.2
229.5
147.2
133.9
86.4

See footnotes at end of table.

Monthly Labor Review

August 2001

125

Current Labor Statistics:

Productivity Data

42. Continued—Annual indexes of output per hour for selected 3-digit SIC industries
[1987 = 100]
Industry

SIC

Toys and sporting goods………………………………
Pens, pencils, office, and art supplies………………
Costume jewelry and notions…………………………
Miscellaneous manufactures…………………………

394
395
396
399

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

108.1
118.2
105.3
106.5

109.7
116.8
106.7
109.2

104.9
111.3
110.8
109.5

114.2
111.6
115.8
107.7

109.7
129.9
129.0
106.1

113.6
135.2
143.7
108.1

119.9
144.1
142.2
112.8

125.7
127.5
118.0
109.4

131.6
132.5
131.2
108.5

124.0
129.3
150.2
111.2

118.5
111.1
104.0
92.9

127.8
116.9
103.7
92.5

139.6
123.4
104.5
96.9

145.4
126.6
107.1
100.2

150.3
129.5
106.6
105.7

156.2
125.4
106.5
108.6

167.0
130.9
104.7
111.1

169.8
132.4
108.3
111.6

173.3
129.9
109.7
110.7

182.3
131.6
110.3
108.3

481
483
484
491,3 (pt.)
492,3 (pt.)

113.3
104.9
92.6
110.1
105.8

119.8
106.1
87.6
113.4
109.6

127.7
108.3
88.5
115.2
111.1

135.5
106.7
85.3
120.6
121.8

142.2
110.1
83.4
126.8
125.6

148.1
109.6
84.5
135.0
137.1

159.5
105.8
81.9
146.5
145.9

160.9
101.1
84.7
150.5
158.6

170.3
100.7
83.5
160.1
144.4

189.1
101.8
81.5
162.7
145.0

Lumber and other building materials dealers………
Paint, glass, and wallpaper stores……………………
Hardware stores………………………………………
Retail nurseries, lawn and garden supply stores……
Department stores………………………………………

521
523
525
526
531

104.3
106.8
115.3
84.7
96.8

102.3
100.4
108.7
89.3
102.0

106.4
107.6
115.2
101.2
105.4

111.4
114.2
113.9
107.1
110.4

118.9
127.8
121.2
117.0
113.4

117.8
130.9
115.5
117.4
115.9

121.6
133.5
119.5
136.4
123.5

121.8
134.8
119.0
127.5
128.8

134.2
163.5
137.8
133.7
135.5

142.3
163.2
149.3
151.2
147.4

Variety stores……………………………………………
Miscellaneous general merchandise stores…………
Grocery stores…………………………………………
Meat and fish (seafood) markets……………………
Retail bakeries…………………………………………

533
539
541
542
546

154.4
118.6
96.6
98.9
91.2

158.8
124.8
96.3
90.8
96.7

173.7
140.4
96.5
99.2
96.5

191.5
164.2
96.0
97.7
86.5

197.4
164.8
95.4
95.7
85.3

211.3
167.3
93.9
94.4
83.0

238.4
167.6
92.1
86.4
75.9

257.7
170.3
91.7
90.8
67.6

268.7
185.7
92.2
95.7
68.1

319.5
195.2
95.4
99.3
83.8

New and used car dealers……………………………
Auto and home supply stores…………………………
Gasoline service stations………………………………
Men's and boy's wear stores…………………………
Women's clothing stores………………………………

551
553
554
561
562

106.7
103.6
103.0
115.6
106.6

104.9
100.2
104.8
121.9
111.2

107.4
101.6
110.2
122.3
123.6

108.6
100.8
115.9
119.5
130.0

109.7
105.3
121.1
121.8
130.4

108.1
109.1
127.2
121.4
139.9

109.1
108.2
126.1
129.8
154.2

108.8
108.1
126.1
136.3
157.3

108.7
113.0
133.9
145.2
176.1

111.9
116.0
140.6
154.6
190.5

Family clothing stores………..…………………………
Shoe stores……………………………………………
Furniture and homefurnishings stores………………
Household appliance stores…………………………
Radio, television, computer, and music stores………

565
566
571
572
573

107.8
107.9
104.6
104.3
121.1

111.5
107.8
105.4
106.7
129.8

118.6
115.5
113.9
115.5
139.9

121.5
117.3
113.3
118.0
154.5

127.7
130.7
114.7
121.5
179.1

141.8
139.2
117.4
138.4
199.3

146.9
151.9
123.6
140.7
208.1

150.2
148.4
124.2
153.5
218.4

153.1
145.0
127.2
181.4
260.3

156.5
151.1
134.1
183.9
314.6

Eating and drinking places……………………………
Drug and proprietary stores……………………………
Liquor stores……………………………………………
Used merchandise stores……………………………
Miscellaneous shopping goods stores………………

581
591
592
593
594

104.5
106.3
105.9
103.0
107.2

103.8
108.0
106.9
102.3
109.0

103.4
107.6
109.6
115.7
107.5

103.8
109.5
101.8
116.8
111.5

102.1
109.9
100.1
119.5
117.1

102.0
111.1
104.7
120.6
123.1

100.6
113.9
113.8
132.7
125.3

101.6
119.7
109.9
140.3
129.1

102.0
125.6
116.5
163.6
138.8

104.3
129.8
114.6
181.9
145.2

Nonstore retailers……………..………………………
Fuel dealers……………………………………………
Retail stores, n.e.c………………………………………

596
598
599

111.1
84.5
114.5

112.5
85.3
104.0

126.5
84.2
112.5

132.2
91.8
118.1

149.0
99.0
125.8

152.4
111.4
127.0

173.3
112.4
140.2

186.5
109.0
147.8

208.0
105.8
157.3

222.2
115.1
161.0

Commercial banks………………………………………
Hotels and motels……………………...………………
Laundry, cleaning, and garment services……………
Photographic studios, portrait…………………………
Beauty shops……………………………………………

602
701
721
722
723

107.7
96.2
102.3
98.2
97.5

110.1
99.3
99.9
92.1
95.8

111.0
108.0
99.3
95.8
100.9

118.5
106.5
99.9
101.8
97.0

121.7
109.9
105.0
108.3
101.1

126.4
110.5
106.6
116.2
104.8

129.7
110.0
109.8
110.7
107.6

133.0
108.2
109.0
114.1
108.5

132.6
111.6
116.2
121.6
110.5

135.2
113.5
121.8
105.1
113.3

Barber shops……………………………………………
Funeral services and crematories……………………
Automotive repair shops………………………………
Motion picture theaters…………………………………

724
726
753
783

100.7
91.2
107.9
118.1

94.9
89.9
100.1
118.2

113.2
103.8
105.1
114.8

121.9
98.7
105.7
113.8

118.8
104.3
114.3
110.4

115.7
100.2
121.6
105.0

128.8
97.6
116.1
104.1

150.4
101.9
117.2
103.4

157.4
104.2
124.9
106.1

138.0
99.7
127.6
110.5

Transportation
Railroad transportation…………………………………
4011
Trucking, except local 1 …………...…………………
4213
U.S. postal service 2 ………………...…………………
431
Air transportation 1 …………………………………… 4512,13,22 (pts.)

Utitlities
Telephone communications……………………………
Radio and television broadcasting……………………
Cable and other pay TV services……………………
Electric utilities…………………………………………
Gas utilities………………………………………………

Trade

Finance and services

1

2

Refers to output per employee

n.e.c. = not elsewhere classified

Refers to ouput per full-time equivalent employee year on fiscal basis.

126

Monthly Labor Review

August 2001

43. Unemployment rates, approximating U.S. concepts, in nine countries, quarterly data
seasonally adjusted
Annual average
Country
United States….....
Canada.................
Australia……………
1
Japan …………………
1
France ………………
1
Germany ……………
1,2
Italy …………………
1
Sweden ………………
1
United Kingdom …

1999

2000

1999
I

II

III

IV

I

II

III

IV

4.2

4.0

4.3

4.3

4.2

4.1

4.1

4.0

4.0

4.0

6.8
7.2
4.7
11.2

5.8
6.6
4.8
9.7

7.1
7.5
4.7
11.4

7.1
7.4
4.8
11.3

6.8
7.1
4.8
11.2

6.2
7.0
4.7
10.8

6.0
6.8
4.8
10.2

5.8
6.7
4.7
9.7

5.8
6.3
4.7
9.6

5.7
6.5
4.8
9.2

8.7
11.5
7.1
6.1

8.3
10.7
5.9
–

8.8
11.8
7.1
6.2

8.8
11.7
7.0
6.1

8.8
11.5
7.1
5.9

8.7
11.2
7.1
5.9

8.4
11.3
6.7
5.8

8.3
10.8
6.0
5.5

8.2
10.6
5.6
5.4

8.1
10.1
5.2
–

1
Preliminary for 2000 for Japan, France, Germany (unified), Italy,
and Sweden and for 1999 onward for the United Kingdom.
2

2000

Quarterly rates are for the first month of the quarter.

NOTE: Quarterly figures for France and Germany are
calculated by applying annual adjustment factors to current
published data, and therefore should be viewed as less precise in-

dicators of unemployment under U.S. concepts than the annual
figures. See "Notes on the data" for information on breaks in
series. For further qualifications and historical data, see
Comparative Civilian Labor Force Statistics, Ten Countries,1959–2000 (Bureau of Labor Statistics, Mar. 16, 2001).
Dash indicates data not available.

Monthly Labor Review

August 2001

127

Current Labor Statistics:

International Comparison

44. Annual data: Employment status of the working-age population, approximating U.S. concepts, 10 countries
[Numbers in thousands]
Employment status and country

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

126,346

128,105

129,200

131,056

132,304

133,943

136,297

137,673

139,368

140,863

14,128
8,490

14,299
8,619
65,470

14,387
8,776
65,780

14,500
9,001
65,990

14,650
9,127
66,450

14,936
9,221
67,200

15,216
9,347
67,240

15,513
9,470
67,090

15,745
9,682
p
66,990

Civilian labor force
1

United States ………………………..…………..…………………
Canada..........................................................................
Australia.........................................................................
Japan.............................................................................

64,280

14,168
8,562
65,040

France............................................................................

24,470
39,130

24,570
39,040

24,640
39,140

24,780
39,210

24,830
39,100

25,090
39,180

25,210
39,480

25,540
39,520

25,860
39,630

–
–

22,940
6,780
4,591
28,610

22,910
6,940
4,520
28,410

22,570
7,050
4,443
28,310

22,450
7,200
4,418
28,280

22,460
7,230
4,460
28,480

22,570
7,440
4,459
28,620

22,680
7,510
4,418
28,760

22,960
7,670
4,402
28,870

23,130
7,750
4,430

–
–
–
–

2

Germany ………………………..…………..…………………………
Italy................................................................................
Netherlands....................................................................
Sweden..........................................................................
United Kingdom.............................................................
Participation rate

p

29,090

3

1

United States
Canada..........................................................................
Australia.........................................................................
Japan.............................................................................
France............................................................................
2

Germany
Italy................................................................................
Netherlands....................................................................
Sweden..........................................................................
United Kingdom.............................................................

66.2
66.7
64.1
63.2
55.9
58.9
47.7
56.8
67.0
63.7

66.4
65.9
63.9
63.4
55.8
58.3
47.5
57.7
65.7
63.1

66.3
65.5
63.6
63.3
55.6
58.0
47.9
58.2
64.5
62.8

66.6
65.2
63.9
63.1
55.5
57.6
47.3
59.0
63.7
62.5

66.6
64.9
64.6
62.9
55.3
57.3
47.1
58.9
64.1
62.7

66.8
64.7
64.6
63.0
55.5
57.4
47.1
60.3
64.0
62.7

67.1
65.0
64.3
63.2
55.3
57.7
47.2
60.6
63.3
62.8

67.1
65.4
64.4
62.8
55.7
57.7
47.6
61.4
62.8
62.7

67.1
65.8
64.2
62.4
56.0
p
57.9
47.8
61.5
p
63.2
p
62.9

67.2
65.9
64.7
p
62.0
–
–
–
–
–
–

Employed
1

United States ………………………..…………..…………………
Canada..........................................................................
Australia.........................................................................
Japan.............................................................................

117,718

118,492

120,259

123,060

124,900

126,708

129,558

131,463

133,488

135,208

12,747
7,676
62,920

12,672
7,637
63,620

12,770
7,680
63,810

13,027
7,921
63,860

13,271
8,235
63,890

13,380
8,344
64,200

13,705
8,429
64,900

14,068
8,597
64,450

14,456
8,785
63,920

14,827
9,043

France............................................................................

22,120
36,920
21,360
6,380
4,447
26,090

22,020
36,420
21,230
6,540
4,265
25,530

21,740
36,030
20,270
6,590
4,028
25,340

21,730
35,890
19,940
6,680
3,992
25,550

21,910
35,900
19,820
6,730
4,056
26,000

21,960
35,680
19,920
6,970
4,019
26,280

22,090
35,570
19,990
7,110
3,973
26,740

22,520
35,830
20,210
7,360
4,034
27,050

22,970
36,170
20,460
7,490
4,117

2

Germany
Italy................................................................................
Netherlands....................................................................
Sweden..........................................................................
United Kingdom.............................................................
Employment-population ratio

27,330

p

p

63,790
–
–
–
–
–
–

4

1

United States ………………………..…………..…………………
Canada..........................................................................
Australia.........................................................................
Japan.............................................................................
France............................................................................
2

Germany ………………………..…………..…………………………
Italy................................................................................
Netherlands....................................................................
Sweden..........................................................................
United Kingdom.............................................................

61.7

61.5

61.7

62.5

62.9

63.2

63.8

64.1

64.3

64.5

60.2
57.9
61.8
50.6
55.5

58.9
57.0
62.0
50.0
54.4

58.5
56.6
61.7
49.0
53.4

59.0
57.7
61.3
48.7
52.8

59.4
59.1
60.9
48.8
52.6

59.1
59.1
60.9
48.5
52.2

59.7
58.8
61.0
48.5
52.0

60.4
59.2
60.2
49.1
52.3

61.3
59.6
59.4
49.8

62.1
60.4
p
59.0
–
–

44.5
53.4
64.9
58.0

44.0
54.4
62.0
56.7

43.0
54.4
58.5
56.2

42.0
54.8
57.6
56.5

41.5
54.9
58.3
57.2

41.6
56.5
57.7
57.6

41.6
57.4
56.9
58.3

41.9
58.9
57.6
58.7

p

52.8
42.3
59.4
p
58.7
p
59.1

–
–
–
–

Unemployed
1

United States ………………………..…………..…………………
Canada..........................................................................
Australia.........................................................................
Japan.............................................................................

8,628

9,613

8,940

7,996

7,404

7,236

6,739

6,210

5,880

5,665

1,381
814
1,360

1,496
925
1,420

1,530
939
1,660

1,359
856
1,920

1,229
766
2,100

1,271
783
2,250

1,230
791
2,300

1,148
750
2,790

1,058
685
3,170

918
638

France............................................................................

2,350
2,210

2,550
2,620

2,900
3,110

3,060
3,320

2,920
3,200

3,130
3,500

3,130
3,910

3,020
3,690

2,890
3,460

1,580
400
144
2,520

1,680
390
255
2,880

2,300
460
415
2,970

2,510
520
426
2,730

2,640
510
404
2,480

2,650
470
440
2,340

2,690
400
445
2,020

2,750
310
368
1,820

2,670
260
313

2

Germany ………………………..…………..…………………………
Italy................................................................................
Netherlands....................................................................
Sweden..........................................................................
United Kingdom.............................................................

1,760

p

p

3,200
–
–

–
–
–
–

Unemployment rate
1

United States ………………………..…………..…………………
Canada..........................................................................
Australia.........................................................................
Japan.............................................................................
France............................................................................
2

6.8

7.5

6.9

6.1

5.6

5.4

4.9

4.5

4.2

4.0

9.8
9.6
2.1
9.6
5.6

10.6
10.8
2.2
10.4
6.7

10.7
10.9
2.5
11.8
7.9

9.4
9.7
2.9
12.3
8.5

8.5
8.5
3.2
11.8
8.2

8.7
8.6
3.4
12.5
8.9

8.2
8.6
3.4
12.4
9.9

7.5
8.0
4.1
11.8
9.3

6.8
7.2
4.7
11.2
8.7

5.8
6.6
p
4.8
p
9.7
p

8.3
Germany ………………………..…………..…………………………
p
Italy................................................................................
6.9
7.3
10.2
11.2
11.8
11.7
11.9
12.0
11.5
10.7
Netherlands....................................................................
5.9
5.6
6.5
7.2
7.1
6.3
5.3
4.0
3.4
–
p
Sweden..........................................................................
3.1
5.6
9.3
9.6
9.1
9.9
10.1
8.4
7.1
5.9
p
United Kingdom.............................................................
8.8
10.1
10.5
9.7
8.7
8.2
7.0
6.3
–
6.1
3
1
Labor force as a percent of the working-age population.
Data for 1994 are not directly comparable with data for 1993 and earlier years. For
4
additional information, see the box note under "Employment and Unemployment
Employment as a percent of the working-age population.
NOTE: See Notes on the data for information on breaks in series for the United
Data" in the notes to this section.
2
States, France, Germany, Italy, the Netherlands, and Sweden.
Data from 1991 onward refer to unified Germany. See Comparative Civilian Labor
Dash indicates data are not available.
Force Statistics, Ten Countries, 1959–2000 , Mar. 16, 2001, on the Internet at
p = preliminary.

http://stats.bls.gov/flsdata.htm.

128

Monthly Labor Review

August 2001

45. Annual indexes of manufacturing productivity and related measures, 12 countries
[1992 = 100]
Item and country

1960

1970

1980

1988

1989

1990

1991

1993

1994

1995

1996

1997

1998

1999

Output per hour
United States.......……...........................................
Canada..................................................................
Japan.....................................................................
Belgium..................................................................
Denmark................................................................
France....................................................................
Germany................................................................
Italy........................................................................
Netherlands...........................................................
Norway...................................................................
Sweden..................................................................
United Kingdom.....................................................

–
38.7
14.0
18.0
29.9
21.8
29.2
20.2
18.6
36.7
27.3
31.2

–
56.6
38.0
32.9
52.7
43.0
52.0
37.9
38.1
57.8
52.2
44.7

70.5
75.1
63.9
65.4
90.3
66.5
77.2
65.9
69.2
76.7
73.1
56.1

96.9
90.9
84.8
92.0
94.1
87.5
91.5
86.7
93.7
92.1
90.5
82.3

95.7
93.7
89.5
96.9
99.6
91.9
94.6
89.4
97.1
94.6
93.2
86.2

96.9
95.7
95.4
96.8
99.1
93.5
99.0
92.5
98.6
96.6
94.6
88.3

97.8
95.3
99.4
99.1
99.6
96.9
99.0
95.2
99.6
97.5
95.5
92.2

102.1
104.5
100.5
102.5
104.5
100.6
101.6
102.9
101.4
100.6
107.3
104.0

107.3
109.9
101.8
108.4
–
108.5
110.1
105.6
112.7
101.4
119.4
106.8

113.8
111.0
109.3
113.2
–
114.5
113.2
109.3
117.7
102.0
121.9
104.8

117.0
109.5
115.8
115.5
–
115.0
116.8
109.5
119.7
102.0
124.5
103.2

121.1
112.8
121.4
122.4
–
122.6
122.4
111.5
125.7
103.0
133.0
104.0

127.0
112.5
120.4
123.6
–
124.0
126.7
111.1
127.8
103.9
135.6
104.6

134.8
115.2
124.1
124.5
–
128.9
128.5
112.9
–
103.9
139.5
109.2

–
34.2
10.7
30.7
40.8
31.0
41.5
21.9
31.7
56.5
45.9
67.7

–
60.6
38.8
57.6
68.0
64.1
70.9
45.8
59.5
89.1
80.7
90.3

75.8
86.0
59.9
78.2
91.3
88.7
85.3
80.4
77.4
103.6
90.7
87.2

103.2
110.1
84.6
93.3
100.8
92.2
90.9
94.5
92.8
105.3
109.8
101.4

102.4
112.6
90.2
99.1
104.3
97.2
94.0
98.1
96.9
101.3
110.9
105.4

101.6
108.6
96.3
101.0
102.7
99.1
99.1
99.6
100.1
100.2
110.1
105.3

98.3
99.0
101.4
100.7
101.7
99.8
102.3
99.2
100.6
98.3
104.1
100.0

103.5
104.6
96.0
97.0
99.0
95.7
92.5
96.4
98.2
102.7
101.9
101.4

111.1
113.2
95.4
101.4
109.3
100.3
95.2
102.2
104.2
106.7
117.1
106.1

118.4
118.1
100.6
104.2
114.7
104.9
95.3
107.2
107.8
109.0
128.4
107.8

121.3
119.8
106.7
105.1
109.7
104.6
93.5
105.6
108.4
110.1
131.1
108.2

127.7
128.1
111.1
109.9
112.6
109.7
96.3
108.3
114.1
115.7
138.6
109.6

133.5
133.1
103.6
111.8
115.3
111.5
100.9
110.3
116.6
117.6
144.6
109.9

139.3
141.3
103.9
113.8
111.5
114.2
102.2
111.4
–
114.0
150.7
109.7

92.1
88.3
76.3
170.7
136.5
142.3
142.3
108.7
170.6
154.0
168.3
217.3

104.4
107.1
102.3
174.7
129.0
149.0
136.3
120.9
156.2
154.3
154.7
202.1

107.5
114.6
93.8
119.7
101.1
133.3
110.5
122.0
111.8
135.0
124.0
155.3

106.6
121.2
99.8
101.5
107.2
105.4
99.3
108.9
99.0
114.3
121.4
123.2

107.1
120.2
100.8
102.3
104.7
105.8
99.3
109.7
99.8
107.1
119.0
122.3

104.8
113.5
100.9
104.3
103.7
105.9
100.1
107.7
101.5
103.7
116.4
119.2

100.4
103.9
102.0
101.5
102.1
103.0
103.3
104.2
101.0
100.8
109.0
108.5

101.4
100.1
95.6
94.7
94.8
95.1
91.0
93.6
96.9
102.1
94.9
97.5

103.6
103.0
93.7
93.6
–
92.4
86.5
96.7
92.4
105.2
98.1
99.4

104.0
106.4
92.0
92.0
–
91.6
84.2
98.0
91.6
106.9
105.3
102.9

103.7
109.4
92.2
91.0
–
91.0
80.1
96.5
90.5
107.9
105.3
104.8

105.5
113.5
91.5
89.8
–
89.5
78.7
97.1
90.8
112.3
104.2
105.4

105.2
118.3
86.1
90.5
–
89.9
79.6
99.3
91.2
113.2
106.6
105.0

103.3
122.7
83.8
91.5
–
88.6
79.5
98.6
–
109.8
108.0
100.5

14.9
9.9
4.3
5.4
4.6
4.3
8.1
1.6
6.4
4.7
4.1
3.1

23.7
17.0
16.5
13.7
13.3
10.3
20.7
4.7
20.2
11.8
10.7
6.3

55.6
47.7
58.6
52.5
49.6
40.8
53.6
28.4
64.4
39.0
37.3
33.2

84.0
77.8
79.2
81.1
82.9
81.6
79.1
69.3
87.7
83.3
71.8
67.7

86.6
82.5
84.2
85.9
87.7
86.0
83.2
75.9
88.5
87.2
79.4
72.9

90.8
89.5
90.7
90.1
92.7
90.6
89.4
84.4
90.8
92.3
87.8
80.9

95.6
94.7
95.9
97.3
95.9
96.2
92.1
93.6
95.2
97.5
95.5
90.5

102.7
99.6
104.6
104.8
104.6
103.0
106.1
107.5
103.7
101.5
97.2
104.3

105.6
100.4
106.7
106.1
–
105.6
112.3
107.8
108.2
104.4
99.8
106.5

107.9
103.6
109.5
109.2
–
108.4
118.5
112.8
110.6
109.2
106.3
107.4

109.3
102.8
110.9
112.0
–
110.2
125.2
120.3
113.2
113.6
114.2
108.2

111.4
106.7
113.9
115.2
–
113.0
128.0
125.4
115.8
118.7
119.7
111.4

117.3
110.8
115.8
116.0
–
114.9
128.9
123.0
118.3
126.2
123.3
117.0

123.2
110.8
117.7
116.0
–
119.3
130.8
126.5
–
133.4
127.4
122.6

–
25.6
30.9
30.1
15.4
19.5
27.8
7.9
34.4
12.9
15.0
9.8

–
30.1
43.3
41.7
25.2
24.0
39.8
12.4
52.9
20.4
20.6
14.1

78.8
63.2
91.7
80.3
55.0
61.3
69.4
43.1
93.0
50.8
51.0
59.1

86.7
85.2
93.4
88.1
88.2
93.3
86.5
79.9
93.6
90.4
79.4
82.2

90.5
88.0
94.0
88.7
88.1
93.6
87.9
84.9
91.1
92.2
85.1
84.6

93.7
92.3
95.0
93.0
93.6
96.8
90.3
91.3
92.1
95.6
92.8
91.6

97.7
99.7
96.5
98.1
96.3
99.3
93.1
98.4
95.5
100.0
100.0
98.2

100.6
97.6
104.1
102.3
100.1
102.4
104.5
104.4
102.3
100.9
90.6
100.3

98.5
94.3
104.9
97.9
93.0
97.3
102.0
102.1
96.0
102.9
83.6
99.7

94.8
95.5
100.1
96.4
93.8
94.7
104.7
103.2
94.0
107.1
87.2
102.5

93.5
95.9
95.8
95.6
100.9
95.9
107.2
109.9
94.6
111.4
91.7
104.8

92.0
95.9
93.8
93.3
102.0
92.2
104.6
112.4
92.2
115.2
90.0
107.1

92.4
98.8
96.2
93.7
102.8
92.7
101.8
110.8
92.5
121.5
90.9
111.9

91.4
98.1
94.9
93.4
108.9
92.6
101.8
112.0
–
128.5
91.3
112.3

–
32.0
10.9
19.4
13.5
21.1
10.4
15.6
16.0
11.3
16.9
15.6

–
34.8
15.3
27.0
20.3
23.0
17.1
24.4
25.7
17.8
23.1
19.2

78.8
65.3
51.3
88.3
58.9
76.8
59.6
62.0
82.3
63.9
70.3
77.8

86.7
83.6
92.4
77.0
79.0
82.9
76.9
75.6
83.2
86.1
75.4
82.9

90.5
89.8
86.3
72.3
72.6
77.6
73.0
76.2
75.5
82.9
76.8
78.5

93.7
95.6
83.1
89.5
91.3
94.1
87.3
93.8
88.9
95.0
91.3
92.5

97.7
105.1
90.9
92.3
90.8
93.1
87.5
97.6
89.8
95.7
96.3
98.2

100.6
91.4
118.8
95.1
93.2
95.6
98.6
81.8
96.8
88.3
67.7
85.3

98.5
83.4
130.1
94.2
88.3
92.9
98.2
78.1
92.8
90.7
63.1
86.5

94.8
84.1
135.1
105.2
101.1
100.6
114.1
78.0
103.0
105.0
71.2
91.6

93.5
85.0
111.7
99.3
105.0
99.2
111.3
87.8
98.6
107.1
79.7
92.6

92.0
83.6
98.3
83.7
93.1
83.6
94.1
81.3
83.0
101.1
68.6
99.3

92.4
80.5
93.1
83.0
92.6
83.2
90.3
78.6
82.0
100.0
66.6
105.0

91.4
79.8
105.7
79.3
94.1
79.6
86.6
75.9
–
102.2
64.3
102.8

Output
United States............……......................................
Canada..................................................................
Japan.....................................................................
Belgium..................................................................
Denmark................................................................
France....................................................................
Germany................................................................
Italy........................................................................
Netherlands...........................................................
Norway...................................................................
Sweden..................................................................
United Kingdom.....................................................
Total hours
United States...........…….......................................
Canada..................................................................
Japan.....................................................................
Belgium..................................................................
Denmark................................................................
France....................................................................
Germany................................................................
Italy........................................................................
Netherlands...........................................................
Norway...................................................................
Sweden..................................................................
United Kingdom.....................................................
Compensation per hour
United States..................…....................................
Canada..................................................................
Japan.....................................................................
Belgium..................................................................
Denmark................................................................
France....................................................................
Germany................................................................
Italy........................................................................
Netherlands...........................................................
Norway...................................................................
Sweden..................................................................
United Kingdom.....................................................
Unit labor costs: National currency basis
United States..........…............................................
Canada..................................................................
Japan.....................................................................
Belgium..................................................................
Denmark................................................................
France....................................................................
Germany................................................................
Italy........................................................................
Netherlands...........................................................
Norway...................................................................
Sweden..................................................................
United Kingdom.....................................................
Unit labor costs: U.S. dollar basis
United States.........................................................
Canada..................................................................
Japan.....................................................................
Belgium..................................................................
Denmark................................................................
France....................................................................
Germany................................................................
Italy........................................................................
Netherlands...........................................................
Norway...................................................................
Sweden..................................................................
United Kingdom.....................................................

NOTE: Data for Germany for years before 1992 are for the former West Germany. Data for 1992 onward are for unified Germany. Dash indicates data not available.

Monthly Labor Review

August 2001

129

Current Labor Statistics:

Injury and Illness
1

46. Occupational injury and illness rates by industry, United States
3

Industry and type of case

Incidence rates per 100 full-time workers

2

1988

1989

1

1990

1991

1992

1993

4

1994

4

1995

4

1996

4

1997

4

1998

4

1999

4

5

PRIVATE SECTOR
Total cases ............................…………………………..……………
Lost workday cases.......................................................................
Lost workdays........……….............................................................

8.6
4.0
76.1

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
–

Agriculture, forestry, and fishing
Total cases ............................…………………………..……………
Lost workday cases.......................................................................
Lost workdays........……….............................................................

10.9
5.6
101.8

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
–

Mining
Total cases ............................…………………………..……………
Lost workday cases.......................................................................
Lost workdays........……….............................................................

8.8
5.1
152.1

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
–

Construction
Total cases ............................…………………………..……………
Lost workday cases.......................................................................
Lost workdays........……….............................................................

14.6
6.8
142.2

14.3
6.8
143.3

14.2
6.7
147.9

13.0
6.1
148.1

13.1
5.8
161.9

12.2
5.5
–

11.8
5.5
–

10.6
4.9
–

9.9
4.5
–

9.5
4.4
–

8.8
4.0
–

8.6
4.2
–

General building contractors:
Total cases ............................…………………………..……………
Lost workday cases.......................................................................
Lost workdays........……….............................................................

14.0
6.4
132.2

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
–

Heavy construction, except building:
Total cases ............................…………………………..……………
Lost workday cases.......................................................................
Lost workdays........……….............................................................

15.1
7.0
162.3

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
–

Special trades contractors:
Total cases ............................…………………………..……………
Lost workday cases.......................................................................
Lost workdays........……….............................................................

14.7
7.0
141.1

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
–

Manufacturing
Total cases ............................…………………………..……………
Lost workday cases.......................................................................
Lost workdays........……….............................................................

13.1
5.7
107.4

13.1
5.8
113.0

13.2
5.8
120.7

12.7
5.6
121.5

12.5
5.4
124.6

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
–

Durable goods:
Total cases ............................…………………………..……………
Lost workday cases.......................................................................
Lost workdays........……….............................................................

14.2
5.9
111.1

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
–

Lumber and wood products:
Total cases ............................…………………………..…………
Lost workday cases....................................................................
Lost workdays........………..........................................................

19.5
10.0
189.1

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
–

Furniture and fixtures:
Total cases ............................…………………………..…………
Lost workday cases....................................................................
Lost workdays........………..........................................................

16.6
7.3
115.7

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
–

Stone, clay, and glass products:
Total cases ............................…………………………..…………
Lost workday cases....................................................................
Lost workdays........………..........................................................

16.0
7.5
141.0

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
–

Primary metal industries:
Total cases ............................…………………………..…………
Lost workday cases....................................................................
Lost workdays........………..........................................................

19.4
8.2
161.3

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
–

Fabricated metal products:
Total cases ............................…………………………..…………
Lost workday cases....................................................................
Lost workdays........………..........................................................

18.8
8.0
138.8

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
–

Industrial machinery and equipment:
Total cases ............................…………………………..…………
Lost workday cases....................................................................
Lost workdays........………..........................................................

12.1
4.7
82.8

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
–

Electronic and other electrical equipment:
Total cases ............................…………………………..…………
Lost workday cases....................................................................
Lost workdays........………..........................................................

8.0
3.3
64.6

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
–

Transportation equipment:
Total cases ............................…………………………..…………
Lost workday cases....................................................................
Lost workdays........………..........................................................

17.7
6.6
134.2

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
–

Instruments and related products:
Total cases ............................…………………………..…………
Lost workday cases....................................................................
Lost workdays........………..........................................................

6.1
2.6
51.5

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
–

Miscellaneous manufacturing industries:
Total cases ............................…………………………..…………
Lost workday cases....................................................................
Lost workdays........………..........................................................

11.3
5.1
91.0

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
–

5

See footnotes at end of table.

130

Monthly Labor Review

August 2001

1

46. Continued—Occupational injury and illness rates by industry, United States
Industry and type of case

Incidence rates per 100 full-time workers

2

1988

1989

1

1990

1991

1992

1993

4

1994

4

1995

4

3

1996

4

1997

4

1998

4

1999

4

Nondurable goods:
Total cases ............................…………………………..……………
Lost workday cases.......................................................................
Lost workdays........……….............................................................

11.4
5.4
101.7

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
9.2
169.7

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........………..........................................................

9.3
2.9
53.0

8.7
3.4
64.2

7.7
3.2
62.3

6.4
2.8
52.0

6.0
2.4
42.9

5.8
2.3
–

5.3
2.4
–

5.6
2.6
–

6.7
2.8
–

5.9
2.7
–

6.4
3.4

-

5.5
2.2
–

Textile mill products:
Total cases ............................…………………………..…………
Lost workday cases....................................................................
Lost workdays........………..........................................................

9.6
4.0
78.8

10.3
4.2
81.4

9.6
4.0
85.1

10.1
4.4
88.3

9.9
4.2
87.1

9.7
4.1
–

8.7
4.0
–

8.2
4.1
–

7.8
3.6
–

6.7
3.1
–

7.4
3.4
–

6.4
3.2
–

Apparel and other textile products:
Total cases ............................…………………………..…………
Lost workday cases....................................................................
Lost workdays........………..........................................................

8.1
3.5
68.2

8.6
3.8
80.5

8.8
3.9
92.1

9.2
4.2
99.9

9.5
4.0
104.6

9.0
3.8
–

8.9
3.9
–

8.2
3.6
–

7.4
3.3
–

7.0
3.1
–

6.2
2.6

-

5.8
2.8
–

Paper and allied products:
Total cases ............................…………………………..…………
Lost workday cases....................................................................
Lost workdays........………..........................................................

13.1
5.9
124.3

12.7
5.8
132.9

12.1
5.5
124.8

11.2
5.0
122.7

11.0
5.0
125.9

9.9
4.6
–

9.6
4.5
–

8.5
4.2
–

7.9
3.8
–

7.3
3.7
–

7.1
3.7
–

7.0
3.7
–

Printing and publishing:
Total cases ............................…………………………..…………
Lost workday cases....................................................................
Lost workdays........………..........................................................

6.6
3.2
59.8

6.9
3.3
63.8

6.9
3.3
69.8

6.7
3.2
74.5

7.3
3.2
74.8

6.9
3.1
–

6.7
3.0
–

6.4
3.0
–

6.0
2.8
–

5.7
2.7
–

5.4
2.8
–

5.0
2.6
–

Chemicals and allied products:
Total cases ............................…………………………..…………
Lost workday cases....................................................................
Lost workdays........………..........................................................

7.0
3.3
59.0

7.0
3.2
63.4

6.5
3.1
61.6

6.4
3.1
62.4

6.0
2.8
64.2

5.9
2.7
–

5.7
2.8
–

5.5
2.7
–

4.8
2.4
–

4.8
2.3
–

4.2
2.1
–

4.4
2.3
–

Petroleum and coal products:
Total cases ............................…………………………..…………
Lost workday cases....................................................................
Lost workdays........………..........................................................

7.0
3.2
68.4

6.6
3.3
68.1

6.6
3.1
77.3

6.2
2.9
68.2

5.9
2.8
71.2

5.2
2.5
–

4.7
2.3
–

4.8
2.4
–

4.6
2.5
–

4.3
2.2
–

3.9
1.8
–

4.1
1.8
–

Rubber and miscellaneous plastics products:
Total cases ............................…………………………..…………
Lost workday cases....................................................................
Lost workdays........………..........................................................

16.3
8.1
142.9

16.2
8.0
147.2

16.2
7.8
151.3

15.1
7.2
150.9

14.5
6.8
153.3

13.9
6.5
–

14.0
6.7
–

12.9
6.5
–

12.3
6.3
–

11.9
5.8
–

11.2
5.8
–

10.1
5.5
–

Leather and leather products:
Total cases ............................…………………………..…………
Lost workday cases....................................................................
Lost workdays........………..........................................................

11.4
5.6
128.2

13.6
6.5
130.4

12.1
5.9
152.3

12.5
5.9
140.8

12.1
5.4
128.5

12.1
5.5
–

12.0
5.3
–

11.4
4.8
–

10.7
4.5
–

10.6
4.3
–

9.8
4.5
–

10.3
5.0
–

Transportation and public utilities
Total cases ............................…………………………..……………
Lost workday cases.......................................................................
Lost workdays........……….............................................................

8.9
5.1
118.6

9.2
5.3
121.5

9.6
5.5
134.1

9.3
5.4
140.0

9.1
5.1
144.0

9.5
5.4
–

9.3
5.5
–

9.1
5.2
–

8.7
5.1
–

8.2
4.8
–

7.3
4.3
–

7.3
4.4
–

Wholesale and retail trade
Total cases ............................…………………………..……………
Lost workday cases.......................................................................
Lost workdays........……….............................................................

7.8
3.5
60.9

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
–

Wholesale trade:
Total cases ............................…………………………..……………
Lost workday cases.......................................................................
Lost workdays........……….............................................................

7.6
3.8
69.2

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
–

Retail trade:
Total cases ............................…………………………..……………
Lost workday cases.......................................................................
Lost workdays........……….............................................................

7.9
3.4
57.6

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
–

Finance, insurance, and real estate
Total cases ............................…………………………..……………
Lost workday cases.......................................................................
Lost workdays........……….............................................................

2.0
.9
17.2

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
–

Services
Total cases ............................…………………………..……………
Lost workday cases.......................................................................
Lost workdays........……….............................................................

5.4
2.6
47.7

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
–

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.
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.
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:

-

-

7.8
4.2
–
12.7
7.3
–

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).
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.
Dash indicates data not available.

Monthly Labor Review

August 2001

131

Current Labor Statistics:

Injury and Illness

47. Fatal occupational injuries by event or exposure, 1993–98
Fatalities
1

Event or exposure

Total…………….....................................................................

2

1993–97

1997

1998

Average

Number

Number

Percent

6,335

6,238

6,026

100

Transportation incidents...............................................................
Highway incident……....................................................................
Collision between vehicles, mobile equipment………….............
Moving in same direction…………...........................................
Moving in opposite directions, oncoming…………..................
Moving in intersection…………................................................
Vehicle struck stationary object or equipment…………..............
Noncollision incident...................................................................
Jackknifed or overturned—no collision…………......................
Nonhighway (farm, industrial premises) incident...........................
Overturned…………...................................................................
Aircraft……………………………………………………………………
Worker struck by a vehicle……………………………………………
Water vehicle incident…................................................................
Railway…….………….…...……………………………………………

2,611
1,334
652
109
234
132
249
360
267
388
214
315
373
106
83

2,605
1,393
640
103
230
142
282
387
298
377
216
261
367
109
93

2,630
1,431
701
118
271
142
306
373
300
384
216
223
413
112
60

44
24
12
2
4
2
5
6
5
6
4
4
7
2
1

Assaults and violent acts..............................................................
Homicides…............………............................................................
Shooting………………………………………………………………
Stabbing………………………………………………………………
Other, including bombing……………………………………………
Self-inflicted injuries............………................................................

1,241
995
810
75
110
215

1,111
860
708
73
79
216

960
709
569
61
79
223

16
12
9
1
1
4

Contact with objects and equipment.…………............................
Struck by object…............………...................................................
Struck by falling object………….................................................
Struck by flying object…......………….........................................
Caught in or compressed by equipment or objects…............………
Caught in running equipment or machinery………….................
Caught in or crushed in collapsing materials…............……….......

1,005
573
369
65
290
153
124

1,035
579
384
54
320
189
118

941
517
317
58
266
129
140

16
9
5
1
4
2
2

Falls..………………………...............................................................
Fall to lower level…............……….................................................
Fall from ladder…………............................................................
Fall from roof…......………….......................................................
Fall from scaffold, staging…......…………...................................
Fall on same level…............………...............................................

668
591
94
139
83
52

716
653
116
154
87
44

702
623
111
156
97
51

12
10
2
3
2
1

Exposure to harmful substances or environments..………………
Contact with electric current…............………................................
Contact with overhead power lines…………..............................
Contact with temperature extremes…............………....................
Exposure to caustic, noxious, or allergenic substances…............…
Inhalation of substances…………...............................................
Oxygen deficiency…............………...............................................
Drowning, submersion…………..................................................

586
320
128
43
120
70
101
80

554
298
138
40
123
59
90
72

572
334
153
46
104
48
87
75

9
6
3
1
2
1
1
1

Fires and explosions ..………………………...................................

199

196

205

3

26

21

16

–

3

Other events or exposures ……….………………………………………….
1

Based on the 1992 BLS Occupational Injury and Illness

3

Includes the category "Bodily reaction and exertion."

Classification Structures.
2
The BLS news release issued August 12, 1998, reported a
total of 6,218 fatal work injuries for calendar year 1997. Since
then, an additional 20 job-related fatalities were identified,
bringing the total job-related fatality count for 1997 to 6,238.

132

Monthly Labor Review

August 2001

NOTE: Totals for major categories may include subcategories not shown separately. Percentages may not add to
totals because of rounding. Dash indicates less than 0.5
percent.